Vehicle Industry and Competitiveness of Regions in Central and Eastern Europe

Tömböly Teodóra; Anita  Fuzi; Melinda Smahó

The aim of the book is presenting the economic and regional contexts, which influence the development of the vehicle industry (and within it the passenger car (automotive) production), in Central and Eastern Europe on the one hand, and – within this larger region – in the Central and Western Transdanubian region on the other hand. Furthermore, the book aimes to show the effect of this industrial sector on the future development trends of the two domestic regions. In this way, the Hungarian territorial units as well as their centres can be positioned in the larger region, which holds up a more and more spectacular industrial specialisation. Thus, also the main nodes of the development strategy based on the vehicle industry can be drawn out by integrating the results explored in other dimensions (e.g. innovation activity and the business environment of suppliers) of economic contexts. This book has been published as a result of the project „TAMOP-4.2.1/B-09/1/KONV-2010-0003:Mobility and Environment: Research in the fields of motor vehicle industry, energetics and environment in the Middle- and West-Transdanubian Regions of Hungary. The Project is supported by the European Union and co-financed by the European Regional Development Fund”

Vehicle Industry and Competitiveness of Regions in Central and Eastern Europe Edited by János Rechnitzer – Melinda Smahó SZÉCHENYI ISTVÁN UNIVERSITY UNIVERSITAS-GYŐR Nonprofit Ltd. Győr, 2012 Szerzők: Barta, Györgyi; Csizmadia, Zoltán; Dusek, Tamás; Füzi, Anita; Gombos, Szandra; Józsa, László; Kollár, Katalin; Lados, Mihály; Lengyel, Imre; Lukovics, Miklós; Nárai, Márta; Rechnitzer, János; Savanya, Péter; Smahó, Melinda; Tóth, Tamás; 2012 ISBN 978-615-5298-02-8 All rights reserved by the authors, Széchenyi István University and the publisher as copyright proprietors, yet non-commercial multiplication and distribution are allowed in constant form with the indication of the publisher. Any kind of alteration, adaptation, abbreviation or commercial multiplication and distribution are only allowed with the prior written permission of the authors, Széchenyi István University the publisher. Published by the UNIVERSITAS-GYŐR Nonprofit Ltd. (UNIVERSITAS) Győr, 2012 Legally responsible publisher: managing director of the UNIVERSITAS Layout editor: Nagy, Zoltán. Printed by the Palatia Nyomda és Kiadó Kft. Legally responsible manager: Radek, József. This book has been published as a result of the project „TAMOP-4.2.1/B-09/1/KONV-2010-0003: Mobility and Environment: Research in the fields of motor vehicle industry, energetics and environment in the Middle- and West-Transdanubian Regions of Hungary. The Project is supported by the European Union and co-financed by the European Regional Development Fund” CONTENTS Part I. Positions of Vehicle Industry in Central and Eastern Europe János Rechnitzer – Melinda Smahó: Economic Effects of the Vehicle and Automotive Industry in the Regions of Central and Eastern Europe and Hungary .............................................................................................................. 7 Györgyi Barta: Central and EasternEuropean Automotive Industry in European Context..................................................................................................................... 33 Melinda Smahó: System of Knowledge Transfer in the Automotive Industry.............. 71 Anita Füzi – Szandra Gombos – Tamás Tóth: Location Factors of Automotive Industry in Central and Eastern Europe ................................................................. 108 Part II. Competitiveness of Regions and Production Centres Imre Lengyel: Competitiveness of Regions of Central and Eastern European Countries ................................................................................................................ Miklós Lukovics – Péter Savanya: Competitiveness of the Visegrád Countries’ Counties from the Aspect of Automotive Industry .............................. Tamás Dusek: Competitiveness of Automotive Centres in Central and Eastern Europe ....................................................................................................... Mihály Lados – Katalin Kollár: Local Economic Development and the Automotive Industry in Győr ................................................................................. 129 165 196 228 Part III. Characteristics of the Supplier Network Zoltán Csizmadia: Features and Spatial Differentation of Supplier Networks in Automotive Industry .......................................................................................... 251 Márta Nárai: Innovation activities of companies related to car manufacturing, automotive industry ............................................................................................... 268 László Józsa: Analysis and Development Strategies – Summarized Exploratory Research of Company Performance....................................................................... 283 List of Contributors ..................................................................................................... 301 PART I. POSITIONS OF VEHICLE INDUSTRY IN CENTRAL AND EASTERN EUROPE ECONOMIC EFFECTS OF THE VEHICLE AND AUTOMOTIVE INDUSTRY IN THE REGIONS OF CENTRAL AND EASTERN EUROPE AND HUNGARY JÁNOS RECHNITZER – MELINDA SMAHÓ Keywords: vehicle industry automotive industry Central and Western Transdanubian region Central and Eastern European competition area supplier network Within the framework of the project „Mobility and Environment: Research in the fields of motor vehicle industry, energetics and environment in the Middle- and West-Transdanubian Regions of Hungary, TAMOP-4.2.1./B-09/1/KONV-2010-0003” one of the sub-programmes – in two part programmes – has undertaken to examine the social, economical and location factors of the vehicle industry as well as the emerging of the supplier’s network. The aim of the research was presenting the economic and regional contexts, which influence the development of the vehicle industry (and within it the passenger car (automotive) production), in Central and Eastern Europe on the one hand, and – within this larger region – in the Central and Western Transdanubian region on the other hand. Furthermore, the research aimed to show the effect of this industrial sector on the future development trends of the two domestic regions. In this way, the Hungarian territorial units as well as their centres can be positioned in the larger region, which holds up a more and more spectacular industrial specialisation. Thus, also the main nodes of the development strategy based on the vehicle industry can be drawn out by integrating the results explored in other dimensions (e.g. innovation activity and the business environment of suppliers) of economic contexts Concept of the research Preliminary research has proven that in the three hundred-kilometre circle of the GyőrEsztergom-Szentgotthárd triangle several millions of engines are produced and between 500 and 600 thousand vehicles are assembled yearly. Thus, until the start of the 2010’s a Central and Eastern European automotive manufacturing large region had evolved where parallel factories can be found and each of them are owned by a different economic organisation. The aim of the research was presenting the economic and regional contexts, which influence the development of the vehicle industry (and within it the passenger car (automotive) production), in Central and Eastern Europe on the one hand, and – within this larger region – in the Central and Western Transdanubian region on the other hand. Furthermore, the research aimed to show the effect of this industrial sector on the future development trends of the two domestic regions. Earlier research confirmed that the production capacities of the domestic vehicle (and within it the automotive) industry are concentrated in these two regions, and also the supplier network can be considered as important. The two regions can be found in a shaping Central 8 János Rechnitzer – Melinda Smahó and Eastern European automotive industry competition area, therefore it is essential to position the Hungarian regional units and their centres in a larger region which holds up a more and more spectacular and sector-dependent industrial specialisation. One direction of the research covered the comprehensive presentation of the vehicle production in Central and Eastern Europe, and – inside of this large region – the evaluation as well as the positioning of the Hungarian regions’ competition area. The objective was to map the vehicle production capacities mainly in the Central and Eastern European region1 (Germany, Austria, Slovenia, Czech Republic, Slovakia, Poland, Hungary, Romania), but sometimes in other Eastern and Southern European countries as well (Croatia, Serbia, Romania, Bulgaria). The aim of the analysis was to recognize and compare the development trends, product structure and production capacities of the vehicle industry facilities settled in the regions of the mentioned countries on the one hand and incidentally to evaluate their supplier networks on the other hand. The research invesigated the local, regional economical as well as social effects induced by the location of the vehicle industry; furthermore it explored the characteristics and specialities of the granting system initiated in order to attract and accept the sector in the territorial units in question (country, region, settlement). It was elaborated the competitiveness analysis of regions as well as vehicle production centres of the Central and Eastern European growth area. By this general competitiveness analysis, factors affecting general economic development were identified, recorded and compared, thus the position of regions and vehicle industry centres could be measured as well as assimilated. The competitiveness analysis was supplemented by the reviewing of location factors of the vehicle (automotive) industry in the analysed regions and vehicle industry centres. Within its framework, the national-, regional- and local-level economic incentives, granting and institutional systems as factors shaping the market environment, as well as the factors determining the spatial location and concentration of vehicle industry (clustering) were also analysed. Thus, the main nodes of the development strategy based on the vehicle industry could be drawn out by integrating the results explored in other dimensions (e.g. innovation activity and the business environment of suppliers) of economic contexts. Another direction of the research was to map the supplier firms located in the Central and Western Transdanubian regions, which are mainly connected to the vehicle (automotive industry) and the evaluation of their innovation and development circumstances as well as management systems. The research registered the production capacities (enterprises) connected to vehicle (automotive) industry and examined their general economic characteristics (production, employment, plants, and main location factors). It was evaluated the role such sectors play inside of the whole of the two regions’ economy by defining the factors on the one hand, which are beneficiary from the aspect 1 The research region defined as Central and Eastern Europe includes the following countries: Germany, Austria, Poland, Czech Republic, Slovakia, Slovenia, Hungary, Romania. The multivariable statistical analysis exclusively included the figures of such countries while in further investigations other countries were also involved in addition to those mentioned already. Economic Effects of the Vehicle and Automotive Industry in the Regions … 9 of accepting the sector and on the other hand, in relation to which further developments are necessary – based on the location- and general business evaluation. We evaluated the role of such sectors in the integrity of the two regions’ economy by defining the factors on the first hand, which are beneficiary from the aspect of accepting the sector and on the other hand, in relation to which further developments is necessary – based on the settlement and general business evaluation. Questionnaires (118 companies) and – in case of the most important enterprises – deep interviews (43 companies) were carried out in order to examine the innovation activity as well as the renewal ability of the supplier enterprises by searching those internal and external factors, which shape their product development and market position. In connection with this, it was analysed to what extent these firms have been integrated into the local economy of the settlement, area and region, as well as their their co-operation and co-operation needs towards the economic capacities and development institution systems (universities, research organisations, innovation services, stock of professionals, etc.) being available in the settlement, area and region. It were evaluated the flows of networking of the enterprises connected to the vehicle (automotive) industry so far as well as their future networking opportunities – defined via surveys. The examination also covered the analysis of the business environment and management system of the enterprises related to the observed sector. Most of the supplier firms related to the vehicle (automotive) industry are small and medium-sized enterprises, which are able to establish a modern company organisation and management system as well as to shape the market connections in a planned way at their own level, thus, differently. The objective of the research was to map the market and business milieu of the supplier enterprises of the vehicle (automotive) industry to evaluate their company management and organisation systems, as well as to elaborate recommendations on the development and continuous renewal of the organisation and the relations. Based on the research results, development directions were defined for the vehicle (automotive) industry at national, regional and local level, regarding the renewal of the business environment, as well as the expansion of the supply-elements of education and training. International contexts and regional positioning of the vehicle (automotive) industry The executed research proved clearly that in the past twenty years in Central and Eastern Europe the vehicle industry has developed dynamically (Barta 2012; Losoncz 2012). Within this, the automotive industry became from a net importer to a net exporter because while in 2006 300 thousand vehicles were produced, by 2012, already 1.1 million vehicles are planned. The investments in the automotive industry were realised mainly via direct foreign investments. The cheap and qualified labour force as well as the appearance at new markets favoured this, but the geographical vicinity of the Western European markets should not be forgotten either. Most of the automotive 10 János Rechnitzer – Melinda Smahó industry investments in the Central and Eastern European region were green-field investment developments and the settlement of first-circle suppliers started at the same time as they were established and by this, the development of the vehicle industry value chain (pyramid) (Figure 1). The second- and third-circle suppliers where the enterprises of the countries where the plants are located represent larger and larger proportions, started to be settled only gradually, later in time but mainly after the turn of the millennium or they are established nowadays. FIGURE 1 System of relations among the car manufacturers and their suppliers OEMs Engines Bodies (design) Car assembly Sales (marketing) Shifting value added Squeezing to cut costs OEM Fising input in a form of technological know-how Tier 1 suppliers Automotive systems (e.g. interior, steering) Shifting value added Squeezing to cut costs Alliances Joint ventures M&A Capital links OEM Tier 1 Consolidation Tier 1 Consolidation Tier 1 Bottom-up pressure resulting from rising material costs Tier 2, 3, ... suppliers Individual parts and modules Tier 2 Tier 2 Tier 2 Tier 2 Tier 2 Tier 2 Source: The Automotive Sector in CEE… (2007, 9) based on Smahó (2012). The consequence of the economic crisis that started in 2008 was a decline in the examined countries but by 2010, the Central and Eastern European region reached its previous level. It can be considered as a result that the automotive factories were not closed which can be owed to the flexibility of the producers and the work and organisation experiences of the past 10–15 years but the adaptation of the employees should not be neglected either. In the countries of the region, some governments had taken measures as well in order to protect the dynamic sector, which appeared in the form of incentive purchases supporting the revitalisation of the market. The purchase incentives of the Western European countries (wreck car programmes) aimed at vehicles with lower consumption and better parameters regarding the burden to the environment; because the production of such types are the most important in the Central and Eastern European region therefore the demand of the production of such manufacturers (Hyundai – Kia, Fiat) did not decrease. In addition to all this, the governments of the large region – similarly to the countries of Western Europe – consider that the vehicle and automotive industry plays an important role. When providing the grants, they drew the attention clearly to that; they expect the maintenance of employment, the preservation of work places and plants, as well as the reconsideration of production plans. The European adaptation strategy was more successful than that in North America (Table 1). Economic Effects of the Vehicle and Automotive Industry in the Regions … 11 TABLE 1 Strengthening of Central and Eastern Europe (CEE)* in global automotive industry Number of vehicles produced (1000 units) Share of countries in CEE and global automobile manufacturing CEE=100% Germany Austria Czech Republic Poland Slovakia Romania Slovenia Hungary Serbia Aggregate Russia Turkey Global aggregate Global=100% 2000 2010 2000 2010 2010 5,527 141 456 505 182 78 123 137 13 7,162 1,206 431 58,374 5,906 105 1,076 869 557 351 211 168 18 9,261 1,403 1,094 77,858 77.2 1.9 6.4 7.1 2.5 1.1 1.7 1.9 0.2 100.0 63.8 1.1 11.6 9.4 6.0 3.8 2.3 1.8 0.2 100.0 7.6 0.1 1.4 1.1 0.8 0.5 0.3 0.2 0.0 12.0 1.8 1.4 100.0 * In our research the CEE region does not include Russia and Turkey but it includes Germany and Austria. Source: Barta (2012). In the Central and Eastern European region, the production of the automotive industry increased by up to 30% in the 2010’s but it was a bit behind the global production dynamism (33.4%). The dominance of the companies in Germany is decisive but the proportion of work distribution between Germany and the other countries of Central and Eastern European region changed in the past 10 years; the German share was reduced from 72:23% to 64:36%, which shows the production potential increase of the examined region. The global reorganisation of the vehicle- and automotive industry could be observed in the past decade, which could be shown in Europe as well because the four most important car producing countries operated 70 factories and makes in 1950 while only six remained of them by 2008. The restructuring happened differently by each country but based on the trends of world economy the consequences of this were amalgamation, the establishment of strategic alliances, and the consolidation of the market of suppliers. Out of such transformation types, relocation of complex car factories affected the Central and Eastern European region, because the relocation of production started from the high-cost regions, new markets appeared, the competition became stronger, and several new functions were integrated into the motor vehicles via research and development, while the expectations from the products of consumers also grew. Thus, Central and Eastern Europe became a winner of the global production and market reorganisation starting from the 1990’s. The relocation of the automotive 12 János Rechnitzer – Melinda Smahó industry started and by today, the following four groups can be separated based on their linkage to the European node areas, the features of the owners’ role and work distribution: − The EU members in Central and Eastern Europe: Poland, Czech Republic, Slovakia, Hungary, Slovenia; − Romania and Bulgaria – that joined later; − Turkey, which concluded a free-trade treaty with the EU in the hope of later accession; − Ukraine and Russia, which are tied mainly to the Russian node region but they hope to develop closer relations with the EU. This latter is more applicable to Croatia and Serbia. The countries of Central and Eastern Europe are defined as a strongly integrated, peripheral market while the remaining countries (Turkey, Ukraine, and Russia) are classified into the peripheral region. In the countries of the Central and Eastern European region the slow but systematic embedment of foreign companies is going on but at different intensities. The various multinational companies follow different strategies each just because of the partial differences in location factors, in capabilities of the countries as well as in grant systems supporting firms’ location and operations. The research has proven that from among the location factors the following factors are more favourable in the large region than in the parent countries: − lower costs of wages (between 1996–2005 the hourly wages may have doubled; but the Romanian wages constitute only 8% and the Czech ones only 16% of the German wages); − vicinity to the Western European market; − outstanding work culture in several countries in machine production, and in certain countries in automotive industry or in the larger vehicle industry; − the transportation and site infrastructure that can be considered favourable – mainly connected to the earlier industrial centres; − in addition, the gradually developing system of state grants. The Central and Eastern European region has considerable vehicle and automotive industry traditions (Hardi 2012). Thus there are countries which had production traditions already before 1989 with their own technology and development and traditions from before the Second World War (Czech Republic, Eastern Germany, partly Hungary), there are countries where there was production based on western licences (Poland, Yugoslavia and Romania), component producers where assembly did not exist before that is to say supplier countries (Hungary, Bulgaria). After reviewing the development of vehicle and automotive industry in each country it could be stated that before the change of the political system there were no important vehicle and automotive industry centres or zones built on them. In each country in only one or in a few large industrial centres vehicle and automotive industry or some segment of this industry was dominant but they did not become such an industrial base, which could Economic Effects of the Vehicle and Automotive Industry in the Regions … 13 have served the development or renewal of the sector in the long run. However, they played an important role in that the larger centres started with a competitive advantage after the change of the political system in gaining vehicle and automotive industry firms arriving from the countries of Western Europe and initiating brown and/or green-field investments. Among the location factors, the historical past in vehicle and automotive industry production or earlier location conditions played an important role as well but such factors do not have to be considered as primary settlement aspects in the Central and Eastern European region. An unbelievable mass of knowledge is accumulated in the vehicle industry the content, features and place of which occupied in the production process has changed much as well (Smahó 2012). During the research it was examined that changes in the production systems how repositioned the knowledge hubs and how required to exceed and reorganise the previous knowledge flow. The production and principally development needs and the knowledge system built on them as well as the institutional framework have been restructured also because of the fast change in the requirements from the vehicles. While in the 50’s-60’s of the last decade the developments were realised almost completely in production centres, by the expansion of the Toyota method, they were gradually relocated to primary suppliers and as far as it concerns the adapting production that has been spreading today already decisive development functions go into this circle already. Three special features of the vehicle industry innovation could be explored. The first one is that as a consequence of the transformation of the value chain, the suppliers play a more and more important role in the development process, the second one is that a deep technological change characterises the sector, the result of which is the spreading of modular systems and by this the product scale is widening to a great extent. In the end, the third trend is that more and more innovation and development appear in lower-category (cost and function) vehicles, moreover, their new solutions are transferred into higher-category vehicles. It could be justified that at this increased development speed the suppliers would settle closer to car factories, assembly plants in order to establish the direct relations but at the same time there is strong concentration in course in the supplier network itself, which increases the innovation potential. The enterprises specialised clearly to development are connected to this circle in a more and more intensive way, which participate in the complex development of the suppliers but of the production facility as well. During the regional analysis of research and development activities, as the highest level of knowledge production and transfer, we could state that institutions are established gradually after the appearance of vehicle industry units in the Central and Eastern European region. The Czech Republic, with its most considerable production traditions, is outstanding in the region with its research and development institutions (development units, university education, research base); however, in each country of Central and Eastern Europe it can be observed that systems serving the functional renewal of vehicle industry appear. The differences between the countries can be felt in this regard as well, there are really developing (Slovakia, Poland), possessing good skills, conditions but also there are that develop slower (Hungary) (Table 2). 14 János Rechnitzer – Melinda Smahó TABLE 2 Automotive industry research and development capacities in some countries of Central and Eastern Europe (2010) Category Scientific and technology park University centre Excellence centre Technology development centre Research centre / Research institute Centre providing engineering services Test centre Innovation centre Totally Slovenia Slovakia Hungary Romania – 6 – 63 4 8 1 3 85 1 1 7 9 8 6 2 2 36 – 3 – 13 – 3 – 1 20 – 2 1 6 3 4 – – 16 Source: Smahó (2012). We expanded the analysis of the location factors of vehicle industry regarding the countries of Central and Eastern Europe as well via a general, country-level comparison analysis (Füzi–Gombos–Tóth 2012). Our objective was to systematize the location factors characteristic to the sector, by following the trends specified in the literature and highlighting especially hard (measurable) factors such as vehicle industry traditions, logistics, transportation (infrastructural) conditions, the potential supplier environment, the tax system, the labour market and its costs and in the end, the business milieu, which can be measured by the speed of foundation. It could be stated that there were vehicle industry traditions in almost all the countries of Central and Eastern Europe, which might have given guidance for settlement but which had an effect only informally upon decision-making or which, could be felt only if certain location conditions were used. Certain elements of the business environment (level of corruption, speed of company foundation, the blue- and white-collar labour market, the taxation system, the transportation infrastructure, and the potential supplier networks) are very different in the countries of the region. Within each factor, large differences can be observed which may inspire the location choice, but it is important how a cost benefit regarded as favourable (e.g. blue- and white-collar labour force) can compensate the unfavourable circumstances existing in other factors (e.g. bureaucracy, low level of research and development, the under-developed supplier network) which – as other research confirmed this – change slowly in these countries. In Table 3 we defined the ranking of the countries based on the examined six location factors. There are no big differences in this ranking compared to preliminary research. The leading role of Germany and Austria is clear but the latter country have quite bad position in the ranking with two factors therefore they can enter into competition with the upcoming, dynamical countries of the region. They are the Czech Republic and Poland that more and more break away with the former eastern block and supply better and better location conditions. Hungary and Slovakia move together with Slovenia with a medium-level but uneven location factor offer at the same time. However, Economic Effects of the Vehicle and Automotive Industry in the Regions … 15 Romania, Bulgaria and Croatia are positioned at the end of the ranking by offering the least favourable choice in almost all the factors. In the countries of Central and Eastern Europe in the general – thus not soft – location factors the differences are spectacular, the competition for the vehicle industry companies using modern technology can be felt clearly within the region. The countries of Central and Eastern European region battle for replacing each other. TABLE 3 Ranking of regions based on location factors Vehicle Economic Taxation industry environsystem traditions ment Germany Austria Czech Republic Poland Hungary Slovenia Slovakia Romania Bulgaria Croatia 1 2 3 4 5 8 6 7 9 10 2 1 5 4 6 3 7 10 9 8 6 10 8 4 9 3 7 5 1 2 Labour market 1 5 4 2 3 9 7 6 8 10 Infrastruc- Supplier ture network 1 2 3 8 5 4 6 10 9 7 1 2 3 5 4 8 6 7 9 10 Totally 12 22 26 27 32 35 39 45 45 47 Source: Füzi–Gombos–Tóth (2012). Research was carried out on the role played by the state in connection with the vehicle industry and more closely, automotive industry in the countries of Central and Eastern Europe (Pájer 2012). It can be stated that in the member states of the European Union in the region – in accordance with community laws – the state grant system is almost the same the general objective of which is to create jobs, to renew the industrial structure and to help the development and integration of peripheral regions (Table 4). Minimal differences can be observed in the methods, value limits of each grant, as well as in the procedural systems; there are also differences in the sector trends of the grants as well as in their size in the preferred regions. Differences can be registered in case of Slovenia and Slovakia. With the first country, the regional preference is clear while in the second one the employment criterion are coupled with higher granting intensity and the system of transferring real estate is simpler. In Serbia that is not the member of the European Union, the state grant is connected to volume size of the investment and it is connected more to long-lasting tax allowances. In the case of the member states of the European Union located in Central and Eastern Europe the more important vehicle and automotive industry large investments (exceeding 100 million euro) must be announced to the European Commission when a grant is allocated and are subject to authorisation. The system, the information need, the process as well as the time scheduling of judgement need renewing because this procedure reduces the competitiveness of the 16 János Rechnitzer – Melinda Smahó Economic Effects of the Vehicle and Automotive Industry in the Regions … 17 countries of the region compared to the non-union member states located in other regions, such as Eastern Europe and South-Eastern Europe. When analysing the competitiveness of the central and eastern europen countries we must not forget whether the incoming multinational companies can insure the models of quality production on the first hand and whether each country is able to serve the increasing competitive factors on the other hand. Research has proven clearly that the incoming big companies bring some of the elements of their domestic work and production models (educational structure, work organisation, supplier networks, service needs) into the receiving country and they build up their activities in the receiving countries’ regions based on such factors. It can be experienced that among the countries of the region – primarily it is true for the Visegrád Countries – there are not big differences in the location factors therefore their competitive position is almost identical. The difference may come from the fact how much they are able to adapt the above production and work models and what development opportunities they offer to vehicle and automotive industry and to each of its companies. The research directed attention to the safety of the workplace, which means to what extent the presence of qualified labour force is guaranteed and how its extension can be insured in adapting it to the development. It can be experienced that increasing lack of skilled labour force should be expected in the countries of the region, especially in the regions preferred by the vehicle and automotive industry and this can hinder the expansion of production capacities or the evolvement of their more diversified structure. During the research it was suggested how the appearance of the Central and Eastern European region in the automotive and vehicle industry can affect the industry of Western Europe, whether the tensions can acuminate between the regions and at the same time between the countries which might have political and economic consequences. It can be proven that the competition cannot be shown between Germany and the countries of Central and Eastern Europe but between the peripheral countries in Southern Europe and the region examined by our research. This proves that the import to the German automotive industry might not have increased globally but it has been restructured because the countries of the Central and Eastern European region have increased their export jointly to Germany more than Spain and Portugal have increased it (between 1995 and 2005 from 9% to 37%). All the above is confirmed by that the value of foreign working capital inflow into the vehicle and automotive industry was 17 billion euro until 2006 of which the share of Hungary (28.8%), Poland (30.3 %) and the Czech Republic (28.9%) can be defined respectively. Near the assembly factories, the largest suppliers have appeared as well and by this, the sector has developed dynamically because in the large region the share of the sector in the industrial added value increased from 5.8% to 7.3% between 2000 and 2005. The countries of the Central and Eastern European region started to compete for receiving the vehicle and automotive industry investments. As we have marked, the state grants show almost identical systems and structures but there are still essential differences in the taxation systems and disparities in the economic political incentives of 18 János Rechnitzer – Melinda Smahó the sector can be observed as well. On the whole, it can not be found any considerable differences between the countries, however, the political climate, the economic-politic balance, the qualification level of the available labour force, the complexity of the training and educational system, as well as the administrative environment and the site offer of the country in question can be essential factors in location choice and development. Competitiveness of regions and production centres The objective of the other big block of research is to define the parameters – then based on them create categories – of specified regions (NUTS 2) and centres (NUTS 3 and centres) within the Central and Eastern European region, which characterise the regional units from the aspect of receiving the vehicle and automotive industry. The aim of the ranking and categorizing is to demonstrate the position of Hungarian regions and centres. Thus the objective is on the first hand to specify those economic, social and other factors, which strongly determine the position and ranking of the examined regional units, and on the other hand – by positioning Hungarian regions and centres – to give recommendations for improving their position and increasing their competitiveness. Our analyses contributed to the evaluation of the theoretical models of competitiveness and to the research connected to it to the extent that new elements could be integrated into the existing model (Lengyel 2012). The basic categories of classical work productivity and employment were refined owing to which social capital elements as well as the parameters relating to the traded sector (sectors producing for export) were integrated into the model in addition to the basic factors of research and development, factors displaying human capital and those grasping the working capital. In the first phase of the research – that we can call regional dimension – we compared the NUTS 2 units of eight countries, which mean 93 regions and there 91 vehicle and automotive industry economic organisations are operated. The analyses were based on 25 variables which were evaluated by various mathematical and statistical methods. By analysing the factors of competitiveness such as work productivity and employment it could be stated that the region is strongly differentiated i.e. a clearly delimited fault line shows up there. The segregation can be characterised by the fact that regions of the developed Western European market economies and the upcoming regions of Central and Eastern Europe separate definitely from each other. In the former group, high employment rate is coupled with high productivity, while in the latter one low employment rate is accompanied by lower productivity. Our research area – the Western and Central Transdanubian regions – may be in a more favourable position compared to the regions of the former socialist countries, it may be closer to the fault line existing between the two country groups; it is not far from the Czech regions, regarding both aspects (Figure 2). On the contrary to this, the remaining Hungarian regions – except for the capital region because it is closing up to Economic Effects of the Vehicle and Automotive Industry in the Regions … 19 the Western European type – were ranked to the peripheries of the larger region by getting much behind. It could be proved that the presence of the vehicle and automotive industry companies does not mean a differentiating factor in the complex competitiveness and the clear influence of such sectors cannot be caught in the act on either employment or work productivity. FIGURE 2 Types of regions by competitiveness principal component Source: Lengyel (2012). From deeper examinations – the analyses of factors affecting competitiveness – it could be stated that two factors define the position of the regions in competitiveness. The first one is called human capital – this factor includes the development level of the labour force, the ability to attract labour force and the existence of patents –, which divides the large region to a great extent by showing a more sophisticated picture in its differentiation. Our examined regions are closer again to the values of the Czech and Polish regions, which are not far from the limit values. However, the remaining Hungarian regions were far behind, they are characterised by the same values as the peripheral Roman regions. The other factor is research and development – R&D expenditures, the proportion of employees in the high-tech sector, generation of fixed capital, winner framework programmes –, which symbolises the presence of knowledge-based economy and innovative sectors and by this, it spreads the Central and Eastern Euro- 20 János Rechnitzer – Melinda Smahó pean region to a larger extent. In this “mushroom-shaped” division the two regions of our research area move together but they are more behind the Czech and Polish regions. The analysis strengthens the Hungarian – or it can be said, Central European – feature again that the capital region is characteristically differs from the remaining regions – in our case Budapest is segregated specifically spectacularly –, and it is closer to the developed regions, the cap of the „mushroom”. In the „stem”, as the block falling behind, the remaining Hungarian regions can be found indicating that their research potential is unfavourable and by this their competitiveness is specifically weak in Central and Eastern Europe. The next level of the spatial features of the vehicle and automotive industry is the definition of the position of those regional units, which include production facilities themselves or may be potential areas of operation for them (catchment areas) (Lukovics–Savanya 2012; Dusek 2012). We narrowed the research area (Central and Eastern Europe) because the analyses proved that it is more appropriate to evaluate the competitive situation of the Hungarian regions in relation to the Visegrád Countries more in details. The reason for this is that a vehicle and automotive industry potential has evolved in these four countries and it is developed continuously via both the capacity increase of the facilities and the building up of the supplier networks. The location factor offer of the four countries has become more favourable (production culture, presence of suppliers, special professional training, transportation infrastructure, system of state grants), but it should not be forgotten that the mentioned countries have almost the same conditions in the offer of such factors. Therefore the competition is more intensive for expanding the facilities, receiving suppliers or building the suppliers’ network in this company group. The research directed attention to how the vehicle and automotive industry zones are shaped in the Visegrád Countries, that is to say the further industrial capacities have been built that can be found near certain larger factories, assembly facilities belonging to this sector and by this a future large region of vehicle and automotive industry is shaping, which might cover several smaller spatial concentrations that are separated regarding their character. In the spirit of the previous findings, also the examinations were continued in two directions. The first one was the comparison of the NUTS3 area units of the Visegrád Countries by defining the dimensions of their competitiveness but the other direction – with a newer narrowing – is only the analysis of the vehicle and automotive industry centres, showing how the sector affects their development and exploring their position compared to one another. The first direction of deeper examinations at regional level is thus the NUTS3 level (in the group of examined countries we observed 108 units) where we aimed at using the indicators that we had elaborated earlier for the competitiveness. It should be remarked that the deeper we go down in the regional consideration, the more difficult it will be to find uniform figures that can be compared. Therefore, it was necessary to supplement the factors belonging to the basic category of competitiveness with those factors that are related only partially to their interpretation sometimes. Economic Effects of the Vehicle and Automotive Industry in the Regions … 21 The analyses realised via multidimensional scaling showed that firstly the average ranking number of Hungarian counties is the highest in the country group, therefore, their situation is less favourable all in all compared to the counties of the other three countries (Figure 3). The cluster analyses made the image more detailed by that they defined development groups, i.e. the counties represented the same level in development therefore their competitiveness can be judged the same as well. FIGURE 3 Competitive ranking of countries Source: Lukovics–Savanya (2012). The counties of the four countries are strongly different in this relation. There are quite moderate differences among the Czech counties thus they were concentrated into groups with „relatively strong” and „strong on the average” competitiveness. The Polish counties are already more different, they were ranked into the „weaker than the average” and „weaker” groups, while in case of the Slovak counties high duplicity can be observed already: their competitiveness is either very weak or rather falling behind. The Hungarian counties are also different; most of them are in one of the categories with weak competitiveness. Two of the six examined counties (Győr-Moson-Sopron 22 János Rechnitzer – Melinda Smahó and Komárom-Esztergom) were ranked into the group with relatively strong competitiveness, two of them (Fejér and Vas) belonged to the cluster with features stronger than the average, while two of them have the values of areas with weaker than the average (Zala and Veszprém). The second direction of research was also based on the NUTS3 regional units of the Visegrád Countries and the former analysis was supplemented by a comparison made between the group of regions with or without vehicle and automotive industry (Dusek 2012). We wished to test by this analysis – in addition to the analyses made earlier – whether the sector contributes to the development of the area and if yes what level its intensity can be in each country. It can be stated that the competitiveness of regions possessing vehicle and automotive industry is much stronger than the competitiveness of the counties – more exactly, centres and their surroundings – that do not concentrate the companies of the sector. This better competitiveness represents an important attractive force to the further companies connected to vehicle production thus they can achieve constantly higher dynamism. Competitiveness can differentiate also countries which can be analysed deeper in accordance with development differences of the regions with and without vehicle and automotive industry. The research statements become deeper by that we break down these counties based on whether they are town or non-town regions (Table 5). TABLE 5 Competitiveness of the sub-regions with and without vehicle factories by countries Country Average of sub-regions with a vehicle factory Average of sub-regions without a vehicle factory Average of all the sub-regions 640 474 520 684 548 577 412 338 404 410 609 412 365 509 444 Czech Republic Poland Hungary Slovakia Together Source: Dusek (2012). The towns having vehicle and automotive industry were able to realise higher GDP increase while they showed stronger migration and flat building values near lower unemployment. The counties (sub-regions) without vehicle and automotive industry were behind the other ones in relation to both the towns and regions without towns in all of the examined parameters. It can be confirmed thus that the presence of the vehicle and automotive industry in one or another county (sub-region) influences the economic flows favourably, furthermore, strengthens the town functions and increases their attraction at the same time. Location conditions as well as the situation of centres with vehicle industry compared to one another were analysed, and within them, the three centres of the Western and Central Transdanubian regions were positioned (Filep–Tömböly 2012). It can be Economic Effects of the Vehicle and Automotive Industry in the Regions … 23 shown that the towns receiving the vehicle and automotive industry vary considerably in their size, characteristics, functions and influence on the region (catchment areas, number of institutions, their region-organising effects). During the location process do not these aspects were decisive because the around fifty towns where vehicle industry is registered move on the wide scale of small, medium and large towns. The similarity is important in the fact that the institutions of industrial infrastructure were built gradually (industrial park, innovation centres), the transportation connections (railway junction point, vicinity of an airport) are favourable, and the higher education institutions are on the spot or at available vicinity and the centres play regional or local organisation roles as well. Furthermore it can be stated that centres in Hungary are not in an unfavourable position based on such functions. The location conditions of the three centres (Győr, Esztergom, Szentgotthárd) are renewed continuously therefore they are able to serve the operation of the vehicle production and offer urbanisation advantages to that (Figure 4). The research examining the contexts of the vehicle and automotive industry and the regional development strategies draws the attention to the fact that the sector group has not been integrated directly to the development concepts of the 46 NUTS 2 regions of the Central and Eastern European region (Tóth 2012). The development level of the regions varies to a large extent in the larger region therefore the development gravity centres are really differentiated. As far as the capitals and regions possessing important economic potential the supporting of development should be underlined which targets the intensive improvement of higher education as well as research and development potentials. This can be favourable to the vehicle and automotive industry of each country but it is known from other research that such potentials can be integrated into the development very slowly and mainly the skilled labour force can mean improved attraction and resource offer. In less developed regions rather infrastructure development is emphasised and within this, the more favourable shaping of the location factors are aimed at, which might offer opportunities for capacity increase and for the location of the newer members of the supplier network. The research found little reference for vehicle and automotive industry in the lagging regions, after all the aim is to shape the availability of such regions and to insure employment at least at a minimal level. The developments of the regions in the Central and Eastern European area count less with vehicle and automotive industry or its capacity increases but the larger region is very divided, there are ever deepening differences between the regions thus the capitals and their surroundings as well as the centres showing growth potential can have the chance to receive vehicle and automotive industry or the activities connected to it. From among the country studies the chapter covering Slovakia publishes interesting and instructive results (Kovács 2012). The Slovak economic policy shaped the vehicle and automotive industry developments consciously and three car factories settled into three centres after the beginning of the third millennium. The location policy is instructive itself as well, after all the features of the country, the regions and the centres in question were exploited, by applying a wide granting system. Slovakia exploited favourably its EU membership, by introducing the common currency it achieved 24 János Rechnitzer – Melinda Smahó FIGURE 4 Vehicle industry centres and their production potential in the Visegrád Countries Poznan Poznan Warszawa Warszawa Polkowice Polkowice Jelcz-Laskowice Mlada Mlada Boleslav Boleslav Praha Praha Starachowice Starachowice Walbrzych Walbrzych Vrchlabi Vrchlabi Kvasiny Kvasiny Kolín Kolín Gliwice Gliwice Nosovice Nosovice Tychy Tychy Niepolomice Niepolomice Bielsko-Biala Bielsko-Biala Žilina Žilina Bratislava Bratislava Trnava Trnava Győr Győr personal car commercial vehicle engine Edited by Tamás Hardi, 2012. Szentgotthárd Szentgotthárd Esztergom Esztergom Economic Effects of the Vehicle and Automotive Industry in the Regions … 25 economic stability which favoured and which favours the emerging assembly facilities that wish to build markets. It is instructive that the supplier networks were built continuously, their directions were defined (electric systems, internal appliances, drive gears, body elements other driving structures), then the transparent granting policy was also established to them. Owing to this the location of first-level suppliers – mainly companies that were organised by foreign ownership – started fast in the Slovak economy which was followed by the appearance of the second and third level suppliers the majority of which are owned by Slovak owners. By the automotive industry centres but in other industrial centres as well (Nitra, Banska Bistrica) the suppliers appeared and the cluster establishment was started by them. The research draws the attention to the weaknesses of the Slovak automotive industry which can be observed in the moderate participation of the university and research and development facilities and institutions on the first hand and in the concentration of production and supplier networks in the western part of the country – as the reproduction of regional disproportioning – on the other hand. The Slovak example proves that the targeted location of the vehicle and automotive industry can contribute largely to the renewal of an emerging economy. Characteristics of the supplier network in Hungary At the presentation of the research concept it was mentioned that a questionnaire with 118 companies was carried out in order to examine the supplier network of the Hungarian vehicle industry. Almost two third (28.9%) of the examined firms were located in the selected two regions (Western and Central Transdanubia) but the other regions of the country were represented in the necessary proportion as well. 94 percent of the enterprises were established after 1990 and within this, more than half of the companies (57.4 %) were launched between 1990 and 2000. The sample is characterised mainly by medium and large enterprises (59.4%), and only 30.1 percent of the enterprises examined by us were established via green-field investment. The proportion of Hungarian ownership came out above 50 %, and in case of 53.0 percent of the examined organisations the share of activities connected to vehicle industry was above 75 % therefore it can be stated that the sample represents the Hungarian vehicle industry to the necessary extent. We supplemented the questionnaire with the deep-interview examination of 43 vehicle industry suppliers located in the Central and Western Transdanubian regions (Józsa 2012). It could be stated based on the primary research that the examined suppliers did not have strong domestic competitors therefore they play an important role in the sector as they state. By systematizing the strengths of the enterprises, the favourable location factors are outstanding (social capital, geographical position, proximity, favourable business environment, professional knowledge, stable employee background), the modern business aspect (flexibility, quality, specialisation, modern company management systems), and the continuous innovation constraint (low-series production, providing service supplements, success orientation, reliability, participation 26 János Rechnitzer – Melinda Smahó in the development). The analyses covered the weaknesses of the suppliers as well. Such weaknesses are resulted from the quantitative and qualitative factors of the labour force (local lack of professionals, lack of foreign language skills, underdeveloped work place culture), the weaknesses of the economic environment (bureaucracy in administration, changing legal regulations, lack of grants, tenders) and in the end from the increased competition (vacuum effect of big companies, geographical distance, size of companies). The organisation of business relations does not mean a problem in case of companies, which belong to a parent company seated in a foreign country; the market organisation is solved in their case and similarly they do not have to deal with development – or only to a minimal extent. Nevertheless, in the case of suppliers in Hungarian ownership or which do not connect to larger international companies, the organisation of markets demands considerable forces, they build their markets mainly on earlier business relations. These organisations are prevented in that they do not have the necessary capital either for the insurance of continuous and good-quality raw material supply nor or the continuous development. The enterprises supplement the lack of capital via intensive resource collection where they request the Hungarian grants allowed to enterprises as well as the innovation-promoting tools but they can receive ever less because of the lack of state resources. It is a generally expressed weakness that either the quantity for the quality of the skilled labour force are not insured in the two examined regions (skill level, work culture, language skills) for the constant company expansion and development. However, despite all of these, the development directions were defined by most of the companies, thus they aim at the increase of the market share, the widening of the production profile to which they connect production, plant and labour force expansion. In order to realise these goals, they define strategic objectives such as strengthening of customer relations, reduction of dependence relations, guaranteeing financial stability as well as implementing product and production development. According to the survey, it could be stated clearly that – in spite of the economic crisis – the supplier firms in the vehicle industry are development-oriented, they have defined future objectives and for them, they are able to mobilise the necessary tool system, however at varying intensity; but they also consider the enlargement of the national-level and regional granting systems as necessary. The first block of the questionnaire related to the development and operation of the network systems of the vehicle industry enterprises (Csizmadia 2012). It could be stated from the examinations that in this sector population the statements concerning to other Hungarian supplier relations are valid as well. The difference is only that the participants of the examination are surprisingly close to the central players of the chains (producers or first-tier suppliers), and at the same time, they are also the members of the networks in some ways. Unfortunately, the relations are not multi-complex, they concentrate only to one activity. With one third of the enterprises of the sample the harmonised relations can be shown definitely, which relate to purchasing, research and development or the joint application of other (service provider) functions. The first marks of arranging into a network can be recognised with the vehicle industry enterprises but these networks cannot be defined at regional level (regional dimension), Economic Effects of the Vehicle and Automotive Industry in the Regions … 27 they appear rather in the sector focus yet. In the case of the examined two regions the organisation of regional networks can be recognised the reason for which is that the enterprises located there entered the chain earlier (1990’s), their relations with the foreign companies and large automotive companies are stronger therefore they have more favourable conditions for building strategic alliances than organisations with a similar profile located in other parts of the country. The relation analysis established with the environment of the enterprises showed that the economic chambers as well as the local municipalities are the players that the enterprises have intensive and continuous co-operation with (Reisinger 2012). At the enterprises of the examined regions the relations with higher educational institutions can be either recognised or felt (research orders, consulting) but in such co-operation it is not good organisation or consciousness that are remarkable but it aims mainly to insure the following generation of professionals. The research underlined that settlements receiving the enterprises, as primary location factors do not influence the organisations, and they do not have sensible influence, effect on either the operations of the enterprises or on their further development or on the shaping of their relations. Most of the settlements or their municipalities can live only indirectly (reputation, attraction of other enterprises) with the presence of the suppliers, and vice versa, the enterprises themselves are unable to have constructive strengths from the settlements (in relation to education, training in a better case). Innovation activity can be considered as a special form of relations, which characterises 90% of the organisations (Nárai 2012). Most of the innovation activities cover product development, as well as product and production renewal but organisational and marketing innovation can be observed as well. At the same time one third of the organisations consider innovation as the decisive, definitive factor of the competitiveness. On the contrary they consider market relations, cheap but skilled labour force or standing on several feet as more important. However, it can be shown that the enterprises having more capital strength, employing larger numbers of more skilled labour force and possessing wider supplier relations are more willing to innovate. The second big block of the questionnaire analysed the business and market operations of the supplier enterprises. When searching the conditions of strategic thinking it could be stated that at most companies the conscious and organised system of future shaping could be recognised. In most cases strategic aspect can be shown only in the short run and it is realised with the involvement of a narrow circle of company management (Bencsik 2012). In the two regions the time dimension of this strategic aspect thinking covers a longer distance just because of the longer company history and the more arborescent. The relations between ownership structure and strategic thinking could be also shown based on the research. The sample proved that the strategic thinking of Hungarian-owned companies with less capital strength is weaker than the planning activities of foreign-owned companies with more capital resources but in the latter case strategy building takes place especially centralised – at the parent company. The company size and the capital strength play a decisive part in conscious future shaping. 28 János Rechnitzer – Melinda Smahó The next block examined the components of the successful enterprise (Eisingerné 2012). By the aid of the questionnaire, the research could identify the criterion, which defines the competitiveness of companies in the vehicle industry. Such criterion are the favourable price, the safe partnership relations, the high and stable quality, the outstanding productivity, the wide product choice and the good adaptation ability; the organisation is able to stay in the competition if such factors are present jointly and the organisation can owe its successful operation of such factors at the same time. The Hungarian-owned suppliers established in the Central and Western Transdanubian regions are able to fulfil only a few of the previous factors. Thus they are able to operate as Tier 2 suppliers constantly; there are only a few of them that can achieve the success of being Tier 1 supplier. The chances of small and medium-sized enterprises are clearly moderate, only their very small number is able to break out, establish successful enterprises and close up to the foreign-owned companies. When examining the relations between the company size and management it could be shown that in case of companies which are more centralised and belong to a larger international organisation the information system might be more developed but they are less able to react fast (Ercsey 2012a). The way of seeing the things, as well as the mentality and relations of the company management are decisive in the efficiency of leadership; in this regard the two examined regions show a more favourable image than other Hungarian regions. The situation of Hungarian-owned, medium-sized organisations with less hierarchical ranking is similarly favourable because they are able to react to changes faster than the stronger, very centralised enterprises. Such advantages can be shown in information management as well and the enterprises underlined the role of this function in several regions, which shows the movement toward more developed company management. When examining the organisational systems of marketing activity it could be shown that the existence of this function depends largely of the size of the company (Ercsey 2012b). In smaller organisations, marketing is part of the company management but in regions with stronger market influences and older production traditions (e.g. Western Transdanubia) marketing is managed as an outstanding activity. The customer satisfaction is a decisive element of the marketing strategy of all the enterprises but flexibility does not characterise the organisations. Neither costs nor the profit but the client’s constraint predominate the price and business policies; not the principle of return play the decisive part in price calculation but the needs of the clients that are ruling. The suppliers are exposed to assembly facilities (OEM) and this dependence cannot be reduced either by innovation or cooperation opportunities (Lőre 2012). Economic Effects of the Vehicle and Automotive Industry in the Regions … 29 Recommended development principles and directions The research has proven that the vehicle and automotive industry is a fast-developing, dynamic sector of the Central and Eastern European area for the development initiatives of which countries possessing almost identical location conditions as well as regions and centres with already more differentiated in location factors – compete with each other. In this ever-accelerating market space the Hungarian regions and large centres have to strengthen their position. Moreover, they have to develop it in a way that they can assist the renewals of the existing vehicle and automotive industry bases on the first hand and on the other hand they can promote the establishment of new capacities – that wish to connect partially to the existing ones. The two development trends have shared elements therefore we have to aim at underlining such shared elements in our recommendations. It became clear from the research that the regions and centres could be the winners of the vehicle and automotive industry developments of the coming five-eight years, which consciously shape the location factors. By establishing the location environment the undisturbed operation and development of the sector can be insured while the market relations are also growing. According to the research findings, the qualification level and the available quantity of the labour force are the most important starting points for the future development. The fast renewal of skilled worker education, introduction of dual training in higher education, the preparation for the entrance to the labour market, maintaining the favourable elements of the work culture and establishing newer ones (such as especially foreign language skills, the development of communication skills, adaptive ability at the work place, shaping of participation in team work) are the most important conditions for the future development of the vehicle and automotive industry. It would be appropriate to think and develop in regional dimension with secondary level (skilled labour) training which might mean the harmonisation of education capacities on the first hand and on the other hand, the more reasonable shaping of work distribution – and resources – at the same time. Concerning the development of education, not only the secondary level training should be renewed but also much attention should be paid to higher education. In universities, in addition to transferring new knowledge, strengthening language training, developing innovation activity, a basic competition requirement is that the basis of research and development should be built and renewed in a versatile way. It would be appropriate to establish the network of higher education institutions that should be connected to the vehicle and automotive industry to generate and promote educational, training and research connections between them. The number of specialisation would be worth increasing and the professional engrossment would be worth widening via international relations and their networks. In addition to higher education and the research and development built on it, organisations supporting innovation were established in the two regions, which have considerable experiences in the sector of small and medium-sized enterprises (SME’s) in connection with supporting technical, product and activity development as well as 30 János Rechnitzer – Melinda Smahó their process. It can be experienced that such innovation centres and their organisations can be found in almost all centres accepting vehicle and automotive industry companies or more important suppliers. It would be beneficiary if the sector could play a more important role in their activity, and enterprises, which are connected to vehicle production or which wish to develop into this direction would be treated with more attention. Decentralised innovation-supporting tools (funds) would be necessary for this, which were available at spatial (regional) level and could be distributed based on the needs of the towns accepting vehicle industry or their organisations. In the Central and Western Transdanubian region the industrial infrastructure is at a high level therefore the location conditions are insured, which can accept the units of the vehicle and automotive industry. However, the network of industrial parks does not provide their offers in a harmonised way, there are no specialised location systems, and the centres rather compete instead of co-operating. The joint offer and the market participation do not appear. By distributing the suppliers in a more reasonable manner – labour force, transport costs, specialised knowledge, places of training and education – considerable reduction of costs can be achieved, which could result in further economic effects (establishment of newer enterprises, improving transportation connections, renewal of the environment of settlements, vivifying smaller region effects), and at the same time it could improve the competitive position of the two Hungarian regions in the Central and Eastern European region. It can be experienced that in the Central and Eastern European large region supplier concentrations are shaping around each vehicle industry centres. They are the natural and reasonable trends of industrial development. It is the task of regional policy to give incentives to the generation and then to the continuous operation of such concentrations at national or regional or local level. In addition to the support of the above mentioned site offer, the encouragement of innovation process, and the supply of professionals, it will be a future task to strengthen the establishment of network systems. However, the number of clusters connected to vehicle and automotive industry may be high in Hungary and the enterprises of the two examined regions joined such organisations, but these groups are not able to find their own, special character, they have not become the resources of renewal of the sector yet. The level of establishment should be exceeded in case of the clusters (establishment, construction, planning of the organisation) to which clear central and regional support, stable organisational systems and clear development objectives are necessary – that can be achieved. Last but not least it should be underlined that in the two region a zone of vehicle- and automotive industry emerges – spontaneously at the moment – for the targeted shaping of which the large-scale co-operation of the players would be necessary (state, enterprises, local municipalities, bridge organisations, educational and higher educational institutions, research and development organisations, interest representation organisations, etc.). The location factors cannot be developed in a segregated way any longer, the only local renewal of labour force basis will not produce any results as well as the individual development of transportation and infrastructural systems and various public services (health, education, public institutions) will not do either. In the developing vehicle and Economic Effects of the Vehicle and Automotive Industry in the Regions … 31 automotive industry region they must be shaped in a harmonised and targeted way – based on development plans. 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CENTRAL AND EASTERN EUROPEAN AUTOMOTIVE INDUSTRY IN EUROPEAN CONTEXT GYÖRGYI BARTA Keywords: integration economic recession technological advancement centre-periphery low-wage work model relocation Abstract: The globally organised automotive industry is one of the most essential sectors in the European economy, in terms of scale, its role in employment, its driving role in the economy, as well as its predominance in the field of research and development. In this study three dimensions of the recent history of the European automotive industry are discussed and highlighted: the development stage of it starting from the 1990s, the effect of globalisation and the economic integration of the Central and Eastern European countries after the change of the political system; the years of economic recession which have meant a dip in the development of the automotive industry; as well as the anticipated changes in the foreseeable future which are expected to revolutionise the role and structure of the automotive industry. The second part of this study examines the integration process of the Central and Eastern European region regarding its effects on the automotive industry. The process is characterised by a centre-periphery relation. However, in the ECE countries, the automotive industry is almost exclusively linked to foreign direct investment (FDI). This relationship, however, has been changing, and the question is whether these significant developments will open chances for these countries to narrow the gap between them and the more developed part of the world. Introduction Automobile manufacturing is an extremely important sector in Europe. One third of the vehicles produced in the world are manufactured there; after Asia, Europe is the second largest car and motor manufacturer in the world. The European automotive industry employs 6 million people directly, and a further 12 million jobs are associated with this sector indirectly. The automotive industry generates 3% of GDP in Europe, and it represents 7% of the aggregate industrial production as well as 5% of European exports. The last ninety years of the European automotive industry’s history can be divided into four periods: the initial stage between 1920 and 1930, the period of dynamic advancement and progress following World War II, and the slow-growth period between 1960 and 1970, and finally the period starting with the 1990s which is considered on the one hand as the evolution of globalisation, and, on the other hand, provided opportunities for Central and Eastern Europe to catch up with the West European automotive industry after the change of the political system. This region, with its automotive industry established chiefly by the investment of foreign capital, has developed from net importer to net exporter within two decades, and the Central and 34 Györgyi Barta Eastern European countries have become absolute winners of the development of the global and the European automotive industry. It should be clarified at this point which countries are referred to when Central Europe or Central and Eastern Europe are discussed (this region is collectively referred to as Central and Eastern Europe, abbreviated here as CEE). A determinant role for the sake of Central Europe is played by Germany – due to its size and economic leadership. Austria also belongs to this region but is not so much interested in the automotive industry. The Central and Eastern European regions encompass the Czech Republic, (Southern) Poland, Slovakia, Hungary, Slovenia, Romania and Bulgaria, as well as Croatia and Serbia. This study discusses the automotive industry of this region. (Other surveys include also Russia and Turkey in this region). The CEE region generated 12% of world automotive production in 2010. The major share was represented by the German-owned automotive industry, but ratios have changed significantly between Germany and the CEE countries during the past 10 years from 77:23% to 64:36%, i.e. without Germany. A total of 4.4% of the world’s vehicle production is now manufactured in the CEE countries (three-fourth of it being produced in the Czech Republic, Poland and Slovakia). Foreign direct investment and the restructuring referred to above, as well as relocation of production sites have triggered a professional debate within the CEE region: How much can the automotive industrial performance of countries receiving foreign working capital investment be considered an economic achievement of their own? Where are the limits of development? Does the development of the automotive industry assist Central and Eastern European countries in closing the gap to the more developed world? Even in the investing countries doubts were raised: Will relocation cause job losses in the core territories or not? This study consists of two parts: − In the first part, the global status of the automotive industry as well as its development is discussed. The literature dealing with this popular topic is abundant. Within the framework of this brief study two issues are set in focus: the economic and territorial effects of the economic recession which are discussed in detail; in addition, it was impossible to omit a very exciting issue, namely that the automotive industry will step into a new era soon, which will see a radical transformation of the structure of the automotive industry throughout the world. − The second part provides an analysis of the integration of Central and Eastern European countries into the car manufacturing sector of Europe and the world, as well as presenting an assessment of this region’s chances of catching up. The situation of the countries forming the periphery of Europe is examined within the framework of the centre-periphery relationship. Central and Eastern European Automotive Industry in European Context 35 Global importance and dynamics of the automotive industry Global status and development of the automotive industry The automotive industry in the world and in Europe In 2006, the world’s automotive industry was concentrated in three large regions: Western Europe, North America and Japan. Combined, they produced nearly two thirds (62.9%) of all the vehicles in the world. However, regarding the volume of production, they were closely followed by China. By 2010, the world’s automotive industrial production pattern had radically changed: Owing to the boom-like growth in China, over half of the world’s vehicles were produced in Asia (while Japan’s share declined notably). The share of European production decreased somewhat (the referenced research includes Russia and Turkey in this group), but still accounting for one-fourth of the world’s vehicles manufactured. The share of North America (consisting of the USA and Canada) decreased dramatically, but the share of South America grew. Obviously, the focus of the automotive industry shifted from the developed part of the world into the group of emerging and developing countries: The ratio of 63%:37% recorded in 2007 changed to 43%:57% in 2010 as for the number of vehicles produced in the respective world regions (Table 1) (Halesiak et al. 2007). The European automotive industry – besides its characteristic big share in passenger car production – takes an essential role in employment: In this sector, 6 million people are directly employed (1.2 million people are employed in the automotive industry; 4.8 million are employed by suppliers), and indirectly nearly 12 million jobs are associated with this industry – both at large companies and small and medium sized enterprises. This sector operates Europe’s most extensive privately owned research and development units, into which approximately 20 thousand million Euros have been invested until now; additionally, it is the key driving force of innovation. The automotive industry generates 3% of the EU’s GDP, it accounts for 7% of overall industrial production and for 8% of the aggregate government expenditure of the Member States of the European Union, and it represents 5% of total European exports. The Central and Eastern European automotive industry is developing rapidly. This region has changed from a net importing area to a net exporting region. In 2006, over 300,000 vehicles were produced, more than those sold in the region, and for 2012, 1.1 million vehicles are scheduled to be manufactured. Development projects in the automotive industry are mainly associated with foreign direct investment (FDI). In principle, this region is attractive for FDI due to lower wages and highly skilled labour. In addition, it is also considered to be a promising new market. The majority of industrial automotive investments have manifested themselves in green-field development projects. The geographical vicinity to West-European markets is a significant factor to be considered when new productions sites are being planned. The CEE region is an excellent choice for lower cost production, which is an important criterion in the intense global competition. New assembly plants were followed by 36 Györgyi Barta suppliers and subcontractors. Later on, a relocation of more complex activities with higher added value took place. TABLE 1 Regional distribution of the automotive industry (OEM*) Region Vehicles produced, in% North America South America Western Europe Central and Eastern Europe** Africa Asia and Oceania Of which: Japan China South Korea India Total 2007 2010 22.9 4.6 23.4 7.4 0.9 40.8 12.6 8.6 17.9 7.4 0.8 52.7 16.6 10.4 5.5 2.7 100.0 12.4 23.5 5.5 4.5 100.0 *OEM = original equipment manufacturer (complex vehicle factories). **CEE excluding Germany and Austria and including Russia and Turkey. Source: Own calculations, based on OICA statistical figures, and Halesiak et al. (2007, 6). Evolutionary periods of the automotive industry, a chronology of processes Periods of consolidation and deconsolidation alternated in the past ninety years of the European automotive industry. What does consolidation mean? Industrial consolidation means the reduction in the numbers of domestic manufacturers or domestic brands in a particular country. Market consolidation means the decrease in the numbers of manufacturers and brands on the market of a particular country. Consolidation, therefore, refers to the concentration of (all) domestic manufacturers or domestic and all car brands produced in a particular country (while production and profitability is constantly increasing). Deconsolidation indicates the appearance of new (domestic or foreign) players and new car brands (Diez–Becker 2010). In the history of the world’s automotive industry, the number of global players has grown continually. In the 1960–1970s, the appearance of Japanese manufacturers on the American and European markets meant the beginning of a new era, and in the 1980– 1990s they were followed by Korean automobile manufacturers. Statistical figures already indicate that the next era will feature the dominance of Chinese manufacturers (Figure 1). Central and Eastern European Automotive Industry in European Context 37 FIGURE 1 Production trends (number of vehicles) in the automotive industry of some countries surveyed between 1950 and 2010 16 000 000 14 000 000 12 000 000 10 000 000 8 000 000 6 000 000 4 000 000 2 000 000 United Kingdom France Germany Italy Sweden Japan 2010 2000 1990 1980 1970 1960 1950 0 USA Source: SMMT, Motor Industry of Great Britain (2003). Consolidation and deconsolidation in the European automobile industry The European automobile industry went through four major stages: − The 1920–1930s can be considered as the first consolidation stage (this is the era of industrial pioneers and the first mergers). − The second stage comprised the 1950s, the years of prosperity following World War II. − The third stage began in the 1960s, when the fast pace of economic growth began to slow down and the market of sellers changed into a market of customers. − The fourth consolidation stage commenced in the 1990s as a response to the challenges posed by globalisation. More details about the fourth phase The fourth phase was characterised by two essential changes: The establishment of the European Single Market (from 1986), and the change of the political system in Eastern Europe. The majority of Eastern European, formerly socialist countries joined the EU. These changes enhanced the European economic integration. However, globalisation 38 Györgyi Barta created a keener competition also in the European market. The political and economic transformation of the Eastern European countries gave ample space for the settlement and extension of lower cost production in the automotive industry. This era cannot only be characterised by the withdrawal of players from the market (nevertheless there were some examples of these as well: Chiefly, the car brands formerly produced in the socialist countries disappeared, such as Trabant, Wartburg, etc.), because also company fusions occurred (Škoda, Seat – VW). Production of the automotive industry in the Central and Eastern European region increased by nearly 30% in the decade under review, falling only slightly behind the dynamism of global production (world production increased by 33.4%). Within the CEE countries, German companies play a dominant role (the extent of this predominant role is much larger if the territorial distribution of the companies by proprietorship is examined. This will be discussed in detail below). The division of labour between Germany and the CEE countries changed during the 10 years under review: from 77:23% to 64:36%, from which every CEE country benefited. In the aggregate, the CEE region contributes about 12% to world production (on the basis of the number of vehicles manufactured) (Table 2). TABLE 2 Strengthening of Central and Eastern Europe (CEE*) in global automobile manufacturing Number of vehicles produced (1000 units) Share of countries in CEE and global automobile manufacturing CEE=100% Germany Austria Czech Republic Poland Slovakia Romania Slovenia Hungary Serbia Aggregate Russia Turkey Global aggregate Global=100% 2000 2010 2000 2010 2010 5,527 141 456 505 182 78 123 137 13 7,162 1,206 431 58,374 5,906 105 1,076 869 557 351 211 168 18 9,261 1,403 1,094 77,858 77.2 1.9 6.4 7.1 2.5 1.1 1.7 1.9 0.2 100.0 63.8 1.1 11.6 9.4 6.0 3.8 2.3 1.8 0.2 100.0 7.6 0.1 1.4 1.1 0.8 0.5 0.3 0.2 0.0 12.0 1.8 1.4 100.0 * In our study, the CEE region does not include Russia and Turkey, but includes Germany and Austria. Source: Own calculation based on the figures of OICA statistics. Central and Eastern European Automotive Industry in European Context 39 Impact of the recession: Transformation of the European automotive industry and its alternative options The European automotive industry had gone through some profound restructuring well before the outbreak of the recession (2008–2010). Several problems triggered the restructuring: European automotive industry suffered from − market saturation (in West Europe every third person had an automobile in 1993); − a significant decline in demand (chiefly due to traffic congestion in cities); − oversized production capacities; − increasing raw material and fuel prices (mainly due to the increasing price of crude oil); − technological lag (due to insufficient expenditure in R&D); − a relatively high level of production costs. Prior to the outbreak of the recession, new markets and new production areas were established (for instance in the CEE region, in China and India) and production costs were significantly cut back by the relocation into countries offering lower labour costs. The recession affected the European automotive industry quite severely, both in the West and in the East – although to differing degrees (Table 3). While global production in 2010 was again already in excess of the level recorded in the period preceding the crisis, in Europe the recovery was slow. However, the CEE region (including Germany) had a mitigating effect on the decline of European production, so much so that in this region the number of vehicles produced in 2008 was still not decreasing, and by 2010 output levels approximated those recorded in the year directly preceding the onset of the recession (Figure 2). The lowest point of production in Germany was reached in the first quarter of 2009, then, following a continual increase in the second half of 2010, another setback occurred. TABLE 3 Slow-down of automotive production in the years of the economic recession Changes in the number of vehicles produced (%) 2008 vs. 2007 Global production* Europe’s production CEE 96 95 100 2009 vs. 2008 87 77 87 *OICA members. Source: Own calculation based on the figures of OICA statistics. 2010 vs. 2007 106 84 97 40 Györgyi Barta FIGURE 2 Change in the production of automotive industry, 2007–2010* (number of the produced vehicles) 25 000 000 20 000 000 15 000 000 10 000 000 5 000 000 Central and Eastern Europe Europa 2010 2009 2008 2007 0 Japan USA Source: Calculated by Szabolcs Szabó based on OICA figures. In other CEE countries, production still showed significant growth in 2008 (with the exception of Austria). In 2009, the volume of automobile manufacturing dropped considerably in Hungary and Slovakia, in addition to Austria. However, the Czech Republic – as the most significant automobile manufacturer in the region after Germany – posted a positive year-end balance even in the second year of the general recession. By 2010, each country increased its production considerably compared to the production in the previous year – with the exception of Austria and Serbia. As a consequence, production levels recorded in 2007, i.e. in the year before the outbreak of the crisis was exceeded by the Czech Republic, Poland, Romania and Slovenia, while Germany approximated it. However, Hungary, Austria and Serbia achieved merely half or two thirds of this level (Figure 3, Table 4). Accordingly, the figures show that it was in 2009 that automobile production really dropped. Nevertheless, by 2010, the CEE region by and large managed to re-achieve the output posted preceding the crisis. The fact that, for the European automotive industry, this was a relatively minor and shorter recession was the result of a concerted effort by the EU, the governments concerned, the automobile manufacturers and the trade unions. It was not generally attributable to a domestic market effect as vehicle-purchasing dropped dramatically: Between 2007 and 2009 sales of new automobiles in Great Britain dropped by 21%, in Spain by 53%, in Romania by 60%, in Hungary by 63%, in Ireland by 71% and in Iceland by 87% (Figure 4). Central and Eastern European Automotive Industry in European Context 41 FIGURE 3 Change in production of the automotive industry in CEE countries, 2007–2010 % 150 100 50 2010 III. n.é. 2010 II. n.é. 2010 I n.év 2009 IV. n.é. 2009 III. n.é. 2009 II. n.é. 2009 I n.év 2008 IV. n.é. 2008 III. n.é. 2008 II. n.é. -50 2008 I n.év 0 -100 Germany Slovenia Czech Republic Hungary Poland Austria Slovakia CEE Romania n.é. = quarter * Data pertaining only to ACEA members (figures for 2010 are estimated only). Source: Calculated by Szabolcs Szabó on the basis of ACEA data. TABLE 4 Change in the number of vehicles produced during the crisis in CEE Country Variation in the number of vehicles produced (%) 2008 vs. 2007 Germany Czech Republic Poland Slovakia Romania Slovenia Hungary Austria Serbia 97 101 119 101 101 100 118 66 117 Source: Own calculation based on OICA figures. 2009 vs. 2008 86 104 92 80 121 108 62 48 144 2010 vs. 2009 113 110 99 121 118 99 159 55 79 42 Györgyi Barta FIGURE 4 Change in the number of cars registered in CEE countries between 1990 and 2010 (Previous year = 100%) % 30 20 10 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 -10 1991 0 -20 -30 -40 -50 -60 -70 00 Germany Germany Slovenia Czech Republic Hungary Poland Romania Austria Slovakia CEE Austria Romania CEE Source: Calculated by Szabolcs Szabó based on data of ACEA. Annually, 16.7–17.7 million vehicles were sold in the EU between 1998 and 2008. In January 2009, this figure decreased by 3.5 million. In the first quarter of 2009, the number of new automobiles registered declined by 35.6% – compared to the previous year: minus 31.1% in Western Europe and minus 48.7% in the new EU member states (Jürgens–Krzywdzinski 2009). Approximately 5000 European suppliers also experienced difficulties. Demand dropped by half, and a sizeable number of SMEs went bankrupt. However, the success of the crisis-mitigating strategy is owed mostly to changes in employment during the years of recession. In the aggregate the impact of the recession on employment was also extremely high, but we still do not have a comprehensive view. Approximately 10% of the 12 million jobs were lost in the European automotive industry in 2009, which struck Germany most (until the middle of 2009, some 50,000 jobs at the manufacturers and 20,000 jobs at suppliers disappeared). (6) Employment in Slovakian, Polish and Romanian automotive companies dropped in absolute figures as well, while in other countries it was stagnant or employment rose only at a low pace. (It should be noted here that regarding this issue the available data are either deficient or unreliable.) (Figure 5). Central and Eastern European Automotive Industry in European Context 43 FIGURE 5 Changes in employment in CEE countries between 2002 and 2010 % 25 20 15 10 5 2010 2009 2008 2007 2006 2005 2004 2003 -5 2002 0 -10 -15 -20 Germany Romania Czech Republic Slovenia Poland Hungary Slovakia Austria Source: Calculated by Szabolcs Szabó based on data of ACEA. At the end of 2009 and at the beginning of 2010, Europe seemed to have started to recover from the global financial and economic crisis, but currently “clouds of another crisis” are gathering over Europe. The effect of the recession varies, and prospects for revival and growth differ in each country. Prior to the economic and financial crisis, the increase in Germany’s and Sweden’s exports has driven economic growth. The Central European countries were able to turn the opportunities inherent in the export of cheap commodities to their advantage, while other countries, such as Italy and France could demonstrate a certain economic growth deriving from an increase in domestic consumption; Great Britain intensified its financial activities, and Spain raised its investments in the construction industry. Financial and wage deregulation in European countries also fostered growth; however, the gaps in incomes became even wider, especially in England, Portugal, Spain and Greece. These processes were just the opposite in the Scandinavian countries, in Germany and in France. At the onset of the recession, the exporting countries were those who suffered most. Afterwards it hit those countries where domestic consumption used to be the driving force of economic growth. At that time, however, the exporting countries’ situation (Sweden, Germany) already started to improve. For most European countries – with the exception of Germany and Switzerland – the recession was far from coming to an end, and it is also difficult to predict how European markets or consumption will develop in the coming years. 44 Györgyi Barta It is worth dwelling on the crisis-mitigating strategies of some European countries (EU), of the governments (of major automobile manufacturing countries) and of companies that proved to be successful and enriched the CEE region with some useful experience. Corporate and governmental interventions and their effects during the crisis According to automobile manufacturers the decrease in the sale of vehicles had less adverse effects on how they formed their strategies than the freezing of bank loans. Automobile factories reduced production and they sold their stock of vehicles already produced. Hiring was suspended; permanent staff was put in a “parking” status temporarily; the contracts of temporary employees were not renewed, and production plans were rescheduled. The strategy was to decrease production to a level which is sustainable without bank loans. It is deemed to be a great achievement that no car factory was closed down until the summer of 2010 (with the exception of a Fiat factory in Sicily, when assembly of the Panda model was relocated to Poland). In France, PSA and Renault survived due to state subsidies. (It was before the crisis that a VW factory was closed down in Belgium, and PSA shut down a plant in Great Britain.) Even American parts manufacturers provided support to allow for as few factories be shut down in Europe as possible, in order to preserve their export markets in Europe. Ford closed down one factory in Bordeaux, and Land Rover and Jaguar were sold well before the outbreak of the crisis to Indian Tata, and Volvo was sold to China. Before the crisis set in it was already doubtful if Opel/Vauxhall could survive. GM intended to sell those factories (which it did not allow to export to markets it wanted to export its American products to). Thus Opel could not benefit from the export successes its German competitors achieved in Asia. All in all, the European automobile manufacturers managed to adapt to the crisis, there was hardly any plant closed and even the rate of dismissals was relatively low. They managed to quickly implement temporary solutions (flexible work-time introduced during the past decade and annual scheduling of work-time were perfectly utilised: days and holidays were given off adjusted to production needs, or even paid in cash, the overtime was either prolonged or shortened according to necessities). Automobile manufacturers managed to pull through the period of recession much better than their suppliers or subcontractors. The suppliers’ situation was made even more difficult by delayed payments by the automobile manufacturers. To counterbalance this, the governments endeavoured to provide assistance to the SME sector by encouraging banks to lend money. Nevertheless, these measures did not prove to be sufficient. Governments and the EU had to take some action as well. This happened on three fields: − Banks lent loans again to enable continuation of production and development projects, but they promoted only the production of environmentally friendly cars; − Sales of less polluting premium-category cars were also promoted in countries where such cars were produced; Central and Eastern European Automotive Industry in European Context 45 − Governments supported partial financing of wages of workers temporarily sent on mandatory vacation. Although similar actions and measures were taken by the governments of various countries, they failed to harmonise them. Germany and France took the necessary steps at the very beginning of the crisis and made efforts to provide assistance to the extent needed and possible. Italy first refused to support an allowance or premium for purchasing new cars (“scrappage allowance”), but later it became inclined to do so. Great Britain and Spain, perceiving the impending collapse of the market, started their scrappage allowances at the very moment when it was terminated in Germany and France. State support for buying new cars had such a great influence in Germany and France that sales increased even during the years of recession. State subsidy also had an influence on the customer choice of cars purchased: In 2009 the proportional rate of small passenger cars increased, while sales of luxury cars, four-wheel-drive cars and vans decreased. This also had a significant effect on automobile manufacturing. Hyundai-Kia and Fiat benefited from their cheaper car production in the CEE. In Germany, state subsidies were available for purchasing of premium cars as well. Accordingly, governments have become important players within the automotive market again, although this role had never ceased before, either. Governments – even those that earlier benefited especially from the free market – expressly expected the manufacturing companies to maintain actual employment levels and production sites in return for government subsidies. Moreover, in some countries it was an explicit demand that production plans of companies had to be redrawn. All of this basically breached EU regulations. It is attributable to the application of those sales promoting premiums in the European countries, as well as to the fact that only few countries turned towards the “new economy”, that European markets survived the recession in a better shape than that of North-America. Further opportunities for recovering from the crisis, new short term directions of development Efforts of automobile factories Further opportunities remained, of course, for those who were able to survive the crisis. Automobile manufacturers are interested in various directions of development: They try to improve their competitiveness, they consider the merger with companies in trouble, they forge strategic alliances, they try to achieve larger shares in prospering markets, and they launch new products to meet new demand while (slowly) decreasing the emission of pollutants (Freyssenet 2010). Cost reduction: − The ratio of social security contributions was cut back in Germany and France. Germany introduced a “social” VAT (basically a VAT increase), which meant that social contributions were partly passed from employers to consumers. Ger- 46 Györgyi Barta man products became more competitive this way, and imported goods became less competitive on the German market. − French automobile manufacturers were successful in convincing the government to reducing the tax on industrial activities. − A bill on a carbon tax – which had already been introduced in many European countries – was not passed in Sweden. France, having been the leader in the combat against climate change, eventually gave up imposing the tax as well. − The EU levied a tax on the import of second-hand cars. Structural changes: − The bankruptcy of an automobile manufacturer opens opportunities for others. Fiat acquired parts of Chrysler, GM sold Saab (which recently went bankrupt), and Ford sold Volvo. The government of the United States bailed out GM, thus it managed to sustain Opel/Vauxhall for the time being. − European manufacturers forged new alliances and joint ventures with Japanese, American, Indian and Chinese automobile companies. VW acquired a share of 20% in Suzuki/Maruti. Fiat acquired 35% of Chrysler. Renault-Nissan reinforced the capital relationships with Daimler. Renault is extending its business in India (Ssang Yong). PSA concluded contracts with Mitsubishi and Chinese companies (Dongfeng, Changan). Seeking New Markets: − European automobile manufacturers were seeking to expand in the markets of the emerging and developing economies. VW extended on the markets of: Brazil, China, Russia, India; PSA is present in Brazil and China, but it does not have an important role anywhere. At the same time it appeared on the Russian market and in India with Mitsubishi. Renault was unable to reinforce its situation in Brazil. Korean Samsung could get a foothold in the Chinese market, but its expansion in India remained uncertain. Fiat is present in Brazil, but it was unable to get into either the Indian or the Chinese markets. It is trying to expand in Russia, too. CEE – as a consumer market – is less significant, but for large automobile manufacturers it is not negligible. Technological development: − Automobiles are required to produce less CO2 emission: Fiat is developing cars driven by gas and agro-fuels (e.g. biomass), but it deals less with electric cars. Progressive programmes are seen at VW, PSA, Daimler and BMW: First petrol driven engines are being optimised, hybrid cars are being introduced, and at a later stage, electric cars followed by fuel cell cars. In their opinion, electric cars will remain a marginal solution even after a relatively long period of time. Nevertheless they do not cancel the introduction of electric cars from their agenda. Central and Eastern European Automotive Industry in European Context 47 Governmental interventions Setting up Clusters: − Cooperation between small and medium sized enterprises and R&D institutes must be developed systematically, and cluster-based innovation centres are to be established. Local and regional R&D infrastructures must be reorganised and enlarged. Technical research and education in automotive engineering are scattered among locations and various players and they are not well integrated. Everywhere, a regional academic base (universities, research institutes) is indispensable for the setting up of clusters. Local R&D activities are themselves attractive for other investments or projects. For regional clusters the goal is to establish relationships between diverse competencies and technologies in the hightech sectors (IT, communications, software development, space research, chemical industry), and to set up competence and vocational or professional education centres (Blöcker et al. 2009). Requirements for a qualified labour force: − Research carried out in the West-European automotive industry has found that there is a lack of experts in the fields of electronics, accumulator technology, new electronic systems, integrated technical development, quality management, management, business development and financial innovation management. − There are debates whether a considerable shift will take place in the automotive industry from the need for highly qualified labour towards less qualified; or if it will be just the opposite, and the proportion of qualified employees will increase in this sector in the future. According to a survey, the following opinions were predominant: • Cheap labour will be less important in the automotive industry; • Qualified labour will remain the determining human resource in the future; • Standardised work processes will be enhanced; • The need for up-to-date technical knowledge will increase; the life cycle of knowledge will be shortened; • Profound technical knowledge and practical skills will remain important in the future; • Furthermore, it will be important to acquire skills and knowledge of more than one profession, i.e. the need for multidisciplinarity will increase; • Managerial and organisational skills will become more important; • Labour mobility and the need for flexibility will increase; • Access to professional qualifications will be widened; • Vocational training will increasingly take place outside the company. National R&D policies related to the European automotive industry: − European governments follow different strategies. In Sweden, experiments are carried out with cars driven by agro-fuels, in Italy gas driven cars (CNG and LPG) have long been a choice. R&D subsidies provided by the governments in 48 Györgyi Barta France, Great Britain, Spain, Portugal, Denmark, Ireland and Switzerland are focused on electric cars. Germany adopted “technical neutrality”. It is generally accepted that CO2 emission is to be decreased, and consumers should be allowed the chance to choose. However, every strategy can be countered by soaring mineral oil prices (which would foster the market chances of hybrid cars). It is also commonly known that the ever increasing number of cars in the emerging countries with large populations, especially China and India, will eventually not find enough mineral oil supplies to drive them. This, and air pollution, is why China is especially interested in the manufacturing of electric cars. Although in some years, the recession will probably be considered merely a historical episode it is likely that we are approaching another “car revolution”. Electric cars do not only represent a different type of motorisation, but a new kind car construction as well; it may entail a radical reformation and simplification of design, production and distribution – once the problem of energy storage is solved in a more satisfying manner. The social background, geographical location and economic capacities of the global automotive industry are not synchronised with the development of new markets and new manufacturing countries. New cars will probably not be petrol driven, and the inhabitants of large, emerging countries will not merely be consumers, and users of the new cars but they will be involved in their production as well. A new competitive situation is about to evolve in the automotive industry. The recession is not over yet, but competition for the markets of the future is already in full swing. The future: We have come to a junction Two different scenarios have been created for the future of the automotive industry until 2025: one is the green revolution and the other one is the revolution of mobility (Diez– Becker 2010). Green revolution To achieve the target of reducing CO2 emission experiments are being carried out with bio-fuels, hybrid cars, electric cars and hydrogen fuels. Current results are not yet suitable to base manufacturing in commercial volumes on. Probably, hybrid technology will play a major role. Electric cars are expected to be sold in larger quantities from around 2020, and perhaps by 2030 these will be the cheapest, provided the accumulator technology achieves a breakthrough. Biomass and waste as fuel will also play an important role (second generation bio-fuel). Hydrogen is expected to be the fuel leading to electric cars (via fuel-cells), which will become essential in the period between 2030 and 2050, and although by 2050 electric cars will dominate the market, heavy vehicles will still consume liquid fuels. Obviously, an exact concept has yet to be found concerning the dominant technologies of the future. A new social value has appeared in politics which has become increasingly open for the concept of innovative and alternative mobility. “Green revolution” refers to the fact Central and Eastern European Automotive Industry in European Context 49 that an increasing political pressure has urged the introduction of environmentally friendly cars. Accordingly, they are politicians who insist on accelerating a “green technological development”, a significant decrease in CO2 emission of cars, while threatening the manufacturers with punitive action if they fail to make all reasonable efforts to achieve such targets. The technology of electric drives will probably play a major role in this. If this path of development is chosen, the European automotive industry will need 10 to 15 years to introduce advanced “green technologies”. The automotive industry will have to make considerable financial investments in R&D in order to adapt production concepts and restructure value chains. Financing the implementation of new technologies will probably be a bottleneck for some companies. As a consequence, access to the necessary funding will be a selective factor regarding the survival of some automobile manufacturers. Consolidation will be low, whereas new competitors can be expected to enter the marketplace. For some European automobile manufacturers there will be fundamental financial problems to cope with. If the scenario of the “green revolution” will come true it will entirely restructure European automobile manufacturing in the future. “Mobility revolution” In this scenario the main impetus comes from the consumer. This version is based on the assumption that the majority of drivers will not own cars in the future, but will participate in car pools or car sharing and use cars only temporarily when they need them. Besides the ecological aspects, financial considerations will be more important as buying and running a car is becoming increasingly expensive. This is already a trend, accelerated by growing urbanisation which makes the use of one’s own car more and more complicated. Cities with very advanced public transport systems (or alternative vehicles such as electric bicycles) facilitate individual mobility without the use of cars. Another, perhaps smaller segment of mobility will still rely on using cars or other means of transport, such as trains or aeroplanes. According to this scenario, the automotive industry would be perfectly restructured. Until now automobile manufacturers used to be system leaders in the automotive industrial value chain, but they would lose this role to mobility providers who would, in turn, establish contact with the consumers directly. Market acquisition potential would no longer be associated with car brands, but with mobility brands. To sum it up: The automotive industry has come close to a turning point. The question is who will survive? Who will sustain itself until the next development stage in this industrial sector? The European automotive industry – its scale, productivity and brand portfolio as well as the ownership structure – is extremely heterogeneous. This heterogeneity challenges the long term survival of European automobile manufacturing. Each manufacturer is to seek and find the answers itself as to what product to manufacture and what services to render in order that its position be competitive in the future. What sources 50 Györgyi Barta can they use and how will they be able to restructure the manufacturing value chain efficiently? A business model sustainable in the long run is what is to be formulated and implemented. In the case of the “green revolution”, this model is relatively simple: It “merely” means to further improve the current business model. The product, i.e. the car, is in its focus, which will reach the customer through the standard sales channels and which will perhaps be produced in altered structures of the value chain. The vision of the other scenario – “Mobility Revolution” – entails a total reformation. Until now, it was the automotive industry that took the role of the developer and the manufacturer as well; with the “mobility revolution”, however, the leading positions in the value chain will be taken over by service-providing companies. But: Is there sufficient inner potential for such a transformation within the automotive industry? Or will new service providers be sought outside this industrial sector? Central and Eastern European region Who are the competitors? This study discusses issues related to the Central and Eastern European automobile manufacturing – in a European context. It fits the research project to analyse the role of the automotive industry in the Northern Transdanubian region of Hungary. The common base to approaching this topic, and the difference at the same time, is that the status and effects of the automotive industry are examined at different territorial levels. However, the question is: Is this “territorial” base relevant? The automotive industry is a strongly integrated sector involving a complex chain of global “Tier 1” subcontractors and finishing brand producers (OEM). Such companies are the leaders of the automotive industrial value chain. Obviously, the development of the sector highly depends on the short and long term strategies and decisions of such companies. The interesting question is: What are the effects of company-level decisions at the various territorial and regional levels? It makes sense and it is relevant to survey the automotive industry at diverse territorial or regional levels, but this cannot be separated from the aspect of how a particular company is related to a country or region: i.e. it is important to know where the headquarters of the company is; which nation the owner belongs to; and which activity of the company or element of the value chain is settled in or relocated to a particular country or region. Obviously these aspects determine the perceptible or measurable effects in a particular region. If we select any territorial level as the target of our analysis, the global relationships of the companies operating in a particular region must not be neglected either. Many different answers may be given to the question – who are the competitors? – posed in the subtitle. In principle, the large automobile manufacturing companies compete with one another, but also countries are in competition with one another – mobi- Central and Eastern European Automotive Industry in European Context 51 lising their own resources – to attract or anchor some segment of the automotive industry within their borders. Even regions smaller or larger than a country compete for investors, due to the European Union regional policy. Every territorial level has different opportunities and tools to further their interests; and, of course, the impact of the automotive industry operating in a particular region will be different according to the developmental level of that particular region. In this section the automotive industry of the Central and Eastern European region is examined at different levels: globally and in Europe, focusing on the group of Central and Eastern European countries. The European regions are presented as they evolved in terms of the development of the automotive industry. This is not intended as a comprehensive and detailed statistical description. But the typical problems and correlations related to individual regional levels are highlighted: mainly centre-periphery correlations between Western and Eastern Europe; the competition among the CEE countries for direct foreign investments, and the impact of the already existing automotive industry on the countries examined. The chapter begins with a brief presentation of automobile factories, mainly European car factories, but disregarding individual corporate problems and issues as they would be beyond the scope of this study. Global players are changing: Automotive industrial companies in the world and in Europe The prediction made at the beginning of the 1990s, according to which the number of automobile manufacturers will decrease significantly (maybe 6 will remain all over the world) – has not yet come true. At present more than 100 legally and financially independent companies are engaged in car manufacturing throughout the world. Deducting small-series manufacturers (below 1000 cars/year), there are still 60 to 70 companies. The number of integrated automobile manufacturers is approximately 32, of which the 13 largest can be considered global companies, and 8 companies are partially global, while 9 are engaged primarily on national markets (Tables 5 and 6). A low level of globalisation, high production and sales revenues characterise large countries such as Russia, India and China; while a high level of globalisation coupled with high production and sales revenues characterise the following automobile manufacturers (alphabetically): BMW, Daimler, Fiat/Chrysler, Ford, Fuji (Subaru), GM, Honda, Hyundai, Mitsubishi, PSA, Renault-Nissan, Toyota, VW. The number of European automobile companies has decreased significantly over the last sixty years: In the 1950s there were still 70 vehicle manufacturing companies and brands of which altogether 6 were left by the year 2008. This dramatic consolidation occurred in the 1970–1980s, and it was not a result of globalisation. In the consolidation of the European automotive industry general and specific features are mixed in each country: 52 Györgyi Barta TABLE 5 Ranking of companies that produced over one million automotive vehicles in 2008 Ranking Corporate Group 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Total Toyota General Motors VW Ford Honda Nissan PSA Hyundai Suzuki Fiat Renault Daimler Chrysler BMW Kia Mazda Mitsubishi Number of vehicles 9,237,780 8,282,803 6,437,414 5,407,000 3,912,300 3,395,065 3,325,407 2,777,137 2,623,567 2,524,325 2,417,351 2,174,299 1,893,068 1,439,918 1,395,324 1,349,274 1,309,231 69,561,356 Source: OICA (2009). In: Diez–Becker (2010, 14; fig. 4). TABLE 6 Consolidation of German, French, British and Italian automotive industry: changing numbers of independent manufacturers Period Germany France Great Britain Italy 1950–1960 1970 1980 1990 2000 2008 Independent vehicle manufacturing companies in 2008 11 10 5 5 5 3 BMW Daimler VW 20 5 3 2 2 2 PSA Renault 20 6 4 1 0 0 19 6 3 2 1 1 Fiat Source: OICA (2009). In: Diez–Becker (2010, 17; fig. 6). Central and Eastern European Automotive Industry in European Context 53 − In Germany, all non-military industry was almost totally destroyed at the end of World War II; due to low income levels, the manufacturing of small cars became essential in the 1950s, and the disciplining force of a liberal economic policy became noticeable. − French automobile manufacturing was characterised earlier by a relatively high demand for luxury cars. After World War II, adaptation caused difficulties to many automobile manufacturers, and eventually led to several close-downs. Unlike most of the German automotive companies, the French government’s participation in their automotive industry was always significant, and it hampered the adaptation to market requirements. However, French vehicle companies have always been willing to cooperate with other – even non-European vehicle companies (Toyota, Nissan, SsangYong, AvtoVAZ). − The disappearance of British automotive companies was linked to the economic policy in Great Britain. Deindustrialisation was the most intensive in this European country. The automotive industry shrank significantly, which was partly attributable to the trade unions which firmly resisted the often painful structural reforms. The changes in economic policy implemented in the 1980s came too late, and as a consequence, an independent British automobile industry practically ceased to exist. − Fiat was so firmly locked into the Italian market that it made entering of other vehicle manufacturers close to impossible, unless they were able to target some gaps (luxury cars, sports cars, etc.). The Fiat company was further strengthened by governmental interventions, too, for instance in subsidies for underdeveloped Italian regions. This prevented, for example, the break-through of Japanese cars on this market until the 1990s. In the year 2000, GM acquired a share of 10% in Fiat. Globalisation weakened the position of Fiat, especially on the global market. The proportional share of the largest automotive OEMs in 2006 on the basis of the number of vehicles produced was the following: GM 13.1%, Toyota 11.8%, Ford 9.2%, Renault-Nissan 8.4%, VW Group 8.3%, Daimler/Chrysler 6.7%, Hyundai-Kia 5.6%, Honda 5.4%, PSA 4.9%, Fiat 3.4% (Source: Companies’ annual reports (OICA). In: Halesiak et al. (2007, 7; fig. 2). Major problems of automobile manufacturing companies included – before the recession – increasing production costs (global price war, increasing oil prices, higher R&D expenses) and decreasing profitability (decreasing attractiveness for investors, especially in the USA). Some automobile concerns reacted to market changes with restructuring even before the recession: − As of the 1980s, the automobile manufacturers made attempts to reduce risks, or share costs by mergers, strategic alliances, and the establishment of joint ventures. 54 Györgyi Barta − Brand automobile manufacturers (OEM) paid higher attention to market strategies, which extended to passing over part of costs to the suppliers. By this a more transparent and simpler production organisation was set up and they managed to even cut costs. − Until 2005 and in this restructuring process, Japan led the automotive industry. Their role was imitated both in the American and in the West-European markets. Their success was built upon perfectly organised production processes, on clear production positions and better understanding of economic tendencies. − At that time, automobile manufacturing in the United States of America had to cope with difficulties: due to the fact that the domestic market was cyclic, they lost market shares to Japan, and mainly because it was inflexible (they insisted on cars with high fuel consumption). In addition, the finish of American cars was below Japanese and European. − Although Europeans and Americans partially walked in similar shoes, the former showed a somewhat better performance than the Americans. Many players are present on the European automotive market which means advantages and disadvantages alike. They had to achieve considerable cost reduction which led to relocation. The winner of this process was unequivocally the CEE region. Correlations between West and Central Eastern Europe – centre-periphery relationships in the automotive industry Normally two statements are conceptualised referring to centre-periphery correlations: − This is a system of relationships, since it is impossible to consider the centre without speaking about the periphery as well. And then again, it is the special relationship with the core region, i.e. the centre, which actually makes a region the periphery. The centre predominates in this relationship, taking mainly advantages of, and benefits from, the periphery. Decision making – which affects the situation of, and the potentials for, development in the periphery – takes place at the centre. To emphasise this correlation is essential as it often occurs that a periphery is taken out of this context and dealt with individually. For the purpose of this study we attempt to examine the situation and problems of both poles with special regard to the European automotive industry. A rarely posed question also emerged: Does the improvement of the situation in the periphery have negative effects on the centre (Domanski–Lung 2009; Diez–Becker 2010; Özatagan 2011)? − When examining a short period of a centre-periphery system it might appear to be stable, and it rarely occurs that the centre becomes periphery, and vice versa. However, studying some past decades in the history of the automotive industry provides evidence that there have been such changes. In certain countries, some regions have drifted to the periphery of a core territory, while a periphery also has had certain zones being nearer to, or farther form, the centre, and even Central and Eastern European Automotive Industry in European Context 55 between these zones there have been movements. It must be underscored that even in the case of a positive shift, a centre will always be sharply differentiated from the periphery. As a consequence, the factors determining and separating the poles will generally remain quite stable. A periphery situation is a condition (e.g. the CEE region, Hungary’s situation within the automotive industry), which will always remain obvious. Features of a division of labour First of all, it must be mentioned that Germany is part of the core territory of the automotive industry in Europe, while the periphery includes Central and Eastern European, formerly socialist countries, and some studies list here Russia and Turkey as well (and in both countries the role of the automotive industry is important, too). The core territory is within the area of the EU15, but, basically, it is composed of only four countries, namely Germany, France, Italy and England that have had a traditional automotive industry. In the 1970–1980s, Spain used to be the largest country at Europe’s periphery. At the same time, the United Kingdom suffered significant losses of its former position. Today it does not own any major car brand. A new division of labour has been established in Europe, including companies that relocated to Central and Eastern Europe. In the European automotive industry, the CEE regions form the European periphery, which has had a significant role in parts production and will have a not so insignificant role in. Although some of the former socialist countries had their own automotive industry, the progress following the change of the political system has been associated with remarkable foreign direct investment (FDI) in this sector. The majority of such investments were of the green-field type, but through privatisation and, subsequently, the acquisition of inherited socialist automobile factories, or other companies, they were also linked to brown-field investments. Two main reasons led to the fact that the foreign capital investment directed to the automotive industry selected these countries: It was seeking new markets for its products as well as cheap production conditions. Not only lower wages, but also the quality, the reliability and geographical closeness of a workforce were important aspects in the selection of new production sites (Figure 6). The automotive industry of the European periphery is not a homogeneous one. Four groups of countries can be distinguished in accordance with the extent of integration associated with the European core territory (more precisely the links to the EU), the features of automotive industrial ownership and the position taken in the division of labour: − Central-European EU member states: Poland, the Czech Republic, Slovakia, Hungary, Slovenia; − Romania and Bulgaria – as countries involved in the accession at a later date; − Turkey, which concluded a treaty on free trade with the EU in the hope of accession at a later date; 56 Györgyi Barta − Ukraine and Russia, which currently have more links to the Russian core territory, but hope to establish closer relationships with the EU. This latter prospect actually applies more to Croatia and Serbia (Halesiak et al. 2007). FIGURE 6 Comparative advantages of the CEE countries in the automotive industrial sector Central Europe South Eastern Europe Source: Own calculations based on Halesiak et al. (2007, 16; fig. 18). Central and Eastern European Automotive Industry in European Context 57 The countries of Central and Eastern Europe (Poland, The Czech Republic, Slovakia, Hungary and Slovenia) are considered as being strongly integrated peripheral markets (their situation is comparable to that of Mexico in NAFTA). The Central and Eastern European (CEE) peripheral regions include Romania and Bulgaria, as well as the potential future EU members, Croatia and Serbia. In the automotive industry of the CEE region, a slow embedding of foreign companies has taken place; the production strategies of the investing transnational automotive companies facilitate gradual growing of added value in this region, and also R&D institutes have appeared – preferring development to research, however. At the same time it is typical for the automotive industry of this region that labour intensive activities with low added value are performed by low-wage labour. In the manufacturing value chain the automotive industry of the CEE has focused on assembling macro components (modules), and on the production of low cost generic components meant for export. In the course of increasing production, a higher rate of specialisation has evolved, nevertheless the centre-periphery relationship has remained stable, i. e. the peripheral situation of the CEE remains unchanged. Low-cost work model In 1992, Pyke and Sengenberger formulated the theory of “high-road – low road” (Pyke–Sengenberger 1992) which depicts the two forms of development experienced by industrial districts in global competition. Low-road can be interpreted as a wagereducing solution as it is seeking low-wage labour and a deregulated labour market. While the high-road model, which can be referred to as a quality-work model, is based on the improvement of effectiveness and on innovation. This, however, results in a rising wage level, the improvement of social conditions and a better protection of workers’ rights. These industry sociologists put quality production in focus as the fundamental element of industrial restructuring. The quality work model is based on institutionalised interest representation, the sustainment of high-standard employment and wage level, an inner flexibility of a corporate organisation (this also applies to work organisation) and a long term investment in vocational education. While in the low-wage work model the workers’ interest representation is weak, the privileges of the employer are strong. It is a general practice that the labour force is employed for a short term, temporarily, or provisionally, and in this employment system high fluctuation is typical, the labour market is uncertain, the market pressure on employment is high, the wages are low and finally the company’s interest in the vocational training and the development of competencies of its employees is minimal. The quality work model encourages long term investment in vocational training, and the enhancement of competencies, which are preconditions to the security of employment. This entails high inner flexibility as well. The strategy of cheap work is based on low labour costs and semi-skilled work. Semi-skilled workers’ low wages are only sustainable under the conditions of harsh competition on the labour market. Flexibility can 58 Györgyi Barta be achieved by changing the staff number as seen necessary (dismissal, temporary work, occasional work). Basically, the two types of work models in the centre and the periphery of the automotive industry move the development in Europe in this field. Closing up and relocation The development of the automotive industry in the CEE commenced at the beginning of the 1990s and it is still in progress. First, the Western investors acquired a sequence of post-socialist companies (VW in the Czech Republic, in Slovakia and Poland; Fiat in Poland; Renault in Slovenia). Afterwards these companies were transformed into not much more than suppliers. Initially they produced only for the CEE markets. When cost-cutting became inevitable due to the keen competition between West-European vehicle manufacturers, the focus was mostly directed at CEE locations. VW and Fiat modernised their plants in the CEE, with the intention of manufacturing products for West-European markets. VW, GM and Toyota started parts production in the CEE (chiefly engines and gear-boxes). Qualified, but still cheap labour, governmental incentives for investments (special economic zones, tax allowances) attracted more and more investments to this region. In the first years of the new millennium, a new wave of automotive investments – mainly Korean and French – began, which in turn led to an increasing investment by suppliers. General tendencies in the development of CEE plants were: First older models were manufactured, or partially or completely assembled there. As of the second half of the 1990s, some progress was made: With the modernisation of technologies at affiliate companies and divisions (Škoda in Bohemia, VW in Poznan), and by adopting standardised systems, the competencies of the CEE plants were extended (with technical process functions, logistics and sales). The product range also expanded: besides small cars also the bigger models appeared, i. e. the compact and premium category. Moreover, aggregates with high added value were produced (such as engines), and even exports to the West grew (over 90% of the manufactured vehicles were exported, mainly to Western Europe, at the end of the 1990s). For the CEE countries, relocation has been a positive process because it helped catching up technologically with Western Europe. Improvements in the quality of products as well as the enhancement of competencies have been highly appreciated benefits. Nevertheless, the process of catching up remains restricted, as the automotive industry in CEE is still characterised by labour-intensive production which does not require a high technological level. On the one hand, R&D and design remained in most cases at the headquarters of the automotive manufacturers (with the exceptions of Škoda VW and Renault Dacia). On the other hand, threatening competitors of the CEE region, that is countries farther to the East (Russia, Ukraine, and especially Asian countries), have strengthened, although the impetus to relocate plants from the CEE region farther to the East was weak for automotive companies. Investments in China have not weakened the automotive industry of the CEE. Nevertheless the advantage of CEE is Central and Eastern European Automotive Industry in European Context 59 decreasing continuously as a consequence of increasing wage levels (German investors have already complained about this trend in Poland, and they are said to be favouring more and more the Ukraine and China). After 2005, the increasing lack of qualified labour in the CEE region squeezed the labour market, and wages began to rise. Between 1995 and 2006 the hourly wages in euro doubled, although the wages in Romania were 8%, and the wages in The Czech Republic were 19% of the wages paid in Germany. In 2004, with the accession to the EU and with increasing FDI, the migration of labour was facilitated. This exerted some pressure on companies. In 2006 and in 2007, workers went on strike in VW, MAN, Toyota and GM factories in Poland demanding higher pay and better working conditions. Similar actions took place at VW Škoda in Prague, or at Dacia in Romania and at Suzuki in Hungary. No matter what progress the automotive industry in the CEE region makes, the competencies regarding innovation and decision making will remain in the hands of the core territories. At the same time this suggests that the current localisation of creativity, knowledge accumulation and decision making and dependent situation of the peripheral regions will remain unchanged. As a consequence, what is now periphery will remain periphery. It is not impossible, however, that a country will turn from periphery into a core territory, and that a country will disappear from the periphery and will be replaced by another peripheral country. An important issue regarding the development of CEE is whether Western Europe will transfer the model of quality work to CEE. Some case studies suggest that although certain elements (qualification structure, work organisation, work time organisation) are taken by foreign investors to CEE, the work model established differs from the domestic one, primarily in terms of the partnership approach between management and employees. Obviously, it is impossible to introduce the same work model to a recipient country 1:1 owing to the recipient country’s different social/economic environment. Therefore hybrid models are developed. It is also true that escaping from domestic constraints is an explicit aim of investors. In relation to foreign direct investment, or relocation, three essential effects are to be examined: What is the situation with workplace security, vocational training and the employees’ interest representation at automotive companies with foreign owners in the CEE region? The quality work model focuses on workplace security and has already appeared in some CEE companies when, for instance, at the time of recession the majority of qualified labour was not dismissed by companies. This situation was made, however, more difficult to handle by the increasing shortage of skilled labour. It must be noted here, however, that the group of qualified labour composes a minority. Uncertainty of employment is more typical for the majority of semi-skilled workers (on probation, and workers employed temporarily to satisfy increased production needs) than in Western Europe (in many West European automotive factories, temporary or provisional employment is much more restricted). 60 Györgyi Barta The other important issue is vocational training, because it is a long term investment that helps employees keep their jobs, at least with many companies. In a low-cost work model neither the employer nor the employee are interested in investing in vocational training. The question is: What is the situation in CEE when it comes to vocational training? Due to the collapse of the socialist vocational training system, in CEE professional or vocational education is still insufficient. It is somewhat compensated by the training organised at subsidiaries of multinational companies, or by the participation of affiliate companies in external professional education (e.g. at a university). Of course, there exist state education systems in CEE as well. A certain duality has developed in this respect, i. e. state and corporate education or training facilities. These are some examples: Bosch in the Czech Republic, FSO in Warsaw and Fiat in Tychy are involved in local professional or vocational training. There are two cases in Hungary: Audi in Győr and Bosch in Miskolc. These companies opened departments at the local universities. In the Czech Republic an agreement has been made between the German and the Czech Chambers of Industry for the purpose of promoting and supporting the local vocational and professional training). The general opinion is that professional or vocational training is still an unresolved issue in CEE, especially since foreign corporations require more skilled labour. In Hungary, a lack of qualified labour has become apparent well before the recession (Palkovics et al. 2009). The third aspect is the issue of labour representation. Although the socialist heritage is different in each country (for instance, in Poland trade unions were stronger than anywhere else), in general motivation to set up a trade union seems to be weak. Especially small and medium sized enterprises (SMEs) reject cooperation with trade unions. The relationship between large companies and trade unions is different. There are some examples of powerful representation of employees’ interests, for instance at Volvo, at VW or at German Mahle Group (a big automotive supplier). In other cases, following initial conflicts (Fiat, GM in Poland), cooperation between management and trade unions proceeded at a slow pace. With Japanese companies, the source of tension was originally the setting up of trade unions in the first place (Toyota in Poland, Suzuki in Hungary). However later, relationships normalised. In the case of brown-field investments, some trade unions were “inherited”, while in the case of green-field investments there were no trade unions at all at the beginning. With these newly incorporated companies, the establishment of trade unions and their functioning entailed many conflicts (Jürgens–Krzywdzinski 2009). Losses to the core territories? Relocations from Western Europe Disputes about the division of labour between the European west and east started at the beginning of the 1990s, due to relocations. Germany was criticised for letting its economy turn into a “bazar economy”, i. e. the economy dealt with the final manufacturing of products only, while the components were produced in low-wage countries. These criticisms were targeted principally at the automotive industry. It was not just about activities relocated to other countries, but also about the loss of competencies at Central and Eastern European Automotive Industry in European Context 61 the core regions. This was actually a minor problem in the case of big integrated vehicle manufacturers. It caused more problems at the suppliers’ side. As a result of this situation the proportion of labour costs compared to the aggregate costs declined considerably. As a consequence, relocation had become a determining competitive factor among large automotive companies. German automotive suppliers relocated 25–38% of their production abroad between 1997 and 2001, mainly to CEE and China, and not merely production but also an increasing proportion of technical services were also relocated. The change in the division of labour among European countries gave rise to hot debates in Western Europe, especially in Germany. As a result of these political debates, the EU Council of Ministers made the decision to cease promoting relocations in 2006. At the same time, detailed analyses – with the exception of some cases raising media attention – have stated that there was only a relatively small rate of shifting in the westeast division of labour, and its impact on employment in the West is hardly detectable. The question is whether the integration of the CEE region into the European automotive production network really “hollows out” the West-European automotive industry – regarding employment and the further development of the quality-work model. And: Does relocation and, in general, foreign direct investment in the western and eastern regions of Europe lead to a decrease of economic differences or will they increase the labour market competition? When examining the impact of relocation on the core countries and, in particular, on their labour markets, Germany should be separated from all other countries. The statistical figures clearly indicate that in Germany relocation did not hurt the domestic economy at all. The level of industrial employment in Germany did not decline in the 1990s. German automotive factories relocated those activities requiring low qualification mainly to low-wage countries, and, generally, the positive development of employment in the German automotive industry did not change. However, in other countries – in Portugal, Belgium, Great Britain – job losses due to relocation were significant. It has to be noted that those countries either do not belong to the core territory of European automobile manufacturing, or their development in the automotive industry made them lose their status of being central to the European automotive market, or their status was typical of peripheral countries to begin with. Obviously, the competition is not between Germany and the countries of the peripheral CEE region, but between the SouthEuropean peripheral countries and the CEE. In practice, South-European countries became losers of relocation – Portugal, Spain, Greece, or even the southern part of Italy. The considerable increase in the import volume of vehicles is another indicator of what impact relocation has had. It is undoubted that there was a certain increase in the import volume, but in the case of Germany it was not too significant compared to France or Italy. In the aggregate, German imports did not grow spectacularly, but the special structure of German imports did change: Import of parts from CEE grew considerably (between 1995 and 2005 from 9% to 37%), while the rate of automobile parts imported from Spain or Portugal dropped by half. This means that Germany – the 62 Györgyi Barta only country in Western Europe – fundamentally changed the territorial structure of production and imports – by involving the CEE region. There are several reasons why relocation did not affect the German automotive industry adversely. First, the economic situation in Germany improved from the middle of the year 2000 because very stringent market reforms were introduced. This reduced the political constraint associated with any relocation towards low-wage regions. But the economic situation may vary and it will. Second, Germany profited from its unrivalled premium-car brands. The premium product market is less price-sensitive and it supports the “Made in Germany” label. Third, the fact that Germany started from a leading position enhanced the advantage of German companies in CEE in the price competition compared to other West European countries. From the end of the 1990s, Japanese, Korean and French automobile manufacturers also appeared in the CEE region, probably diminishing the German advantage. However, German industrial strategic planning is second to none. The automotive industry of Central and Eastern European countries In 2007, 2.3 million persons were employed in the automotive industry, 80% of them worked in the EU15 countries, and 20% were employed in the new EU member states. Additionally, the number of people employed by automotive industrial suppliers and service providers in Europe was approximately 10 million. Severe structural problems emerged in the automotive industry in the first years of 2000: dropping sales, increasing material costs and R&D expenses and soaring oil prices. The automotive industry responded to these problems with overall restructuring: strategic partnerships were established, simpler – leaner – organisations were set up, higher pressure was exerted on suppliers and relocations towards regions with lower production costs were commenced. One of the main winners of this process was the Central and Eastern European (CEE) region. Investors were motivated by several main factors, when they chose the Central and Eastern European region for their investments: They sought a region with low manufacturing costs, as well as new markets for their products. In addition, they needed ample space for new top-of-the-art factories they couldn’t find in their home countries. Foreign direct investment was a key factor in the development of the automotive industry in CEE. Until 2006, FDI by the automotive industry was almost 17 thousand million euro. Until 2006, it was primarily Hungary, Poland and the Czech Republic where foreign investments flowed into the automotive industry, then Slovakia joint these three countries, and at present, it is virtually these four countries that have received 90% of all foreign automotive industrial investments in the CEE region (Table 7). Central and Eastern European Automotive Industry in European Context 63 TABLE 7 FDI in the automotive industry of CEE in 2006 (%) Country Romania Slovenia Hungary Poland Czech Republic Slovakia* Total Share of FDI 6.6 1.3 28.9 30.3 28.9 4.0 100.0 Note: Automotive industrial investments in Slovakia increased after 2006. Source: Halesiak et al. (2007, 23; fig. 21). The CEE region has attracted the largest global automobile manufacturers into these countries: − Poland: Fiat, VW, Opel, GM; MAN, Volvo, Scania – bus manufacturing; − The Czech Republic: VW/Škoda, Hyundai, Toyota, PSA; bus manufacturing: Iveco (Italian); − Slovakia: VW, Kia, PSA; − Hungary: VW-Audi, Suzuki (this was the first FDI in post-socialist countries); − Other Balkan countries: Renault (Romania). In the second stage, the ‘Tier 1’ foreign suppliers also settled in the CEE region, mostly in the Visegrád countries. The ten largest suppliers of the world that settled in the CEE (2005) were: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. Bosch (Germany) > Hungary, the Czech Republic, Poland, Romania, Slovakia; Denso (Japan) > Hungary, the Czech Republic, Poland; Delphi (USA) > Hungary, the Czech Republic, Poland, Slovakia; Johnson Controls (USA) > Hungary, the Czech Republic, Poland, Slovakia; Slovenia; Magna (Canada) > Slovakia, the Czech Republic, Poland; Aisin Seiki (Japan) > the Czech Republic; Lear (USA) > Hungary, the Czech Republic, Poland, Romania, Slovakia Visteon (USA) > Hungary, the Czech Republic, Poland, Slovakia; Faurecia (French) > the Czech Republic, Poland, Romania, Slovakia; TRW (USA) > the Czech Republic, Poland, Romania. (Source: Companies’ websites. UniCredit [2007]). In general, the EEC business environment was suitable for foreign investments. But although this region offered a great number of cheap and relatively well-qualified labour, productiveness lagged behind West-European averages (Table 8). Wage differences have decreased gradually between Western and Eastern Europe: Wages are rising fast in the CEE region (in 2007 the average wage level was 2.5 times 64 Györgyi Barta higher in the automotive industry than it was in the year 2000; that is 250%). This, however, had a bad impact on productivity figures, since the Western subsidiaries in CEE were not (allowed to be) innovative enough. The automotive industry is developing in the most dynamical way in Central and Eastern European countries; its share in the industrially added value grew from 5.8% to 7.3% between 2000 and 2005 (Figure 7). TABLE 8 Labour costs and productivity in the automotive industry in the Western and Eastern parts of Europe, in 2006 Country Work productivity (gross added value/number of employees) Hungary Poland Czech Republic Slovakia Bulgaria Romania Slovenia EU25 EU25=100 (EU15=106) EUR/employees Labour cost EUR / employees 75 61 69 69 34 37 82 100 37.2 22.8 23.2 20.3 5.6 7.2 23.4 58.0 13.8 9.5 10.5 10.1 3.7 4.8 15.8 45.0 Work productivity and wages (summarised) (%) 268.5 239.8 220.1 199.7 151.5 148.6 147.9 129.0 Source: Eurostat, UniCredit, New Europe Research Network. In: Halesiak et al. (2007, 28). % FIGURE 7 Development of the Central and Eastern European automotive industry, 2000–2005 Gross value added in Euro (at price rates of 2005) 14 12 10 8 6 4 2 0 2000 2001 2002 2003 2004 2005 Note: Share of automotive industry from the industrial added value: 5.8% (2000); 5.8% (2001); 6.3% (2002); 6.7% (2003); 7.1% (2004); 7.3% (2005). Source: Halesiak et al. (2007, 11; fig. 7). Central and Eastern European Automotive Industry in European Context 65 Some renowned automotive brands have established factories here during the past two decades, mainly as green-field investments. They are strategically located so that the majority were settled in a zone of 500 km from the boundary to Western Europe (Figure 8). This was done quite deliberately for several reasons (distance, infrastructure, existing affiliates and clusters). FIGURE 8 Location of vehicle assembly plants in CEE Poland Czech Republic Slovakia Hungary Slovenia Romania Croatia Serbia Bulgaria Foreign owners Local owners Source: Own calculations based on Halesiak et al. (2007, 5). It should be mentioned again that this region will become increasingly important as a new market for the global automotive industry. Currently about 45 million vehicles run in CEE countries. Whereas market saturation (number of vehicles per the number of inhabitants) is far behind Western Europe (in CEE, the ratio is 20 vehicles per 100 inhabitants, in Western Europe it is 50 vehicles per 100 persons), thus with faster economic growth it can also be expected that due to higher personal incomes car ownership and car usage rates will increase dynamically. It should be added that in this 66 Györgyi Barta region the average age of first and second hand cars is also higher, thus the replacement demand will be bigger, too. The automotive industry is an essential element in the development of the economy in the EEC region (Tables 9 and 10). In large countries, the effect of the automotive industry is smaller (Poland, Romania), in some countries hardly any effects are detectable (Croatia, Bulgaria), while in the Czech Republic and Slovakia the automotive industry has become a predominant factor, not only in industry but also in the whole economy. At the time of the recession, due to the considerable setback in many countries (in Slovakia, Germany, Poland and Hungary) the GDP share of this sector also decreased, but not in the Czech Republic and Romania, where growth remained unbroken even during the crisis (Figure 9). TABLE 9 Proportion of the automotive industry in the economy of countries of CEE, in 2005, % (based on the increase in gross added value, %) Country Czech Republic Hungary Slovakia Romania Poland Slovenia Croatia Bulgaria Total Proportional share of automotive industry in GDP 3.1 2.3 2.2 1.7 1.2 1.1 0.2 0.1 – Proportional share of automotive industry in industrial GDP 11.8 10.2 9.5 7.6 6.5 4.3 1.2 0.4 – Proportional share of automotive industry in the automotive industrial GDP of the CEE region 29 18 8 13 28 3 1 100 Source: Own calculation based on Halesiak et al. (2007, 12; fig. 8–9). TABLE 10 Change in proportional rate of automotive industry in industry in CEE, % Country 2007 2008 2009 Germany Czech Republic Poland Slovakia Romania Slovenia Hungary Austria CEE 21.4 14.5 7.9 29.2 5.5 9.1 10.8 4.4 18.6 22.1 16.8 8.6 37.6 7.8 11.7 8.0 7.0 19.2 15.1 23.1 7.4 30.7 8.3 14.3 7.8 7.1 14.1 Source: Eurostat. Central and Eastern European Automotive Industry in European Context 67 FIGURE 9 Proportional rate of the automotive sector in the industrial production in the countries of CEE, between 2005 and 2009, % % 40,0 35,0 30,0 25,0 20,0 15,0 10,0 5,0 Germany Slovenia Czeh Republic Hungary Poland Austria Slovakia CEE 2009 2008 2007 2005 0,0 Romania Source: Edited by Szabolcs Szabó based on Eurostat figures. Concluding these thoughts it is still worth posing the question of whether CEE countries are competitors to one another in the automotive industry? The answer is yes and no. Central and Eastern European countries (here only the post-socialist countries are meant) have similar characteristics (countries with small areas, a socialist heritage, capital shortage, middle rate development), i.e. they mostly possess the same incitements to attract or not attract investors. Undoubtedly they make remarkable sacrifices to acquire foreign investments: They develop their infrastructure (mostly, construct motorways), participate in investments abroad with governmental support, they develop professional and vocational training to satisfy the demands of investors, they create investment-friendly taxation schemes, tax holidays included. Big subsidies for greenfield-investments are also the rule. Two examples are provided regarding the different taxation systems by countries, and the dates of amending the taxe schedules, and supports received from local governments (Tables 11 and 12) (Varga 2011; Kemenczei 2009, 2010). Similar- type factors of attractiveness are created here and there, but they all fall into the same category. The economic policy of the Visegrád countries also shows remarkable differences regarding the importance attributed to foreign investments. As a general conclusion, CEE countries have to take serious and constant efforts to attract foreign 68 Györgyi Barta capital but basically they are unable to step over their limits, thus more or less they offer similarly attractive factors for investing countries. It might also be interesting to consider, that for historical reasons or other, CEE is basically the strategic playfield of (mostly) German automotive giants, for better or worse. In the statements of the automotive industry investing and capital recipient countries appear not individualised, as these countries become integrated during the globalisation into the international division of labour. For instance, the parts and components manufactured in Hungary are used by the Slovakian manufacturer to assemble the finished product. The geographical position of the Visegrád countries enables foreign investors to see these countries as a cluster. Therefore these countries are much more involved in cooperation rather than being competitors to one another (Sipos 2010). Incorporated companies with a high share of foreign capital are mostly deemed as remote business units of transnational companies (Ansani–Singer 1992). The scale, structure and time of investments are determined by the strategies of the investing companies. It is the investor who decides on what role to give to the recipient country. The major investors in the CEE region are German automotive companies that follow their own long-range strategies in planning, building, production, vocational training, etc. TABLE 11 Business taxes in Visegrád countries, % Tax type Corporate tax, surtax Local tax on industrial activities Tax on dividends, Health Contribution Hungary Czech Republic Poland Slovakia 2003 2008 2003 2008 2003 2008 2003 2008 18 16 4 31 21 27 19 25 19 2 2 None None None None None None 20 25–35 14 15 15 15 19 15 None Source: Kemenczei (2009, 34). TABLE 12 Forms of support provided by the local municipalities for multinational companies settled in the countries of CEE (% of the companies) Czech Republic Reduction, cancellation of local tax Reduction, cancellation of rental fees Provision of land at low price or free Taking over of problematic real estates Fast administration Source: Gelei–Venter–Gémesi (2011). 35.1 2.7 1 8.9 0.0 8.1 Poland 16.3 0.9 1.3 5.3 7.9 Hungary 21.4 3.8 4.4 3.1 26.3 Central and Eastern European Automotive Industry in European Context 69 Conclusions The Central and Eastern European region was the main winner of the global and European development in the automotive industry. Dynamic development commenced with an annual growth of 20% in added value production, and currently the CEE automotive industry generates 10% of the industrial added value production. The CEE region generated 16% of Europe’s production in 2010. The CEE automotive industry is export oriented, although imports also increased significantly, several countries of the region (the Visegrád countries and Slovenia) became net exporters (Figure 10). This rapid growth could happen only with significant foreign direct investment. The usage of cars also increased rapidly in this period in the CEE, thus this region not only became an essential manufacturing region but also it became an important market. The development of the CEE automotive industry is a success story. This region is expected to remain the development area of the West-European automotive industry, for the differences in manufacturing costs between the western and eastern parts of Europe diminish slowly, the region is stable and reliable, and keen competition keeps forcing the western companies to further extend their businesses in Eastern Europe although some relocation of production farther to the East is also anticipated. FIGURE 10 Net exporters of CEE in 2006 Key: 1 – Turkey; 2 – Poland; 3 – Slovenia; 4 – Czech Republic; 5 – Hungary; 6 – Slovakia; 7 – Croatia; 8 – Romania; 9 – Bulgaria. Source: Own editing based on UniCredit New Europe Research Network. In: Halesiak et al. (2007, 22; fig. 25). 70 Györgyi Barta References ACEA (European Automobile Manufacturers’ Association): http://www.acea.be/images/uploads/files/20100930 Production EU27 1006 III MV.pdf; http://www.acea.be/images/uploads/files/20101223 ER 1012 2010 III Q3.pdf [11 August 2011]. Ansani, J. A. – Singer, H. W. (1992) Rich and Poor Countries. Routledge, London. Blöcker, A. – Meissner, H-R. – Jürgens, U. (2009) Anticipation of Change in the Automotive Industry. Analysis of Automotive Regions. Study 3. Diez, W. – Becker, D. (2010) Brand and Ownership Concentration in the European Automotive Industry. Possible Scenarios for 2025. Institute for Automotive Research, KPMG Europe LLP. Domanski, B. – Lung, Y. (2009) The Changing Face of the European Periphery in the Automotive Industry. – European Urban and Regional Studies. 16. pp. 5–10. Eurostat: http:// epp.eurostat.ec.europa.eu/portal/page/portal/prodcom/data/excel_files_nace [10 August 2011]. Freyssenet, M. (2010) Transformation and Choices of European Automobile Industry Post– Global Financial Crisis. GERPISA, CNRS Paris. http://freyssenet.com/files/Transformation%20and%20Choices%20of%20European%20Auto mobile%20Industry%20Post%20Global%20Financial%20Crisis%20-%20site.pdf [10 August 2011]. Gelei A. – Venter L. – Gémesi K. (2011) A multinacionális vállalatok a járműgyártás iparágban. In: Chickán A. (szerk.) A multinacionális vállalatok hatása a hazai versenyre és a versenyképességre. Budapesti Corvinus Egyetem Vállalatgazdaságtan Intézet, Budapest. pp. 179–231. Halesiak, A. – Mrowczynski, K. – Ferrazzi, M. – Orame, A. (2007) The Automotive sector in CEE: What’s next? UniCredit Group New Europe Research Network, Wien/Mailand. 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Pyke, F. – Sengenberger, W. (1992) Industrial Districts and Local Economic Regeneration: Research and Policy Issues. In: Pyke, F. – Sengenberger, W. (eds) Industrial Districts and Local Economic Integration. International Labour Organization, Geneva. pp. 3–30. Sipos M. (2010) A járműipar Szlovákiában. Nemzetgazdasági Minisztérium Tudásgazdaság Főosztály, Stratégiai Műhely UniCredit Group. Varga Gy. (2011) Tépelődés az autóúton. – Népszabadság. 2 June. p. 12. SYSTEM OF KNOWLEDGE TRANSFER IN THE AUTOMOTIVE INDUSTRY MELINDA SMAHÓ Keywords: automobile industry research and development functional upgrading The study investigates the knowledge-based process and knowledge-transfer system of the automotive industry introducing the relevant theoretial concepts on the one hand, and analysing the knowledge-based process of the Central and Eastern European (CEE) automotive industry on the other hand. The theoretical-historical literature review confirmed that knowledge and/or its any form appears and plays a role in the production paradigms of the automotive industry, and at the same time, its characteristics differenciates the production system according to more dimensions. Dramatic changes that have taken place for the last two decades have caused modification in the value chain’s structure and have shortened the product life cycle. Furthermore, they predicts a turnround in the direction of the innovation. Thus, the main points of the production and development tasks have been changing that have led to the restructuring of the international labour division of the automotive industry on the one hand, and to the launch of upgrading process in the automotive industry of the CEE countries. The research states that the building and broadening of R&D capacities have started in the analysed Central and Eastern European countries’ automotive industry. This process incorporates both the starting up of foreign companies’ R&D units and the revival and development of the domestic research centers. Introduction According to the sectoral innovation approach there exist systematic and significant differences between the innovative attitudes of individual industrial sectors, for instance, in the pace of technical change as well as in the field of the organisation of innovative activities (Reinstaller–Unterlass 2008). Automobile industry, being one of the keystones of the economy in Europe, belongs to the so-called medium-high tech industries. Its future competitiveness is highly determined by the innovation system supporting the creation of new and attractive products (product innovation) on the one hand, and their high-standard and effective production (process innovation) on the other. Innovation in automobile industry may be interpreted largely as a collaborative work, i.e. the outcome of cooperation between the car manufacturing companies and their technologically experienced Tier1 suppliers (Sofka et al. 2008). A peculiarity of this sector is that the production of components, having high added value, being capital intensive and requiring research and development, is combined with the manufacturing of parts and components having low added value and being labour intensive (Fortwengel 2011). At the end of the first decade of the new millennium 63 per cent of the companies engaged in automobile industry in the EU25 may be considered as 72 Melinda Smahó knowledge-producing, while 37 per cent is knowledge-applier, which, compared with other sectors of industry, may be esteemed as a favourable proportion (Reinstaller– Unterlass 2008). The number of patents applyed by automobile industry also suggests the innovative nature of this sector. In 2008, nearly 6300 patent applications derived from the European automobile industry, which made more than half (54%) of the applications received by the European Patent Office in 2008. The rest of patent applications were received from Japan (22%), came from the United States of America (16%), and arrived from China/Taiwan and South Korea (less than 1%) (ACEA 2010). On the basis of the foregoing it may be assumed that the role of knowledge as well as knowledge based processes in automobile industry is not negligible at all. The objective of this study is to reveal the knowledge based process and knowledge transfer system of vehicle (automotive) industry); on the one hand through the presentation of theoretical relations, on the other hand through analysing the knowledge based process applied in automobile industry throughout the Central and Eastern European Countries. The first chapter of this study examines the role knowledge plays in the production system of automobile industry. Following the review of the main – in particular knowledge related – peculiarities of production paradigms in chronological order, comes a deeper analysis and comparison of some production system. The second chapter investigates the actual trends of knowledge transfer in automobile industry, on the one hand by approaching and revealing the characteristics of research and development and innovation, on the other hand by investigating the suppliers’ status and roles taken in knowledge based process. The third chapter discusses the geographical dimensions of knowledge transfer in automobile industry, relevant to two Western European countries (Germany, Austria) and six Central and Eastern European countries (Poland, the Czech Republic, Slovakia, Slovenia, Hungary and Romania). Role of knowledge in the production system of automobile industry Historical overview In the small-scale industrial and craft manufacturing system, at the turn of the 19th and the 20th centuries, knowledge can be traced in the form of the craftsmen’s professional competence. They would design and manufacture the components and parts of cars, conforming to the individual demands and requirements of customers, as independent entrepreneurs. As for professional work, their roles were predominant, while the car manufacturing undertakings engaged in the assembling of components and parts took “merely” the role of a co-ordinator. Heuristic knowledge production serving for discovery and understanding was therefore restricted to only few craftsmen or undertakings, considering the fact that at that time there existed no collective knowledge base that other producers or professionals could have also extended, constructed or improved; moreover, even the formal technical education requisit for engineers or technicians was also lacking. At the same time, craftsmen – in the course of their work – System of Knowledge Transfer in the Automotive Industry 73 cumulated more and more tacit knowledge that they acquired empirically over the years; they shared such knowledge with their assistants and apprentices during their collaboration and the process of working together, thus the latter had the opportunity to learn the craft by observation or “by watching” (learning by doing). The craftsmen’s resources (professional knowledge, capital) perfectly fitting for individual manufacturing, however, proved insufficient for the pursuance of systematic research and development activities, and limited the technical improvement within the framework of this paradigm (Havas 2010; Wibbelink–Heng 2000). At the outset of the 20th century it was Henry Ford, who recognised the absolute importance and inherent opportunities of technical development. In his factory, opened in 1910, he applied machine tools that were much more developed than those used earlier; and such tools were combined in 1913 with another technical innovation, the conveyor belt, produced based on József Galamb’s designs, who was Hungarian by origin. The use of modern machinery facilitated the mass production of standardised, interchangeable and easy-to-assemble parts, which was accompanied by the decrease of specific or per unit time and cost indicators. The greatness of Ford’s achievement did not lie in the development of individual techniques and technologies but in the effective combination of already existing technology elements in a mass production system (Wibbelink–Heng 2000; http://www.hfmgv.org/ exhibits/hf/#fmc). This novel, much more developed production technology, however, was coupled with the masses of unskilled workers. In accordance with Taylor’s theories regarding the division of labour, anyone could be able to briefly learn the simplified operations of disintegrated work processes, and by this the workers became easily replaceable or substitutable. Engineering work was characterised by strong specialisation: first development and production was separated then product and production development parted within the field of development and eventually product developers became specialised in the designing of certain parts (Havas 2010). Owing to the knowledge accumulated within a corporation and the inner economies of scale, Ford was always able to develop the technology of mass production faster at its suppliers. Car manufacturing factories adapting the principles of mass production paradigms were, even later on, able to take their leading positions in respect of technology over the suppliers, so that the parts were typically designed by their own engineers, and assigned the suppliers with merely some morsel of subtasks, impeding knowledge drain or leakage by this (Havas 2010; Wibbelink–Heng 2000). From the middle of the 80’s the ‘Fordist’ production system was superseded by the Toyota production scheme (lean production)1 developed by Eiji Toyoda and Taiichi Ohno, which spread not only throughout Japan, but it captivated the car manufacturing companies and suppliers in Western Europe and in North America as well, and all over the world it determined – and still keeps determining – the car manufacturing trends (Cséfalvay 2004). In fact, the Japanese transformed or re-tailored and further developed the system of Fordist mass production, so that the production system was adjusted to their culture and domestic market. The global success of the Toyota-method (and lean production) was attributable largely to the fact that following World War II the 74 Melinda Smahó technology and knowledge transfer was directed from the automobile industry of the USA and Western Europe to Japan, and – in relation to this – to the progress made in the field of organisational learning. At that time Japanese government would encourage car manufacturing companies to bring the knowledge and technology related to car production from the West. Technology import was carried out on the one hand in the framework of associations and co-operations with British, French and American car manufacturing companies on the other hand indirectly by way of “reverse engineering activities” – i.e. through dismantling and studying the cars produced by competitors (Haak 2006; Wibbelink–Heng 2000). In factories operating in accordance with the principles of lean production, teams of skilled workers are engaged in the resolution of variegated problems and endeavour to manufacture products of high quality. Employees are trained and educated for a long time and their works are often rotated inside the corporate organisation – for the purpose of enabling their learning processes – and – in line with the Toyota management’s philosophy – they are constantly involved in the improvement and development of the system (kaizen). The fundament of Kaizen philosophy is a kind of corporate culture where the employees may – without fearing of punishment – focus attention on imperfections or flaws and may identify problems and subsequently they work collectively on the resolution thereof taking advantage of benefits deriving from knowledge sharing and knowledge flow. If collective work is successful individual knowledge will bring about a new standard applicable to the company as a whole, consequently this progress may be interpreted as one of the processes of organisational learning. One of the key elements of the paradigm is the reduction of waste which shall be understood not only in material, physical sense, but also to the waste considered by the system as being the “worst”, to reworking, that is to the wasting of human resources (Haak 2006; SAP 2003). Additionally the Toyota-method opened another channel of knowledge flow, that is the one between companies by the Toyota company promising guaranteed orders and the sharing of surplus profit deriving from cost reduction for the sake of the company’s economic production (cost reduction) to its suppliers, who were willing to adapt and introduce the production principles – especially the just-in-time system forming a part thereof (Haak 2006). With the Toyota-method the knowledge flow appeared formally moreover it was promoted between car factories and their suppliers – but of course, with a restricted and controlled scope. This production system is an alloy of all the advantages that are inherent in handicraft production and the Fordist mass production, obviating the high costs that the former entails and the inflexibility that characterise the latter (Haak 2006). The flexible manufacturing or mass customization, evolving at the end of the 1980s and at the outset of the 1990’s, may be construed as the extension of the principles of lean production to certain extent. Mass customization of production is enabled by the advancements in production-supporting-technology by allowing the use and sharing of the common data base of parts and products, as well as production capacities and problem data among those involved. By interpreting this knowledge as a resource and by utilizing this potential the companies are able to react more swiftly to the changes in System of Knowledge Transfer in the Automotive Industry 75 market conditions, which means a competitive advantage for them (Henriksen– Rolstadås 2010; SAP 2003). At the end of the 1990’s and at the beginning of the 2000’s technology had dramatic impact on productiveness. With the information becoming ubiquitous customers advanced to “crowned kings”, and at present the (car manufacturing) companies’ success depends highly on the swift and efficient reaction and adaption to the “kings’ ” ever changing demands. Two major features of adaptive production paradigm are flexibility and fastness that the companies may achieve through integrated solutions which adjust the supply chain perfectly to the companies’ own operational processes, production machinery and operative systems (SAP 2003). Knowledge flow between car manufacturing companies and their suppliers is not merely a potential or stimulating factor but also a requirement, being prerequisite for the smooth operating of the value chain system. Knowledge base and knowledge based process On the basis of the foregoing analysis it is obvious that knowledge appears and also plays a role in every paradigm, nevertheless its peculiarities strongly differentiate production system along several dimensions (Table 1). Innovational process at companies in the automobile industry are vigorously formed by their knowledge base which is different in each industrial sector, but it also depends on the corporate strategy. As a matter of fact, in the knowledge base of particular industrial sectors the explicit and tacit knowledge is present in a differently proportioned composition; furthermore the potentials for the codification and restriction of knowledge are also different. In synthetic knowledge base the application of the knowledge in-hand or a new combination of the attainable knowledge lead to innovation. Research and development activities and the interrelations between the university and the industry are not very significant and in principal they focus on applied researches, on product and production development. As a result of inductive process knowledge is developed in the course of testing, experiments, and practical work. In principal, the source of knowledge is experience, the learning-by-doing, therefore the knowledge created in synthetic knowledge base is chiefly of tacit type (Cooke et al. 2007). As opposed to the foregoing, in the case of analytical knowledge base the production of scientific knowledge and the access to knowledge source are of determining significance. Fundamental and applied research as well as constant technological development can be equally found at corporate R&D divisions on the one hand and at universities as well as at research institutes on the other hand. University-industry relationship is strong and is based on scientific co-operation; the existence of academic spin-off companies are frequent. Knowledge input and output are codified to a greater extent than in the case of the other knowledge base, at the same time, in analytical knowledge base for the application and use of codified knowledge, in most of the cases tacit knowledge is needed. Production of new knowledge takes place with the usage and application of existing studies, scientific principles and methods, while the output of formally organised knowledge creation process is codified in the 76 Melinda Smahó System of Knowledge Transfer in the Automotive Industry 77 78 Melinda Smahó form of scientific studies, reports or patent applications. The aim of research and development activities is the production of scientific discoveries, technical and technological innovations which will be patented later on (Cooke et al. 2007). Although basically every company has both synthetic and analytical knowledge base, in the case of the handicraft production the former while in the case of mass production the latter one dominates, and the background of lean and adaptive production schemes is ensured by the synthesis of the two mentioned knowledge base (Henriksen–Rolstadås 2010). To suggest differences, without the claim for completeness, some examples are demonstrated below. In the case of mass production a large and central staff is responsible for development and quality issues; quality control is grounded on explicit knowledge and at the end of the production process (e.g. after a car is ready) it is carried out in large scales. Learning process take place on the basis of directions or commands, however in the course of this to make the workers understand and observe the quality principles means or might mean a problem. Supplier relations also rely on explicit knowledge, at the same time, they are formal (e.g. tender, well-defined requirements, documentation). This is because suppliers are selected on the basis of objective criteria, thus the car manufacturers endeavour to keep an arm’s length distance from their potential suppliers. On the contrary, in the case of lean production quality control is much less centralised, and even the labour force is involved in it: the operators working on the production line may stop production if any quality flaw is detected. In the lean management system, tacit knowledge plays a predominant role, the sharing of which takes place on the one hand between persons close to customers (i.e. the sales) and the manufacturer on the other hand between the manufacturer and the supplier. At the same time it is indispensable and is challenging to make this knowledge explicit – and a part of the analytical knowledge base – since the sales and marketing divisions give input to the research&development department and to the production, while decision making regarding the producibility of new products requires conciliation among the research and development, the production unit and the suppliers. To the smooth functioning of such processes the fast and undisturbed flow of codified knowledge is indispensable (Henriksen–Rolstadås 2010). The major principles included in Table 1 above are shaded by the fact that research and development at lean companies may be centralised, minor corrections and improvements however are better to be decentralised, i.e. to allocate them to local units being closer to consumers and suppliers. This may be explained by the fact that the linear or radical innovation associated with the centralised research and development is largely based upon explicit knowledge, the spatial spreading of which is not limited. As opposed to this the fundament of incremental innovation is formed by tacit knowledge, to the attainment of which the car manufacturers must be close in space to the consumers and suppliers. In the case of lean management the relationship between the car factory and the Tier 1 suppliers is crucial; Tier 1 suppliers play a central role in the process of knowledge creation and knowledge transfer, considering the fact that they are expected by the car manufacturers to keep coming up with new and improved solutions. System of Knowledge Transfer in the Automotive Industry 79 This, however, requires access to R&D institutes and the analytical knowledge base, but also a very close relationship is needed within the development teams and with the synthetic knowledge base thereof (Henriksen–Rolstadås 2010). Nowadays adaptive production focuses not merely on knowledge creation and knowledge transfer but much more on the fast adaptation of knowledge and this is largely promoted by the application of information technologies (Henriksen–Rolstadås 2010). The symbiotic co-operation between car manufacturers and suppliers is prerequisite for the alignment of production process, which requires knowledge transfer among the partners via standards, requirements and informal relationships. Territorial determination of knowledge flow, at the same time, might be mitigated by the application of info-communicational technologies. Time is required for the acceptance and adaptation of the principles of a newly created production paradigm, thus the coexistence of characteristics of different production systems often occurs at companies (Henriksen–Rolstadås 2010). The following chapters discuss the deeper correlations inherent in the lean and adaptive production schemes – and their alloys – being commonly accepted nowadays in the developed countries. Current tendencies knowledge transfer in automobile industry Characteristics of research & development and innovation in automobile industry The innovational peculiarities of automobile industry, which predominate nowadays, developed as a consequence of and influenced by the dramatic changes that have occurred in this sector since the beginning of the 1990’s as for the economic and social conditions and circumstances as well as the ever changing consumer demands and requirements, and they show significant differences compared to the peculiarities that used to characterise the previous period. The first such change was the transformation in the structure of the value chain, which had or has been accompanied by decreasing production and development depth at car manufacturing companies. At present, relatively low is the number of internationally active OEMs in automobile industry, who design, produce and sell the car on his own, as a complete product. The major part of the units – the so called modules – constituting nearly 65% of the added value of a modern car – is produced by the multi-tier supplier system, and this proportion – according to the experts’ estimations – is expected to reach 78% by 2020 (Fortwengel 2011; Kremlicka et al. 2011; Sofka et al. 2008; Kinkel–Zanker 2007). Outsourcing of the production processes was accompanied by the outsourcing of the related development activities to the suppliers – in principal to Tier1 suppliers. While two-third of the developments were performed by the OEMs in 2000, in 2010, this ratio was only around 50%, and by 2020 it is estimated – according to the forecasts – to drop to onethird; that is within some years two-third of the developments in automobile industry 80 Melinda Smahó will be performed by and will fall under the responsibility of suppliers (Figure 1) (Kremlicka et al. 2011; Kinkel–Zanker 2007). Considering the division of labour per field of speciality, in the technological development of cars with conventional driving the supplier companies are also involved in – moreover they are responsible for – development, while the development of fuel cell technology – at least for the time being – is concentrated in the hand of OEMs (Kinkel–Zanker 2007). FIGURE 1 OEMs and suppliers’ participation in value creation Source: Kremlicka et al. (2011, 3). The second essential factor forming the innovational process in automobile industry is the profound technological change that took place during the past two decades and nowadays may be considered as nearly constant. At the same time, the new technological potentials emerge more often outside the traditional fields of speciality, in particular in the fields of electronics, the software, the alternative driving systems of motors and alternative fuels, as well as new materials and new production technologies. Development targets include primarily higher safety, higher comfort, the increasing performance as well as environment friendly features. On the short run, for instance in the case of motor developments, the incremental improvement of combustion engines, while on the medium-term hybrid drive and on the long run the fuel cell technology is expected to forge forward (Reinstaller–Unterlass 2008; Kinkel–Zanker 2007). As a consequence of the accelerated technological advancement the service life cycle of models has declined drastically – from 10 years to 3 to 6 years. Parallel with System of Knowledge Transfer in the Automotive Industry 81 this the concept of model updating has also changed; nowadays it is not the development of a completely new vehicle, but “merely” a facelift is meant by it. That is design of the old model is mostly retained and the alterations target primarily the details of design and extend to modifications that are not at all directly visible for customers. Japan shall be treated as an exception in this respect; there car manufacturers still count with longer service lives, whereas their customers still require significant and substantial improvements not merely a facelift. Another typical strategy to put “new models” on the market is the extension and differentiation of the product range, including the satisfaction of customers’ demands via niche models and by this to reveal new niche markets as well. This is facilitated and made economical by the fact that in high proportion identical (global) underframes and modules are integrated in different models; since the research and development expenditure regarding certain parts that may be built-in more than one model, may be projected to a higher serial number, thus their specific value can be drastically reduced (Kremlicka et al. 2011; Kinkel–Zanker 2007). However there have already been overlapping among the cars of corporate groups assembling more than one brands, the new production technology developed by the Volkswagen Group, namely the “baukasten principle” (MQB, Modulare Querbaukasten) has facilitated since 2012 the integration of standardised components in the case of 30 or 40 models to an extent that two apparently different cars are built, 60 to 70 per cent, of the same parts. This is expected to mean 30% cost saving for the company, and from 2020 it will enable the production of 50 different Audi, Seat, Škoda and Volkswagen models. This is a remarkable sum, regarding the annual capacity of the holding scheduled for 10 million cars, and at the same time it is an immense price- and competitive advantage (Becker 2010; Autógyári kannibalizmus 2011). The third direction of changes is the so-called Low Cost-High Tech trend, which can be derived from the transformation of social and economic relations and the consumers’ demands. The population of young urban customers has become a consumer category with growing significance and they raise higher expectations against low category cars than usual in respect of the technical solutions and accessories that the small cheap cars are generally equipped with. In principal in countries with low purchasing power – where the segment of the ultra-low-cost car has appeared again – the car manufacturers can manage to satisfy these demands cost effectively only through extremely smart innovations. High technical requirements coupled with low retail prices – and depressed manufacturing costs – result in the reversal of the former innovational trends: innovative solutions are not any longer put from the higher category cars, after a certain time, into lower category vehicles, but quite the contrary (Figure 2) (Kremlicka et al. 2011). Let us examine how these features and tendencies of innovation affect the knowledge based process, system of motivation and relations of the role players of automobile industry! 82 Melinda Smahó FIGURE 2 Reversal dispersion of automobile industrial innovation Innovation pressure Luxury NEW Large Medium Small Basic ULCC CLASSIC Price pressure Classical direction of innovation New direction of innovation Note: ULCC = ultra-low-cost car Source: Kremlicka et al. (2011, 5). Suppliers and their knowledge based process Automobile industry is a typical example to the so-called quasi-hierarchical value chains, in which the lead firms – the OEMs in automobile industry – organise and control the value chain by virtue of their corporate and market power. They decide on which suppliers to involve in the network and which to exclude therefrom, furthermore, it is their competence to define the characteristics of supplied parts, as well as the production, transportation and quality control process relevant to such parts, not only against the direct suppliers but also all along the supply chain (Figure 3) (Humphrey– Schmitz 2002; Pavlínek–Ženka 2010). Fairly large burden is laid upon suppliers due to their intensive involvement in value creating process and to the shortening of the product’s life cycle. As a consequence of shorter product life cycle the development cycle of supplied parts or components also became shorter, namely from 40 moths at the beginning of the 1990’s by today it has been reduced to approx. 20 months. Besides faster development of innovative products it is more and more expected from the suppliers to solve pre-financing of the research and development activities, and they are also supposed to undertake the risk of a System of Knowledge Transfer in the Automotive Industry 83 possible failure. As a matter of fact R&D work is often not directly appreciated but based on the number of pieces actually sold from a particular product, which encumbers the planning of the returns on an investment. Additionally, suppliers are expected to assume the risk of product liability passed to them by the OEMs, moreover they are to achieve certain rate of cost reduction as well. The latter – at least theoretically – may be accomplished through the synergies related to developments and the returns to scale. In practice the suppliers are to save costs on production due to the increasing financial requirements of the development for the sake of surviving (Kinkel–Zanker 2007). This might encourage them to the introduction of new technologies, or even to the relocation of their business to another geographical area in order to take advantage of the benefits concomitant with such relocation (namely, the lower wages, state subsidies, tax benefits) (Szalavetz 2010). FIGURE 3 System of relations among the car manufacturers and their suppliers; Structure of the value chain OEMs Engines Bodies (design) Car assembly Sales (marketing) Shifting value added Squeezing to cut costs OEM Fising input in a form of technological know-how Tier 1 suppliers Automotive systems (e.g. interior, steering) Shifting value added Squeezing to cut costs Alliances Joint ventures M&A Capital links OEM Tier 1 Consolidation Tier 1 Consolidation Tier 1 Bottom-up pressure resulting from rising material costs Tier 2, 3, ... suppliers Individual parts and modules Tier 2 Tier 2 Tier 2 Tier 2 Tier 2 Tier 2 Source: The Automotive Sector in CEE… (2007, 9). Requirements raised against the suppliers pertaining to management and production – nevertheless the increasing standardisation and the large scale mounting of identical parts – are growing more and more serious, whereas it is necessary to conform to a great number of customer- and variant-specific demands. Their situation is further hampered by the fact that OEMs drastically cut back on the number of suppliers by outsourcing their production process (former Tier 1 suppliers become Tier 2 suppliers), which they reason with their assumption that only few suppliers possess the competencies and capacities they expect and which are requisite for the development and production of complete vehicle modules. Furthermore, OEMs hope to achieve through concentration the reduction of transaction costs and the realisation of economies of scale advantages at the remaining suppliers (Kinkel–Zanker 2007). In fact, only Tier 1 suppliers have the appropriate innovational competencies, they are the ones who are to be capable of accomplishing radical (strategic) product and tech- 84 Melinda Smahó nological innovations, additionally, they are expected to produce their own parts, to assemble the complex module associated with the parts as well as to manage the supplier chain related to this module – in compliance with the OEM’s demands and requirements (Gelei–Venter–Gémesi 2011). According to the logic of modular production it is indispensable that the OEMs and the Tier 1 suppliers shall be located geographically close to one another (Pavlínek–Ženka–Žížalová 2010), therefore with the relocation of the car manufacturers – in order to establish the module-competence – often, the suppliers are encouraged/forced to global presence, and they regularly acquire their competitors, along with their technologies, as a best practice (Kremlicka et al. 2011). Tier 2 suppliers have only product-competences, which covers the implementation of incremental innovations i.e. the development of the specifications or production technologies (for instance in the case of a model change) of the manufactured product (Figure 4) (Gelei–Venter–Gémesi 2011). Although less and less suppliers are capable of meeting the ever increasing requirements, those who persist are given higher recognition and are respected by the car manufacturers as equal strategic partners. Consequently the competition between suppliers has become strained; the companies growingly emphasise the importance of direct contact with the car manufacturers and when they make decisions regarding the location of their production sites they upgrade the importance of the large car manufacturers’ territorial vicinity (Kinkel–Zanker 2007), as well as the essence of informal knowledge flow. Innovational competence TIER1 Product competence TIER2 Capacity competence TIER3 and below Management of module product supplier network + Strategic innovation Incremental innovation + Managing relations with own suppliers Price, compliance with specifications, quality, standard of services, volume, flexibility, reliability Source: Own editing based on Gelei–Venter–Gémesi (2011, 186–190). Product complexity, profit FIGURE 4 Pyramid of supplier competences System of Knowledge Transfer in the Automotive Industry 85 At the same time not only conventional suppliers may benefit from the outsourcing of development functions but also the companies rendering development services. These development companies have appeared as new, independent role players in automobile industry hence they may enter into service of any – or even more than one – car factories or suppliers at a time. As third parties they are increasingly involved in the cooperation between the suppliers and OEMs and with their technical knowledge they support and assist the participants of the development network significantly, furthermore they often undertake the role of the “lead firm” in the development process of modules and components, including also the responsibility for the coordination of development networks. In Germany, the number of employees at such companies has quadrupled in the period between 1998 and 2003, which – at least in Germany – suggests their growing significance. To such an extent that nowadays such companies undertake the complete development of vehicles marketed on gap markets. At the same time, their future role cannot be sufficiently estimated, since the system suppliers taking over more and more development functions from the car manufacturers are not interested in transferring or outsourcing the developments, on the contrary, they take all efforts to retain them, to enhance and reinforce their own key know-how (Kinkel– Zanker 2007). Geographical dimensions of the knowledge transfer in automobile industry: Central and Eastern-Europe Knowledge flow and international division of labour Theories reasoning the new international division of labour consider peripheries not merely as territories exploited by the centre and playing exclusively raw material supplying functions but also as regions having productive functions as well (Fortwengel 2011). Moreover with the shortening of the product life cycle and with the acceleration of the learning process of affiliate companies relocated to the peripheries the geographical division of labour may not be simplified any longer so that the production of mature products with low added value is put to the peripheries, while new products with high added value are manufactured by the centre (Szalavetz 2010). In this respect the theory of the Global Commodity Chains (GCC) emphasizes the role of the lead firms in this industrial sector, and it sees the path of development in the union with them – in the case of automobile industry with the OEMs. However the theory of the Global Value Chains (GVC) examines the patterns and imprints of international division of labour in the era of geographically fragmented production process with geographically scattered role players, taking the unequal distribution of benefits also into consideration. This theory sets upgrading into focus and distinguishes four forms of it. Product upgrading refers to the case when companies shift to the direction of manufacturing products being more sophisticated than the former ones, while process upgrading means increased efficiency, which may be implemented either through the introduction 86 Melinda Smahó of new technologies or through production system restructuring. Intra-chain upgrading or functional upgrading involves the extension of the current scope of a company’s activities by adopting new functions either preceding or following the existing ones in the chain (e.g. besides production designing, marketing, research and development, etc.). Inter-chain upgrading occurs when companies apply or utilise the competences acquired in the course of one of the functions in another sector (Fortwengel 2011). The quasi hierarchical value chains typical to automobile industry are favourable for product and process upgrading while they hinder or even impede functional upgrading. An exception from the latter is when the suppliers are involved in the research and development functions, which appears as a new function at them. The suppliers’ product and process upgrading are carried forward by the product and process standards specified by the lead firms (OEMs), while in the case of the process modernisation also the expected cost reduction may mean a considerable incentive for the incremental improvement of the production procedures. However the upgrading potentials in the case of small supplier companies being at the bottom of the hierarchy are remarkably restricted due to the strong concentration of companies (Pavlínek–Ženka 2011). In the first half of the 1990’s the automobile industry in Western Europe and in Central and Eastern Europe was characterised by an international division of labour analogous to the duality of centre and periphery. Owing to direct foreign capital investments in the green and brown field production units established in the countries of Central and Eastern Europe (Poland, the Czech Republic, Slovakia, Hungary, Slovenia, Romania) at the outset only small and cheap “low-tech” models were manufactured (e.g. Fiat Seicento in Poland), and the products were manufactured by means of modern technology conforming to the world standard. In the first period of the investments in automobile industry no product upgrading took place, but a very significant technological development was carried out. From the end of the 1990s the OEMs changed their strategies, redefined the roles of the countries in Central and Eastern Europe, and more and more export oriented assembling and component manufacturing functions were located there. These plants equipped with world standard technologies shifted to the manufacturing of high-tech products representing high added value (e.g. the VW Tuareg of premium category, or the Porsche Cayenne manufacturing in Bratislava), of course, at much cheaper wage costs than those paid in the Western-European factories. This process can be perfectly traced in the change of the rate of products of low, medium and high added value. Between 1996 and 2006 considering the collective output of the Czech Republic, Hungary, Poland and Slovakia the rate of products with low added value dropped from 26.1% to 23.9% while that of those with high added value increased from 14.1% to 32.3%. The most spectacular change occurred in Poland where the rate of automotive industrial products with high added value grew from 4% in 1996 by 2006 to 33.3 per cent. Thus the initial technological upgrading was also supplemented from the end of the 1990’s with product upgrading (Fortwengel 2011). All these have affected the purchasing strategies of the traditional car manufacturing companies as well as their changes. Parallel with their extension in Central and Eastern System of Knowledge Transfer in the Automotive Industry 87 Europe the OEMs have increasingly expected from their suppliers to follow them and to settle their sites in the vicinity of the newly established assembly plants to serve them. This “follow sourcing” strategy has led to the restructuring of global automobile industry and to the appearance of the so-called global suppliers. The geographical expansion of supplier companies towards the Central and Eastern European countries is truly reflected in the development of the number of automotive industrial companies (Table 2). TABLE 2 Number of vehicle industrial companies (NACE 34) in some European Countries Country Germany Austria Czech Republic Poland Slovakia Hungary Slovenia Romania Number of Companies (pc) 1999 2000 2002 2007 Change (%) (2007/1999) 2,308 206 288 1,646 41 194 124 218 2,283 193 341 1,145 53 202 126 300 2,558 237 573 1,070 76 396 96 352 2,483 307 491 1,328 141 409 104 402 107.6 149.0 170.5 80.7 343.9 210.8 83.9 184.4 Source: Eurostat, Structural Business Statistics. Since the end of the 1990’s the number of automotive industrial companies have set out to increase intensely in nearly every reviewed CEE countries. Slovakia, where almost three-and-a-half-times growth was achieved in the period between 1999 and 2007, showed the most remarkable change. In Hungary, the number of automotive industrial companies more than doubled, but the Czech Republic (170%) and Romania (184%) could also record a growth of similar order of magnitude. Considering the absolute data and the orders of magnitude, Germany and Poland constitute a separate category, and in both countries the “waving” of the number of companies in a minor or greater extent is observable. The question to be posed here is what quality tendencies are hidden behind the increasing number of companies: only the labour intensive productive activities have been relocated to the CEE countries, to utilise the benefits deriving from lower wage rates, or functional upgrading has taken place and knowledge intensive research and development activities have also been introduced? Before giving an answer to this question let us take a closer look at the automotive industrial research and development potentials of Germany and Austria belonging to the central region of European car manufacturing. Altogether 91 car or motor manufacturing factories (OEM) can be found in the eight countries examined in the framework of this study, and the mentioned factories are concentrated in 54 regions2. Regarding the GDP proportional research and development figures a sharp demarcation line is perceptible between the regions of Germany and Austria, and those of the Central and Eastern European countries. It is obvious that the 88 Melinda Smahó car factories (OEMs) of Germany and Austria – with the exception of five German factories – are located in regions where the GDP proportionate R&D expenditure is over 1%. Moreover, almost the same applies to the Czech Republic, where merely one or two regions having car factories (Moravskoslezsko) are below the 1% limit (Figure 5). FIGURE 5 OEMs location and R&D expenditure (2007) in per cent of GDP Total expenditure of R&D (GERD) in % of GDP 3,01 - 6,81 2,00 - 3,00 1,01 - 1,99 0,51 - 1,01 0,00 - 0,50 (10) (13) (25) (15) (30) Source: Own editing based on Eurostat and ACEA figures. Map by Tamás Hardi. The research and development data relevant to the automotive industry also support the highly prominent role of Germany (Tables 3 and 4). On the basis of turnover automobile industry is the largest sector in the country; the research and development expenditure of 18 billion Euro in this sector is over one-third of the national value and nearly one-fourth of the added value of this segment. In 2007, the R&D expenditure of the automotive industry in Germany represented almost 70% of the same value of the EU (Pavlínek–Ženka–Žížalová 2010), and even Braunschweig, a region of Europe being the most specialised to automotive industry is also located here (Eurostat 2010). Twenty-one research and development centres closely related to the OEMs are functioning in the country, which represent 42% of the R&D institutes operated by the European OEMs and Tier 0.5 suppliers. German car manufacturers and their suppliers are world leaders in the field of innovation with their over 3500 registered patents a year. The background for this is provided by the high standard higher educational System of Knowledge Transfer in the Automotive Industry 89 90 Melinda Smahó TABLE 4 Expenditure per person engaged in research and development Country Germany Austria Czech Republic Poland Slovakia Hungary Slovenia Romania Expenditure per person engaged in research and development (thousand EUR/person) 2002 2007 174.4 175.1 69.0 n.a. 6.3 17.0 35.7 3.1 211.5 156.3 89.1 24.1 41.7 61.8 53.4 0.7 Change (%) 121.3 89.3 129.2 n.a. 666.7 363.9 149.5 21.3 Source: Own calculation on the basis of Eurostat, Structural Business Statistics figures. system of the country, with over 100 universities and colleges giving excellently qualified labour force to this industrial sector. The number of people working in automotive industrial research and development is in excess of 83 thousand persons, which makes almost 10% of the employees in this sector. The automotive industrial R&D expenditure per person engaged in research and development is also the highest here, namely it was over 211 thousand Euros in 2007. Beyond this, several innovational clusters integrate the requirements, achievements and challenges of this industrial sector, scientific research and education in scientific fields, related to automobile industry (Figure 6). The innovation political incentives and supports granted to the automobile industry also significantly contribute to its success and achievements (The Automotive Industry in Germany… 2008). Germany’s leading position in automobile industrial research and development was confirmed also by the ranking of the EU’s Investment Scoreboard in 2010, which listed the first one-thousand European companies having the highest expenditure of research and development in the years of 2010. Volkswagen Holding, based in Germany, leads this ranking, and among the altogether 43 companies in the list all carrying out their businesses in automobile industry further 19 – i.e. altogether 20 – are also based in Germany (e.g. Daimler, Bosch, BMW, Continental, Porsche, etc.) (Annex 1). In accordance with its automotive industrial R&D indices Austria can be ranked between Germany and the CEE countries however it showed great differences in scale compred to both (Tables 3 and 4). In the European ranking of the EU Investment Scoreboard two Austria based automobile industrial companies are listed (Miba, KTM Power Sports), and with this it may be stated that more than half of the 43 automobile industrial companies (22) have German or Austrian headquarters (Annex 1). On the basis of the foregoing it may be assumed that these two countries, having advanced automotive industrial research and development potentials and significant corporate headquarters – in the course of the extension of the companies towards the Central and Eastern European countries –, have (also) functioned as knowledge exporting countries. System of Knowledge Transfer in the Automotive Industry FIGURE 6 Network of competence centres related to automobile industry in Germany Source: The Automotive Industry in Germany… (2008, 5). 91 92 Melinda Smahó Functional upgrading, research and development Functional upgrading may be measured by means of several different methods and index figures. Pavlínek and Ženka (2010) consider the rate of R&D expenditure compared to added value, as well as the number of R&D employees in proportion to all other employees as the index numbers of functional upgrading. At the same time, according to global commodity chain and global value chain theories the research and development activities and the existence of research centres suggest functional upgrading process (Fortwengel 2011). In the following we attempt to discover the Central and Eastern European process by alloying these two approaches. The research and development figures of the six CEE countries in 2007 unequivocally suggest the leading role of the Czech Republic (Tables 3 and 4). The number of employees of the country engaged in automotive industrial research and development activities is in excess of that of Austria, but the volume of research and development expenditure (290 million EUR), and the rate thereof in proportion to the added value (6.7%) were also here the highest. In the period between 1997 and 2008 the automobile industrial research and development expenditure of the Czech Republic quadrupled and exceeded the aggregate rate achieved in Hungary, Poland, Slovakia and Slovenia (Pavlínek–Ženka–Žížalová 2010). In the case of the R&D expenditure of Slovakia, Hungary and Slovenia and the rate of them projected to one employee a drastic increase can be experienced, however it is coupled with a very low base value as initial point. In Romania automotive industrial research and development unequivocally dropped and declined. Despite the increasing of research and development expenditure the rate thereof in proportion to the added value showed a declining tendency in almost each country, which – with the exception of Romania – can be explained by the fact that the pace of increase in added value surpassed that of the R&D expenditure. Narrowly defined automobile industry, in 2010, amounted to 39.1% of the total industrial research and development expenditure in the Czech Republic, while the same ratio reached 16.3% in Hungary, 11.7% in Poland and 3.5% in Slovakia (Pavlínek–Ženka–Žížalová 2010). The Skoda Auto gives over three-fourth of automobile industrial research and development expenditure in the Czech Republic. On the background of this on the one hand is the agreement (1991) made between the Czech government and the Volkswagen company in accordance with which the new owner is obliged to retain the Skoda brand, as a consequence of which at the outset of the 1990s the R&D capacities characterising the period before 1989 were maintained, and later new research and development functions were introduced in the factory to support the adaptation of the VW technology and along with this to promote the manufacturing of Skoda models as well as to extend its product range. On the other hand the Mladá Boleslav region, hosting the Skoda Auto, had one of the largest and best qualified labour force bases in Central and Eastern Europe. Relying on the advantages of cheap and well-qualified labour force VW introduced some routine research and development functions (e.g. computer aided designing) in the factory of the Czech Republic at the beginning of the 1990’s (Pavlínek–Ženka–Žížalová 2010). System of Knowledge Transfer in the Automotive Industry 93 Before 1989, in Central and Eastern Europe only the Czech Republic and EastGermany designed and developed individually its passenger cars, the car factories in the rest of the CEE countries worked in accordance with West-European technological licences. In the Czech Republic the majority of corporate automotive industrial research centres were established before 1989 and following the transformation of the regime they went into the hands of foreign large companies or domestic and foreign joint ventures. The new owners recognised the “virtues” of know-how and excellently qualified researchers and developers, therefore they retained these research centres moreover they established new research and development units in the country. Between 1995 and 2007 the number of large automobile industrial R&D centres employing over 100 persons increased from one to five, while the number of small units having a staff of less than 20 persons grew from 35 to 88 (Pavlínek–Ženka–Žížalová 2010). The automobile industrial research and development activities are either co-located with factories or are carried out in stand-alone R&D centres (Szalavetz 2010). In 2006, the Visegrad countries had on the aggregate 40 automotive industrial research centres (Figure 7), from among which the staff number of 26 was over 50 persons. The majority of R&D centres was concentrated in the Czech Republic and Poland, while they were moderately present in Hungary and in principle in Slovakia. Over half of the centres were established after 2004, which also suggests that the establishment of automotive industrial research and development in Central and Eastern Europe – with the exception of the Czech Republic and the former East-Germany – was only a recent process (Pavlínek–Domański–Guzik 2009). Transnational companies may apply manifold strategies in the course of the territorial distribution of the research and development activities. In the majority of cases the routine type, applied research and development activities are placed to the periphery (CEE), while the basic research and higher grade R&D functions are located in the mother countries of transnational companies, and carried out by specialised research centres. The so-called multi-local strategy is more advanced but occurs less frequently, when the research centre situated in either of the CEE countries is specialised in the designing and manufacturing of a unique component (becomes product specialised), serving and supplying the whole company, or at least the European division thereof. This latter strategy is built upon the utilisation of the specialised professional knowledge of individual affiliate companies. In spite of the foregoing the majority of research and development activities are still concentrated in WesternEuropean automobile industrial centres, taking advantage of the synergy effects and obviating the parallel research between different factories (Pavlínek–Domański–Guzik 2009). Engineers employed in local factories established in CEE countries were, at the beginning, assigned only with technical support or and process engineering tasks, but later they were allowed to participate in the designing of locally produced cars and components. Nowadays each car factory employs engineers assigned with process engineering tasks, testing and other routine research and development activities, although they are not in all cases referred to as researchers. More essential research and 94 Melinda Smahó FIGURE 7 Major OEMs and R&D centres in the Visegrad Countries, 2006 Słupsk POLAND Solec Kujawski Sady Bolechowo Warsaw Poznań Grójec Polkowice Wałbrzych Wrocław Lublin Starachowice Jelcz Mladá Boleslav Vrchlabí Kvasiny Gliwice Prague Kolín Nový Vysoké Mohel- Jičín CZECH REPUBLIC Mýto nice Kopřivnice České Budějovice Plzeň Częstochowa Mielec Tychy Cracow Niepołomice Skawina Andrychów Sanok Žilina Trenčín Kechnec Trnava SLOVAKIA Bratislava Esztergom Pilisszentiván 1 Győr 2 3 Budapest Szentgotthárd HUNGARY 4 5 6 Note: 1 – PC assembly plant; 2 – commercial vehicle assembly plant; 3 – engine plant; 4 – transmission plant; 5 – major automotive R&D centres with component plant; 6 – major automotive R&D centres without component plant. Source: Pavlínek–Domański–Guzik (2009, 47). System of Knowledge Transfer in the Automotive Industry 95 development activities, at the same time, are performed by the individual research centres. Relocation of the automotive industrial research and development activities is strongly motivated by the fact that the investors have recognised the advantages inherent in the differences of highly qualified engineers’ and researchers’ wages in Western European and Central and Eastern European countries – although they possess nearly identical level of knowledge – as well as the opportunities to gain extra profit. Consequently numerous global companies have established research and development facilities in CEE countries (Table 5). TIER 1 supplier category – and also the related module development functions – are mainly dominated by companies with foreign owners, while the domestic, Tier 2 and 3 suppliers product and functional upgrading process are restricted and pushed into background (Gentile-Lüdecke–Giroud 2012; Pavlínek–Ženka 2010). Besides the corporate research and development in respect of automobile industrial R&D the relations between universities and the industry, as well as the role of automobile industry related Centres of Excellence are also determining (Szalavetz 2010). TABLE 5 Research and development facilities of major automobile industrial companies in some countries of Central and Eastern Europe Country Investors Poland Delphi, Faurecia, TRW Automotive, Volvo, Remy Automotive, Valeo, Volkswagen Bosch, Mercedes-Benz, TRW Automotive, Valeo, Visteon, Ricardo Audi, Bosch, Denso, Magna-Steyr, Visteon, Knorr-Bremse, Continental, Thyssen-Krupp PSA, Volkswagen, Johnson Controls, Visteon Czech Republic Hungary Slovakia Source: The Automotive Sector in CEE… (2007, 26). Initially companies from the United States of America established research and development centres in Poland, and still nowadays their dominance is perceptible, however the ice is broken nowadays and also the German VW is represented in this country. The largest research centre of the country is the Delphi in Krakow and the TRW in Częstochowa, and the former employs 560 while the latter 160 engineers (Domański–Gwosdz 2009). Within Central and Eastern Europe automobile industrial research and development and technological centres can be found in the largest numbers in the Czech Republic, which can be reasoned with the strong engineering traditions and the high standard of technical higher education. The number of students to be graduated as engineers is estimated to be 79 thousand, and from among them annually 17 thousand are graduated. In seven towns of the country at altogether nine universities there are courses related to automotive industry, for instance at the second largest technical university of Europe, the Czech Technical University (CTU). The mentioned universities closely co-operate 96 Melinda Smahó with the role players of automobile industry and the projects implemented in the framework of such co-operations further enhance the standard of education (Figure 8) (Czechinvest 2009). In the case of Slovenia we may witness a dynamic increase of research and development capacities in the period between 2002 and 2007: the number of persons employed in R&D grew 1.6 times, while the R&D expenditure became 2.4 times higher (Tables 3 and 4). The favourable process is uninterrupted which is indicated by the fact that by 2010 the country could exhibit 85 automobile industrial research and development facilities mainly operated by the business sector, among which there were 63 technological centres (Table 6, Figure 9). In Slovenia the automobile industrial research and development have been primarily orientated to the satisfaction of market demands and to achieving higher and higher profit. Due to fast changes research and development capacities proved to be scarce, therefore the resources of universities (2 faculties at the University of Ljubljana and 2 faculties at the University of Maribor) have also been utilised. Accordingly, by today, the aggregate number of registered researchers and developers employed in the Slovenian automobile industry is in excess of 1000 persons (ACSEE 2010). FIGURE 8 Vehicle industry related university faculties in the Czech Republic Source: Czechinvest (2009, 12). System of Knowledge Transfer in the Automotive Industry 97 TABLE 6 Automobile industrial research and development capacities in some countries of Central and Eastern Europe (2010) Category Slovenia Scientific and Technological Park University Centre Centre of Excellence Technology Developing Centre Research Centre/ Research Institute Centre rendering engineering services Testing Centre Innovation Centre Total Slovakia 6 63 4 8 1 3 85 1 1 7 9 8 6 2 2 36 Hungary Romania 3 3 2 1 6 3 4 1 20 16 13 Source: own editing in accordance with ACSEE 2010, 15–16. FIGURE 9 Distribution of some CEE countries’ R&D capacities per proprietor (2010) Source: Own editing based on ACSEE 2010, 16 In the recent years supporting the automobile industrial research and development and innovation has received also in Slovakia a prominent role and governmental promotion. The major direction of developments is e-mobility that is the construction of infrastructure for electric cars. In this topic research has been performed at the technical universities of Bratislava and Kosiče, as well as at the University of Žilina. Further automotive industrial research is in progress at the Academy of Fine Arts and Design in Bratislava, and at the Alexander Dubček University in Trenčin. Besides the universities the Slovakian R&D centres, the institutes of the Slovakian Academy of Sciences, as 98 Melinda Smahó well as the research and development centres of global companies, altogether 36 research facilities form the base of automobile industrial researches. Half of these are operated by the corporate sector, one-fourth belongs to higher education, and the other one-fourth of these facilities is run by the government. Another feature that makes the Slovakian automotive industrial knowledge transfer interesting is that the three car factories located in the country and having different cultural backgrounds (the German Volkswagen, the Korean KIA Motors and the French PSA Peugeot Citroën) have separate supplier networks, not allowing any opportunities for “transversal” knowledge flows (ACSEE 2010; SARIO 2011). In Hungary, the research and development facilities owned by foreign companies (Table 5), some domestic companies (e.g. Rába Futómű Kft., Borsodi Műhely), and the universities and academic research institutes are the major role players of the knowledge based processes in automotive industry. Inside the Universities from among the regional university knowledge centres (RET) established in 2006 those dealing with automotive industrial research deserve special attention, such as the Széchenyi István University (SZE) Automotive Industrial Regional University Knowledge Centre (JRET), or the Budapest University of Technology and Economics (BMGE) Electronic Vehicle and Vehicle Steering Knowledge Centre (EJJT). The role players and system of relations in the two knowledge based networks constituted by the participation of these regional university knowledge centres are demonstrated in Figure 10. Although no direct research and development and innovational co-operation have been established between these two networks, the higher educational and academic institutes along with some corporations (e.g. Audi) connect these role players directly (Csonka 2009). Today (2010) Hungary has 20 automotive industrial research facilities, four-fifth of which is associated with the business sector (Table 6, Figure 9). Unequivocally, the regions of Western Transdanubia (and especially Győr-Moson-Sopron County) and Central Transdanubia are the ones that lead in corporate automotive industrial researches (Figure 11). In the Western Transdanubian region between 2005 and 2009 there were 12 automotive industrial companies that maintained research facilities. The number of these dropped to 7 by 2009, where 304 persons were employed as researchers and developers. During the same period the companies in this region belonging to the automotive industrial sector spent 19 billion Hungarian Forints (at market price) on research and development, but in 2008 this sum declined to 4.8 billion HUF, and in 2009 this amount was estimated to be 3.8 billion HUF (Table 7) (A járműipar helyzete… 2011). In Romania, between 2002 and 2007, a significant decline in the research and development capacities occurred (Tables 3 and 4). In 2010, 16 automobile industrial research facilities are recordable in the country and nearly two-third is engaged in the business sector. Outsourcing of research and development to the local suppliers was launched by the Dacia, and afterwards foreign suppliers also established research and development activities in the country, to satisfy the Dacia’s demands. Concurrently, the research and development centre, built by the Renault in Titu – from a loan received from the European Investment Bank –, is engaged in testing and the improvement of System of Knowledge Transfer in the Automotive Industry 99 Renault technologies. With respect to research and development the strengths of the Romanian automobile industry include the traditions of technical education, the established Romanian R&D network, as well as the research centre established in the country by the Renault parallel with the relocation of the production. However among the weaknesses we shall highlight the fact that the potentials of universities and R&D institutes situated far from the car manufacturers are not utilised, and universities and research institutes are underfinanced (ACSEE 2010). FIGURE 10 Knowledge-based automobile industrial co-operations in Hungary Foreign countries Legend: The size of lines and arrows indicates the direction and significance of information flow. JRET relations EJJT relations Other research and development, and other cooperations The size of the sign indicates the partner’s size. Academic sphere, research institute Hungarian enterprise Foreign enterprise in Hungary Foreign enterprise Higher educational institution Note: the narrowest arrow: haphazard co-operation; arrow with medium thickness: prototype, product or procedural innovation; strongest link: co-operation for the implementation of frequent complex R&D tasks. The arrows are pointing at the beneficiary. Source: Csonka (2009, 101). 100 Melinda Smahó FIGURE 11 R&D expenditure at vehicle industrial companies and the rate thereof in proportion to gross added value in Hungarian regions, 2008 % 10,0 Million HUF 5000 4500 14,0 4000 12,0 3500 3000 10,0 2500 8,0 2000 6,0 1500 4,0 1000 500 0 2,0 Central Hungary Central Transdanubia R&D expenditure Southern Transdanubia Western Transdanubia Northern Hungary Northern Great Plain Southern Great Plain 0,0 In percentage of the automotive industrial gross value added Source: A járműipar helyzete… (2011, 33). TABLE 7 R&D expenditure at vehicle industrial companies in Western Transdanubia Year 2005 2006 2007 2008 2009 Average of 2005–2009 Million HUF Its share Rate of investments (%) Expenditure per person engaged in research and development, thousand HUF* 30.3 25.9 40.8 29.8 26.3 7.3 2.6 8.2 12.2 17.8 9,100.1 9,666.3 26,144.2 19,316.2 16,698.9 31.2 10.4 16,449.4 From aggregate national economy From the aggregate automotive industrial companies 1,911.0 2,213.6 6,274.6 4,809.7 3,757.3 67.6 56.2 64.0 53.8 41.3 3,793.2 54.8 * On the basis of calculated staff number. Source: A járműipar helyzete … (2011, 35). Existence of knowledge flows directed to Central and Eastern Europe as well as their effects are confirmed by some scientific studies. Pavlínek and Ženka (2010) have established – relying on the analysis of 490 Czech automobile industrial companies in terms of their upgrading process – that between 1998 and 2006 several notable but very selective and uneven industrial upgrading process were carried out in the automobile System of Knowledge Transfer in the Automotive Industry 101 industry of the country. Product, process and functional upgrading process occurred as well, from among which the most essential one, the functional upgrading, was detectable at one-fifth of the studied companies. As a result of functional upgrading the Czech Republic has improved its position taken in the automobile industrial value chain, and could mitigate the distance between it and Germany, as well as the countries considered as the semi-periphery of car manufacturing, it has still been unable to overcome its peripheral situation (Pavlínek –Ženka 2010). In the case of Poland, Gentile-Lüdecke and Giroud (2012) drew the conclusion from the analysis of 380 automobile industrial companies (141 affiliate companies with foreign proprietor, and 239 domestic suppliers), that the companies with foreign owners enjoying higher autonomy in their decisions regarding the suppliers and manufacturing products for the wider (Central and Eastern) European market, are much more committed to the knowledge transfer towards the domestic suppliers, than those working for the local market. The knowledge acquired from the foreign affiliate companies with high probability improves the domestic suppliers’ performance, but really strong ties in relationship are needed to improve and develop co-operation and mutual understanding being prerequisite for corporate growing. Despite these, the knowledge received from the foreign affiliates and the innovativeness of suppliers are not significantly interdependent: to produce new knowledge the suppliers need to rely on their own research and development facilities and opportunities (Gentile-Lüdecke–Giroud 2012). It may be established in accordance with the data and correlations revealed in this chapter that the appearance of foreign automotive industrial companies has contributed remarkably to the upgrading of the automotive industry in Central and Eastern European countries, in respect of products, technologies and functions alike. In the surveyed CEE countries the development and expansion of the automotive industrial research and development capacities were commenced, which, besides the settlement of research facilities belonging to foreign companies also extended to the activating and developing of domestic research facilities’ capacities. However the process of functional upgrading is still selective and uneven, it has been launched and hopefully it will be continued in the future as well. Summary The objective of this study was to give an overview of the system of automotive industrial knowledge transfer and knowledge based process from several views. It was verified, through a historical overview about the role of knowledge in automobile industrial production systems, that knowledge, or any form of it appears and plays role in each paradigm, however its features strongly differentiate the production systems along more than one dimension. In the manufacturing systems of handicraft-small-scale industry the craftsmen’s professional knowledge was predominant, while the new technical procedures introduced in the Fordist mass production were coupled with Taylor’s work organisational principles and masses of unskilled workers. However in 102 Melinda Smahó the lean production scheme the professional knowledge and problem solving abilities are revaluated and appreciated again, and not only do the knowledge flows appear but also they are promoted between car manufacturers and suppliers. Adaptive production requires fastness, flexibility and perfect adaptation are also achieved through and enabled by knowledge based process and the supporting information technologies. Since the beginning of the 1990’s dramatic changes have taken place in automobile industry leaving their marks also on the innovational features of this sector. Outsourcing and modularisation concomitant with the lean production resulted in the structural change of the value chain, as a consequence of which an increasing proportion of production as well as research and development tasks are delegated to the suppliers. At the same time fast and constant technological changes take place in automobile industry: the life cycle of products is shortened, there are more and more opportunities for product differentiation and cost reduction, furthermore new technological potentials emerge outside the traditional fields of expertise (e.g. electronics, software, engines/motors with alternative drive, alternative fuels, new materials and new production technologies). The third direction of changes, the so-called Low Cost-High Tech trend, projects the prospect of the “reversal” in the innovational direction. Intensive joining in value creating process and the shortened product life-cycle lay huge burdens on suppliers, while OEMs raise increasingly serious requirements (such as permanent cost reduction, pre-financing of research work, conformance to an increasing number of specific needs and demands) towards them – mainly towards the Tier 1 suppliers with innovational competences. Emergence of companies – as potential competitors – being independent of OEMs and providing development services has made their situation even more difficult. Shifting of the focus points in production and development tasks has led to the change in international division of labour within this industrial sector as well as to the transformation of the system of relationships and to the initiation of modernisation processes in automobile industry of Central and Eastern Europe being reckoned with as the periphery of European car manufacturing. As a consequence of green and brown field foreign investments technologies of world standard and new management knowledge streamed into the automobile industry of CEE countries. Process upgrading was followed by the modernisation of the product structure, which is indicated by the increasing proportion of high added value products. The third step is functional upgrading that is the commencement of research and development activities’ relocation. In the second half of the past decade, in Central and Eastern European countries, not merely the number of automotive industrial research and development centres was increased but also the extent and seriousness of tasks performed or taken over by them grew. Research and development functions that the CEE countries performed, at the same time, have been typically retained as routine, or applied research tasks, while the fundamental or base research has been further on carried out in the traditional automobile industrial centres of more developed countries. A strong motivating factor to relocate the R&D functions to Central and Eastern Europe is the notable difference in the wages paid to researchers and developers possessing similarly high standard System of Knowledge Transfer in the Automotive Industry 103 knowledge and qualifications in Western-Europe and in the CEE countries. Regarding each surveyed country it may be stated that in them by today the research and development facilities of companies with foreign owner, the domestic companies, as well as the universities and academic research institutes have become the major role players in the knowledge based process of automotive industry. In the field of functional upgrading the Czech Republic is worth to be highlighted from among the surveyed CEE countries. Its traditions regarding vehicle developing (keeping up the research and development units that existed even before 1989 after they have been acquired by foreign owners), as well as its excellent technical higher education provide a good ground for research and development activities. As a result of functional upgrading the Czech Republic has improved its position taken in the automobile industrial value chain, and could mitigate the distance between it and Germany, as well as the countries considered as the semi-periphery of car manufacturing, it has still been unable to overcome its peripheral situation. On the basis of research results for each surveyed Central and Eastern European countries it may be stated that to smaller or greater extent the functional upgrading process has been launched in automotive industry, but they have still not succeeded to break out from their peripheral positions. In my perception, however, they have already “found the good way” and what they should do is to proceed on the path of knowledge based upgrading; their competitive advantages should be grounded upon knowledge in order that they can face successfully with all future tendencies that are anticipated in automotive industry (BRIC countries forging ahead, diminishing the wage cost based competitive advantages). In the surveyed CEE countries the establishment and expansion of automotive industrial research and development capacities have been initiated, which have included – in addition to the settlement of research facilities owned by foreign companies – the capacity activating and developing at domestic research facilities as well. However the process of functional upgrading is still selective and uneven but at least it has commenced, and hopefully will continue. Note 1 The difference between the Lean Production and the Toyota production system is that as long as the former may be applied to the production system of a company belonging to any sector, the Toyota production system represents the Toyota Corporation’s production management system exclusively (Haak 2006). 2 The eight countries examined in this study encompass altogether 93 NUTS2 regions. 104 Melinda Smahó References ACEA (2010): Automotive Sector Tops R&D Investment Scoreboard. http://www.acea.be/news/news_detail/automotive_sector_tops_rd_investment_scoreboard/. ACSEE (2010): Švač, Vladimír–Chudoba, Štefan, Bárta–Jozef, Bušen, Dušan–Mihalič, Branko– Antal, Attila–Borsellino, Diego–Haba, Cristian-Gyozo– Madzharov Nikolay–Stancheva Stela–Vratonjic Dejan (2010): Innovation Trends and Challenges and Cooperation Possibilities with R&D in Automotive Industry. Automotive Cluster, West Slovakia in Trnava, http://www.autoclusters.eu/index.php/download. [11 January 2012]. 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Serie Research Memoranda, Vrije Universiteit Amsterdam Faculteit der Economische Wetenschappen en Econometrie, April 2000. 106 Melinda Smahó ANNEX 1 Ranking of the European automotive industrial companies as per R&D investments (2010) Rank (1000 European companies) Company name Country R&D Staff number R&D investment Ranking Investment (persons) per one employee (R&D (million (thousand investment EUR) EUR/person) per person) 1 Volkswagen Germany 6,258 351,907 17.8 7 3 Daimler Germany 4,852 258,120 18.8 6 7 11 Robert Bosch Germany 3,824 276,418 13.8 12 BMW Germany 2,773 94,446 29.4 5 15 Peugeot (PSA) France 2,402 198,220 12.1 17 17 Fiat Italy 1,936 196,723 9.8 22 20 Renault France 1,728 124,749 13.9 10 23 Continental Germany 1,525 142,695 10.7 18 31 Porsche Germany 924 148,199 6.2 31 45 ZF Germany 621 62,558 9.9 21 48 Valeo France 557 57,930 9.6 23 49 Michelin France 545 110,007 5.0 33 69 Hella Germany 323 22,852 14.1 9 74 MAHLE Germany 310 44,151 7.0 27 94 Rheinmetall Germany 214 20,079 10.7 19 97 126 Behr Spyker Cars Germany Holland 209 154 16,522 3,888 12.6 39.7 16 4 131 Pirelli Italy 150 30,329 4.9 34 143 ZF Lenksysteme Germany 140 10,480 13.3 14 152 GKN United Kingdom 135 35,096 3.9 38 166 Burelle France 120 15,682 7.6 25 195 Eberspaecher Germany 98 5,637 17.3 8 257 IMMSI Italy 63 8,057 7.8 24 320 ElringKlinger Germany 46 4,453 10.3 20 384 Grammer Germany 33 7,745 4.3 37 28 4,153 6.7 29 23 4,723 4.8 36 425 Haldex Sweden Germany 470 WET Automotive Systems 471 Miba Austria 23 3,064 7.4 26 481 KTM Power Sports Austria 22 1,594 13.8 12 486 Montupet France 22 3,202 6.7 28 499 Carraro Italy 21 4,014 5.1 32 504 MGI Coutier France 20 4,122 4.9 35 536 Veritas Germany 18 2,829 6.3 30 625 TI Fluid Systems 14 15,690 0.9 42 657 Nokian Tyres United Kingdom Finland 13 3,338 3.8 39 System of Knowledge Transfer in the Automotive Industry 107 Count. Annex 1 Rank (1000 European companies) Company name Country 722 Brembo Italy Italy 729 Cobra Automotive Technologies Hymer Antonov Kassbohrer Gelaendefahrzeug Germany Torotrak 837 848 873 10 5,880 1.7 41 10 781 13.0 15 Germany 7 2,591 2.7 40 United Kingdom 7 27 252.3 1 6 478 13.4 13 6 53 111.4 2 5 12,352 0.4 43 5 86 54.0 3 974 CIE Automotive United Kingdom Spain 989 Twintec Germany 903 R&D Staff number R&D investment Ranking Investment (persons) per one employee (R&D (million (thousand investment EUR) EUR/person) per person) Source: Own editing in accordance with the figures of the EU Investment Scoreboard 2011. LOCATION FACTORS OF AUTOMOTIVE INDUSTRY IN CENTRAL AND EASTERN EUROPE ANITA FÜZI – SZANDRA GOMBOS – TAMÁS TÓTH Keywords: capital flow location indicators regional development level By writing of this study we had an objective to set up a model which is able to explain the location decisions in the Central and Eastern European region. As an initial presumption we have connected the local capital flow to the regional competitiveness and have analysed the location factors behind the decision makings. After uncovering the theoretical background we set up a 6 factors model which consists of the industrial traditions, business environment, labour market, taxation, infrastructure and local supplier network. As a final conclusion we have tried to set up ranking with the 10 analysed countries. Introduction The purpose of our study is to identify the economic indicators which are able to infuence the industrial location decisions. The focus of the analyses is on the Central and Eastern European region compared to the control group, the developed Western European German and Austrian markets. In the first part of the study we build up a general competitiveness report among the regional countries, the basis of which is the stock and flow of yearly foreign direct invested money. After collecting these macroeconomic details we tried to collect the location indicators and set up a model that explains the flow of capital. Except for the industrial traditions and local supplier network we could provide general economic figures but in this two areas we had to choose a leading industrial sector. We have choosen the automitive industry because beside its leading position it has a tight connection to the German and Austrian market and has made a huge contribution to the regional economic performance. Flow of capital Economic literature offers a wealth of possibilities to measure competitiveness, considered as a general economic index. It is widely spread especially in the field of finance. The most common method is to follow the flow of direct international capital investments. This clearly describes the appeal of an economy (Lengyel 2003). During the past two decades since the significant changes in the regime of the Eastern-European countries a general flow of capital can be seen. Its main driver is cost efficient production. By the beginning of the 90s Western-European companies reached the inner boundaries of their growth. Its result was Location Factors of Automotive Industry in Central and Eastern Europe 109 that they opened towards Eastern Europe – they found new markets and outsourced a part of the production for cost efficiency reasons (Lemoine 1998; Kinkel–Zanker 2007). The opening of new markets in the region happened on a different timescale depending on the development and predictability of an economy. Table 1 gives a summarizing overview of this process, which took 20 years. In this context the international direct capital investment is shown in separate regions, differentiating between the current substance and the inflow per year. The chart shows that the performance level of the German and Austrian economy is far higher than any Eastern European countries. Both of the two countries have the highest indexes in terms of current substance and inflow per year. However the CEEC’s appeal has sharply risen. The Czech Republic, Poland and Hungary strictly fall into line with the top, as the other countries of the region tend to increase their competitiveness (Pavlinek 2004). It is worth examining the proportion of the capital inflow to the GDP, which can act as a guideline by estimating the growth potential of an economy. Based on the above mentioned facts it can be claimed that Germany and Austria are still able to increase their national economy’s growth potential, while there is a significant potential in CEEC, which can be used under stable economic circumstances. However to determine general competitiveness we choose direct capital investment, competitiveness and deployment factors depending on the characteristics of the industry. An area from the angle of competitiveness can be attractive for a multinational company, which deals with services – while for other reasons (like human resources or infrastructure) is not satisfying for a vehicle factory. The next chapters of the study deal with the production sector and the indicators of deployment in the automotive industry, taking into consideration the advantages and disadvantages as well as the future of the developed and the transformed countries. TABLE 1 Foreign direct investment stock and flow Flow (million USD) 2001–2005 2006–2010 Austria Bulgaria Czech Republic Croatia Poland Hungary Germany Romania Slovakia Slovenia 36,029 182 1,580 1,407 4,769 5,633 156,179 21 540 2,129 99,917 1,279 10,375 1,915 28,509 13,627 580,308 907 2,668 4,574 Source: Own countruction after World Bank (2011). Stock (2010) (million USD) GDP % 170,581 1,575 14,018 5,416 30,983 19,423 1,394,225 1,455 3,316 7,318 45.0 3.3 7.3 8.9 6.6 15.1 42.5 0.9 3.8 15.6 110 Anita Füzi – Szandra Gombos – Tamás Tóth Location indicators Both the theories and the practice oriented models emphasize the identification of the deployment factors, and their analysis, because on one hand it helps the regions to keep their automotive industrial companies and on another hand it helps to find new investors. Bossak és Bienkowski (2004) conducted research on the deployment factors of the manufacturers: − − − − − − − − − − − − − − low transaction costs, low investment risk, developed market of capital, ensured ownership, high input into R&D, developed infrastructure, liberal economic policy, no barriers to enter or to leave the market, institutions, which help innovation, are available low taxes and incidental expenses, well-educated experts, expanded local market, stable political and economic circumstances, positive vision about the development of the country. In the case of companies operating in the field of manufacturing vehicles special factors also count, like the number of suppliers with ISO 9000/2000 standard, the distance from the centres, the availability of raw material, the guarantees given by the government, the operating clusters, as well as the cooperation between the role players of the industry, the universities, the R&D institutions and the consultancies. According to research by Murray et. al (1999) the relevant location factors for vehicle manufacturers can be categorized into 3 groups. Those indicators belonging to the first group, which influence the level of the operating costs, are, for example salaries (the average and the minimal), overheads, price of raw materials, upcoming costs due to real estate, and taxes. Furthermore work productivity, niveau and availability of infrastructure belong to the first group. Following that there is the regulation environment, the distance from the markets, demographical characteristics, and the volume of urbanization. The third group contains the factors regarding the standard of living, like the condition of the natural environment, education opportunities and crime rate. The German Investment Agency also recited most of the above mentioned factors in its study of 2008. According to the study of this institution the following points should be considered: − nearness of the markets, − properly educated human resources, − R&D institutions, Location Factors of Automotive Industry in Central and Eastern Europe 111 − the development of R&D support, − availability of other manufacturers and suppliers in connection with vehicles and their market position, − infrastructure, − stable investment environment, and different motivation systems. KPMG also conducted research in this field in 2009. Its main goal was to examine the deployment strategies of the vehicle industrial suppliers. It says there are 4 main factors to observe, which appear on a different scale in a different country: the nearness of the markets, the costs, the ability for innovation (meaning the advantages or disadvantages of a given location), and finally the low political, economic and social risks (KPMG 2009). Werner (2003) emphasizes the nearness of the markets (like the EU) in his study, the advantages ensured by the government, the well-educated workers, and the favorable economic expectancies. These expectations are influenced by many factors, which is why the indicator described by Werner (2003) is a summarizing category, and its elements should be identified individually. The Allen & Overy (2008) study concentrates on the CEEC region. Within this framework the taxation system, the availability of the EU structural and cohesive system, adequate human resources, the transportation infrastructure, the availability of the buyers and the stable economy are given importance. Rechnitzer et al. (2003) divides the factors in two big groups and named them hard and soft deployment factors (Table 2). Based on the available literature we strived to design a model which simply and clearly describes the motivations by the deployment, and takes into consideration the factors, which help make the decision. In the following we examine 6 different deployment factors (industrial traditions, economic environment, taxation system, infrastructure, human resources, supplier network), which explain the process of the flow of capital. TABLE 2 Classification of location factors Hard locaion factors Soft location factors Industrial traditions Logistic, and infrastructiral network Potential local suppliers Taxation system Labour market Business environment Attractiveness of the region, city Value of free time Cultural factors Quality of government Living environment R&D basis Opportunity for industrial cooperations Innovation potencial Source: Own construction after Rechnitzer et al. (2003). 112 Anita Füzi – Szandra Gombos – Tamás Tóth Industrial traditions The automotive industry has great traditions in the CEEC area, which can be a baseline by the choice of the location both in the case of a West-European and a Far East company (ACEA 2011). European and Asian car manufacturers built spare-part plants and assembly capacities based on the competitive advantages of the region. One of the most important competitive advantages is the ability to adopt new production technologies, so it is good to examine the automotive industrial traditions in each country, which was a stable basis for the largest car manufacturers. The former Czechslovakia had the strongest traditions in this field: the Skoda car industry was established in 1899, and by 1990 it had become the the biggest and oldest car manufacturer among the CEE countries (Werner 2003). It was the first which specialized in designing vehicles. The Tatra factory produces vans. It is also a prominant company in this region. The Trnavské automobilové závody (TAZ, manufacturer of trucks), and the Bratislavské automobilové závody (BAZ) operating with Skoda license models are the determining companies in the Czech Republic (Jakubiak-Kolesar et al. 2008). Poland also has great traditions: the first Fiat factory was established in the 1930s. Inexpensive and well educated human resources, a large home market and a highly qualified human capital were available – all of these factors contributed to give the country an acknowledged and preferred position on the market (KPMG 2007) In Yugoslavia an engine factory was established in 1929, which operated with licenses. Another important year is 1954, when the production of cars began, based on the Fiat license (ibid). Before World War II. in Slovenia the first vehicles were produced in the capital city. The Avtomontaža factory manufactured buses, followed by the production of vans. At that time the Avtomontaža was already dealing with international companies. Nowadays these partnerships are still alive. The production of cars began in 1954 in Novo Mesto. Another milestone is that they started to manufacture caravans and commercial vehicles together with the French Renault (ACEA 2011). Romania has a 60-year-old past in terms of car manufacturing. It began with the production of Dacia models based on Renault licenses in 1967. Car manufacturing was launched in 1927 in Bulgaria. Later on the activity was expanded to assemblage based on western and soviet licenses (ibid). In the case of Hungary the story of the Rába Magyar Vagon- és Gépgyár (nowadays it is called Rába Holding Rt.) is significant. Győr was an excellent location for establishing larger works, because there was an important railway crossing and 4 rivers meet in the city. Following the establishment of the factory its first main product was railway carriages, and they also began to make vans and cars. The other prominent car manufacturer was Ikarusz, which was the biggest coach manufacturer in Europe with its 15,000 buses per year in the ’90s. The roots of the automotive industry in the CEE region origin can be traced back to the first decades of the 20th century. Its dynamic development and competitiveness were halted by World War I. and II. and the economic policies of the Soviet Union. Location Factors of Automotive Industry in Central and Eastern Europe 113 Socialist industrialization considered the automotive industrial traditions, which played a determining role in the life of every country concerned. They wanted the countries to manufacture their own cars, which could be exported through the use of Western-European and Asian licenses. Despite great support this industry decreased after the fall of Communism, and in order to turn this process around, foreign capital was needed (Husan 1997). Assembly industry was installed upon its own production capacities in the greenfield investment framework. Thanks to these efforts the automotive industrial districts came alive after the fall of Communism and development could be experienced again. The investors were foreign companies like Fiat, Citroen, Renault. They had already domiciled automotive industrial factories in the region during socialism. Their activity is still operating in the 21th century. Table 3 gives an overview of the role-players of the CEEC’s automotive manufacturers, emphasizing the timing of their establishment. The operation of the companies in brackets is over, or due to a transaction (fusion, acquisition) they lost their independence. The data of the chart exemplify that the Czech Republic, Poland and Hungary have the greatest traditions. In these countries the automotive industry played an important role during the communist era. Their industrial positions remained strong. Such a positive process can not be seen in Romania, which has added little value to its GDP since the fall of communism. The greenfield investments were replaced by brownfield investments. The volume of foreign capital flow to Slovakia decreased, because the only car manufacturer, Renault, was present before the end of communist regime. Unlike the other 2 countries Slovakia had no automotive industry at all – after communism Volkswagen, PSA Peugeot – Citroen and Hyundai-Kia abruptly appeared. TABLE 3 Vehicle manufacturing companies in Central and Eastern Europe Estimation of vehiche industry companies Before 1990 Czech Republic Between 1990 and 2000 Slovakia Fiat, Volkswagen AG, SOR Solaris, Opel-GM, Volkswagen, MAN, Scania, Volvo (MÁVAG), Rába, (Ikarusz) Suzuki, Audi, GM Dacia-Renault, ARO, (Daewoo) (MARTA, Citroen) – Volkswagen Slovenia Renault Poland Hungary Romania Tedom, Tatra, Avia Ashok Leyland Motors, Skoda Fiat, (FSO) Source: Own construction (2012). – After 2000 Toyota Peugeot Citroen, Hyundai Toyota Mercedes-Benz Ford PSA PeugeotCitroen, HyundaiKia – 114 Anita Füzi – Szandra Gombos – Tamás Tóth Business environment One of the most important competitive disadvantages of the CEEC is that the economic and social culture does not follow western trends at all, so the instability of the economic environment causes a relevant competitive disadvantage on a global scale. Independent studies mention corruption and white-collar criminality as primary sources of risk – but there are also difficulties in a company start-up (PWC 2007). Table 4 is a ranking by the World Bank which shows the elements of a business-friendly environment (the ranks can be seen in the brackets) with the number of company start-ups from 2009 assigned. TABLE 4 Business environment Austria Bulgaria Czech Republic Croatia Poland Hungary Germany Romania Slovakia Slovenia Business-friendly environment ranking (2011) Registered business set up (2009) 32 59 64 80 62 51 19 72 48 37 3,228 35,545 21,717 7,800 14,434 42,951 64,840 56,698 15,825 5,836 Source: Own construction after World Bank (2011). Corruption The global flow of capital has a relevant barrier; corruption, which seems to be invincible. In an analysis of the economic circumstances corruption can not be ignored, because its negative effect can be so efficient that no other factor can compensate it. Corruption is especially strong in the public sphere – there is no countable transaction time and the financial planning is also lax in the fields of public procurements and other licensing areas. The low salaries of governmental employees encourage bribery to become a daily habit. Due to the fact that society takes no serious steps to fight it, corruption and its most common form, bribery, blossom in the CEEC. Besides the critical mass government agencies should oppose corruption – unfortunately many members of this sphere are also involved in it. Proof of this is a survey of Transparency International (2011), which examined the measures against corruption in different European countries. Almost all of the participants received negative qualifications. Corruption interrupts the normal process of corporate procurement in the B2B relations of the CEE region – it particularly disagrees with the culture of the WesternEuropean and American parent company. The counteraction of subordination in the Location Factors of Automotive Industry in Central and Eastern Europe 115 private sector is not the states’ responsibility – it belongs to the internal controlling division of a company (Transparency International 2011). Table 5 shows the continuously up-dated corruption index collected by Transparency International. It clearly shows the different attitude of the West and East. Investors should decide about the volume of risk taking – not only monetary, but in the terms of the measurement represented. TABLE 5 Corruption index and ranking, 2011 Country Austria Bulgaria Czech Republic Croatia Poland Hungary Germany Romania Slovakia Slovenia Ranking Index 15 73 53 62 41 50 15 69 59 27 7,9 3,6 4,6 4,1 5,3 4,7 7,9 3,7 4,3 6,4 Source: Own construction after Transparency International (2011). Business start-up A corner stone of certain and predictable economic environment is the simplicity of the company start-up process. The main goals for the company incentives of government agencies can be the destruction of the formation constraints, the minimization of the authority processes and transit time. Table 6 shows that the CEEC pay particular attention to ensure a business-friendly environment – so they have simplified the process of the start-up. Although large enterprises are less sensitive to such monetary and temporal inputs, a dynamic development of the SMEs can be observed thanks to these actions. Labour market Blue-collar workers The low wage demand of blue-collar workers was what helped the outsourcing trend of the automotive industry to rise sharply. In the frame of the socialist systems high standards of education were hard to reach. Obligate employment removed the market’s regulation and selection ability. Total employment induced inner unemployment, which collapsed in the face of the real market causing mass unemployment. This shock was 116 Anita Füzi – Szandra Gombos – Tamás Tóth TABLE 6 Corporate set-up process, 2012 Austria Bulgaria Czech Republic Croatia Poland Hungary Germany Romania Slovakia Slovenia Austria Time to set up a business (days) Process to set up a business (steps) 28 18 7 20 15 4 32 14 13 18 6 8 4 6 9 9 4 6 6 7 6 2 Source: Own construction after World Bank (2011). also a possibility for investors: they had the chance to choose the most appropriate employees. Their main characteristics were low wage demand, middle education, high productivity (MacNeill–Chanaron 2005). The differences between western and eastern wages are still present. There is no compulsory minimum wage in Austria, whereas in Germany its level is determined by profession and education and these differences can be felt all over Europe. Another typical feature of the CEEC is that the unions place pressure on the companies and on the government, which results in a minimum wage which can not be substituted by the market’s selective power, such as already happened in Western-European countries (World Bank 2011). Table 7 contains the minimal wages of CEEC. The range itself gives information, furthermore compared to the average wage and connected to the corporate added value it represents the competitiveness of the local blue-collar workers. Based on these facts we can claim that the officially determined minimum wages dispersion is high. In accordance with the productivity it makes the added value predictable (World Bank 2011). White-collar workers As previously mentioned while the mass of inexpensive blue-collar workers is among the most attractive indicators of the 90’s, the main base of the location factors is educated labour in the 21th century. Traditional CEE education is high-level (particularly in the Czech Republic and Hungary), and has become available for a wide range of society. The result is that investors can easily find the right white-collar workers. This class is a stable and reliable segment of the market, and above all their wage demand is not much higher than the wage demand of the non-educated employees (Gauselmann–Knell–Johannes 2010). Location Factors of Automotive Industry in Central and Eastern Europe 117 TABLE 7 Minimum wages on the labour market, 2011 Monthly minimal wage (€) Minimal wage to average wage (%) Minimal wage to value added (%) 123 319 381 349 281 157 317 748 40.4 35.0 37.8 35.7 38.8 30.5 33.5 43.5 22 21 32 27 25 24 23 37 Bulgaria Czech Republic Croatia Poland Hungary Romania Slovakia Slovenia Source: Own construction after World Bank, Eurostat (2011). In today’s innovative economic environment a national economy can not keep its competitive advantage only because of low wages. In knowledge intensive industries, like automotive industry the human element is challenging the governments. The right education system and strategy can ensure a competitive advantage for a country on a global scale. The modernization and customization of higher education can form a base for the investments. The educational expenses in table 8 orient to the performance of the national economy in each region. The participants spend 4–5% of the GDP on public education – from pre-school to university education (OECD 2011). TABLE 8 Portion of graduates on the labour market, 2009 Number of graduates in a year Austria Bulgaria Czech Republic Croatia Poland Hungary Germany Romania Slovakia Slovenia 52,157 57,803 96,207 31,693 574,972 68,158 466,196 310,886 75,364 18,103 Proportion of graduates to the population (%) 0.62 0.76 0.92 0.72 1.51 0.68 0.57 1.45 1.39 0.88 Source: Own construction after World Bank, Eurostat (2011). Graduates in real areas (%) 26 25 26 24 21 20 30 22 23 25 Education expenditure to GDP (2008) (%) 5.5 4.6 4.1 4.3 5.1 5.1 4.6 n/a 3.6 5.2 118 Anita Füzi – Szandra Gombos – Tamás Tóth For the choice of a car manufacturer’s location the availability of graduates is important. The conclusions of table 8 is that there is no strong correlation between the number of fresh graduates and the volume of foreign capital input. Yet the education of work craft labour is an important task in each country – if it wants to prevail on the global market. The efforts taken to strengthen higher education in the CEEC can be seen from the rate of graduates. We have to admit that there is a lack of economic and engineer experts. Besides this positive process we have to mention the differences of the demand and supply sides of the labour market in the CEE region, which can be felt in highereducation. Putting reforms into effect and the reconstruction of the educational system requires serious effort from the decision-makers and executives. The conformity is the only way to get and sustain the competitive advantage (OECD 2007). Taxation The indicatiors related to human resources admittedly play very important role in the location decisions of industrial companies but from the point of view of cash flow and financial return we have to examine some fiscal aspects as well like the tax system of the analysed country. The tax burden settled by the state is measurable with exact figures but to show the real indexes it is essential to take into account different taxes and rates. Although the European Union enforce a unified tax system since its establishment its implementation has failed so far and all of the member states operate with their own different taxation systems. Those new member CEE states stand out where taxation is so complicated and intransparent that it makes financial planning more difficult (relating the investments) both in the short and long run (Limpók 2010). A department of the World Bank is continuously following up the changes of the mentioned national economies and examines the total tax burden separated into 3 classes (World Bank 2011). According to the table 9 we can identify that in the developed welfare countries (Austria, Germany) we can meet the ordinary high burdens and in the CEE region we are faced with govenments with hardly 30 percent total tax rates (Bulgaria, Croatia). Hungary and Czech Republic stand out among the CEE region countries using a high total tax burden that seems unattractive from the perspective of investors but as we previously presented the FDI figures actually show the opposite. The reason for the relatively attractive business environment is that in the last 15-20 years the goverments of the analysed countries have provided tax benefits for the investor companies that could reduce the burden thus making the country more attractive for investing foreign capital. This practice had a visible outcome, however as the directives of the EU forbid it so the method can not be applied in the future. We can summarize that although the tax policies of the analysed countries are different both in their theoretical and practical approach we can not see a close connection between the foreign direct investments and the total tax burdens. If we examine the developing routes of the different countries we can not expect a single EU taxation system in the near future because the goverments would loose one of the most Location Factors of Automotive Industry in Central and Eastern Europe 119 important fiscal instrument with which they could regulate the operation of internal markets. The expectations of the EU, however, sharply separate the concept of regulation and interventions so we will not be able to rely on a technique in the future with which the goverments would be able to intervene in the operation of a sector prefering this way an invester company. TABLE 9 Corporate taxes, 2011 (%) Austria Bulgaria Czech Republic Croatia Poland Hungary Germany Romania Slovakia Slovenia Taxes on profit Taxes on work Other taxes Total tax rate 15.0 4.9 7.5 11.5 17.4 14.8 19.0 10.4 7.2 14.1 34.8 19.2 38.4 19.4 23.6 34.1 21.8 31.8 39.6 18.2 3.4 4.1 3.2 1.5 2.6 3.5 5.9 2.2 2.0 2.4 53.1 28.1 49.1 32.3 43.6 52.4 46.7 44.4 48.8 34.7 Source: Own construction after World Bank (2011). Probably the most essential factor of the taxation policy is a predictability in a long run that can facilitate the checking of the cash flow and fosters the influx of the foreign direct investments. Both the European Union and its member states must enforce the single taxation system in the future because with this common policy the affected regions could become more competitive from the viewpoint of foreign investors. Infrastructure Due to the intensive material flow the industry places serious pressure on logistics and transport. The existence of appropriate transport connections, railway and motorway networks and airports are basic requirements. The efficiency and competitiveness of production is determined by the availability of remote sales markets, transaction costs and contact with the different headquaters (Klauber 2008). One of the most determinative elements of the location decisions is the availability of the sites because in this way the competitiveness is raised inside the industry. The easy availability and the right intermodal connections can boost the influx of foreign direct investment and place into focus the time factor because it brings the purchase and the sales markets closer together and ensures more space for the workforce mobility. Though examining the quality and quantity criterions of the road and railway infrastructure we can conclude that CEE has a perceived competitive disadvantage compared to Western Europe. 120 Anita Füzi – Szandra Gombos – Tamás Tóth The analysed Central and Eastern European countries have noticeably different highway supply figures which are the table 10. We can see that the pre-accession funds had a positive effect on motorway construction, the CEE economies could connect to the European area and its availability was improved so they could become a potencial site for Western European and Asian multinational companies. According to the Eurostat figures of 2009 Hungary has a 1.273 km long motorway network which is the best result in the region with Romania in the worst position with 321 km. Besides the quantitative data we should investigate the changing of lengths of motorway. Among the CEE countries this value has tripled in Hungary in the last 10 year period but Croatia and Romania were able to exceed these figures owing to construction between 1999 and 2009. TABLE 10 Total length of motorways between 1998 and 2009, km Austria Bulgaria Czech Republic Croatia Poland Hungary Germany Romania Slovakia Slovenia 1999 2004 2009 Change (%) 1999=100 1,634 324 499 382 448 11,515 317 113 399 295 1,677 331 546 742 569 12,174 552 228 483 316 1,696 418 729 1,097 1,273 12,813 849 321 747 391 4 29 46 18 184 11 168 184 87 33 Source: Own construction after Eurostat (2011). The density of the motorway lines (table 11) is concentrated mainly in the capital city deistricts that results in a crossing of the roads. In the location decisions the distance to the capital cities was determinative in almost every CEE countries: in the case of this is demonstrated by the location of Audi in Győr, in Slovakia Volkswagen in Bratislava and Skoda in Mlada Boleslav in Czech Republic. When examining the railway networks we can conclude that the density of the network is relatively low in the Central and Eastern European region, beside which the trains are old and in poor condition. The proportion of electrified lines is also low and is in need of modernization. However the lines between their own and other Western European capital cities are satisfactory so the automotive industry companies place particular importance on the proximity of railway junctions. Location Factors of Automotive Industry in Central and Eastern Europe 121 TABLE 11 Density of motorways and railway network, 2008 Density of motorway lines (km/1000 km2) Austria Bulgaria Czech Republic Croatia Poland Hungary Germany Romania Slovakia Slovenia 20.7 3.9 9.3 20.1 2.7 13.7 35.9 1.4 8.5 38.6 Density of railway lines (km/1000 km2) 70 37 122 49 62 79 106 45 73 61 Source: Own construction after Eurostat (2011). Local supplier network In the industrial area is of fundamental importance whether there is a competitive market for local suppliers within the sector and whether there is an opportunity to build it up or not. One of the main principles in the industrial production is that the end-stage product manufacturing plants produce only essential components and they purchase the other parts from the suppliers. These manufacturers have specific needs and expectations from their partners and have strict technical requirements and deadlines (Klauber 2008). The finished product manufacturing plant does the assembly function schedules the procurement and organizes the logistic tasks. This special manufacturing organization results in a very competitive production where the supplier are organized in a multilevel system highlighted the outsourcing and specification functions in the 21 century. The CEE region became a target area by the multinational inverstors in the last 2 decades and could integrate to the supplier pyramid. The region has a competitive advantage through the cheep and flexible workforce and because of the fast availability of the sales markets (Gyukics-Klauber et al. 2011). The supplier companies located in the region have built up a pyramid of at least 3 levels. Most of these corporations are subsidiaries in the CEE region. We could hardly find locally owned companies. The second and lower levels are available, however, and they hold many benefits but only for the partners which are able to fulfill the conditions. The quality is not negotiable as the end product manufacturers place very strict requirements on the area of flexible delivery and production. The competition among the part suppliers is excessively heavy as they could be replaced anytime which subsequently continuously generates a chance to decrease the purchase prices. Primarily those companies are able to survive and ask for higher sales prices which produce complex, special highly innovated products and do so by applying systems of quality stan- 122 Anita Füzi – Szandra Gombos – Tamás Tóth dards (Gyukics-Klauber et al. 2011). Chart 12 shows the proportion of ISO certificated companies in the analiysed countries. We can conclude that this region can not meet the quality requirements so far and the dispersion is also remarkably high among these figures. TABLE 12 ISO certification ownership, 2009 ISO certificated companies proportion (%) Bulgaria Czech Republic Croatia Poland Hungary Romania Slovakia Slovenia 19,9 43,5 16,5 17,3 39,4 26,1 28,6 28,0 Source: Own construction after World Bank (2011). The proximity of the suppliers also makes the programming of the production more flexible and easier as well as the logistics and purchasing functions so that numerous suppliers want to locate close to its main sales market. Table 13 gives a summary of the 10 biggest automotive supplier companies in the CEE region detailing their activities and locations. The key for success is the presence of innovation and the build-up of tight collaborative strategies. It is excessively important in location decisions to find the strategically appropriate supplier partner. The key for long term partnership is R&D potential and technological development. The automotive industry dictates one of the fastest technical progresses in the industrial sector and the claims are continuously changing so it is easy to loose the market if someone can not keep up. Table 14 summarizes the regional R&D activities, the most widely used index of which is the expenditure to GDP besides which we often apply the number of hired researchers per million people. There are some extremes in the supplier networks of the CEE region. The located Western European and Asian companies usually bring our own suppliers and rely little on the local network. Sometimes the local companies do not force the partnership even with the multinational company located in its region (Klauber 2008). The main reasons for the low number of business relationships are the lack of capital and the language and communication deficiencies. Beside the low activity, numerous corporations want to integrate to the supplier pyramid. One of the most fashionable solutions are clusters which are organized from inside as a buttom-up model. This organization is not so widespread in the Central and Eastern European region but has serious traditions in the Western part of Europe. For example these clusters have their own management and budget in Germany and Austria and are used in decentralized decision-making processes. The clusters as business forms Location Factors of Automotive Industry in Central and Eastern Europe 123 are not so popular in Hungary as there is a low willingness for cooperation in social and business areas as well (Grosz 2005). TABLE 13 Top 10 vehicle industry supplier of the CEE region Romania Slovakia Bosch (Germany) Automotive electronics, Chassis, Break systems X X X X X Denso (Japan) Air conditioning X X X X Delphi (USA) Integrated systems, modules X X X X Johnson Controls (USA) Seat, door technics, Dashboard X X X X Magna (Canada) Chassis, Seats, lighting systems X X Aisin Seiki (Japan) Gear shift, clutch X Lear (USA) Seats, Electronic systems X X X Visteon (USA) Inside accessories, Driving systems X X X Faurecia (France) Seats, Exhausting X X X TRW (USA) Break systems, Steering wheels X X X Source: Own construction after Unicredit Group (2011). X X X X X Slovenia Hungary Countries Poland Profile Czech Republic Company X 124 Anita Füzi – Szandra Gombos – Tamás Tóth TABLE 14 R&D activity, 2008 Austria Bulgaria Czech Republic Croatia Poland Hungary Germany Romania Slovakia Slovenia R&D expenditure (GDP %) Number of researchers (per million people) 2.66 0.49 1.47 0.90 0.61 0.96 2.54 0.59 0.47 1.66 4 123 1 499 2 886 1 514 1 623 1 733 3 532 908 2 331 3 490 Source: Own construction after World Bank (2008). Conclusions We have itemized the indicators which play an important role in location decisions in the study but an investor’s decision can not be based solely on the review of objective factors. Subjective indicators, the governmental and local governmental lobby often overwrites the return and risk which can be expressed with figures and in turn the calculable, long-term sustainable economic environment can compensate for the shortterm competitive disadvantages which stem from other factors’ adverse effects (Schwab 2010). During the decision making process regarding enterprise location the economic environment and the economic region could be attractive but in the examination of the above mentioned factors we also have to calculate up the status of the location’s saturation. Practically, the existence of a labour market with a stable base is pointless in the long run as well as a well developed infrastructural environment in the region, if previously settled industry has used up the labour force and the infrastructure is also at the top of its utilization. The saturation process can redraw the economic map of a state and can open gates for regions with lower industrial efficiency earlier. Consequently, decisions are made by considering the objective and subjective, real and human fields but the result of the process is strongly influenced and deformed by the saturation data and the governmental lobby. The capital’s flow clearly observes the direction from west to east, in turn the meso level and regional centres saturate, developing through this the economic map of the vehicle industry. To complete the study we set up a ranking for all six location factors which shows the achievement of the examined ten countries in each category (Table 15). Location Factors of Automotive Industry in Central and Eastern Europe 125 TABLE 15 Ranking of regions after location factors Industrial Business Taxation traditions environment Germany 1 2 6 Austria 2 1 10 Czech Republic 3 5 8 Poland 4 4 4 Hungary 5 6 9 Slovenia 8 3 3 Slovakia 6 7 7 Croatia 10 8 2 Romania 7 10 5 Bulgaria 9 9 1 Labour market 1 5 4 2 3 9 7 8 6 10 Infrastructure 1 2 3 8 5 4 7 6 10 9 Supplier system 1 2 3 5 4 8 6 10 7 9 Total 12 22 26 27 32 35 40 44 45 47 Source: Own construction (2012). The table shows that with an exception of the tax load in the case of all location factors Germany and Austria in the top position, thus proving the capital flow processes presented at the beginning of the study. The Central and Eastern European region can be competitive on the global market first and foremost because of its blue and white collar labour force with low wage demands and favorable tax system but its uncertain economic environment can be unattractive to foreign capital investment. It is gratifying that the real direction of location in the vehicle industry and the capital’s flow are consistent with the conclusions of our model which proves that we have choosen correctly the factors of the analyses. References ACEA European Automobile Manufacturer’s Association (2011) http://www.acea.be/ Allan & Overy (2008) http://www.allanovery.com/ Bossak, J. W. – Bieńkowski, W. (2004) „Międzynarodowa zdolność konkurencyjna kraju i przedsiębiorstw”. Szkoła Główna Handlowa, Warszawa. Eurostat (2011) http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home/ Gauselmann, A. – Knell, M. – Stephan, J. (2010) Investment motives of FDI into Central East Europe. – 11th Bi-Annual Conference of European Association for Comparative Economic Studies, Comparing Responses to Global Instability, 26-28 August, 2010, Tartu. Grosz A. (2005) Klaszteresedés és klaszterorientált politika Magyarországon – potenciális autóipari klaszterek az észak-dunántúli térségben. Doktori értekezés. Győr–Pécs. Gyukics R. – Klauber M. – Palócz É. – Páczi É. – Vakhal P. (2011) A magyar kis és középvállalatok beszállítói szerepének erősítéséről szóló stratégia kidolgozása a gép- és gépjárműipari ágazatban: a jelenlegi helyzet tanulságai és a lehetőségek kihasználásának eszközei. Kopint Konjunktúra Kutatási Alapítvány, Budapest. Husan, R. (1997) Industrial policy and economic transformation: The case of the Polish motor industry. – Europe-Asia Studies 1. pp. 125–39. Invest in Germany (2008) The Automotive Industry in Germany – Driving Performance Through Technology. Invest in Germany GmbH, Berlin. 126 Anita Füzi – Szandra Gombos – Tamás Tóth Jakubiak, M. – Kolesar, P. – Izvorski, I. – Kurekova, L. (2008) The Automotive Industry in the Slovak Republic: Recent Developments and Impact on Growth. Working Paper No. 29. Commission on Growth and Development. Kinkel, S. – Zanker, C. (2007) Globale Produktionsstrategien in der Automobilzulieferindustrie. Springer-Verlag Berlin Heidelberg, Heidelberg. Klauber M. (2008) A járműipari ágazati stratégia kialakítását megalapozó szakmai átvilágító tanulmány. Kopint-Tárki Konjuktúrakutató Intézet, Budapest. KPMG (2009) Global location strategy for automotive suppliers. KPMG. KPMG (2007) The Automotive Industry in Central and Eastern Europe. KPMG. Lemoine, F. (1998) Integrating CEE. Working Paper No. 107, BRIE Working Paper Series, Berkeley Roundtable on the International Economy, UC Berkeley. Lengyel I. (2003) Verseny és területi fejlődés: térségek versenyképessége Magyarországon. JatePress, Szeged. Limpók V. (2010) A működőtőke és az adópolitika kapcsolata, különös tekintettel Magyarországra és Ausztriára. Doktori értekezés. Széchenyi István Egyetem, RGDI, Győr. OECD (2007) Entrepreneurship and Higher Education. OECD. OECD (2011) Local Economic and Employment Development (LEED). OECD Publishing, Paris. MacNeill, S. – Chanaron, J. (2005) Trends and drivers. – International Journal of Automotive Technology and Management. 5. pp. 83–106. Murray, M. N. – Dowell, P. – Mayes, D. T. (1999) The Location Decision of Automotive Suppliers in Tennesse and the Southeast. Center for Business and Economic Research College of Business Administration, University of Tennessee, Research paper. Pavlinek, P. (2004) Regional development implications of foreign dierct investment in Central Europe. – European Urban and Regional Studies, 11. pp. 47–70. PWC (2007) Eastern Influx. Automotive manufacturing in Central and Easter Europe. PWC. Rechnitzer J. – Edelényi B. – Németh K. – Smahó M. (2003) Új típusú telepítési tényezők és a gazdasági szereplők térpreferenciái az ezredfordulón. – NYUTI közlemények 152/b. MTA RKK NYUTI, Győr. Schwab, K. (2010) The Global Competetiveness Report 2010-2011. World Economic Forum. Transparency International (2011) Progress report. Unicredit Group (2007) The automotive sector in CEE. Unicredit Group. Werner, R. (2003) Location, Cheap Labor and Government Incentives: A Case Study of Automotive Investment in Central Europe Since 1989. Columbia University School. World Bank (2011) Doing Business. World Bank. PART II. COMPETITIVENESS OF REGIONS AND PRODUCTION CENTRES COMPETITIVENESS OF REGIONS OF CENTRAL AND EASTERN EUROPEAN COUNTRIES IMRE LENGYEL Keywords: regional competitiveness endogenous development human capital Nowadays the competition between regions and consequently the examination of regional competitiveness has become a research question of outstanding importance. In our study we will first look at the definition of competitiveness and the frames of interpretation related to its definition, then we will focus on the models of competitiveness and the questions of its measurement. We update the pyramid model of regional competitiveness, which rests on endogenous development theories, and integrate the viewpoints of the region’s key sectors, clusters, so that it may be applied in case of car industry as well. Afterwards we will proceed to analyse the competitiveness of 93 NUTS2 level regions of 8 Central and Eastern European countries with the help of an empirical data base, using multivariable statistical methods. Introduction Nowadays the increase of global competition can be observed in almost all markets, as a consequence of which the economic role of countries has weakened in comparison to how it used to be, and the value of functional (nodal) regions has been raised. The companies of the global industrial sectors plan in groups of countries with respect to product markets, sales; while in course of the organization of input markets and production they are thinking in sub-national regions, generally cities and their surrounding areas. The companies taking part in global competition have realized that the sources of their competitive advantages are concentrated in space; therefore they have to take steps to strengthen these advantages locally. This competition of industrial sectors resulted in the raising of the value of the economic role of regions, which can be observed on the one hand in the rivalry, special competition between regions, and on the other hand in the increased business capitalization of the agglomeration advantages resulting from spatial concentration. Holding one’s ground permanently in the competition between regions emphasized the concept of competitiveness. Nowadays the investigation of the competition between regions has become one of the major questions of regional science, generating vivid disputes. According to the well-known opinion of Krugman (1994) there is no competition between countries, since in the specialization of labour emerging according to comparative advantages, all countries will be winners with the standard of living improving everywhere. Therefore also in case of regions, the increasing rate of productivity and not competitiveness is 130 Imre Lengyel going to be the determining factor. On the other hand, according to Porter (2007) the competition between regions can be observed, but even here, similarly to the competition of industrial sectors, the competitive advantages, in other words, absolute advantages became important, since nowadays the comparative advantages hardly prevail. As he states: “Competitiveness depends on the productivity with which a location uses its human, capital, and natural resources. Productivity sets the sustainable standard of living” (Porter 2008, 3). It seems to be an accepted fact in regional science that the competition between regions exists, but its characteristics differ both from the competition between companies and the competition between countries (Batey–Friedrich 2000; Chesire 2003; Malecki 2002). Capello (2007a, xviii) states that “regions compete on absolute rather than comparative advantage”. The consequences of regional competition are similar to the result of the competition between countries: the standard of living, employment and wages increase in the successfully competing regions, new investments appear, talented and creative young people, businessmen move there, etc. (Malecki 2004; Polenske 2004). Due to the recognition of these factors success in competition and the examination of competitiveness have become major research questions in the recent decades. The theoretical and practical studies dealing with the investigation of regional competitiveness can be classified under three main topics, which are built on each other in the integrated, complex approach of competitiveness (Barkley 2008): − How can we define competitiveness and the factors that influence it? − By what indicators can productivity be measured? − How can productivity be improved? In the European Union car industry is one of the highlighted sectors, in which the EU can preserve its current competitive advantage. European car industry is characterised by the concentration of strategic sections, centres in a few developed regions, while a part of the executing, assembling works have already been outsourced, e.g. to the regions of postsocialist countries in Central and Eastern Europe. Therefore car industry is important not only for the developed, but also for the developing convergence regions, as it may contribute to the improvement of their competitiveness. In our study we will first look at the definition of competitiveness and the frames of interpretation related to its definition, then we will focus on the models of competitiveness and the questions of its measurement. We will update the pyramid model of regional competitiveness, which does not rest only on endogenous development theories, but also integrates the viewpoints of the region’s key sectors, clusters, so that it may be applied in case of car industry as well. Afterwards we will proceed to analyse the competitiveness of 93 NUTS2 level regions of 8 Central and Eastern European countries with the help of an empirical data base, using multivariable statistical methods. Competitiveness of Regions of Central and Eastern European Countries 131 Definition of competitiveness and its coming into prominence Nowadays the definition of competitiveness overlaps the theoretical and the practical, economic-political categories of both economic growth and economic development (Camagni–Capello 2010; Lengyel 2009a). Besides the many theoretical works which would be able to fill a library, it is sufficient to mention the surveys dealing with the countries’ competitive rankings appearing in yearly publications (IMD 2010; WEF 2010), and one of the key areas of the EU’s regional policy (one of the aims of the 2007–2013 programming period is to improve regional competitiveness and employment), the European Regional Competitiveness Report first published in 2010 (Annoni– Kozovska 2010). It seems that a kind of joint “rebirth” of the concepts of economic growth and development lies behind the “fashion” of the concept of competitiveness: competitiveness is an economic growth which entails sustainable social and environmental development. This new, complex view is well presented by the fact that Roberta Capello (2007a) in her textbook entitled ‘Regional Economics’ associates the various modern trends of local development and regional growth with territorial competitiveness as a key concept. Whereas in the period of 1960–1990, in case of the traditional growth models, growth was measured by the indicators of wages and employment, or productivity and standard of living, from the 1990s onwards the improvement of competitiveness was unequivocally considered. Competitiveness unifies the idea of productivity (as economic effectiveness) favoured by Krugman and Porter with the expectation of the joint improvement of employment and standard of living. With the increase of globalization the socio-economic background conditions have changed, the effects of which the traditional neoclassical trends were no longer able to describe properly. It is important to note that the non-traditional factor availability (innovation, territorial capital), and the endogenous territorial elements have become major growth factors, partly as a consequence of regional competition (Capello 2007b; Camagni 2009; Rechnitzer–Smahó 2011). It is also important that competitiveness has unequivocally become the key concept in the interpretation of regional economic growth. It also follows from this that although in certain cases (Keynesian) central governmental interventions are necessary, beyond this, to improve competitiveness unique, multi-sectored, integrated economic development strategies have to be developed, organized bottom-up, and built on endogenous characteristics in every region (Lengyel 2009b). Competitiveness is an umbrella term difficult to define, it expresses a tendency to compete, ability for competition, and a capacity for gaining a position and maintain permanent stand in competition, which is primarily indicated by success (measured in some way), the size of market share, and the increase of profitability. Regional economic development essentially means the programs aimed at the improvement of a particular region’s competitiveness, the encouragement of especially those workplaces which come into being in the business sector meeting demands outside of the region (Lengyel 2009a). 132 Imre Lengyel In the course of the years many concepts of competitiveness were formed which spring from diverse opinions. From an economic point of view, the competitiveness of territorial units, i.e. countries and regions can be measured by the productivity of the inputs, as Krugman (1994) and Porter (2008) also said. Competitiveness of regions and cities may be well described by the widely recognized definition of Storper (1997, 20): “The ability of an (urban) economy to attract and maintain firms with stable or rising market shares in an activity while maintaining or increasing standards of living for those who participate in it.” However, definitions of competitiveness are elusive, since they usually cover forms of regional economic growth accompanied by rising standards of living in the region. However, as opposed to the economic view, in regional science it can be considered generally accepted that the competitiveness of regions, cities is more than the productivity of inputs, since it essentially means a regional economic growth, as a result of which the average standard of living in the region improves (Camagni 2002; Lukovics 2009; Malecki 2002). Labour productivity can be also high if many people work for very low wages (e.g. in mining industry), or if the number of permanently unemployed people is high, like it can be observed in dual-structured developing countries. This however means only short term success, because the social expense of one-sided economic production will be very high in a few years’ time. The recognition that welfare should be extended to everyone, not only its participants, has already been made in the study of the countries’ competitiveness. Welfare can extend to a greater part of society if the employment rate is high, since sustainable and high standard of living can only be attained with high employment rate. Therefore besides the total factor (capital and labour) productivity which demonstrate economic growth, employment rate is also an important measure of competitiveness. On the basis of the above, nowadays regional competitiveness consists of two different, contradictory economic categories; expressing the joint expectation of productivity and employment. Built on this approach, the standard notion of competiveness is widely accepted as (EC 1999, 75): “the ability of companies, industries, regions, nations and supra-national regions to generate, while being exposed to international competition, relatively high income and employment levels”. In other words “high and rising standards of living and high rates of employment on a sustainable basis” (EC 2001, 37). The European Competitiveness Reports also adopt this approach (EC 2008, 15): “competitiveness is understood to mean a sustained rise in the standards of living of a nation or region and as low a level of involuntary unemployment, as possible”. In our study we also apply the standard concept of competitiveness, on which the pyramid model we took as a basis is built. This model systematizes the impact factors of exceedingly complex processes affecting welfare, labour productivity and employment. In our empirical study we also apply the pyramid model updated on the basis of the results of the newest theoretical trends. Competitiveness of Regions of Central and Eastern European Countries 133 Measurement of competitiveness: a further development of the pyramid model Productivity and employment are the two basic indicators of regional competitiveness, but these well-known economic categories as certain the results of past processes, and do not refer to ability, i.e. the prospective future change of competitiveness. Therefore we also have to investigate those factors on which the future growth of both productivity and employment depends in the middle and long run. In case of standard competitiveness relatively high income (measured by GDP per capita) and relatively high employment level (shown by the employment rate) constitute the two major factors. These two factors can be measured separately as well, but a connection between them can be demonstrated in a well-known way, since the GDP per capita can be divided into three multiplication components: GDP GDP total population = employment employment * working-age population * working-age population total population The third factor (working-age population / total population) changes slowly over time and is rather a demographic than economic term. These remarks suggest that measuring regional competitiveness can be traced back to two interdependent economic categories: Regional income ≅ Labor productivity × Employment rate. It follows from the above that regional competitiveness has no single accentuated indicator, cannot be described with one factor; it rather means an aggregation of relatively well measurable and obvious economic categories which are closely related to each other. The categories include the economic growth expected by economists (GDP/capita) and labour productivity, as well as employment held important by regionalists. Not only the current magnitude of the indicators is of interest, but also their change in time. If we set aside the consideration of the age composition of a given region, three basic indicators remain: − the magnitude of the regional GDP per capita, and its rate of growth; − labour productivity in the region, and its rate of growth; − employment rate in the region, and its change. It is generally accepted that in case of the above indicators not only the absolute level, but also the rate of change shall also be taken into consideration, as a result of which competitiveness is: − from the static approach: the magnitude of the three economic categories in a given year; − from the dynamic approach: the rate in which the three categories change in a given period of time. 134 Imre Lengyel It is also accepted that the approach of regional competitiveness is primarily relative, i.e. regional units are correlated to each other. A region may also be correlated to one of its former situations observed in an earlier time period, but the change measured in comparison to its former position will not show whether in comparison to the other competing regions this is much or little. The improvement of a region’s competitiveness is not an objective, but a means of economic development. Namely the logical structure of a region’s development is the following: − Target: to increase the population’s quality of life, standard of living, prosperity, welfare; − Means: to strengthen a region’s competitiveness, which requires the improvement of productivity; − Basis: to utilize and strengthen the capabilities, abilities of a region. The rate of growth of productivity primarily depends on technological change, partly on the development of innovations, and partly on the implementation of innovations (technology transfer), which enable companies to strengthen and stabilize their competitive advantages (Vas 2009). The growth of productivity, and therefore the improvement of competitiveness are based decisively on the abilities of a region. It is not important in which industrial sectors the regions compete, what is important is how they compete, what company and industrial sector strategies they use (Porter 2008). In this line of thought competitiveness is only a means, which promotes the permanent improvement of the quality of life, the average standard of living of a region’s population. FIGURE 1 Decomposing regional prosperity Prosperity Domestic Purchasing Power - Standard of living - Inequality Per Capita Income - Consumption taxes - Local prices ~ Efficiency of local industries ~ Level of local market competition Labor Productivity - Skills - Capital stock - Total factor productivity Labor Utilization - Working hours - Unemployment - Workforce participation rate ~ Population age profile Source: Porter (2007, 7). Competitiveness of Regions of Central and Eastern European Countries 135 Studying the elements of economic growth, Porter (2007) interpreted the factors affecting the quality of life, standard of living, welfare in harmony with the concept of standard competitiveness (Figure 1). The population’s prosperity, standard of living, as the target of the improvement of competitiveness, is on the one hand dependant on the income per capita, which is determined by labour productivity and the utilization of work force (essentially: employment). On the other hand, standard of living depends on the type of region, and also on the level of purchase power in the region, i.e. the average standard of living generated by the produced income (in a less developed region it is generally cheaper to make a living; public services, properties, etc. are less expensive). Therefore we have to estimate on the basis of the purchase power parity what kind of standard of living can be sustained from a given income. The countries’ and region’ performances are compared on the basis of the purchase power parity also in the EU, but it is also important within a given country, in case of different types of regions, areas how the local purchase power influences the standard of living. Our study reviewing the competitiveness of Central and Eastern European regions is built on the pyramidal model since it is coherent with the above-mentioned findings, and is established on the basis on the inputs- outputs – outcomes relationship (Lengyel 2004, 2009a). Outcomes are the standard of living, the prosperity of any region depends on its competitiveness. Outputs are the basic competitiveness indicators: per capita Gross Regional Product (GRP), labor productivity and employment rate. Sources of competitiveness, inputs influencing regional competitiveness can be divided into two groups of direct and indirect components. Of particular importance are competitiveness factors with a direct and short-term influence on economic output, labor productivity and employment rates. But social, economic, environmental and cultural processes and parameters, the so-called ‘success determinants’, with an indirect, long-term impact on competitiveness are also to be taken into account. Three levels can be distinguished with regard to the targets of regional development programming and the various characteristics and factors influencing competitiveness: − Revealed competitiveness (or basic categories) (ex post indicators, output): these output categories measure competitiveness and include income, labor productivity and employment rate. − Competitiveness factors (ex ante factors): input factors with an immediate impact on revealed competitiveness categories. These can be used to influence regional competitiveness by means of institutions in short-term programming periods. − Success determinants (social and environmental backgrounds): input determinants with an indirect impact on basic categories and competitiveness factors. These determinants take shape over a longer period of time and their significance reaches beyond regional policy-making. The pyramidal model has been adopted by many authors in international literature (Berumen 2008; Gardiner–Martin–Tyler 2004; Resch 2008; Sinabell 2011; Snieska– Bruneckiené 2009), since “this model is useful to inform the development of the determinants of economic viability and self-containment for geographical economies” (Pike– 136 Imre Lengyel Champion–Coombes–Humphrey–Tomaney 2006, 26). “This is an aggregate notion, …, in a regional context, labour productivity is the outcome of a variety of determinants (including the sort of regional assets alluded to above). Many of these regional factors and assets also determine a region’s overall employment rate. Together, labor productivity and employment rate are measures of what might be called ‘revealed competitiveness’, and both are central components of a region’s economic performance and its prosperity (as measured, say, by GDP per capita), though obviously of themselves they say little about the underlying regional attributes (sources of competitiveness) on which they depend” (Gardiner–Martin–Tyler 2004, 1049). As it can be perceived in the pyramidal model, “more recent analytical review has sought to identify the interrelated factors that drivel competitiveness” (Pike–Rodrígues-Pose–Tomaney 2006, 112). Kitson, Martin and Tyler (2004) also measure regional competiveness by the three related indicators: productivity, employment and standard of living. According to them competitiveness is both influenced by hard and soft elements. Hard elements consist of well-measurable economic, demographic, infrastructural, etc. factors, while soft elements include quality, hard to measure characteristics. In systematizing the sources of a region’s competitive advantages they highlighted six factors, in case of which the frame of interpretation is provided by the concept of “capital”: productive capital, human capital, social-institutional capital, cultural capital, infrastructural capital, intellectual/creative capital. While productive capital is relatively well-measurable, serious disputes of interpretation and measurability can be expected in case of human capital. Furthermore, not only the measurement but also the definition of cultural capital, or social-institutional capital is yet in the experimental phase. It is also of importance that it is not enough to look at the measurable factors in case of the particular capital types, it would also be good to estimate the quality elements (network relationships, trust etc.), because in today’s knowledge-based economy these have become the motive forces of development. We have renewed the pyramidal model on the basis of the above thoughts, starting from the growth theory, and taking into account the thoughts of Porter (2007), Parkinson (2006), as well as those of Kitson, Martin and Tyler (2004). Growth theories are traditionally based on the dual factors of capital and labour, to which technology and the human factor were added later. Nowadays, however, other viewpoints have also emerged in the analysis of endogenous growth and development, which are becoming increasingly important in regional trends. Stimson, Robson and Shyy (2009) modelled regional endogenous growth in the nonmetropolitan regions of Australia. They considered 27 independent variables in five factor groups: the structure and size of an industrial sector, unemployment, human capital and income, occupational shifts and know-how, effects of choosing coastal and island locations, and proximity to the metropolitan area. Stimson, Stough and Salazar (2009) suggested a new conceptual model framework for regional endogenous development. Endogenous development as a dependent variable is measured by two indicators, on the one hand by the change of employment or income, and on the other hand by the changing of the employment-based location Competitiveness of Regions of Central and Eastern European Countries 137 quotient (LQ). Explanatory variables include the availability of resources, estimated by 13 indicators, and market fit, measured by 4 indicators. In their model they use more indicators to consider the quality of leadership, institutions and entrepreneurship as well. In my opinion, in the theoretical literature on regional competitiveness and in regional political documents besides the well-measureable, hard economic and infrastructural indicators, hard-to-measure, soft indicators are increasingly gaining ground, especially innovation and knowledge (Lukovics 2006; Rechnitzer 2008). Similar to the way described in case of the theories of growth, regional competitiveness studies are increasingly influenced by endogenous growth and development theories, in which human capital, social capital play an important part (Lengyel 2011). The modifications of the pyramid model can be traced back to endogenous growth and development theories, and consist of the redefinition of the competitiveness factors (Figure 2): (ou Targ tco et me s) FIGURE 2 The renewed pyramid model of regional competitiveness c o Re v mp ea eti led tiv en ess Quality of life Standard of living Regional performance Gross Regional Product de Suc ter ce mi ss na nts Co mp e fac t itive tor ne ss s Labour productivity Research and technological development Human capital Employment rate Productive capital and FDI Traded sectors and clusters Social capital and institutions Economic structure Innovative activity and entrepreneurship Regional accessibility and infrastructure Skills of workforce Social structure Decision centres Environment Regional culture Source: based on Lengyel (2004, 2011). 138 Imre Lengyel a) Research and technological development (RTD): determines the competitiveness of companies in a decisive way, because innovations and the introduction of new technologies and new products can become competitive advantages. Innovations can come from outside of a region (technology transfer, know-how), or they can be the own developments of the companies operating in the region. The permanent growth of a region’s competitiveness is primarily facilitated by the effective R&D activity in the region. b) Human capital (HC): an efficient educational and training system determining the standard, qualification of human capital, as well as the related entrepreneurship has become important in the formation of the differences in regional competitiveness. Not primarily the quantitative characteristics of the work force, but rather its know-how, attitude, risk-taking have become of critical importance. As a consequence of quick technological and market changes, frequent re-trainings, life-long studying became prominent, which calls attention to the importance of the adaptability of human capital. c) Productive capital and foreign direct investments (PC-FDI): The regions’ economic development is strongly connected to their ability to draw and sustain a successful production activity. The existing working capital is one of the depositaries of productivity. Incoming FDI increase employment (one of the basic categories of regional competitiveness) on the one hand in a direct way, by generating new productive capacity, and on the other hand in an indirect way, by improving the competitiveness of local companies working as suppliers, subcontractors, outside workers, sub-agents. d) Traded sectors and clusters (TSC): the income flowing into the region is generated in the traded sector, therefore these sectors are of major importance, as the economic base (export base) model also states. But local sectors also contribute as subcontractors, local business partners to the success of the companies participating in global competition, i.e. the formation of networks and clusters increases regional competitiveness, income, and improves employment. e) Social capital and institutions (SCI): are of basic importance in regional economic growth, since besides “tangible” elements (such as infrastructure for example), intangible assets also play a part in development. Social capital is especially important from the point of view of regional development, which is built on the characteristics of inter-company cooperation, cultural traditions and attitudes, aggregated experience, behavioural patterns, risk management, creativity etc. An efficient economy requires not only institutions (economic organizations, the organizations of employees, administrative institutes) in general, but also an efficient system of relationships built on trust between them, which can be strengthened by civil social organizations (e.g. churches, non-profit organizations). Competitiveness of Regions of Central and Eastern European Countries 139 The renewed pyramidal model builds both on endogenous growth and development theories. The factors taken as a basis in case of endogenous growth theories appear in the model, as well: capital (productive capital and FDI in the model), labour (human capital in the model), and technology (research and technological development in the model). However, the social capital stated in endogenous development theories, and the clusters playing an important part in the updated economic base model also came to be included in the pyramidal model’s competitiveness factors. Similarly to the regional growth theories, for the investigation of the relations between revealed competitiveness (RC) and the competitiveness factors, it is possible to draw up the Regional Competitiveness Function (RCF): RC = f (RTD, HC, PC-FDI, TSC, SCI) RCF fundamentally expresses the relationships between revealed competitiveness (RC) measured by three basic categories and the competitiveness factors influencing it, complementing the thoughts of traditional regional economic growth with the newest findings of endogenous growth and development trends. The importance of the traded sector and clusters in regional specialization was pointed out by Porter (2003, 2008), Stimson, Robson and Shyy (2009). In the meantime, sociological research called the attention to social capital (and territorial capital), which among others was also specially highlighted by Camagni (2009), Faggian and McCann (2009), Florida (2002) and Glaeser (2008). In the course of the empirical study of the regions of Central and Eastern European countries the renewed pyramidal model is taken as a starting point. Not only basic categories, revealed competitiveness shall be analysed with the help of multivariable statistical procedures, but also the background processes described by the competitiveness factors. The empirical study of the regional competitiveness of Central and Eastern European countries In the course of the empirical study the competitiveness of the NUTS2 level regions of eight countries has been analysed, altogether 93 regions, touching on 91 car and motor factories operating there. The distribution of the 93 regions between the countries is disproportioned, since Germany’s 39 regions represent an outstanding proportion, whereas the number of Slovenia’s regions (2) is very small: − − − − − − − Austria 9 regions (6 car and motor factories); Czech Republic 8 regions (11 car and motor factories); Poland 16 regions (16 car and motor factories); Hungary 7 regions (4 car and motor factories); Germany 39 regions (46 car and motor factories); Romania 8 regions (4 car and motor factories); Slovakia 4 regions (3 car and motor factories); 140 Imre Lengyel − Slovenia 2 regions (1 car and motor factory). The objectives of the empirical study: − the typifying of regions on the basis of their similarity; − the comparison of regions according to their competitiveness, accentuating the possible role of car factories; − the demonstration of the extent to which the utilized indicators, indicator groups influence regional competitiveness. Our study follows the rationale of the renewed pyramidal model. The basic categories show the competitiveness attained in the pas period, as ex post indicators. On the one hand, the competitiveness factors express their contribution to the basic categories. On the other hand, they refer to the ‘ability’, the future potential, as ex ante indicators: how regional competitiveness is expected to be modified by their development in the near future. We tried to compile the database of the empirical analysis according to the redefined pyramidal model. Unfortunately, as it often occurs in the course of international studies, the data supply of the countries differs, e.g. Germany provides the data related to qualifications for NUTS1 level regions, instead of NUTS2. In many cases the supply of data is also incomplete, or in case of the appearance of new regions there are no older data. A part of soft type information (e.g. information related social capital) is not included in public and verifiable databases. Only partial information is available about the car industry, the number of car factories per region. As a result of the above we were not able to conduct a full-scale analysis of all the competitiveness factors with indicators following the rationale of the pyramidal model. In spite of this, we are of the opinion that regional competitiveness can be investigated with the existing indicators, and interesting and important correspondences can be pointed out. In the course of the gathering of data1 we primarily relied on the Eurostat database and the publicly released indicators of cohesion reports no. 4 and 5. For the computerized investigations the SPSS–18 program pack was used. Our database utilized for the empirical study consists of (Table 1): − 4 indicators expressing basic categories; − 21 indicators describing competitiveness factors. In the course of the examination of empirical data more methods were used: − standardization: with hierarchical clustering and multidimensional scaling; − principal component analysis: to form a common scale from the 3 basic categories; − factor analysis: to filter dominant factors on the basis of the competitiveness factors; − multivariable linear regression: to demonstrate the competitiveness factors influencing regional competitiveness. Competitiveness of Regions of Central and Eastern European Countries 141 TABLE 1 Indicators of empirical investigation Code Denomination Source Basic categories eugdp08 empr1509 dispinc07 labprod07 Regional gross domestic product (PPS per inhabitant in% of the EU27 average), 2008,% Employment rate of the age group 15–64, 2007,% Disposable income of private households (Purchasing power standard based on final consumption per inhabitant), 2007 Labour productivity in industry and services (GVA per employee, in the average of EU27), 2007,% Eurostat Eurostat Eurostat CR5 Research and Technological Development gerd07 emphigh08 fp707 pat1607 lisbind08 Total intramural R&D expenditure (GERD), percentage of GDP, 2007,% Employment in high-technology sectors within the number of total employed, 2008,% 7th Framework Program, average funding per head (EU27= 100),% Patent applications to the European Patent Office (EPO), average 2006–2007, per inhabitant Lisbon Index (0–100), 2008 Eurostat CR5 CR5 CR5 CR5 Human Capital adedu08 tertedu34 age25–64 weeklyh10 mwork78 gfcf07 Population aged 25–64 with tertiary education (ISCED 5–6), 2008,% Population aged 30–34 with a tertiary education (ISCED 5–6), 2008,% The proportion of people aged 25–64 in the total population, 2004,% The number of average weekly hours worked (in full-time job), 2010, hour That proportion of people from the active age population who moved into the region from outside in the past two years (from within the EU, 2007–2008,% Productive Capital and FDI Gross fixed capital formation per inhabitant (all NACE activities), 2007, Euro CR5 CR5 CR4 Eurostat CR5 Eurostat Traded Sectors and Clusters indust05 serv05 Employment in industry (% of total employment), 2005,% Employment in services (% of total employment), 2005,% adedutr08 eudev07 povrisk08 Participation of adults aged 25–64 in education and training, 2008,% EU Human Development Index (0–100), 2007,% The proportion of the population subjected to poverty even after receiving social benefits, 2008,% Unemployment rate, 2009,% Population aged 25–64 with low education, (ISCED 1–2), 2008,% Share of long-term unemployment (12 months and more), percentage of total unemployment, 2009,% Youth unemployment rate, 2008,% UN Human Poverty Index (between 0–100), 2007 CR4 CR4 Social Capital and Institutes unempr09 lowedu08 lunempr09 unempy08 unhump07 Sources: Own compilation. CR5 CR5 CR5 Eurostat CR5 Eurostat CR5 CR5 142 Imre Lengyel Classifying of regions The groupings generated on the basis of the similarities of the 93 regions, the typifying of the regions was examined by clustering and multidimensional scaling. In both cases 25 indicators were used (see Table 1), i.e. 4 basic competitiveness categories and 21 competitiveness factors were considered, performing standardization per indicator. In case of cluster analysis a hierarchical procedure was chosen, which contracts similar regions on the basis of one tree structure until only one group remains; the steps of the procedure can be illustrated in a dendrogram. In the course of this procedure we can choose in a slightly arbitrary way the groups at which step shall be considered as the subject of our study, in this case the 6 types were accepted after step 10 (Table 2). There was one outlier: Voralberg (AT 34) which constituted an independent type until the very last step. The six clusters form characteristic types: − Cluster 1: all Hungarian, Polish, Czech and Slovakian regions, except the capital regions, with 31 car factories in 31 regions, − Cluster 2: the Romanian regions, except the capital region, with 4 car factories in 7 regions, − Cluster 3: the Czech, Slovakian, Hungarian, Polish Romanian capital regions, with 3 car factories in 5 regions, − Cluster 4: German metropolitan (Hamburg, Bremen etc.) regions and the region of Vienna, with 11 car factories in 6 regions, − Cluster 5: East-German (post-socialist) regions, 10 car factories in 9 regions, − Cluster 6: the two Slovenian, and the rest of the Austrian and German regions, with 32 car factories in 34 regions. On the basis of the spatial separation of regional types established by clustering, the use of the 25 indicators compiled for the study of regional competitiveness, it can be stated that the types are determined by national characteristics (Figure 3). The regions of the post-socialist countries (except Slovenia and Romania) are present only in two clusters, in clusters 1 and 3, with the capital regions belonging to the latter. The regions of Romania, except the capital, have unique characteristics, creating a separate group (Cluster 2). The German, Austrian and Slovenian regions also constitute graphically separate groups, the ’East-German post-socialist’ regions belong to the independent Cluster 5, while the rest are very similar to each other, except a few metropolitan regions (Cluster 4). Car factories can be found in each cluster, i.e. no region-specific location can be demonstrated. In case of the two greater number types, in the 31 post-socialist country regions (in Cluster 1) 31 car factories are operating in 16 regions, while in Cluster 6, listing 34 regions, 32 car factories can be found in 20 regions. Thus there is an car factory roughly in every second region, the most, 5–5 car factories can be found in the Polish Dolnoslaskie and the Czech Severovychod regions, the car factories in the same region obviously belong to different world companies. The car manufacturers’ seats, Competitiveness of Regions of Central and Eastern European Countries 143 strategic divisions are located almost only in West-German regions, while in the other regions there are assembly plants, sites with low level decision independence. Let us note that the number of car and motor factories exceeds the number of regions in two countries, in Germany (46 factories in 39 regions) and the Czech Republic (11 factories in 8 regions). TABLE 2 Types of hierarchical clustering for regions 1 2 3 4 5 6 SK03 SK04 HU31 HU32 HU33 HU23 PL11 PL21 PL63 PL42 PL51 PL43 PL61 PL62 PL41 PL31 PL52 PL22 PL33 PL32 PL34 CZ03 CZ05 CZ06 CZ07 CZ02 HU21 HU22 CZ08 SK02 CZ04 RO11 RO42 RO12 RO21 RO41 RO22 RO31 CZ01 SK01 HU10 PL12 RO32 DE60 AT13 DE50 DE12 DE21 DE91 DE42 DEG0 DED1 DE80 DEE0 DE41 DED2 DED3 DE30 SI01 SI02 AT11 AT12 AT21 AT22 AT31 AT33 AT32 DE93 DEF0 DE92 DEA1 DEA5 DEC0 DE73 DEB1 DE94 DEA3 DE22 DE27 DE24 DEA4 DE71 DEA2 DE11 DE14 DE13 DE23 DE72 DEB3 DE26 DE25 DEB2 Source: Own compilation. 144 Imre Lengyel FIGURE 3 Types of clustering for regions Source: Own compilation. Clustering highlights similarity, so on the basis of the 25 indicators similar historical courses seem to show up, picturing the long-term dominance of the socio-culturalhistorical roots between countries. A powerful spatial separation can be observed; the regions making up the individual clusters constitute “bands” from west to east. The regions of the post-socialist countries, including the East-German provinces, detach themselves from the rest, with the only exceptions of Slovenia and Romania. The Hungarian regions are in Cluster 1, except for Central Hungary, which is listed in Cluster 3. The effect of the urbanization agglomeration advantages can also be observed (Capello 2007a, Lengyel–Rechnitzer 2004), on the one hand, the capital regions of the post-socialist countries constitute a separate group, and on the other hand the German (Hamburg, Bremen etc.) and Austrian (Vienna) metropolises also detach themselves (Clusters 3 and 4) from the rest. The 25 indicators describing competitiveness and the factors influencing it probably indicate basic institutional and social settlement, which can change only in the course of a longer time period. The similarities between regions were also examined by multidimensional scaling, using a PROXSCAL procedure. In a two dimensional point figure mainly similar shapes can be observed for hierarchical clustering, whereas the different types’ relationship to each other, their location, proximities and similarities are also pictured (Figure 4). Competitiveness of Regions of Central and Eastern European Countries 145 FIGURE 4 Position of regions by multidimensional scaling Source: Own compilation. In the figure the regions of the post-socialist countries detach themselves from the German and Austrian regions (Voralberg, AT34 is an outlier here as well), only the Slovenian regions integrate into the latter, and the capital regions got close to them (Prague, CZ01 “positioning” from outside). The multidimensional typifying made on the basis of 25 indicators pictures different courses of development, and similarly to clustering, it pinpoints the socio-economic-historical background and past impact still subsisting today. It is very important to note that the regions do not mix, the regions within the same country showing similar characteristics are located in each other’s proximity, only the capitals are detached. That is to say that the characteristics, institutional background, etc. of a given country still determine regional characteristics. The differences between countries are stronger than the differences within the countries. The Hungarian regions can be found in three groups: Central Transdanubia (HU21) and Western Transdanubia (HU22) together with certain Polish regions got close to German and Austrian regions. Central Hungary (HU10) is also on the border between the post-socialist countries’ regions and those of Germany, while the remaining four Hungarian regions form a separate group, which is the farthest from that of the developed German regions. While in the course of clustering six Hungarian regions 146 Imre Lengyel were classified in one cluster, multidimensional scaling has thrown light on the Hungarian regions’ different path of development: the characteristics of the Central Transdanubia (HU21) and Western Transdanubia (HU22) regions are close to those of certain German, Austrian and Slovenian regions, as well as to those of Central Hungary. While Southern Transdanubia (HU23), Northern-Hungary (HU31), Northern Great Plain (HU32) and Southern Great Plain (HU33) constitute a separate group, they differ most from the German and Austrian regions. This confirms the results of other studies: while the economics of three Hungarian regions integrated into the economy of the EU, the other four regions are still very far from this (Lengyel–Leydesdorff 2011). In the pyramidal model the basic categories are the effects, and the competitiveness factors are the causes, however, they are in obvious interaction with each other. Calculating separately and illustrating together the one dimensional scaling of the 21 competitiveness factors and the four basic categories it is possible to see whether the specific characteristics of the regions are prevalent, i.e. whether there are dominant background processes, or the results of the two different scaling are randomly diffused (Figure 5). FIGURE 5 Positions of regions by one-dimensional scaling Source: Own compilation. Competitiveness of Regions of Central and Eastern European Countries 147 There seems to be a strong connection between the two scales calculated from the two different indicator groups: the one dimensional projection of the regions according to basic categories resulted in a figure similar to that of the scaling calculated from the 21 competitiveness factors. The linear correlation of the two data rows is -0,906, which means that they move closely together. The polynomial regression curve fitting on the points is: y= 0,1754 x2 – 0,9529 x – 0,0771, where R2=0,8359. On the basis of the results of typifying and scaling utilizing competiveness indicators it is probable that regions form groups in the long run on the basis of their specified social-historical characteristics. These types are not random: the regions of a country generally cluster in one place, are similar to each other, and only partly mix with the regions of other countries. Only the capitals of the post-socialist countries and the Slovenian regions can get close to the German and Austrian regions. The distribution of car factories, as it was shown in the course of clustering, is not dependent on regional types, since there are divisions in every group, in about every second region. Revealed competitiveness Revealed competitiveness is measured by basic categories. As it was demonstrated GDP per capita can be broken down using the decomposition method: to the product of labour productivity, employment rate and age composition (the latter is usually left out). The available income of the households is also listed among these indicators (as it appears in the reviewed up-to-date specialised literature), which shows the level of welfare, standard of living of those living in the given region. These indicators determine competitiveness not separately, but together. As mentioned before, competitiveness can be regarded as the renewal and augmented interpretation of economic growth, since in the latter case generally only one indicator, the GDP is taken as a basis. From the decomposition of the GDP it follows that labour productivity and employment are the two basic indicators of competitiveness. On the basis of these two indicators the situation of the 93 regions shows interesting, although well-known and anticipated correspondences (Figure 6). The linear correlation of the two data rows is +0,842, which means that they move closely together. The regression curve fitting to the points is: y=19,443 ln (x) – 19,477, where R2=0,7376. On the basis of labour productivity and employment the two groups of regions can be well divided into groups above and below the CZ02 – SI01 – RO32 – HU10 line. The group above the line includes all German and Austrian regions, as well as the Czech, Romanian, Hungarian, Polish and Slovenian capital regions, and the two Slovenian regions. While the group below the line consists of all the other regions of the post-socialist countries. Similar spatial correspondences were pointed out on the basis of these indicators like in the course of typifying, certain regional types distinctly detach from each other, especially depending on the characteristics of the countries. 148 Imre Lengyel FIGURE 6 Connection between employment rate and labour productivity Source: Own compilation. It is also demonstrated that among the post-socialist countries employment is high, about 65%, in the Czech regions, followed by several Polish regions, while in the Romanian and Hungarian regions employment is much lower even in case of similar labour productivity. Among the 93 regions, employment rate is the lowest in four Hungarian regions: Northern Great Plain (48,1%), Northern Hungary (48,6%), Southern Transdanubia (52,1%) and Southern Great Plain (53,%). While in the other two regions, in Central Transdanubia (57,8%) and Western Transdanubia (59,7%) employment is a little higher, but even so it qualifies as very low. With respect to labour productivity (which is compared to the average of EU=27 on purchase power parity) the 5 regions of the lowest value include two Romanian, two Hungarian (Southern Great Plain 46,5% and Northern Great Plain 48,4%) and one of the Polish regions. Neither Central Transdanubia (56,1%) nor Western Transdanubia (58,5%) reaches 60% of the EUaverage. Consequently, according to both basic indicators of competitiveness, the com– petitiveness of four Hungarian regions is very weak, while the other two regions (Cent– ral Transdanubia and Western Transdanubia) are in a slightly better position only due to their higher employment rate. Competitiveness of Regions of Central and Eastern European Countries 149 It is a basic question whether the car and motor factories of the regions influence the employment rate and the level of labour productivity. The correlation between the number of car factories and the other two indicators (0.14 with employment rate, and 0.12 with labour productivity) shows that they are not moving together. I.e. the influence of car industry is not detectable either in employment or labour productivity. There must obviously be some influence, but on the one hand, the number of car factories is not sufficient to demonstrate this, and on the other hand, in the regions where there is no car industry, other industries play a key role in the development of both employment and labour productivity. To perform further calculations a common competitiveness indicator is formed from the three basic categories, and to contract the information contained by the basic categories principal component analysis is applied (Lengyel 2011). From the four basic categories, GDP per capita will be ignored. With the help of the three indicators on the right side of the decomposition equation, labour productivity (labprod07), the employment rate of people aged 25–64 (empr1509) and the available income of households (dispinc07), a principal component (RC) is established with the use of principal component analysis, which shall later be considered as a dependent variable: − RC contains 92,8% of the information of the 3 indicators; − Communalities: labprod07: 0,938; empr1509: 0,883 and dispinc07: 0,961. This principal component shall hereinafter be referred to as competitiveness principal component, an indicator of revealed competitiveness (RC). The indicator values are dispersed around the interval of zero, therefore the regions of negative values may be regarded as regions of weak competitiveness, while those of positive values are considered as regions of strong competitiveness. The values of regions according to the competitiveness principal component, as types specified by factor values, show sharp spatial characteristics (Figure 7). A coherent area, the ’Alps-area’ can be observed, which consists of South-German and North-Austrian regions of the strongest competitiveness. The other German and Austrian (and one of the Slovenian) regions, which may be regarded as the “middle mountains” connected to the Alps, constitute the second group (including Prague and Bratislava), which can still be regarded as being of strong competitiveness. The “hillcountry” situated east from the Alps comprise the third group, consisting of mainly Czech regions, which means just one or two smaller hills the further we get from the Alps. The fourth group is the plain, with regions of very weak competitiveness. The competitiveness principal component shows that the competitiveness of the regions depends strongly on their geographical proximity and distance from the “core”. The majority of the post-socialist countries’ regions (except Slovenia and the Czech Republic), comprising a coherent area, can be found in the fourth type of regions with the weakest competitiveness, only the capitals and some industrial regions could make it into the third type. On the basis of the factor values Northern Great Plain, Northern Hungary and Southern Great Plain stand at the three last positions among the 93 regions, followed by two Romanian regions and Southern Transdanubia. Consequently, 150 Imre Lengyel these four Hungarian regions are numbered among the weakest, the last six regions with respect to revealed competitiveness, as well. Car factories are distributed unevenly among regional types according to the competitiveness principal component: in the 17 regions of the first, strong competitiveness type there are 21 car factories, in the 34 regions of the second type there are 33 factories, in the 16 regions of the third type there are 26 factories, while in the 25 regions of the fourth type there are 11 factories. Consequently, in the regions of strong competitiveness there are relatively many, while in the regions of weaker competitiveness there are few car factories. On the basis of this it can be supposed that the European (especially German) car manufacturers regard transport distance as an important factor to be considered, on the one hand between the parent company and the plant, and on the other hand the plant and the West-European markets. The competitiveness principal component and the level of economic development (GDP/capita) are strongly related (Figure 8): the linear correlation of the two data rows is +0,8752, showing that they move strongly together. The regression curve fitting to the points is: y=2,0706 ln (x) – 9,0873, where R2=0,8752. FIGURE 7 Types of regions by competitiveness principal component Source: Own compilation. Competitiveness of Regions of Central and Eastern European Countries 151 FIGURE 8 Connection between competitiveness principal component and GDP per capita Source: Own compilation. Examining the regions together on the basis of the two indicators, the competitiveness principal component and the level of economic output (GDP/capita) it can be also pointed out that the German and Austrian regions detach themselves from the other regions. The least developed regions of the weakest competitiveness include both Central Hungary and the other six Hungarian regions, located in the bottom left quarter in the company of Romanian and Polish regions. Examining the regions together on the basis of the two indicators, the competitiveness principal component and the level of economic output (GDP/capita) it can be also pointed out that the German and Austrian regions detach themselves from the other regions. The least developed regions of the weakest competitiveness include both Central Hungary and the other six Hungarian regions, located in the bottom left quarter in the company of Romanian and Polish regions. The EU regional competitiveness index also publishes the relative competitiveness positions of the 27 member states’ regions on a scale of 0–100 (Annoni–Kozovska 2010). There is a very close relationship between the competitiveness principal component and the EU’s competitiveness index (Figure 9): the linear correlation of the two 152 Imre Lengyel data rows is +0,8738, meaning that they move closely together. The linear regression line fitting to the points is: y= 0,0499 x – 2,7014, where R2=0,8738. There are differences between the competitiveness principal component and the EU regional competitiveness index, but the closeness of the correlation is showed by the fact that these differences are not considerable. The competitiveness principal component assigns greater importance to the employment rate, while the EU regional competitiveness index processes a multitude of indicators (e.g. infrastructure, institutional system, etc.) following Porter’s methodology (Annoni–Kozovska 2010). However, the earlier observations can be repeated here as well: the competitiveness of the German and Austrian regions separate from the rest, followed by the other countries’ capital regions and the Slovenian regions (one of the two is obviously a capital region here as well). The EU’s regional competitiveness index of the four Hungarian regions of less competitiveness is between 27–29% on the scale of 0–100, while Central Transdanubia and Western Transdanubia scored 36,4% and 37,4% respectively, and even Central Hungary attained only 56,4%, besides several Romanian regions. FIGURE 9 Connection between competitiveness principal component and EU regional competitiveness index Source: Own compilation. Competitiveness of Regions of Central and Eastern European Countries 153 Up to now we have demonstrated the competitiveness of regions on the basis of data available for last year, i.e. from a static approach. It is worth to examine the change of the three basic categories, as dynamic indicators: the changes in the employment rate of people aged 20–64, in 2000–2008 (empl08-00), the growth of productivity within the sector (in the EU27’s average), in 2007/2000 (prodgr07/00), the available income of households (PPCS, on the basis of the final consumption per capita), in 2007/2000 (disp07/06). A principal component was generated by principal component analysis, which we regard as dynamic dependent variable: − The principal component contains 75,4% of the information of the 3 dynamic indicators; − Communalities: empl08-00: 0,66; prodgr07/00: 0,777 and disp07/06: 0,826. In the upper left quarter there are German and Austrian regions of strong position, but weak dynamics (Figure 10). The change of the indicators of German and Austrian regions with strong competitiveness is much less than that of the other regions, which is understandable, because high level employment for instance cannot be continuously increased. The regions of Prague and Bratislava are located in the upper right quarter, which can be considered strong according to both dimensions, but the regions of Warsaw and Budapest (Central Hungary) are not far from the border of this quarter either. The bottom left quarter, which is considered weak according to both dimensions, includes the Polish regions and Central Transdanubia (although on the edge of the quarter), the positions of which worsened in the past decade, as it was shown by several studies. In the bottom right quarter there are five Hungarian regions of weak competitiveness, which however have somewhat improved their situation, noting that the dynamic value of Western Transdanubia is only 0,24. The Romanian regions are the most dynamic, who started obviously at a very low value, but their growth accelerated in 2000–2008. Factors influencing competitiveness: Factor analysis and regression analysis The five competitiveness factors of the pyramidal model could be characterised by a very different number of indicators, therefore the relations between the competitiveness factors and revealed competitiveness shall not be examined separately. It may be noted that multicollinearity can also occur among the indicators of the five competitiveness factors, which makes correct statistical analyses more difficult (Szakálné Kanó 2008). Instead of considering which indicator belongs to which basic factor, independent factors were formed by compacting the information included in the 21 indicators by factor analysis, among which there is no multicollinearity, the remaining members are distributed normally, and there is no homoscedasticity either. Then a multivariable linear regression analysis was performed with these factors, taking into consideration the competitiveness principal component (RC), as dependent variable calculated from 154 Imre Lengyel the three basic categories. It is the advantage of this method that it makes the testing of the pyramidal model’s structure possible, as well. Its disadvantage is that the meaning of the individual factors generated in the process has to be explained afterwards with the help of the indicators included in them, and the factor structure can differ from the competitiveness factors of the pyramidal model. FIGURE 10 Connection between static and dynamic competitiveness principal component Sources: Own compilation. By performing a factor analysis on the basis of the 21 indicators five factors were generated, which contain 81,5% of the information included in the indicators. Varimax rotation was applied on the factors to form the components of the individual indicators. From among the rotated components of the factors in the absolute value the values above 0,5 were taken into consideration (Table 3). The economic interpretation and factor weight of the 5 factors are the following: − Factor 1: Human capital: human development, workforce attraction and patents (HCD), factor weight: 18,873. Human development, people moving in, high patent announcements shape this factor positively, while the proportion of people of active age and the number of hours worked affect it negatively. Competitiveness of Regions of Central and Eastern European Countries 155 TABLE 3 Factors and their components Factors Denomination Components Factor 1: HCD Human capital: human development, workforce attraction and patents eudev07 EU Human Development Index (0–100), 2007,% 0,701 mwork78 That proportion of people from the active age population who 0,684 moved into the region from outside in the past two years (from within the EU, 2007–2008,% pat1607 Patent applications to the European Patent Office (EPO), 0,614 average 2006–2007, per inhabitant age25–64 The proportion of people aged 25–64 in the total population, –0,819 2004,% The number of average weekly hours worked (in full-time job), –0,906 weeklyh10 2010, hour Factor 2: RTD fp707 gerd07 emphigh08 lisbind08 gfcf07 Research and Technological Development 7th Framework Programme, average funding per head (EU27=100),% Total intramural R&D expenditure (GERD), percentage of GDP, 2007,% Employment in high-technology sectors within the number of total employed, 2008,% Lisbon Index (0–100), 2008 Gross fixed capital formation per inhabitant (all NACE activities), 2007, Euro Factor 3: SCP povrisk08 lowedu08 unhump07 unempr09 unempy08 0,820 0,642 0,602 0,544 Social Capital: Poverty The proportion of the population subjected to poverty even after receiving social benefits, 2008,% Population aged 25–64 with low education (ISCED 1–2), 2008,% UN Human Poverty Index (between 0–100), 2007 Factor 4: SCU lunempr09 0,866 –0,733 –0,869 –0,915 Social Capital: Unemployment Share of long-term unemployment (12 months and more), percentage of total unemployment, 2009,% Unemployment rate, 2009,% Youth unemployment rate, 2008,% Factor 5: HCH Human Capital: High Education tertedu34 Population aged 30–34 with a tertiary education (ISCED 5–6), 2008,% adedu08 Population aged 25–64 with tertiary education (ISCED 5–6), 2008,% indust05 Employment in industry (% of total employment), 2005,% Source: Own compilation. 0,965 0,955 0,688 0,741 0,684 –0,881 156 Imre Lengyel − Factor 2: Research and technological development (RTD), factor weight: 17,901. The high share of the expenses spent on R&D, the high proportion of people employed in the high-tech sector, and high fixed capital generation constitute this factor. − Factor 3: Social capital: poverty (SCP), factor weight: 17,224. The factor comprising high poverty ratio, low education. − Factor 4: Social capital: unemployment (SCU), factor weight: 15,265. This factor is made up of the unemployed, among them the high ratio of permanently unemployed and young unemployed people. − Factor 5: Human capital: high education (HCH), factor weight: 12,306. The high ratio of highly qualified people has a positive effect on this factor, while the ratio of people employed in industry has a negative effect on it. From the 21 indicators 19 are connected to one of the factors, two were left out: the proportion of the people employed in services and the proportion of people participating in education and courses from the population aged 25–64. The three competitiveness factors of the pyramidal model appeared also in the factors: research and technological development, human capital and social capital (the latter divided into two-two parts respectively). From the competitiveness factors those two were not represented to which the appropriate number of measurable indicators was not found: working capital and FDI, and the traded sectors and clusters (one of their indicators joined a connected factor). Only Factor 1, human capital: human development and the proportion of people of inactive age factor became “mixed”, into which one indicator of social capital and one of research-development were also included besides the characteristics of human capital. Consequently, the pyramidal model seems to be appropriate for the systemization of factors influencing competitiveness. The results of the factor analysis can be analysed in themselves as well, however, our main aim at present is to demonstrate to what extent the competitiveness principal component (RC) as dependent variable is explained by the 5 factors as independent variables. In case of the multivariable linear regression the 5 factors explain 93,5% (R2=0,935) of the dependent variable’s (RC) dispersion. Examining integration the Durbin-Watson test is 1,571, which signifies weak negative autocorrelation by a 5% significance level. On the basis of the calculations the following model was generated: RCi = + 0,691 HCDi + 0,439 RTDi + 0,322 SCPi – 0,334 SCUi + 0,22 HCHi + Ei The regression coherence shows what effect a factor has on regional competitiveness, e.g. one unit improvement of HCD results in 0,691 improvement of the dependent variable (RC). The equation demonstrates that regional competitiveness is largely determined by human capital and research-development. While in case of social capital poverty moves in a similar direction to competitiveness, it moves in inverse ratio to unemployment. This relationship also shows that regional competitiveness is really close to the field of endogenous development, since it is moved by slow spatial social processes. While the proportion of people with high qualifications may improve in a Competitiveness of Regions of Central and Eastern European Countries 157 decade or two, the modification of more characteristics of the social capital in a given case requires a time period of more generations. Factor 1 (human capital: human development, workforce attraction and patents) exerts the greatest influence on regional competitiveness. This means the high standard of human capital, since in Europe the developed metropolises are generally the destinations of migration, which provide workplaces and high income. However, Factor 1 is influenced in inverse direction by the proportion of active aged people (25–64 years old) and the average weekly hours worked, probably because there are less working hours in the competitive regions, and the proportion of young and elderly people is higher. The spatial distribution of the values of Factor 1 (human capital: human development, workforce attraction and patents) shows a west-east slope (Figure 11). Here, too, the German regions are at the top, but in a different way compared to that of the competitiveness principal component: almost two thirds of the German regions constitute the strongest group, especially in the western and central parts of the country. The second group also includes German and Austrian regions, while in the third group German and Austrian regions (Vienna and Carinthia) appear besides the regions of post-socialist countries. The weakest type consists of Polish and Romanian regions, but Czech (including Prague), Slovakian (Bratislava) and the Slovenian region also belong here. FIGURE 11 Types of regions by human capital factor Source: Own compilation. 158 Imre Lengyel It becomes also apparent that there is hardly any difference between the 7 Hungarian regions according to Factor 1, from the international point of view regional differences perceived in Hungary are less conspicuous in this indicator group. Car factories are relatively evenly distributed in the regional types according to human capital factor: in the 23 regions of the first type of strong competitiveness there are 19 car factories, in the second type’s 21 regions there are 27, in the third type’s 34 regions there are 30, while in the fourth type’s 15 regions there are 16 factories. Examining the relation between the competitiveness principal component and Factor 1 results in the delineation of two types of regions (Figure 12). In the right upper quarter there are only German and Austrian regions, while in the left bottom quarter there are the regions of the post-socialist countries (with the exception of a few capital regions). This also means that the previously observed two regional types, moving on two different tracks of development, detach from each other even according to Factor 1. Considering Factor 1, the Hungarian regions are in a much better position in comparison to their revealed competitiveness, since they come directly after the German and Austrian regions. Consequently, the human factors at home are more developed than what is shown by revealed competitiveness (Lengyel–Ságvári 2011). FIGURE 12 Connection between competitiveness principal component and human capital factor Source: Own compilation. Competitiveness of Regions of Central and Eastern European Countries 159 Factor 2 also has a serious impact on regional competitiveness: assistances won from the EU research funds, gross expenses spent on R&D, the number of people employed in the high-tech sectors. It can be unequivocally stated that regional competitiveness depends largely on the magnitude of R&D, the expansion of knowledgebased, innovative economies (Bajmócy–Szakálné Kanó 2009). The types of regions according to the human capital factor are spatially much more dispersed than they used to be (Figure 13). It can be observed here as well, that the German and Austrian regions are at the top (with Prague and one Slovenian region), but they are much less in number, and form an “island”, not a block. The German and Austrian regions dominate also in case of type 2, plus out of the 7 Hungarian regions 5 are listed here (together with Bucharest and Vienna), and 2 out of 4 Slovakian regions, too. The third type can be found almost consistently in all countries, while the fourth group includes Polish and German regions. FIGURE 13 Types of regions by R&D factor Source: Own compilation. It is a characteristic feature of the R&D activities that they are spatially concentrated, and with their global connections they are connected not to their direct neighbours, but to professionally outstanding partners located anywhere in space. Among the regional types according to Factor 2 car factories display concentration characteristics: in the 13 regions of the first type of strong competitiveness there are 22 car factories, in the 23 regions of type two there are 19 factories, in the 48 regions of type three there are 46 factories, 160 Imre Lengyel while in the 9 regions of type four there are 4 factories. Consequently, in those German and Austrian regions where there is a high portion of assistance won from EU research funds, gross expenses spent on R&D, and people employed in the high-tech sectors, there are significantly more car factories. Examining the connections between the competitiveness principal component and Factor 2 results in a spatial structure slightly different than what it used to be earlier (Figure 14). The German and Austrian regions of strong competitiveness are dispersed in a very wide band according to Factor 2, and part of them is even in a situation similar to the regions of the post-socialist countries. The latter regions can rather be found in a block, in the bottom left quarter. Considering the 93 regions the Hungarian regions are situated in the middle, leading the field among the post-socialist countries’ regions. Consequently, considering Factor 2, the Hungarian regions are in a much better position in comparison to their revealed competitiveness, overtaking among others German and Austrian regions. FIGURE 14 Connection between competitiveness principal component and R&D factor Source: Own compilation. Competitiveness of Regions of Central and Eastern European Countries 161 The investigation of the 21 factors influencing competitiveness with the help of factor analysis and regression analysis points out that human capital and research and technological development have a very serious influence on regional development. Whereas considering human capital the German and Austrian regions excel, on the basis of research and technological development more regions of the post-socialist countries reach the middle field. According to these two factors the Hungarian regions belong to the middle field, the leading group of the post-socialist countries’ regions. Summary In our study the newest trends connected to regional competitiveness were reviewed, from which the theories of endogenous growth and development were highlighted. Nowadays these trends describe the growth and development taking place under the conditions of global competition, therefore in the course of economic development aimed at the improvement of regional competitiveness, the development of a strategy built on local characteristics, organized from below is required. Human capital and social capital constitute the most important factors, which though may be centrally encouraged, are intrinsically connected to a specific place and may be exploited locally. The redefinition of the pyramidal model was introduced to interpret, measure the concept of regional competitiveness and demonstrate its influencing factors, in which besides human and social capital, traded sectors are also included. Multivariable statistical procedures were applied to demonstrate the correspondences, examine the database compiled from the data of the 93 regions of the 8 Central and Eastern European countries. Due to the difficulty of obtaining international data, the database generally contains data from the years 2008 and 2007, i.e. shows the situation before the global crisis. From the results we point out that the competitiveness of the German, Austrian and Slovenian regions is in every respect considerably stronger than that of the other countries’ regions, only the capital regions may be numbered among them. Regions of strong competitiveness cluster spatially, and the regions of the following type are located in their neighbourhood, in their geographical proximity. With respect to the Hungarian regions, with the exception of Central Hungary all the other Hungarian regions belong to the regions of the weakest competitiveness in almost every respect. Four of our regions (Southern Transdanubia, Northern Hungary, Northern Great Plain and Southern Great Plain) constitute a separate group, they are the lasts not only in employment, but they are of the weakest competitiveness according to the competitiveness principal component, falling behind even the Romanian and Polish regions. The situations of Central Transdanubia and Western Transdanubia are slightly better; their competitiveness approaches that of the medium Czech regions. The spatial distribution of car factories is more or less even in the three stronger types, whereas there are few factories in the regions of the weakest competitiveness. 162 Imre Lengyel The results of the factor analysis and the regression analysis show that although the competitiveness of the domestic regions is weak, on the basis of human capital and R&D, the factors determining future competitiveness, there is hope for their situation to improve quickly. In other words, although both employment and labour productivity are of a low level in the domestic regions, the network of research institutes and the preparedness of the work force would enable a significantly quicker rated economic growth. The revealed competitiveness of the Hungarian regions lags behind in comparison to the regions of the post-socialist countries, but overtakes them on the basis of the mentioned potential development factors. Consequently, the potential conditions of the improvement of regional competitiveness are given; the question is whether the national economic, regional development policy can properly take advantage of them. References Annoni, P. – Kozovska, K. (2010) EU Regional Competitiveness Index. European Commission Joint Research Centre, Luxembourg. Bajmócy, Z. – Szakálné Kanó, I. (2009) Measuring the Innovation Performance of Hungarian Subregions. – Bajmócy, Z. – Lengyel, I. (eds) Regional Competitiveness, Innovation and Environment. 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(2008) Regressziószámítás alkalmazása kistérségi adatokon (Hungarian). – Lengyel, I. – Lukovics, M. (eds) Kérdőjelek a régiók gazdasági fejlődésében. JATEPress, Szeged. pp. 264–287. Vas, Zs. (2009) Role of Proximity in Regional Clusters: Evidence from the Software Industry. – Bajmócy, Z. – Lengyel, I. (eds) Regional Competitiveness, Innovation and Environment. JATEPress, Szeged. pp. 162–182. WEF (2010) The Global Competitiveness Report 2010–2011. World Economic Forum, Genf. COMPETITIVENESS OF THE VISEGRÁD COUNTRIES’ COUNTIES FROM THE ASPECT OF AUTOMOTIVE INDUSTRY MIKLÓS LUKOVICS – PÉTER SAVANYA Keywords: automotive industry economic area localization Visegrád Countries competitive ranking of NUTS3 territorial units The car industrial regions of the Visegrád Countries (Czech Republic, Poland, Hungary and Slovakia), encompassing the area of Central and Eastern Europe, form an integral part of the new structure of European car manufacturing which is expanding due to economic integration. The localization of this industry is being shaped by numerous global and industry specific factors in the expanding economic space: supplier networks that are becoming global, regionally organized manufacturing structures, and macro-regionally integrated markets. The dominant participants of this industrial sector’s concentration, the car manufacturers and their strategically important technological and supplier partners lead the networks being built in the sector, in which the process of outsourcing and specialization are observable both at the level of companies, certain sector activities, and the spatiality of the industrial sector. The competitiveness of the regions, the available resources, and the characteristics of the company competition edge in a given region interpreted by Porter can essentially determine the role of car industrial territories in the sector’s structure. Therefore the measurement and comparison of regional competitiveness raises important questions from the viewpoint of automotive industry as well, either the positions of the car industrial districts of given regions are evaluated in the sector, or the concepts of economic development going in this direction. The purpose of the present essay’s section on automotive industry is to provide a theoretical frame to consider how the results of the competitiveness analysis of the counties of the given countries can be interpreted in assessing the relative competitiveness of the car industrial regions of Central and Eastern Europe. Introduction The globalization processes of markets and industrial sectors, which characterised the past three decades, constitute a generally accepted statement in regional economics (Lengyel 2003). The development of logistics and IC technologies enabled the formation of (global) production systems spanning great geographical distances, while also on the side of consumption and market new consumer and cultural trends crossing geographical borders prevail (Lengyel 2010). According to several approaches the process of globalization has fundamentally rearranged the economic-geographical look of automotive industry. Some of the doubtlessly common attributes of industrial sectors participating in globalization is the establishment of global production systems and the organization of market structures spanning borders (Dicken 2007). The establishment of global production chains and 166 Miklós Lukovics – Péter Savanya integrated markets were catalyzed by the expansion of commercial and investment activities liberalized within the frames of international agreements, and parallel to this, by the expansive institutionalization of economic integrations (e.g. ASEAN, EU, NAFTA). The multinational activities of car industries and the vindication of their business interests played an active part in the building of economic integrations and their legal institutionalization (Heribert 2007). The increasing practice of outsourcing and the establishment of value chains based on new, cooperative connections are other common characteristic features of these industrial sectors (Bieserbroek–Sturgeon 2010; Chanaron–MacNeill 2005). As a result of this, the car industrial supply companies of the developed countries increased their activity in both commerce and capital outsourcing, while on the other side, in the developing countries the industrial sectors performing supplier activities underwent an enormous (mainly quantitative) development (Humphrey–Memedovic 2003; USITC 2010). Industrial suppliers operating in developed countries became global corporations, with multinational presence and global potential to serve a wide circle of affiliated companies (Bieserbroe –Sturgeon 2010; Chanaron– MacNeill 2005). In the economic mapping of automotive industry, the investigation of globally organizing sector production systems and integrated market structures, however, a conceptual definition has to be introduced that will assist us in the interpretation of the sector’s described characteristics. Dicken (2007) and Florida–Sturgeon (2000, 19-20) in the conceptual definition of global economy differentiates between internationalization processes and globalization processes. Internationalization processes mean that economic activities cross borders, go beyond the institutional system of national economies. This can be interpreted as a quantitative change, within the frames of which the geographical borders (districts) of economic activities expand, making connections between (national) economies. On the other hand, the processes of globalization can be portrayed as a qualitative change. Moving beyond internationalization, (international) economic activities crossing national borders form functionally integrated systems. Within the frames of globalization, the activity of the individual economic actors (corporations) constitutes an internationally coordinated (organized) process system. Besides the above mentioned processes, however, the structure of automotive industry is characterised by numerous facts that established value chains built on regionally defined markets and functioning in global-regional production connections in the industrial sector. − Concentration: It is a characteristic feature of automotive industry that it is marked by an extremely concentrated corporeal structure: a few giant corporations established in the course of acquisitions and purchases dominate the industrial sector.1 Parallel to the increased concentration of corporations and the car industrial sector, the standardization of technological and business practices of the industrial sector can be observed. The planning of conceptions built on a common platform, and the modular production practice of certain model-designs diversified by markets and segments built on this, or the application of JIT production systems can be mentioned here. In the competition between car The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 167 manufacturers the efficient and system-based process management became a key factor in every field of corporeal activity (technologies, product and design development, production technologies, production and market organization, marketing innovations, the observation of industrial sector and partnertechnologies, the adaptation of sector’s best practice) (Lorentzen 2011). − Production capacities installed in the markets: The end-product manufacturing phases of the production processes – which in this case mean the final assembly (manufacturing) of the automobiles – and in a wider sense the manufacturing of the component-modules are installed in the vicinity of the distribution’s target markets. The reasons for this are partly political, and can partly be explained by the markets’ peculiarities, as it will be seen below. The fullness of markets, the proliferation of motorization, the “produce where you can sell” market behaviour of car manufacturers resulted in the trend that the corporations spread the production infrastructures to more countries of the world than they had done before. − Regionally organizing industrial sector structures: Automotive industry is characterized by strong regional market differentiation. Although automotive industry has increasingly progressed towards global integration since the 1980s, the integration resulted in a powerful regional sector pattern. Concentration characterizes mainly the sector’s business structure, and the company strategies determining the sector’s laws of movement. The production capacities installed in the markets and the regionally organizing industrial sector structures established the economic-geographical look of the industrial sector as the mirror images of each other, in a parallel way. The automotive industry of Europe, and thus the automotive industry of Central and Eastern Europe, the Visegrád Countries, is determined by these economic and industrial sector power lines (macro-regional economic integration, outsourcing and activity localization). The establishment of the institution system of the EFTA (European Free Trade Association), Central-Europe’s European economic integration starting in the 1990s and gradually expanding to the east has made these countries’ economic resources relevantly available for car manufacturers.2 Car manufacturers installed their production-assembly units based on the workforce available in the region which is considerably cheaper than the national base, channelling them into the production and market structure of European automotive industry, as well as into the macro-regional supplier systems built on global resources. Macro-regions in automotive industry As defined by Bieserbroek et al. (2009) the economic map of the world’s automotive industry shows a quasi temporary picture between globalization processes and national markets, which corresponds to the previously described conceptual definition. On account of globalization changes, the national type position of the industrial sector (connected to national character) has transformed in certain parts into a globally inte- 168 Miklós Lukovics – Péter Savanya grated system. These global integration processes embedded the actors of automotive industry into a network of globally impacting production, market systems. This global system is constituted by stably established regional systems (regions growing out from the integrations of national economies) at an operative level. The diversity of market demands, and the growth oriented pressure of reaction-adaptation requires the elaboration of new models and solutions meeting the demands of a defined market.3 Perhaps the primal motive for the establishment of regionally organized sector structures is the process of macro-regional economic integrations, the merging of markets and parallel to this, the centre-periphery organization of company processes. Summing up the previous conceptual definitions, the sector value chains coming into being within the industrial sector are internationally active, while the activities connected to the individual territories are characterized by globalization. On the side of the industrial sector markets, besides the new possibilities of emerging markets, the significance of the (national) bases remained dominant for the “traditional” car industrial districts (EU, USA) and individual car manufacturers (Figure 1). Regional embedding has a very strong effect, regarding production sales ratios, which still reflect the dominance of “basis regions”. The smaller rearrangements in production and sales observable in the recent years mainly reflect the organization of interregional production forms and the increasing freedom of world trade.4 FIGURE 1 Global trade flows in automobiles in 2004 Note: Trade flows in billion USD Source: Dicken (2007, 304). The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 169 On the production side we can also find strongly regional systems with global characteristics, which tendency has been strengthening since the 1980s. Car manufacturers and their multinational supplier partners operate in a global context consisting of multi-regional systems. In the operative working of the production chain the component producing and supplier system installed into a particular local region supplies regional manufacturing markets. Outsourcing and FDI activity, which is regional or aimed at the peripheries between regions, can also be considered a general trend, utilizing cheap production and operational costs (the relationship of USA–Mexico in North-America; Spain and Eastern Europe in Europe, Southeast-Asia and China in Asia). Regional organizations are strengthened by political and commercial pursuits both within and outside regions. In many cases automotive industry is iconic in the eye of the public (e.g. organized trade union and industrial lobby). The import products and the sharpening, crowding competition may trigger strong political counter-reactions against a car manufacturer wishing to enter the market, which may hamstring the taking of new markets for the new importer manufacturer. This effect is especially significant if domestic car production represents a traditional national brand, a significant industrial potential bearing national characteristics and an employment base. On the other hand, the economic-political regime and the public (trade unions) welcome manufacturers entering the market as investors and creators of workplaces more warmly. In spite of the expansion and integration of trade zones (e.g. WTO), in line with these considerations car manufacturers establish local production units in the regions, instead of exportoriented distribution, “crossing” thereby the obstacles of the political and economic environment.5 The expansion and borders of the socio-technological space can be defined as a regional integration force, which constitutes an important element in the operative working of the corporations’ production and manufacturing strategies. The forms of cooperation norms and coordination play a basic role in the building of company connections, and the efficient operation of production chains, (JIT) production process systems. The role of incoming and outgoing logistics in the operation of production systems based on modern JIT principles constitutes an additionally important factor. In this kind of operation of supplier and logistics connections expected by car manufacturers the suppliers localize their activity near the manufacturers, ensuring thereby the expected flexibility in the production chain. On the whole it may be said that component part production takes place in global dimensions, while the modular production processes operate in the regional network of manufacturers installed in the target markets and suppliers. The localizations of automotive industry in the economic space Automotive industry dominated by a few companies, similar to many other sectors, is characterized by increasing and dynamically changing competition, which is (was) doubtless catalyzed by globalization. For companies the conscious definition and development of competitive advantages constitute key factors. The geographical locali- 170 Miklós Lukovics – Péter Savanya zation of competitive advantages (in the Porterian sense) and company activities shows a close connection (Freyssenet–Lung 2004b; Porter 1990), which reinforces the significance of the concept and investigation of regional competitiveness in the evaluation of the automotive industry of the Visegrád Countries, in the situational analysis of car industrial districts. In their survey, in the course of the typification of the localization of automotive industry Florida–Sturgeon (2000) differentiated between four types according to the motivation of the companies’ activities, and the qualitative evaluation of localization. The typification demonstrated by them can be analysed on the basis of localization viewpoints (Bernek 2000) (Table 2). “Nowadays the most important territorial level is the global economy itself. The most important elements and tendencies of world economy globalization are organized and prevail at this territorial level: a remarkably quick technological, especially communication technological development; transnational companies and international production organized by them; and a never before experienced acceleration of the role and importance of money” (Bernek 2000, 89–90). Starting from the previously defined qualitative meaning of globalization we can say that the spatial lines of economic organization are drawn by the spatial flows taking place between internationally active economic actors (in our case the companies of automotive industry), while the principles of spatial organization are characterized by the organizational principles of the flows. These flows include both physical (the physical content of products and services), and virtual (services and information) flows. Following this line of thought in the investigation of the spatial organization of car manufacturing, the value chain modelling the flows of the industrial sector and the actors (companies) defined behind the flows and the characteristics of their connections may serve as a pivot for the evaluation of the organization of position, localization in the heterogeneous (global) economic space. In other words, why certain company activities land at particular points of determined characteristics in the economic space, along what principles certain activities (companies) make their localization decisions. In this chapter, we are going to look at the company strategies spanning the automotive industry and their impact on the industrial sector as a whole following this line of thought. The sector value chain described by Humphrey–Memedovic (2003, 22) characterizes the companies of this industrial sector and their strategies in a comprehensive way. These correspondences of economic space and automotive industry provide a practical viewpoint and frame of interpretation to the county level regional competitiveness analysis of the Visegrád Countries. Our aim is to outline a comprehensive evaluation approach on the regions’ competitiveness situation from the viewpoint of automotive industry as well. The production and business structures of automotive industry have undergone fundamental changes in the mirror of the processes consummating from the 1980s, global and regional processes equally characterize the changes of the production structures of automotive industry. The globalization processes and newly established production systems, company outsourcing and specializations rearranged and reinterpreted the The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 171 place and role of the actors of the automotive industry value chain.6 The linear perception of production processes was more and more replaced by an integrated value chain, and the adaptive cooperation of the actors in it (Figures 3–4) (Grosche–Schmid 2008). TABLE 2 Typification of OEM’s locations Florida-Sturgeon typification Localization viewpoint Strategic intent Capacity level Wages Development Level of integration Level of background industry Export Type 1 Type 2 Closeness of marCloseness of kets, company markets, company competitive competitive advantages advantages (capabilities) (capabilities) High High High High Yes In some cases High High Type 3 Type 4 Cost cutting, rationalization, efficiency Covering of markets High Low No Medium Low Low No Low High Medium-to-high Medium Low Low (except Japan) Low High Low (General) Typification of Dunning’s eclectic theory Type of interna- Vindicating stratetional investgic advantages ment Market-oriented Increasing efficiency Exploiting local resources Long-term strategic Increasing market aims, sustaining (global, regional, international local) success, controlling local competitiveness market Localization The above factors Cost differences, and the competimarket size and advantage tiveness of the type, government given territorial politics level Internalization Competitive and Decreasing transacstrategic advan- tion costs, adjusting advantage tages, risk to local demands decreasing, controlling of markets Ownershipspecific advantage Rationalization of Increasing comexisting investments petitiveness Production speciali- Differences in the zation and concen- costs of production tration of national factors economies Vertical company Price regulation, integration – direction, controlcompany value ling of markets chain Source: Own compilation based on Bernek (2000, 95) and Florida–Sturgeon (2000, 13). 172 Miklós Lukovics – Péter Savanya The value chain of automotive industry is characterized by global supplier connections and production and marketing processes localized in the regions.9 The schematic diagram of regional structure embedded in a global context that is being built in automotive industry is illustrated on Figure 5. As several essays analysing the localization and spatial differentiation of the industrial sector point out (Bieserbroek–Sturgeon 2010; Chanaron–MacNeill 2005; Freyssenet–Lung 2004a; Freyssenet–Lung 2004b; Haiss–Mahlberg–Molling 2009; Heribert 2007; Humphrey–Memedovic 2003; Haiss–Mahlberg–Molling 2009), the spatial localization of automotive industry is decisively determined by the installation decisions of car manufacturers (see before Florida–Sturgeon (2000) and Dunning’s typification). FIGURE 3 Value chain and organizational structure of the automotive industry Product-Design planning and development Material production 3 3 3 Design and engineering companies CAR MANUFACTURER Financial and investment partners 2 3 2 3 2 1st tier supplier and technological partner Agencies Distributors and traders Service providers Source: Own compilation based on Bieserboeck et al. (2009, 16). component production Production of modules, subassemblies Assembly Marketing Distributionn After-sales services The Competitiveness of the Visegrád Countries’ Counties from the Aspect… FIGURE 4 Restructuring of the car manufacturing pyramid Source: Grosz (2000, 128). FIGURE 5 Regional structures of car manufacturing Basis (carindustrial district) Technological, design and devolpment centers (carindustrial district) Production Regionally localized units of compnents-modules assembly (carindustrial districtcts) Global outsourced processes (componenets, etc.) Regional market and production strutures Source: Own compilation. 173 174 Miklós Lukovics – Péter Savanya In the industrial sector, the 1st tier supplier and strategic partners, as global companies at the same time, localize their own functional units near the car manufacturers’ units (plants) in order to make use of the advantages of spatial closeness. For the 1st tier supplier the car manufacturer is the client, so the values of the advantages of spatial closeness rise in the efficient service of the car manufacturer, the support of the processes. This advantage has a special significance in the process management of modular production built on JIT principles. This tendency is referred to as the phenomenon of co-localization in literature. This tendency is unequivocally described by Florida–Sturgeon (2000) when examining the temporal closeness of car manufacturers and the plant establishment of the 1st tier supplier integrating the supply base (Florida– Sturgeon 2000, 64). This effect is especially strong in case of the automotive industry’s new localization built on global principles, which in the course of the past 20–30 years meant the industry’s outsourcing of production and supplier capacities into peripheral regions. The supplier integrator can either lean locally (at a territorial level) on the established supplier network (tier 2, tier 3 supplier), or on his globally organized own channels (global link). Car manufacturing localization should not be interpreted as the static places of production processes connected to the industrial sector, but rather in the networks defined by Bernek (2000), the position of the value chain’s functional subsystems (as a subnetwork built from factors) in the differentiated economic space. In this definition of the localization of car manufacturing the concept of place is rather replaced by geographical expansion and the concentration of a network (car manufacturing district). In the value chain of automotive industry (see before) the individual functions are supplied by a network of subsystems built at certain points of the economic points. The strategic directors of this global production system are the car manufacturers (OEM) and its integrator organizers are the 1st tier suppliers. The other actors of the network and the subnetwork located in space (tier 2, tier 3 supplier) take part in the car manufacturing value chain connected to them. The competitive advantages taken in the Porterian sense and the geographical localization of company activities show a close connection (Freyssenet–Lung 2004b; Porter 1994). A company’s competitive advantages defined in Porter’s diamond model can be seen well at the different levels of the value chain, which also explains the locality of activities (company localization), the industrial sector map reflecting firm strategies. The company activities exploiting high level competitive advantages (technology and innovation, financial connections) centralize in developed areas capable of establishing specialized factors. In a region the activities requiring the closeness of the market and the coordination connected to the company are located on the peripheries, which are mainly built on companies capable of fulfilling the appropriate functions of the value chain, and workforce that has the necessary qualifications, but costs less. The localization of these company activities are motivated by the basic factors, and the availability of a few special factors, which are important from the viewpoint of the company’s activity. In car manufacturing, besides the appropriately built basic infrastructures the special factor is constituted by the area with technological-industrial culture/past and the The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 175 workforce of the appropriate basic qualification. Standardizable and mass production activity are globally outsourced.7 In the interpretation of a region it shall be emphasized that in the localization of the activities, the competitive advantages available in the different territories of the individual regions and the localization possibilities of the companies capable of exploiting them were expanded by the development of traffic infrastructures and coordination techniques (process organization, computer and data transfer technologies, etc.). This way the regional production structures which used to characterize car manufacturing in earlier times constitute systems spanning whole continents with the appropriate level of coordination. Positions of the Visegrád Countries in the car manufacturing of Europe European car manufacturing is characterized by both global processes discussed earlier and regional structures. The biggest change of the region’s car manufacturing industry was the integration of the Central and Eastern European economy, which simultaneously brought changes of global origin into the industrial sector and dislocation in the region’s car manufacturing localization, which are emphasized by the industrial sector analyses and the theoretical literature everywhere (EC 2002, Freyssenet–Lung 2004a, Freyssenet–Lung 2004b, Haiss–Mahlberg–Molling 2009, Heribert 2007, Radosevic–Rozeik 2005). With respect to globalization the integration of these countries into the European economy created a bridge, a gate of entry into the Western-European markets for Asian car manufacturers (Toyota, Kia, Hyundai, Suzuki), who, as FDI investors, built production capacities in the region’s countries. The cars manufactured and assembled here were not burdened by import obstacles, and the properly qualified workforce available in these countries, which is much cheaper than in the west, and makes production possible directly for the European markets, provided a serious market possibility, which the Asian manufacturers did exploit. On the other hand, as a result of the economic convergence processes these countries are potential and growing markets for car manufacturers. The production and supplier networks of the European car manufacturing industry were substantially restructured in the last twenty years by the economic integration of the Central and Eastern European countries, which process is still going on nowadays (Haiss– Mahlberg–Molling 2009). The European car manufacturers built new component and production capacities to exploit the competitive advantages available in the area: based mainly on a low-income, but appropriately qualified workforce, and utilizing the industrial structures capable of adapting production technologies. (First in Poland and the Czech Republic, as well as in Hungary, and later in Romania, and we also have to mention Turkey, which became one of the greatest car manufacturers of the world.) In these economies governments and economic policies sought to accept significant direct and 176 Miklós Lukovics – Péter Savanya indirect assistance and attract these investors in order to promote economic close up (Haiss–Mahlberg–Molling 2009; Radosevic–Rozeik 2005). The appearance of Asian manufacturers in Europe altered the structure of European car manufacturing structures. The European supplier networks, built on the chain of industrially independent companies for the utilization of the Japanese modular production technologies, developed systems supporting modular production technologies, localized their operative units in the vicinity of the production and assembly units established in Eastern-Europe. These newly built systems had an effect on the transformation of both Asian and European car manufacturing systems.8 Today the European production structure is characterized by those innovative supplier integrator-partners, who support the establishment of systems between manufacturers and suppliers. The modular and component supplying companies worked out special competences, taking over this activity from car manufacturers. Since the end of the 1990s the systems of these specialized, independent companies have served as the supplier bases of car manufacturing value chains (Heribert 2007). In Europe the presence of the specialized small and medium supply companies further strengthened the outsourcing processes. With the progress of integration these enterprises formed networks, giving rise to syndicated product development and joint production capacities. The building of these systems is enhanced by cluster-based policies, and the institutional support of network innovations (Heribert 2007). Considering the whole region, the localization of car manufacturing industry is determined by the interwoven processes of specialization and clustering (EC 2002): − Specialization appears in the marketing and production strategies of car manufacturers, to exploit the expansion of markets relevantly available for the whole industrial sector, and entering these markets. − The economic and territorial process of car manufacturing’s industrial clustering is decisive in Europe, especially in the integrated economic space of the EU. Notwithstanding, the cluster-based economic policies replacing the modern industrial sector approach and the EU policies encourage the establishment of the dynamic competitive advantages of the industrial sector concentration and networking connected to the economic space, emphatically supporting the development of clusters. The integration process of the regional car industrial structure was assisted by the expansion of international and interregional trade within Europe, which strengthened the specialization of production processes and potentials. This process is especially well reflected by the localization of the assembly plants of car manufacturers, which is motivated by platform-based model production and marketing strategies, and the installation decisions building on the given region’s capabilities (Figure 6). The economic structure of the industrial sector reveals a rearrangement due to the explosive development of the Central and Eastern European component and modular subassembly production, although the centre-periphery relationships are still persistent, the differences are significant. The leading developed Western car industrial areas in The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 177 Europe clustered by the establishment and exploitation of competitive advantages preserved their position in the industrial sector, sustaining their technological and market advantages through established and operating manufacturer-supplier connections and efficient innovation networks (EC 2002). As we have seen earlier, considering the nationality of basis markets and car manufacturers, the base country has a decisive role in the capacities of individual car manufacturers, with respect to either the number of manufactured cars, or the number of employees. FIGURE 6 Localization of the automotive industry in Europe Key: 1 – ACEA-tagok (BMW, DAF, Daimler-Chreyler, Fiat, Ford, GM, MAN, Porsche, PSA Peugeot-Citroen, Renalult, Scania, Volvo, Volkswagen Ag.); 2 – Nem ACEA-tagok (főként kelet-európai és néhány nyugati kisebb gyártó); 3 – Japán gyártók (Honda, Isuzu, Mitsubishi, Nissan, Suzuki, Toyota); 4 – Koreai gyártók (Daewoo, Hyndai). Source: ACEA (2008). 178 Miklós Lukovics – Péter Savanya The 2002 analysis of the EC states that the production units and regions, which came into being in Southern-Europe, especially in Spain as a result of the companies’ outsourcing strategies in the 1980s, still have a significant industrial sector role in European car manufacturing. When the European economic integration started, these areas represented the outsourcing destinations of labour-intensive or standardizable (mass production) activities, and assembly activities. Governments actively supported working capital investments, and announced economic development and regional development programs based on the presence of automotive industry. As a result of the investments, industrial capacities related to car manufacturing and connected potentials came into being in individual regions, car industrial districts and areas were formed. The assembly and production networks established here, besides the car industrial proliferation of the areas newly joining the European integration, have the edge owing to the already established and working regional car manufacturing and supply networks. Cohesion resources and community economic policies encouraging clustering have also promoted this process, which means the countries of Central and Eastern Europe have had for less than ten years. From the almost one decade perspective of the report we can say that the competitiveness of this area has worsened as a consequence of disposing government policies, which increased the standard of wages by raising internal consumption in a proportion that is bigger than the increase of productivity.9 The automotive industry of Central and Eastern Europe displays a continuous development, which continues further in the period after the crisis (Haiss–Mahlberg– Molling 2009). The institutionalization of clustering can already be seen, although its functional operation approaches the level of development of car industrial regions operating in the west only in one or two regions (mainly in the Czech Republic). In case of the Visegrád Countries, and especially the regions of Western Transdanubia, Central Transdanubia and Central Hungary, the creation of the local embedding of car manufacturers is a key question from the viewpoint of the area’s automotive industry and regional economic development. It is important to make steps in this direction. The former appeal of the area, the lowly paid, but appropriately qualified workforce providing a competitive advantage for car manufacturers, and the vicinity and good accessibility of Western-Europe constitutes less of a competitive advantage nowadays.10 With the lack of an established local supply base, a major part of the added value of the assembly car manufacturing depending on import supply chains comes from outside of the region. Its economic impact, excluding the numbers of the export macroeconomic GDP, does not really go beyond the factory gates. The small and medium enterprises of the region incorporating as suppliers into the value chain of car manufacturing can literally connect the car manufacturer’s activity to the region. The added value connected to the area’s economy, the creation of workplaces and wages make the multiplicator influences prevail. The region’s knowledge and innovation potential has an important role in drawing car industrial activities of high added value into the region, and the conscious establishment of industrial sector connections, the formation of networks, and the dynamization of the regional innovation systems are also decisive (Blöcker–Jürgens–Heinz 2009; Dimitrova–Stratmann 2008). The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 179 Placing the Visegrád Countries in the system of European automotive industry and economic space, we have to expand the concept of the macro-region of automotive industry even beyond the borders of the widened European Union. The process of economic integration, the business connections and production chains cover a much larger territory in the EFTA system than the institutional borders of the Union. Consequently, from the viewpoint of automotive industry, the competitiveness indicators of the counties of the four Visegrád Countries have to be placed and evaluated in a much larger context. The analysis of competitiveness based on the pyramid model gives a relative picture about the countries’ counties. Interpreting the competitiveness of the territorial units of the macro-region that is Central and Eastern Europe, important consequences can be drawn with respect to automotive industry as well. The comparative analysis points out the situation of our country’s counties and their positions in the competition of the Central and Eastern European regions, showing what level of company advantages the economies of the individual territorial units are capable of creating. The analysis extending to the counties of the Visegrád Countries provides a comparative picture about the relative competitiveness of the Central and Eastern European regions. Utilizing the earlier described industrial sector strategies and structures as a theoreticallogical frame, the analysis of the region’s competitiveness can provide important lessons about the positions and the direction of development of particular local regions and the car industrial districts localizing in them. Empirical analysis The purpose of the analysis is to investigate the competitiveness of the Visegrád Countries at NUTS3 level, and to rank the competitiveness of these levels. To do this, first the indicators and the model on which the investigation is based shall be introduced, followed by the methods applied. Frames of investigation The uniform definition of competitiveness and the pyramid model elaborating it serve as the basis of our investigation. The applicability of the model requires the availability of the appropriate indicators. This means that each category of the model should be characterized by a commeasurable index-number. This proved to be difficult. In the course of empirical investigations only those indicators can be applied which in their content mean the same for each territorial unit, i.e. the index number expresses in content the same in the different countries. Consequently, in the course of the analysis only the EUROSTAT data could be used. Furthermore, the circle of these indicators is fairly narrow, so in case of certain categories of the pyramid model there are 4–10, while in case of other categories there are absolutely no data available at NUT3 level. Consequently, only a part of the pyramid model may be applied for analysis, in such a way that the pyramid should not tilt. In the first approach this means two things. On the 180 Miklós Lukovics – Péter Savanya one hand, all categories shall be applied at the given level; on the other hand, the number of indicators describing the individual categories shall be in balance. We reached the conclusion that in the first approach only the topmost level of the pyramid will be used for analysis, i.e. the basic categories (wages, labour productivity, employment), in a way that each category will be described by maximum 2 indicators. Then we will compare the results with the index-numbers describing other, not applied categories of the pyramid model (Table 2). Since more indicators are applied collaterally, the multivariable statistical procedures can be used as basic methods. Firstly, we would like to set a competitive ranking for the investigated territories on the basis of the indicators describing the basic categories. For this one-dimensional scaling a special case of multidimensional scaling will be used. And finally the result of the ranking shall be used with the other indicators. Secondly, we will group the investigated NUTS3 units with the help of cluster analysis. Then the established clusters will be typified, characterized. TABLE 2 Indicators used in the analysis Indicators describing basic categories Indicators used for further characterization, typification GDP per capita at market price in the average percentage of the EU, 2008 Gross added value per employed person, million Euro/capita, 2008 Unemployment rate,%, 2008 Employment rate,%, 2008 Population growth in comparison to the previous year,%, 2008 Migration change in comparison to the previous year,%, 2008 Life expectancy at birth, year, 2008 The share of agriculture, fishing from the territory’s gross added value,%, 2008 The share of industry, excluding building industry from the territory’s gross added value,%, 2008 The share of building industry from the territory’s gross added value,%, 2008 The share of services from the territory’s gross added value,%, 2008 The share of wholesale and retail, hotels and restaurants, traffic from the territory’s gross added value,%, 2008 The share of financial mediation, real estate services from the territory’s gross added value,%, 2008 The share of administration, community service from the territory’s gross added value,%, 2008 The number of enterprises per 1000 inhabitants Activity rate,%, 2008 Gross added value per capita, million Euro/capita, 2008 Source: Own compilation. The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 181 Multidimensional scaling (MDS) Multidimensional scaling provides the geometrical representation of objects (Füstös– Kovács 1989). MDS, as data reduction system starts from a distance matrix, and by significantly reducing the dimension number, reaches its output, a diagram displaying correspondences, from which in a fortunate case the incidental clusters can be delineated (Lengyel 1999). In effect we are expecting a point diagram drawn in a reduced, two dimensional space, which displays the investigated units’ position in comparison to each other from a complex competitiveness aspect (Lukovics 2008). The reduction of dimensions has to occur in a way that the order of the elements’ distance should not change. S-stress is one of the most common control-indicators used for this, the value of which falls between 0 and 1. The geometrical representation formed as a result of multidimensional scaling is the more perfect the less its S-stress value is (Székelyi–Barna 2003; Kovács–Petres–Tóth 2006). The meaning of the established artificial dimensions can be analysed by the correlation relationship of the dimensions and the variables shaping the dimensions. Since in case of the coordinates resulted by MDS the order and not the exact numerical value is essential, the correlation can be characterized by the Spearman’s rank correlation coefficient. The artificial dimensions can be named on the basis of the significant relationships. If we try to represent the objects in one dimension, we are talking about onedimensional scaling. On the basis of this it is theoretically possible to determine the objects’ ranking besides the aggregation of the original variables, which can provide the opportunity to establish a complex competitive ranking. For this two conditions have to be met. On the one hand, the S-stress value cannot exceed 0,1, and on the other hand, the established artificial variable can be considered as competitive ranking. This can be ascertained on the basis of the indicators providing the basis of MDS, and the direction and strength of the correlation of the established artificial dimension. It shall be noted that the advantage of the methodology applied for the establishment of the ranking is that it does not attempt to examine competitiveness on the basis of one indicator. However, this complexity can cause several problems and limitations in the course of the analyses. On the one hand, the basic model serving as the basis of the investigation and the set of indicators describing it can greatly influence the established rankings. This means that either the changing of the set of indicators or an investigation conducted in a frame system other than the pyramid model may result in another ranking. Applying the one-dimensional scaling to the indicators characterizing the pyramid model’s basic category, on the basis of the 0,053 S-stress value, the procedure can be considered to be good. On the basis of studying the rank correlation coefficients (Table 3) it can be stated about the established artificial dimension that the value of the coordinate established in the artificial dimension is in a strong positive relation with the value of GDP per capita, the gross added value per one employed person and the employment rate, and is in a strong negative relation with the unemployment rate. On the basis of this we can estab– 182 Miklós Lukovics – Péter Savanya lish the complex competitive ranking of the NUTS3 units of the Visegrád Countries on the basis of 2008 data (Table 4). According to our expectations, the ranking is lead by the four capitals: Prague, Warsaw, Bratislava and Budapest. If the MDS coordinates of the analysed territories are illustrated on a point diagram depending on ranking, together with the marking of the country (Figure 5), then on the one hand it can be seen that the four capitals and Poznan stand out at the top of the list, and on the other hand, the Czech territories can be found rather in the first half of the ranking, while the Hungarian territories are positioned rather in the second half of the ranking. The Polish territories can be found everywhere in the ranking, the Slovakian territories are also rather in the first half of the ranking, but here we can find elements near both end of the ranking, too. To examine whether there is a significant difference between the positions of the Visegrád Countries in the NUTS3 ranking a Kruskal-Wallis test was applied. According to the null hypothesis of the test there is no significant difference between the positions of the NUTS3 territories of the countries, which however we reject besides a five per cent significance level (Test function=20,3). In the SPSS 18.0 software it is possible to investigate this more deeply (Figure 6), on the basis of the Post Hoc test supplied by correction based on the comparison number. In the ranking the average rank number of the Hungarian counties is 66., while that of the Czech territories is 20,4, that of the Polish territories is 58,3, and that of the Slovakian territories is 54. These discrepancies are significant only in the Czech-Hungarian and Czech-Polish correlation, i.e. it can be established that the Czech NUTS3 territories occupy a significantly better place in the ranking than the Hungarian and Polish ones (Table 5). If we look at the position of the Hungarian counties, we can see that Budapest is among the firsts in the ranking. The Counties of Komárom-Esztergom and GyőrMoson-Sopron also belong to the first third of the list, at identical places (21,5.) The first half of the list also includes (at places 34–48) Pest, Fejér, Vas and Zala. These territories perform poorly along maximum one parameter. Nógrád, Borsod and Szabolcs can be found at the end of the list. These territories perform poorly along each dimension (Table 6). TABLE 3 Relation of the MDS dimension and the indicators of the base categories Variable GDP per capita at market price in the average percentage of the EU, 2008 Gross added value per one person employed, million Euro/capita, 2008 Unemployment rate,%, 2008 Employment rate,%, 2008 Source: Own compilation. Correlation coefficient value Significance level N ,886 ,000 108 –,824 ,000 108 ,644 ,690 ,000 ,000 108 108 The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 183 TABLE 4 Competitive ranking of NUTS3 units Rank number Territory Rank number Territory 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 22 22 23 24 25 26 27 Hlavní mesto Praha Miasto Warszawa Bratislavský kraj Budapest Miasto Poznan Legnicko-Glogowski Miasto Kraków Trnavský kraj Stredoceský kraj Jihomoravský kraj Miasto Wroclaw Tyski Trojmiejski Jihocecký kraj Plzenský kraj Miasto Lódz Katowicki Pardubický kraj Zlínský kraj Královéhradecký kraj Komárom-Esztergom Gyor-Moson-Sopron Vysocina Miasto Szczecin Warszawski-zachodni Moravskoslezský kraj Poznanski 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 Zilinský kraj Opolski Rybnicki Vas Karlovarský kraj Nitriansky kraj Sosnowiecki Ciechanowsko-plocki Skierniewicki Warszawski-wschodni Leszczynski Zala Piotrkowski Bialostocki Sieradzki Gorzowski Rzeszowski Czestochowski Zielonogórski Lódzki Wroclawski Veszprém Olsztynski Csongrád Ostrolecko-siedlecki Oswiecimski Lubelski 28 29 Trenciansky kraj Liberecký kraj 64 65 30 31 32 33 34 35 Olomoucký kraj Ústecký kraj Bydgosko-Torunski Bielski Pest Gliwicki 66 67 68 69 70 71 Szczecinski Sandomierskojedrzejowski Kaliski Pilski Starogardzki Kielecki Elblaski Krakowski 36 Fejér 72 Tarnowski Source: Own compilation. Rank number Territory 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 Gdanski Suwalski Hajdú-Bihar Bács-Kiskun Jász-Nagykun-Szolno k Koninski Slupski Bytomski Lomzynski Nowosadecki Tolna Tarnobrzeski Krosnienski Elcki Baranya Radomski Chelmsko-zamojski Bialski Przemyski Somogy Nyski Békés Heves Grudziadzki Jeleniogórski Wloclawski Pulawski 100 Walbrzyski 101 Koszalinski 102 103 104 105 106 107 Presovský kraj Stargardzki Kosický kraj Nógrád Borsod-Abaúj-Zemplén Szabolcs-SzatmárBereg 108 Banskobystrický kraj 184 Miklós Lukovics – Péter Savanya FIGURE 5 Competitive ranking of countries Source: Own compilation. FIGURE 6 Average location of NUTS3 areas Source: Own compilation. The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 185 TABLE 5 Locational comparison of NUTS3 areas Position (relative location) Country of comparison Czech Republic Czech Republic Slovakia –33,57 Slovakia +33,57 +37,87 (sig<0,05) +45,57 (sig<0,05) Poland Hungary Poland Hungary –37,87 (sig<0,05) –4,30 –45,57 (sig<0,05) –12,0 +4,30 +12,00 –7,7 +7,70 Source: Own compilation. TABLE 6 Hungarian counties in the given dimensions Collectively On the basis On the basis On the basis of On the basis of unemployof GDP gross added value of employper employed ment rate per capita ment rate person Budapest Komárom-Esztergom Győr-Moson-Sopron Pest Fejér Vas Zala Veszprém Csongrád Hajdú-Bihar Bács-Kiskun Jász-NagykunSzolnok Tolna Baranya Somogy Békés Heves Nógrád Borsod-AbaújZemplén Szabolcs-SzatmárBereg Source: Own compilation. 4 21,5 21,5 34 36 40 48 58 60 75 76 77 15,5 27 8 27 31,5 31,5 48,5 53,5 67 83,5 79 76,5 4 26,5 18,5 43 38,5 43 47,5 61 61 68 80 86,5 4 72 22 23 45 59 74 71 79 70 85 93 4 7 37 88 44 39 32 63 47 71 54 49 83 87 92 94 95 105 106 92 96 95 93,5 97 103 106 68 68 91,5 94,5 74,5 108 86,5 62 61 86 91 65 99 68 77 80 65 74 79 105 91 107 107 106 84 104 186 Miklós Lukovics – Péter Savanya Analysing the connection of the established ranking (MDS coordinate) (Table 7) with the previous variables, we can see that the ranking does not show any significant relation with the growth of the population, the share of building industry, services (general), wholesale and retail, financial services from the gross added value. While at the same time, the competitive ranking shows a significant positive relation of medium strength with migration change and life expectancy at birth. The competitive ranking shows a significant weak relation of positive direction with the number of enterprises per one thousand inhabitants and the activity rate, as well as the share of industry (excluding building industry) from the gross added value. TABLE 7 Relation of the competitive ranking and other indicators Variable Population growth in comparison to the previous year,%, 2008 Migration change in comparison to the previous year,%, 2008 Life expectancy at birth, year, 2008 The share of agriculture, fishing from the area’s gross added value,%, 2008 The share of industry (excluding building industry) from the area’s gross added value,%, 2008 The share of building industry from the area’s gross added value,%, 2008 The share of services from the area’s gross added value,%, 2008 The share of wholesale and retail, hotels and restaurants, traffic from the area’s gross added value,%, 2008 The share of financial mediation, real estate services from the area’s gross added value,%, 2008 The share of administration, community service from the area’s gross added value,%, 2008 Number of enterprises per 1000 inhabitants Activity rate,%, 2008 Gross added value per capita, million Euro/capita, 2008 Source: Own compilation. Correlation coefficient value Significance level N ,077 ,427 108 ,494 ,000 108 ,526 ,000 108 –,591 ,000 108 ,259 ,007 108 –,061 ,529 108 –,141 ,146 108 ,086 ,374 108 ,069 ,481 108 –,611 ,000 108 ,278 ,004 108 ,368 ,000 108 ,883 ,000 108 The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 187 At the same time the competitive ranking shows a significant negative relation that is stronger than medium with the share of fishing, agriculture, and community service from the gross added value, i.e. the more agriculture and community service dominate in the gross added value in an area, the worst position does the area have in the ranking. Cluster analysis In the course of cluster analysis we can attempt to create groups the elements of which are as closely related to each other as possible, and relatively differ more from the elements of the other clusters (Falus–Ollé 2000). The objects are assigned to a precise class on the basis of their similarity or difference. The distance of the objects per pair constitutes their degree of similarity (Hajdu 2003). Since the units of the variables may differ greatly from each other, we are working with standardized data. In practice several clustering procedures are known, which differ from each other mainly in the applied metrics and the applied clustering method. In the course of our analyses twostep clustering was used. This technique was chosen for more reasons. On the one hand, this procedure automatically offers a cluster number, and on the other hand, we get the average Silhouette coefficient as a result of the procedure, which practically serves to decide whether the established clusters can be statistically interpreted, i.e. whether the grouping is appropriate. The value of this can fall between -1 and +1. An indicator value below 0,2 cannot be interpreted, an indicator value above 0,5 refers to excellent, while a value between 0,2 and 0,5 refers to acceptable classification (Kaufman–Rousseeuw 1990). Thirdly, the problem with the k-center clustering prevalent in practice is that the software chose the initial cluster centers pseudo randomly, i.e. they regard the data of a given record as cluster center. The hazard of this is that by rearranging the data table (rearranging the small areas) we get different results. In order to eliminate this error source we decided not to apply this method. Two-step clustering is practically an entropy-based clustering procedure, which alloys dynamic and hierarchical clustering techniques. Clusters are formed in two steps. First all objects will be classified into an existing cluster or a new cluster will be opened. Secondly, the clusters established as a result of the previous step are classified by the procedure using a hierarchical procedure – in our case – on the basis of Akaike’s information criterion. In the course of our analysis the clustering is done on the basis of the competitive ranking (on the basis of MDS coordinates) comprising the basic categories of the pyramid model. Since clustering is sensitive to the outlier values, these have to be filtered first. A possible way to do this is to do a hierarchical clustering on the basis of the principle of the closest neighbour. The outlier observations can be then detected on the basis of the dendrogram established in the course of the procedure (Sajtos–Mitev 2007). The result of the 188 Miklós Lukovics – Péter Savanya procedure is the same as what we have seen on the graphic diagram of the competitive ranking: we can find two outlier groups. The first group is composed of the capitals and Poznan, while the other group consists of the counties occupying the last two places of the ranking: Szabolcs-Szatmár-Bereg County and Banskobystrický kraj. Filtering these two groups, we performed the two-step clustering on the remaining NUTS3 areas. The applied clustering procedure suggested the application of five clusters (Table 8). The value of the average Silhouette coefficient is 0,7, which can be considered expressly good. TABLE 8 Relation of the competitive ranking and other indicators Cluster Frequency Distribution % Averages MDS value 18 24 32 21 6 101 17,8 23,8 31,7 20,8 5,9 100,0 0,67 0,22 –0,21 –0,57 –0,95 – Area of relatively strong competitiveness Area of stronger than average competitiveness Area of weaker than average competitiveness Area of weaker competitiveness Area of relatively weak competitiveness Total Source: Own compilation. In the relatively strong cluster there are 8 Czech and 7 Polish NUTS3 areas, and only 1 Slovakian and two Hungarian areas, the Counties of Komárom-Esztergom and Győr-Moson-Sopron which also have car industries (Table 9). TABLE 9 NUTS3 areas according to clusters and countries Cluster Country Czech Republic Area of relatively strong competitiveness Area of stronger than average competitiveness Area of weaker than average competitiveness Area of weaker competitiveness Area of relatively weak competitiveness Total Source: Own compilation. Hungary Total Poland Slovakia 8 2 7 1 18 5 3 13 3 24 0 6 26 0 32 0 5 16 0 21 0 2 2 2 6 13 18 64 6 101 The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 189 54,2 per cent of the stronger than medium cluster is Polish. The proportion of Hungarian, Czech and Slovakian areas may be regarded balanced in case of this cluster. 81,3 per cent of the weaker than average cluster is Polish, while 18,8 per cent is comprised of Hungarian areas. Here there are absolutely no Czech and Slovakian areas. The cluster of weaker competitiveness, similarly to the former one, consists of only Polish (76,2%) and Hungarian (23,8%) areas. The cluster of relatively weak competitiveness is made up of 2-2-2 Slovakian, Polish and Hungarian NUTS3 units. From the point of view of countries we can say that the Czech areas belong only to the relatively strong (61,5%) group and that of stronger than average competitiveness (38,5%). The Polish NUTS3 areas belong most frequently to the areas of weaker than average competitiveness (40,6%). The Hungarian counties belong to the following clusters (Table 10). TABLE 10 Hungarian counties and clusters Area Budapest Komárom-Esztergom Győr-Moson-Sopron Pest Fejér Vas Zala Veszprém Csongrad Hajdú-Bihar Bács-Kiskun Jász-Nagykun-Szolnok Tolna Baranya Somogy Békés Heves Nógrád Borsod-Abaúj-Zemplén Szabolcs-Szatmár-Bereg Source: Own compilation. Cluster Outstandingly good Area of relatively strong competitiveness Area of relatively strong competitiveness Area of stronger than average competitiveness Area of stronger than average competitiveness Area of stronger than average competitiveness Area of weaker than average competitiveness Area of weaker than average competitiveness Area of weaker than average competitiveness Area of weaker than average competitiveness Area of weaker than average competitiveness Area of weaker than average competitiveness Area of weaker competitiveness Area of weaker competitiveness Area of weaker competitiveness Area of weaker competitiveness Area of weaker competitiveness Area of relatively weak competitiveness Area of relatively weak competitiveness Falling behind 190 Miklós Lukovics – Péter Savanya By determining the average value of the indicators describing the basic categories of the pyramid model in the individual clusters (Figure 8) we can say that the worse competitiveness cluster someone belongs to, the worse the employment and unemployment rates will be. With respect to the GDP per capita and the gross added value per person employed we can see a similar picture, except for the fact that the parameters of the two weakest clusters display a reverse order. FIGURE 8 Average rate of indicators of base categories in clusters Source: Own compilation. All the counties belonging to the cluster of relatively strong competitiveness have reached a prestigious place in the indicator shaping the competitive ranking. The counties belonging to the cluster of relatively weak competitiveness are very weak especially in their employment and unemployment data, while they are rather weak according to the two other dimensions. The weaker a cluster is, the worse is the picture shown by the average rank number of the individual dimensions’ rankings (Table 11). The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 191 If we examine the average share of agriculture, industry (building industry exclu– ded), building industry, services within a cluster (Figure 9), it can be stated that the weaker competitive cluster someone belongs to, the less is the share of industry (building industry) from the gross value added. TABLE 11 Hungarian counties and clusters Cluster On the basis of On the basis of unemployment rate GDP per capita Area of relatively strong competitiveness Area of stronger than average competitiveness Area of weaker than average competitiveness Area of weaker competitiveness Area of relatively weak competitiveness On the basis of gross added value per person employed On the basis of employment rate 22,8 15,7 27,7 22,2 40,7 37,3 36,0 54,2 57,6 69,0 74,4 59,5 84,3 88,7 80,8 70,8 103,2 78,6 52,2 97,8 Source: Own compilation. FIGURE 9 ‘Average’ rate of the gross added value in clusters Area of rela tively weak competitiveness Area of wea ker competitiveness Area of wea ker tha n a vera ge… Area of stronger tha n a vera ge… Area of relatively strong competitiveness 0% 20% 40% 60% 80% 100% The sha re of a griculture, fishing from the a rea ’s gross va lue added, %, 2008 The sha re of industry, excluding building industry, from the area’s gross value a dded, %, 2008 The sha re of building industry from the area’s gross value a dded, %, 2008 The sha re of services from the a rea ’s gross va lue added, %, 2008 Source: Own compilation. 192 Miklós Lukovics – Péter Savanya Summary The automotive industry of the Visegrád Countries, with Hungary among them, doubtlessly constitutes part of the European automotive industry nowadays. At a global level automotive industry used to be the car manufacturing of individual nations in the form of quasi territorial subsystems independent of each other. In the value chain the production processes are no longer connected to the car manufacturers in one person, they rather constitute an international network and flow processes coordinated by the strategic participants of the industrial sectors, the car manufacturers and great suppliers. National level industrial sector units covering the whole verticum have been transformed, today automotive industry represents an industrial sector production and marketing system embracing the macro-regions of economic integrations (ASEAN and MERCOSUR, EFTA, NAFTA). With respect to automotive industry we can practically speak about national car industries integrated into a “global” system. Within this the individual national industrial sector networks operate as functional sub-network units in the industrial sector structure of a macro-region. “Global” here is a qualitative attribute, i.e. the companies at the certain levels of the car manufacturing value chain function in a horizontally coordinated network as elements of a vertically organized industrial sector structure. As the spatial reflection of these processes, the geographical dimensions of automotive industry have also changed. The “economic geography” of the globally active automotive industry is determined by the macro-regions of the individual industrial sectors and the networks interpreted within this. The spatial dimension of global processes is provided by the territorial networks located in the vertical system of the industrial sector. The strategic directors of the industrial sector’s organization are the car manufacturers and the first tier suppliers strategically cooperating with them. The other companies of the value chain, the other participants of the local networks are connected to the industrial sector through the integrator first tier suppliers. The localization decisions of car manufacturers and global suppliers have an essential role in the spatial development of automotive industry, in the establishment and development of local industrial sector networks. Placing the Visegrád Countries in the system and economic space of European automotive industry we have to expand the concept of the macro-region of automotive industry, business relations and production chains cover a much larger area in the EFTA system than the industrial borders of the European Union. Interpreting the competitiveness of territorial units of the macro-region comprising Central and Eastern Europe important consequences can be drawn with respect to automotive industry as well. The comparative analysis demonstrating relative positions illuminates the situation of the Hungarian counties and their position in the competition of Central and Eastern European regions, and reveals what level of company competitive advantage the economies of the individual territorial units are able to establish. The empirical study extending to the counties of the Visegrád Countries provides a comparative picture of the relative competitiveness of the Central and Eastern European territories. The The Competitiveness of the Visegrád Countries’ Counties from the Aspect… 193 competitiveness analysis of the regions offers important lessons about the positions of the individual local spaces, and car industrial districts localized in them, about the direction of courses of development in the policies of the territories building greatly on automotive industry, as well as for the participants, companies of already existing industrial sector networks. In our essay we examined the Visegrád Countries on the basis of GDP per capita, gross value added per employee, unemployment rate and employment rate at NUTS3 level. With the help of multidimensional scaling a complex ranking of NUTS3 units was established. The ranking is lead by the four capitals: Prague, Warsaw, Bratislava and Budapest. We pointed out that the Czech NUTS3 areas are significantly better placed in the ranking than the Hungarian and Polish NUTS3 areas. It was demonstrated that if in a territory agriculture and community services dominate in the gross value added, the territory occupies a worse place in the ranking. Territorial units were typified with the help of cluster analysis. Besides an outstandingly good (capitals and Poznan) and an outstandingly weak cluster, 5 clusters were identified. In the relatively strong cluster there are 8 Czech and 7 Polish NUTS3 areas, and altogether 1 Slovakian and two Hungarian areas, Komárom-Esztergom and Győr-Moson-Sopron Counties which have car industries. It was established that the weaker competitive cluster an area belongs to, the less the industry’s (building industry’s) share will be from the gross value added. Note 1 Eleven car manufacturing companies give almost 85% of the car industrial production even besides the expansion of car manufacturing in the dynamically developing countries. The global expansion of the leading car manufacturers and the biggest car industrial suppliers was strengthened in the 1990s by purchases, fusions and associations formed by cross proprietary shares (Bieserbroeck et al. 2009; Dicken 2007). After the financial crisis part of these associations are still standing (pl. Nissan-Renault), while in some cases consolidation pressure entailed the detachment of earlier purchased companies (e.g. GM-Saab). 2. The institutional system of the EFTA has expanded much earlier, more quickly and much further than the institutional borders of the European Union along economic relation systems and interests. 3 E.g. the production of right hand drive and left hand drive cars, stronger suspension and bigger fuel tanks in the developing countries with sparse infrastructure etc. 4 The markets of emerging and developing countries play a great role in this tendency, where milliards are becoming potential customers with the raising of wages. The data of the table reflect the changes of ten years, which comparing the relative and absolute magnitude of the numbers show a very dynamic tendency. 5 American car manufacturers outsourced a great proportion of their component, module and car manufacturing processes to Mexico, which process was greatly promoted by the establishment of NAFTA. The political lobby of American manufacturers had a great role in this. The establishment of the NAFTA made it possible for Japanese and European car manufacturers supplying the American market to employ cheap South-American workforce and apply outsourced production and marketing strategies building on the re-export to North-American markets. In spite of this they built their production potentials and supplier network on the North-American target markets (Biesrbroeck et al. 2009, Bieserbroeck–Sturgeon 2010). 194 6 7 8 9 10 Miklós Lukovics – Péter Savanya Almost 60% of the value of a manufactured new car is produced by the suppliers (Chanaron– MacNeill 2005). We furthermore mention the statements of Porter’s global-local paradox each of which is true in automotive industry (Lengyel 2010, 92). The systems of Japanese car manufacturers represent a different approach of modular production. Toyota and Honda strongly control and organize production systems, and concentrate their development activities parallel to this. The developing Asian regions, which serve as target areas for outsourcing for Japanese car manufacturers, often have very limited infrastructural and technological production systems and no background of developed small and medium enterprises which characterizes Europe. Wide-scale process management and control thus become key factors in the outsourced building of supplier and production systems (Freyssenet–Lung 2004a, Heribert 2007). The financing difficulties following the crisis of 2008 have unequivocally brought these problems to the surface at a macroeconomic level. In the “recovery period” following the outbreak of the crisis the tendency was that these economies showed continuous stagnation or even weakening, while western economies, which had had developed bases even before the crisis, found their way back to growth. Macroeconomic performance, wage standard raised by governmental disposing politics utilizing EU sources, and the abyss formed between increased internal consumption and usage brought the deformity of economic structures to the surface, which manifests in culminating unemployment and state debt rates that affected Portugal, Spain, and not to mention Greece. The opening of the scissors between wage standard and the productivity of economic structure worsened the general competitiveness in these economies. The previous tendencies of this process have presumably deteriorated the car industrial competitiveness of these countries and their attractiveness from the viewpoint of capital investments in the long run. The economic integration of Eastern-Europe and the economic development of these countries made previously existing differences more balanced. 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University College London, Centre for the Study of Economic and Social Change in Europe – School of Slavonic and East European Studies, London. Sajtos L. – Mitev A. (2007) SPSS kutatási és adatelemzési kézikönyv. Alinea Kiadó, Budapest. Székelyi M. – Barna I. (2003) Túlélőkészlet az SPSS-hez. Többváltozós elemzési technikákról társadalomkutatók számára. Typotex Kiadó, Budapest. U.S. International Trade Commission (2010) ASEAN: Regional Trends in Economic Integration, Export Competitiveness, and Inbound Investment for Selected Industries. U.S. International Trade Commission, Washington DC. COMPETITIVENESS OF AUTOMOTIVE CENTRES IN CENTRAL AND EASTERN EUROPE TAMÁS DUSEK Keywords: competitiveness car industry Central and Eastern Europe complex indicators The aim of the investigation is to analyse the competitiveness of automotive centres in Central and Eastern Europe compared to each other and their environment. Due to practical and methodological reasons discussed in the analysis the investigation covers four countries: Hungary, the Czech Republic, Slovakia and Poland. There are many examples of the analyses of competitiveness between countries and regions within countries, investigations below national level, referring to more countries is however more rare and presents a greater challenge methodologically due to spatial division which differs from country to country, and due to the international limitations of comparison of national regional statistics. In our essay we first present the investigated territory itself and its spatial division, together with the theoretical and practical reasons which play a part in the delimitation of the territory. Afterwards we will look at the availability of data and the compilation of the database. We are of the opinion that this review is necessary in order to ensure the better understanding of the practical analysis. In the course of the practical analysis all territorial units will be examined together first, then we will analyse the situation of territories with car factories separately, where we will demonstrate that on the average these territories can be regarded more competitive than the territories without car factories. The methodological background of the analysis Choosing the territory to be examined and the territorial level Due to conceptual and practical reasons we included the car factories of four countries in the analysis: those of Hungary, Slovakia, the Czech Republic and Poland. The circle of countries could have been extended primarily westwards and south-eastwards. It is well-known that these four countries are characterized by a significantly different level of development at a national level than Austria and Germany. In addition to such significant differences, in the course of any spatial division below national level the territorial units are mainly distinguished by which country group they are found in (in the more developed Austria and Germany, or the less developed four countries). Therefore the number of groups and categories used in the analysis should be significantly increased for appropriate differentiation, i.e. a great part of Hungary for example should not be considered homogenous compared to Austria and Germany. The same problem, but with the opposite sign, would present itself if Romania and Bulgaria would be included in the investigation. Competitiveness of Automotive Centres in Central and Eastern Europe 197 Apart from these conceptual reasons, the circle of the examined countries is also narrowed by the practical possibilities related to the compilation of the database. From this viewpoint the difficulty is that each additional country decreases the number of usable indicators, since the scope of spatial statistical indicators of the individual countries differ. We only wished to use those indicators which are available in all countries. In the course of certain analyses, especially when examining more countries, incomplete indicators are also used, complementing the missing values in an artificial way. Because of the small number of countries in the present analysis this disputable practice was not deemed feasible. It is also necessary to examine whether the content, operationalization, localization, temporality of indicators which can be considered identical on the basis of their names is really identical or at least does not contain such a degree of differences which exclude analysability. Independent of this, in case of financial indicators the problem of converting the different currencies of the countries to a common currency still presents itself. The spatial level of the analysis is determined partly by conceptual, partly by practical reasons. The use of settlement level data and the conducting of settlement level analyses were rejected due to conceptual reasons. Although automotive factories are point-like and well localizable, they are generally situated on the border of a settlement, further away from the inhabited area, while their workforce-attraction range extends much further than the given settlement; depending on traffic possibilities, it can be up to 100 km, or a two-hour journey. The purchase of service-type inputs (cleaning, maintenance, safeguarding, printing etc.) exerts its influence in a similar spatial range, i.e. not at settlement level. Therefore an investigation conducted at settlement level would not be reasonable even in case of cities of the similar order. A few automotive factories however are situated in small cities or villages. Altogether six factories are situated in settlements with a population of less than 10 thousand inhabitants, from which the population of two settlements does not even reach two thousand inhabitants. For instance administratively the Czech Hyundai factory belongs to Nosovice, the area of which is 6,45 square kilometre (from which two square kilometres belong to the factory), which had a total of 994 inhabitants in 2010. The number of people employed in the Hyundai factory was 2000 in 2008, 2500 in January 2011, and the planned final number of employees is 3400. The settlement is situated five kilometres from the Frýdek-Mistek of sixty thousand inhabitants, and thirty kilometres from Ostrava, along road E462. The comparison of settlements with car factories is not possible methodologically because the order of differences and the administrative borders are inadequate from the point of view of analysis. Theoretically the comparison of the labour market attraction range of car factories would be an appropriate solution, there are however no statistical data to draw such arbitrary borders. On the other hand, the attraction districts do not cover the space without gaps, and the attraction districts of certain centres have parts overlapping each other. Therefore it is the NUTS3 territorial level where the analysis can be conducted in an adequate way and where there are data available. Lower level territorial data comparable among countries do not exist due to the different territorial 198 Tamás Dusek administrative systems and the basic territorial statistics of the individual countries. While in Hungary an imposingly wide scale of settlement level indicators are available for research, in the other countries there are less available data even in case of cities, and at the level of units which correspond to villages, though they are different from those of Hungary in terms of administration and average size, it is even more difficult, if not impossible to compile a comparable database. The basic characteristics of spatial division and territorial units The four examined countries, Hungary, Slovakia, the Czech Republic and Poland are divided into a total of 108 territorial units at NUTS3 level (Table 1). The circle of statistical indicators available in the individual countries is largely determined by whether the territorial units of the given level are administrative units at the same time, or exist only in a statistical sense for territorial statistical analyses. Hungary, Slovakia and the Czech Republic are identical with each other in the sense that in all the three countries the NUTS3 level consists of units which beside statistical functions fulfil administrative functions as well (counties and krajs). This is fortunate from the viewpoint of the availability of data, since the official territorial statistics come into being within the frames of the administrative units. In Poland however the situation is different, in this country the NUTS3 level consisting of units called sub-regions, NUTS3 only serves the purpose of statistical information, has no administrative content, so the available data are much more limited compared to the Hungarian data. The NUTS2 level however has administrative functions in Poland (the 16 counties) while in the other three countries it primarily serves purposes of territorial development and statistics and has less administrative content. In Hungary for example there is only a minimal difference between the NUTS2 and NUTS3 levels in terms of available data, and the NUTS2 data are almost exclusively the aggregates of NUTS3 data. Only the results of a few regional surveys (e.g. household statistical data) cannot be disaggregated to county level. TABLE 1 Number of NUTS 3 units per country Country Czech Republic Hungary Poland Slovakia Source: Eurostat. Number of territorial units 14 20 66 8 Competitiveness of Automotive Centres in Central and Eastern Europe 199 For the sake of simplicity in the analysis territorial units shall be referred to as subregions when we look at all territorial units together, because the county-kraj-sub-region triple name would be clumsy to use, so the traditional name of “county” will be used only in case of the Hungarian counties. The expression of “region” is usually applied to NUTS2 level. The territorial arrangement is very favourable from the viewpoint of comparability, there are no outstandingly big or small units whether on the basis of territorial size, or the number of the population (Table 2). The units comprising metropolises differ slightly from this, which are double or triple of the average in terms of the number of population, and one tenth of the average in terms of their size. This significance however is inevitable due to the cohesiveness of the settlement network and the indivisibility of the settlement. In the Czech Republic, Poland and Hungary the capital is an independent sub-region, while in Slovakia the almost 50 km district of Bratislava constitutes a mixed urban-rural sub-region. In addition to this, we can find further seven metropolises in Poland (Lodz, Krakow, Wroclaw, Poznan, Katowice, Szczecin, Gdansk–Gdynia–Sopot) which constitute independent sub-regions, separated from their environments. This spatial division is favourable owing to the greater information content of data, while at the same time the artificial statistical division of the cities from their environment entails certain disadvantages as well, because this way the regional-territorial differences and the differences along the hierarchy of settlements appear simultaneously in the given spatial division, therefore this has to be taken into account separately in the course of the analyses. TABLE 2 Main characteristics of NUTS 3 units per country Territory size (km2) Country Czech Republic Hungary Poland Slovakia Population (person) average minimum maximum dispersion average 5,633 496 11,015 2,659 747,682 308,403 1,250,255 316,593 4,651 525 8,445 1,790 501,549 207,637 1,712,210 350,313 4,738 262 12,091 2,727 577,816 276,767 1,709,781 196,070 6,034 2,053 9,454 2,209 655,848 490,378 minimum maximum 803,955 dispersion 95,283 Source: Own calculation on the basis of Eurostat data. The outstanding characteristics of the independent metropolitan sub-regions appear in the territorial units’ population density as well (Figure 1). The sub-region of Bratislava does not belong to the units of extremely high population density; its population density is only a tenth of that of Budapest. There are three sub-regions in Upper Silesia, in South-Poland with higher population density than Bratislava. There are no extremely lowly populated territories (as in Scandinavia or the Baltic Countries). 200 Tamás Dusek FIGURE 1 Population density of NUTS3 units Population density Inhabitant/square km 1351-3310 250-568 100-250 80-100 40-80 Map: Tamás Hardi. The generation of such simple indices however poses two major problems in case of small territorial units, which should either be integrated into the indicator itself or should be taken into consideration when interpreting the results. One of the problems is related to the commuting of the workforce among regions, and the other is connected to the demographical composition of the population (age structure, health indicators). As a result of the commuting of the workforce among regions it can happen that more people work in a region than those who have permanent residence there (this is true to miniregions such as the previously mentioned village of Nosovice, or Kékkút in Hungary), Competitiveness of Automotive Centres in Central and Eastern Europe 201 but commuting perceivably influences the development of specific indicators even at NUTS3 level, also in relation to wages and production (GDP) (Dusek–Kiss 2008). Commuting exerts an influence on the specific level of employment as well: the workforce can be taken into account also on the basis of the place of work (this is in the numerator of the specific indicator), and population (denominator) according to residence. This leads to the fact that 904 thousand people work in Prague, which is a proportion of 74,6% compared to the number of the population. In Warsaw this same proportion is 68,4%. These high proportions are obviously a result of the excess workforce coming from commuting. The appropriate indicator of employment is based on workforce surveying, since there the population is counted on the basis of residence, so the inhabitants of Central Czech Republic working in Prague appear in Central Czech Republic. Age structure and health composition also makes the comparison of small territorial units more difficult. It can occur that certain territories attract people of high income in pension age, which worsens the specific indicators of production and employment compared to the number of the population, but otherwise would not constitute a real competitive disadvantage. It is difficult to filter these types of factors because they would be investigable by the connecting of various independent databases, which for the most part cannot be done. The basic characteristics referring to economic output are however not sufficient to examine competitiveness, since as it was previously mentioned, competitiveness is a multidimensional phenomenon which can be characterized by a group of indicators. The compilation of a database containing wide-scale economic-social data covering four countries is not easy even at NUTS3 level, because the circle of data available at Eurostat is considerably restricted; it is mainly limited to GDP and its composition. Even the considerably general demographic data are incomplete. So the indicator list had to be complemented in addition to the Eurostat data by the territorial data of national statistical offices. In selecting the indicators the previously mentioned condition that the data had to be available for all the four countries appeared as a limiting factor. For this reason mostly Poland became the bottleneck with the least number of NUTS3 level indicators. Unfortunately it happened in case of several potential indicators (e.g. the average wages of industrial employees, the average of pensions, R&D expenses, R&D employees, the income of self-governments) that they were missing only in one of the four countries, and therefore could not be used. At the same time not all indicators would have been automatically included in the analysis even if significantly more indicators had been available. E.g. the usability of R&D data at this territorial level is questionable, because the NUTS3 units are too small compared to the research conducted in today’s global networks. The lack of data on export is similarly not considered to be a disadvantage, because the majority of this also comes from the transactions between the units of multinational companies situated in different countries, which moreover is an indicator containing an aggregation (the purchased material inputs) and can be therefore very deceptive. 202 Tamás Dusek The indicators used in the analysis are shown in Table 3 according to the basic categories of competitiveness. These are in line with the indicators used in the relevant literature and earlier competitiveness analyses, and except the development of average wages, which was unavailable at the given territorial level, no important index number is missing. We had to leave out of the analysis three potential indicators despite the fact that their inclusion, as secondarily important indicators, would have been considered reasonable, and they were available for all the four countries: number of enterprises (enterprise activity), number/proportion of university students, and the number/proportion of libraries. TABLE 3 Indicators used in the analysis Basic factors of competitiveness Economic output Employment Appeal Social capital Health Indicator GDP per capita, in Euros, in purchase power parity Unemployment rate Economically active population Number of people employed in industry Number of dwellings built Migration balance Number of crimes Life expectancy at birth Source* Year E 2008 E E E N E N N 2008–2009 2008–2009 2008 2008 2006–2008 2008 2008 * E – Eurostat; N – National statistical publications. Source: Own compilation. The recording of enterprises in Poland took place with a different content than in the other three countries, due to the two orders of magnitude smaller Polish data, this data proved to be inadequate for comparison between countries. The situation is the same in connection with the number of university students, in 23 sub-regions of Poland there were absolutely no university students, and there were places with only 11 students. Therefore this indicator had to be left out, too. The use of the number of libraries was also rejected on the basis of the analysis of data, this indicator rather reflects settlement network characteristics (the number of settlements), and cannot be used to describe human infrastructure. The indicators refer to the most recent year available, which is in most cases the year 2008. Regional GDP data of 2009 are for example still unavailable in August 2011. The majority of Eurostat data are available in a timeline (the earliest starting year is 1999, but it is a later year in case of the majority of the indicators), which also opens the possibility for a temporal comparison in a narrower circle. The 2009 data of unemployment rate and economic activity are known; these are used in the analysis based on individual indicators. When generating complex indicators however, we calculated with 2008 data in case of these indicators as well. Competitiveness of Automotive Centres in Central and Eastern Europe 203 General review of the whole territory’s competitiveness according to individual indicators First from among the available index numbers three key indicators will be examined separately: the regional gross domestic product per capita, which is the best substitute for civil income from all possibilities. The second indicator is the unemployment rate, and the third is economic activity. The second and the third are more closely related to each other, than the first. Later we will generate from these indicators a synthetic index number which describes competitiveness with a number; the purpose of the present analysis is the investigation of the most important individual aspects of competitiveness. Besides the three basic indicators we will also look at five additional indicators which make the description more complete. The 2008 picture generated on the basis of GDP per capita can be seen in Figure 2. For proper differentiation we determined eight departments which are more than the traditional. The departments consist of an identical number of sub-regions, one eighth of the sub-regions in each. On the map on the left hand side of the figure the sub-regions above the median (sub-regions of favourable position), while on the right hand side map the sub-regions under the median are differentiated. All sub-regions of the Czech Republic are above the median, and in Slovakia only the sub-region of Eperjes landed below the median. In Hungary, as it is well-known, the capital and the north-western quarter of the country are above the average, the other counties are below the average. Nógrád County is the last territorial unit, Szabolcs-Szatmár-Bereg County is the last but one, followed by eight East-Polish sub-regions. A west-east division can also be observed in Poland, but in a much smaller degree than in Hungary, since there are regions deeply below the average even in the west, and slightly above the average in the east. In the Czech Republic two western regions are the last ones, but the differences are not as big as in the other three countries. Urban territorial units occupy the first two places, which is not surprising, and is in line with every previous experience and expectation. From among these the sub-regions of the capitals are at the first four places. This on the one hand means a “real” difference of development, greater productivity and employment, a greater proportion of higher income professions and higher income received for identical work. On the other hand, however, the difference is excessive in comparison to the actual differences of development due to the influences of commuting. Among non-urban sub-regions the first four are the Lower-Silesian Legnicko-Glogowski, Nagyszombat (Trnava) and the Upper-Silesian Tyski and Lower-Moravia. Győr-Moson-Sopron County, which is the first among the Hungarian counties, is at place 15 of the whole ranking, and place 8 among non-urban sub-regions. 204 Tamás Dusek FIGURE 2 GDP per capita in PPP, in the average of the four countries, 2008 GDP/capita 115-277 101-115 89-101 76-89 46-89 GDP/capita 46-59 59-66 66-71 71-76 76-277 Map: Tamás Hardi. The temporal development of competitiveness connected to economic output can also be analysed by GDP per capita. In the course of temporal comparison one has to be careful, because the smaller territorial units we analyse, the greater random fluctuations can be from one year to another, which reflect the outstandingly good or bad performance of a dominant enterprise or industrial sector for the given year, but do not necessarily indicate permanent change. Therefore the isolated analysis of changes from one year to another are not recommended. When analysing a longer time period this has to be taken into consideration in such a way that the basis year should possibly not contain outstanding data, but the longer a time period is, the less significant it is. The year 2002 was not an outstanding one and six years constitute a sufficiently long time period, therefore it was selected to be the basis year. There is no structural change, significant regional rearrangement between the two time periods. The only significant change was the change of Hungary’s and Slovakia’s average positions, which can also be seen in the static map, but it is even more prominent in the figure showing the difference between the two years (Figures 3–4). During this period the national average of Hungary decreased from 113% of the four countries’ average to 102%, while Slovakia increased from 99% to 115%. The changes of the averages of Poland (89%) and the Czech Republic (129%) are within one percentage point, meaning that their GDP change was more or less identical to the average of the four countries in that period. At Sub-regional level we can naturally find much greater differences. The first placed Bratislava increased with 41,9 percentage points above the average of the four countries, the second is Tmava with 32,8 percentage points. Among the first seven Competitiveness of Automotive Centres in Central and Eastern Europe FIGURE 3 GDP per capita in PPP, in the average of the four countries, 2002 GDP/capita GDP/capita 116-269 51-62 103-116 88-103 62-69 81-88 52-81 69-73 73-81 81-269 Map: Tamás Hardi. FIGURE 4 The change of GDP per capita between 2002 and 2008, in the average of the four countries GDP/capita increase above the average, % 10-42 5-10 2-5 0-2 under the average Map: Tamás Hardi. GDP/capita increase under the average, % 10-22 5-10 2-5 0-2 above the average 205 206 Tamás Dusek subregions there are five Slovakian and two Polish ones (Legnicko-Glogowski and the Central-Polish Ciechanowsko-plocki). The least growing Slovakian sub-region is Banská Bystrica, where there was only a 0.5 percentage point growth. This is little in comparison to the Slovakian average, and reflects significant national regional inequalities, but it is significantly more favourable for instance than the 16% decrease of the neighbouring Nógrád County. Although the Czech Republic did not change in terms of national average, the Liberecký and Karlovy Vary sub-regions decreased significantly (20% and 16%), while Lower-Moravia increased significantly (10%). In Poland only the performance of the sub-region of Szczecin was outstandingly bad (18% decrease). In Hungary only the relative situation of Komárom-Esztergom County improved (four percent increase), all the other countries decreased to an extent of more than five percentage points. The decrease naturally refers to the relative position, in an absolute sense there was economic growth everywhere during the six years, it was only well below that of the average of the four countries. Unemployment rate can also be considered one of the basic indicators of competitiveness. There are strong territorial differences on the basis of this as well in the sub-regions of the four countries, which do not totally correspond to what we have seen in case of the indicator of GDP per capita (Figures 5–6). E.g. although the capital sub-regions are in the most favourable position, the majority of the Polish metropolitan sub-regions can be found only in the middle field, worse placed than on the basis of GDP. The principal territorial difference is given by the outstandingly high unemployment rate of Central- and Eastern-Slovakia, the rate here exceeds 13% in four sub-regions. Excluding this, the indicator is similar to the GDP in the sense that generally the Czech sub-regions are in the most favourable position, and within Hungary and Poland the ranking of sub-regions is fairly similar to the ranking according to GDP. At the same time, compared to 2002, the situation was significantly rearranged by 2009. In 2002 unemployment was extremely high in Poland, it was 12% even in Poznan, the sub-region of the most favourable position, and it exceeded 30% in six West-Polish sub-regions. We can hardly find an example of so high unemployment at a national level. On the other hand, the first 29 places were occupied by only Hungarian and Czech sub-regions, and the thirtieth place was given to Bratislava, the best positioned sub-region in Slovakia. It is necessary to look at the development of unemployment together with the development of the activity rate, because low activity coupled with low unemployment rate can be more unfavourable from many aspects than a higher economic activity coupled with higher unemployment. In the first case low unemployment can be explained by low activity, the great number of passive unemployed people withdrawn from the labour market. At a national level the data differentiate well into the very low activity Hungary (42% in 2009), the equally low activity Poland (45,3%), and the high activity Czech Republic (50,5%) and Slovakia (49,7%) (Figure 7). The interesting point of regional differentiation however is that the Polish sub-regions can be found roughly evenly dispersed between the minimum and maximum values. Competitiveness of Automotive Centres in Central and Eastern Europe FIGURE 5 Unemployment rate in 2009,% unemployment rate, % unemployment rate, % 3,1-5,7 11,7-19,0 5,7-7,0 7,0-7,6 10,4-11,7 7,6-8,5 8,5-19,1 9,3-10,4 8,5-9,3 3,1-8,5 Map: Tamás Hardi. FIGURE 6 Unemployment rate in 2002,% unemployment rate, % unemployment rate, % 3,6-5,5 24,5-34,5 5,5-8,3 8,3-13,4 21,6-24,5 13,4-16,1 16,1-19,4 3,6-16,1 16,1-34,5 Map: Tamás Hardi. 19,4-21,6 207 208 Tamás Dusek FIGURE 7 Economic activity (Economically active population/total population), 2009 economic activity, % economic activity, % 52,3-56,8 34,3-38,0 49,4-52,3 47,8-49,4 38,0-40,1 45,6-47,8 43,2-45,6 34,3-45,6 45,6-56,8 40,1-43,2 Map: Tamás Hardi. The first nine sub-regions of the lowest activity are Polish, followed by Polish and Hungarian sub-regions up to place 62, where the Kassa sub-region, the Slovakian subregion of the lowest activity, can be found. The Hungarian territorial unit of the greatest activity is Budapest, at place 59, i.e. 49 sub-regions overtake it from the other three countries, its activity is even lower than that of the weakest Slovakian sub-region and significantly lower than the weakest Czech sub-region. So on the average the activity of Hungary and Poland only moderately differ from each other, the Polish activity rate is diffused in a much wider range, since there are 11 Polish sub-regions among the most active 14 sub-regions. The economic activity of the Czech Republic and Slovakia is significantly higher than that of the two other countries’, and the regional differences within the country are significantly smaller. It is characteristic of Hungary and Slovakia that where unemployment is lower, the economic activity is higher (the correlation between the two indicators is stronger than medium, 0,7). This applies to the Czech Republic, too, but the West-Czech sub-region Karlovy Vary has an outstanding value, where besides higher unemployment there is higher activity, and this significantly decreases the closeness of the relation. On the other hand in Poland there is no relation between unemployment and activity rates, there are several examples for all four types (lower unemployment–higher activity, lower unemployment-lower activity, higher unemployment-higher activity, higher unemployment-lower activity). Next we are going to examine five index numbers, which describe certain aspects of competitiveness indirectly. The correlation coefficients of the new indicators with the earlier indicators are shown in Table 4. From the relations of the already analysed Competitiveness of Automotive Centres in Central and Eastern Europe 209 210 Tamás Dusek indicators it is worth to note how little the relation between the unemployment rates of 2002 and 2009 is, especially compared to the relation between GDP/capita in 2002 and 2008. This is interesting also because analysing this separately in case of the various countries we can find much closer relations everywhere, the drastic decrease of unemployment in Poland (from a very high basis) however resulted in a lower coefficient when the four countries were analysed together. The table also affirms that higher economic activity entails lower unemployment, but the lowness of the correlation indicates that there may be many exceptions to this. The other parts of the table shall be referred to in the course of the introduction of the five new index numbers. Migration balance is important because a positive balance characterizes the subregions offering attractive possibilities for work and making a living, while a rather negative balance characterizes those sub-regions which have less favourable work opportunities to offer. This indicator however is less suitable for the comparison of countries, because international migration belongs to those areas which are statistically more difficult to follow. Figure 8 shows the balance of internal and international migrations, for greater reliability in the average of three years. In Hungary, Slovakia and the Czech Republic this indicator correlates well with economic output and unemployment rate. In Poland the picture is more complex again, it is apparent here as well that the balance of urban agglomerations is rather the positive one, and there is no close relation between economic output and migration in other aspects either. FIGURE 8 Internal and international migration per 10,000 inhabitants, average of 2006–2008 migration per 10000 inhabitants migration per 10000 inhabitants 48-190 -81- -31 12-48 -5-12 -31- -22 -12- -5 -16- -12 -12-190 -81- -12 Map: Tamás Hardi. -22- -16 Competitiveness of Automotive Centres in Central and Eastern Europe 211 Life expectancy at birth is dispersed in a 9.2-year range, which would be of a very significant degree in a comparison between countries. Borsod-Abaúj-Zemplén County is the last, falling much behind the second worst Upper-Moravia (Figure 9). It is interesting to note that two metropolitan sub-regions, Lódz and Katowice which count as industrial centres are also among the worst positioned sub-regions, while life expectancy at birth is 4.5 years longer in Warsaw and Cracow (the first two Polish subregions). The Czech Republic is responsible for the majority of the total dispersion, because here the dispersion range itself is 8.8 years. The first six places are occupied exclusively by Czech regions, but Prague is not among them, it is only at place 27 among all sub-regions, and is in the middle field within the Czech Republic. In the other three countries however the capital sub-regions are at the top within the particular countries, but even so Budapest is only the 57th in the total ranking, i.e. is below the median. Within Poland this indicator does not correlate with economic output either, because the south-eastern and eastern sub-regions which are placed at the back in the economic ranking are early in the ranking here. FIGURE 9 Life expectancy at birth, 2008 Life expectancy Life expectancy 77,0-81,1 71,9-73,5 76,0-77,0 75,5-76,0 73,5-74,0 75,0-75,5 71,9-75,0 74,5-75,0 75,0-81,1 74,0-74,5 Map: Tamás Hardi. The building of new dwellings reflects the development of the economic situation quite well, but demographic conditions also exert a significant influence on its extent. From all the analysed secondary indicators this is the most closely connected to GDP per capita and unemployment rate; it has a positive relation with the former, and a negative with the latter. The agglomeration sub-regions surrounding metropolises 212 Tamás Dusek occupy the first places; these indicate the positive deviations from the values influenced by the economic situation (Figure 10). In an absolute sense this indicator is the most closely related to unemployment, and secondly to migration balance, which is not at all surprising. FIGURE 10 Newly built dwellings per 10,000 inhabitants, 2008 Dwellings/10000 inhabitants Dwellings/10000 inhabitants 56-111 12-19 42-56 35-42 19-22 30-35 12-30 27-30 30-111 22-27 Map: Tamás Hardi. The proportion of industrial employment per population is indirectly also connected to competitiveness, because a greater proportion indicates either the greater economic activity of the population, or greater productive capacity, or both. The indicator itself is similar in its extent to that of building dwellings, it is slightly more loosely connected to GDP and unemployment rate, while its connection to economic activity is closer (Figure 11). Komárom-Esztergom County ranks first, outstandingly overtaking the second Polish Tyski sub-region by five percentage points. These first two are followed by a number of Czech sub-regions, where only the service providing centre, Prague is not included among the leading sub-regions. The lowest level of industrial employment can be found primarily in the Eastern-Polish sub-regions. The last indicator analysed is the number of crimes per inhabitant (Figure 12). It is well-known that these kind of statistics are to be handled with extreme care, their temporal and spatial comparison is made more difficult by the arbitrariness of discriminating between offence and crime, their national differences and temporal change, the difference in the reconnaissance ratio, the statistical contraction of more crimes tried simultaneously and the lack of discrimination between crimes of extremely different weight and kind (from murder to parking ticket counterfeit). In the knowledge of these limitations we still present crime statistics, because even if it is less suitable for Competitiveness of Automotive Centres in Central and Eastern Europe FIGURE 11 Industrial employment per 100 inhabitants (2008) industrial employment per 100 inhabitants 130-195 195-229 229-245 industrial employment per 100 inhabitants 385-673 337-385 310-337 245-276 276-310 276-673 130-276 Map: Tamás Hardi. FIGURE 12 Crimes per 10,000 inhabitants, 2008 crimes per 10000 inhabitants 130-195 195-229 229-245 crimes per 100 inhabitants 385-673 337-385 310-337 245-276 276-310 276-673 130-276 Map: Tamás Hardi. 213 214 Tamás Dusek comparison between countries, it does show regional characteristics. On the basis of these it can be first of all ascertained that the metropolitan sub-regions are in the front line everywhere. Territorial differences within countries are observable only in the Czech Republic and Poland; more crimes are committed in the western sub-regions. In case of the eight, with the two plus years altogether ten analysed indicators, it is worth to see to what extent it is possible to ascribe territorial differences to differences between countries and differences within countries. This question, which can be analysed by the variance-quotient in the simplest way, was touched on in case of certain indicators. The results are displayed in Table 5. On the basis of this, it was in case of the 2002 unemployment rate that the value of a particular sub-region was the most influenced by which country it is located in, because by this time due to the high Polish data the differences between the countries were responsible for 63.8% of the variable-quotient between regions, and only the remaining 36.2% was ascribable to the differences within countries. Industrial employment ranks second, which was principally influenced by the high ratio of the Czech Republic. TABLE 5 Factors explaining spatial differences Indicator 1 2 3 4 5 6 7 8 9 10 GDP/capita, 2008 GDP/capita, 2002 Economic activity, 2009 Unemployment, 2009 Unemployment, 2002 Migration, average of 2006–2008 Life expectancy at birth Dwellings/10000 inhabitants Industrial employment Crime/1000 inhabitants By means of differences between countries By means of differences between urban sub-regions and non-urban sub-regions part explained from regional differences,% 12,3 53,1 12,7 55,0 24,5 2,5 20,9 12,3 63,8 1,7 19,5 0,2 24,3 1,9 4,4 21,7 33,6 0,0 20,6 34,1 Source: Own calculation. Apart from the differences between countries, the other generally analysable characteristic feature is the effect the difference between urban regions and non-urban regions has on the overall difference. Here the four capital regions and further seven Polish urban regions were separated from all the other sub-regions, i.e. Bratislava was also considered as an urban region despite the fact that it really constitutes a sub-region together with its agglomeration and wider surroundings. This distinction has an effect mostly on GDP dispersion, explaining more than half of the variance, in case of this indicator the difference between countries played a negligible part. The difference of industrial employment is not influenced by this distinction because the urban industrial average and the industrial average of the other sub-regions roughly correspond to each Competitiveness of Automotive Centres in Central and Eastern Europe 215 other, significant differences in industrial employment occur within the circle of nonurban sub-regions. The complex indicators of competitiveness The former analyses examined the components of competitiveness only individually. This has its own raison d'ętre, but the individual analysis of the different indicators cannot replace the expression of competitiveness by a synthetic index-number. First the three basic indicators are expressed by one indicator. The original index-numbers are transformed with the help of range in the following way: xi' = xi − x min xmax − xmin With this transformation the indicators become unit-independent, the minimum value will be zero, and the maximum value will be one. The basic indicators of the Human Development Index are transformed in the same way. The thus transformed indicators of GDP per capita, unemployment rate and activity rate are averaged and then multiplied by a thousand so that it is more easily dealt with. This way the indicator will have a value in the range of zero and thousand. In case of unemployment rate the indicator has to be reversed, because the smallest value is the most favourable there, and the greatest value is the worst. The first 10 and last 10 territorial units of the resulting competitive ranking are displayed in Table 6; in the appendix the whole list is shown. The three capital regions stand out from the field, the fourth, Budapest significantly falls behind the other three capitals. There are only Hungarian and Polish sub-regions among the worst ones. Figure 13 shows a spatial distribution, not really in a differentiated way, as in case of the former indicators, but the territorial differences are beautifully delineated in it. As the second method of performing a joint, complex analysis of the indicators, we separated the sub-regions of different types from each other with the help of cluster analysis. This method may be regarded richer in information than the first one in the sense that it separates those sub-regions from each other which are altogether of similar competitiveness, but which are different from the viewpoint of competitiveness factors. For instance, a region with high GDP and high unemployment can be of an averagely similar competitiveness to a sub-region with lower GDP and lower unemployment, while belonging to two different types at the same time. These distinctions cannot be ascertained from the former ranking. Those six indicators were included into the analysis which are connected to competitiveness and are suitable for international comparisons between countries. So in addition to GDP per capita, activity rate, and unemployment rate, we have now the specific building of dwellings, life-expectancy at birth and migration rate. Industrial 216 Tamás Dusek employment was not included, because it is a structural indicator; and the number of crimes was also excluded from the analysis due to its incomparability between countries. Before performing the cluster analysis, the data sheets were divided by their dispersion to make them unit-independent. Five clusters were created, because this enables an appropriate degree of differen– tiality. The cluster centers can be seen in Table 7, the spatial distribution of clusters in shown in Figure 14. The cluster centers are given in their original units, because they would be less graphic when standardized. Capitals are again the best positioned subregions, which are well separated from all the other clusters. The sub-regions of the worst positions are also well separated, which are in the worst situation on the basis of all the six indicators. On the basis of their spatial distribution they form an integrated territory in Eastern-Hungary, Southern Transdanubia, East-Slovakia and NorthwestPoland, and to a lesser degree in Southwest-Poland. Among the other three clusters there are no such great differences. Almost all of the six sub-regions of the second cluster (except Plzen) are on the periphery of metropolises with favourable unemp– loyment rate. TABLE 6 Complex indicator of the competitiveness of sub-regions, 2008 Sub-region Hlavní mesto Praha Bratislavský kraj Miasto Warszawa Budapest Stredoceský kraj Jihocecký kraj Skierniewicki Trnavský kraj Plzenský kraj Miasto Lódz Jihomoravský kraj Baranya Somogy Békés Stargardzki Nógrád Walbrzyski Grudziadzki Koszalinski Borsod-Abaúj-Zemplén Szabolcs-Szatmár-Bereg Competitiveness GDP/capita (Euro, PPP) Activity Unemployment 940 922 908 717 660 641 641 636 633 629 608 275 272 265 209 195 191 189 176 166 94 43 624 42 002 41 671 35 919 18 819 17 031 10 389 20 856 17 292 17 390 19 672 11 525 10 039 9 343 9 018 7 298 10 861 9 683 11 465 10 122 8 348 54,3 56,5 57,6 45,9 51,2 51,0 59,2 53,1 51,8 56,1 49,2 38,1 38,8 38,6 36,6 38,5 34,3 32,1 32,4 37,3 37,4 1,9 3,4 4,6 4,3 2,6 2,6 4,6 5,9 3,6 6,5 4,4 10,4 10,3 10,2 11,6 12,7 11,9 10,2 11,8 14,7 17,5 Source: Own calculation on the basis of Eurostat data. Competitiveness of Automotive Centres in Central and Eastern Europe 217 FIGURE 13 Complex indicator of competitiveness, 2008 complex competitiveness 555-940 482-555 408-482 336-408 94-336 Map: Tamás Hardi. TABLE 7 Cluster center values (2008 data) Indicator GDP/capita Activity Unemployment Building of dwellings (10000 inhabitants) Migration (10000 inhabitants) Life expectancy at birth Number of sub-regions belonging to the cluster Source: Own calculation. 1 2 3 4 5 40 804 53,6 3,6 14 919 44,1 4,0 14 331 43,3 5,7 14 004 49,2 6,8 10 742 40,1 10,5 77,1 69,8 76,2 77,0 118,2 75,8 44,7 –2,0 77,0 30,9 3,6 74,4 23,3 –28,5 74,3 4 7 28 37 32 218 Tamás Dusek FIGURE 14 Spatial distribution of the types of competitiveness, 2008 Clusters 1 2 3 4 5 Map: Tamás Hardi. The difference between the third and fourth clusters is minimal, with perceivable difference only in the number of dwellings built and life expectancy at birth, the third is in a better position than the fourth with respect to these, however, activity is bigger in the fourth. As a whole the picture did not really change in comparison to the former situation of three indicators, which is caused by correlation between the indicators, i.e. if a sub-region is more favourable from the viewpoint of an indicator, it is more favourable in the others as well. Competitiveness of Automotive Centres in Central and Eastern Europe 219 The situation of sub-regions with automotive factories The list of the four countries’ automotive and motor factories can be seen in Table 8. The suppliers of the automotive factories are not included in the analysis, because it would be impossible to separate the supplies for automotive factories and other industrial sectors. The altogether 33 factories are in 28 sub-regions, since there are two factories in five sub-regions. The table includes only currently operating enterprises; the ones under planning or implementation, such as Mercedes-Benz in Kecskemét are excluded, since the effect of these would be perceivable only later. Some factories manufacture both motors and vehicles. In Hungary there are only greenfield automotive factories, while in the Czech Republic only two out of the 11 factories, and half of the 16 factories in Poland were established as greenfield investments. Part of the greenfield investments were established in cities with former engineering traditions (e.g. Győr, Szentgotthárd), and the Volkswagen factory of Bratislava is the heir of the former small factory unit of Skoda. TABLE 8 Automotive factories in the four countries Settlement Settlement’s, population* Factors Beginning of production** Production Tedom Divize Motory (Tedom Engines Division) Toyota Peugeot Citroën Automobile Czech Tatra Škoda Avia Ashok Leyland Motors SOR Libchavy Škoda Hyundai Motor Manufacturing Tedom Divize Bus Iveco Czech Republic Škoda 1990 2005 engine production cars 1990 1990 1990 1990 1990 2008 1990 1990 1990 cars, trucks cars trucks buses cars cars buses buses cars 175,183 FIAT-GM Powertrain 1990 1,250 Solaris Bus and Coach 1996 engine production buses General Motors Manufacturing Poland/Opel Polska Toyota Motor Industries Poland 1998 cars 2005 engine production 1 Czech Republic Jablonec nad Nisou 45,328 2 Kolin 30,935 3 4 5 6 7 8 9 10 11 Koprivnice Kvasiny Letnany (Prague) Libchavy Mlada Boleslav Nosovice Trebic Vysoké Myto Vrchlabi Poland Bielsko-Biala 1 2 3 Bolechowo (Poznan) Gliwice 4 Jelcz-Laskowice 23,044 1,381 1,248,026 1,708 44,750 994 38,156 12,669 12,710 195,181 15,496 220 Tamás Dusek Count. Table 8 Settlement Settlement’s, population* Factors Beginning of production** Production engine production, pick-up trucks trucks 5 Lublin 348,961 Andoria MOT 1990 6 7 8 9 10 11 Niepolomice Polkowice Poznan Poznan Slupsk Starachowice 9,263 22,087 552,735 552,735 96,871 51,766 MAN Nutzfahrzeuge Volkswagen Motor Polska MAN Nutzfahrzeuge Volkswagen Poznań. Scania Production Slupsk MAN Nutzfahrzeuge (MAN Star Trucks and Buses) Fiat Auto Poland 2007 1999 1998 1990 1990 1990 2002 1990 cars 632,561 632,561 Toyota Motor Manufacturing Poland FSO (Fabryka Samochodów Osobowych) Volvo Polska Jelcz Polskie Autobusy cars, engine production cars 1995 buses, trucks buses 30,914 130,478 Magyar Suzuki Zrt Audi Hungaria Motor Kft 1991 1993 General Motors Powertrain – Magyarország Autóipari Kft. 1991 auto engine production, cars engine production Volkswagen Slovakia PCA Slovakia (PSA Peugeot Citroën) Kia Motors Slovakia (HyundaiKia) 1991 2006 cars cars 2004 cars, engine production 12 Tychy 129,438 13 Walbrzych 120,724 1,716,855 14 Warsaw 15 Wroclaw 16 Wroclaw Hungary 1 Esztergom 2 Győr 3 Szentgotthárd 1 2 Slovakia Bratislava Trnava 3 Zilina 8,881 431,061 67,605 85,252 1990 trucks cars buses trucks, buses *2009 or 2010; **In case of the year 1990 production started before 1991. Source: Collected by Melinda Pató. The number of employees directly employed in factories was an estimated 95 thousand in 2010 (Table 9). The proportion of employees in automotive industry is high especially in the Czech Republic, while at the same time, the value of Hungary can be considered significant because Suzuki, Audi and General Motors all started their production after 1990. Automotive industry has the greatest tradition in the Czech Republic, principally due to Skoda founded in the 19th century, which manufactured 193 thousand cars in 1989, from which 45 thousand were exported to Western-Europe Competitiveness of Automotive Centres in Central and Eastern Europe 221 (Jakubiak et al. 2008). 55% of people employed in the Czech Republic work in the Skoda factories. Although the proportion of greenfield investments is small in the Czech Republic, these happened after 2000 and are very significant in their absolute size (Toyota-Peugeot-Citroën in Kolin and Hyundai in Nosovice). Hungary counted as a great power in bus production until 1990, but following a slow cut-back the sector disappeared by 2007. In Slovakia there were two greenfield and one brown field investments. In Bratislava Volkswagen used Skoda’s licence manufacturing Bratislavské automobilové závody (BAZ, Bratislava Automotive Factors) facilities, and introducing a totally new technology (Jakubiak et al. 2008). This way Volkswagen’s settlement here may as well be regarded as a greenfield investment. There used to be a factory manufacturing pick-up trucks in Trnava, but the Peugeot-Citroën factory settling here can be considered a greenfield investment, similarly to KIA in Zilina. Owing to these three great new automotive industrial investors, Slovakia became the first in the world with respect to the number of cars per inhabitant in the course of the 2000s. TABLE 9 Number of automotive factories and their employees Country Czech Republic Poland Hungary Slovakia Altogether Number of factories Employees (2010, thousand people) 11 16 3 3 33 40,0 29,3 12,2 14,0 95,5 Source: On the basis of the collection of Melinda Pató. The average competitiveness of sub-regions with automotive factories significantly exceeds the competitiveness of sub-regions without automotive factories (Tables 10– 11). This is true both of the complex and all other individual indicators, even if the urban and non-urban regions are analysed separately. The cause and effect relationship is probably not one-way, but there is a mutually strengthening back and forth relationship. I.e. higher competitiveness creates more advantageous circumstances for the establishment of automotive factories, and the establishment and operation of automotive factories improves the region’s competitiveness. It is worth to note that the GDP per capita increased by 6 percentage points faster in the automotive industrial regions between 2002 and 2008. This was not only due to the previously mentioned outstandingly growing sub-region of Bratislava, because even if we consider the only non-urban regions, the difference is still 3,8 percentage points. In Slovakia the greatest competitiveness difference is between the averages of the three sub-regions with automotive industry and the five sub-regions without automotive industry. The merging of cause and effect can be well observed within Slovakia: the three western regions with automotive industry were 222 Tamás Dusek originally more developed than the Central- and Eastern-Slovakian regions, but the coming of automotive factories has further increased the already existing differences. TABLE 10 Competitiveness of sub-regions with and without automotive factories by countries Country Average of subregions with automotive factories 640 474 520 684 548 Czech Republic Poland Hungary Slovakia Altogether Average of subregions without automotive factories 577 412 338 404 410 Average of all subregions 609 412 365 509 444 Source: Own calculations. TABLE 11 Competitiveness of sub-regions with and without automotive factories Indicator Sub-regions with automotive factories total Complex indicator GDP/capita, 2008 Activity Unemployment Life expectancy at birth Dwellings Migration GDP/capita, 2002 GDP changes, 2002– 2008 cities only non-urban sub-regions only Sub-regions without automotive factories total cities only non-urban sub-regions only 548 123,6 46,5 5,6 771 224,8 49,8 3,8 495 99,5 45,8 6,0 410 79,0 44,3 7,9 561 135,9 46,3 5,7 398 74,5 44,1 8,1 75,6 76,5 75,4 75,1 75,0 75,1 477 2626 120,1 793 2887 212,6 401 2563 98,1 332 –496 81,5 501 –733 139,7 319 –477 76,9 3,5 12,2 1,4 –2,5 –3,8 –2,4 Source: Own calculation. It is worth to look at the automotive industrial sub-regions of weaker competitiveness separately. These are found in Poland: the complex indicator value of the subregions of Walbrzych, Slupsk, Gliwick, Bielsk is below the average of the sub-regions without automotive factories. The Toyota motor factory in Walbrzych was established with a middle-size greenfield investment in 1999, the number of employees was two thousand in 2010. The Scania factory in Slupsk was originally the joint company of Scania and Kapena, until all shares were bought by Scania in 2003. The number of employees amounts to 700 people. The General Motors factory in Gliwice employs Competitiveness of Automotive Centres in Central and Eastern Europe 223 three thousand people. There is a Fiat motor factory in Bielsko-Biala, with 1200 employees. All factories belong to the smaller, small-medium sized factories at the most, at least considering the average size of automotive factories (in the four countries jointly 2900 employees constitute the average according to places of production). The smallest factory however can be found in Prague; 283 employees worked in the Avia in 2008. The small weight of this obviously does not perceptibly influence the situation of Prague, while Volkswagen in Bratislava with its eight thousand (more than ten thousand back in 2006) employees counts as a dominant enterprise even on Bratislava’s scale. The biggest factory is Skoda’s central plant in Mlada Boleslav, and owing to its successful operation Mlada Boleslav with forty-five thousand inhabitants is one of the richest Czech cities. Summary The site of the analysed four countries’ automotive factories are situated in settlements of remarkably different sizes, the difference between the smallest and the largest settlement is four orders of magnitude, more than a thousand-fold. Therefore the methodological conditions of settlement level comparison are not given, an average size automotive factory plays a totally different part in the labour market, economy of a city of million inhabitants, as in a thousand-inhabitant village and its surroundings. The territorial effect of automotive factories were therefore analysed at NUTS3 level that can be filled with statistical data. In the four countries the competitiveness of automotive industrial regions, sub-regions on the average significantly exceeds the competitiveness of regions without automotive industry, with higher income producing capacity, lower unemployment and higher economic activity. This also demonstrates that automotive industry is a key actor of modern processing industry, which affects the production of many other industrial sectors due to its size and input- and output connections, and generally influences economy through the income generated in the industrial sector. Automotive industry has the greatest traditions in the Czech Republic, but two significant new greenfield investments took place here as well. 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Competitiveness of Automotive Centres in Central and Eastern Europe 225 APPENDIX 1 Complex indicator of the competitiveness of sub-regions, 2008 Code and name of sub-region Competitiveness CZ010 – Hlavní mesto Praha 940 CZ020 – Stredoceský kraj 660 CZ031 – Jihocecký kraj 641 CZ032 – Plzenský kraj 633 CZ041 – Karlovarský kraj 526 CZ042 – Ústecký kraj 498 CZ051 – Liberecký kraj 546 CZ052 – Královéhradecký kraj 601 CZ053 – Pardubický kraj 604 CZ063 – Vysocina 602 CZ064 – Jihomoravský kraj 608 CZ071 – Olomoucký kraj 533 CZ072 – Zlínský kraj 604 CZ080 – Moravskoslezský kraj 525 HU101 – Budapest 717 HU102 – Pest 479 HU211 – Fejér 467 HU212 – Komárom–Esztergom 530 HU213 – Veszprém 416 HU221 – Gyor–Moson–Sopron 555 HU222 – Vas 476 HU223 – Zala 457 HU231 – Baranya 275 HU232 – Somogy 272 HU233 – Tolna 310 HU311 – Borsod–Abaúj–Zemplén 166 HU312 – Heves 287 HU313 – Nógrád 195 HU321 – Hajdú–Bihar 302 HU322 – Jász–Nagykun–Szolnok 337 HU323 – Szabolcs–Szatmár–Bereg 94 HU331 – Bács–Kiskun 336 HU332 – Békés 265 HU333 – Csongrád 370 PL113 – Miasto Lódz 629 PL114 – Lódzki 482 PL115 – Piotrkowski 587 PL116 – Sieradzki 533 GDP/capita (Euro, PPP) 43 624 18 819 17 031 17 292 13 957 16 249 14 753 16 907 16 848 15 868 19 672 15 187 17 091 17 420 35 919 14 150 15 057 16 933 11 797 18 281 14 068 13 309 11 525 10 039 11 525 10 122 11 137 7298 11 423 10 438 8348 10 794 9343 12 010 17 390 12 037 12 258 10 173 Activity Unemployment 54,3 51,2 51,0 51,8 52,1 48,6 48,3 50,0 49,7 49,9 49,2 49,0 49,9 49,1 45,9 44,0 43,1 46,2 43,6 44,5 44,5 45,4 38,1 38,8 40,5 37,3 40,3 38,5 37,9 40,9 37,4 40,7 38,6 41,1 56,1 50,9 58,5 53,2 1,9 2,6 2,6 3,6 7,6 7,9 4,6 3,9 3,6 3,3 4,4 5,9 3,8 7,4 4,3 5,1 5,5 5,1 6,9 3,5 5,5 6,6 10,4 10,3 10,1 14,7 11 12,7 8,9 8,5 17,5 8,6 10,2 7,7 6,5 8,2 7,7 6,2 226 Tamás Dusek Count. Appendix 1 Code and name of sub-region PL117 – Skierniewicki PL121 – Ciechanowsko–plocki PL122 – Ostrolecko–siedlecki PL127 – Miasto Warszawa PL128 – Radomski PL129 – Warszawski–wschodni PL12A – Warszawski–zachodni PL213 – Miasto Kraków PL214 – Krakowski PL215 – Nowosadecki PL216 – Oswiecimski PL217 – Tarnowski PL224 – Czestochowski PL225 – Bielski PL227 – Rybnicki PL228 – Bytomski PL229 – Gliwicki PL22A – Katowicki PL22B – Sosnowiecki PL22C – Tyski PL311 – Bialski PL312 – Chelmsko–zamojski PL314 – Lubelski PL315 – Pulawski PL323 – Krosnienski PL324 – Przemyski PL325 – Rzeszowski PL326 – Tarnobrzeski PL331 – Kielecki PL332 – Sandomiersko– jedrzejowski PL343 – Bialostocki PL344 – Lomzynski PL345 – Suwalski PL411 – Pilski PL414 – Koninski PL415 – Miasto Poznan PL416 – Kaliski PL417 – Leszczynski Competitiveness GDP/capita (Euro, PPP) Activity Unemployment 641 505 521 908 352 523 460 587 475 287 408 336 441 410 344 365 392 539 437 528 393 509 431 369 362 352 467 367 386 10 389 14 870 10 400 41 671 10 106 11 516 16 773 21 855 9484 8390 10 505 8735 11 911 13 851 13 719 11 199 15 267 20 219 14 575 20 286 8252 8386 12 436 8671 8684 8140 11 000 10 316 12 099 59,2 52,8 52,6 57,6 44,7 48,3 39,5 47,6 49,1 36,4 43,3 36,7 45,1 37,5 35,9 42,9 38,6 47,0 44,6 42,4 46,1 54,6 49,1 47,2 44,2 43,8 47,1 45,5 45,7 4,6 9,5 6,5 4,6 10 4,3 4,4 5,4 6,3 7,3 6,5 5,2 6,6 4,4 6,6 8,7 6,6 6,7 7,7 4,4 7,9 7,4 9,8 10 8,5 8,5 6,1 9,8 9,8 569 512 355 355 309 408 569 430 374 9937 12 202 8559 9368 10 980 10 616 28 166 10 948 11 817 58,6 49,5 40,6 41,2 35,9 46,4 38,0 46,2 36,8 7,6 5,9 6,6 7,3 7,1 8,4 3,3 7,4 4,8 Competitiveness of Automotive Centres in Central and Eastern Europe 227 Count. Appendix 1 Code and name of sub-region Competitiveness PL418 – Poznanski PL422 – Koszalinski PL423 – Stargardzki PL424 – Miasto Szczecin PL425 – Szczecinski PL431 – Gorzowski PL432 – Zielonogórski PL514 – Miasto Wroclaw PL515 – Jeleniogórski PL516 – Legnicko–Glogowski PL517 – Walbrzyski PL518 – Wroclawski PL521 – Nyski PL522 – Opolski PL613 – Bydgosko–Torunski PL614 – Grudziadzki PL615 – Wloclawski PL621 – Elblaski PL622 – Olsztynski PL623 – Elcki PL631 – Slupski PL633 – Trojmiejski PL634 – Gdanski PL635 – Starogardzki SK010 – Bratislavský kraj SK021 – Trnavský kraj SK022 – Trenciansky kraj SK023 – Nitriansky kraj SK031 – Zilinský kraj SK032 – Banskobystrický kraj SK041 – Presovský kraj SK042 – Kosický kraj 445 176 209 442 382 409 448 518 348 495 191 513 288 434 431 189 296 417 387 284 290 491 360 367 922 636 582 506 495 279 321 334 GDP/capita (Euro, PPP) Source: Own calculation on the basis of Eurostat data. 16 115 11 465 9018 18 136 12 834 12 246 12 002 21 649 11 074 21 200 10 861 12 272 9011 13 830 15 771 9683 10 386 9867 11 653 8962 10 982 19 024 9768 10 898 42 002 20 856 16 456 15 366 15 796 13 657 10 659 14 922 Activity Unemployment 38,2 32,4 36,6 39,8 42,3 41,7 45,6 42,8 46,2 47,3 34,3 52,1 38,2 40,6 40,3 32,1 42,5 45,1 41,9 38,2 37,3 38,5 35,4 40,9 56,5 53,1 49,8 50,9 48,5 50,1 46,7 45,2 4,1 11,8 11,6 6,1 8,2 6,3 6,6 5,8 11,5 9,5 11,9 7,5 8,7 5,1 5,9 10,2 11,5 6,9 7,2 8,8 8,9 3,3 3,7 7,2 3,4 5,9 4,5 8,5 7,8 18,5 13,0 13,4 LOCAL ECONOMIC DEVELOPMENT AND THE AUTOMOTIVE INDUSTRY IN GYŐR MIHÁLY LADOS – KATALIN KOLLÁR Keywords: local economic development strategy automotive industry The essay introduces the brief theoretical background of local economic development. The development path of Győr is analysed, followed by the examination of how the theoretical frameworks of local economic development can be seen in this development path, paying special attention to automotive industry, the actors of local economic development, and also the practice of strategic planning of the city and its economic development strategy. Furthermore the reader is given a brief introduction to the automotive industry of Győr-Moson-Sopron county, including Győr. A theoretical background of local economic development It is not easy to give a definition for local economic development. The difficulty is caused by the fact that there are overlaps in some characteristics with other development concepts such as settlement development, spatial development, rural development and regional development. In order to get closer to an independent definition of economic development, it is reasonable to look at the concepts of the above-mentioned fields of development. Settlement development entails planning and implementation activities that aim at the influencing of the processes of the settlement. As a part of spatial development it is actually the implementation of spatial development at settlement level (Farkas 2006). Spatial development is the conscious, development oriented intervention of municipal self-governments and national governments into the spatial processes (Faragó 2001). Rural development is a field within spatial development, during which conscious interventions are made in those rural areas whose population density is usually low and where agriculture is dominant among the branches of the economy (G. Fekete 2005). Regional economic development, putting economic processes in the centre, is focused on nodal regions (Lengyel 2002). Although local and regional economic development are similar to each other, there are some differences too: in the case of local economic development, the focus of development is a specific dominant settlement, while this is not always the case in regional economic development (Bajmócy 2011). Having briefly discussed the above development definitions, in our study we use the following definition for local economic development: local economic development is a conscious intervention into the life and processes of local economy that may utilise both external and internal resources, its initiator may be an external actor like the central Local Economic Development and the Automotive Industry in Győr 229 government or foreign capital, still the most important is the cooperation of the local actors who may act as initiators, supporters, managers or acceptors of the development ideas (Mezei 2006). The range of actors in local economic development is extremely wide. Different authors apply different methods for grouping them. Lengyel, e.g., differentiates among four “legs” of local economic development; in his opinion the four main actors are as follows (Lengyel 2010): − − − − Local governments (Subnational governments); Business sphere; Institutions of knowledge transfer; Development agencies. The thoughts in the paragraphs above reveal that local economic development is by far not the exclusive responsibility of the local governmental organs and is not a process implemented according to the regulations of the central government, either. The system standing “on four legs”, on the other hand, is not complete, because none of the categories include local inhabitants who may also be active participants in local economic development, either by individual actions or group activities. These groups e.g. may become non-governmental organisations, which is again a category that is missing in the above list of four types of actors. Nevertheless we can say that the first two “legs” are the ones that play the most important role in the process in the majority of cases. In the definitions we have to highlight the importance of the local actors. External actors often participate too in the planning process wither with their financial, or intellectual capital and even trust, but the participation of local actors is indispensable, in fact, it is best if they are the initiators of the developments. Trust is also important because it is an irreplaceable tool to “start up” the community – it is an engine, actually (Czene–Ricz 2010). The role of the central government in the realisation of local economic development is evident, in fact, it is of crucial importance in the implementation of some development objectives, as they generate the creation of the institutional system necessary for the development or e.g. the provision of the regulatory background (Horváth 1998). The next level is the territorial level, whose role in local economic development is extremely different across the various countries; it is usually the regulatory background and the administrative system that are the dominant factors. The role of this tier was appreciated in the Western part of Europe in the early 1990s (Pálné Kovács 1999). This circle contains all actors of the subnational levels, including regional self-governments, local selfgovernments, municipal associations, development agencies, businesses, institutions of knowledge transfer, non-governmental organisations and the inhabitants. The role of local government is crucial, in some countries exlusive in the process of local economic development. This is usually influenced by three factors: the prevalent political direction, in the first place; the legal environment and finally the municipal organisation. The political direction has a significant impact on objectives and the 230 Mihály Lados – Katalin Kollár methods for the realisation of them. Although municipal self-governments do not have obligatory local economic development tasks, the legal environment does play a crucial role in the obligations and freedom of action of the self-governments. The organisation of the municipal self-government, finally, also influences the success of the tasks to be implemented during development, because the methods of the realisation will be adjusted to the characteristics of the existing structure (Bajmócy 2011). The reason for the creation of local and regional development agencies is also the implementation of economic development objectives. Coming from their operation, they are closely linked to the governmental sector. Agencies may be e.g. innovation agencies, business development agencies or even local economic development agencies. Local businesses participate in local economic development in two functions: on the one hand, they are active developers, and they are also the target group, on the other hand. As a target group, however, businesses are far from being a single group; the character and the tools of development are not the same for each business and group of businesses, either. Local economic development itself targets a group of the businesses and not the whole of the business sector. The size of the company is a dominant factor in how they can join the process of economic development; larger companies are able to put more capital, time and resources into the process, but it may happen that coming from their power and role they become absolute leaders, leaving no space for the consideration and implementation of objectives other than theirs. It is also important to see that it is not always the demand of the existing local businesses that should be taken into consideration: we must not neglect the possibility of the birth or strengthening of new industries, either (Bajmócy 2011). It is a dominant feature of businesses that these days they participate in market process not on their own but in cooperation with one another in different forms. Such cooperations are e.g. networks or clusters (Angyal 2003). The fourth group of actors includes the knowledge transfer institutions: these institutions have a very important role on the development of the competitiveness of the respective area. Their main task is the creation of new knowledge, the promotion of its flow and the training of human resources. As we have already mentioned, non-governmental/non-for-profit organisations can also play a significant role in the process of local economic development, either if they take place in the elaboration of development documents, the work of the municipal selfgovernments or even in the management of investment as their main activity, or if they do so indirectly, e.g. by information transfer or opinion shaping (Reisinger 2010). In the next section we are focusing on the „first leg” of local economic development, the role of local governments. We will analyse that how the theoretical framework of local economic development turned into practice in a Hungarian big city, Győr. Local Economic Development and the Automotive Industry in Győr 231 Development path of the city of Győr Győr is the sixth biggest city in Hungary by population (131,267 people), the total number of inhabitants in the city and its hinterland exceeds 200,000. In the European urban hierarchy system Győr and its agglomeration is thus taken as a Functional Urban Area (FUA) with international/national importance. These are the centres that are featured in the maps of European urban centres (HCSO). While the number of population of the city has by and large been stagnating in the recent two decades, as a combined effect or natural decrease and positive migration balance, the number of inhabitants of the settlements in the direct attraction zone of Győr – along the main transport routes – is continuously growing, induced by the impacts of suburbanisation and agglomeration processes. The engine of this process has been the successful transformation and the implemented development path of the economy of Győr has over the last two decades. This process resulted that Győr has become by now the second strongest economic pole in Hungary after Budapest and its agglomeration. The leading factor in this economic development is automotive industry. This development is not without roots: industry, including machinary and automotive industry settled down in Győr 120 years ago. The emblematic representative of this industry, the Rába Magyar Vagon- és Gépgyár (Rába Hungarian Wagon and Machinery Works) manufactured a wide range of vehicles until the end of World War II: railway carriages, cars, lorries, city vans ands military vehicles. In fact, during the war the company even produced aircraft (e.g. Messerscmidt Me2010 bomber). After the establishment of the socialist planned economy and the birth of the internal market of the eastern block, the COMECON, the activity of the company became specialised. Apart from the military vehicles, the manufacturing of complete vehicles was stopped. On the other hand, the manufacturing of parts of different vehicles became dominant, like bus engines, undercarriages of trucks and agricultural machinery (tractors). After the systemic change, the elimination of the COMECON and the decline of state orders resulted in a significant loss of markets, which forced several times the restructuring and the narrowing of the activity of the factory (Dusza 2003). In the present product range of the company, the manufacturing of undercarriages is dominant. Looking at the hundred-year history of the factory we can say that the Rába factory accumulated a substantial knowledge base of automotive industry in the city of Győr, from development through manufacturing of parts right to assembly. This basis was very much necessary after the second third of the 1990s for the automotive industry “boom” in the city, including the settling down of Audi Hungaria Motor Kft. in Győr. The city of Győr implemented the economic restructuring concomitant with the systemic change more successfully than the average Hungarian and Central and Eastern European cities did. The reasons for this are manifold. The most important factor is the accessibility. Győr was relatively rapidly accessible both on rail and road, and on a network of better quality than the Hungarian average of transportation. So the city became geographically more easily accessible for foreign direct investment. 232 Mihály Lados – Katalin Kollár This in itself, however, would be too little for a successful change. A factor almost as important as accessibility is the almost century-old industrial culture of the city, offering job opportunities for men and women alike, and the trained labour force necessary for this. In addition, coming from the outstanding industrial role that Győr had before the systemic change too, the infrastructure (both quality and quantity) was much better built out in the city than in the majority of the Hungarian and in many other Central and Eastern European cities. This gave Győr a competitive advantage in the attraction of production plants. This was supplemented by the receptiveness and openness of the (municipal self-government of the) city toward investors. These factors together made Győr a really popular destination for the foreign direct investments, both as regard greenfield and brownfield investments, often realised through privatisation. In the two decades following the systemic change, the economic structure of the city basically transformed. Induced by the changes of the market conditions and the cost factors influencing them (costs of labour and transportation), within the formerly diversified industry of Győr the centres of light industry (textile and food processing industry) declined or even ceased to exist in several waves. Parallel to this, other sectors like commerce or financial services were reinforced by the rapid building out of the commercial and banking and insurance networks. The most intensive growth, however, was induced by machinery sector including automotive industry, as a result of the settling down and the attraction of Audi company (Mónus 2007). Of course this process cannot be linked to a single company, because Győr is not located in a vacuum. The automotive industry investments realised in the environment of the city in a 200–300 kilometre radius in the last two decades, the relative proximity of spare parts manufacturing and car assembly in the hinterland of Győr is leading to the birth of an automotive industry cluster in the Central and Eastern European space in the Marshallian sense of the word. The investment plans made for this decade make the city of Győr, together with its region, one of the real automotive industry poles of the Central European space (Grosz 2005b). Actors and tools of local economic development in Győr Starting from the broader frameworks, in the time of the systemic change the external actors influencing the operation of the local economy can be divided into two groups. One of the actors is the Hungarian state that promoted economic transformation, the realisation of the shift to the market economy by the creation of the necessary regulatory environment. The most important of these is the Corporation Act, the Transformation Act and the Privatisation Act, and on the side of the resources, the operation of the Investment Promotion Fund. In Győr the acts listed above resulted in an entrepreneurial activity above the national average, which could be seen in the growth above the countryside average in the number of enterprises per thousand inhabitants, the smaller number of factory closedowns than in other parts of Hungary and parallel to this the unemployment rate Local Economic Development and the Automotive Industry in Győr 233 far below the national average. In the first third of the 1990s, the majority of the Győr centred state owned companies were transformed into economic corporations, and in many cases they were already privately owned after the privatisation. Several of the traditional light industry companies of long traditions, however, did not survive this transition (e.g. Richards, Vegetable Oil Factory, Dairy Company). The other dominant external actors in this period were the member states of the European Union and the OECD with their advanced economies, who, as a part of their national economic policy, promoted working capital investments in the countries of the disintegrating east block. This had a major contribution to the transformation of the market structure of the respective countries, on the one hand, and, on the other hand, the local employment of the labour force could decrease immigration from these countries into the more advanced states after the borders were less strictly guarded. In these years Győr became a popular destination of foreign direct investments, in fact, the city was often referred to as a part of the investment golden triangle of Central Europe, together with Vienna and Bratislava. Foreign direct investments were active not only in green-field and brownfield developments but also in the creation of the hard and soft business infrastructure like Győr International Industrial Park and the Business Assistance Enterprise Development Foundation. In the second half of this decade and in the beginning of the new millennium the state promoted local economic development through the system of economic and spatial development. In the first period, an example is the launch of the industrial park programme in 1996. In the framework of this programme, in the first step businesses and organisations that wanted to develop concentrated industrial locations could gain the industrial park title. The parks were founded by city governments in many cases. In the second step, parks that had been awarded the title and businesses located in these parks could apply to the Earmarked Provision for Economic Development for location development; in 1997 a total of 74 projects were given no less than 5.1 billion HUF support. As a result of the supports, investments worth six and a half times the resources were realised (http://cegvezetes.hu/1998/04/penzhez-lehet-jutni/). International actors now include the European Union as a result of the accession process to this integration. In Győr and its neighbourhood several economic infrastructure development projects were implemented in the framework of the Austria –Hungary Interreg IIA Phare CBC programme, e.g. the development of port, airport, innovation centre and chamber trade centre. As regards the fourfold division of the local actors, it was definitely the municipal selfgovernment that had a leading role in the initial period of the transformation. The selfgovernment of the City of Győr was a partner in the foundation of the Győr International Industrial Park Ltd., the Győr-Gönyű Port Inc. and the Győr-Pér Airport Ltd. 234 Mihály Lados – Katalin Kollár Tools of investment promotion Why should companies choose Győr? As we have already mentioned, the geographical location of the city is excellent: on the one hand, it is on the Vienna–Bratislava–Budapest innovation axis, on the other hand, Győr is halfway between Vienna and Budapest. The transport endowments of the city are excellent; it has good east-west railway, road and waterway connections, although its north-south relations are in need of development. At the north end of the park there is the Vienna-Budapest international railway line, to which the park has two own rails. The river port of Gönyü located 20 kilometres away allows access to the city via a port linked to sea waterway. As regards international airports, the one at Budapest is 130 kilometres, the Vienna-Schwechat Airport is 90 kilometres, the Bratislava Airport is 60 kilometres away from Győr. In Pér, only 15 kilometres from Győr, there is a small airport suitable for the traffic of aircrafts up to 75 passengers. The development of the airport started around the millennium, with the construction of a paved runway, the reception building and the related establishments. The significant part of resources of this development was provided by the European Union and also by Audi Hungária Motor Kft. The investments of the Győr-Pér Airport Ltd. – founded in 1994 – include, among other things, the fencing of the airport and the provision of the lighting system. The municipality considers the continuous development of the airport indispensable, as one of the most important aspects for investors in their location decisions is the presence of a nearby working airport. The traffic figures of the last year (Table 1) show that airport had an increasing operation until the world wide financial and economic crisis started in autumn 2008. Novadays the growth of traffic flow is in increase again, however the most important user of the airport is still Audi. TABLE 1 Traffic flow of Győr-Pér Airport between 2003 and 2010 Specification Number of international operations International passengers Number of all operations 2003 2004 2005 2006 2007 2008 2009 2010 358 867 1 252 1 258 1 727 1729 2 127 2 738 2 387 4 376 6 620 3 450 9 761 12 893 13 395 13 289 3 117 3 208 3 719 3 287 8 137 10 329 4 369 4 981 Source: By the authors, based on data of the Győr-Pér Airport. Although the owners (the Municipality of Győr and Pér, and self-government of Győr-Moson-Sopron county) decided to sell the airport in 2008, the primary objective is the development of the facility, and the new owner is expected to continue the operation of the airport (Győr Megyei Jogú Város Gazdasági… 2011). Location decisions of companies may also be influenced by the rate of local business tax. In the city of Győr the tax is 2% of the net income, which is the maximum rate by the Law on Local Taxation. The municipality offers tax allowances of the local Local Economic Development and the Automotive Industry in Győr 235 business tax in different forms in order to attract businesses to the city. These tax allowances are included in a municipality decree on local taxes. Formerly an allowance of this kind was the exemption from taxation that new businesses locating in the Győr industrial park were offered for the first two years of their existance. Exemptions of enterprises from local taxation had to be cancelled by the city as of 1 January 2008, in harmony with the Competition Act of the European Union. The municipality introduced local business tax, property tax and tourism tax from among the local taxes. A central tax above which the city disposes is motor vehicle tax. As regards the volume of income, local business tax is the most significant (Table 2). The revenues of the city from this source almost doubled from 2007 to 2008. This is primarily due to the elimination of the tax exemptions of the businesses – Audi Hungária Motor Kft. in the first place and other businesses located in the industrial park to a lesser extent. The decline in the amount of local business tax in the two years afterwards, however, reflects the financial and economic world crisis. An opposite tendency can be seen in property tax, due to the enlargement of the tax base provided by the new commercial facilities inaugurated in the respective period. The municipality expects its tax revenues to increase in the middle run, but this is hindered by central regulations in the field of local business tax: the central budget takes away a part of this revenue (Győr Megyei Jogú Város Önkormányzatának Gazdasági Programja 2011–2014). TABLE 2 Local taxes and motor vehicle tax revenues in Győr between 2007 and 2010, million HUF Local business tax Property tax Tourism tax Motor vehicle tax 2007 2008 2009 2010 8,098.4 1,610.4 57.8 1,047.2 15,725.2 1,539.4 67.5 1,044.6 13,893.3 1,690.6 56.9 1,014.1 13,601.3 1,910.4 63.1 1,070.4 Source: by the authors, based on the Economic Programme of the Municipality of Győr 2011–2014. Institutional frameworks One element of the institutional framework of local economic development is the Győr International Industrial Park Ltd. established in 1991. This company operates the industrial park. The ownership of Győr municipality has represenred 40% since the foundationof the company. Although the initial concept of the park was to offer a location for small and medium-sized enterprises, from the first half of the 1990s it became more attractive for foreign companies, because the financial situation of the small and mediumsized enterprises did not allow the implementation of new green-field investments. The more intensive moving in of foreign companies started after 1995. The first time that a Hungarian owned company bought a site in the park was in 1996, by now the Hungarian businesses have outnumbered their international counterparts. The industrial park – which 236 Mihály Lados – Katalin Kollár was the first industrial park not only in Hungary but in the whole of Central Europe – was awarded the title of “Industrial Park” in 1997. At that time it boasted of 11 companies and 1,000 employees (Deák 2002). Novadays the park is situated on a land of 175 hectares, of which approximately 90% is utilised, according to data of 31 August 2011. Presently a total of 101 businesses from no less than 14 countries operate here, the number of employees reaches 5,000. The majority of the businesses working in the industrial park are in the manufacturing industry sector (Figure 1). The main economic branches include machinery, automotive industry, electronics, plastic industry, commerce and logistics. The investment worth 455 million € produces approximately 200 billion HUF revenue annually (www.ipgyor.hu). Looking at the revenues of the businesses operating in the park we can see that the incomes of the biggest ones exceed 3 or 4 billion HUF, and there are many companies that have somewhat less income which is still above 1 billion HUF. The crisis had an impact on the industrial park, although even in the year most affected by the crisis, 2009, the total revenues of the companies exceeded 122 billion HUF, and the number of employees was above 5,500. This number has decreased by approximately 1,000 as an effect of the crisis, but is expected to rise to the starting figure of 2009 again by the end of this year (Győr Megyei Jogú Város Gazdasági… 2011). FIGURE 1 Enterprises in the Győr Industrial Park on the grounds of sectors Financial Transportation, services; 1,2% storage; 1,2% Other public and personal services; 2,4% Real estate and producer services; 19,5% Manufacturing; 41,5% Trade, repair; 26,8% Construction; 4,9% Energy-, gas-, heating-, water and waste management; 2,4% Source: Lakatos (2011, 39). The presence of Audi Hungária Motor Kft. has an outstanding significance in both the city and the industrial park. There are several companies among the businesses of Local Economic Development and the Automotive Industry in Győr 237 the industrial park that are suppliers to Audi. The new investment recently launched by Audi will certainly have a significant impact on the Industrial Park in the future as well, and also on the city of Győr, increasing the recognition and economic role of Győr both in the region and Hungary. Although there is still 13.2 hectares of free land in the park, the plans of the Győr International Industrial Park Ltd. include the 15–30 hectare enlargement of the park, as a response to the development activity by Audi. In the park there is a company called INNONET Innovation and Technology Centre, established in 1997 as a result of the collaboration of several institutions and businesses, supported by the Phare CBC programme of the European Union. The establishment of this centre did not only increase the prestige of the park but also resulted in significant cooperations among the international businesses of the park and the local small and medium-sized enterprises. The centre operates as a non-for-profit company, its owners are the Municipality of Győr, the Győr-Moson-Sopron County Chamber of Commerce and Industry, the Hungarian Association for Innovation and the Universitas-Győr Foundation. The Centre actually works as an incubator, its objective is the creation of favourable conditions for innovative small and medium-sized enterprises. For the time being the capacities of the centre are utilised in almost 100%, so its present capacities do not allow the Centre to offer services for new businesses (http://www.ipgyor.hu/#). The TECHNONET Automotive Industry Technology Competence Centre was opened in September 2011 as an enlargement of the INNONET. In the implementation of the project, the INNONET owners had a significant role, of special important among them was the Municipality of Győr and the Győr-Moson-Sopron County Chamber of Commerce and Industry that raised capital in order to create the TECHNONET. For the implementation of the first phase of the project INNONET was given a 400 million HUF non-refundable support which covered 80% of the total costs. In the first phase offices, meeting rooms and joint service facilities were constructed, the second phase was about the construction of four workshops for small enterprises. The objective of TECHNONET is the promotion and support of the research and development activity of businesses. The significance of the newly created institution lies in the provision of advanced technology services besides a high level management support, as opposed to INNONET that offers basic services (Ingatlan.net). In cooperation with the British company United Biscuit that privatised the Győri Kekszgyár (Győr Biscuit Factory), the city of Győr established the Business Assistance Foundation, an organisation dealing with assistance for the creation of start-up businesses and the development of small and medium-sized enterprises. The Foundation started to operate in 1992, its objectives include the decrease of unemployment, the improvement and enlargement of the skills, entrepreneurial capacities and knowledge of the economic actors (Business Assistance Alapítvány bemutatkozás). 238 Mihály Lados – Katalin Kollár Innovation potential of Győr and knowledge transfer Knowledge can be accumulated (Dőry 2005). The foundation of the development of knowledge-based regions is given by the creation of knowledge, as well as its utilisation in the economy. The scenes for the creation of knowledge can be research places, research institutes, and higher education institutions (Dőry–Mészáros–Rechnitzer 1998). The spread of knowledge is a formal and informal process during which the research findings become known to the public. The spread of knowledge means the transfer of knowledge mediated by the educational system, and the sales of knowledge products as well. One way of the creation of knowledge is research and development, whose objective may be enlargement of the knowledge or its utilisation for the development of new applications. Knowledge becomes a socially useful thing by innovation, i.e. its application in society and economy (Smahó 2008). The production and utilisation of knowledge is the basis of the development and renewal ability of settlements. A survey conducted in 2004 and 2005 analysed the knowledge-based renewal capacity of 251 Hungarian towns and cities on the basis of five groups of indicators: innovation, human resources, social activity, economic development level, and schooling and management. The settlements were categorised into 12 clusters, of which seven contains towns and cities with high renewal ability. Győr, together with Székesfehérvár and Kecskemét, is in the third cluster called ’strong economic centres with emerging innovation potential’. According to the findings of the research, the economic development level of these cities is high, their innovation parameters are adequate, but their human resources potential is limited (Csizmadia 2005; Rechnitzer–Csizmadia–Grosz 2004). Research and development, and innovation can be seen as the primary determinants of competitiveness. Both factors are extremely important in automotive industry, as this is a sector with a very strong competition. As regards the region of Western Transdanubia, the overwhelming majority of the research and development activity done by automotive industry companies is realised in Győr-Moson-Sopron county (Table 3). Of the seven automotive industry companies of the region that operated a research place in 2009, the headquarters of six are in this county. Also, 90% of the staff doing academic activity worked for a Győr-Moson-Sopron organisation in the respective year. Looking at the regional level we can say that more than half of the expenditure of academic activities was spent on automotive industry related purposes between 2005 and 2009. The total of the budget of the businesses in this sector on research and development investments was 19 billion HUF, three-quarters of which can be linked to companies located in GyőrMoson-Sopron county. Local Economic Development and the Automotive Industry in Győr 239 TABLE 3 R&D expenditures in automotive industry between 2005 and 2009, million HUF Specification R&D costs R&D investments R&D expenditure R&D in Western Transdanubia From which: automotive industry Within that: Győr-Moson-Sopron county Vas county Zala county Hungary (automotive industry) 31,064.7 16,997.9 3,542.3 1,968.3 34,607.0 18,966.2 12,872.0 4,125.9 – 52,229.9 1,673.6 294.7 – 8,476.4 14,545.6 4,420.6 – 60,706.2 Source: HCSO (2011, 47). The increase of productivity can be promoted by research and development, but also by innovation. Innovation activity is especially important in automotive industry, because this is a market where there is a definitely high demand for products featuring advanced technology. At regional level, the total expenditure of automotive industry companies related to innovation exceeded 96 billion HUF in 2008 (HCSO 2011). If we look at the innovation potential of Győr, we can see that in the physical plan of the city the dynamism visible in the economy – growing output and productivity, high level investments – are not harmonised by the innovation performance of the region. As regards the city’s research and development and base and its role in the Hungarian higher education, Győr lags behind and can only be taken as a second rank innovation centre, although the actors and institutions that have innovation potential are present in the city (Physical Plan of the City of Győr 2005). We do believe that such institutions are the already mentioned INNONET, TECHNONET Automotive Industry Technology Competence Centre, and also the PANAC, the Széchenyi István University, the university’s Regional University Knowledge Centre of Automotive Industry and Research Centre of Automotive Industry, Electronics and Logistics Cooperations. The decision on the foundation of the Pannon Automotive Cluster (Pannon Autóipari Klaszter, PANAC) was established in December 2000. The concentration of automotive industry in Northern Transdanubia offers an excellent opportunity for the clustering of automotive industry. Active participants in the creation of the cluster were, among others, the Western Transdanubian Regional Development Council and the automotive industry businesses of the area, such as Suzuki, Audi, Opel or Rába, but Széchenyi István University also joined as a founding member. By 2008, the number of organisations joining the cluster reached 95. The primary objective of this cluster, similarly to the other clusters, is the preparation of the members, their enabling to become successfully operating suppliers. The cost efficiency of the suppliers is also an interest of the transnational companies of the region, because they can increase their cost advantages thereby. The biggest obstacle of the creation of the supplier network with the participation of Hungarian companies is that the majority of these businesses do not meet the require- 240 Mihály Lados – Katalin Kollár ments of the customers, so the primary suppliers of the transnational corporations are usually foreign businesses. The most important concrete objective of the cluster then is the promotion of the modernisation of the capacities, and the technical development of the Hungarian businesses, and also the improvement of the financial stability. Further goals include the support of the internationalisation of the activity of the members and the creation of the national automotive industry strategy. On the foundation of the cluster a survey was made that tried to explore in which areas companies expected assistance. The responses revealed that it is mostly the access to supports, preferential operational credits, partner search, and the access to information in which members require most help from the cluster. The major obstacle for the cluster in carrying out its activity is the lack of financial resources (Grosz 2005a). The most prominent representatives of research and development in both the region and Győr are higher education institutions. Győr accommodates the Apáczai Csere János Faculty of the West Hungarian University, the Theological College of Győr and the Széchenyi István University. In the three faculties of the latter university (Kautz Gyula Faculty of Economics, Faculty of Technical Sciences, and Deák Ferenc Faculty of State Sciences and Law) and its Music Institute approximately 12 thousand students learn in 43 BA, five-year and master’s courses and also in 13 higher level vocational trainings and 11 postgraduate specialist training courses. The main focus of technical training is on automotive industry, logistics and informatics. There is an opportunity for participating in PhD training in three doctoral schools of the institute, in the field of regional and economic sciences, technical sciences and law (SZE). At the Széchenyi István University, R&D activity is done in organised frameworks, with extended cooperations within the institute among the faculties, and also between the academic and the business sector, contributing thereby to the improvement of the competitiveness of the latter. Between 2004 and 2006 a number of regional university knowledge centres and cooperation centres were established in Hungary, with the aim of stimulating the connections among the economic organisations, higher education institutions and research institutes, on the one hand, and for the promotion of innovation and R & D, on the other hand (www.nkth.gov.hu). At Széchenyi István University too these institutions were founded, named Regional Knowledge Centre of Automotive Industry, and Cooperation Research Centre of Automotive Industry, Electronics and Logistics. The Regional University Knowledge Centre of Automotive Industry, created with the support of the Pázmány Péter Programme in 2005, deals with the research of up-todate materials and technologies related to automotive industry, and the Centre is also active in the featuring of new possibilities in mechanical constructions (JRET). The foundation of the Centre took place with the participation, in addition to the University, of Rába Futómű Kft., Borsodi Műhely Kft. and SAPU Bt. (now SMR Automotive Mirror Technology Hungary Bt.). The research activity is done in joint business and university research groups, alleviating thereby bilateral knowledge flow and researchers’ Local Economic Development and the Automotive Industry in Győr 241 mobility. The knowledge centre sees as its mission the promotion of the innovation and research and development activity of the economic organisations operating in Győr and its technology region (Szilasi 2007). The Cooperation Research Centre of Automotive Industry, Electronics and Logistics started its operation in 2008 with the support of a tender of the Economic Development Operational Programme. The businesses and departments participating in the project actively cooperate in the area of automotive industry, informatics, electronics and logistics in order to contribute by the high level implementation of joint R & D activity to the increased efficiency of companies (http://jelkkk.sze.hu). The most important partners of the Centre include Audi Hungária Motor Kft., GM Powertrain Magyarország Kft. and Magyar Suzuki Zrt. (Hungarian Suzuki Inc.), but of course there are many other first and second level automotive industry suppliers such as Nemak Győr Alumíniumöntöde Kft., for example (Szilasi 2007). The Audi Hungária Group of Automotive Engineering Departments operating at the university was established in early 2012 for the coordination and promotion of the joint research activity of Audi and the university. In the joint financing of the university, Audi Hungária Motor Kft. and the Municipality of Győr a modern combustion engine laboratory was created, and the Research Centre of Automotive Industry also started its operation in March 2011. On 1 January 2012 the Audi Hungária Group of Automotive Engineering Departments was founded, consisting of three departments. The objectives of the creation of the group included the further strengthening of the intensive presence of Audi in research activity, the further development of practice-oriented training of engineers, and the strengthening of the research and development potential related to automotive industry. The group of departments deals with the development of materials and technologies that are applied in the engines as well. Last but not least we have to mention the secondary level institutions that also participate in the process of knowledge transfer. There are 30 secondary schools in Győr for the time being, of which 23 are maintained by the municipal self-government. Audi has regular cooperations with e.g. the Lukács Sándor vocational school of Mechatronics and Mechanical Engineering. Strategic planning and local economic development strategy in Győr The dominant or perhaps the most important factor in the success of local economic development is the creation of the development strategy. Researches have pointed out that the objective of such strategies is usually the strengthening and enlargement of the local economy and capacities. Its point is in the harmonisation and reconciliation of the different aspects and goals of the local actors. In this process it is not the so-called allocative planning method that is applied; the ground is a kind of future vision. The 242 Mihály Lados – Katalin Kollár comparison of this vision with the reality, the present situation of the respective territorial unit confronts us with the special problems of the area. During the 1990s the municipal government of Győr has had a relatively moderate strategic planning activity. The preparation of the new physical plan of the city started at the time of the transition to the local governmental system. Part of the approximately four-year planning process was the definition of a development strategy, in which a special emphasis was on the support of developments promoting the development of the university. As regard the economy, the main goal was the assistance of the development of small and medium-sized enterprises, in which a key element was the development of the Győr International Industrial Park. No economic development concept or strategy as such was made in this period, with the exception of the tourism development strategy approved by the general assembly in 1996. The new decade, with the approach of the accession to the European Union and then the actual accession in 2004 reinforced the strategic planning activity of the city. This first plan was the creation or renewal physical plan in the first third of the decade. Of course it is an internal need to supervise the physical plans at certain intervals, but in this case there was an external determination as well. The process of the accession to the EU appreciated the role of planning at national, territorial (regional, county and micro-regional) and local level. A precondition for the acquisition of EU development resources is the presence of adequate plans. At local level this required fresh and valid physical plans for the development that required space. Accordingly, all municipalities were obliged to renew their physical plans until the end of 2002. This deadline was put one year later by the Parliament, on the initiative of a representative from Győr. The regulation of the content requirements of the regional development and physical plans (1998) ordered urban development concepts to be the first chapters in the physical plans of the settlements, so the preparation of this document was the first of the strategic plans in the first third of the decade. A characteristic feature of this strategy was the direct inclusion of the local society into the strategy making process, in the framework of “Future workshop” meetings organised in the 23 districts of Győr. Simultaneously the city also sensed that its development track should be planned together with its hinterland, the agglomeration of Győr. Thinking about the future in the local community was also promoted by the fact that it became known that a Hungarian city would be the European Capital of Culture (ECC) in 2010. This opportunity activated the majority of the big cities in Hungary. Győr also made its ECC concept, formulated during intensive professional consultations with the potential stakeholders. In this dialogue not only the cultural actors of the city (institutions and artists) were involved but also the representatives of the economy, the university and the civic sector. The concept was not concentrated on the possible cultural events of the year 2010 exclusively but on the linking of culture with the hundred year old industrial traditions and modernisation of the city. In this a key role was played by innovation and knowledge represented by the automotive industry, as generator, sponsor and consumer of culture. Local Economic Development and the Automotive Industry in Győr 243 The national planning process founding the 2007–2013 Union programming period started in 2004–2005. The New Hungary Development Plan had a strong focus on the growth pole theory of regional economics and its French practice. The government defined the circle of those cities that, as selected development poles of the programme, would pull their regions with themselves as a result of the innovation and economic development implemented in them. Győr was in this circle too, so the city had to work out its own pole strategy. Each city had to concentrate on their own defined pull sectors, which in Győr was evidently automotive industry, so the pole of Győr was named “Autopolis”. This concept is of special importance because its final version is a definite local development strategy. The city was given government subsidy for the planning process that was done in a cooperation of the city, the university and the major actors of the local economy (chamber, Győr International Industrial Park, Innonet, PANAC). The strategy was focused on the development of economic infrastructure, with a special emphasis on automotive industry. From the resources provided by the government not only a general strategy was made; in the framework of the strategy the respective actors defined their key projects and prepared the necessary planning documentation for them (Table 4). TABLE 4 Planned resource and cost structure of the projects of the Pole Programme between 2007 and 2013 (indicative list) Name of key project Resources total (in million HUF) Planned date of implementation Actual date of implementation Széchenyi István University: “New Knowledge-Space” Building 3000 2007–2009 2011 Széchenyi István University: “INNOSHARE Regional Information Transfer Centre” 2500 2007–2009 2011 TECHNONET Automotive Industry Technology Competence Centre I. 1000 2007–2009 2011 TECHNONET Automotive Industry Technology Competence Centre II. 300 2009–2011 2011 Source: by the authors on the basis of the Economic Programme of the City of Győr 2006–2010 (2006). For the coordination of implementation, a pole management organisation had to be set up, which was founded as a 100% municipality-owned company. The managing body of the programme is the Győr Development Policy Coordination Task Force that looks at the future vision of the city and the development ideas of the Széchenyi István University, and defines those factors on which the future of the pole can be built. These are as follows: 244 Mihály Lados – Katalin Kollár − vehicle manufacturing; − enlargement of the suppliers and logistics capacities; − increased use of renewable energies. The objective then is the increase of international competitiveness by the development of vehicle manufacturing, the development of the suppliers and logistics capacities and the utilisation of renewable energies. The future vision of Győr is to become the regional centre of innovation, on the basis of knowledge and technical inovations as a development pole of Western Transdanubia. The strategy stated that the long-term development of the city is jeopardised by the inadequate quality of human resources, and quantitative problems can also be seen in some segments. As regards higher education, a definite effort has to be made for the support of the launch and development of trainings that promote the dynamic operation of the economy. Those research institutes and laboratories must be established and supported that promote economic growth. After these innovation-oriented developments, Győr may become the city with the strongest economy in the region and may also be suitable for joining researches and developments of European significance. The industrial and service activities having higher added value induce the appearance of spillover effects in other settlements of the region as well. The development of vocational training – by which we mean both secondary school and university and adult education – is indispensable for Győr to satisfy the needs of the economy and for modern industries to settle down in the city. Also, closer ties should be built with the businesses and the organisations dominant on the labour market (Győr Megyei Jogú Város Fejlesztési… 2006). The pole programme as a selected governmental economic development programme of the New Hungary Development Plan “faded away” after the inner reshuffling of the government. However, the plans have not been made in vain. By now, all projects specified in the Autopolis strategy have been implemented by the support of the Economic Development Operational Programme and the Western Transdanubian Operational Programme (see Table 4). This process was assisted by the fact that the region of Western Transdanubia, as the only region, linked the planning of the regional operational programme for the 2007– 2013 period with a regional plan package made on partnership basis. In the framework of this the comprehensive development programme of the region was made not only for the planning period but also long term development concepts (until 2020) for the region and the constituent three counties and the cities of the region were made, together with a middle-term programme for the Structural Funds period. In the economic chapters of these documents one finds the development ideas specified in the Autopolis strategy. After the launch of the programming period, big cities were obliged to make integrated urban development strategies (IUDS) for the implementation of projects renewing the (inner) cities with the support of the regional operational programme. The government provided the cities with single planning methodology and a list of the necessary content for the making of the IUDS. The planning of the IUDS in Győr took Local Economic Development and the Automotive Industry in Győr 245 place with the cooperation of professional groups, and the plans that had been made for the city in the previous years were also taken into consideration. The making of the most recent initiative called Local Agenda 21 of Győr was also connected to the implementation of an urban project. The respective document redefined the development of the city alongside the principles of sustainable development. In the framework of this, as the first step, professional groups by sectoral breakdown looked at in the autumn of 2010 all comprehensive and sectoral concepts and programmes that had been made in Győr in the previous ten years. The screening of these approximately fifty documents in a single methodology – also taking sustainability requirements into consideration – was the foundation of a community based urban strategy that would have served as a guideline for the 2014–2020 programming period or the development of the city and the local economy. Unfortunately the planning process stopped after the approval of the recommendations made on the basis of the assessment of the plans by the general assembly in December 2010. Győr was one of the “smart cities” assessed by the staff of the West Hungarian Research Institute of the Centre for Regional Studies, Hungarian Academy of Sciences in 2011. Smart of liveable cities are settlements able to use available technological possibilities in an innovative way, contributing thereby to the creation of a more liveable urban environment. During the survey, the performance of nine Hungarian cities – Debrecen, Győr, Kőszeg, Miskolc, Pécs, Szeged, Székesfehérvár, Tatabánya and Veszprém – was analysed, by seven dimensions, sub-systems. Győr had an outstanding performance in the business and communication subsystem (Figure 2). Figure 2 Performance of Győr compared to the best practice Source: Horváthné Barsi–Lados (2011, 9). Within the subsystem ‘business life’ those indices and indicators were analysed that determine the business environment of a city; these relate to the quantity of businesses, 246 Mihály Lados – Katalin Kollár their innovation capacity and their performance shown in the application of information and communication technologies. In the subsystem ‘communication’ the presence or lack of information and communication technology and its quality is looked at. On the whole we can say that Győr had a very good performance in all subsystems, although it only ranked fifth as regards the indices measuring innovation performance. The research findings revealed that Győr has excellent economic and business environment and circumstances but its innovation performance is weaker, it lags behind the other cities in R & D capacity. Nevertheless the economic competitiveness and the industrial potential of Győr make it the second big city of Hungary, after the capital city (Horváthné Barsi–Lados 2011). The strategic objectives defined by the strategic programme of the city, the middleterm integrated urban development strategy and the Local Agenda 21 programme, by which the future of Győr must be secured, are as follows: Győr should − allow inhabitants to have outstandingly high conditions of living; − continuously renew its economy in order to increase its competitiveness; − enhance its role in the region. The respective development directions are the following: − − − − Priority 1: human resources development; Priority 2: working and developing economy; Priority 3: development of urban services; Priority 4: protection of the environment. On the basis of the strategic plan of the city, the ultimate goal is to make Győr – winner in 2010 of the title Hungarian City of Culture, the Most Sporting City, Senior Friendly Municipality, in 2011 the title Bicycle Friendly City – a modern city with modern economy, the centre of the region (Győr Megyei Jogú Város Stratégiai... 2003, HHP Contact Tanácsadó KFt. – Győri Építész Műhely et al. 2008). This is also expressed by the following slogan: Health, culture, innovation! The future is being built in Győr! Summary Győr – as a result of the development path the city has trailed in the two decades following the systemic change – is one of the strongest economic poles in Hungary now. The dominant factor in this economic development is automotive industry. Among the automotive industry centres of Hungary, Győr – the second big city in Hungary after Budapest in economic competitiveness and industrial potential – has number one position. Its geographical location and transportation endowments are excellent, infrastructure is adequately built out, the city is open to receive investors and promote their settling down; it continuously develops and influences those location factors that may play a significant role in the locations decisions of the businesses. Local Economic Development and the Automotive Industry in Győr 247 Győr, in our opinion, has implemented in the last decade an extremely intensive and conscious urban development in which automotive industry was taken as the flagship industry of the development of the city. In the framework of this activity, an economic development strategy was made as well. It is an example to be followed that during the respective planning works the municipality tried to address the communities and the dominant stakeholders. It is good that there are overlaps of the actors in several planning works, as this way there were no repeated breaks in the major development directions of the various documents. In these documents, the development of the local economy was always a priority, as this is the sector that is capable of producing the incomes that the city can spend on welfare measures and the improvement of the quality of life. References Angyal Á. (2003) A hálózatok, mint többközpontú szervezetek. Vezetéstudomány. 3–4. pp. 76– 87. Bajmócy Z. (2011) Bevezetés a helyi gazdaságfejlesztésbe. Jate Press, Szeged. Business Assistance Alapítvány bemutatkozás. http://www.kva.hu/index.php?tid=277703132180 6266&qs_tr=f104&menuitem=0 [20 November 2011]. Cégvezetés: http://cegvezetes.hu/1998/04/penzhez-lehet-jutni/ [20 November 2011]. Czene Zs. – Ritz J. (2010) Helyi gazdaságfejlesztés. Ötletadó megoldások, jó gyakorlatok. NFM, NGM, VÁTI Nonprofit Kft., Budapest. Csizmadia Z. (2005) A magyar városhálózat innovációs potenciálja. In: Grosz A. – Rechnitzer J. (szerk.) Régiók és nagyvárosok innovációs potenciálja Magyarországon. MTA Regionális Kutatások Központja, Pécs-Győr. Deák Sz. (2002) A hazai ipari parkok és a betelepült vállalatok jellemzői. – Buzás N. – Lengyel I. (szerk.) Ipari parkok fejlődési lehetőségei: regionális gazdaságfejlesztés, innovációs folyamatok és klaszterek. SZTE GTK, JATEPress, Szeged. 175–200. o. Dőry T. – Mészáros R. – Rechnitzer J. (1998) Tudomány és regionalitás Magyarországon a 90-es években. Tér és Társadalom. 3. pp. 105–127. Dőry T. (2005) Regionális innováció-politika. Kihívások az Európai Unióban és Magyarorszá– gon. Dialóg Campus Kiadó, Budapest–Pécs. Dusza A. (2003) A birodalom végnapjai. X. Meditor Kft., Győr. Faragó L. (2001) SWOT-elemzés a területi stratégiák kialakításának folyamatában. Falu-VárosRégió. 6. pp. 3–5. Farkas P. (2005) Egymásba kapaszkodva: település- és közösségfejlesztés a globalizáció korában. ĽHarmattan Kiadó, Budapest. G. Fekete É. (2005) Vidékpolitika. Miskolci Egyetem Világ- és Regionális Gazdaságtan Intézet, Miskolc. Grosz A. (2005a) Klaszteresedési folyamatok Magyarországon – különös tekintettel az autóiparra. Pécsi Tudományegyetem Közgazdaságtudományi Kara, Regionális Politika és Gazdaságtan Doktori Iskola. Évkönyv 2004–2005. Grosz A. (2005b) A közép-európai térség autóipari beruházásainak telephely választási motivációi és piaci kapcsolatai. Kézirat, Győr. Győr Ipari Park: http://www.ipgyor.hu/# [22 November 2011]. Győr Megyei Jogú Város Fejlesztési Pólus Stratégiája. Győr Megyei Jogú Város Polgármesteri Hivatal Városépítési Iroda Stratégiai Tervezési Csoport (2006. január 31.) Győr. Győr Megyei Jogú Város Gazdasági Programja 2006–2010. (2006) Győr. 248 Mihály Lados – Katalin Kollár Győr Megyei Jogú Város Gazdasági Programja 2011–2014. (2011) Győr. Győr Megyei Jogú Város Középtávú Integrált Városfejlesztési Stratégiája. (2008) HHP Contact Tanácsadó KFt. – Győri Építész Műhely – Győri Mérnök Műhely – MTA RKK Nyugatmagyarországi Tudományos Intézete, Győr. Győr Megyei Jogú Város Stratégiai Programja. (2003) Győr. Győr Város Rendezési Terve. (2005) Győr. Győr-Pér Airport: http://www.gyor-perairport.hu/passenger/ [20 November 2011]. Horváth Gy. (1998) Európai regionális politika. Dialóg Campus, Budapest-Pécs. Horváthné Barsi B. – Lados M. (2011) „Smart Cities” tanulmány. MTA RKK NYUTI, Győr. Ingatlan.net: http://ingatlan.net/magazin/2011/09/atadtak-a-technonet-kozpontjat-a-gyori-ipariparkban/ [22 November 2011]. A járműipar helyzete és szerepe a Nyugat-Dunántúlon. (2011) Központi Statisztikai Hivatal, Budapest. Járműipari Regionális Egyetemi Tudásközpont (JRET): http://jret.sze.hu/index.php?option=com_ content&task=view&id=35&Itemid=67 [25 November 2011]. JEL-KKK 2008–2011: http://jelkkk.sze.hu/ [25 November 2011]. 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(2004) A magyar városhálózat tudás alapú megújító képessége az ezredfordulón. – Tér és Társadalom. 2. pp.117–156. Reisinger A. (2010) Társadalmi részvétel a helyi fejlesztéspolitikában – különös tekintettel a civil/nonprofit szervezetek szerepére. Doktori értekezés. Győr. Smahó M. (2008) A tudás és a regionális fejlődés összefüggései. Doktori értekezés. Győr. Széchenyi István Egyetem (SZE): http://felveteli.sze.hu/catview/index/id/3230/m/636 [2012. január 10.]. Szilasi T. (2007) Széchenyi István Egyetem és a vállalati szféra kapcsolata. In: Lados M. – Rechnitzer J. (szerk.) Egyetem a régióért. MTA Regyionális Kutatások Központja, Pécs– Győr. PART III. CHARACTERISTICS OF THE SUPPLIER NETWORK FEATURES AND SPATIAL DIFFERENTIATION OF SUPPLIER NETWORKS IN AUTOMOTIVE INDUSTRY ZOLTÁN CSIZMADIA Keywords: supply chain supplier networks intercompany co-operations The objective of this study is to examine the fundamental features and spatial differentiation of automotive industrial supplier networks. Relying on former researches conducted in Hungary, the goal is to give an overall presentation of the fundamental peculiarity which suggests that the supplier networks are not deep, not complex, the forms of cooperation beyond the supply and ordering relations are missing, the chance to achieve the direct Tier 1 supplier position is not much and all in all a still limited functionality characterises these inter-organisational cooperation channels in Hungary. Our findings confirm the former experiences, however, at certain points some changes took place. The characteristics of cooperation are summarised along three issues: 1) fundamental features of supplier and customer relations (the profile of the system of relationships), 2) special differentiation potentials, 3) and the effects of economic-organisational facilities shaping the relationships in the network. Introduction The comprehensive objective of this research is to map the embedding of undertakings – that are situated in the two examined regions, and that are predominantly related to automobile manufacturing – into the economic field of the area concerned and into the broadly defined region; their cooperation with the available economic capacities; the networking processes that have taken place hitherto and the potentials through the empiric analysis thereof based on the national survey of intercompany supplier and customer relations. The sub-analysis presented here primarily aims to give the possibly most complex description of the cooperation between suppliers and customers (another study deals with the external relations of other direction), the identification of the influencing factors and collect the peculiarities of spatial, temporal, and content/functional characteristics. Considering the fact that the sample composed of 118 elements includes companies 94.5% of which take the positions of both the supplier and customer, this survey provides appropriate grounds for the descriptive analysis of the properties characterising both relationship types. According to our research methodological model, an undertaking may have relations oriented to at least three directions in organisational space: to the potential suppliers and customers, to the players of development, support, and innovation institutional system in the form of other external relations (Figure 1). The analysis of the relation- 252 Zoltán Csizmadia ships extends, in addition to occurrence and quantitative parameters, to essential properties, such as the factors influencing the establishment of the relationship, the territorial location of partners, the period of time, the firmness of the relationship, the exclusiveness of relationship, the occurrence of assisting/supporting and the research/ development aspects. Besides the mapping of network parameters, as a second very important target, we also pay attention to examining along what peculiarities do supplier-networks show any special regional differentiation, i.e. in what sense are supplier and customer networks of undertakings – performing business activities in the Northern Transdanubian region – different and in what respect do the networks show individual features. Finally, at the level of correlations, the roles of other, non-territorial based (economic-organisational) factors influencing the networks are reviewed. FIGURE 1 Directions of the analysis – network types and potential influencing factors Relationship with the suppliers − Does it have suppliers? − Number of suppliers − Reasons − Volume of purchases − Spatial location − Term − Type of relationship − Assistance − R&D cooperation − Other types of cooperation Suppliers Other external relationships − Importance of horizontal relationships − Direction of relationships − Types − Intensity − Purpose of relationships − Cluster membership Company Relationship with the customers − Who they supply to? − Complexity of the sphere of customers − Spatial location − Reasons − Exclusiveness − Term − Type of relationship − Forms of cooperation − Assistance Customers Factors influencing relationships Year of incorporation – Plants – Ownership structure – Number of employees – Sales revenues – Since when it is a supplier? – Main product supplied – Proportion of supply activities in sales revenues – Number of product lines – Proportion of sales revenues deriving from the largest customers – Exclusiveness – R&D – Knowledge flow motivation – Future prospects – Strategy – Export – Market position Source: Own draft. Features and Spatial Differentiation of Supplier Networks in Automotive Industry 253 Some fundamental concepts Positioning of automotive industrial companies often takes place presuming a complex relationship network, sometimes even seeming confusingly complicated. Dual situation is presumed, that is, the companies may concurrently take supplier and customer positions, integrating at different levels into the comprehensive structure of supplier systems/pyramids/networks. It is worth clarifying briefly the major points in the theoretical/ conceptual issues of supplier networks, before kicking out to present what was measured and how in the empiric part of the sub-research. The comprehensive study prepared by Andrea Gelei can be a good starting point to this task, which provides a detailed overview of the key concepts basing upon the international literature (Gelei 2008). In the majority of cases suppliers are members of complex business networks. Business network is a structure, in which a number of nodes (these are the individual business units, e.g. manufacturing companies, customers, logistical or financial service providers, research centres, etc.) are interlinked through several connecting ties having special contents (these are the actual inter-organisational relations). Thus the networks are not merely conceptual units, but also the organised patterns actually observable in the interactions between the cooperating partners (Gelei 2008, 4). Due to their complexity business networks can be disintegrated into certain components. The most commonly spread distinguishing of the components is internal and external business network. Internal business network comprises on the one hand the internal structural units that are predominant, play central roles, and typically owned by the parent company in a multinational corporation, on the other hand the system of relationships existing among such units. External business network is the conglomeration of suppliers, salespersons, and other independent organisations as well as their relations forming around a company or corporate group. In this sense, in the framework of this research we attempt to reveal, classify and compare the links or bonds constituting the structures of external business network. In another approach, the specific patterns of any such economic interactions may be considered as supply chains, supply networks, which are deemed as a sequence of value creating processes required for the creation of a product or service package and connecting several cooperating organisations that eventually produce a product or service suitable for satisfying the customer’s needs and requirements. In this case a function and process oriented approach is discussed, and the focus is on the operating and direct functions of the network instead of the organisation thereof. The business, supply networks defined above may also be considered as peculiar organisational model. According to Gelei, the vertically integrated company operation model and network operation model can be distinguished (Gelei 2008, 10). The essence of the vertically integrated model is that organisations endeavour to keep the activities fundamentally defining competitiveness in-house, the importance of partnership relations is minor, dependence on cooperating partners is low, cooperation based relations are for a short term only and partners can be relatively easily replaced. On the 254 Zoltán Csizmadia contrary, in the network operation model the emphasis is placed on the fact that the entire supply chain, also the activities being dominant in terms of the central company’s competitiveness are carried out outside the boundaries of the company, thus partnership relations become critical factors influencing success, those involved in such cooperations highly depend on one another, and typically powerful, stable and long term relationships are formed. Major results of former Hungarian research In the recent years the researches on supplier relationships and complex supplier networks have been more and more upgraded, and the issues regarding these often come up also in economy development and innovation policy related discourses and documents. On the basis of some lately published research and development support materials a relatively comprehensive picture may be drawn about the current status of domestic supplier networks and their development trends. It is by and large commonly agreed in the Hungarian literature that the construction, operating and extension of the supplier networks are essential issues regarding the modernisation and long term development of economy (Gém–Mikesy–Szabó 2011). In the past two decades Central and Eastern European region has become the “foreign multinational machine and automobile manufacturers’ systematic target area in terms of relocation and it has built in the supplier pyramid. The competitive advantage of this region primarily derives from its cheap, flexibly employable, motivated labour force and fast access to the major markets” (A magyar kis és középvállalatok supplieri szerepének...2011, 4). The study emphasises that the development of the supplier network in Hungary is in excess of the regional average, but compared to West-European standard it is lagging, the multinational companies that settled down in the country, as well as the Tier 1 suppliers serving them have formed a supplier pyramid composed of at least three levels. The main problem is that the majority of primary suppliers are affiliated firms of foreign companies, thus for domestic undertakings realistically only the secondary or even lower level supplier statuses are available. The characteristics of supplier networks cannot be comprehended without knowing the motivational background. What advantages may derive from supplier activities, or from the integration into the supplier networks? The most important advantages are the following: − direct impact on financial results, − customers placing orders for high volumes, paying correctly, being ready to provide also technical assistance, − better performance on the market, − improvement of effectiveness, − conquering new markets, − launching or extending international activities, Features and Spatial Differentiation of Supplier Networks in Automotive Industry 255 − making the business activities more predictable, − access to new knowledge, competence, relationships, − flow of manufacturing cultures and network effects in local economy. Gelei and Nagy (2004), relying on the international specialised literature (Walter et al 2001) seized the issue of motivation along the direct and indirect value dimensions of supplier networks. Direct value dimensions include profit (direct profitability attributable to a particular consumer), the quantitative (scale of volume generated by a particular consumer) and the security (orders guaranteed for considerably long term) dimensions. Parallel with these, four types of indirect value dimensions can also be distinguished: innovational (innovation is resulted from the cooperation with the customer), market (cooperation and references may bring forth new market opportunities, new orders), exploratory (informational proceeds of cooperation) and access (access to other important role players owing to the cooperation). All these suggest that supplier networks may represent significant values and potentials for each company, although the probability of the development of any such relationships depends on the interplay of many a factor. According to the latest research results first a summary is given on what we know about domestic industrial supplier networks (Gém–Mikesy–Szabó 2011), then it is examined what peculiarities such co-operation have in relation to automotive industry (A magyar kis- és középvállaltok supplieri szerepének... 2011). The “profoundness” (complexity) of domestic industrial supplier networks is low, and those involved focus fundamentally on the supply of only one or only few products. A further problem is that the rate of occurrence of cooperation forms beyond supply is very low: only 11 per cent of domestic industrial companies provide, or contract for additional services, and only in the case of 7% can other common activities also be observed beyond the supplies (e.g. research-development, collective tenders, etc.), and only in the case of 3% cross supplier networks even the state borders. In conventional, vertically integrated supplier networks relationships are much more tied, and are restricted in general on the supply of a sole product. SMEs having horizontal sectoral relationships perform more complex supplier activities with higher chances. The customer large companies endeavour to establish close relationships with their suppliers working in the same sector, however, their relationship is restricted only to product supply, while with their SME partners working in different sectors the create strategic relationships. Supporting the suppliers is not even, but quite a commonly accepted practice (only 24% of the industrial customers did not provided any support for their suppliers), and the larger a company was the more chance it had that the company granted support to the suppliers. The three most common supplier support type is quality assurance, logistics and technological support. Foreign large corporations use more “sophisticated” means of supporting which have long term influence on the relationships (advising on financial support, management and organisation). Among the factors influencing the forming of supplier networks, according to the surveys, the first three places were taken by personal acquaintance, former business relations and references, as well as recommendations by business partners. Supplier 256 Zoltán Csizmadia networks are extending constantly (78% of the companies in the industrial sector plan future extensions) with different interests in the background. The suppliers target the reinforcement of their market positions and the acquisition of new markets, while the customers wish to use the extending company relationships to achieve cost reduction primarily. The most essential inhibiting factor impeding the extension of supplier networks is the low capability to conform to quality requirements, and it is also a problem that there are only few Hungarian suppliers providing product related services. The suppliers declared the too low prices and rigidness of the existing supplier networks as the most serious problems that they face. The latest survey carried out among companies also highlights that the companies share the opinion, that “market incentives (such as tax allowances) and not regulatory means (e.g. the specification of supplier quotas) shall be applied to promote deepening and establishment of company relations” (Gém–Mikesy–Szabó 2011, 19). As regards the Western Transdanubian region there is another essential finding of the survey. In accordance with the assessment of market achievements and macro– economic processes, the schemes for investments and the investment of resources, as well as the supplier’s proportional share the performance of Hungarian SMEs engaged in supply activities was classified by cluster analysis. Four groups were set up: passive winners (14.7%), the successful ambitious (28.7%), zealous strugglers (33.3%), the hopeless (23.3%). In the first two groups comprising the most competitive companies the firms engaged in machine engineering (46%), the middle sized enterprises and the “West-Hungarian companies being able to exploit any external economic boom or upturn due to their favourable geographical situation” (32%) are all over-represented. Furthermore, among the successful suppliers the cross-sectoral, more profound, and more complex supplier networks, more significant assistance provided by the customer, less impeding or inhibiting factors are more typical, and merely the strengthening of industrial sectoral clusters can further enforce the supplier networks (Gém–Mikesy– Szabó 2011, 61–62). The survey referred to above (A magyar kis- és középvállalatok supplieri szerepé– nek... 2011) and addressing the strategy based development of machine and automotive industrial sectors, at several points refines and tinges the overall view depicted in the foregoing. Estimated according to the West-European standard the automobile industrial supplier network in this region may be considered to be lagging, moreover some 90% of the products manufactured by automotive industrial suppliers – according to estimations made in this industrial sector – goes to export. Low is the number and proportion of supplier companies and in the views of those excluded the suppliers compose a “closed elite club”. It is only in extraordinary cases, that at present, a company manages to become Tier 1 automotive industrial supplier, moreover, Hungarian companies are rare among them, and in the near future, Hungarian companies can not achieve integrator positions either. They have the potential only to get Tier 2 or lower supplier positions. Those highly liquid middle sized enterprises having free capacities have the best chances, which have already proven “their profess–sionnal and organisational merits Features and Spatial Differentiation of Supplier Networks in Automotive Industry 257 and values” and their scope of activities also conforms to actual customer demands (A magyar kis- és középvállalatok supplieri szerepének... 2011, 8–14). By today, a “vertical supplier network comprising at least three hierarchically const– ructed levels have developed in machine and automotive industry”, in which the second level (Tier 2) suppliers mean the “load bearing backbone” of the whole supplier pyramid. Long term partnerships here depend primarily on the supplier’s technological and R&D capabilities, the personnel conditions, and the distance from the customer. Keeping pace with the ever changing and increasingly higher requirements of the customers is a key factor in sustaining the supplier networks. The following list represents with appropriate accuracy the group of factors that may have influence efficient supplying: − − − − − − − − − − − − − − ability to manufacture technically more complex products, adaptation of the customer’s production documents, production related development, improve the effectiveness of production technology, product development upon the customer’s request, mutual product design, management of the supply chain, ability to sell the engineering knowledge, the development results, intellectual work, strategy construction, improvement strategy, qualified staff, team of engineers, the standard of management, technical and economic management communication, data provision, language command, accessibility, trust and social capital of the firm membership in professional associations, networks and clusters, geographical or at least temporal closeness, favourable transport infrastructure. In relation to the problems in co-operation between the supplier systems the study underlines two main possible reasons. For domestic companies the most serious obstacle in achieving the supplier position is the difficulty to fulfil the quantities expected by the customers and to create the capacities necessary for this, as well as to satisfy the constant development demands. The authors of the study made an obvious recommendation to resolve the foregoing problems, namely that the actors of the split supplier market should cooperate more, or through mergers or acquisition they should establish larger companies. The cluster should be the special form of the co-operation built upon this loose collaboration (A magyar kis- és középvállalatok supplieri szerepének... 2011, 25). The above mentioned very critical assessing analyses also cast light on several problems and breakthrough points, and specified the reference system of our own assessment, in which the results revealed in the special pattern of supplier companies focused on the research sector become comparable and may be interpreted in a broader circle. 258 Zoltán Csizmadia Fundamental nature of supplier and customer networks The majority of the undertakings involved in the survey (94%) take both supplier and customer positions in certain supply chains and networks. Consequently the fundamental nature of their supplier and customer relations is practical to be discusses next to one another but still distinguished. In the following two summarising tables (Table 1 and Table 2) essentially the major features of inter-organisational relations with such functions are included and the substantial descriptive networking parameters adhering to the supplier and customer positions are set in focus. In the first step, the profile of the two relationship types is depicted on the basis of some distribution figures. The majority, 94%, of the supplier companies, that we could contact, are also present in the network as customers. This means basically different network strategic position and function for them. The rate of suppliers supplying the car factories directly (Tier 1 suppliers) is surprisingly high (56%), and also the proportion of those supplying to tier 1 suppliers (tier 2 suppliers) is also high (68%). The majority of companies involved in the survey are really ‘close to the fire’, and take prominently important positions in the deep structure of the supply chains due to the shortness of the distance from the manufacturing company in the network. For the majority of suppliers the automotive industrial supply activities is the most important channel of economic transactions (with a sales revenue ration of 75%), and a remarkable proportion of their sales (on the average 50%) derives from the business deals with a sole (their largest) customer, which suggests significant dependence on the network and system of relations (Table 1). Supplier networks are not territorially, or spatially concentrated, and the proportion of EU and domestic customers is also remarkable. By and large one-third of them have only domestic relations and the other one-third has only international relations. One-third of them are in supplier positions exclusively. It is impossible to attribute any typical feature to contracts behind supplier networks on the basis of their term, but it is obvious that, in general, the co-operation contracts are concluded for a term at least or even exceeding three years. We may not speak about a complex motivation and success factor system. According to the majority of the companies behind the orders good quality (80%), reasonable price levels (74%) and the suppliers’ capabilities and capacities (60%) are guaranteed. Entrance to the network, remaining and movements in it depend basically and primarily on these three factors. The majority of companies consider the supplier networks established with their customers as a relationship with long term prospects built upon framework orders, which is reinforced by the peculiarities of the formerly experienced concentration of financial resources assigned to the channels of interaction (proportion within the sales revenues, weight in sales), and the features of the consequential and potential dependence and interdependence. At the majority of companies supporting activities are also associated with the formal, relatively long term, often exclusive or prominent supplier positions. Customers/Clients are, in general, the most willing to provide Features and Spatial Differentiation of Supplier Networks in Automotive Industry 259 assistance in the field of quality assurance and technical support. On the average a typical supplier may count on any support or assistance provided by the customer in two fields. According to expectations, the frequency of activities going beyond the supplier relations is low in the networks (although it is higher than shown by national surveys performed earlier). Merely 36% of the undertakings mentioned any co-operation with the customers also in other fields. With the highest probability co-operative research and development (20%), or collective purchasing (13%) occurs. TABLE 1 Characteristics of supplier networks Characteristics N % 62 53 Supplies EU companies Supplies domestic companies Supplies only domestic companies Supplies only EU companies 82 76 35 41 70 65 30 35 Supplies automobile factories directly Supplies Tier 1 suppliers Supplies Tier 2 suppliers Supplies only one tier Surely exclusive supplier Surely not exclusive supplier 65 79 46 61 39 46 56 68 40 53 34 40 Typical term of supply contracts with customers – longer than 3 years One year Less than 1 year Assessment of the relationship – long term, perspective relationship built upon framework contracts Relationship built upon strategic alliances 39 27 23 35 25 21 61 53 34 29 Support to suppliers – received assistance from the customer, yes Quality assistance related support Technical assistance On the average how many types of assistance could it expect from the customers? (Max 6) 83 52 52 71 44 44 Cooperation with the customer – yes Collective research-development Collective purchasing 43 24 15 36 20 13 Reason for the order – good quality Favourable price level Supply capacity, capability 94 87 70 80 74 59 Proportion of automotive industrial supplier activities in sales revenues is over 75% Average proportion of the largest customer’s share in the total sales Source: Questionnaire survey 2011. N=118. 48 2 260 Zoltán Csizmadia TABLE 2 Characteristics of customer relationships Characteristics N % It has suppliers – customer and supplier positions Typical number of suppliers – between 11–50 Over 100 111 45 26 94 41 24 Average proportion of purchases from suppliers in sales revenues,% Varies between 34–66% Varies between max 33 or 67–100% 44 26/26 48 46 27/27 It has only domestic suppliers It has only foreign suppliers It has domestic and foreign suppliers too 30 26 55 27 23 50 Supplier selection – purchasing division Parent company 56 38 51 34 36 23/24 34 22/22/22 61 55 Typical term of purchasing contracts concluded with the suppliers– 1 year Less than 1 year, 1–2 years, over 3 years Assessment of the relationship – long term, perspective relationship built upon framework contracts Loose relationship, built upon orders 28 25 Support to suppliers – granted assistance to suppliers, yes Quality assistance related support Technical assistance On the average how many types of assistance was granted to suppliers? (Max 7) 68 47 44 61 43 40 Cooperation with the customer – yes Collective purchasing collective research-development collective training and coaching 36 19 13 12 33 17 12 11 Reason for the order – good quality Favourable price level Flexible supply capacity, capability 97 91 72 88 83 66 Suppliers’ individual R&D activities are deemed to be important – yes Collective R&D activities are performed with the suppliers – yes 14 21 13 19 2 Source: Questionnaire survey 2011. N=118. The majority of companies, as referred to above, are not only automotive industrial suppliers, but also customers at the same time. That is why it is possible to summarise the basic characteristics of customer relations as well, becoming familiar with the expectations towards the companies being on the supplier side of the system, so to say, from the customer’s point of view. With highest probability the scale of an average sphere of suppliers varies between 11 and 50 companies. One-fourth of the companies, however, have over 100 suppliers. Purchases from suppliers represent a very significant proportion of sales revenues (48% average proportions) at most of the companies, Features and Spatial Differentiation of Supplier Networks in Automotive Industry 261 moreover, at one-fourth of the companies this proportion even exceeds a rate of 67%, which shall be considered as a remarkable volume concentration. The spatial location of their suppliers shows a heterogeneous picture: at most of the companies the customer relations are built upon the miscellaneous sphere of international and domestic partners. Examining such automotive industrial economic transactions and relations from the customer’s side, the main factors of motivation, selection and success are also quality (88%), favourable price (83%) and willingness to flexible supplies (66%). Approaching the relationships from the customer’s side, the time interval or term becomes shorter, and there is no unequivocally preferred response category, although the occurrence of the one-year interval is higher than the average. All in all, there is no specified time interval or term in customer relations. As customers, the companies prefer the strategic alliances less, besides framework orders a more prominent role is attributed to loose relations (25%). As customers, 61% of the companies support their suppliers, primarily in the field of quality assurance and technology. As customers, one-third of the companies’ relations with suppliers extend to other levels as well. In principal, inter-organizational cooperation can be observed in the field of purchasing (17%), R&D (12%) and in minor rate in the field of training (11%). On the other hand, individual research-development does not seem to be an important criterion when suppliers are selected. Merely 13% of the companies appearing also as customers deem this an essential criterion, and only every fifth company carries out R&D activities collectively with its supplier. Spatial differences After summarising the fundamental basic features of the two network forms in this section the spatial differentiation of the significant elements are examined. The answer is sought for the question whether the supplier networks have certain special peculiarities in the Northern Transdanubian region (34 questionnaires, 28.8% of the samples). Altogether over 25 variables were used to describe the basic features of supplier and customer relations. In the two secondary spatial samples cross-table analysis was applied to examine the spatial differentiation of these relationship network parameters. In the case of seven sets of questions can significant differences be observed as regards the basic characteristics of the networks of automotive industrial supplier companies performing their business activities in the Northern Transdanubian region and in other parts of the country. Accordingly, two groups were compared, and the summary is given in the following table (Table 3) with the indication of significant deviations, demonstrating the special peculiarities of the companies belonging to the economic field of the northern part of Transdanubia. Surprisingly, there are no regional differences at all in terms of closeness to car factories and Tier 1 suppliers and within the proportion within the sales revenues deriving from supply shows such a concentration rate (that is a typical tendency), behind which no spatial differentiation can be observed. 262 Zoltán Csizmadia TABLE 3 Marks of the spatial differentiation, regional specific features Features of Supplier networks Special features of Northern Transdanubia Commencement of automobile industrial activities They have foreign customers Also before the 90’s, early entries, Companies from the years preceding 2000 are overrepresented higher probability, 79% Average term of supply contracts Longer than 3 years (55%) Strength of relationship with customers Strategic (38%) or framework type (53%) occur with higher probability Number of suppliers high (between 51–100: 29%, over 100:32%) Proportion of purchases from suppliers in sales revenues higher (at least a proportion of two-third in the case of 37% of them) Frequency of foreign suppliers higher (91%) Source: Questionnaire survey 2011. N=118. One of the most obvious difference appears in the fact that the automobile industrial activities of suppliers performing their activities in Northern Transdanubia has longer traditions, and their proportion is higher at companies, which are engaged in this sector for over 10 or 15 years. The other region specific element is the probability of occurrence of foreign suppliers and/or customers, which is 12–14 percentage point higher in Northern Transdanubia. As suppliers, the companies in the Northern Transdanubian region conclude their contracts for longer terms and the relationships established with the customers are closer, stronger and more profound (strategic and perspective framework agreements occur in higher proportion). On the other side of supplier networks or chains, as customers or clients the companies of the region also show some peculiarities. On the one hand the scale of the supplier set is bigger than in the case of other companies of the region; the undertakings in this region with 50 or even 100 supplier sets are over represented (their rate collectively is 60%, while in other regions only 32%). Relationship networks established with the suppliers show special differences also in the case of international interactions, or in the rate of sales revenues deriving from purchases from them. In the region the occurrence and higher numerical ratio of international suppliers is more typical, and purchases from them are more concentrated and the volume of sales revenues is more intensive. Economic-organisational parameters influencing the networking The correlations between the (pendant) network variables included in the researchmethodological model described at the beginning of this study, and the independent variables measuring the organisational background were tested through cross-table analyses. This procedure is suitable for the analysis of paired correlations, and it is expedient due to Features and Spatial Differentiation of Supplier Networks in Automotive Industry 263 the usage of low sample element number and only few elements of categorical variables. The mapping of paired correlations of nearly 20 different supplier and customer network indicators and 8 to 10 organisational-economic background parameters means by scale 200 cross tables. The results are summarised in Tables 4 and 5. Only significant relationships are discussed, the indices were arranged in accordance with the scale of the number of explanatory variables influencing certain aspects of the inter-company cooperation, while the internal ranking was set up in accordance with the value of the test statistics (Cramer’s V) measuring the correlation for the sake of the possibly fastest transparency and easiest orientation. Potential background factors influencing the relationships established with the customers (as suppliers) and suppliers (as customers) were separately analysed. Our objective was to identify the main determining factors and depict a certain big picture. At this point deeper and multi-variable correlations are not discussed. The most apparent phenomenon was the low number of variables influencing the relationships, at least in the sphere of independent variables applied by us. Basically in most of the cases only the staff number and the sales revenues being closely correlated may be considered as a considerable differentiating factor. In certain cases even the foreign ownership interest, the number of product lines manufactured, the proportion of blue collar workers, and the weight or concentration of the supply or purchasing within the sales revenues got roles. Other independent variables of our initial model were in nearly each case without any effect. The summarising tables include the directions of correlations, or data from which these may me read and defined, but some more important results were highlighted. All in all it may be stated that the fundamental peculiarities that we could become familiar with during former domestic researches return in the data of the latest empiric survey, thus we may not speak about any surprising, schematic or new tendencies. As suppliers (Table 4) primarily in the foreign (or in minor rate and following a reverse logic the domestic) customer frequency can remarkable differences be observed in accordance with the economic-organisational profile of the companies. The bigger the company, the higher the sales revenues, the proportion of supplies within the sales revenues, the number of product lines manufactured, and the proportion of blue collar workers or the foreign ownership interest, the more probable is the occurrence of foreign companies in the sphere of customers. Besides the occurrence of supplier networks the term or time interval thereof is also influenced by several factors. A positive relationship can be observed between the term of the contract (2 to 3 or even more years) and the site, the sales revenues, the foreign ownership interest and the weight of the supply within the sales revenues as well. Actually, in other cases only the size or scale of the company can be considered as determining factor, and the commonly known correlation is confirmed at us too, that direct automobile industrial suppliers, the strong supplier networks, the complex cooperation are more predominant at large suppliers. In addition to the mainly conventional relationships that may be considered linear (the more, the larger, the more complex, all the more...) other correlation pattern can be detected in only one case: in the case of assistance received as a supplier the middle sized companies are in more favourable situation. 264 Zoltán Csizmadia TABLE 4 Differentiation of relationships with customers Frequency of EU customer/client (sample average 70%) – Size of the undertaking; Cramer’s V: 0.525 large company (90%) – middle–sized undertaking (87%) – small–sized undertaking (46%) – Sales revenues; Cramer’s V: 0,482 – with the increase of sales revenues the probability grows – Proportion of automotive industrial supplies within sales revenues; Cramer’s V: 0.422 Over 75% (85%) – under 25% (37%) – Foreign undertaking; Cramer’s V: 0.327 higher probability – 100% foreign ownership (94%) – Number of product lines manufactured; Cramer’s V: 0.293; 2–5 types (54%) – 11–25 types (92%) – Proportion of blue collar workers; Cramer’s V: 0.242 Between 50 and 75% (78%) – over 75% (71%) – under 50% (33%) Frequency of domestic customer/client (sample average 65%) – Sales revenues Cramer’s; V: 0.451; with the increase in sales revenues its probability decreases – Size of the undertaking; Cramer’s V: 0.396 small–sized undertaking (84%) – middle–sized undertaking (61%) – large company (39%) – Proportion of automotive industrial supplies within sales revenues; Cramer’s V: 0.358 maximum 50% (87%) – 75% over (51%) – Foreign undertaking; Cramer’s V: 0.236; minor probability – 100% foreign ownership (47%) V. Term of Supplier contracts – Sales revenues; Cramer’s V: 0.345 With the growth of sales revenues (over 2 billion HUF) the probability of long term contracts also increases – Size of the undertaking; Cramer’s V: 0.309 Positive relationship – the larger a company is, the longer term the contracts are concluded for – Foreign undertaking; Cramer’s V: 0.316 Long term contracts occur with higher probability – 100% foreign ownership (64%) – Proportion of automotive industrial supplies within sales revenues; Cramer’s V: 0.249 the larger a company is, the larger the probability of occurrence in the case of long term contracts is Direct supplies to automobile factories (sample average 43%) – Sales revenues; Cramer’s V: 0.320; with the increase in sales revenues its probability grows – Size of the undertaking; Cramer’s V: 0.318 large company (58%) – middle–sized undertaking (54%) – small–sized undertaking (23%) – Proportion of automotive industrial supplies within sales revenues; Cramer’s V: 0.294 75% over (54%) – 25% under (23%) Strength of supplier relationship (perspective or alliance based) – Sales revenues; Cramer’s V: 0.306 Strategic alliances occur mainly over 2 billion HUF – Size of the undertaking; Cramer’s V: 0.237 With the growth of size the probability of close relationships also increases Assisting the supplier’s activities by the customer (sample average 70%) – Sales revenues; Cramer’s V: 0.325 Support or assistance granted to companies with low or high sales revenues is rare (60%), it is the most frequent between 0.5 and 10 billion HUF (87%) Features and Spatial Differentiation of Supplier Networks in Automotive Industry 265 – Size of the undertaking; Cramer’s V: 0.277 large company (83%) – middle–sized undertaking (77%) – small–sized undertaking (61%) Cooperation with the customer (sample average 35%) – Foreign undertaking; Cramer’s V: 0.316 Lower probability – 100% foreign ownership (18%) Source: Questionnaire survey 2011. N=118. TABLE 5 Differentiation of relationships with the suppliers Frequency of foreign suppliers (sample average 73%) – Sales revenues; Cramer’s V: 0.436 with the increase in sales revenues its probability grows – Proportion of automotive industrial supplies within sales revenues; Cramer’s V: 0.423 The higher this proportion is the more probable the frequency of foreign suppliers is: with a proportion over 75% (88%) – with a proportion under 25% (39%) – Size of the undertaking; Cramer’s V: 0.403 large company (93%) – middle–sized undertaking (79%) – small–sized undertaking (55%) – Foreign undertaking; Cramer’s V: 0.298 higher probability – 100% foreign ownership (91%), not foreign ownership (64%) Proportion of purchases from the suppliers within the sales revenues in 2010 – Sales revenues; Cramer’s V: 0.370 with the increase in sales revenues its probability grows – Size of the undertaking; Cramer’s V: 0.322 The larger the size the higher the proportion in sales revenues is 67–100% proportion: large company (44%) – middle–sized undertaking (34%) – small– sized undertaking (9%) – Foreign undertaking; Cramer’s V: 0.233 higher probability of concentration – 67–100% proportion in the case of companies with 100% foreign ownership (48%) Frequency of cooperation with the supplier (sample average 32%) – Sales revenues; Cramer’s V: 0.292 with the increase in sales revenues its probability grows – Proportion of automotive industrial supplies within sales revenues; Cramer’s V: 0.290 over 75% (43%) – under 25% (6%) – Size of the undertaking; Cramer’s V: 0.239 large company (47%) – middle–sized undertaking (37%) – small–sized undertaking (19%) Foreign undertaking; Cramer’s V: 0.232 higher probability – 100% foreign ownership (48%), not foreign ownership (25%) Number of suppliers – Sales revenues; Cramer’s V: 0.445 With the growth of sales revenues the number of suppliers also increases – Size of the undertaking; Cramer’s V: 0.396 Positive relationship: large company over 100 suppliers (55%) – majority of SMEs with 50 (52%), but mainly with de under 10 suppliers only Frequency of domestic supplier (sample average 75%) 266 Zoltán Csizmadia – Sales revenues; Cramer’s V: 0.364 with the increase in sales revenues its probability decreases – Foreign undertaking; Cramer’s V: 0.263 Lower probability – 100% foreign ownership (59%) Assistance, supporting of suppliers (sample average 61%) – Size of the undertaking; Cramer’s V: 0.319 large company (80%) – middle–sized undertaking (66%) – small–sized undertaking (42%) – Sales revenues; Cramer’s V: 0.335 with the increase in sales revenues its probability grows Source: Questionnaire survey 2011. N=118. When focusing on the customer roles of companies under review and the relationships established by them in these roles with other suppliers (Table 5), no significant new differentiating factors were revealed to step in from the research model either. In this case, also the frequency of foreign suppliers, the volume or concentration of purchases from foreign suppliers, and as a new element, the occurrence of co-operation can be considered to be the most differentiated. All in all the direction of the revealed relationships followed the same logic: besides the higher sales revenues, the number of staff, the foreign ownership interest, and in certain cases, the customer’s position, the concentration of supplier activities, its weight within the sales revenues also contribute to the more favourable tendency in the occurrence of international orders, cooperation with the suppliers, the scale of the supplier network (number of suppliers) and support granted to the suppliers. Conclusions Owing to the size of the corporate data base forming basis for this survey it is not suit– able for the usage of more sophisticated research models of explanatory character. Nevertheless, the screening of correlations, that seem to be reliable in statistical sense, from the loads of possibilities of relations provided a base for interpretation which we could securely build upon to state that the general features of supplier networks and the systems thereof that we could get familiar with during less targeted surveys that applied more comprehensive and more heterogeneous samples than automotive industry also “work” in and apply to automotive industry. The really individual feature besides the descriptive, profiling raw data it is more rather the spatial differentiation where we managed to detect certain individual features of the suppliers and customers (secondary sample) carrying out their business activities in the Northern Transdanubian region. The interviewed companies are surprisingly close to the central players (automobile manufacturers and Tier 1 suppliers) of supplier networks and chains, or they, themsel– ves, can be considered as Tier 1 suppliers, or being integrated into the system at a lower level, nearly each of them had a relatively widespread own set of suppliers too. Behind the relations built upon supplier and customer cooperation there is a significant Features and Spatial Differentiation of Supplier Networks in Automotive Industry 267 concentration of resources, and the weight of important partners within the proportion of sales revenues and sales is really prominent. In line with the findings of international and domestic researches, the quality, price and flexibly supply capacities mean the triple, fundamental basis for entering and remaining in the networks successfully. Relationships, in general, are not multiplex, in the majority of cases they are focused on a sole function. Nearly one third of the automotive industrial suppliers interviewed had a multiplex relationship network, in which collective R&D activities, trainings and coaching, or synchronized purchases were also included. Half or two-third of the companies participated both in international and domestic supplier networks or systems, and only a minor proportion (25%) has relationship networks that were reduced to the domestic economic field. We managed to reveal also spatial differences among the automobile industrial suppliers. The companies in the Northern Transdanubian region joined to supplier net– works earlier, and established relationships with foreign customers with higher proba– bility, which are based upon close relationships of long term framework contracts or strategic alliances, and as customers they had more widespread supplier networks with higher volume concentration within the sales revenues. References A magyar kis és középvállaltok beszállítói szerepének erősítéséről szoló stratégia kidolgozása a gép- és járműipari ágazatban: a jelenlegi helyzet tanulságai és a lehetőségek kihasználásának eszközei 2011. Kopint Konjunktúra Kutatási Alapítvány – Commerzbank – Noerr és Társai Iroda, 2011. május. Munkacsoport-vezető: Klauber Mátyás. Gelei Andrea – Nagy Judit 2004. Partnerkapcsolatok értéke a hazai ellátási láncban – fókuszban a beszállítói vállalatok. Budapesti Közgazdaságtudományi és Államigazgatási Egyetem, Vállalatgazdaságtan Tanszék, 51. sz. Műhelytanulmány, HU ISSN 1786–3031. Gelei Andrea – Nagy Judit 2005. Versenyképesség az autóipari ellátási láncban – a vevői érték és dimenziói az egyes beszállítótípusok esetében. – Vezetéstudomány. 3. pp. 10–20. Gém Erzsébet – Mikesy Álmos – Szabó Zsolt (2011) Beszállítói kapcsolatok: a méret a lényeg? A beszállítói kapcsolatok természete és hatása a vállalati működésre az ipari szektorban. Magyar Fejlesztési Bank Zrt., Budapest. Sass Magdolna – Szanyi Miklós 2009. Klaszterek és a multinacionális vállalatok helyi beszállítói hálózatának fejlődése. – Európai Tükör. 9. pp.21–46. Walter, A. – Ritter, T. – Gemünden, H. G. 2001. Value creation in buyer-seller relationships: theoretical considerations and empirical results from a supplier's perspective. – Industrial Marketing Management. 30. pp. 365–377. INNOVATION ACTIVITIES OF COMPANIES RELATED TO AUTOMOTIVE INDUSTRY Internal and external factors influencing innovation activity in the supplier network MÁRTA NÁRAI Keywords: automotive industry innovation activity In my essay I explored the innovation activity of companies working (also) in automotive industry taking part in the research, and attempted to identify the factors assisting/encouraging innovation activity together with the judgement of their effect, power to influence. In line with the relevant literature, in the course of our research innovation was interpreted in the fields of product, process, organizational-organizing and marketing innovation, and analysed accordingly. Our results demonstrate that in the circle of companies working (also) in automotive industry innovation activity is significantly higher than among companies, enterprises operating in other sectors. A significant part of the companies implemented innovations related to production, manufacturing, and the range of products. The factors promoting innovation were analysed with the help of a five-grade scale; where the presence of solvent demand proved to be the most decisive factor, which was followed by the presence of properly qualified workforce, the appropriate capital supply, and the presence of the appropriate suppliers and subcontractors. The last places of the ranking are occupied by the cooperation with educational and scientific institutes, research capacities, and the availability of consulting services; the automotive companies do not regard the effect, influencing power of these factors on innovation activity too favourably. Introduction Automotive industry is one of the most innovative industrial sectors worldwide, from where the majority of the most modern technologies, solutions, concepts proceed (Demeter–Gellei–Jenei 2004). At the same time, in this industrial sector the effectiveness of the supply chain is very decisive from the point of view of competitiveness, it is of crucial importance how efficiently the companies, company groups can operate and cooperate with each other (Demeter–Gellei–Jenei 2004). Automotive industry is basically built on the pyramid principle, the great automotive companies stand at the top of the hierarchy, followed by the subsidiaries, then the integrators (first tier suppliers), and the second-third tier suppliers. The maximum collaboration of the members of the supplier chain is indispensable for efficiency. Innovation Activities of Companies Related to Automotive Industry 269 Among the companies, firms operating in the country, performing automotive industrial activities, mainly fulfilling supplier roles, one of the important segments of the research conducted by the István Széchenyi University’s JÁTÉK research group is on the one hand to get to know these companies’ innovation activity, see their innovation activity, and on the other hand to explore those determining factors which in case of enterprises connected to car manufacturing, automotive industry influence their innovation activity. The emphasis does not only fall on the exploration of those factors which determine the innovation and development activity of a company within the organization, but we are also seeking those external conditions, circumstances which shape development possibilities, situation in this segment. Our purpose is to identify, define both those factors which support, assist innovation, and those factors which obstruct, hinder it. Innovation activities In the recent years several researches were conducted in the individual regions (e.g. Western Transdanubia, Central Transdanubia, Southern Transdanubia), the purpose of which was to explore the companies’ innovation activity and the factors determining it (Grosz–Rechnitzer 2005; Csizmadia–Grosz–Tilinger 2007; Csizmadia–Grosz 2009; Szépvölgyi 2009). These surveys however were not focused on a particular industrial sector, as our present research; the innovation activity, inclination for innovation of the interviewed enterprises proved to be considerably low: 60–70% of the companies did not make any steps which would qualify as innovative in any area. In general the processing industrial companies proved to be the most innovative. The previous researches which were not conducted at industrial sector level serve as good possibilities for comparison for our present analysis. According to the approaches dealing with innovation, an enterprise realises an innovative activity if it implements an improvement, development or further development in one of the following areas: − product-innovation (the development of a new product or service, the further development of an already existing product/service) − process-innovation (manufacturing, production methods, activities, technology, logistics, transport or distribution methods) − organizational-organizing innovation (methods related to business practice, work supervision, management system, the appearance of new methods in a workplace organization, organizational structure, decision-making procedure, external contact management), and recently − marketing innovation (product design, packaging, product advertising, market launch, pricing). In the course of the research conducted in the circle of automotive industrial suppliers we also interpreted innovation activity, in line with the relevant literature, in the field of product, process, organizational-organizing, and marketing innovation, and analysed it accordingly. In our questionnaire we listed 17 innovation activities, and 270 Márta Nárai asked the answering companies to indicate which characterized the given company, enterprise in the past three years. The great majority (91.5%) of the 118 companies working (also) in automotive industry, car manufacturing that filled in the questionnaire are characterized by innovation; there were only 10 enterprises in the sample (8,5%) that did not implement any innovation or development connected to automotive industry in the past three years. Innovation activity is much higher in the circle analysed by us, than in the circle of companies, enterprises working in other sectors – i.e. not in automotive industry (see Grosz–Rechnitzer 2005; Csizmadia–Grosz–Tilinger 2007; Csizmadia–Grosz 2009; Szépvölgyi 2009). The majority of non-innovative companies comprising less than a tenth of our sample (seven out of ten) are micro and small enterprises, while there is no example of this among big companies with more than 250 employees. The correspondence between company size (on the basis of the number of employees) and innovation activity is significant, but not too strong (the Cramer V coefficient value is 0,3191). There is an interesting correspondence to note between regional, territorial location and innovation activity: there is a significant, very strong (Cramer V 0,667) connection between which county the questioned company operates in and whether it has any innovation activity. On the basis of the established results the counties of Baranya, Borsod-Abaúj-Zemplén, Szabolcs-Szatmár-Bereg, and Békés can be highlighted, the automotive industrial suppliers working in these counties are the least characterized by any kind of innovation activity, the proportion of innovative companies in their circle is substantially lower than the sample average (0; 40; 50; and 67%). The reliability of this correspondence’s validity is however strongly influenced, decreased by the low number of elements – the number of elements is very much dispersed between 1–17 per county. No significant correspondence was found between the year of funding and innova– tion activity. The surveyed companies implemented improvements connected to automotive industry in an average of 6.1 areas in the past three years (considering all companies this is an average of 5.6). The minimum value with respect to innovative organizations was 1, while the maximum value was 15 (Figure 1), i.e. there are companies (2) in the sample, who indicated almost all innovation activities listed by us. The majority implemented four kinds of innovations (20 companies), but many companies indicated three (13), two, five, or eight (10–10) areas. Innovation Activities of Companies Related to Automotive Industry 271 FIGURE 1 Number of innovation activity types implemented in the last three years* * Calculated on the basis of the indicated innovation activities. Source: Questionnaire survey (2011). The companies striving for innovation implemented mainly process-innovations and product innovations (Table 1). The proportion of those companies was outstanding (57,6%–57,6%), which developed further already existing products and/or improved an applied technology, or changed technology. On the other hand, making developments in informatics, improving manufacturing, production methods; or inventing, developing, establishing some new product used in automotive industry characterized at least half of the companies. A relatively small proportion (11–21%) of the companies implemented marketing innovation developments, improvements. Among organizational-organizing innovations most companies (a bit more than half of the companies) mentioned developments in informatics, and introduced new methods in work supervision, organization. Changes, innovations were implemented least of all in contact management, decision-making procedure, distribution method and management (Table 1). We attempted to create innovation groups with the help of cluster analysis, but did not get meaningful results, we distinguished two main groups, the groups of innovative and non-innovative companies, this however has not provided any plus information in comparison to our findings so far. 272 Márta Nárai TABLE 1 Frequency of innovation activities implemented in the past three years Innovation type Product-innovation development of a new product development of a new service further development of an already existing product further development of an already existing service Process-innovation change of manufacturing, production method introduction of a new activity technology change, development of an applied technology Organizational-organizing innovation change, development of logistics, transport method change of distribution method introduction of a new method in work supervision, organization introduction of a new method affecting the management system change in workplace organization, structure introduction of a new method in the decision-making procedure appearance of new methods in the external contact management development in informatics Marketing innovation developments affecting marketing developments in sales Innovative companies number proportion (%) 60 28 68 28 50,8 23,7 57,6 23,7 62 47 68 52,5 39,8 57,6 34 13 28,8 11,0 51 43,2 26 22,0 36 30,5 16 13,6 13 11,0 61 51,7 23 25 19,7 21,2 Source: Questionnaire survey (2011). We tried to explore the latent structure of the complexity of innovation activities with factor analysis. In case of our present sample the Maximum-likelihood method was deemed the most appropriate. From the 17 innovation types listed in the questionnaire six factors were created by 47% information preservation. The KMO-value – which is one of the most important index-number to judge how appropriate the variables are for factor analysis (Sajtos–Mitev 2007) – is 0,77 in the completed survey, which means that our variables are appropriate. The element number of the sample warns us that the factor weights have to reach at least 0.5 so that they can be considered significant. The innovation activities falling into one factor generally go together, i.e. if one of them was present in a company, then generally the innovation constituting the other elements of the factor took place with a greater probability. The factors are shaped in an interesting way, the composition of which is shown in Table 2. The last three factors Innovation Activities of Companies Related to Automotive Industry 273 consist of only one innovation activity, the development of a new product, the develop– ment affecting the logistic, transport method, and the introduction of a new activity form individual factors respectively. At the same time, there are three activities, which do not fit into the model on the basis of factor values, these are the following: the deve– lopment of a new service; the appearance of new methods in external contact manage– ment; the further development of an already existing product. The factor analysis was repeated without the non-fitting three variables. This resulted in four factors (KMO 0,757), the explained variance is still not better than before, it is 45%, i.e. a significant part of the information is lost. The composition of the factors created this way is shown in Table 3. The composition of the factors was changed to the extent that from the variables previously composing the three indepen– dent factors two variables were moved into other factors, while the introduction of a new activity still constitutes an independent factor. The high degree of innovation activity and the most common forms of innovation well demonstrate that the automotive industry is an innovative sector, and the majority of the national companies active in automotive industry implements innovations affecting production, manufacturing, and product range. The dimension of innovation plays an important role in automotive industry among the value functions offered by the suppliers to the customer (Gelei–Nagy 2004). On the basis of the approach of the cited authors, Möller–Törönnen (2003) innovation is interpreted as an efficiency function, which greatly contributes to competitiveness, since innovation ability refers to the possibility that as a result of the cooperation with a customer (client) a product or process innovation may ensue, i.e. the supplier is capable of development, innovation, is able to realize the customer’s (client’s) idea, and adapt itself to the – even continuous – changes of customer demand. Gelei–Nagy (2004) re– gards this form of innovation an indirect (incremental) innovation, which is an expectation towards every automotive industrial supplier who wish to remain in the competition in the long run. There is however a ‘higher’ level of innovation called strategic innovation, which strongly increases the competitiveness of first tier suppliers (integrators); at this level the supplier has to respond not only to the innovation induced by the cus– tomer, but in some cases the supplier itself becomes the true innovator, i.e. the supplier TABLE 2. 274 Márta Nárai Innovation Activities of Companies Related to Automotive Industry 275 TABLE 3. The composition of factors without the three non-fitting variables, factor weight matrix Maximum-likelihood method – Rotated Factor Matrix a Factors 1 Sales – marketing Developments in sales Developments affecting marketing Change of distribution method Development of a new product Developments in informatics Change of manufacturing, production method Introduction of a new method in work supervision, organization Change of technology, development of applied technology Change, development of logistic, transport method Introduction of a new method in the decision-making procedure Introduction of a new method affecting the management system Change in workplace organization, structure Introduction of new activity 2 3 Technology – Work methodology organization .802 .618 .569 .469 4 New activity .281 .250 .712 .575 .553 –.267 .439 .392 .765 .630 .251 .595 .268 .617 Source: Questionnaire survey (2011). formulates suggestions – developments –, which make the customer (client) change, taking steps to adapt. In spite of the fact that among the surveyed companies innovation is strongly present, only one third (31.4%) of the companies filling in the questionnaire evaluated the capacity for innovation as the most important element of the company’s competitiveness. One fifth of them emphasized R&D activity. From the mentioned factors the capacity for innovation proved to be only the fifth most decisive factor of competitiveness, much behind good price (72,9%), good contact with customers (69,5%), cheap but qualified workforce (50,0%), and standing on more legs (40,7%). Compared to judging it a competitiveness factor, significantly less companies, only one tenth (9,3%) considered innovation the main driving force of their company’s operation, and a similarly small proportion of answering companies (8,5%) set this goal 276 Márta Nárai for the next three years. They lay emphasis primarily on the expansion of clientele (59,3%), the decrease of expenses (29,7%), and the expansion of their product range (28,0%). Innovation activity/capacity appears in the judgement of competitiveness and the plans of the future as a less stressed element. For that matter, a significant connection was found between the (subjective) judgement of the companies’ – both national and international – competitiveness and their innovation activity with an error limit of 5%, although the strength of the connection is weak, its Cramer V value does not reach 0.3 (in case of the judgment of national competitiveness it is 0,261, and in case of the judgement of international competitiveness it is 0,249). A significant proportion of companies implementing innovations, developments consider themselves very competitive (41%) and of average competitiveness (44% and 55%) both in a national and international comparison. At the same time, among non-innovative companies there was no company that would consider itself very competitive either in national, or in international comparison; in a national regard they all evaluated their companies as average, while in an international regard half of them considered their companies to be hardly competitive. We examined whether we can find a correspondence between the applied innovations, innovation activities and the judgement of competitiveness. On the basis of the established results, however, even with an error limit 5% (significance level), no significant connection can be demonstrated between innovation activities belonging to the circle of product, process, organizational-organizing, marketing innovations and the judgement of national and international competitiveness. The judgement of competitiveness is therefore independent of the type of innovations a company implemented in the past three years. The factors determining innovation The relevant literature generally classifies the factors influencing innovation negatively into four groups: − the group of expense factors (e.g. lack of capital, lack of potential resources available outside the enterprise, high innovation costs) − problems connected to knowledge (lack of qualified workforce and information) − market factors (e.g. the market is dominated by already established enterprises, the demand for innovation is uncertain) − reasons against innovation (e.g. it is not needed due to previous innovations, lack of demand for innovations) (e.g. Csizmadia–Grosz–Tilinger 2007; Szépvölgyi 2009). Among the assisting factors generally the following ones are the most common to appear (Szépvölgyi 2009): − capital resources Innovation Activities of Companies Related to Automotive Industry − − − − − − − − 277 availability of risk capital presence of solvent demand properly qualified workforce presence of proper suppliers and subcontractors willingness to cooperate innovation and economic support research capacities and supply consulting services. From the viewpoint of innovativity not only a company’s size and capital resources and the presence of personal conditions prove to be important factors, but also the way of company management, contact characteristics, production and sales co-operation, and collaboration, especially with universities, scientific centres, other innovative enterprises and service providers. The presence of innovation incentives, supports, services is also not of negligible significance, nor their degree of accessibility, and at the same time more long-term economic development strategies would also be absolutely needed (Pitti 2008). Getting to know all these factors and explore their power to influence is indispensable in the course of our present research. In our automotive industrial research we analysed the factors which promote innovation with the help of a five-grade scale, we listed 12 factors, the role of which from the viewpoint of a given company had to be judged with the help of a five-grade scale (where 1: absolutely not, and 5: to a significant extent) on the basis of how much they do or do not assist, encourage the innovation activity of a company. Among the surveyed 118 companies (suppliers) with automotive industrial interests the presence of solvent demand proved to be the most decisive factor promoting innovation activity with average values above 4 (Figure 3). This factor influenced, assisted the innovation activity of half of the companies to a significant degree, and to a decisive degree (value four) in case of almost third of the companies (Figure 4). No other factor reached the average value of 4 or above, and it did not happen in case of any other factor that at least half of the companies, enterprises considered its influencing power significant. After solvent demand, the presence of properly qualified workforce, appropriate capital resources, and the presence of appropriate suppliers and subcontractors proved to be the factors assisting, encouraging innovation activity the most. The roles of production and sales co-operations, innovation and economic supports, or the general business climate were valued much lower. The co-operation with educational and scientific institutes, like for example the co-operation with universities, research capacities, and the availability of consulting services are at the last places of the ranking with average values of approximately 2.5; the impact, influential power of these factors on innovation activity are not too favourably evaluated by automotive companies. In the opinion of a great proportion of them (around 50%) these factors absolutely not assist, encourage innovation activity or do so only to a very minimal degree. At the same time it is important to note that there is a relatively decisive proportion of companies (about 278 Márta Nárai 30%), for which even the latter factors – except the availability of consulting services – prove to be decisive or significant assisting/encouraging factors (Figure 4). Those companies that are in contact with universities and/or research institutes, evaluate the innovation encouraging influence of educational and research institutes much more positively, only a very small proportion of them are of the opinion that these institutes do not at all promote the innovation activity of market actors (6,3% in case of universities, 2,7% in case of research institutes), contrary to those who do not cooperate with such actors (34,6%; and 26,6%). In case of both universities and research institutes the contact is significant and of medium strength (Cramer V 0,412; and 0,379). Our results also demonstrate that the presence of contact with the different professional and/or scientific institutes in itself does not have an innovation supporting influence, which is true both for the co-operation with research institutes and the chamber of commerce and industry or incubator houses. In case of the co-operation with universities, however, we found – although with an error limit of 5% – a significant (although of a very weak strength) connection between the presence of the contact and the implementation of innovation activity. A great majority (80%) of the non-innovative companies is not in contact with universities, while among innovative companies this proportion is much smaller (41,7%, and 45% when considering the whole sample). Among the companies which do not co-operate with universities the proportion of companies that implement no innovations whatsoever is five times higher than among those who have such co-operations (15% as opposed to 3%; sample average: 8,5%). FIGURE 3 Factors promoting innovation, average values The presence of solvent demand 4,23 The presence of properly qualified workforce 3,92 Proper capital supply 3,8 The presence of appropriate suppliers and subcontractors 3,65 General business climate 3,23 Production and sales co-operations 3,23 Innovation and economic supports 3,1 The presence, coherence of economic development… 2,85 2,76 Co-operation with educational and scientific institutes The availability of risk capital 2,74 2,64 Research capacities and demand The availability of consulting services 2,5 0 Source: Questionnaire survey (2011). 0,5 1 1,5 2 2,5 3 3,5 4 4,5 Innovation Activities of Companies Related to Automotive Industry 279 FIGURE 4 Frequency of judgements related to the influence of factors promoting innovation activity,% 2,6 3,4 12,9 2,6 23,3 4,3 The presence of solvent dema nd The presence of properly qua lified workforce 7,8 Proper ca pita l supply 8,6 11,6 Production a nd sa les co-opera tions 7,8 Genera l business clima te 12,5 18,4 19 25 The a va ila bility of risk ca pita l 23,4 18,7 Resea rch ca pa cities a nd dema nd 22,1 The a va ila bility of consulting services 23,7 32,5 25,9 26,2 23,9 3 40 4 14,9 23,7 7 21,6 8,6 24,3 7,5 21,2 27,4 28,9 20 6 22,8 31,6 21,1 18,8 37,1 38,8 Co-opera tion with educa tiona l a nd scientific institutes 2 24,3 21,4 35,7 10,3 15,8 0 38,8 38,3 The presence, coherence of economic development stra tegies not at all 33,6 26,7 23,5 12,3 Innova tion a nd economic supports 51,7 36,2 18,1 7,8 6,1 The presence of a ppropria te suppliers a nd subcontra ctors 29,3 10,5 7,9 28,9 60 5,3 80 100 to a significant degree Source: Questionnaire survey (2011). More than half of the companies (55%) are in contact with universities, a third of them are in contact with research institutes, two third with the chamber of commerce and industry, 40,7% of them with schools, and 9,3% of them (also) with incubator houses. When discussing innovation it is necessary to look at what characterizes the companies’ R&D activity, since the factors of research-development and innovation capacity cannot be separated from each other. Let us suppose that the two activities are not independent of each other. Let us see the results of our research! Less than half of the questioned companies (46,2%) have R&D activity, only a quarter of these companies have an independent R&D department, and in case of a further eighth of them the engineering constitutes the basis of the R&D activity. On the other hand, more than half of the questioned companies, enterprises at least partly regard it important that the automotive suppliers have R&D activity. There were companies in the sample that laid great emphasis on research-development, that continuously observe the market and the other competitors, and many times develop further what a competitor ’comes up’ with. They are of the opinion however that for an efficient development activity not only the work of the engineers but also that of the marketing professionals is important, since they are the ones who find out things to develop and the directions for development. 280 Márta Nárai „It is not the task of the development engineers to think about what to develop, that is the task of the marketing professionals…” (excerpt from an interview) A quarter of all the companies and more than half of the companies having R&D activity (57%) are capable of product development, not only production development or smaller modifications related to the products. In their case, about a great majority of them (77%) it can be stated that they are not only capable of product development, but in the past three years have actually developed some new products. Then again this is also true for more than the third of the companies who do no research-development. Although we can find a significant relation between R&D activity and this – and only this – form of product-innovation, this relation is of a slightly weaker than average strength (Cramer V 0,361). At the same time, no significant connection can be demonstrated between R&D activity and the further development of an existing product, the development of a new service, or the further development of an existing one. The same can be said about the developments affecting the field of procedures, organizationorganizing, and marketing, i.e. whether a company innovates in these fields is independent of whether it does research-development or not. Our previous assumption was not justified. In addition to product development, a correspondence was found in only one instance: in case of the change of the manufacturing-production method a weak connection could be demonstrated, with an error limit of 5%, with the presence of R&D activity (Cramer V 0,26). A fifth of the companies co-operate with the company that orders the supply of a product connected to automotive industry in the field of joint research-development, which can doubtlessly have some part in the relatively high research-development and high innovation activity characterizing the sample. This form of co-operation is ’practiced’ by the majority, joint acquisitions and sales were indicated by much less companies (12,7%; and 6,8%). It is also important to emphasize that a significant part of the organizations received support/assistance for their becoming automotive suppliers from the company ordering the supply, which (can) help, and (can) promote development, improvement, further development, i.e. innovation, and which could be the generator of the company’s further development. These assistances include e.g. the sharing of know-how; the training, teaching of colleagues; the transfer of machines, technologies or any help related to quality insurance. The latter was mentioned by more than two fifth of the questioned companies, a fourth of them mentioned the transfer of technology and the training of colleagues, while a sixth of them mentioned the sharing of know-how (Figure 5). A significant connection however cannot be demonstrated between any of these factors and innovation activity. Innovation Activities of Companies Related to Automotive Industry 281 FIGURE 5 Proportion of companies who received support from the company ordering the supply of products which has (could have) a positive influence on innovation according to the type of assistance (%) 50 44,4 45 40 35 30 20 15 26,7 24,8 25 16,4 10 5 0 The sharing of know-how The traning, teaching of colleagues Source: Questionnaire survey (2011). The transfer of machines, technologies The help related to quality insurance Conclusion In our essay we explored the innovation activity of companies working (also) in automotive industry taking part in the research, and attempted to identify the factors assisting/encouraging innovation activity together with the judgement of their effect, power to influence. In line with the relevant literature, in the course of our research innovation was interpreted in the fields of product, process, organizational-organizing and marketing innovation, and analysed accordingly. Our results demonstrate that in the circle of companies working (also) in automotive industry innovation activity is significantly higher (91,5% of them mentioned some innovation activity) than among companies, enterprises operating in other sectors. The high degree of innovation activity and the most frequent forms of innovation – a significant part of the companies implemented innovations related to production, manufacturing, and the range of products – well demonstrate that automotive industry is really an innovative sector. In spite of the high innovation activity, the role of innovation capacity was not evaluated by companies as very significant from the viewpoint of competitiveness. The factors promoting innovation were analysed with the help of a five-grade scale; where the presence of solvent demand proved to be the most decisive factor, which was followed by the presence of properly qualified workforce, the appropriate capital supply, and the presence of the appropriate suppliers and subcontractors. The last places of the ranking, with average values of approximately 2.5, are occupied by the co- 282 Márta Nárai operation with educational and scientific institutes, research capacities, and the availability of consulting services; the automotive companies do not regard the effect, influencing power of these factors on innovation activity too favourably. Note 1 The Cramer V coefficient is a symmetrical indicator, it is connected to Chi-square statistics, and indicates the strength of the connection between two variables. Its value is between 0 and 1, the closer it is to 1, the stronger connection it indicates between the two given variables. Cramer V can be considered one of the most reliable indicators (Sajtos–Mitev 2007). ANALYSIS AND DEVELOPMENT STRATEGIES – SUMMARIZED EXPLORATORY RESEARCH OF COMPANY PERFORMANCE LÁSZLÓ JÓZSA Keywords: automotive suppliers market environment economic crisis R+D+I+O activities Automotive industry is deemed to be a prominent sector in Hungary and can be mentioned as one of the propulsive industries in Hungarian economy despite the hardships entailed by the economic crisis. In terms of strategic aspects its job creating ability, contribution to the GDP and its power to form the reputation of the country in business respect are essential. This study makes an analysis on the market environment of domestic suppliers and it examines the companies’ performance and development directions, focusing in particular on the automotive industry of the Central and Western Transdanubian regions. Introduction From the beginning of the 1990’s an intense upsurge was experienced on the car market in Hungary. The status of infrastructure in the country also played a positive role in the extension of automotive industrial market. Favourable endowments or facilities of premises, the professional knowledge and experience of experts, and the relatively cheap but still qualified labour force all contributed to attracting several foreign investors into the country and to encouraging them to commence intensive development projects, utilising Hungary’s favourable geopolitical situation. Additionally, diverse macro-economic factors, such as the government’s tax policy, influenced the processes of economy favourably. Suppliers have remarkable automotive industrial traditions and owing to this wellconstructed supplier chains were established during the past 20 years. Hungarian automotive and parts sectors have been integrated properly into the European and global division of labour. The two decades of experiences of investors’ programs helped in organising the specialised domestic industrial capacities into a network, where the suppliers are clustered in significant organisations of interest representation (Havas, 2010). The clusters that can be managed as organisational innovations are functioning for the time being only formally until the end of the state subsidy period, however, they are either incapable of sustaining individually, or can sustain individually but only to a limited extent. The distrust being a typical feature of Hungarian business life does not favour to the evolution of supplier networks either. 284 László Józsa Outlook to Europe – Processes on the automotive industrial market in the recent past Role players of automotive industry – Sales, regional competition In our days it is still a typical tendency that the Central and Eastern European region has gradually become the centre of European automobile production and from the viewpoint of Asian car manufacturers it has, step by step, become the centre of automobile manufacturing, since it is anticipated that the demand for – primarily small and environment friendly – vehicles produced in this region will probably increase in the future. In accordance with the report made by the European Automobile Manufacturers’ Association (Association des Constructeurs Européens d’ Automobiles – ACEA) in 2010 nearly 13 million vehicles were produced in the European Union, which was 15% higher than the volume manufactured in the same period of the previous year, but it still had a 14% lag compared to the quantities produced in 2008 before the recession. According to the forecasts of the Business Monitor International (BMI) the automotive industry of Central and Eastern Europe may count with an increase by nearly 7% in the forthcoming 5 years. Consequently, the annual production of this region is in excess of 4.22 million units, highly the level of 3.4 million units achieved in 2008. Hungary, Slovakia and Romania – owing to their export oriented approach – enhanced their positions on the automotive market of the region with an annual increase of 25.9%, 20.7% and 18.4% in 2010 respectively. In accordance with forecasts automobile manufacturing will reach the pre-recession level of production by 2012, and afterwards further increase is expectable (Figure 1). The importance of this region is evidenced by the fact that 10 world leading automobile manufacturers have production facilities in Hungary. The sales potentials of Central and Eastern European markets are determined either by the domestic demand, such as in Poland, or they depend on the West European demands (such as in the Czech Republic, in Hungary, Slovakia and Romania) (BMI, 2010). Besides the significance of emerging markets the automobile manufacturers should not disregard the developed markets, which have got long term priority among the foreign automobile manufacturers. One of the main attractive factors of the WestEuropean region for the manufacturers is that it possesses all the advantages that are typical of developed markets (infrastructure, qualified labour force, technology, etc.). Additionally, due to the higher life standard on demand-side it is assumed that demand will not sink very low and the market will remain stable. The fact, that the policies of most West-European governments treat the supporting of automotive industry as an essential objective, plays an important role in the sustaining of the leading positions of developed markets. It should be instanced here that these countries not only introduced the wreck premium faster at the peak of the recession, but they also attempted to resolve doubts throughout the European Union about the emission norms to be put in force in 2015. But it should also be mentioned Analysis and Development Strategies – Summarized Exploratory Research… 285 that different European programs have been launched to popularise environment friendly vehicles. German government has separated 500 million Euro for the purpose of supporting the realisation of the plan that by 2012 one million electric cars shall run on roads; the French government intends to devote 1.5 billion Euros, until 2020, to reach the aim that 2 million electric and hybrid cars shall be in traffic on roads. In the meantime the United Kingdom has granted 25% premium or discount for the purchasing of electric cars the price of which is less than 5000 Pounds (ACEA, 2010). FIGURE 1 Automobile manufacturing in Central and Eastern Europe, 2007–2014 Source: Lepsényi, 2010. West-European countries can hardly compete with the Central and Eastern-European countries in respect of low production and wage costs. For restoring profitability the automobile manufacturers have been focusing on restructuring, thus they relocate certain part of their production to Central and Eastern Europe. Development of sales figures in Europe in the period between 2009 and 2010 In Europe compared to 2009 in 2010 the number of cars sold decreased by 4.7%: in the continent altogether 13.7 million cars were sold. The Greek market suffered the largest decline (–36.1%; 140 691 cars), followed by the Hungarian car market (–27.9%; 43 815 cars, which is less by 5 thousand than that of Luxembourg), and the German (–23.4%; 2 916 260 cars) car market. From among the largest car markets the sales dropped in France (0.7%) and in Italy (9.2%) (Jato Dynamics, 2010).On the contrary, there were 286 László Józsa markets where the number of cars sold increased: for example in Ireland (53.9%; 88 423 cars), in Iceland (45.7%; 3106 cars) and in Sweden (35.7%; 289 683 cars) the car pur– chases showed an upswing. The British and Spanish markets extended slightly by 1.8, and 3.1 per cent. Volkswagen kept leading the list of brands even in 2010, with VW Golf which was the most popular car in Europe. Table 1 demonstrates the change in the aggregate sales in Europe of the 10 most popular passenger car brands and models in the period 2009–2010. In 2011 in Europe, none of the 10 most popular models of the year 2010 could improve the number of registrations realised in the first quarter of 2010. The most popular model was still Volkswagen Golf, while the second one was the Ford Fiesta, which posted 27.7% decrease in turnover compared to the previous year (Table 2). TABLE 1 Development of sales of the Top 10 brands and models in Europe, 2009–2010 (units) Top 10 brands 1. Volkswagen 2. Renault 3. Ford 4. Peugeot 5. Opel/Vauxhall 6. Citroen 7. Fiat 8. Audi 9. BMW 10. Mercedes Top 10 Model 1. Volkswagen Golf 2. Ford Fiesta 3. Volkswagen Polo 4. Renault Clio 5. Opel/Vauxhall Corsa 6. Peugeot 207 7. Opel/Vauxhall Astra 8. Renault Megane 9. Fiat Punto 10. Citroen C3 2010 2009 Change (%) 1,536,473 1,138,180 1,118,089 1,002,956 998,692 835,114 823,097 623,510 608,502 590,412 1,642,114 1,088,736 1,289,599 990,276 1,057,579 866,483 1,010,696 612,378 571,688 588,100 –6,4 +4,5 –13,3 +1,3 –5,6 –3,6 –18,6 +1,8 +6,4 +0,4 492,556 402,207 354,068 338,245 317,950 305,468 291,219 260,542 257,645 224,953 571,075 472,158 283,069 313,102 351,858 367,474 275,906 231,015 324,125 167,400 –13,7 –14,8 +25,1 +8,0 –9,6 –16,9 +5,6 +12,8 –20,5 +34,4 Source: Jato Dynamics, 2011. http://hvg.hu/cegauto/20101119_auto_toplista#utm_ ource =hvg_ daily&utm_medium=email&utm_campaign=newsletter2010_11_19&utm_content=normal, (Date of downloading: 22.1.2011). Analysis and Development Strategies – Summarized Exploratory Research… 287 TABLE 2 Development of sales of the Top 10 brands and models in Europe, 2011 (January to September) (units) Top 10 Brand March 2011 March 2010 Change (%) Q1 2011 Q1 2010 Change (%9 Volkswagen Golf Ford Fiesta Volkswagen Polo Opel/Vauxhall Corsa Opel/Vauxhall Astra Ford Focus Renault Clio Peugeot 207 Renault Megane Citroen C3 53,055 50,534 39,311 39,189 37,125 36,339 36,048 31,021 26,534 26,021 59,267 69,085 37,726 42,244 39,313 40,332 43,830 41,540 29,848 29,653 –10.5 –26.9 +4.2 –7.2 –5.6 –9.9 –17.8 –25.3 –11.1 –12.2 123,480 101,859 93,740 83,383 79,404 73,222 89,157 73,280 65,092 56,737 135,745 140,932 95,154 86,421 79,390 79,758 103,359 91,808 70,942 64,606 –9.0 –27.7 –1.5 –3.5 +0.0 –8.2 –13.7 –20.2 –8.2 –12.2 Source: Jato Dynamics, 2011 (URL:http://hvg.hu/cegauto/20110421_nepszeru_autok (Date of downloading: 20.10.2011). TABLE 3 Top 10 brands and models in Hungary, period January–October, 2010 Top 10 brands 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. Volkswagen Ford Skoda Opel Renault Suzuki Toyota Nissan Peugeot Fiat Sold units 3658 4303 3681 3649 2973 2049 2140 1170 1196 1397 Top 10 types Skoda Octavia Suzuki Swift Ford Focus Volkswagen Golf Opel Astra Renault Mégane Nissan Qashqai Volkswagen Polo Renault Fluence Opel Corsa Sold units 2250 753 2361 1424 1839 851 693 719 758 553 Forrás: Jato Dynamics (2010). http://hvg.hu/cegauto/20101119_auto_toplista #utm_source=hvg_ daily&utm_medium=email&utm_campaign=newsletter2010_11_19&utm_content=normal (Date of downloading: 20.11.2010). In Hungary, in 2010, the most popular car brand was Ford, the second one was Skoda, and the third one was Volkswagen. The most popular model was still the Ford Focus, followed closely by Skoda Octavia (Table3). In the period between January and September in 2011 nearly 34 thousand passenger cars were registered or put in service in Hungary. The domestic sales figures related to the 10 most popular car models are illustrated in Table 4. 288 László Józsa TABLE 4 Top 10 brands and models in Hungary, period January-September, 2011 Sold units Top 10 brand 1. Skoda Octavia 2. Opel Astra 3. Ford Focus 4. Volkswagen Golf 5. Volkswagen Passat 6. Renault Fluence 7. Renault Mégane 8. Dacia Duster 9. Volkswagen Polo 10. Opel Corsa 2339 2135 1925 917 828 766 720 704 672 664 Forrás: Jato Dynamics (2011). http://hvg.hu/cegauto/20110421_nepszeru_ autok (Date of downloading: 20.10.2011). Analysis of the domestic suppliers’ market environment Following the political transformation in Hungary the car market and automotive industry soared. The favourable situation of infrastructure in Hungary also contributed to the expansion of the industry and market. Analysing the supply-side it can be stated that due to the favourable endowments of plants, the experts’ competence as well as their experiences gained from former projects, and last but not least the wages of labour force being lower than those paid on West-European markets the foreign investors saw excellent potentials in the Hungarian supply market. However the demand-side also changed concurrently. Better living standards of consumers, the higher real incomes of people, and perhaps their desire and openness to novelties contributed to the fast development of car market. But the recession has changed the situation to worse. In Figure 2 the regional distribution of passenger cars in 2010 is indicated. In terms of industrial production, in Hungary, the largest setback, by 17.2% was faced in 2009, and the export sales dropped by 18.8%. By 2010 the sector figures improved, with the exception of domestic sales, but they still did not reach the level recorded prior to the recession. Apart from the automobile and automobile component manufacturers several other suppliers can be categorised among leather, rubber, plastic, paint, glass, metal processing, or electronic industrial sectors from among the role players of domestic automotive industry. The market of the part manufacturing companies also differ a lot from one another, considering the fact that there are companies who produce only for automobile factories, while others supply only commercial vehicle assembling plants, Analysis and Development Strategies – Summarized Exploratory Research… 289 another group supplies both types of vehicle manufacturers, and others supply also consumers outside the automotive industry. At the turn of millennium Hungarian vehicle manufacturing was an industrial sector generating the third highest production value, and in the period between 2005 and 2007, it was the second one in this ranking: during this period of two or three years its weight increased from 12.2% (2000) to 17.3% (2007), i.e. by 41.8%. The weight of companies engaged in automotive industrial activities was even higher, but it did not exceed the rate achieved by the largest domestic processing industrial subsector, the “production of electric machinery and instruments”, with 25 to 26% (KSH, 2008). FIGURE 2 Regional distribution of cars in 2010 Western Transdanubia 11% Central Transdanubia 11% Central Hungary 33% Source: Own editing based on the figures of KSH, 2011. Southern Great Plain 13% Northern Great Plain 13% Northern Hungary 10% Southern Transdanubia 9% 290 László Józsa FIGURE 3 Regional distribution of buses in 2010 Western Transdanubia 9% Central Transdanubia 15% Southern Great Plain 10% Northern Great Plain 12% Northern Hungary 13% Central Hungary 31% Southern Hungary 10% Source: Own editing based on the figures of KSH, 2011. FIGURE 4 Regional distribution of trucks in 2010 Western Transdanubia 10% Central Transdanubia 11% Southern Great Plain 14% Northern Great Plain 12% Northern Hungary 10% Central Hungary 34% Southern Transdanubia 9% Source: Own editing based on the figures of KSH, 2011. The share of automotive industry in the aggregate sales revenues of the 500 domestic companies’ with highest sales revenues was 9.8%, and within the sales revenues the rate of export was 90% (HVG, 2010). This rate was generated by altogether 40 companies, namely the following: Analysis and Development Strategies – Summarized Exploratory Research… Audi Hungaria Motor Kft. Magyar Suzuki Zrt. Robert Bosch Elektronika Kft. Lear Corporation Hungary Kft. Denso Gyártó Magyarország Kft. LuK Savaria Kuplunggyártó Kft. Visteon Hungary Kft. BorgWarner Turbo Systems Kft. Continental Teves Magyarország Kft. BPW-Hungária Kft. Rába Járműipari Holding Nyrt. Hammerstein Bt. ZF Hungária Kft. SMR Automotive Mirror Technology Hungary Bt. Robert Bosch Energy and Body Systems Kft. ZF Lenksysteme Hungária Kft. Ibiden Hungary Kft. MÁV-Gépészet Zrt. LKH Leoni Kábelgyár Kft. 291 Rába Futómű Kft. Knorr-Bremse Fékrendszerek Kft. Delphi Thermal Hungary Kft. Knorr-Bremse Vasúti Jármű Kft. BOS Automotive Products Bt. Linamar Hungary Nyrt. Magyar Toyo Seat Kft. Emcon Technologies Kft. Dana Hungary Kft. General Motors Powertrain Autóipari Kf t. Suoftec Kft. W.E.T. Automotive Systems Kft. Schwarzmüller Járműgyártó Kft. Modine Hungária Kft. Videoton Autóelektronika Kft. Benteler Autótechnika Kft. AGC Autóipari Magyarország Kft. Summit D&V Autóipari Kft. Rába Járműipari Alkatrészgyártó Kft. Wescast Hungary Zrt. Bombardier MÁV Kft. Hungarian automotive industry’s internal resources and features are taken into consideration, and the external, directly or indirectly influencing factors, such as economic policy, political, legal and other features are summarised in the framework of a SWOT analysis in Table 5. Development trends at supplier companies The companies of this sector pay much attention to R&D&I activities, which, in long terms, is an indispensable precondition to competitiveness. The intensity of domestic automotive industry’s R&D activities, however, shows significant lag compared to other EU member states, and more precisely, to Central European countries. The R&D activities in the domestic automotive industry are less intensive only in Portugal, Romania and Slovakia, and this fact – showing continuous improvement – means a considerable challenge for the role players of domestic automotive industry. There are several powerful, large and middle sized companies also carrying out R&D activities, and manufacturing for the international market present in Hungary, but R&D&I activities need to be enhanced in order that the companies shall be able to keep up with other role players of the global automotive industry. To this end it is indispensable to armour the technical education with innovative approach, to let it give competent, proactive and excellently qualified experts to the labour market. 292 László Józsa Description of automotive industrial Research&Development Significant academic and corporate technical research and development traditions may be deemed as strengths as well as the fact that at Tier1supplier level at several large companies remarkable R & D activities are carried out for the international market. Among the weaknesses it should be mentioned that R & D is highly concentrated, that is only few companies perform effectively R & D activities; the weakness of the R & D activities performed at automotive industrial SMEs is attributable to the lack of sources and motivation; apart from the select universities there are few higher educational institutes giving well-qualified development engineers to the market. A tool to keep the multinational large and middle sized enterprises in Hungary and to attract new ones is relevant motivation of R & D activities through economic political means; in line with R & D activities ordered by the industry and market knowledge centres and national laboratories should be set up. It may be identified as a certain risk that there is a lack of researchers in West Europe nevertheless the salaries paid to Hungarian research and development engineers are nearly half of those paid in West-Europe. Local R&D activities related to production represent specific attractiveness, which assists to retain the automotive industrial capacities once settled in Hungary and to which foreign interests are associated, along with a supplier sector of appropriate scale and quality. Additionally, the fact should be mentioned, that as an effect of the financial crisis certain part of the R&D experts of automotive industry will leave his or her profession. TABLE 5 Description of the automotive industrial suppliers’ environment Strengths − Remarkable traditions in automotive industry and the related supplier chains; − Hungarian automotive and part manufacturing sector have integrated properly into the European and global division of labour; − The majority of the large Tier 1 international automotive suppliers are present in Hungary; − Several very strong large and middle sized companies performing also R&D activities and manufacturing to the international market are present in the country; − Two decades’ experience gained in investment programs assisted in the organisation of domestic specialised industrial capacities into a network; Weaknesses − The clusters are functioning, for the time being, only formally and only until the end of the state subsidy period; they are unable to sustain independently; − Tier 2–3 suppliers’ prices are so much depressed by customers that they hardly generate any profit, thus they do not have any source for development; − Supplier companies “ripen” relatively slowly: on the average a company becomes a full supplier for the customer in two years; − Hungarian supplier network is not adaptive, either they are incapable or they can only slowly follow the increase of production volume at the automobile factory; − The rate of Hungarian supplies – in the case of both passenger car assembling plants in Analysis and Development Strategies – Summarized Exploratory Research… Strengths − Suppliers have significant professional interest representation organisations. Weaknesses Hungary – is low and often they are not directed to products or parts conveying high technical value, but a high rate of supply is represented by services not integrated in the finished product and by subsectors being not knowledge intensive; − In the region of existing car factories there are no proper building sites available for the suppliers. Opportunities − Large automotive industrial companies may act as cluster organisers; − Due to the high volume orders the car factories and their tier 1 suppliers are classed-up by suppliers; − New suppliers might be attracted to Hungary due to the settlement of Daimler factory, which provides opportunities for the whole sector; 293 Threats − As a consequence of the financial recession loan-lending to the SMEs is more expensive, or it might also be terminated, which may entail the bankruptcy of the masses of SMEs who are not liquid enough; − Distrust being a typical characteristic in Hungarian business life is not favourable for the development of supplier networks; − Circular debts may reach the suppliers, thus even the already existing supplier network may also get damaged. Source: Own editing (2011) based on BMI, 2010 and Havas, 2010. In a short term, the substitution of this intellectual capacity is unrealistic. Large companies do not let the R&D activities of key fields out of the parent company’s hands, thus in Hungary there is no chance to carry out R&D activities of higher relevance, or if yes, then just in very few exceptional cases. Some factors influencing competitiveness and being important in respect of strategy: − Improvement of labour force-supply, − Development of labour force demand/supply, number of vacant positions, − Number of employees bearing higher educational degrees or PhD scientific degrees in research sector, − Retaining labour force, number of jobs saved, − tendering system adjusted to the needs in automotive industry, − displacement of supplies in the direction of products to be integrated and representing higher technical standard categories (based on the priorities of the supplier program), − ration of component supply within overall supply, − development of transport and network infrastructures, − acceleration of logistical developments being relevant in respect of automotive industry, − number and value of logistical investments, 294 − − − − − − − − László Józsa preservation of R&D workplaces, introduction of close-to-production R&D at Tier–3 suppliers, R&D expenses at Tier 3 suppliers, Pursuance and resuming of investment promoting, economy development and cluster-building programs with higher sources, Number of winning automotive industrial clusters, Acceleration of investment promoting programs, Reliefs for administration and taxation and reliefs provided by industrial parks, Investors’ opinion of the business environment. According to Havas (2010) Hungary takes the last-but-one position in the EU–27 ranking set up in accordance with the ratio of innovative undertakings, and is also lagging significantly behind the EU–27 average: with its ratio of 20.1% compared to the average 38.9%. However the ratio of innovative – i.e. introducing a new product or procedure – Hungarian automotive industrial undertakings is much over the processing industrial average, and the rate of sales revenues from new products is also higher in automotive industry. From among the types of innovation being typical to the Hungarian automotive industry we may mention product innovation; process innovation: just-in-time, TQM, lean manufacturing cells, production planning, heat treatment; organisation management innovation: set up of new functions (divisions) in the rural plants becoming more and more independent as well as at Hungarian affiliate companies receiving more rights in decision making; introduction of new financial and accounting methods (e.g. Suzuki suppliers); marketing innovation. But it is also important to mention that knowledge sharing networks: supplier programs (Suzuki, Opel, ZF), clusters appeared. Heat treatment shall be mentioned among the non-research and development activity based innovation; modernisation of the manufacturing equipment from maintenance costs (in the lack of sources granted for development projects, for the sake of a good achievement in the competition between the plants of the international parent company, for gaining new contracts (Havas, 2010). Presentation of the supplier companies’ performance – Findings of the exploratory research This sub-section is based upon the data of the primary research accomplished in the first quarter of 2011. One stage of the survey is composed of the in-depth interviews made with automotive industrial suppliers functioning in Central and Western Transdanubia. The information comprised in the in-depth interviews pertaining to company performance and the competition on the market is discussed below. The majority of the companies involved in the survey have no competitors on the domestic markets and they participate in international competition through their parent companies, where, as they declared, they play important roles. The following strengths can be underlined in the case of automotive suppliers based on the survey: Analysis and Development Strategies – Summarized Exploratory Research… − − − − − − − − − − − − − − − − − − − − − − 295 Professional/vocational knowledge, Social resources, System of relations, flexibility, possibility for small series production, provision of extra services, proactivity, conforming quality, geographical location (infrastructural background), wide product portfolio, wide market, stable base of employees, experience, specialisation, product development, innovation, success orientation, business environment, integrated corporate management system, family owned, reliability, market share. The interviewees mentioned the following factors as weaknesses: − problems attributable to the small size of companies (lack of capacity, fast increase, manufacturing large series products), − burdens, − bureaucracy, − statutes, − change of generations, − local lack of labour force, shortage of experts especially young specialists, − economic background is not predictable, the market is uncertain, − lack of foreign language command, − brain drain by other companies, − geographical location (closeness of the state border, drain of labour force), − insufficiently developed office culture (workers’ low discipline). Two major trends are observable as regards the customer relations. At companies with foreign parent companies the headquarters concludes contracts, salespersons are employed i.e. the company headquarters liaise with one another in the seller-costumer relationships. The significance of the other trend rests in the fact that customer relations are established and maintained with the assistance of the personal and internal system of 296 László Józsa relations built at the former workplaces, taking benefit from former references and good reputation. In the case of existing customer relations at management level trust, transparency, reliability, quality and consistence are inevitable. Among the weaknesses of automotive suppliers the secure raw material supply is the fundamental one to be mentioned. Unfavourable purchasing conditions, rising raw material prices, due to the recession reduced capacities, quality defects detected among the Hungarian suppliers and inflexibility may also be listed as reasons for weaknesses. The lack of experts is also a problem, whereas the generation of under–40 to 50years of age is missing in several professions and trades. “Soil-bound” character of Hungarian employees should also be mentioned as a weakness. Proper business culture, business norms, business strategies are missing, and in many cases the fundamental goal is still to gain the most profit in the possibly shortest time. The majority of the suppliers involved in the survey do not participate in any cooperation networks for manufacturing, sales or business. Regarding automotive industrial development the companies examined in this survey availed themselves of several technology and other development related tender facilities in the past two years. − ÚMFT (procurement of assets) − GOP (capacity expansion, procurement of assets, technology development, production management system, job creation, product development), − NKTH Nemzeti Technológiai Platform (National Technology Platform) (R&D co-operation with universities within the Integrated Automotive Industrial Product and Technology Development System (IJTTR) and the procurement of assets), − INNOREG (special precision-type face grinding and form grinding technology). − NYDOP (plant development, education) − Baross Gábor Program (product development, production of new tools, procurement of assets) − INNOCCSEKK (motor development, prototype production) − KDOP (enlargement of the production hall, technology development) The companies determined also development targets to be achieved by 2014. Fundamentally, they intend to stabilize their operation, and subsequently they wish to enhance their market shares – by way of portfolio extension (both in Europe and on the global markets). Extension is accompanied on the one hand by organisation development and staff increase, on the other hand by the education and development training provided to the existing blue collar and white collar staff. Some of the companies will accomplish these by means of their own, in-house training and coaching materials. As a result of the expansion instead of the rented premises or facilities they intend to have their own, independent premises. Once they have their own premises they target to expand it (production hall, office building). Besides increasing the production capacities they also intend to enhance effectiveness of the existing machinery, and they plan to Analysis and Development Strategies – Summarized Exploratory Research… 297 carry out technology developments especially for the purpose of quality product manufacturing. In relation to the development of supplier system the reduction of the shipping expenses is set as a target, to this end, steps are taken to establish the Hungarian supplier sphere. Their future strategies include on the one hand to reinforce relationships with the current customers (proactivity, common developments), on the other hand to extend the clientele in order to obviate dependence in the relationships. In terms of finance, the most essential is to sustain liquidity. The problems of the organisations are associated with the lack of professionally or vocationally qualified labour force, with the economic and legal environment, and with the size of the company. In the regions under review the highly qualified and experienced labour force is missing, in principal, the lack of resource in competent engineers with foreign language command causes problems. It is even more difficult to keep employees with competitive abilities. In the field of high labour costs minor companies cannot be competitive, and this results in high fluctuation. As regards qualified labour force the change of generations causes dilemmas, namely due to the fact that the career correction or the possibility of shifting between qualifications in the case of elderly labour force has yet to be solved on the Hungarian education market. The younger generation has no sufficient professional knowledge, foreign language command and professional experience. During the rapid growth following the first cycle of recession difficulties were faced with the provision of appropriate number of labour force and in many cases its unpredictable character also entailed problems. Not even after the rapid growth did the development of organisational structure take place, considering the fact that the structure supporting the decision making mechanism is still not in hand. One of the major problems in the economic environment is the fact that material and energy costs are growing, the profit is declining, there is a dependence on material suppliers, the exchange rate varies, and the capacity of the supplier network is still instable. Even troubles with financing emerge (due to delayed payment of customers); capital lacks and borrowing loans is also troublesome. Fast changing customer demands even amplify economic uncertainty. Many companies are inflexible due to its small size. In several cases, however, there is no way to extend the business. Results of the questionnaire survey This subsection is built upon the data collected in the course of the questionnaire survey performed in the framework of this research. Table 6 demonstrates the per-country distribution of automotive suppliers involved in the survey. 298 László Józsa TABLE 6 Per-county distribution of suppliers in Western Transdanubia and Central Hungary Frequency % Valid% Cumulative% Budapest Győr-Moson-Sopron County Komárom-Esztergom County Pest County Vas County Zala County 12 7 6 15 5 4 24.5 14.3 12.2 30.6 10.2 8.2 24.5 14.3 12.2 30.6 10.2 8.2 24.5 38.8 51.0 81.6 91.8 100.0 Total 49 100.0 100.0 Source: Own survey, 2011. From the Western Transdanubian and Central Hungary 49 automotive suppliers participated in the questionnaire survey. The sales revenues in 2010 were under 500 million HUF in the case of nearly one-third of the respondents. Over half of the undertakings involved declared that the activities performed as automotive suppliers dominate in respect of their sales revenues. In respect of product lines with the highest frequency the manufacturing of 2–5, and 6–10 product lines takes place, which suggests strong diversification of the portfolio. The following position is typical to most of the Hungarian automotive suppliers as regards pricing and market tendencies. In the past three years the major impetus for the undertakings was represented by market expansion, the growth of existing customers and the extension of the product range. Willingness for co-operation is unfortunately still to be considered very low. As for market position, over half of the respondents experienced slight improvement during the past three years. Stableness and the existing relations predominate when partnership relations are established. Conclusions, recommendations Several factors influence automotive industrial decision making. Customers’ requirements are determining as regards the style, reliability and output of the cars. Commercial, security and environmental regulations set incentives to encourage modernisation, technology improvement, and alterations in the fields of design and manufacturing. Both the competition between companies and company strategies give essential impetus to research, innovation and the development of manufacturing processes. In addition to consumer demands exerting constant pressure on car factories, national peculiarities and the definition of new market segments are also prominent. Their roles taken in the industrial segment is determined by how fast they are able to react to any such demands. One of the most essential factors is the demand for brand Analysis and Development Strategies – Summarized Exploratory Research… 299 new cars, which on the average increased by less than 1% during the past decade, and according to forecasts this tendency will continue, but its focus will be set in the world outside Europe. The most rapidly developing region is currently South America, with an average growth of 10%. Development of the energy prices is also an influencing factor, whereas it affects the consumers’ decisions, accordingly, the tendency – that low fuel consumption as a requirement towards a car overrules the comfort level and size of a car – was especially observable in the period between 2009 and 2011. Furthermore, clearly distinguished layers of consumers are also identifiable, for whom environment awareness is of crucial importance, and besides they possess the income ratio and purchasing potential to become interested in the purchasing of cars produced with the application of the latest, environment friendly technologies. Changes are also significant on supply side as well compared to the period preceding the recession. From among the great many economizing measures triggering cost reduction the factor essentially affecting the labour market shall be highlighted, according to which in many cases the companies prefer employing wage workers and workers with definite term contracts to their own employees or workers at the production lines. All in all it may be stated that Hungarian automotive industry is to be cope with global challenges. Table 9 below gives a summary of such challenges. Table 10 gives a summary of the trends in automotive industry. TABLE 9 Challenges in the automotive industry External factors − Legal background (environment, security/safety), − Material and energy price, − Exchange rate and interest rate, Customers − Stagnating demand, depressed prices, − Segmentation and polarization (low price vs. premium), − Declining loyalty, Competition − All the segments are reached fast, − Everyone is optimising, regrouping, − global – aggressive Asian companies, Industry − complex alliances, − consolidation, “ecosystem” (suppliers, sales persons). Source: BMI, 2010 and Havas, 2010, and own editing based on own studies, 2011. TABLE 10 Trends in the automotive industry Supplier’s side − − − − differentiated outsourcing outsourcing to cheap countries risk management transparency Demand side − − − − unbalanced growth fragmentation increasingly volatile importance of remanufacturing Source: BMI, 2010 and Havas, 2010, and own editing based on own studies, 2011. 300 László Józsa Limits of this Research It is essential to underline the following factors that represent the limits of this research: − This research is of revealing character. − Research regions rely on primary figures (Western Transdanubia and Central Hungary). − The survey was performed in the first half of 2011. − The method of this research does not enable generalisation, considering the fact that it is not supported by research results received from representative samples. Practical application of the results, management implications –Trends of future research work One of the possible future trends of research to be underlined might extend to the examination of sales figures relevant to the complete Hungarian automotive industry, based on which middle term and long term forecasts may be provided for the companies of this sector. Relevant to the manufacturers and suppliers’ R&D&I activities there were no figures with sufficient information-content available and accessible, thus this field is recommended to be studied. The research is worth to be extended in the future territorially and respondents should be involved in the survey from each region of Hungary and the international comparison is also possible. Furthermore in respect of the competitiveness of this industrial sector and Hungary it shall also be surveyed in which direction the manufacturers and suppliers perform research-development-innovation activities; and what position they take compared to other role players of the European and global markets. LIST OF CONTRIBUTORS Györgyi Barta, DSc, university professor, Széchenyi István University, bartagy@sze.hu scientific advisor, Hungarian Academy of Sciences Research Centre for Economic and Regional Studies Institute of Regional Studies, barta@rkk.hu Zoltán Csizmadia, PhD, associate professor, Széchenyi István University csizmadia@sze.hu research fellow, Hungarian Academy of Sciences Research Centre for Economic and Regional Studies Institute of Regional Studies, cszoltan@rkk.hu Tamás Dusek, PhD, associate professor, Széchenyi István University, dusekt@sze.hu Anita Füzi, PhD student, Széchenyi István University Doctoral School for Regional Science and Economics, anita.fuzi@sze.hu Szandra Gombos, PhD student, Széchenyi István University Doctoral School for Regional Science and Economics, gombossz@sze.hu László Józsa, CSc, university professor, Széchenyi István University, jozsal@sze.hu Katalin Kollár, project administrator, Audi Akademie Hungaria Kft., akademie.Kollar@audi.hu PhD student, Széchenyi István University Doctoral School for Regional Science and Economics, kollarkatalin86@gmail.com Mihály Lados, CSc, associate professor, Széchenyi István University, lados@sze.hu senior research fellow, head of department, Hungarian Academy of Sciences Research Centre for Economic and Regional Studies Institute of Regional Studies, ladosm@rkk.hu Imre Lengyel, DSc, university professor, University of Szeged, ilengyel@eco.u-szeged.hu Miklós Lukovics, PhD, associate professor, University of Szeged, miki@eco.u-szeged.hu Márta Nárai, PhD, associate professor, Széchenyi István University, naraim@sze.hu research fellow, Hungarian Academy of Sciences Research Centre for Economic and Regional Studies Institute of Regional Studies, naraim@rkk.hu János Rechnitzer, DSc, university professor, Széchenyi István University, rechnj@sze.hu scientific advisor, Hungarian Academy of Sciences Research Centre for Economic and Regional Studies Institute of Regional Studies, rechnj@rkk.hu Péter Savanya, PhD student, University of Szeged, savanya.peter@eco.u-szeged.hu Melinda Smahó, PhD, assistant professor, Széchenyi István University, smahom@sze.hu Tamás Tóth, PhD student, Széchenyi István University Doctoral School for Regional Science and Economics, tamas.toth@sze.hu Research supporting staff Károlyné Pálvölgyi, administrative assistant, Széchenyi István University, palvolgy@sze.hu Melinda Pató, executive-expert, Széchenyi István University, patom@sze.hu Eszter Szabados, executive-expert, Széchenyi István University, szabados@sze.hu

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