How do Perceived Benefits and Costs Predict Volunteers’ Satisfaction? Kirstin Hallmann & Anita Zehrer VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations Official journal of the International Society for Third-Sector Research ISSN 0957-8765 Voluntas DOI 10.1007/s11266-015-9579-x 1 23 Your article is protected by copyright and all rights are held exclusively by International Society for Third-Sector Research and The Johns Hopkins University. This e-offprint is for personal use only and shall not be selfarchived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”. 1 23 Author's personal copy Voluntas DOI 10.1007/s11266-015-9579-x ORIGINAL PAPER How do Perceived Benefits and Costs Predict Volunteers’ Satisfaction? Kirstin Hallmann1 • Anita Zehrer2  International Society for Third-Sector Research and The Johns Hopkins University 2015 Abstract The impact of volunteer tourism on participants has gained interest in tourism research with popular topics of study such as motivation, expectations, and values. However, only a few studies have examined outcomes of the experience such as satisfaction and most works were purely descriptive. The purpose of this research is to find out more about the drivers of satisfaction focusing on experienced benefits and costs with the volunteer experience. The paper reports a quantitative online survey distributed to volunteers (n = 290) via volunteer organizations operating on all continents. Regression analyses show that experienced benefits relating to the self and the career are positively and costs are negatively correlated with satisfaction. Résumé L’impact du tourisme bénévole sur les participants a suscité un intérêt pour la recherche sur le tourisme grâce à des thèmes populaires d’étude comme la motivation, les attentes et les valeurs. Toutefois, seules quelques études ont examiné les résultats de l’expérience, tels la satisfaction, et la plupart des travaux étaient purement descriptifs. Le but de cette recherche est d’en apprendre davantage sur les facteurs de satisfaction en s’intéressant principalement aux avantages ressentis et aux coûts de l’expérience du bénévolat. Le document présente une étude quantitative en ligne distribuée aux volontaires (n = 290) par l’intermédiaire d’organismes bénévoles présents sur tous les continents. Les analyses de régression montrent que les bénéfices ressentis liés à l’individu et à la carrière sont corrélés positivement à la satisfaction et les coûts négativement. & Kirstin Hallmann k.hallmann@dshs-koeln.de Anita Zehrer anita.zehrer@mci.edu 1 German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany 2 MCI Management Center Innsbruck, Weiherburggasse 8, 6020 Innsbruck, Austria 123 Author's personal copy Voluntas Zusammenfassung Die Auswirkungen des Voluntourismus auf die Teilnehmer sind von zunehmenden Interesse für die Tourismusforschung mit beliebten Studienthemen, wie Motivation, Erwartungen und Werte. Allerdings haben nur wenige Studien die Folgen der Erfahrung, wie Zufriedenheit, untersucht, und die meisten Arbeiten waren rein deskriptiv. Zweck dieser Studie ist es, mehr über die Zufriedenheitstreiber herauszufinden, wobei man sich auf den erlebten Nutzen und die Kosten im Zusammenhang mit der Erfahrung der Ehrenamtlichen konzentriert. Die Abhandlung berichtet über eine quantitative Online-Befragung, die über ehrenamtliche Organisationen auf allen Kontinenten an Ehrenamtliche (n = 290) verteilt wurde. Regressionsanalysen zeigen, dass der erlebte Nutzen mit Hinblick auf das Selbst und die Karriere in positiver Beziehung und die Kosten in negativer Beziehung zur Zufriedenheit standen. Resumen El impacto del turismo solidario sobre las participantes ha ganado interés en la investigación del turismo con temas populares de estudio como la motivación, las expectativas y los valores. Sin embargo, sólo unos pocos estudios han examinado los resultados de la experiencia, tales como la satisfacción, y la mayorı́a de los estudios fueron meramente descriptivos. El propósito de la presente investigación es averiguar más cosas sobre los impulsores de la satisfacción centrándose en los beneficios y costes experimentados en la experiencia del voluntario. El documento presenta una encuesta online cuantitativa distribuida a voluntarios (n = 290) a través de organizaciones de voluntarios que operaban en todos los continentes. Los análisis de regresión muestran que los beneficios experimentados relativos a uno mismo y a la carrera estaban correlacionados positivamente y los costes estaban correlacionados negativamente con la satisfacción. Keywords Volunteer tourism
Volunteering
Social exchange theory
Utility
Social projects Introduction The term ‘volunteer tourism’, which is often referred to as a ‘life-changingexperience’, applies to tourists who volunteer in an organized way to undertake holidays that might help society in terms of community-based projects or the environment in terms of ecological projects (Wearing 2001). Volunteer tourism is a broad and multi-dimensional concept (Andereck et al. 2012; Holmes and Smith 2012). The volunteer activity usually makes people feel empowered and is an altruistic attempt that can take place in varied locations. Social exchange theory, which is the theoretical basis of this research, argues that individuals enter into relationships with other individuals where they believe they can receive valued benefits; this theory can be used to provide a theoretical underpinning for studies on volunteers, since ‘‘as part of the volunteer tourism experience, interactions occur and the self is enlarged or expanded, challenged, renewed, or reinforced’’ (Wearing 2001). While much has been written on motivations of tourists and volunteers, little 123 Author's personal copy Voluntas research has been conducted concerning positive and negative impacts that experiences such as volunteering may have (e.g., McGehee and Andereck 2009; Doherty 2009; Tomazos and Butler 2012; Guttentag 2009). Although no clear typology of volunteer tourists exists, the authors distinguish among three forms of volunteer tourists: (a) Volunteers in social or ecological projects which often is referred to as a gap-year or bridge year (Jones 2004); (b) volunteers at sports events with public recognition of the contribution of volunteers to major sporting events is widely heralded (Kemp 2002); and (c) volunteers on organic farms often referred to as Willing Workers on Organic Farms (WWOOF). In addition, continuous and episodic volunteers can be distinguished (MacDuff 1995 cited after Bang and Chelladurai 2009) or collective and reflexive volunteers (Hustinx and Lammertyn 2004). The terms continuous or collective volunteer refer to those engaging over a longer period of time, usually rooted in a local community (Hustinx and Lammertyn 2004). In contrast, the terms episodic or reflexive volunteers describe volunteers who provide their time and service at particular incidents only. Volunteers in social or ecological projects or working on organic farms are thus rather classified as continuous or collective volunteers while those volunteering at sport events are considered as episodic or reflexive volunteers. Yet, volunteering in social or ecological projects or organic farms which represents the target group of this research can be also short-term. The impact of volunteer tourism on participants has recently gained strong interest and tourism researchers investigate upon volunteer’s motivation, expectations, and values (e.g., Alexander 2012; Andereck et al. 2012; Jarvis and Blank 2011; McGehee 2012; Wearing and McGehee 2013; Zahra and McGehee 2013; Tomazos and Butler 2012). Thereby, a clear profile of volunteer tourists (female, well-educated, young) emerged (e.g., McGehee 2002; Janoski and Wilson 1995). However, only a few studies have examined satisfaction of those. The general conclusion from earlier studies is that there is a positive association between people’s quality of life and engagement in volunteering (Cattan et al. 2011). The purpose of this research is to find out more about how the experienced benefits and costs of the volunteering activity are related to satisfaction with the entire volunteering activity. Thus, the following leading research questions shall be answered: (1) (2) (3) What are the drivers for satisfaction with a volunteering experience? Which types of experienced benefits and costs influence satisfaction? How do socio-demographic variables and resources (income, time, and education) impact on satisfaction? Following this outline, the paper undertakes a review of the relevant literature regarding: the concepts of (i) social exchange theory (ii) volunteer tourism, and (iii) drivers of the volunteering activity, and (iv) satisfaction. The research methodology, which is a quantitative approach, follows as well as the analysis of the experienced benefits and costs of the volunteering experience and its impacts on satisfaction. The paper then discusses the limitations of the study and future research possibilities and concludes with a summary of the major findings of the study and the contribution to theory. 123 Author's personal copy Voluntas Theoretical Framework and Literature Review Social exchange theory (Homans 1958; Thibault and Kelley 1959) argues that individuals enter into relationships with other individuals where they believe they can receive valued benefits yet incur few costs. This theory is often used to provide a theoretical underpinning for studies on volunteering (e.g., Doherty 2009; Bang et al. 2009; Weerts and Ronca 2007). These relationships can be social or economic and the transactions can be also of social or economic nature (Cropanzano and Mitchell 2005). Volunteering is seen as an exchange relationship, where individuals offer their time, skills, and energy to assist with an event, and experience various benefits, as well as costs, in return. In general, relationships can be distinguished from transactions and both entail a social and an economic exchange (cf. Cropanzano and Mitchell 2005). Following this line of thought, volunteering is characterized as a social relationship including interpersonal attachment with a social transaction (Granger et al. 2014). As such, it may be assumed that volunteers will be more likely to engage in future volunteering behavior to the extent that they have experienced positive outcomes as a result of that behavior in the past (e.g., Doherty 2009; Tomazos and Butler 2012); similarly, they will be less likely to volunteer again if they have experienced negative outcomes. Thus, utility, a measure of satisfaction and subjective well-being that a person derives from consumption (Stutzer and Frey 2010), shall be maximized. Social exchange theory is often employed to explain organizational behavior (Cropanzano and Mitchell 2005) and reciprocity as interdependent exchange is at the core of the theory. Following Meeker (1971), Eisenberger et al. (1986), Cropanzano and Mitchell (2005) and Molm (2003) interpersonal exchanges can be treated as individual decisions. In the past, researchers have assumed that these decisions are based on reciprocity, rationality, altruism, group gain, status consistency, and competition (Meeker 1971; Eisenberger et al. 1986). Drawing from social exchange theory, this paper analyzes the perceived costs and benefits, since benefits are assumed to outweigh the costs, thus generate utility. Following McGehee and Andereck (2009), who directly applied the theory to volunteer tourism, perceived benefits and costs serve as a predictor for satisfaction in this research. In addition, the influence of socio-demographic variables and resources (income, time, and education) on satisfaction will be tested. Volunteer Tourism Volunteering is an elusive concept to define as it embraces different kinds of activity and participation at all levels and aspects of society (Burgham and Downward 2005; Callanan and Thomas 2005) which is pursued during leisure time and considered as self-interested activity (Stebbins 1996). Basically, a volunteering activity ,…is uncoerced help offered either formally or informally with no or, at most, token pay done for the benefit of both other people and the volunteer’’ (Stebbins 2004). The concept of volunteering takes on different meanings in different settings (Handy et al. 2000) due to varied political, historical, cultural, 123 Author's personal copy Voluntas religious, and social frameworks (Du Boulay 1996; Holmes et al. 2010). Following Stebbins’ (1996) serious leisure perspective, volunteering can be characterized as a systematic pursuit to find a career in the acquisition of special skills and knowledge. Volunteers are also an important element of the tourism workforce (LockstoneBinney et al. 2010). Volunteer tourism grew substantially since the 1970s to the past several years and received increased attention as a research subject, especially as it was often aligned with sustainable and alternative tourism (Andereck et al. 2012; Guttentag 2009) and is a broad and debatable concept (Lyons 2003). The term applies to ‘‘…those tourists who, for various reasons, volunteer in an organized way to undertake holidays that might involve aiding or alleviating the material poverty of some groups in society, the restoration of certain environments or research into aspects of society or environment’’(Wearing 2001). McGehee and Santos (2005) define volunteer tourism as ‘‘utilizing discretionary time and income to travel out of the sphere of regular activity to assist others in need’’ (p. 760). Although, there is no universally agreed-upon definition, all definitions of volunteer tourism argue for the inclusion of components of both tourism and volunteering. Research that examines volunteers in the tourism context has primarily focused on those who travel to provide international aid (Fairley et al. 2007; Wearing 2001). The volunteer tourists have been the focus of research mainly through establishing their profiles, motivations, behaviors, and experiences; their interactions with host communities; their environmental and social attitudes and values; and aspects of self and cultural identity (Holmes and Smith 2012). Generally, it is agreed that the volunteer tourist seeks a different experience from the mass tourist. He/She much more focuses on interpersonal and personal factors, including giving back to the host community, participating in community development, increased awareness of the host, self-development, altruism, cultural understanding, cultural/historical restoration, medical assistance, educational support, ecological conservation, and avoiding irreversible environmental changes (Andereck et al. 2012; Brown and Morrison 2003; Callanan and Thomas 2005; McIntosh and Zahra 2007; Wearing 2001; Jackson and Adarlo 2014). These prevalent motives represent benefits the volunteers might want to gain from the volunteering activity. Drivers of the Volunteering Activity In general, decisions relating to consumer behavior (like e.g., the decision to take up a volunteering activity and processes and additional decisions following that initial decision) are determined by (1) socio-demographics such as age, gender, or family situation, (2) economic indicators like income, time, or education as human capital, and (3) psychological factors like motivations (e.g., Blackwell et al. 2001; Pizam and Mansfeld 1999). The relationship of socio-demographic factors on charitable behavior in the form of giving time or money has been shown previously. For age mixed findings were reported: on the one hand, age is positively associated with volunteering in sports (Burgham and Downward 2005); on the other hand, there are also findings reporting a negative association with sport volunteering (Taylor et al. 123 Author's personal copy Voluntas 2012). A study of a religious event revealed that prior to the event, significant age differences in terms of expected value (as benefits) were obtained, but after the event there were no significant differences (Fayos Gardó et al. 2013). In a tourism context, for long-term volunteer projects, people tend to be younger (Wearing 2001; Grimm and Needham 2012) supporting the findings of Taylor et al., (2012). Women seem to volunteer more than men (Einolf 2011; McGehee 2002) and higher education is positively correlated with volunteering (Janoski and Wilson 1995) or the majority of respondents have high educational attainments (McGehee 2002). McGehee’s (2002) sample consists mostly of people being single. Considering resources, time and income of individuals are highly related (Becker 1965) through the allocation of time to work. This in turn implies that the time devoted to work cannot be used for leisure. Considering long-term volunteers, the dedicated duration for the stay might be therefore of interest to investigate. Stemming on economics, it can be assumed that individuals with a higher educational level have acquired a higher consumption capital (Stigler and Becker 1977). Consumption skills are important to travel and to volunteer and they can imply physical abilities and mental abilities. Well-educated people might be positively aware of the positive effects that volunteering might create. Following an argumentation from sport and transferred to volunteering (Wicker et al. 2013), this engagement is considered as a consumption good that provides utility during the consumption process, but can also be seen as an investment good. Psychological factors include the willingness to perform processes like thinking, feeling, learning, and acting. Motives are a hypothetic construct to explain the inner drive of an individual, i.e., the reasons for his behavior (Schiffman and Kanuk 2010). The construct attempts to answer the ‘why’ of a certain action or activity. In order to study the motivations of volunteers, a number of frameworks exist. The starting point was Crompton’s (1979) work on push and pull factors as to why people travel. These factors refer to the determinants influencing the traveler’s decision on where to go (Kim et al. 2003) elaborating on two steps: first, push factors induce people to travel; second, pull factors influence the decision about which destination (Kay 2003). Crompton and McKay (Crompton and Mc Kay 1997) modified the push–pull model by integrating Iso-Ahola’s (1982) ‘escape-seeking dichotomy’. They argue it was possible to interpret the pull forces in terms of intrinsic benefits. The different kinds of volunteers though make it somewhat hard to capture general motivations of volunteers (Stebbins and Graham 2004). The studies by Söderman and Snead (2008) and Grimm and Needham (2012) show that there are various motivators for volunteer tourists, such as self-evaluation, knowing limits better, self-confidence, independence, tolerance about different cultures, team work, reduction of selfishness, calmness and balance, learning new skills, meeting new friends, meeting people for future career, and learning new language. These have been often distinguished in various dimensions as for instance self and altruism (Grimm and Needham 2012), personal, interpersonal, and other (Chen and Chen 2011), values, enhancement, understanding, protective, social, and career (Clary et al. 1998), nostalgia, camaraderie and friendship, subcultural connection, and sharing and recognition of expertise (Fairley et al. 2007), or 123 Author's personal copy Voluntas organization, personal development, assignment, community, and celebrities in a sporting context (Downward and Ralston 2006). These can be considered as perceived benefits of the volunteering activity. Sargeant et al. (2006) even argue that these benefits refer to different levels of utility, namely, demonstrable (recognition), emotional (change in emotions through an act of helping) and familial (demonstrate affinity with family and/or friends) utility. Yet, de-motivators in the form of costs might incur as several authors point out (Doherty 2009; McGehee and Andereck 2009). These relate to perceived negative impacts to the host community and the usefulness of the projects (McGehee and Andereck 2009; Guttentag 2009), but could also relate to direct expenses associated with the project (Stebbins 2007) or stress (Wilson and Musick 1999). This approach is in line with social exchange theory, which also postulates that certain activities are either rewarding or costly resulting from a social interaction between at least two persons. Satisfaction Satisfaction with volunteer work is essential for the tourist for a continuing commitment to volunteer work (Clary et al. 1998). One of the most often cited definitions of satisfaction is that of Rust and Oliver (1994) who state that satisfaction reflects the degree to which one believes that an experience evokes positive feelings. Thus, satisfaction is an overall affective response on positive or negative experiences (Oliver 1981). Although a customer might be satisfied, he/she might purchase elsewhere (Jones and Sasser 1995). Thus, satisfaction measures were increasingly backed up with measuring the perceived value and past research has measured consumer satisfaction in conjunction with the measurement of perceived value, respectively experiences (Oh 2000; Woodruff 1997). Perceived value can be defined as ‘‘the consumer’s overall assessment of the utility of a product based on perceptions of what is received and what is given’’ (Zeithaml 1988) and was first conceptualized by Zeithaml (1988). She suggests that perceived quality leads to perceived value and benefits, which results in purchase intentions. Baker (1990) examines a variation of the Zeithaml (1988) model and indicates that the physical environment (i.e., the retail store) has an impact on consumers’ perceptions of quality, price, and value. Zeithaml’s model was further confirmed by Dodds (1996) and further developed by Jayanti and Ghosh (1996). Since then, many authors have researched perceived value as an indicator of repurchase behavior suggesting that consumers are more likely to repurchase if they perceive their experience as having good value and benefit (Cronin et al. 2000; Petrick 2004a, 2004b; Wakefield and Barnes 1996). McGehee and Andereck (2009) show that perceived personal benefits are positively correlated with additional volunteer tourism and argue that this is congruent with social exchange theory. In case volunteering results in personal benefits and value and the experience of volunteering engagement produces positive impacts, it can likely increase satisfaction as well as personal well-being over time (Binder and Freytag 2013). 123 Author's personal copy Voluntas Methodology To answer the research questions, the authors chose a quantitative paradigm and designed a survey using an online questionnaire. Measures The questionnaire included questions relating to (1) demographic indicators such as gender, age, and marital status, (2) economic indicators like human capital, income and time, and (3) psychological indicators such as perceived costs and benefits as outlined in the literature review. Table 1 presents an overview about the measures relating to benefits and costs and their origins. Moreover, the respondents were asked to provide information relating to their satisfaction with the volunteer experience (measured on a three-point scale), as well as on the type of voluntary engagement (social project, ecological project, organic farm, or sport event). A pre-test was conducted with n = 5 respondents who were engaged as volunteers in the past. After the pre-test was conducted, wording for some questions was slightly modified. An overview of the operationalisation of the variables is provided in Table 2. Sampling and Data Collection Data collection took place in April 2011. The link to the online survey was distributed to 51 volunteer organizations operating on all continents (e.g., Global Volunteer Network, Projects Abroad, World Unite, Real Gap, WWOOF Organizations worldwide). These organizations used different means to promote the survey such as Facebook groups, newsletters, blogs, twitter, and simply forwarding the Table 1 Measures from literature Variable Reference Cost project Guttentag (2009) Costs expenses Stebbins (2007) Costs locals Guttentag (2009), McGehee and Andereck (2009), Wearing (2001) Costs stress Wilson and Musick (1999) Benefit 1—self-evaluation Grimm and Needham (2012), Downward and Ralston in a sense of personal development (2006) Benefit 2—limits Wearing (2001) Benefit 3—self-confidence McGehee (2002), Wearing (2001) Benefit 4—independence Clary et al. (1998) Benefit 5—cultures Grimm and Needham (2012), Wearing (2001) Benefit 6—teamwork Peterson (2004), Perkins (1989) Benefit 7—future career Clary et al. (1998), Grimm and Needham (2012), Wearing (2001) Benefit 8—friends Bang et al. (2009) in a sense of interpersonal contacts, Clary et al. (1998); Wearing (2001) Benefit 9—contacts Bang et al. (2009), Clary et al. (1998) 123 Author's personal copy Voluntas Table 2 Overview about the variables and their operationalisation Variable Description Scale Gender 0 = male, 1 = female Dummy Age Measured in categories (1 = under 20 years, 2 = 20–29 years, 3 = 30 and older) Ordinal Single Marital status (0 = else, 1 = single) Dummy Education Level of education (1 = A-levels and higher) Dummy Income Measured in categories for monthly net income (1 = up to 500€, 2 = 500–1000, 3 = 1001–1500, 4 = 1501–2000, 4 = 2001–2500, 5 = 2501–3000, 6 = 3001–3500, 7 = more than 3500), yet transferred into a dummy variable (0 = else, 1 = up to 500€) due to the too few frequencies in the categories Ordinal/ Dummy Duration 1 Duration of volunteer experience (1 = up to 1 month) Dummy Duration 2 Duration of volunteer experience (1 = 2–6 months) Dummy Duration 3 Duration of volunteer experience (1 = more than 6 months) Dummy Cost project After the journey, I was more skeptical about the projects, whether they are reasonable than before (0 = else, 1 = yes). Dummy Costs prices After the journey, I thought the costs for the journey/the project were too high (0 = else, 1 = yes) Dummy Costs locals After the journey, I was less/not sure whether the impact of the locals and their culture would be positive (than before; 0 = else, 1 = yes) Dummy Costs stress It could have been less stress during the stay and while working (0 = else, 1 = yes) Dummy Benefit 1 I can better evaluate myself Ordinal Benefit 2 I know my limits better Ordinal Benefit 3 I am more self-confident Ordinal Benefit 4 I am more independent Ordinal Benefit 5 I am more tolerant about different cultures Ordinal Benefit 6 I have learned to work in a team Ordinal Benefit 7 I have learned new skills and knowledge for my future career Ordinal Benefit 8 I have met new friends Ordinal Benefit 9 I have met people that could be important for my career Ordinal Satisfaction I am glad that I made the decision to do a volunteer journey Dummy Social Having served as a volunteer in a social project (1 = yes) Dummy Ecological Having served as a volunteer in an ecological project (1 = yes) Dummy Organic Farm Having served as a volunteer on an Organic Farm (1 = yes) Dummy If not otherwise indicated, ordinal scales were rated from 1 = disagree strongly to 4 = agree strongly message to all members. Since so many media were used, the number of recipients could not be determined for all organizations and thus the actual population reached is unknown. Hence, a non-random sampling technique, namely snowball sampling, was applied. A requirement to take part in the survey was that each respondent must have volunteered at least once so that post-evaluations of the volunteering experience were possible. The online survey was opened by 545 persons, yet not all of them finished the survey and the final sample size amounted to n = 290. 123 Author's personal copy Voluntas Table 3 Summary statistics Variable Mean Gender .72 Standard deviation .45 Kurtosis -1.09 Skewness -.96 Age Under 20 years .18 .38 .82 1.68 20–29 years .60 .49 -1.83 -.43 30 years and older Single .19 .40 .44 1.56 .77 .42 -.29 -1.31 -.67 Education .66 .48 -1.57 Income .48 .50 -2.01 .09 Duration 1 .35 .48 -1.63 .62 Duration 2 .43 .50 -1.93 .30 Duration 3 .20 .40 .28 1.51 Cost project .12 .32 3.65 2.37 Costs prices .07 .26 9.30 3.35 Costs locals .05 .23 13.75 3.96 Costs stress .17 .38 1.03 1.74 Benefit 1 3.19 .77 .84 -.93 Benefit 2 3.12 .77 .80 -.85 Benefit 3 3.29 .78 1.06 -1.09 Benefit 4 3.36 .83 1.26 -1.33 Benefit 5 3.17 .88 .10 -.90 Benefit 6 2.87 .91 -.55 -.47 Benefit 7 2.77 1.05 -.99 -.42 Benefit 8 3.41 .79 1.54 -1.37 Benefit 9 2.27 1.05 -1.07 .35 .74 .44 -.85 -1.07 Satisfaction Social .11 .31 4.73 2.59 Ecological .05 .23 13.75 3.96 Organic Farm .76 .43 -.46 -1.24 Participant Characteristics The respondent profile was mostly female (71.5 %), in their twenties (60.3 %), having a good educational background (65.6 % at least A-levels), and being single (77.3 %). Most respondents were between 2 and 6 months engaged as volunteers (42.7 %) and earned more than 500€ per month (52 %). The majority of respondents was engaged on an organic farm (76.3 %), followed by social (10.5 %) and ecological (5.4 %) projects and satisfied with their experience (73.4 %). Considering the perceived costs, a minority felt negative regarding some areas such as costs project (11.9 %), costs prices (7.1 %), costs locals (5.4 %) and costs stress (17.3 %). The benefits ranked on a four point scale had mean values from 2.27 to 3.42 on a four-point scale. These results are displayed in Table 3. 123 Author's personal copy Voluntas Data Analysis Data analysis included first checking the data for content validity and outliers. Several new variables were computed. For instance, relating to the type of voluntary engagement multiple categories were of choice for the respondents. These were recoded into dummy variables for each type of voluntary engagement. Only two respondents indicated having been engaged at sport events and thus, they were not considered as a category on their own and excluded from all subsequent analyses. Thereafter, descriptive analyses were carried out. Mean values, standard deviations, kurtosis and skewness for each variable were estimated and they are displayed in Table 3. Some of the variables suggested skewness and kurtosis, yet since the sample is bigger than n = 200, these issues tend to disappear (Waternaux 1976 cited after Tabachnick and Fidell 2007). Therefore, the variables were not transformed. Exploratory factor analysis followed to reduce the data relating to perceived benefits. Following the scree test and the Kaiser criterion, a two factor solution was suggested based on principal component analysis using varimax rotation. The communalities of two variables, namely Benefit 5 and Benefit 6, were smaller than .5 and these variables were therefore excluded. In the final solution, seven variables were used and their factor loadings were higher than .5 and could therefore be considered significant (Hair et al. 2006). Logistic regression analysis was employed to test the underlying influence of socio-demographics, economic, and psychological factors on satisfaction simultaneously. In all models, the demographic, economic, and psychological factors served as independent variables. An a-level of .1 was used for all statistical tests. The independent variables were checked for multicollinearity using variance inflation factors (VIF) and bivariate correlations. All VIFs were smaller than 2 (below the suggested criterion of 10) and all correlation coefficients below .5, except for the duration variables up to 1 month and 2–6 months which had a correlation coefficient of .6 which is still below the suggested threshold of .7 (Hair et al. 2006; Tabachnick and Fidell 2007). Thus, there should be no problem of multicollinearity. In addition, correlations between the independent variables and the residuals were computed. For satisfaction none of these correlations was significant. Further, no correlation coefficient was higher than .1 for satisfaction. Thus, as there are no correlations between the independent variables and the residuals, there should not be an endogeneity problem (Wooldridge 2002). Table 4 displays these correlations. To control for heteroscedasticity, a regression model with robust standard errors was estimated (MacKinnon and White 1985; White 1980). Results The results of the explorative factor analysis are summarized in Table 5. The analysis reveals a two-factor solution. The first factor consists of the variables Benefit 1 (b = .809), Benefit 2 (b = .804), Benefit 3 (b = .814), and Benefit 4 (b = .802), and is therefore labeled Benefits self. The second factor entails the variables Benefit 7 (b = .718), Benefit 8 (b = .711), and Benefit 9 (b = .851), and 123 123 Table 4 Results of the correlation analyses Variable Satisfaction Gender Age 1 Age 2 Age 3 Single Education Income Duration 1 Duration 2 Satisfaction Gender .057 Age: under 20 years .060 .061 Age: 20–29 years .095 -.025 -.577*** -.115* -.034 -.229*** -.082 .148* .189*** .204*** Age: 30 years and older .152** Education .005 .081 -.221*** Income -.057 .033 .136* Duration 1 -.056 .074 .135* Duration 2 .052 -.022 Duration 3 .069 Cost project -.604*** .124* -.288*** .046 .035 -.245*** .146* -.054 -.020 .061 -.051 .004 -.101 .112 -.006 -.055 .074 -.003 -.637*** -.061 -.013 -.010 .056 .089 .039 .048 -.369*** -.113 .070 .019 -.024 .033 -.051 .022 .153** -.073 .086 Costs prices .017 -.001 -.027 .090 -.069 -.007 -.023 .131* .099 -.026 Costs locals -.026 .086 .005 .102 -.117 -.013 -.016 .130* .011 .035 Costs stress -.112 .010 .020 -.087 -.052 -.048 .029 -117 .118* -.432*** -.018 .076 Benefits self .456*** .013 .052 -.021 -.013 .072 -.065 -.095 -.184** .083 Benefits career .302*** -.060 -.002 -.030 .044 -.033 -.047 -.094 -.168** .036 Social .130* .070 .012 .052 -.056 .054 .107 -.018 -.045 .039 Ecological .076 -.060 .005 .011 -.041 -.013 -.080 .011 -.051 -.025 -.100 -.041 -.050 .020 .112 -.017 .051 .007 .078 .079 .000 .030 -.098 .092 .000 .000 .000 .000 .000 Organic Farm Residual Author's personal copy Single Voluntas Variable Duration 3 Costs project Costs prices Costs locals Costs stress Benefits self Benefits career Social Ecological Organic farm Voluntas Table 4 continued Satisfaction Gender Age: under 20 years Age: 20–29 years Age: 30 years and older Author's personal copy Single Education Income Duration 1 Duration 2 Duration 3 Cost project .000 Costs prices -.073 .184** Costs locals -.045 .236*** .167** Costs stress -.049 .165** .083 .009 Benefits self .135* -.052 .000 .008 -.037 Benefits career .166** -.053 -.054 -.053 -.026 Social .022 .148* Ecological .067 .051 Organic Farm 123 Residual -.100 .000 * p \ .05; ** p \ .01; *** p \ .001 -.190*** .000 .120* -.008 -.155** .000 .211*** .009 -.218*** .000 .499*** .019 .082 .016 -.030 .013 .117 .002 -.043 -.094 .000 .000 .000 -.082 -.614*** .000 -.429*** .000 .047 Author's personal copy Voluntas Table 5 Results of the exploratory factor analysis Variable Self Benefit 1 (better evaluate myself) .81 Benefit 2 (know my limits better) .80 Benefit 3 (more self-confident) .81 Benefit 4 (more independent) .80 Career Benefit 7 (skills career) .72 Benefit 8 (new friends) .71 Benefit 9 (people important for career) Eigenvalue Variance explained in % (66.44) KMO Bartlett’s Test for sphericity (df) .85 3.48 1.17 49.76 16.68 .81 774.32 (21)*** Principal components analysis with varimax rotation. * p \ .05; ** p \ .01; *** p \ .001 is named Benefits career. The eigenvalues of both factors are greater than 1.0 and the overall variance explained amounts to 66.44 %. Bartlett’s Test for sphericity exposes a significant v2 of 774.319 (see Table 5). Prior to estimating the final models, predictive validity was examined for both models since fit validity is not sufficient (Armstrong 2012; Gigerenzer and Brighton 2009). Two subgroups of the overall sample were randomly chosen based on a random number assigned to each case and sub-dived into two groups. The models were estimated for each sub-sample, and the scores for the second model were predicted based on the first model and the other way around (Osborne 2000; Woodside 2013). The results suggest that the model is robust over populations (see Table 6) since correlations between the predicted scores and the observed scores of the dependent variable are higher than .3 and significant at the p B .001 level and shrinkage (difference between original R2 and squared correlation; Osborne, 2000) for both models was small (\5 %). Therefore, a model using the entire sample was estimated. The estimated model is statistically significant implying that the sociodemographic and economic variables as well as perceived costs and benefits explain satisfaction. Pseudo R2 amounts to 26.21 %. Inspecting the marginal effects, the perceived costs project leads to a decrease of 13 percentage points in the probability of being satisfied. In other words, those who perceive costs project to be an issue are less likely to be satisfied with the volunteer experience. Yet, benefits self (ME = .23) and benefits career (ME = .09) and being involved in a social project (ME = .14) increase the probability of being satisfied (see Table 7). Discussion and Conclusion The depicted profile of volunteer tourists (below the age of 35 and mainly females, well-educated) is congruent with previously established characteristics of volunteer tourists (Grimm and Needham 2012; McGehee 2002; Jackson and Adarlo 2014). 123 Author's personal copy Voluntas Table 6 Results of the logistic regression analyses using sub-samples to asses predictive validity with the dependent variable satisfaction (displayed are the coefficients) Variable Gender Satisfaction Sub-sample 1 Sub-sample 2 .160 1.134? Under 20 years REF REF 20–29 years .229 .265 30 years and older -.397 -.879 Single .627 .204 Education -.875 .765 Income .318 -1.003? Duration 1 -.353 .611 Duration 2 -.262 .309 Duration 3 REF REF Cost project -.546 -.734 Costs prices -.763 .733 Costs locals -2.001 -.641 Costs stress -.412 -.917 Benefits self 1.740*** 1.547*** Benefits career -.021 1.938** Social .968 x Ecological .931 x Organic Farm REF REF Constant -4.260** -9.571*** Wald v2 31.77 33.82 P .011 .002 -2LL -65.010 -41.895 Pseudo R2 27.25 37.88 N 146 124 Cross validity check# R2 = 10.17 % r = .334***; r2 = .1115; Shrinkage 0.98 % R2: 14.23 % r = .429***; r2 = .1840; Shrinkage 4.17 % p values refer to z-statistics; ? p \ .1; * p \ .05; ** p \ .01; *** p \ .001; # The first sample model was used to predict the scores of the second model and vice versa; x = The value 0 predicts success perfectly and thus the variable was dropped Reducing the different perceived benefit items into two factors was fruitful, since two distinct dimensions emerged. The first dimension, labeled ‘self’ is among other dimensions often identified in other research, though sometimes labeled differently (e.g., Grimm and Needham 2012; Chen and Chen 2011; Downward and Ralston 2006). This applies also to the second dimension, ‘career’ that emerged (e.g., Clary et al. 1998). Thus, the perceived benefits are congruent with previous research on volunteer motivation. Pertaining to the first research question, which aimed to reveal which drivers influence satisfaction, the first model was statistically significant implying that the 123 Author's personal copy Voluntas Table 7 Results of the overall logistic regression analysis with the dependent variable satisfaction (displayed are the coefficients and in parentheses the marginal effects) Variable Model 1: Satisfaction Gender .57 (.09) Under 20 years REF 20–29 years .02 (.00) 30 years and older -.77 (-.13) Single .43 (.07) Education -.16 (-.02) Income -.31 (-.05) Duration 1 .11 (.02) Duration 2 .15 (.02) Duration 3 REF Cost project -.74 (-.13)? Costs prices .28 (.04) Costs locals -.51 (-.09) Costs stress -.59 (-10) Benefits self 1.50 (.23)*** Benefits career .57 (.09)* Social 1.27 (.14)? Ecological .90 (.10) Organic Farm REF Constant -5.40*** Wald v2: 57.70 P .000*** -2LL -120.31 2 Pseudo R p-values refer to z-statistics; 26.21 % ? p \ .1; * p \ .05; ** p \ .01; *** p \ .001 socio-demographic and economic variables as well as perceived costs and benefits serve as significant predictors for satisfaction. The positive impact of perceived benefits is not surprising since this corresponds with maximizing utility and that the benefits shall outweigh the costs underpinning social exchange theory which corresponds to the rationality principle of decision-making (e.g., Meeker 1971). Perceived costs project represent a negative outcome of the volunteer experience and this influences satisfaction negatively. Guttentag (2009) notes that these negative outcomes can happen if the projects devote more time on attracting volunteers than on helping the community. Another issue in this regard could be reciprocal communication between the project and the local community. If communication takes place, these perceived costs might not occur. It can be assumed that the individuals who decided to engage in volunteer tourism are already assuming that they will derive utility from the activity (since they would otherwise not do it) and that the benefits will outweigh the costs. 123 Author's personal copy Voluntas Regarding the second research question, the authors revealed that benefits self, benefits career and being involved in a social project increase the probability of being satisfied. The positive relationship of being involved in a social project could relate to the nature of those projects: Volunteers are more likely to deal with and help other people directly than volunteering in ecological projects or organic farms. This could lead to a feeling that in particular altruistic motives are satisfied. Altruism being a stronger motive for people working in social projects might lead to different perceptions of being rewarded (e.g., a smile of one of the people the volunteer is taking care of might already lead to satisfaction). Since this type of perceived benefits was not included in the analysis, this notion can only be assumed. The answer to the third research question relating to the impact of sociodemographics and resources on satisfaction, however, is that none of the sociodemographic variable contributed significantly to the model. That means, that age and gender are not relevant in the research context with regard to volunteering satisfaction which is congruent to other findings where no age and gender differences were detected in the post-event assessment of volunteers (Fayos Gardó et al. 2013). Summing up, the basic assumptions of social exchange theory are confirmed in the context of volunteer tourists. Following social exchange theory, which is predominantly used to understand workplace behavior (Cropanzano and Mitchell 2005), volunteering can be seen as an exchange relationship, where individuals offer their time and skills to assist with an event, and experience various benefits, as well as costs, in return. Hence, volunteers engage in relationships with other individuals especially when they believe they can receive valued benefits yet incur few costs (Bang et al. 2009; Doherty 2009; Homans 1958; Thibault and Kelley 1959). In doing so, they reach a level of satisfaction which might result in positive subjective well-being and overall utility (Binder and Freytag 2013). However, Stutzer and Frey (2010) note, that people overestimate the influence of particular events on wellbeing in terms of intensity and duration. Thus, future research is needed in this context. Furthermore, we also need to acknowledge that social exchange theory has its critics and usually is being criticized at two levels. The first one would be that the theory pertains to social life as exchange saying that all social interaction is exchange (Molm et al. 2003); the second would be that the theory reduces exchange solely to an economic transaction or psychological process (Cook 2000). Thus one cannot for instance neglect the lack of issues related to the cultural or cross-cultural context that regulate social exchange. Again, further research is needed to elaborate more on the usefulness of social exchange theory in a volunteer context. This study goes along with some limitations. The sample size was rather small and convenience sampling was employed. In addition, the majority of respondents volunteered at organic farms which might be considered as a bias. Yet, the sociodemographic characteristics of the sample are congruent to those of previous research, as indicated earlier so that this issue should not represent a problem. To summarize the theoretical contribution, the findings are underpinned by the rationale of social exchange theory; thus social exchange theory can be applied to the context of volunteers and their volunteering activity and engagement. Besides, 123 Author's personal copy Voluntas this study contributed to the utility concept and identified benefits which can be classified into three types of utility—utility attributed to family, demonstrable utility, and emotional utility (Sargeant et al. 2006). Hence, the two derived factors, benefits self and benefits career, could be classified as focusing on emotional utility (benefits self) and demonstrable utility (benefits career). Thus, familial utility seems not to play an important role in volunteer tourism. This could be different for volunteering activities which do not include travel. Implications for practice center on a better understanding of the antecedents and determinants of satisfaction and are beneficial to understand the decision-making behaviors of their current and prospective clientele. By understanding the underlying dimensions (causes) of satisfaction which might lead to a re-engaging in a similar volunteer experience, managers, tourism marketers, potential service providers such as travel agencies and non-profit organizations should be able to cater experiences to their various markets in a way to maximize future reengagement behaviors. Thus, the challenge for future providers of volunteer vacation is to ensure that the volunteer tourist expectations are being met. Volunteer organizations might also want to explore social media tools, such as facebook or blogs, to recruit future volunteers and should be generally aware of how internet sites represent them online. It is good news for managers recruiting volunteers that there is no influence of any socio-demographic characteristic on satisfaction since they do not need to limit their target groups in this regard. For social projects, the altruistic motive might be highlighted when recruiting volunteers since it can be assumed that it is in particular important for those volunteers as outlined. This could be done with easy means as for instance portraying a child smiling when talking or looking at a volunteer. In sum, the study shows a number of actionable strategies that volunteer organizations, managers and NGOs could employ to further motivate the purchase of volunteer tourism packages. Implications for future research could be testing the model in other contexts, such as sports and could include distance from home and political factors in the receiving country and estimate a multi-level model. 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