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The Journal of Social Psychology

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The quality of volunteers’ motives: Integratingthe functional approach and self-determinationtheory

Stefan Tomas Güntert, Isabel Theresia Strubel, Elisabeth Kals & TheoWehner

To cite this article: Stefan Tomas Güntert, Isabel Theresia Strubel, Elisabeth Kals & TheoWehner (2016) The quality of volunteers’ motives: Integrating the functional approachand self-determination theory, The Journal of Social Psychology, 156:3, 310-327, DOI:10.1080/00224545.2015.1135864

To link to this article: http://dx.doi.org/10.1080/00224545.2015.1135864

Published online: 11 Apr 2016.

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The quality of volunteers’ motives: Integrating the functionalapproach and self-determination theoryStefan Tomas Günterta, Isabel Theresia Strubelb, Elisabeth Kalsb, and Theo Wehnerc

aUniversity of Applied Sciences and Arts Northwestern Switzerland; bCatholic University of Eichstätt-Ingolstadt;cETH Zurich

ABSTRACTVolunteers’ motives have been differentially linked to various aspects of suc-cessful volunteering. Using self-determination theory, we propose that volun-teer functions are systematically related to the experience of self-determinedversus controlledmotivation. This “quality of motivation,” in turn, explains whymotives are differentially associated with satisfaction. We conducted twostudies: Study 1 (N1 = 824) addressed motives, quality of motivation, andsatisfaction; Study 2 (N2 = 323) additionally examined function-specific benefitsand the extent to which they match volunteers’ motives. Overall, our hypoth-eses were supported: values, understanding, and social justice motives werepositively associatedwith relatively self-determinedmotivation (RSM), whereascareer, social, protective, and enhancement motives showed negative correla-tions. The relationships between motives and satisfaction were partiallymediated by RSM. Concerning benefits, Study 2 corroborated these findingsfor values, protective, enhancement, and social justice. This research intro-duces a new perspective on the quality of volunteers’ motives—with theore-tical and practical implications.

ARTICLE HISTORYReceived 12 June 2015Accepted 15 December 2015

KEYWORDSFunctional approach;motivation; satisfaction; self-determination theory;volunteerism

A great amount of research on volunteerism has been devoted to its motivational foundations. Fromhelping people in need to improving one’s résumé, several functions that can be served byvolunteering have been identified. Both the importance of these functions—experienced asmotives—and the extent to which they are matched by environmental affordances have been linkedto successful volunteerism (e.g., Clary et al., 1998; Stukas, Worth, Clary, & Snyder, 2009).

Volunteer motives are differentially related to positive outcomes (e.g., Stukas, Hoye, Nicholson,Brown, & Aisbett, 2014). However, the mechanisms underlying these associations are still unclear. Toshed light on the mediating processes, we made use of self-determination theory (SDT; Deci & Ryan,1985, 2000). We proposed that volunteer functions are systematically related to the quality of motiva-tion—that is, to the experience of either self-determination and volition, on the one hand, or pressureand control, on the other hand. This SDT perspective on volunteer functions offers an explanation forwhy some motives are more strongly related to favorable outcomes than others. This researchcontributes an innovative classification of volunteer motives that does not coincide with previouslysuggested dichotomies of self- versus other-oriented motives. The purpose is to stimulate the discus-sion about the quality of volunteer motivation in terms of self-determination versus control.

The present research integrates the findings of two studies:

● Based on a longitudinal design, Study 1 examined the relationship between volunteers’ motivesat one time and the self-determined versus controlled quality of motivation and satisfaction at alater time.

CONTACT Stefan Tomas Güntert stefan.guentert@fhnw.ch School of Business, Institute for Nonprofit and PublicManagement, University of Applied Sciences and Arts Northwestern Switzerland, Peter Merian-Strasse 86, 4002 Base, Switzerland.© 2016 Taylor & Francis

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● Employing a cross-sectional design, Study 2 not only addressed volunteers’ motives, but alsoinvestigated function-specific benefits (i.e., environmental affordances). Furthermore, Study 2additionally included the recently developed “social justice” function as another motivedimension.

In the following, we give an overview of the functional approach to volunteerism, previousclassifications of volunteer motives, and SDT’s perspective on human motivation. Against thisbackground, we propose that different motives for volunteering can be associated with either self-determined or controlled types of motivation—leading to Hypotheses 1 and 2, which were tested inboth studies.

Subsequently, we present the social justice motive as an extension to the functional approach anddiscuss the functionalist matching hypothesis—leading to Hypothesis 3 and 4, which were testedonly in Study 2.

Functional approach to volunteerism

Volunteering can be described as planned helping that is thoughtfully decided on and not justspontaneously chosen. The question of what motivates people to give their time for the benefitof another person or organization without receiving any tangible benefits stimulated the interestof many researchers. The most influential psychological approach to volunteering, the functionalapproach, assumes that individuals can adopt the same attitudes or be involved in the samebehaviors despite the fact that these attitudes or behaviors may serve very different psychologicalfunctions (Snyder, Clary, & Stukas, 2000). This functionalist rationale has been successfullyapplied to volunteerism. In line with this assumption, Clary et al. (1998) developed an instru-ment, the Volunteer Functions Inventory (VFI), measuring the following six motivationalfunctions:

(1) Values: Through volunteering, people can express values related to humanitarian concernsfor others.

(2) Understanding: Volunteering provides opportunities to explore and exercise one’s skills andto learn about the world and the specific cause the individual is volunteering for.

(3) Enhancement: Through volunteering, the individual’s ego can grow.(4) Protective: Personal problems such as loneliness can be addressed; negative feelings of guilt

might be reduced.(5) Social: If voluntary work is highly valued by important others, volunteering is a good way to

adjust to the environment and strengthen one’s social relationships.(6) Career: Experience gained in volunteering can be beneficial to one’s professional career.

Classification of volunteer motives

In line with the debate in social psychology about whether helping is mainly an altruistic or egoisticaction (e.g., Batson, Duncan, Ackerman, Buckley, & Birch, 1981), researchers often distinguishbetween altruistic (or other-oriented) and egoistic (or self-oriented) motives for volunteering.With respect to the VFI, the values function is mainly considered altruistic or other-oriented (e.g.,Briggs, Peterson, & Gregory, 2010; Cornelis, Van Hiel, & De Cremer, 2013; Erez, Mikulincer, vanIjzendoorn, & Kronnenberg, 2008), as opposed to the remaining functions that are supposed to focuson personal benefits and, thus, to be egoistic, me- or self-oriented (e.g., Briggs et al., 2010; Corneliset al., 2013; Peloza, Hudson, & Hassay, 2009). This distinction of two dimensions is also supportedby factor analytical results (Cornelis et al., 2013; McDougle, Greenspan, & Handy, 2011). Theunderstanding function is usually seen as part of this second group. However, Erez et al. (2008),

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who regard volunteer motivation from an attachment-theoretical point of view, classify the under-standing motivation as exploration-related and, thus, differentiate it from the more self-servingcareer, enhancement, social, and protective motives.

The differentiation of altruistic versus egoistic motives for prosocial behaviors has been criticizedas being too simplistic (e.g. Dovidio, Piliavin, Schroeder, & Penner, 2006); the functional approachemphasizes that volunteering may simultaneously serve multiple functions for the same individual.Despite this legitimate critique, the categorizations can provide some parsimonious orientation withregard to qualities that are represented by the various motivations. In a recent study by Stukas et al.(2014), the categorization of volunteers’ motives into either self-oriented or other-oriented motivesproved useful in explaining their differential relationships with satisfying and sustained volunteering;more specifically, other-oriented motives showed positive correlations with satisfaction and intent tocontinue, whereas self-oriented motives showed negative associations. Nevertheless, these categor-izations do not represent underlying mechanisms that explain why some motives are more stronglyassociated with favorable outcomes than other motives. In this research, we suggest the quality ofmotivation as a mediating process.

Self-determination theory

In contrast to most motivation theories, SDT takes a qualitative perspective (Deci & Ryan, 2000). Ifmotivation was simply studied as a unitary quantitative construct, an essential dimension of humanmotivation would be missed: the degree to which individuals experience either self-determination orcontrol when regulating the behavior. The experience of self-determined motivation has beenassociated with increased overall functioning, personal growth, and both physical and psychologicalhealth (e.g., Deci & Ryan, 2008, for an overview).

SDT differentiates between several types of motivation that can be either described as self-determined or as controlled (see Figure 1). There is some discussion about whether these facetsshould be combined into a single indicator of relative self-determination (see Gagné et al., 2015);depending on the study’s focus, a more differentiated perspective might be chosen (see Güntert,2015). The purpose of the present article was to introduce the general idea that the quality ofmotivation in terms of self-determination versus control represents an explanation for why somemotives for volunteering might be more strongly associated with favorable outcomes than others.Thus, we chose a parsimonious index representing the quality of motivation in order to keephypotheses and analyses clearly laid out.

This is how the index of relatively self-determined motivation (RSM) was formed: We combinedcontrolled and self-determined types of motivation into scales for controlled motivation and self-determined motivation, respectively. Subsequently, the RSM index was created by subtracting

Figure 1. Different types of controlled versus self-determined motivation as conceptualized by self-determination theory (e.g.,Gagné et al., 2015). In the present research, the index representing relatively self-determined motivation was formed bysubtracting controlled motivation from self-determined motivation.

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controlled motivation from self-determined motivation. In the following, the components of theRSM index are explained in detail.

The first differentiation made by SDT is between intrinsic and extrinsic motivation. Intrinsicmotivation refers to the innate propensity of human beings to seek optimal challenges, to exercisetheir capacities, and to explore the environment (Deci & Ryan, 2000). No external rewards orpunishments are necessary to sustain the effort; individuals are motivated because they are interestedin or simply enjoy the activity they are engaged in.

Intrinsic motivation represents the prototype of self-determined motivation. This, however, doesnot imply that extrinsic motivation is necessarily associated with the experience of control, pressure,and alienation. Extrinsic motivation means that the activity is instrumental to some goal external ofthe activity itself. From a developmental perspective, these behaviors are usually required bysocializing agents as necessary and useful. However, regulation of extrinsically motivated behaviorscan be internalized; these behaviors as well can be experienced as “owned” and endorsed by one’score sense of self.

With respect to extrinsic motivation, SDT differentiates three types of regulation:1

● External regulation relates to rewards and (the avoidance of) punishments as immediateexternal contingencies regulating the behavior.

● Introjected regulation relates to contingencies that are not part of the social environment butstill external to the core sense of self—that is, the behavior is regulated by feelings of guilt,shame, or contingent self-worth.

● Identified regulation implies that the behavior is regulated by goals and values the individualconsiders as personally important and identifies with.

To sum up, external and introjected regulation (of extrinsic motivation) represent controlledmotivation. On the contrary, identified regulation (of extrinsic motivation) and intrinsic motivationdenote self-determined motivation.

SDT assumes that the quality of motivation—that is, the experience of self-determination versuscontrol—affects a variety of outcomes, ranging from well-being to performance. This assumption hasbeen successfully tested in various applied domains such as work and organizations (e.g., Gagné & Deci,2005; Gagné et al., 2015). In the context of volunteering, self-determined motivation has been linked tosatisfaction, low intent to quit (Millette & Gagné, 2008), or volunteers’ work effort (Bidee et al., 2013).

Against this background, we suggest that SDT’s perspective on the quality of motivation provides anexplanation for why some volunteer motives are more strongly related to positive outcomes than others.In this research, satisfaction was addressed as a global outcome summarizing volunteers’ attitude towardtheir volunteer activity. SDT does not predict that controlled motivation will generally lead to negativeoutcomes. In contrast, the mere “quantity” of motivation—of either controlled or self-determinednature—may suffice with respect to mundane tasks (see Gagné & Deci, 2005).

From an SDT perspective, we proposed that volunteers’ motives can be systematically associatedwith either self-determined or controlled types of motivation. These assumptions generalize acrossindividuals—that is, any motive could be associated with either self-determination or control for asingle volunteer. Overall, however, we suggested that there are inherent characteristics of volunteermotives that link them more strongly to self-determination than to control, or vice versa.

Two motives were categorized as “self-determined motives”:

● The motive to express one’s altruistic and humanitarian values in volunteering can be alignedwith identified regulation of extrinsic motivation—that is, with efforts that are endorsed by thecore sense of self because the individual strongly values the goals of the respective activity.

● The understanding motive, with its focus on opportunities for learning and practicing one’sskills, can be linked to both types of self-determined motivation (i.e., intrinsic motivation andidentified regulation of extrinsic motivation).

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The remaining four VFI functions were categorized as “controlled motives”:

● The enhancementmotive contains both favorable and problematic aspects: On the one hand, thereare positive aspects (e.g., making friends), and on the other hand, “ego involvement” (Deci &Ryan, 1985, p. 108) can be associated with this function (i.e., a person’s self-esteem might be “onthe line” if he or she volunteers in order to feel more important). For introjected regulation, “theprototypical examples are contingent self-worth (pride) or threats of guilt and shame” (Deci &Ryan, 2000, p. 236). Given the fact that most enhancement items refer to some kind of contingentself-worth (e.g., “Volunteering increases my self-esteem“), we expected the enhancement functionto correlate more strongly with controlled than self-determined motivation.

● The protective motive refers to instrumental aspects: Volunteering is regarded a means toaddress one’s personal problems. One VFI item explicitly addresses feelings of “guilt over beingmore fortunate than others,” which can be reduced by one’s volunteering. Thus, there is a linkto controlled types of motivation.

● The social function clearly refers to external “regulators” of the volunteers’ behavior. Beingconcerned about social rewards and punishments should definitely be associated with con-trolled motivation.

● The career motive shows an obvious link to instrumentality. If volunteering is expected toimprove one’s business or career, external evaluation should become more salient for theregulation of this behavior and might foster the experience of control.

The above classification resembles most closely the distinction made by Gillath et al. (2005; see alsoErez et al., 2008), who separated the understanding motive, which is focused on the exploration of one’senvironment, from what they label as “self-serving” motives (enhancement, protective, social, andcareer). In contrast to Konrath, Fuhrel-Forbis, Lou, and Brown (2012), however, our SDT-basedclassification clearly puts the values and the social motive (both labeled as “other-oriented” byKonrath et al.) into different categories. From an SDT perspective, we argue that complying with theinfluence or even pressure from others rather represents a controlled motive for volunteering.

The present research examined whether specific volunteer motives are—on average or typically—more strongly associated with either self-determined motivation or controlled motivation. Anelegant way to simplify this research question is to make use of the RSM index, which only focuseson the “relative dominance” of self-determined versus controlled motivation.2 Using the parsimo-nious RSM index, we hypothesized:

Hypothesis 1 (H1): Self-determined motives for volunteering are positively associated with RSM,whereas controlled motives are negatively related to RSM.

Making use of SDT, we introduced RSM as a mediating process linking motives to volunteeroutcomes. Self-determined types of motivation have been associated with favorable outcomes invarious applied domains and, more recently, in the context of volunteerism as well (e.g., Haivas,Hofmans, & Pepermans, 2014; Wu, Li, & Khoo, 2015). The quality of motivation is typicallyconceptualized as a process linking aspects of both the environment (such as work design orleadership) and the individual (such as motivational orientations) to a variety of work outcomes(e.g., Gagné & Deci, 2005). Thus, we hypothesized:

H2: Mediated by RSM, self-determined motives show a positive indirect effect on satisfaction,whereas controlled motives show a negative indirect effect.

It is important to note that we did not hypothesize that controlled motives show a negative totaleffect on volunteers’ satisfaction. However, we expected that, due to the negative impact of con-trolled motives on RSM, controlled motives have a weaker impact on volunteers’ satisfaction.

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Hypotheses 1 and 2 were tested in both studies. In Study 2, another self-determined motive—thesocial justice function—was additionally addressed. Furthermore, not only motives, but also func-tion-specific benefits and their matching with volunteers’ motives were examined as antecedents ofRSM and satisfaction.

Social justice function

The six volunteer functions described by Clary et al. (1998) represent a parsimonious set of volunteermotives; still, “there will be circumstances where either fewer functions, or more functions for thatmatter, will emerge” (p. 1528). Building on psychological justice research, the social justice function,was added recently (Jiranek, Kals, Humm, Strubel, & Wehner, 2013). This branch of research hasproven fruitful for a better understanding of human action in various areas of application (e.g., Kals& Maes, 2012; Skitka & Crosby, 2003). Volunteering as well has been shown to be influenced byjustice perceptions and dispositions (e.g., Moschner, 1994; Neufeind, Jiranek, & Wehner, 2014).These findings are in accordance with the assumption of a justice motive as a distinct source ofmotivation in addition to self-interest (Lerner, 1977; Montada, 1998). However, the motivation toprovide social justice through volunteering has not been examined within the VFI.

Even though social justice might also be conceptualized as value (Schwartz, 1994), it is notcovered by the values function of the VFI. Focusing on caring and compassion for other people,the latter stresses benevolence values, whereas social justice and equality constitute universalisticvalues—a distinction that also proves true across cultures (Schwartz, 1994). Moreover, it has beenshown that altruistic motivations—like those addressed by the value function—are distinct fromjustice motivations (Batson, Klein, Highberger, & Shaw, 1995). Consequently, an other-orientedsocial justice function that assesses the motive to contribute to social justice by volunteering wassuccessfully added to the VFI (Jiranek et al., 2013). Departing from the principle of equality, itcaptures the motivation to implement different facets of this principle, like equality of opportunityand participatory justice, as well as overlapping principles like the principle of need. The distinctionbetween the values and the social justice function is empirically supported by both exploratory andconfirmatory factor analyses (Jiranek et al., 2013).

Due to the conceptual similarity with the values motive, we categorized the social justice functionas a self-determined motive and hypothesized the respective relationships (see Hypotheses 1 and 2).

Matching motives and benefits

In Study 2, we examined not only motives, but also the function-specific benefits that might matchvolunteers’ motives. Central to the functional approach is the so-called matching hypothesis. Forvolunteerism to be successful and sustained, it is essential that volunteers’ motives are matched withcorresponding environmental affordances—that is, opportunities of the volunteer activity. Thematching hypothesis has been supported in several studies (e.g., Clary et al., 1998; Stukas et al.,2009).

Stukas et al. (2009) proposed a parsimonious index to represent the overall motive-benefit matchacross the six VFI dimensions and were able to support the superiority of a “total match index” overmotive or benefit scores alone. As the present research focused rather on particular functions thanon the overall matching, we formed univariate match indices by multiplying the correspondingmotive and benefit scores of an individual.

Although the primary focus of this research was on volunteers’ motives, we expected similarassociations with respect to function-specific benefits. The rationale for this assumption is derivedfrom goal content theory (GCT), a “mini-theory” within the broader framework of SDT(Vansteenkiste, Niemiec, & Soenens, 2010). GCT differentiates between intrinsic and extrinsic lifegoals and posits that the pursuit of intrinsic goals (e.g., personal growth and close relationships)contributes to satisfaction of basic psychological needs for competence, relatedness, and autonomy.

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In contrast, pursuit of extrinsic goals (e.g., money and fame) is expected to be either unrelated ornegatively related to basic need satisfaction. A study by Niemiec, Ryan, and Deci (2009) showed thateven attaining extrinsic aspirations—which should be experienced as a success—was leading toanxiety and negative affect.

On the basis of GCT, we assumed that function-specific benefits show similar patterns as thecorresponding motives that we classified as either self-determined or controlled:

H3: Benefits corresponding to self-determined motives are positively associated with RSM, whereasbenefits corresponding to controlled motives are negatively related to RSM.

In parallel to Hypothesis 2, we assumed with respect to benefits and match indices:

H4: Mediated by RSM, benefits and match indices corresponding to self-determined motives show apositive indirect effect on satisfaction, whereas benefits and match indices corresponding to con-trolled motives show a negative indirect effect.

The functional approach does not differentiate between more or less desirable motives: Anypersonally relevant motive that is matched by environmental affordances will lead to positive out-comes. Thus again, it is important to note: SDT does not predict that matching controlled motives willnegatively affect volunteers’ satisfaction. However, because of their negative impact on RSM, benefitsand match indices corresponding to controlled motives should result in lower levels of satisfaction ascompared to benefits and match indices that correspond to self-determined motives.

Method

Procedure and participants

In Study 1, data were gathered as part of a more extensive longitudinal project addressing a widerrange of topics. We focused on volunteering in the social sector and asked several organizations inthe German-speaking part of Switzerland to invite their volunteers to participate in this research.The nonprofit organizations provided various services, for example, a crisis helpline, support forelderly people, or projects for people with disabilities. Volunteers could answer either a paper-basedor an identical online version of the questionnaire.

At Time 1, a total of 2,017 volunteers answered the questionnaire (response rate: 41%); at Time 2(i.e., 16 months after the first measurement point), 1,506 people also answered a secondquestionnaire.3 A large number (41%) of the participants who answered both questionnaires didnot remember the code we had asked them to create at Time 1 (obviously, many participants hadchosen some “password” instead of following our advice to create a code based on information theycould more easily remember at a later time). Thus, we were able to match the individual data of only889 participants.4 We dealt with missing data in a conservative way. Missing data were missingcompletely at random (Little’s MCAR test: χ2 = 5358.6, df = 5205, p > .05). Using the expectation-maximization algorithm (e.g., Graham, 2009, for an overview), imputation was applied if either therewas no more than one missing value among the items pertaining to a scale of up to four items (i.e.,satisfaction and four types of motivation), or there were only one or two missing values among theitems pertaining to a scale of five items (i.e., VFI scales); otherwise, list-wise deletion was applied.Consequently, the final sample size for Study 1 was N1 = 824.

The cross-sectional sample of Study 2 represents a convenience sample. Using a broad range ofchannels (e.g., postings in social networks), volunteers from various fields were invited to participatein an anonymous online survey. In total, 342 participants answered the questionnaire. The numberof missing values was very low; and missing data were missing completely at random (Little’s MCARtest: χ2 = 5015.7, df = 4868, p > .05). Applying the same criteria for imputation as mentioned with

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respect to Study 1, the final sample size for Study 2 was N2 = 323. As the recruitment of participantsstrongly relied on personal networks, some areas of volunteering and particular organizations werehighly represented in this convenience sample: 30% of the respondents, for example, worked forAmnesty International; 43% were engaged in various types of social-sector or church-relatedvolunteering; 15% volunteered in the areas of sports or cultural activities; the remaining 12% workedin areas such as animal protection or politics.

For Study 1, the mean age of the participants was 64.7 years (SD = 10.1), and 59% of thevolunteers were female. On average, the participants spent 3.9 hours (SD = 3.2) per week volunteer-ing for the organization. With reference to Time 1, 81% (or 51%) of the volunteers had been stayingwith this organization for at least 2 years (or 5 years, respectively).

For Study 2, the mean age was 45.7 years (SD = 18.2), and 67% of the participants were female.The participants spent an average of 3.8 hours (SD = 3.7) per week volunteering for the organization,and 76% (or 47%) of the participants had been volunteering for at least 2 years (or 5 years,respectively).

Measures

In Study 1, volunteers’ motives were measured at Time 1, whereas quality of motivation andsatisfaction were measured at Time 2. In Study 2, all variables were part of the same cross-sectionalquestionnaire.

Volunteer motivesUsing the German version of the VFI (Oostlander, Güntert, van Schie, & Wehner, 2014), wemeasured all of the six volunteer functions addressed by Clary et al. (1998). Items were rated on ascale from 1 (not at all important) to 5 (very important). Each scale was measured by five items;sample items are: “I feel compassion toward people in need” (values); “I can learn more about thecause for which I am working” (understanding); “Volunteering makes me feel important” (enhance-ment); “Doing volunteer work relieves me of some of the guilt over being more fortunate thanothers” (protective); “People I’m close to want me to volunteer” (social); and “Volunteeringexperience will look good on my résumé” (career). In Study 2, we additionally measured the socialjustice function introduced by Jiranek et al. (2013), also using five items (sample item: “Volunteeringenables me to create equal opportunities for all people”).

Function-specific benefitsIn Study 2, we also addressed function-specific benefits. These environmental affordances match theindividual volunteer’s motives to a certain degree. Matching motives and benefits has been con-sidered crucial for successful volunteering (Stukas et al., 2009). Stukas et al. suggested two items foreach of the six VFI functions. In order to obtain decent internal consistencies, we extended this set tothree items for each function-specific benefit. Benefit items were rated on a scale from 1 (not at allaccurate) to 5 (very accurate). Sample items are: “Through volunteering here, I can help otherpeople” (values); “Through volunteering, I am learning how to deal with a greater variety of people”(understanding); “I feel better about myself as a result of my volunteering” (enhancement);“Volunteering allows me the opportunity to escape some of my own troubles” (protective);“People I know consider my volunteering as important” (social); “I have the opportunity to makenew contacts that might help my business or career” (career); and “Volunteering at this organizationallows me to even out unequal social conditions” (social justice).

Multiplying the individual motive and benefit scores, we formed match indices for the respectivevolunteer functions. As recommended by Stukas et al. (2009), these product terms were based onunstandardized scores of the motive and benefits scales, respectively. In doing so, we took into accountthat a combination of low motive and low benefit is not considered a “positive match” leading to highersatisfaction; only the high-high combination—that is, motives met by affordances—is expected to have a

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positive impact. If we used standardized scores instead, both low-low and high-high combinations wouldrepresent a motive-benefit match.

Quality of motivationTo measure the quality of volunteers’ motivation, we used an earlier version of the MultidimensionalWork Motivation Scale (Gagné et al., 2015) and adapted it to the context of volunteering. All itemsrepresented answers to the following introductory question: “Why do you or would you put effortinto your volunteer activity?” The answers were rated on a scale from 1 (strongly disagree) to 5(strongly agree). Each scale consisted of four items; sample items are: “Because the volunteer activityI do is interesting” (intrinsic motivation); “Because I personally consider it important to put effortsin this activity” (identified regulation);5 “Because otherwise I will feel bad about myself” (introjectedregulation); and “Because others will respect me more (e.g., supervisor, clients, family)” (externalregulation). The scale for self-determined motivation was formed as the average of the intrinsic andidentified subscales. Correspondingly, the controlled motivation scale was built as the average of theintrojected and external subscales. The index for RSM was formed as the difference of standardscores (i.e., self-determined motivation minus controlled motivation). We went for standardizationto ensure that the overall score equally represented the self-determined and the controlled quality ofmotivation.

SatisfactionWhereas motives and quality of motivation were operationalized exactly the same way in bothstudies, the measurement of volunteers’ satisfaction differed to a minor degree. The items “Overall, Ilike my volunteer activity a lot” and “All in all, I am very satisfied with my volunteer activity” wereused in both studies. In Study 1, one additional item was employed: “I am satisfied with myvolunteer tasks.” In Study 2, there were two additional items: “My volunteer activity gives me alot of satisfaction” and “Overall, my volunteer activity is great.” All items were rated on a scale from1 (strongly disagree) to 5 (strongly agree).

Statistical analyses

Using the procedure recommended by Preacher and Hayes (2008), we conducted mediation analysesfor the relationships of each antecedent (i.e., motive, benefit, or match index) and volunteers’satisfaction, mediated by RSM (see Figure 2).

This approach has the advantage that it estimates and tests the size of the indirect effect. Toconduct the analyses, we used the SPSS macro “PROCESS” (Hayes, 2012). As suggested by Preacherand Kelley (2011), we employed κ2 as an effect size measure for indirect effects: .01, .09, and .25 canbe used as benchmarks for small, medium and large effect sizes, respectively.

Figure 2. Conceptual diagram illustrating the mediation hypothesis.

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Results

Descriptive statistics and correlations

Table 1 and Table 2 show means, standard deviations, intercorrelations, and internal consistenciesfor all variables in Study 1 and Study 2, respectively.

In both samples, the expression of personal values was ranked as the most important function ofone’s volunteering, followed by the understanding motive. With respect to the quality of motivation,self-determined types of behavioral regulation clearly dominated as compared to controlled forms ofmotivation.

As hypothesized, volunteers’ motives were differentially associated with the quality of motivation.In Study 1, self-determined motives (values and understanding) were positively associated with RSM,whereas controlled motives (enhancement, protective, social, and career) were negatively correlatedto RSM. Thus, Hypothesis 1 was fully supported in Study 1. In Study 2, however, Hypothesis 1 wasonly partially supported, because the understanding motive was not significantly associatedwith RSM.

Function-specific benefits (addressed by Study 2) showed a similar correlational pattern as therespective motives—with two exceptions: the benefits corresponding to the social and the careerfunction were not significantly related to RSM. Hypothesis 3 was supported with respect to thevalues, enhancement, protective, and social justice benefits—and, thus, only partially confirmed.

Volunteers’ motives showed differential associations with satisfaction. In Study 1, four out of sixmotives positively correlated with satisfaction: the values and understanding motives showed thestrongest positive correlations, whereas the protective and career motives were not significantlyrelated to satisfaction. In Study 2, with respect to all but the protective function, both motives andbenefits showed significant positive correlations with satisfaction. The size of these correlations,however, differed considerably among the various motives and benefits. The mediation analyses,presented in the following, examined whether RSM explains these differential relationships.

Mediation analyses

For each antecedent, Table 3 shows estimates and bias-corrected confidence intervals (based on5,000 bootstrap samples) for the total effect, the direct effect, the indirect effect, and the

Table 1. Descriptive statistics for all variables of Study 1.

Variable M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14

VFI motive (Time 1)1. Values 4.21 0.60 .782. Understanding 3.74 0.78 .33 .823. Enhancement 3.00 0.85 .29 .47 .814. Protective 1.96 0.83 .20 .33 .62 .835. Social 2.20 0.88 .29 .27 .39 .37 .846. Career 1.91 0.81 .15 .48 .42 .48 .48 .83Quality of motivation (Time 2)7. Intrinsic 4.28 0.66 .28 .43 .25 .12 .18 .19 .888. Identified 4.23 0.60 .34 .34 .23 .12 .20 .17 .57 .739. Introjected 2.94 0.93 .25 .20 .36 .28 .31 .26 .20 .44 .7010. External 2.30 0.93 .17 .15 .35 .30 .39 .33 .06 .25 .70 .8211. Self-determination 4.26 0.56 .35 .43 .27 .14 .21 .21 .90 .87 .35 .17 .8612. Control 2.62 0.86 .23 .19 .39 .31 .38 .32 .14 .37 .92 .92 .28 .8513. RSM 0.00 1.20 .10 .20 −.10 −.15 −.14 −.09 .63 .42 −.48 −.63 .60 −.60 —Outcome (Time 2)14. Satisfaction 4.50 0.60 .20 .21 .12 .05 .11 .04 .58 .42 .10 .03 .57 .07 .42 .91

Note. N1 = 824. VFI = Volunteer Functions Inventory; RSM = relatively self-determined motivation. All measures (except for RSM)were on a scale from 1 to 5. Cronbach’s coefficient α is displayed in the diagonal. Level of significance concerning thecorrelations: p < .05, if abs (r) ≥ .07; p < .01, if abs (r) ≥ .09.

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Table2.

Descriptivestatisticsforallvariables

ofStud

y2.

Variable

MSD

12

34

56

78

910

1112

1314

1516

1718

1920

2122

VFIm

otive

1.Values

4.12

0.66

.78

2.Und

erstanding

3.56

0.78

.07

.79

3.Enhancem

ent

3.00

0.81

.09

.54

.78

4.Protective

1.97

0.76

.10

.38

.61

.75

5.Social

2.25

0.79

.09

.36

.36

.32

.83

6.Career

2.10

1.09

−.14

.58

.45

.27

.30

.92

7.Socialjustice

3.91

0.90

.65

.09

.01

.04

.07

−.05

.88

VFIb

enefit

8.Values

4.29

0.66

.59

.21

.14

.10

.06

−.07

.59

.70

9.Und

erstanding

3.68

0.90

−.00

.78

.50

.38

.36

.50

−.01

.23

.82

10.Enh

ancement

3.04

0.95

.07

.41

.72

.56

.34

.27

−.01

.21

.54

.82

11.P

rotective

1.96

0.97

.00

.32

.45

.78

.24

.23

−.04

.06

.40

.56

.88

12.Social

3.07

0.92

.16

.34

.32

.22

.63

.21

.08

.26

.48

.43

.23

.85

13.C

areer

2.56

1.32

−.12

.56

.34

.22

.28

.82

−.03

.02

.59

.28

.28

.27

.92

14.Socialjustice

3.57

0.94

.48

−.06

−.10

.01

.07

−.15

.75

.55

−.05

−.01

−.00

.10

−.09

.85

Qualityof

motivation

15.Intrin

sic

4.26

0.69

.13

.41

.27

.08

.15

.18

.15

.35

.37

.14

.04

.24

.24

.13

.88

16.Identified

4.28

0.69

.37

.28

.27

.07

.18

.08

.34

.50

.29

.27

.04

.31

.14

.30

.57

.84

17.Introjected

2.85

0.85

.17

.30

.50

.43

.19

.18

.06

.11

.32

.44

.30

.21

.16

.01

.14

.31

.65

18.External

2.40

0.88

.04

.30

.49

.46

.40

.34

−.03

−.01

.32

.40

.36

.23

.26

−.09

−.01

.14

.55

.76

19.Self-determ

ination

4.27

0.61

.28

.38

.30

.09

.18

.15

.28

.48

.37

.23

.04

.31

.22

.24

.89

.89

.26

.07

.88

20.C

ontrol

2.63

0.76

.12

.34

.56

.51

.34

.30

.02

.06

.36

.48

.38

.25

.24

−.05

.07

.26

.88

.89

.19

.80

21.R

SM0.00

1.28

.13

.03

−.20

−.33

−.12

−.12

.20

.33

.01

−.19

−.26

.05

−.02

.23

.64

.49

−.49

−.64

.64

−.64

—Outcome

22.Satisfaction

4.17

0.67

.17

.28

.23

.07

.17

.13

.16

.36

.30

.17

.06

.23

.17

.18

.75

.49

.11

−.02

.70

.05

.51

.88

Note.N2=323.VFI=

VolunteerFunctio

nsInventory;RSM

=relativelyself-determ

ined

motivation.Allm

easures(exceptforRSM)w

ereon

ascalefrom

1to

5.Cron

bach’scoefficient

αisdisplayed

inthediagon

al.Level

ofsign

ificanceconcerning

thecorrelations:p

<.05,

ifabs(r)≥.11;

p<.01,

ifabs(r)≥.15.

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Table 3. The impact of volunteers’ motives, function-specific benefits, and match indices on satisfaction mediated by RSM.

Type of antecedent

Motive (Study 1) Motive (Study 2) Benefit (Study 2) Match index (Study 2)

95% CI 95% CI 95% CI 95% CI

Volunteer function Est. LL UL Est. LL UL Est. LL UL Est. LL ULValuesTotal effect (c) .203 .149 .259 .168 .048 .294 .359 .250 .466 .277 .167 .353Direct effect (c’) .164 .115 .214 .104 .016 .193 .214 .122 .307 .163 .075 .250Indirect effect via RSM(a × b)

.039 .016 .064 .064 .005 .128 .145 .097 .204 .115 .063 .173

Antecedent → RSM (a) .097 .040 .157 .130 .008 .252 .333 .226 .433 .246 .135 .353RSM → Outcome (b) .400 .353 .445 .493 .415 .565 .435 .354 .516 .467 .386 .542κ2 .041 .012 .072 .069 .008 .149 .148 .090 .217 .119 .057 .188UnderstandingTotal effect (c) .212 .152 .264 .281 .178 .373 .301 .197 .390 .304 .207 .388Direct effect (c’) .133 .076 .188 .264 .172 .343 .297 .207 .369 .304 .218 .380Indirect effect via RSM(a × b)

.078 .054 .105 .017 −.029 .068 .004 −.044 .056 .001 −.046 .049

Antecedent → RSM (a) .201 .143 .261 .034 −.061 .133 .007 −.088 .112 .001 −.090 .097RSM → Outcome (b) .389 .337 .435 .498 .419 .568 .505 .424 .575 .506 .428 .577κ2 .080 .051 .114 .019 .001 .060 .004 .000 .010 .001 .000 .001EnhancementTotal effect (c) .116 .059 .174 .229 .134 .312 .171 .068 .266 .224 .135 .306Direct effect (c’) .158 .104 .211 .346 .264 .416 .280 .190 .360 .349 .264 .422Indirect effect via RSM(a × b)

−.042 −.067 −.018 −.117 −.178 −.057 −.109 −.171 −.055 −.125 −.183 −.072

Antecedent → RSM (a) −.097 −.151 −.041 −.203 −.299 −.097 −.195 −.287 −.096 −.215 −.300 −.123RSM → Outcome (b) .431 .382 .476 .577 .499 .643 .561 .476 .634 .582 .502 .650κ2 .049 .017 .086 .163 .075 .249 .143 .061 .229 .172 .091 .254ProtectiveTotal effect (c) .050 −.004 .103 .068 −.021 .150 .057 −.036 .143 .086 −.004 .163Direct effect (c’) .113 .062 .164 .264 .183 .342 .204 .119 .288 .253 .172 .336Indirect effect via RSM(a × b)

−.063 −.088 −.040 −.196 −.256 −.142 −.147 −.206 −.097 −.167 −.222 −.118

Antecedent → RSM (a) −.145 −.196 −.092 −.330 −.406 −.248 −.262 −.346 −.173 −.289 −.362 −.207RSM → Outcome (b) .432 .385 .477 .594 .511 .670 .560 .476 .637 .580 .498 .655κ2 .070 .039 .102 .225 .156 .303 .170 .103 .243 .197 .130 .269SocialTotal effect (c) .111 .058 .162 .166 .056 .256 .226 .130 .317 .195 .082 .280Direct effect (c’) .175 .125 .225 .230 .150 .307 .203 .111 .284 .230 .142 .310Indirect effect via RSM(a × b)

−.063 −.090 −.039 −.064 −.128 −.009 .023 −.025 .075 −.035 −.093 .018

Antecedent → RSM (a) −.144 −.198 −.089 −.120 −.225 −.014 .046 −.052 .146 −.068 −.171 .036RSM → Outcome (b) .441 .392 .486 .534 .452 .608 .497 .417 .569 .522 .441 .596κ2 .074 .041 .108 .084 .008 .170 .025 .001 .075 .048 .003 .138CareerTotal effect (c) .035 −.024 .092 .130 .030 .224 .175 .087 .264 .168 .073 .256Direct effect (c’) .075 .019 .128 .191 .105 .273 .183 .099 .263 .202 .113 .284Indirect effect via RSM(a × b)

−.040 −.064 −.018 −.061 −.117 −.013 −.009 −.056 .036 −.034 −.083 .014

Antecedent → RSM (a) −.095 −.147 −.042 −.116 −.208 −.023 −.017 −.109 .072 −.064 −.154 .028RSM → Outcome (b) .423 .375 .468 .529 .447 .604 .510 .425 .584 .520 .438 .594κ2 .045 .016 .075 .078 .009 .154 .012 .000 .042 .044 .002 .117Social justiceTotal effect (c) .157 .042 .272 .178 .079 .277 .182 .082 .280Direct effect (c’) .057 −.035 .147 .064 −.015 .149 .068 −.015 .153Indirect effect via RSM(a × b)

.100 .046 .159 .114 .063 .170 .114 .063 .170

Antecedent → RSM (a) .201 .097 .306 .232 .135 .322 .231 .134 .326RSM → Outcome (b) .495 .413 .569 .492 .408 .566 .491 .408 .566κ2 .106 .040 .178 .120 .062 .192 .120 .060 .186

Note. N1 = 824 (Study 1); N2 = 323 (Study 2). CI = Confidence interval, bias-corrected and based on k = 5ʹ000 bootstrap samples;Est. = Estimate; LL = Lower limit; UL = Upper limit; RSM = relatively self-determined motivation. In Study 1, motives weremeasured at Time 1, RSM and satisfaction at Time 2 (16 months later). Benefits and the social justice function were onlyaddressed in Study 2. Match indices were calculated as the product of motive and benefit scores.

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“constituents” of the indirect effect (i.e., the antecedent’s effect on RSM, and RSM’s effect onsatisfaction). The estimates for indirect effects have been bolded when statistically significant.

In Study 1, Hypothesis 2 was supported for all of the six volunteer functions. There weresignificant positive indirect effects of self-determined motives via RSM on satisfaction; and theindirect effects of controlled motives were negative and also significantly different from zero. InStudy 2, however, Hypothesis 2 was not confirmed with respect to the understanding motive: Theindirect effect via RSM was not significantly different from zero.

Benefits and match indices were only addressed in Study 2. Hypothesis 4 was partially supported:The indirect effects via RSM of benefits and match indices concerning both the values and the socialjustice function were positive; and the indirect effects via RSM of benefits and match indicesconcerning both the enhancement and the protective functions were negative. However, with respectto the understanding, social, and career function, the indirect impact of benefit and match indiceswas not significantly different from zero.

In order to gauge the size of the indirect effects, we analyzed κ2 as an effect size measurerecommended by Preacher and Kelley (2011). Overall, most effect sizes indicated indirect effectsin the small to medium range. In Study 2, the size of the indirect effects related to the enhancementand protective functions can be labeled as medium to large.

Discussion

Volunteers’ motives have been differentially linked to favorable outcomes; however, the mediatingprocesses still remain unclear (Stukas et al., 2014). Applying SDT, we suggested that the quality ofmotivation that is associated with a specific volunteer function will account for some part of therelationship between volunteers’ motives and satisfaction. Study 2 further extended this rationale tothe impact of function-specific benefits and match indices.

Our hypotheses were fully supported in Study 1: Self-determined motives (values and under-standing) positively correlated with RSM, whereas controlled motives (enhancement, protective,social, and career) showed negative correlations. The relationships between motives and satisfac-tion were partially mediated by RSM. In Study 2, our assumptions were confirmed for five out ofsix VFI motives and for the social justice motive. Taken together, the present research mostlyconfirmed RSM as a process that mediates the relationships between volunteers’ motives andsatisfaction. In line with SDT’s core assumptions, it is the relative quality of self-determinedversus controlled motivation that makes a meaningful distinction between various volunteerfunctions. This result is consistent with findings on the different effects of pleasure- versuspressure-based prosocial motivation on favorable outcomes (Gebauer, Riketta, Broemer, &Maio, 2008).

Overall, the indirect effects via RSM were of small to medium size. Furthermore, all direct effects,except for the social justice function, were still significant, which indicates that there are additionalmediating processes. The quality of motivation, as conceptualized by SDT, represents a relevantmediator, but it is only one. It is important to note that all volunteer motives show positivecorrelations with both self-determined and controlled motivation. In Study 2, for example, theunderstanding motive did not correlate significantly with RSM, but it showed equally strongassociations with self-determined and controlled motivation. These correlations demonstrate thatthe RSM index represents the quality of motivation in terms of a “relative dominance” of self-determined versus controlled motivation. Consequently, the quantity of motivation—across thespectrum of both self-determined and controlled types of motivation—can be suggested as anothermediator of the motive-satisfaction relationship. However, as the purpose of the present research wasto address volunteer functions from an SDT perspective, we exclusively focused on RSM—that is, thequality dimension of motivation (see also Footnote 2).

Volunteers in Study 2 were considerably younger than participants in Study 1. This differencewith respect to age may account for the zero correlation between the understanding motive and RSM

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in Study 2. Probably, the meaning of understanding changes depending on the volunteers’ age. Foryounger volunteers, the understanding motive might bear some similarity to the career motive andbe perceived as instrumental to a goal that is relatively unrelated to the cause one is volunteering for.Conversely, for elder volunteers the understanding function might be less instrumental and ratherreflect interest and curiosity.6 This interpretation is in line with socioemotional selectivity theory(Carstensen, Isaacowitz, & Charles, 1999) and corresponding findings on age-related differences.They suggest that older individuals rather concentrate on the present and are, therefore, motivated toderive meaning from their voluntary activity and to strengthen close social ties, whereas youngerindividuals focus on the more distant future and, thus, attach more importance to knowledge seekingand forming new relationships (Okun & Schultz, 2003; Omoto, Snyder, & Martino, 2000).

Concerning benefits and match indices, our hypotheses were confirmed with respect to thevalues, enhancement, protective, and social justice functions. Although, however, social and careermotives were negatively related to RSM, the respective benefits showed no significant associationswith RSM. Based on GCT, we had expected that affordances corresponding to social adjustment andcareer benefits should negatively affect RSM. Obviously, reactions of important others were notperceived as pressure toward continued volunteering but rather as positive feedback. Similarly, theopportunity to make career-relevant contacts did not result in feelings of external pressure orcontrol.

Limitations of the present research concern the studies’ design and the generalizability of thefindings. The cross-sectional design of Study 2 did not allow for testing assumptions about causality.And, although Study 1 was part of a longitudinal project, more sophisticated analyses regarding thecausality of the relationships require repeated measurements of all variables. Nevertheless, because ofthe separate measurement points, the likelihood that the relationships between motives and RSM aremerely due to common method variance was considerably reduced. Future research should trackboth volunteers’ motives and the quality of motivation over an extended period of time. In doing so,reversed or reciprocal effects of satisfaction with the activity on specific motives for volunteeringmight be explored. Furthermore, future research addressing these structural relationships shouldmodel all variables as latent constructs in order to take measurement error into account.

Both studies had a strong focus on social-sector volunteering and made use of conveniencesamples, which challenges the generalizability of our findings. Future research should systematicallycompare various areas of volunteering and investigate whether the relationships are dependent on,for example, the volunteers’ age. Furthermore, generalizability is limited with respect to outcomes.The present research focused on satisfaction, which is important, but it is only one facet of successfulvolunteering. In Study 1, we were, unfortunately, not able to identify those volunteers who hadactually given up volunteering at Time 2. Future research might examine a wider range of favorablevolunteer outcomes (e.g., Stukas et al., 2014, who examined five facets of well-being) and should, inparticular, include measures from an independent source (e.g., ratings from supervisors or bene-ficiaries, and data on actual retention). From an SDT perspective, future studies should particularlyaddress outcomes that have been closely linked to self-determined motivation such as creativity,cognitive flexibility, extra-role behaviors, and health benefits (see Gagné & Deci, 2005).

This leads us to an important theoretical consideration. Although both intrinsic motivation andidentified regulation represent self-determined motivation, they are distinct motivational qualities,differentially related to outcomes (e.g., Güntert, 2015). Identified regulation will be “more effective inpredicting persistence on uninteresting, but effort-driven tasks, whereas intrinsic motivation will bemore effective in predicting persistence on interesting tasks” (Gagné & Deci, 2005, p. 348). In thepresent research, the values and social justice functions correlated more strongly with identifiedregulation than with intrinsic motivation, whereas the understanding function showed the reversepattern. In a recent study by Wu et al. (2015), volunteers’ experience of competence and efficacy(which can be associated with the understanding function) was linked to satisfaction via themediating process of intrinsic motivation. Thus, we suggest that future research should alsoinvestigate different types of motivation as separate mediating processes.

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Some studies differentiate between self-oriented (egoistic) and other-oriented (altruistic) motivesof volunteers (see Stukas et al., 2014, for an overview). Making use of SDT, this research contributesto overcoming the egoistic-altruistic dichotomy. Volunteering may serve both other- and self-oriented functions at the same time. Whether these motives are accompanied by the experience ofeither self-determination or control significantly affects volunteers’ satisfaction. Remarkably, thelatter differentiation between self-determination and control does not coincide with a self-otherdichotomy that separates the values and the understanding function (cf. Konrath et al., 2012). TheSDT-based categorization presented in this research most closely resembles the one proposed byGillath et al. (2005). Both values and understanding motives represent functions that can be alignedwith the human propensity toward personal endorsement of values and psychological growth (seeDeci & Ryan, 2000). In a longitudinal study by Omoto and Snyder (1995), understanding andpersonal development motives were positively related to duration of volunteer service. Against thebackground of the present SDT-based research, those motives could be described as highly self-determined in nature.

Our research showed that values, social justice, and—in Study 1—understanding motives werepositively related to volunteers’ experience of RSM. Therefore, organizations might prefer to recruitexclusively those volunteers who strongly emphasize these motives. There are, however, importantcaveats. The aim of this research was not to create new categories of “favorable” versus “unfavorable”motives. Instead, we wanted to illustrate that volunteers’ efforts can be grounded either in interestand identification or in external pressure and control. Among the VFI functions, there are, of course,prototypical “candidates” for self-determination versus control—as shown in this research. Theserelationships, however, only tell us something about the average volunteer. Volunteers not fittinginto average pattern shrink the overall size of correlations and mediational effects. An exampleillustrates this idea: A volunteer with a strong career motive does not necessarily experience a lowlevel of self-determination; maybe the person is so passionate about the volunteer task that he or sheregards this activity as the first step of a professional career.

As a consequence, the practical implication of this research is to focus on the self-determinedmotivation of the individual volunteer rather than to select people on the basis of a broad category of“adequate” motives. In addition to recruiting the right volunteers, organizations may also proactivelycultivate motives that are more strongly associated with self-determination (e.g., Clary & Snyder, 2002).Although motives showed comparatively weak correlations with RSM, the association between RSMand satisfaction was remarkably strong in both studies. Consequently, practitioners should foster theexperience of self-determination. Volunteers’ tasks, for example, can be designed to be more motivating(Millette & Gagné, 2008), and supervisors should provide an autonomy-supportive work environment(Haivas, Hofmans, & Pepermans, 2012). We hope that our research further stimulates an SDT-basedapproach to volunteerism and contributes to human flourishing in this life domain.

Notes

1. A fourth type, integrated regulation, represents the highest form of internalized extrinsic motivation: Therespective behaviors reflect a person’s integrated sense of self; this quality of motivation, however, is rarelyaddressed by established instruments.

2. We also explored mediation models using two parallel mediators (i.e., self-determined motivation andcontrolled motivation) instead of RSM as a single mediator. The results were equivalent to the findingspresented in this article. However, due to collinearity problems (self-determined and controlled motivationare positively correlated), we decided to use RSM as a summarizing index representing the quality ofmotivation.

3. Low response rates and attrition might lead to selection biases (e.g., to an over-representation of very satisfiedvolunteers). According to Graham (2009), however, these effects of selective participation and drop-out need tobe very strong in order to seriously affect the validity of the overall correlational findings. The present researchdid not focus on the level of volunteer satisfaction, but on the relationships between variables.

4. We checked for biases due to selective dropout and found only one significant difference: Volunteers, whoparticipated at Time 1, but either did not participate at Time 2 or actually participated but did not provide the

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correct code, showed slightly lower levels of the understanding motive (M = 3.67, SD = 0.80) than theparticipants who returned at Time 2 and provided the correct code (M = 3.74, SD = 0.78); the effect size ofthis difference, however, is only small (Cohen’s d = 0.10).

5. Despite conceptual similarities, intrinsic motivation and identified regulation represent distinct qualities ofmotivation. An exploratory factor analysis of the eight items clearly resulted in a two-factor solution, with itemsrepresenting intrinsic motivation and identified regulation, respectively, loading on separate factorialcomponents.

6. An exploration with respect to Study 2 revealed that, for younger participants (40 years old or younger), theunderstanding motive was more strongly related to the career motive (r = .62) than for participants aged50 years or older (r = .39).

Notes on contributors

Stefan Tomas Güntert is a Lecturer in Organizational Behavior at the University of Applied Sciences and ArtsNorthwestern Switzerland. He received his PhD from ETH Zurich in 2008. His research interests include work design,work motivation, volunteering, nonprofit management, and self-determination theory. Isabel Theresia Strubel is adoctoral candidate in Social and Organizational Psychology at the Catholic University of Eichstätt-Ingolstadt,Germany. Her research interests include volunteering and justice psychology. Elisabeth Kals holds a Professorshipfor Social and Organizational Psychology at the Catholic University of Eichstätt-Ingolstadt. Her research interests aremotivation research, including the field of volunteering, justice psychology, and psychology of emotion, conflictresolution and mediation, decision-making in organizations, and other fields of responsible behavior. Theo Wehner isEmeritus Professor for Work and Organizational Psychology at ETH Zurich and Guest Professor at the University ofBremen. His research interests are volunteering and corporate volunteering, human error and psychological aspects ofsecurity and safety, the relationship between knowledge and experience, and work psychological aspects of the basicincome debate.

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