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r Academy of Management Journal 2016, Vol. 59, No. 2, 414–435. http://dx.doi.org/10.5465/amj.2014.0262

INTEGRATING THE BRIGHT AND DARK SIDES OF OCB: A DAILY INVESTIGATION OF THE BENEFITS AND COSTS

OF HELPING OTHERS

JOEL KOOPMAN University of Cincinnati

KLODIANA LANAJ University of Florida

BRENT A. SCOTT Michigan State University

Although the general picture in the organizational citizenship behavior (OCB) literature is that OCB has positive consequences for employees and organizations, an emerging stream of work has begun to examine the potential negative consequences of OCB for actors. Drawing from the cognitive-affective processing system framework and con- servation of resources theory, we present an integrative model that simultaneously ex- amines the benefits and costs of daily OCB for actors. Utilizing an experience sampling methodology through which 82 employees were surveyed for 10 workdays, we find that daily OCB is associated with positive affect, but it also interferes with perceptions of work goal progress. Positive affect and work goal progress in turn mediate the effects of OCB on daily well-being. Moreover, employees’ trait regulatory focus influences the strength of the daily relationships between OCB and its positive and negative outcomes. We conclude by discussing theoretical and practical implications of our multilevel model.

In the 30 or so years since Smith, Organ, and Near (1983) coined the term “organizational citizenship behavior” (OCB), research has established OCB as a cornerstone construct in organizational behavior (Organ, 1977; Organ, Podsakoff, & Podsakoff, 2011; Podsakoff, Whiting, Podsakoff, & Blume, 2009). De- fined as “individual behavior that is discretionary, not directly or explicitly recognized by the formal reward system, and in the aggregate promotes the efficient and effective functioning of the organiza- tion” (Organ, Podsakoff, & MacKenzie, 2006: 3), scholars have long focused on the “bright side” of OCB. For example, research has identified a number of potential benefits for individuals who engage in more OCB compared to others (e.g., receiving help from others or better performance appraisals; Lyons & Scott, 2012; Whiting, Podsakoff, & Pierce, 2008).

However, in recent years, scholars have ques- tioned the prevailing belief that OCB is uniformly beneficial, instead suggesting that it may have

a “dark side” (for a review, see Bolino, Klotz, Turnley, & Harvey, 2013). For example, OCB may have detrimental effects on performance and long- run career outcomes for individuals who perform more of this behavior than others (Bergeron, 2007; Rapp, Bachrach, & Rapp, 2013; Rubin, Dierdorff, & Bachrach, 2013). These competing streams of re- search highlight a fundamental tension that exists in the OCB literature exemplified by the question: Is OCB good or bad? In this manuscript, we suggest that a more appropriate question is: For whom is OCB good or bad, and why? Accordingly, our goal is to build a bridge across the gulf separating research on the beneficial and detrimental outcomes of OCB for actors by incorporating both perspectives into one theoretical model. In so doing, we attempt to create consensus between these divergent streams of research.

We focus on the daily, within-individual conse- quences of OCB given the “ongoing, dynamic, and time-dependent” nature of this behavior (Bolino, Harvey, & Bachrach, 2012: 127). Previous within- individual examinations of the consequences to actors of engaging in OCB have primarily focused on

We are grateful to our action editor, Gerry George, and three anonymous reviewers whose supportive and in- sightful suggestions helped us to improve this work.

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its benefits, finding that such behavior is associated with increased positive affect (Conway, Rogelberg, & Pitts, 2009; Glomb, Bhave, Miner, & Wall, 2011; Sonnentag & Grant, 2012). Indeed, Glomb et al. (2011: 214) recommended that managers should view OCB “as a mechanism that promotes employee well-being.” Although there is little evidence of the negative consequences of OCB at the within- individual level (as an exception, Halbesleben & Wheeler, 2011, found a positive bivariate relation- ship between OCB and emotional exhaustion), re- search at the between-individual level suggests that individuals who engage in OCB may face trade-offs with task-related activities (Barnes et al., 2008; Rapp et al., 2013; Rubin et al., 2013). Such trade-offs have implications for actor well-being in work contexts, thus highlighting the importance of si- multaneously considering the benefits and draw- backs of daily OCB.

To model these benefits and drawbacks, we adopt a multilevel, person–situation interactionism frame- work. Specifically, we draw upon the cognitive- affective processing system (CAPS) framework proposed by Mischel and Shoda (1995, 1998), and integrate it with conservation of resources theory (COR; Halbesleben, Neveu, Paustian-Underdahl, & Westman, 2014; Hobfoll, 1989). The resulting in- tegrative model suggests that two mechanisms (re- sourcegenerationandresourceconsumption)account for the effects of OCB on well-being at work (Hobfoll, 1989). Moreover, this model identifies two constructs that respectively represent these two mechanisms, positive affect and work goal progress, and that link OCB with three indicators of well-being at work: emotional exhaustion, job satisfaction, and affective commitment (Ganster & Rosen, 2013; Ilies, Wilson, & Wagner, 2009). We then extend our theorizing across levels of analysis by identifying individual character- istics (in particular, promotion and prevention focus; Higgins, 1997; Lanaj, Chang, & Johnson, 2012) as fac- tors that enhance the benefits and drawbacks of daily OCB. The resulting model allows us to provide an- swers to the questions of why and for whom OCB is beneficial or detrimental (Whetten, 1989).

Overall, our investigation, which responds to calls in the literature to examine the consequences of OCB on a more dynamic basis as well as to identify factors that influence the degree to which OCB is beneficial or costly for individuals (e.g., Bergeron, 2007; Bolino et al., 2013; Spitzmuller, Van Dyne, & Ilies, 2008), makes two significant contributions. First, we show that although engaging in daily OCB is beneficial for actors (Glomb et al., 2011), this behavior also

has costs for employee work well-being. From a theoretical standpoint, the simultaneous exami- nation of the resource-generating and resource- consuming mechanisms linking daily OCB to employee work well-being is important because it provides a more comprehensive test of COR. De- spite being inherently dynamic, studies using COR as a theoretical lens have tended to be static in de- sign and have generally focused only on either resource generation or resource consumption (Halbesleben et al., 2014). Second, and perhaps more importantly, we show that the benefits and costs of OCB are contingent on employees’ trait regulatory focus. Thus, by integrating COR and CAPS, our model illuminates that individual differences may influence whether OCB is resource generating or resource consuming. Our integrative, multilevel model, which we discuss below, is shown in Figure 1.

THEORETICAL OVERVIEW AND DEVELOPMENT OF HYPOTHESES

CAPS is a broad theoretical model that is con- cerned with dynamic within-individual variation in response to events experienced in the workplace as well as with the influence of stable individual characteristics on that variation (Cervone, 2005). According to Mischel and Shoda (1995), people appraise their level of personal resources follow- ing workplace events, and this appraisal process

FIGURE 1 Hypothesized Modela

Promotion Focus

OCB

Positive Affect

Well-Being

Emotional Exhaustion

Job Satisfaction

Affective Commitment

Work Goal Progress

Prevention Focus

a Emotional exhaustion, job satisfaction, and affective com- mitment are conceptualized as indicators of daily well-being at work. OCB, positive affect, work goal progress, and well-being are hypothesized as within-individual relationships. Promotion focus and prevention focus are conceptualized as cross-level moderators.

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activates “cognitive-affective units,” or mental rep- resentations that help employees to assess and respond to the events. Importantly, these “cognitive- affective units” include affective responses, goals, and self-regulatory plans—all of which have rele- vance to workplace events such as engagement in OCB. However, while CAPS recognizes that resource levels have implications for employee well-being (Cervone, 2005; Lazarus & Folkman, 1984), the the- ory is silent about how events such as OCB affect resource levels, and about the mechanisms that link OCB with well-being in work contexts.

To further elucidate these issues, we draw upon COR and integrate this theory with CAPS. COR is similar to CAPS in that it also recognizes the im- portant role of personal resources following events such as OCB (e.g., Lilius, 2012); however, COR adds further specificity to our hypotheses. Its basic tenet is that “individuals strive to obtain, retain, and protect” valued resources (Hobfoll & Lilly, 1993: 129), which has implications for actor well-being. According to COR, daily events such as OCB may both generate and consume personal resources. In addition, COR proposes that resource-generating events are ex- pected to provide comfort and serenity, which should improve well-being, whereas resource-consuming events constitute a threatening and stressful situa- tion, which should reduce well-being (Hobfoll, 1989). As we elaborate below, the integration of CAPS and COR suggests not only that OCB is likely to generate and consume resources in ways that have differential implications for actor well-being at work, but also that individual differences in how people appraise their resources should influence the extent to which the consequences of OCB on well-being at work are pos- itive or negative.

Mechanisms Linking OCB to Actor Well-Being

For the remainder of the manuscript, we focus our theorizing on interpersonal OCB (i.e., helping; see Williams & Anderson, 1991) due to its prevalence in organizations (Grant & Hofmann, 2011), particularly on a daily basis (Glomb et al., 2011). We restricted our investigation to this form of OCB, as opposed to organization- or change-directed OCB (Chiaburu, Oh, Berry, Li, & Gardner, 2011), because prior re- search has identified interpersonal OCB as being associated with both resource generation and con- sumption (Glomb et al., 2011; Lilius, 2012), which is particularly relevant from the standpoint of COR.

The majority of research on the outcomes of OCB has emphasized its interpersonally focused

dimension, been conducted at the between-individual level of analysis, and tended to emphasize benefits that accrue to groups and organizations (e.g., efficiency, sales, and customer satisfaction; Podsakoff et al., 2009; Spitzmuller et al., 2008). More recently, scholars have recognized the ongoing and dynamic nature of OCB (Bolino et al., 2012) and have begun to examine this behavior in within-individual studies. In a similar vein as between-individual re- search, however, the general consensus thus far is that OCB is beneficial for actors. For example, Conway et al. (2009) and Glomb et al. (2011) both found that engaging in daily OCB made helpers “feel good,” in that it was associated with positive affect. Sonnentag and Grant (2012) provided corre- sponding evidence with their investigation of daily perceptions of prosocial impact.1

Although OCB may be beneficial to actors by in- creasing positive affect, extant theory also suggests that it may be costly to actors in terms of progress toward work goals; indeed, Bergeron (2007: 1090) noted explicitly that OCB “may come at the expense of meeting goals.” For this reason, we examine both positive affect and reduced progress toward work goals as dual mechanisms for the effects of OCB on actor well-being at work. From the perspective of CAPS, both positive affect and work goal progress represent “cognitive-affective units” that are acti- vated by the resource appraisal inherent when per- forming OCB (Mischel & Shoda, 1995). Furthermore, COR theory suggests that this appraisal process will highlight both resource-generating and resource- consuming considerations while performing OCB (Hobfoll, 1989). Positive affect and work goal prog- ress are expected to reflect these considerations and to have downstream effects on employee well-being at work, favorably via positive affect and unfavorably via work goal progress.

Well-being, in turn, is an important organizational outcome because it has ramifications for costs,

1 In contrast, findings for negative affect have been negligible. For example, although Glomb et al. (2011) found that courtesy was associated with negative affect, they also found that altruism, which is similar to our con- ceptualization of OCB in the current study, was not sig- nificantly associated with negative affect. Similarly, Dalal, Lam, Weiss, Welch, and Hulin (2009) found a significant, concurrent association between positive affect and in- terpersonal OCB but not between negative affect and in- terpersonal OCB. Thus, we focus on positive affect as our beneficial mechanism of OCB; however, we do control for the effects of negative affect in our analyses.

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productivity, turnover, and employee health (Danna & Griffin, 1999). It is commonly viewed as a broad construct or category of phenomena (Danna & Griffin, 1999; Diener, Suh, Lucas, & Smith, 1999) encompassing a variety of psychological and physi- ological indicators. We focus on three such in- dicators that reflect important states particularly relevant to well-being in work contexts: emotional exhaustion, job satisfaction, and affective com- mitment (for meta-analyses, see Halbesleben, 2006; Judge, Thoresen, Bono, & Patton, 2001; Lee & Ashforth, 1996; Meyer, Stanley, Herscovitch, & Topolnytsky, 2002).

Diener (1984) noted that well-being represents a subjective and emotional assessment of important aspects of a person’s work life, and each of our well- being indicators satisfies these criteria. Emotional exhaustion reflects “prolonged physical, affective, and cognitive strain at work” (Fritz & Sonnentag, 2006: 936) and “is an important marker of employee well-being” (Halbesleben & Wheeler, 2011: 608). Job satisfaction represents an evaluative state resulting from an “appraisal of one’s job or job experiences” (Locke, 1976: 1300) and is the most commonly ex- amined indicator of well-being at work (Diener et al., 1999; Ilies, Schwind, & Heller, 2007). Finally, affec- tive commitment captures an employee’s “emotional attachment to, identification with, and involvement in the organization” (Meyer et al., 2002: 21). Affec- tive commitment is an indicator of work well-being because it reflects employees’ “positive affection toward the organization” (Kehoe & Wright, 2013) and shares conceptual similarity with job satisfaction (Le, Schmidt, Harter, & Lauver, 2010). Collectively, therefore, emotional exhaustion, job satisfaction, and affective commitment are important markers of well-being in work contexts.

Beneficial effects of OCB. OCB is an affiliative endeavor (Lepine & Van Dyne, 2001) that facilitates social cohesiveness and builds reciprocal ties among coworkers (Halbesleben & Wheeler, 2015). Drawing from CAPS and COR, we suggest that one likely ben- eficial outcome of engaging in OCB is a boost to posi- tiveaffect.AccordingtoCAPS,individualsexperience affective reactions to interpersonal events, such as OCB, that have implications for individuals’ resources (Mischel & Shoda, 1995). Although CAPS suggests that positive affect is a likely outcome of OCB, the theory is silent on whether this association will be positive or negative. Accordingly, we draw on COR to identify how OCB will influence positive affect.

From the standpoint of COR, OCB is a positive interpersonal activity likely to improve actors’

positive affect because it generates psychological resources (Bono, Glomb, Shen, Kim, & Koch, 2013; Heaphy & Dutton, 2008; Quinn, Spreitzer, & Lam, 2012). Positive events such as OCB build resources by fulfilling basic human needs such as autonomy and relatedness (Bono et al., 2013). Indeed, theoret- ical work on COR (Lilius, 2012) and empirical evi- dence on OCB posit that the latter improves actor affect because it fulfills one’s needs for relatedness and competence (Weinstein & Ryan, 2010), and be- cause it enhances self-evaluations (Williamson & Clark, 1989). Furthermore, helping is often associ- ated with perceptions of making a difference in others’ lives owing to expressed gratitude from re- cipients, which further improves positive affect (Grant & Sonnentag, 2010). Consistent with prior research linking OCB to positive affect, we hypoth- esize the following:

Hypothesis 1. On a daily basis, engaging in or- ganizational citizenship behaviors is positively related to positive affect.

The affective boost associated with OCB should consequentiallyinfluenceourindicatorsof well-being at work: emotional exhaustion, job satisfaction, and af- fective commitment. With regard to exhaustion, OCB improvesmood, which can “undo”negative states such as stress or strains (Fredrickson, 1998; Fredrickson & Levenson, 1998) inherent to emotional exhaustion. Regarding job satisfaction and affective commit- ment, research on mood congruence suggests that the valence of experienced emotions should influ- ence the valence of retrieved memories and evalua- tions (Bower, 1981; Forgas, 1995). Thus, an elevated positive affective state should improve employees’ assessments of their satisfaction with their job and their commitment to their organization (Dimotakis, Scott, & Koopman, 2011; Judge & Ilies, 2004). Indeed, theories other than COR suggest that positive affect can be a restorative feature of OCB (Fredrickson, 2001; Lilius, 2012; Tice, Baumeister, Shmueli, & Muraven, 2007). Because OCB improves positive affect, and because positive affect is proximal to and improves assessments of well-being, we expect positive affect to mediate the relationship between OCB and indicators of well-being at work:

Hypothesis 2. Positive affect mediates the re- lationship between daily OCB and well-being, specifically (a) emotional exhaustion, (b) job satisfaction, and (c) affective commitment. Detrimental effects of OCB. Despite the poten-

tial for resource gain described above, theory and

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research suggest that engaging in OCB has the po- tential to consume personal resources as well. In- deed, CAPS recognizes work goal progress as a “cognitive unit” likely to be assessed by employees following performance of OCB (Mischel & Shoda, 1995). This is because OCB is a “time-dependent” activity (Bolino et al., 2012: 127), and an actor’s time represents a crucial resource transferred to others when performing OCB (Mueller & Kamdar, 2011). Performance of OCB should trigger evalua- tions of goal progress in actors because—as COR acknowledges—time is among an individual’s most scarce resources (Hobfoll, 1989); indeed, several studies have shown that OCB consumes time and other resources. For example, in a study of helping behaviors in teams, Porter et al. (2003) noted that OCB directed at coworkers involves the transfer of resources from one person to another (see also Porter, 2005). In a follow-up study, Barnes et al. (2008) showed that individuals face a trade-off between completing their own work and helping others when faced with limited time.

Time is a relevant and limited resource because workdays are segmented into a finite number of performance episodes organized around relevant work goals (Beal, Weiss, Barros, & MacDermid, 2005). Individuals are generally driven to make progress to- ward work goals (e.g., Diener & Fujita, 1995), but ac- tivities such as OCB that compete for time come at the expense of that progress, thereby forcing a trade-off between how an individual spends his or her limited time at work (Beal et al., 2005; Zohar, Tzischinski, & Epstein, 2003). For example, Grant and Hofmann (2011) noted that helping predominantly occurs in response to a request for assistance, and thus these requests are likely to be disruptive to ongoing per- formance episodes and reduce the amount of time available for ongoing work-related progress (Beal et al., 2005).

In the aggregate, some individuals may be more capable than others at balancing competing de- mands on their time (Rapp et al., 2013), but, epi- sodically, individuals can generally focus on only one activity at a time (Beal et al., 2005; see also Binnewies, Sonnentag, & Mojza, 2009). Although time spent on OCB may interfere with actual levels of task performance (Beal et al., 2005), even if in-role task performance does not suffer by engaging in higher-than-normal levels of extra-role citizenship, employees may feel that they could have accom- plished more had their scarce resources not been directed away from core duties (Perlow, 1999). For these reasons, we expect that OCB will be

negatively associated with daily progress toward work goals:

Hypothesis 3. On a daily basis, engaging in or- ganizational citizenship behaviors is negatively related to perceptions of work goal progress.

Given the centrality of goal progress to employee well-being (Diener et al., 1999), we expect that per- ceptions of work goal progress are associated with our indicators of well-being: emotional exhaustion, job satisfaction, and affective commitment. OCB takes away from individuals’ ability to make prog- ress toward their work goals, and this may foster perceptions of increased workload and time pres- sures that increase emotional exhaustion (Ilies, Dimotakis, & De Pater, 2010; Mueller & Kamdar, 2011). Supporting this notion, in a semester-long study of undergraduates, Brunstein (1993) found that perceptions of goal progress were positively as- sociated with subsequent well-being (which in- cluded feelings of frustration and depression), but well-being was not associated with subsequent per- ceptions of goal progress. Furthermore, theories of stress other than COR, such as subjective well-being (Diener, 1984) and cognitive appraisal (Lazarus, 1991), also posit that well-being deteriorates when individuals’ resources are taxed and they perceive that they are not progressing toward their goals. In particular, Diener et al. (1999: 284) conceived that “resources may facilitate well-being indirectly by allowing individuals to pursue and attain important goals.”

Furthermore, work goal progress is intricately linked to job satisfaction and affective commitment (Maier & Brunstein, 2001). Indeed, employees use goal progress as a means of evaluating their per- formance and tend to be more satisfied with tasks that allow them to achieve their work goals (Latham & Locke, 1991). Similarly, employees tend to have higher levels of affective commitment for organizations that facilitate progress toward val- ued goals (Meyer & Allen, 1997). Given that OCB reduces work goal progress, and for the reasons reviewed here, we expect that it will have detri- mental effects on emotional exhaustion, job satis- faction, and affective commitment. On the whole, therefore, perceptions of work goal progress are expected to mediate the relationship between OCB and well-being at work. On this basis, we hypothesize:

Hypothesis 4. Perceptions of work goal progress mediate the relationship between daily OCB

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and well-being, specifically (a) emotional ex- haustion, (b) job satisfaction, and (c) affective commitment.

The Cross-Level Moderating Effect of Regulatory Focus

Both COR and CAPS recognize that self-regulation capabilities are likely to influence the consequences of performing OCB (Hobfoll, 1989, 2002; Mischel, 2004; Mischel & Ayduk, 2002). According to COR, people are “motivated to enhance resources and buttress these resources against possible future loss” (Hobfoll, Freedy, Lane, & Geller, 1990: 467). Fur- thermore, one of COR’s main corollaries is that cer- tain personality traits influence reactions to the process of gaining resources and avoiding their loss (Hobfoll et al., 1990). In a similar vein, CAPS suggests that self-regulatory plans and competencies have important implications for people’s internal states (Kammrath, 2012) and may affect consequences of behaviors such as OCB. Specifically, CAPS suggests that individuals self-regulate through the interplay of a “hot” and “cool” system (Cervone, 2005; Mischel, 2004). The hot system reflects quick, emotional re- sponses to environmental stimuli, which parallels the positive affect mechanism described earlier. In con- trast, the cool system reflects more specialized, complex, and contemplative responses to situational triggers, which parallels the work goal-progress mechanism described above.

When taken together, both COR and CAPS sug- gest that an approach- and avoidance-oriented reg- ulatory system is particularly relevant to whether events are interpreted as promoting resource gain or resource loss in an organizational context (Higgins, 1997; Lanaj et al., 2012), and may have implications for the outcomes of OCB. Thus, a motivational ap- proach orientation predisposing individuals to fo- cus on resource gain and positive outcomes should enhance the positive impact of OCB on positive af- fect, whereas a motivational avoidance orientation predisposing individuals to focus on resource loss and negative outcomes should enhance the detri- mental impact of OCB on goal progress. Accord- ingly, we draw on promotion focus and prevention focus as two main approach and avoidance moti- vational systems (Higgins, 1997) likely to impact the strength of the relationship between OCB and its outcomes. We also examine promotion and pre- vention foci because CAPS specifically acknowl- edges these two regulatory competencies as consequential for peoples’ internal states following

interpersonal events (Mischel, 2004; Mischel & Shoda, 1999).

Promotion and prevention foci guide peoples’ strategic pursuits and sensitize them to the presence or absence of desired resources and outcomes. Promotion-focused employees pursue advancement and accomplishment by approaching ideals, whereas prevention-focused employees pursue the fulfillment of duties by avoiding errors and mistakes (Crowe & Higgins, 1997; Lanaj et al., 2012). A high promotion focus tends to make individuals more sensitive to the opportunity for resource gain, whereas a high pre- vention focus tends to make individuals more sensi- tive to the potential for resource loss (Appelt & Higgins, 2010; Higgins, 1997; Liberman, Molden, Idson, & Higgins, 2001). Given these distinct strate- gic orientations, promotion focus should attune em- ployees to positive outcomes associated with OCB, because people with this focus value pursuing resource-generating endeavors, whereas prevention focus should sensitize employees to the complex re- source trade-offs associated with performance of OCB, because people with this focus prefer avoiding resource-threateningendeavors(Higgins,1997;Higgins, Shah, & Friedman, 1997).

Specifically, promotion-focused employees seek out attention and rewards through OCB (Lanaj et al., 2012), which allows them to regulate their needs for growth and advancement in the organization (Neubert, Kacmar, Carlson, Chonko, & Roberts, 2008; Scholer & Higgins, 2010). They also tend to experi- ence higher-intensity positive emotions in the pres- ence of potential gains and success, such as those afforded by OCB (Scholer & Higgins, 2010, 2012). Indeed, one of the hallmarks of promotion focus is the experience of positive emotions when pursing desired end states. Furthermore, performance of OCB fits well with the regulatory orientation of promotion-focused employees because it sustains their desire for status and recognition in the work- place (Brockner & Higgins, 2001; Higgins, 2002). This fit is important because promotion-focused people derive more enjoyment and positive emo- tions from activities that fit their regulatory orienta- tion (Freitas & Higgins, 2002; Higgins, 2002). Hence, positive emotions emanating from performing OCB are likely to be stronger for promotion-focused em- ployees since OCB facilitates pursuit of valued ben- efits and fits well with their regulatory orientation. Thus, we hypothesize:

Hypothesis 5. The daily relationship between engaging in organizational citizenship behaviors

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and positive affect is more positive for in- dividuals who are high (vs. low) in promotion focus.

Unlike promotion-focused employees who pursue energizing activities, prevention-focused employees are more cautious and monitor their environment continuously in an attempt to avoid errors and mis- takes (Carver & Scheier, 1990; Lanaj et al., 2012). Prevention-focused employees prefer maintaining the status quo, fulfilling their in-role responsibilities at work and avoiding unexpected experiences (Lanaj et al., 2012; Scholer & Higgins, 2010). Furthermore, whereas promotion-focused employees may view helping episodes as opportunities for growth and advancement, prevention-focused employees may view them as sources of uncertainty that impose limits on their ability to fulfill job duties. This is be- cause OCB represents a resource-intensive discre- tionary activity that may or may not be recognized by the organization (Organ et al., 2011). Given its po- tential costs and uncertain benefits, OCB increases vigilance about failing at work for prevention-focused employees because they are reluctant to expose themselves to losses and tend to “see the world as a zero-sum game” (Scholer & Higgins, 2012: 73). Ac- cordingly, for prevention-focused employees, en- gagement in OCB is likely viewed as directly inhibiting their progress on work tasks. Indeed, re- search suggests that OCB detracts from employees’ abilities to fulfill their task responsibilities (Barnes et al., 2008), which is particularly alarming for prevention-focused employees who tend to be loss averse. Accordingly:

Hypothesis 6. The daily relationship between engaging in organizational citizenship behav- iors and work goal progress is more negative for individuals who are high (vs. low) in prevention focus.

METHOD

Sample

Our sample was comprised of 82 employees who occupied administrative, service, clerical, or technical positions within their organizations and held a wide range of job titles (e.g., data analyst, epidemiologist, bank teller, and tax attorney). Out of the 82 participants, 66 were Caucasian, 4 were African American, 7 were Hispanic/Latino, and 3 were Asian; 2 participants did not indicate their race. The average age of participants was 43.4 years

(SD 5 11.44), and 68 of the participants were women.

Procedure

First, we sent a recruitment email to employees of a Midwestern university describing the study and requesting their participation. As a means of in- creasing the scope of our recruitment, participants were permitted to forward their recruitment email to friends or colleagues who also wished to participate in the study. We did not offer an additional incentive for participants to do so. In total, 41 (50%) of the participants in our final sample were recruited in this manner. Sixty-five participants (79%) were employees of the university; the rest worked for or- ganizations such as banks, museums, or local gov- ernment agencies.

We collected the data via online surveys hosted by Qualtrics.com. We sent a one-time survey to partic- ipants approximately one week before the start of the daily surveys. This survey contained the measures of our person-level constructs (promotion focus and prevention focus). During the daily portion of the study, participants were sent three surveys each day while they were at work for ten workdays. Because our research questions concerned behaviors that occur throughout the workday, as well as well-being assessed in the evening, participants were required to complete all three surveys (i.e., one full day-level data point) and were compensated accordingly. We paid $50 to participants who completed seven full day-level data points (i.e., completed all three sur- veys on the same day) and $75 to participants who completed ten full day-level data points. We offered makeup days for individuals who missed surveys during the two-week study period. Out of 100 in- dividuals who completed the initial sign-up survey, 82 individuals provided 748 day-level data points out of a possible 820 for a response rate of 91.2%. Sixty-two of the participants requested at least one makeup day during the study period (136 total re- sponses; 18%). These individuals were not sig- nificantly different than the other participants on promotion focus or prevention focus, and, more- over, controlling at level 1 for whether the day-level observation was collected on a makeup day did not alter our results.

We sent the first daily survey at the midpoint of participants’ workday (i.e., at or before participants’ lunch break; Time 1). On average, participants began this survey at 12:02 p.m., after having been at work for 3.95 hours. This survey asked employees to focus

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on their day since arriving at work and assessed en- gagement in OCBs. We further collected a measure of perceived work goal progress and task performance at Time 1 to be used as controls in the analyses. We sent the second survey in the late afternoon and asked the employees to complete the survey before leaving work (i.e., Time 2). This survey asked em- ployees to focus only on the portion of the day since completing the first survey. On average, participants began this survey at 4:21 p.m., after having been at work for an average of 7.95 hours.

The second survey contained the perceived work goal progress and emotional exhaustion measures, as well as a measure of task performance for the after- noon to be used as a control in the analyses. By measuring perceptions of work goal progress in the Time 1 survey and controlling for this initial level in the regressions involving Time 2 work goal progress, we were able to assess change in this variable over the course of the day, as well as how this change influences subsequent well-being. Examining change over the day in this manner alleviates (although not entirely) concerns about the direction of causality for our hypotheses (e.g., Johnson, Lanaj, & Barnes, 2014; Scott & Barnes, 2011). The third survey was sent each evening after the participant left work for the day (i.e., Time 3); on average, participants began this survey at 8:30 p.m. The average time elapsed between the Time 1 and Time 2 surveys was 4 hours and 19 minutes, while that between the Time 2 and Time 3 surveys was 4 hours and 48 minutes.

Daily (Within-Individual) Measures

OCB. We measured participants’ daily OCBs in the Time 1 survey using six interpersonally focused items developed by Dalal et al. (2009). Participants were asked to indicate their agreement with six statements about behaviors they had engaged in since arriving at work that day (1 5 “strongly dis- agree” to 5 5 “strongly agree”). Example statements included “I went out of my way to be nice to someone I work with” and “I tried to help someone I work with.” Coefficient a, averaged across days, was .83.

Positive affect. Consistent with recent within- individual studies examining the relationship be- tween OCB and momentary positive affect, we measured positive affect state in the Time 1 survey (Glomb et al., 2011). Participants responded to a short (five-item) version of the Positive and Negative Affect Schedule scale (Watson, Clark, & Tellegen, 1988) that was validated by Mackinnon et al. (1999) and recently used by Scott, Barnes, and

Wagner (2012). Participants were asked to rate the extent to which they were experiencing each state “right now” (1 5 “very slightly/not at all” to 5 5 “extremely”). Example items used in the scale were “excited” and “enthusiastic.” Coefficient a, averaged across days, was .91.

Perceived work goal progress. Because our par- ticipants were employed in a variety of occupations, they may not only have different goals but also may place a different level of importance on those goals (Austin & Vancouver, 1996). Therefore, we held the content of the goal measure constant and asked about goal progress broadly by adapting the six-item mea- sure used by Wanberg, Zhu, and Van Hooft (2010). At Time 2, participants were asked to report their agreement with six statements regarding perceptions of their work goal progress since their last survey (1 5 “strongly disagree” to 5 5 “strongly agree”). Example statements included “I have made good progress on my work goals” and “Things have not gone well with my work goals” (reverse coded). Coefficient a, aver- aged across days, was .83.

Emotional exhaustion. We measured partici- pants’ level of emotional exhaustion with five items adapted from the emotional exhaustion subscale of the Maslach Burnout Inventory (Maslach & Jackson, 1993). At Time 2, participants were asked to report their agreement with five statements regarding their level of emotional exhaustion since their last survey (1 5 “strongly disagree” to 5 5 “strongly agree”). Ex- ample statements included “I feel emotionally drained from my work” and “I feel frustrated by my job.” Coefficient a, averaged across days, was .94.

Job satisfaction. Consistent with prior daily re- search (e.g., Ilies, Keeney, & Scott, 2011), we mea- sured participants’ level of job satisfaction in the Time 3 survey using four items adapted from Brayfield and Rothe (1951). Participants were asked to report their agreement with these four statements (1 5 “strongly disagree” to 5 5 “strongly agree”) re- garding their level of job satisfaction felt at that mo- ment. Example statements were “I feel enthusiastic about my work” and “I feel fairly satisfied with my job.” Average coefficient a across days was .87.

Affective commitment. We measured partici- pants’ level of affective commitment in the Time 3 survey using six items adapted from Meyer and Allen (1997). Similar to job satisfaction, participants were asked to report their agreement (1 5 “strongly disagree” to 5 5 “strongly agree”) regarding their level of affective commitment felt at that moment. Example statements included“This organization has a great deal of personal meaning to me” and “I do not

2016 421Koopman, Lanaj, and Scott

feel ‘emotionally attached’ to this organization” (reverse-coded). Coefficient a, averaged across days, was .85.

Between-Individual Cross-Level Moderators

Regulatory focus. We assessed promotion focus and prevention focus with the measures developed by Neubert et al. (2008). Example statements for promotion focus included “I spend a great deal of time envisioning how to fulfill my aspirations” and “I focus on accomplishing job tasks that will further my advancement” (1 5 “strongly disagree” to 5 5 “strongly agree”). Example items for prevention fo- cus included “At work, I focus my attention on completing my assigned responsibilities” and “Ful- filling my work duties is very important to me” (1 5 “strongly disagree” to 5 5 “strongly agree”). Co- efficient a for promotion focus was .90, and for prevention focus was .85. Meta-analyses have pre- viously demonstrated that these constructs exhibit a modest positive correlation (p 5 .11) with con- siderable variability in this relationship (Lanaj et al., 2012).

Control Variables

Time 1 perceptions of work goal progress. As previously discussed, we operationalized work goal progress as a change variable to demonstrate how these perceptions decrease as a result of OCB. We measured perceptions of work goal progress at Time 1 in the same way as this construct was measured in the Time 2 survey described above and controlled for it in all analyses involving Time 2 perceptions of work goal progress. Coefficient a, averaged across days, was .88.

Time 1 negative affect. As noted above, the existing research examining the relationships be- tween OCB and affect have generally shown that OCB is associated with positive, but not negative, affect (e.g., Dalal et al., 2009). However, scholars have recommended that positive and negative af- fects should be modeled simultaneously because they may influence each other (Watson, Wiese, Vaidya, & Tellegen, 1999). Additionally, Judge, Erez, and Thoresen (2000) noted that negative af- fect in particular may be an important control when predicting well-being, and so we included a five-item measure of negative affect as a control in all analyses involving positive affect and well- being (Mackinnon et al., 1999; Scott et al., 2012). Example items for the scale were “distressed” and

“upset.” Coefficient a, averaged across days, was .79.

Task performance. It is necessary to take task performance into account when examining the pos- itive and negative consequences of daily OCB. Fail- ing to do so makes it impossible to determine whether our results are due to trade-offs between OCB and task performance on some days but not others. Scholars have increasingly recognized a “clear trade-off” between citizenship behavior and task performance (Rubin et al., 2013: 397). For in- stance, both are facets of overall job performance (Organ et al., 2011; Rotundo & Sackett, 2002) and both represent resource-consuming activities at work (Bergeron, 2007; Hockey, 1997). Accordingly, Beal et al. (2005) suggested that, within individuals, citizenship or task performance episodes occur se- quentially across a day, and the total number that can be performed is finite, given that these activities are “bound by the structural element of time” (Beal et al., 2005: 1055). As recently argued by Becker (2005) and Spector and Brannick (2011), control variables should bemodeled inanalyses if there is areasonable theoretical rationale for their inclusion. Given the interdependent nature of OCB and task performance with regard to resources generated and consumed on a day-to-day basis, we control for daily task perfor- mance in our analyses.

Controlling for daily task performance is also im- portant when examining the effects of OCB on work goal progress. Specifically, in order to fully un- derstand whether OCB interferes with individuals’ ability to accomplish their daily work goals—or what the individual wanted to accomplish on a given day—it is important to partial out what the employee did accomplish on that day (i.e., their level of task performance). Task performance is reflective of pro- ficiency or competence in performing assigned tasks (Griffin, Neal, & Parker, 2007), whereas work goal progress represents an assessment of the current level of accomplishment compared to an aspirational level (Carver, 2004; Wanberg et al., 2010). Indeed, Wanberg et al. (2010: 789) noted that goal progress is often operationalized in experimental studies as a “com- parison of individuals’ current performance with de- sired performance (what has been accomplished in comparison to what the person wants to accom- plish).” For these reasons, we controlled for daily task performance when evaluating the relationship be- tween OCB and work goal progress.

We measured task performance throughout the day (at both Time 1 and Time 2) using the seven- item measure from Williams and Anderson (1991).

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Participants were asked to report their agreement with the seven statements regarding their task per- formance up to that point in the workday (Time 1) and since their last survey (Time 2) along a five-point scale (1 5 “strongly disagree” to 5 5 “strongly agree”). Example statements included “I have per- formed the tasks expected of me” and “I have engaged in activities that directly affect my performance.” Coefficient a, averaged across days, was .87 for both the Time 1 and Time 2 assessments.2

Analyses

Because our study utilized a nested design (mul- tiple days nested within employees), we employed a multilevel path analysis model using Mplus 7.11 to test our hypotheses. Our between-individual cross- level moderators (promotion focus, prevention fo- cus) were modeled at level 2. The within-individual variables (citizenship behavior, positive affect, per- ceptions of work goal progress, emotional exhaus- tion, job satisfaction, and affective commitment) were modeled at level 1 using random slopes. The disturbances between positive affect and percep- tions of work goal progress were allowed to covary, as were the disturbances between our dependent variables, following recommendations from Kline (2005). Following Wang, Liao, Zhan, and Shi (2011) and Wang et al. (2013), control variables (e.g., task performance and negative affect) were modeled with fixed slopes. As recommended by Hofmann, Griffin, and Gavin (2000) and Enders and Tofighi (2007), all level 1 predictors were centered at the individuals’ means (i.e., group-mean centering). Centering at each individual’s mean permits an examination of pure daily within-individual fluctuations by ef- fectively controlling for between-individual con- founds. All level 2 variables were grand-mean centered, and simple slope tests for the moderation hypotheses are provided in the figure notes (see the Results section, below). Following Cohen, Cohen, West, and Aiken (2003), the moderation hypotheses were tested by modeling promotion focus and pre- vention focus as having a cross-level main effect on the outcome variable (positive affect or perceptions of work goal progress), as well as influencing the strength of the relationship between each variable and OCB.

The multilevel path analysis was appropriate for ourmodelasitpermitsasimultaneousexaminationof the competing mechanisms for the benefits and costs of daily OCB thatwepropose.Furthermore,itallowed us to model covariances among the random slopes for testing mediation and using procedures appropriate for multilevel analyses (Bauer, Preacher, & Gil, 2006; Kenny, Korchmaros, & Bolger, 2003). Specifically, to test our mediation hypotheses, we followed recom- mendationsfrom Preacher,Zyphur,andZhang(2010) and utilized a parametric bootstrap to estimate and assess the significance of indirect effects (e.g., Selig & Preacher, 2008). The magnitude of the indirect effect was calculated using the formula from Bauer et al. (2006). We then used a Monte Carlo simula- tion with 20,000 replications to build confidence intervals around the estimated indirect effects. Recent published work has estimated multilevel mediation with the same procedure (da Motta Veiga & Gabriel, 2015; Lanaj, Johnson, & Barnes, 2014; Wang et al., 2013).

RESULTS

Table 1 presents the proportion of variance in each of the level 1 constructs that was at the within- individual level. Our level 1 constructs exhibited considerable variance at the daily level, ranging from 17% to 71%.

Table 2 presents the means, standard deviations, and correlations among the study variables. To es- tablish the uniqueness of our study variables, we first conducted a within- and between-individual confirmatory factor analysis. Specifically, at the within-individual level, we included the six core variables in our model (OCB, positive affect, work goal progress, emotional exhaustion, job satisfac- tion, and affective commitment) as well as task performance. At the between-individual level, we included promotion focus and prevention focus. This model exhibited acceptable fit to the data (x2 5 1611, df 5 805, CFI 5 .91, RMSEA 5 .04, SRMR 5 .05).3 Results of this analysis provide overall sup- port for the distinctive factor structure of our study constructs. A depiction of the results of our multilevel path analysis can be seen in Figure 2,

2 Confirmatory factor analysis results support the dis- tinctiveness of work goal progress and task performance. These analyses are available from the authors upon request.

3 The task performance and work goal progress mea- sures each contained reverse-coded items (two and three, respectively). Schmitt and Stults (1985) noted that these items often cross-load on a separate “negative factor.” To address this, we followed their recommendations and allowed the error terms for these items to covary freely.

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below. We also provide pseudo r-squared values (Hofmann et al., 2000; Snijders & Bosker, 1994) assessing the amount of incremental within- individual variance explained by tests of our hypotheses.

Tests of Hypotheses

Within-individual hypotheses. Figure 2 illustrates the results of our analysis. Supporting Hypothesis 1, we found that engaging in OCB was positively related

to positive affect (g 5 .36, p , .05). Engaging in OCB accounted for a 9% incremental within-individual variance in positive affect. Hypotheses 2a–2c pre- dicted that positive affect would mediate the re- lationship between OCB and the three indicators of well-being: emotional exhaustion, job satisfaction, and affective commitment, respectively. Hypothesis 2a was not supported as positive affect was not sig- nificantly related to emotional exhaustion (g 5 2.06, p . .05) and the 95% confidence interval (CI) for the indirect effect included zero (indirect effect 5 2.017,

TABLE 1 Percentage of Within-Individual Variance among Daily Variables

Constructa Within-Individual Variance (e2) Between-Individual Variance (r2) Within-Individual Variance (%)b

Organizational citizenship (T1) 0.24 0.20 54% Positive affect (T1) 0.47 0.59 44% Negative affect (T1) 0.13 0.05 72% Goal progress (T1) 0.33 0.15 68% Goal progress (T2) 0.31 0.13 71% Emotional exhaustion (T2) 0.38 0.72 34% Job satisfaction (T3) 0.17 0.55 24% Affective commitment (T3) 0.14 0.67 17% Task performance (T1) 0.16 0.15 52% Task performance (T2) 0.16 0.14 53%

a T1 represents measures collected in the Time 1 survey, T2 represents measures collected in the Time 2 survey, and T3 represents measures collected in the Time 3 survey.

b The percentage of variance within individuals was calculated as e2/(e2 1 r2).

TABLE 2 Descriptive Statistics of and Correlations among Study Variablesa

Variableb Mean SD 1 2 3 4 5 6 7 8 9 10 11

Level 1 Variables 1. Organizational

citizenship (T1) 3.64 .46

2. Positive affect (T1) 2.85 .69 .22* 3. Negative affect (T1) 1.20 .37 2.01 2.20* 4. Work goal progress (T1) 3.90 .55 .02 .30* 2.18* 5. Work goal progress (T2) 3.91 .52 2.02 .11* 2.05 .36* 6. Emotional exhaustion (T2) 2.29 .58 .05 2.13* .28* 2.19* 2.23* 7. Job satisfaction (T3) 3.69 .42 .01 .19* 2.16* .10* .14* 2.21* 8. Affectivecommitment(T3) 3.46 .37 2.07 .11* 2.12* .06 .07 2.15* .35* 9. Task performance (T1) 4.04 .38 .14* .25* 2.10* .60* .24* 2.09* .07* 2.05 10. Task performance (T2) 4.08 .37 .06 .19* 2.13* .28* .59* 2.15* .11* .09* .29* Level 2 Variables 11. Promotion focus 3.55 .72 .24* .39* 2.13 .10 .02 2.03 .20 .15 .04 2.03 12. Prevention focus 4.05 .49 .06 .07 .03 .24* .07 2.09 .13 .10 .21 .12 .28*

a Level 1, N 5 748; level 2, N 5 82. Correlations, means, and standard deviations for the level 1 variables represent group-mean centered relationships among the daily variables at the within-individual level of analysis. Level 1 variables were aggregated to provide estimates of between-individual relationships with level 2 variables.

b T1 represents measures collected in the Time 1 survey, T2 represents measures collected in the Time 2 survey, and T3 represents measures collected in the Time 3 survey.

* p , .05

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95% CI [2.055, .019]). Hypothesis 2b was supported, as positive affect was significantly related to job sat- isfaction (g 5 .13, p , .05) and the indirect effect CI excluded zero (indirect effect 5 .024, 95% CI [.019, .071]). Similarly, Hypothesis 2c was supported, as positive affect was significantly related to affective commitment (g 5 .07, p , .05) and the indirect effect CI excluded zero (indirect effect 5 .026, 95% CI [.005, .051]). In sum, positive affect mediated the effects of OCB on job satisfaction and affective commitment, and explained, on average, 2% of incremental within-individual variance in these outcomes.

Supporting Hypothesis 3, we found that engaging in OCB was negatively related to perceptions of work goal progress during the day (g 5 2.06, p , .05). OCB accounted for 5% of incremental within-individual variance in work goal progress. Hypotheses 4a–c predicted that perceptions of work goal progress mediate the relationship between OCB and the three indicators of well-being: emotional exhaustion, job satisfaction, and affective commitment, respec- tively. Hypothesis 4a was supported, as percep- tions of work goal progress were significantly related to emotional exhaustion (g 5 2.23, p , .05) and the indirect effect CI excluded zero (indirect ef- fect 5 .016, 95% CI [.002, .031]). Hypothesis 4b was also supported, as perceptions of work goal progress were significantly related to job satisfaction (g 5 .10, p , .05) and the indirect effect CI excluded zero (indirect effect 5 2.009, 95% CI [2.003, 2.017]).

Finally, Hypothesis 4c was supported, too, as per- ceptions of work goal progress were significantly related to affective commitment (g 5 .05, p , .05) and the indirect effect CI excluded zero (indirect effect 5 2.006, 95% CI [2.002, 2.012]). In sum, perceptions of work goal progress mediated the ef- fects of OCB on the well-being outcomes, and accounted for, on average, an 8% incremental within- individual variance in these outcomes.

Between-individual hypotheses. Turning to our cross-level interaction hypotheses, we predicted that promotion focus would strengthen the positive as- sociation between OCB and positive affect (Hy- pothesis 5) and that prevention focus would strengthen the negative association between OCB and perceptions of work goal progress (Hypothe- sis 6). In support of Hypothesis 5, promotion focus was found to moderate the relationship between OCB and positive affect (g 5 .18, p , .05), such that the positive relationship is stronger for in- dividuals who are high (vs. low) in promotion focus (Figure 3).

In support of Hypothesis 6, prevention focus was found to moderate the relationship between OCB and perceptions of work goal progress (g 5 2.12, p , .05), such that the negative relationship is stronger for individuals who are high (vs. low) in prevention focus (Figure 4). Promotion focus did not moderate the relationship between OCB and perceptions of work goal progress (g 5 .05, p . .05) and prevention focus did not moderate the relationship between OCB and positive affect (g 5 2.06, p . .05). Hy- potheses 5 and 6 were thus fully supported.

Supplemental analyses. We also examined whether promotion focus and prevention focus moderated the mediated relationships hypothesized above. To test for moderated mediation (Edwards & Lambert, 2007), the magnitude of the first-stage co- efficient was calculated as being conditional on the coefficient for the cross-levelmoderator (i.e., at 1/ 2 1 standard deviations; Preacher, Rucker, & Hayes, 2007). We analyzed these relationships using an ex- tension of the procedure for testing mediation de- scribed above (Lanaj et al., 2014). The results of these analyses, presented in Table 3, were largely signifi- cant, suggesting that the mechanisms transmitting the effects of OCB to well-being are contingent on in- dividuals’ level of promotion or prevention focus.

DISCUSSION

OCB is widely viewed as the prototypical exem- plar of positive organizational behaviors (Dutton &

FIGURE 2 Model Resultsa

Promotion Focus

OCB

Positive Affect

Emotional Exhaustion

Job Satisfaction

Affective Commitment

Work Goal Progress

Prevention Focus

.18*

.36*

–.06*

–.06

.13*

.10*

.07*

.05*

–.23*

.07 –.12*

.44*

a Level 1, n 5 748; level 2, n 5 82. OCB and positive affect were both measured in the Time 1 survey following prior research (Conway et al., 2009; Glomb et al., 2011). All regressions involving work goal progress use the Time 2 measure and include a Time 1 measure as a control to assess change. For clarity, control variables are not pictured. Emotional exhaustion was also measured in the Time 2 survey, while job satisfaction and affective commitment were measured in the Time 3 survey.

*p , .05

2016 425Koopman, Lanaj, and Scott

Glynn, 2008; Luthans & Youssef, 2007). As Bolino et al. (2013: 542) noted, OCB has “undeniably posi- tive aspects, and investigations of OCB typically emphasize and highlight these positive features.” Recently, however, scholars have started to examine the negative consequences of OCB (Bolino et al., 2013). So far, these two streams of research remain largely disconnected with regard to consequences of OCB for actors. For example, research on the latter has tended to focus either only on positive outcomes (Grant & Sonnentag, 2010; Sonnentag & Grant, 2012), or only on negative outcomes (Halbesleben, Harvey, & Bolino, 2009; Rubin et al., 2013). This tendency has resulted in a literature preoccupied with answering the question “Is OCB good or bad?” As we demon- strated, the implications for actors engaging in OCB are complex, and so focusing on only one side of the issue risks obscuring the bigger picture. Therefore, in our opinion, a more appropriate question is “For whom is OCB good or bad, and why?” Pursuing an- swers to this question allows for a more veridical picture of the effects that OCB has on actors.

Accordingly, our goal in the current paper was to simultaneously investigate both the bright and dark

sides of OCB. In so doing, we attempted to address the current lack of consensus on whether daily OCB is beneficial or detrimental for actors. Integrating CAPS and COR, we modeled dual mechanisms (one positive and one negative) for the daily effects of OCB on well-being and proposed regulatory foci as important boundary conditions on both mecha- nisms. Constructively replicating prior findings, we showed that OCB is related to positive affect (Glomb et al., 2011). We then extended this work in several ways. First, despite recent theoretical arguments that OCB can also consume resources (Gailliot, 2010; Lilius, 2012), few studies have considered this pos- sibility. Due to its resource-consuming nature, we argued theoretically and then showed empirically that OCB reduces perceptions of work goal progress. Second, we integrated these divergent perspectives of OCB by positioning positive affect and percep- tions of work goal progress as dual mechanisms concurrently transmitting both positive and negative effects of OCB on the well-being indicators of emotional exhaustion, job satisfaction, and affective commitment. We found that OCB improves job sat- isfaction and affective commitment via positive

FIGURE 4 Cross-Level Moderating Effect of Prevention Focus on the Relationship between OCB and Work Goal

Progressa

4.3

4.2

4.1

4

3.9

3.8

3.7

3.6 Low OCB High OCB

Low Prevention Focus

High Prevention Focus

W o

rk G

o a

l P

ro gr

es s

a Work goal progress represents change across the day. Simple slope tests confirmthat the relationship betweenOCB andpositive affect is stronger for high promotion-focus individuals (g 5 2.12, p , .05) than for low promotion-focus individuals (g 5 .00, p . .05).

FIGURE 3 Cross-Level Moderating Effect of Promotion Focus on the Relationship between OCB and Positive

Affecta

4.4

4.2

4

3.8

3.6

3.4

3.2

3 Low OCB High OCB

Low Promotion Focus

High Promotion Focus

P o si

ti v e

A ff

ec t

a Positive affect was measured in the Time 1 survey. Simple slope tests confirmthat the relationship betweenOCB and positive affect is stronger for high promotion-focus individuals (g 5 .49, p , .05) than for low promotion-focus individuals (g 5 .23, p , .05).

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affect. Simultaneously, it increases emotional ex- haustion and deteriorates job satisfaction and af- fective commitment via perceptions of work goal progress. Finally, we modeled regulatory focus as exerting a cross-level moderating effect on these mechanisms. We found that promotion focus en- hances the positive relationship between OCB and positive affect, whereas prevention focus enhances the negative relationship between OCB and percep- tions of work goal progress. Supplemental analyses further revealed that regulatory focus moderates most of the indirect effects of OCB on the well-being outcomes.

Overall, our research serves as an important il- lustration of the paradox faced by employees per- forming OCB. In spite of recent recommendations that OCB be viewed as a mechanism that promotes well-being (Glomb et al., 2011), our findings reveal that the situation is not so cut and dry. For example, although OCB can improve well-being at work, we also show that it can reduce it as well. Thus, while it appears that OCB’s effects do endure beyond fleeting emotional experiences, these effects appear to be quite complex. Moreover, there are important bound- aries to these conclusions that must be recognized. For promotion-focused individuals, there are more favor- able implications of performing OCB for well-being. However, for prevention-focused individuals, our re- sults suggest that engaging in OCB is more likely to reduce well-being.

Interestingly enough, this paradox extends beyond research on OCB. Of late, scholars have identified a number of “positive” constructs that, upon closer inspection, appear to have darker aspects to them. For example, Baer et al. (2015) recently showed that experiencing trust at work had both positive and

negative implications for employee emotional ex- haustion. Similarly, Johnson et al. (2014) found that enacting fair interpersonal behaviors replenished actors’ resources whereas enacting fair procedural behaviors depleted resources. When viewed through the lens of self-regulatory theories such as COR and ego depletion, constructs such as helping (and po- tentially others) may have more complicated effects than originally believed. The future of “dark side” research, therefore, appears to be bright indeed.

Theoretical and Practical Implications

By viewing OCB through the lenses of both COR and CAPS, we were able to obtain a richer picture of the effects that OCB has on actors. OCB has impli- cations for personal resources, and the way in which individuals appraise their resources influences whether OCB tends to be beneficial or detrimental for actors. Both theories recognize the importance of personal resources, and their integration helps elu- cidate the complexity of daily OCB. In particular, COR provides theoretical grounding for the resource- generating and resource-consuming nature of OCB (Hobfoll, 1989), whereas CAPS recognizes that be- cause traits and states operate jointly, a multilevel approach is needed to more fully understand the consequences of an episodic behavior such as OCB because its effects depend, in part, on stable indi- vidual differences (Mischel & Shoda, 1995).

Our work enriches COR theory in three important ways. First, although COR is inherently dynamic, the majority of studies utilizing this theory are not longi- tudinal in nature (Halbesleben et al., 2014). Thus, we expand the scope of this theory by examining a prev- alent daily phenomenon that has implications for

TABLE 3 Supplemental Moderated Mediation Resultsa

Outcome

Promotion Focus Prevention Focus

High Low Difference High Low Difference

Upper Lower Upper Lower Upper Lower Upper Lower Upper Lower Upper Lower

Emotional exhaustion

.024 2.077 .014 2.038 .010 2.051 .053 .010 .022 2.017 .058 .001

Job satisfaction .095 .026 .053 .006 .064 .006 2.006 2.027 .006 2.011 2.001 2.028 Affective

commitment .068 .006 .038 .002 .043 .001 2.002 2.019 .002 2.008 .001 2.018

a “Positive affect” represents the mechanism that is moderated by promotion focus; “perceptions of work goal progress” represents the

mechanism moderated by prevention focus. CIs were calculated with an extension of the method for testing mediation (Lanaj et al., 2014). Moderated mediation is supported when the CI for the difference in the conditional indirect effects excludes zero (Preacher et al., 2007). Values in bold type show where the CI excludes zero.

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employee personal resources, and contribute to re- cent work applying COR in a daily context (e.g., Bono et al., 2013). We go further by also simultaneously modeling both resource-generating and resource- consuming processes associated with COR, and, in so doing, respond to a call by Halbesleben et al. (2014) to provide a more comprehensive test of this theory by modeling both mechanisms. Second, we further contribute to COR through the integration of CAPS. The resulting framework from this integration en- hances the scope of both theories by connecting the disparate literatures from which they evolved sepa- rately. Finally, we contribute to COR by extending the range of outcomes associated with this theory to in- clude multiple indicators of employee well-being at work. Our work also enriches CAPS in that although this theory acknowledges that interpersonal events have implications for individuals’ goals, affective states, and well-being, it is not specific about how such events influence actors. Our integration of this theory with COR, therefore, adds further specificity to CAPS regarding why events influence perceptions of goals and affective states, as well as why those pro- cesses subsequently influence well-being at work.

Furthermore, we contribute to both theory and research by taking an actor perspective on the effects of OCB. This perspective is under-investigated in the OCB literature as most of this research focuses on outcomes to the recipient, the group, or the organi- zation (Spitzmuller et al., 2008). The limited re- search that has examined the effects of OCB on the actor has predominantly focused on its positive consequences, but, as shown in the present work, OCB has negative consequences as well. Investigat- ing both positive and negative effects of OCB there- fore extends our current understanding of how and why OCB helps and hurts actors.

Beyond research and theory on OCB, we also con- tribute to the literature on regulatory focus. Re- searchers have paid little attention to these constructs in a daily within-individual context; however, our re- sults suggest that promotion and prevention foci have important implications for the way in which OCB en- gagement is evaluated by actors. Moreover, by identi- fying regulatory focus as a key variable implicated by both COR and CAPS, we extend the conceptual do- mainoftheseconstructsbylinkingthemwiththelarger literature on these two theories. Our work therefore serves as a catalyst for further examinations of regula- tory focus as a cross-level moderator in within-person contexts as motivated by COR and CAPS.

Our study has several practical implications as well. Although there are benefits to engaging in OCB

(e.g., improved mood; Glomb et al., 2011), managers need to be aware that creating pressure for em- ployees to engage in high levels of OCB may in- advertently do a disservice to actors, and this is particularly the case for those with certain pre- dispositions (e.g., prevention focus). This is espe- cially important given the relationship between engaging in OCB and performance evaluations (Allen & Rush, 1998; Podsakoff et al., 2009). In- deed, in some professions or organizations, citi- zenship may be common and expected. In these contexts, organizations may do well to implement programs that monitor employees’ exhaustion and that promote well-being (e.g., Sheldon & Lyubormirsky, 2004). For example, recent work shows that focusing on the prosocial impact of helping events (e.g., through positive reflection) may replenish resources(e.g., Bono et al., 2013). Organizations, therefore, may buffer the negative events of helping by encouraging em- ployees to reflect on the benefits that their help had for others at work.

Moreover, organizations that value citizenship may benefit from selecting on individual differences that make employees less vulnerable to the resource- consuming effects of OCB, such as promotion focus. Alternatively, organizations should be wary of plac- ing prevention-focused employees in positions where they would enact high levels of OCB (e.g., such as helping a newcomer adjust to the workplace). Man- agers, therefore, ought to recognize that individual differences will affect the daily resources and well- being of employees at work. Furthermore, organiza- tions could implement policies and procedures that prime regulatory focus in employees. For example, leaders who want to enhance the benefits of OCB may want to induce a promotion focus in their employees by emphasizing learning and advancement, and avoid inducing a prevention focus by refraining from bringing attentions to the severity of making errors and mistakes at work (Kark & Van Dijk, 2007).

Strengths, Limitations, and Directions for Future Research

Our study has several strengths and limitations that should be recognized and inform future research. For example,our data were collected via self-reports, and, while it is reasonable to argue that participants are a good source for reports of citizenship behaviors and other daily variables (e.g., due to limited observa- tional opportunities by others), reasonable concerns remain about common method variance (CMV; Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). We

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therefore took several precautions to reduce this as well as potential reverse causality concerns.

First, we controlled for morning levels of per- ceived work goal progress in the analyses involving afternoon levels of this construct. This allowed us to examine change in this variable as a function of OCB. Similarly, we controlled for morning levels of nega- tive affect in the analyses involving positive affect. Both empirical strategies alleviate (albeit not en- tirely) concerns of CMV (Scott & Barnes, 2011). Second, we separated the measurements of our study variables across three points in time, and, in the an- alyses, controlled for other related constructs such as task behavior. Both of these approaches additionally help to mitigate concerns of CMV and alternative explanations. Third, we mean-centered all of our daily variables at the individual level, which effec- tively controls for between-individual confounds such as response tendencies and stable traits. Last, CMV is an unlikely explanation for the moderation results that we observed here (i.e., Siemsen, Roth, & Oliveira, 2010). Nevertheless, future research could improve on our design by, for example, collecting observer ratings of daily OCB.

A second limitation of our work is that, although we proposed and tested mediating and moderating mechanisms for the effects of OCB on emotional ex- haustion, other processes that we did not disentangle may also influence these effects. For example, it may be that focusing on the benefits to the recipient or anticipating gratitude could be restorative through experienced pride and contentment for employees performing OCB. Alternatively, expressions of in- difference or displeasure by recipients may exacer- bate the effects of OCB on well-being for actors. In terms of mediators, it could be that feelings of guilt aroused by ignoring in-role responsibilities in order to help a coworker may also mediate the effects of OCB on well-being.

Furthermore, although we showed that well-being on a given day can be affected by OCB, we were un- able to examine potential next-day effects; our sam- ple size dropped dramatically in this lagged analysis and so we could not examine these effects with confidence. This would be a valuable area for future research, however. For example, it may be that neg- ative effects spiral such that individuals experienc- ing diminished well-being may perform more OCB to combat these feelings (Glomb et al., 2011; Halbesleben & Wheeler, 2011). In a similar vein, re- cent research suggests that OCB promotes sub- sequent OCB (Lemoine, Parsons, & Kansara, 2015), which may be due to increased well-being. These are

interesting research questions that we hope will be addressed in future research.

A third potential limitation of the study is that most of our study variables had mid-level means with relatively low standard deviations. Impor- tantly, these standard deviations represent only the within-individual variation in these relationships, and thus our effects are likely conservative compared to a sample with larger variance on these constructs. That said, it is possible that the nature of our re- lationships could change at high or low levels of the outcome (Pierce & Aguinis, 2013), and we invite fu- ture research to explore potential boundaries to our findings at extreme values of well-being.

A fourth limitation is that we did not examine specific features of OCB events. Citizenship events may vary in the extent to which they are complex, novel, or routine, and all these features are likely to influence whether OCB is resource consuming or generating. Helping with a routine problem, for ex- ample, is likely to take less time and require less ef- fort than helping with a complex and new problem. Again, given our operationalization of OCB, the re- sults presented here are likely an underestimation for the impact of OCB on well-being. Future research, therefore, ought to examine OCB features as moder- ators for the effects of OCB on outcomes.

Related to this point, we examined only interper- sonally focused OCB and not organizationally focused or change-focused OCB (Williams & Anderson, 1991). Although our measure of OCB is similar to others uti- lized in daily studies (e.g., Johnson et al., 2014), future researchisinvitedtoreplicatethesefindingswithitems that directly tap into the time and resource intensity that different OCB acts may entail. Indeed, an anony- mous reviewer of this paper noted that the in- terpersonally focused items are relatively mild in natureandsoperhapscitizenshipbehaviorsdirectedat the organization or toward change efforts are more in- tense or time-consuming. Future research could ex- amine these forms of OCB to determine whether they have similar implications for well-being and whether they operate via the same mechanisms.

A fifth limitation of our study is that, although regulatory focus was theoretically identified by COR and CAPS as being relevant to our model, there are other individual characteristics that may also be relevant. For example, extraversion or positive af- fectivity could enhance the positive affect experi- enced after performing OCB (Glomb et al., 2011), whereas neuroticism or negative affectivity may further reduce perceptions of work goal progress. Future research would benefit from an in-depth

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investigation of the individual boundary conditions that influence whether OCB is experienced as being beneficial or detrimental to the actor.

Finally, OCB may have other positive or negative consequences for the actor. Future research could build on our work by expanding the range of mea- sures of well-being to consider physiological (i.e., blood pressure) and behavioral ramifications. For example, it would be interesting to investigate whether well-being due to OCB has downstream ef- fects on behaviors at home (such as helping one’s spouse or children) or at work (such as reciprocating by helping others). Another potential direction would be to consider whether the well-being outcomes associated with citizenship behavior have further downstream negative consequences. For example, performance of OCB may promote subsequent de- viant behavior because individuals may feel a moral license to withdraw effort or to engage in deviance [Klotz & Bolino, 2013; Yam, Klotz, He & Reynolds (2016)]. It is unclear, however, whether the assess- ment of a moral license to engage in deviant behavior istheresultof individualsfeelingthattheyhave more, or fewer, resources attributable to performing OCB. Overall, it is our hope that the current work will contribute to the important conversation on the pos- itive and negative consequences of engaging in OCB.

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Joel Koopman ([email protected]) is an assistant pro- fessor of management in the Carl H. Lindner College of Business at the University of Cincinnati. He received his PhD from Michigan State University. His research interests include organizational justice, employee well-being, and research methodology.

Klodiana Lanaj ([email protected]) is an assistant professor of management in the Warrington Col- lege of Business Administration at the University of Flor- ida. She received her PhD from Michigan State University. Her research focuses on leadership, team performance, and motivation and self-regulation.

Brent A. Scott ([email protected]) is an associate pro- fessor of management at the Eli Broad College of Business at Michigan State University. He received his PhD from the University of Florida. His research interests include mood and emotion, organizational justice, and employee well- being.

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