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Keywords:

  • affect;
  • belief in a just world;
  • intraindividual processes;
  • organizational citizenship behavior;
  • social comparisons

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

Research that has sought to understand why employees engage in organizational citizenship behaviors (OCB) has concentrated on between-person variables, typically ignoring intraindividual influences. Accordingly, we know much about who engages in OCB, in general, but know relatively little regarding under what circumstances people engage in OCB. By integrating social comparison with affective events and just-world theories, we propose and test a dynamic model wherein directional social comparisons are expected to have direct (automatic-motivational) and indirect (affective) intraindividual effects on OCB. The hypotheses were tested using multilevel modeling on 1076 observations from 99 participants that were collected via an interval-contingent experience sampling methodology. The results provide support for the hypotheses that social comparisons are related to OCB through positive affect and the direct effects of social comparisons on OCB are moderated by beliefs in a just world. Theoretical and practical implications are discussed. Copyright © 2011 John Wiley & Sons, Ltd.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

Organizational citizenship behavior (OCB), or extra-role behavior not formally required by organizations that serve to benefit the organization and its members (Organ, 1988; Van Dyne, Cummings, & McLean Parks, 1995), remains a central concern for organizational researchers (Organ, Podsakoff, & MacKenzie, 2006; Podsakoff, MacKenzie, Paine, & Bacharach, 2000). Such interest is hardly astonishing, given that OCBs are inexorably linked to organizational performance and profitability (Podsakoff & MacKenzie, 1997) and are considered to be one of the three main components of individual job performance (Rotundo & Sackett, 2002). To understand OCB, researchers have focused on relatively stable and enduring antecedents, with numerous studies documenting attitudinal, task, organizational, and leadership factors that drive OCB, in general (Organ & Ryan, 1995; Podsakoff et al., 2000).

Although the use of between-person designs has produced significant gains in our knowledge, much remains to be done in understanding what leads to OCB (Podsakoff et al., 2000). For example, a recent review of OCB research has characterized the field as “showing signs of staleness, particularly with respect to research aimed at untangling the motivational basis for OCB” (Zellars & Tepper, 2003, p. 396). Specifically, it has been lamented that prior OCB research has failed to examine new motivational and affective frameworks, which could both advance our understanding of the construct and reinvigorate the field (Zellars & Tepper, 2003). Moreover, prior OCB research has typically adopted a social exchange theory view (e.g., Blau, 1964; Organ et al., 2006) and examined relatively static proxies of social exchange such as high levels of leader-member exchange, perceived organizational support, or job satisfaction (e.g., Kamdar & Van Dyne, 2007; Lester, Meglino, & Korsgaard, 2008; Podsakoff et al., 2000). Although this approach to the study of OCB has been effective in explicating why some employees are more likely to engage in OCB than others in general, it does little to explain the substantial day-to-day fluctuations in behavior within an employee. That is, with few exceptions (e.g., Dalal, Lam, Weiss, Welch, & Hulin, 2009; Ilies, Scott, & Judge, 2006) researchers have been investigating who will engage in OCBs while ignoring the question of under what circumstances employees engage in these behaviors.

As an initial step towards addressing these gaps in the literature, we examine OCB as a temporally dynamic construct focusing on how intraindividual motivational and affective processes can predict OCB on a daily basis. We focus on a novel intraindividual antecedent of OCB: Social comparisons, which theory suggests should have both motivational and affective consequences. Social comparisons, which refer to the “process of thinking about information about one or more other people in relation to the self” (Wood, 1996, p. 520), are universal social phenomena which pervade nearly all aspects of human social interactions (Brickman & Bulman, 1977). In the present paper, we integrate social comparison models with Affective Events Theory (AET; Weiss & Cropanzano, 1996) and just-world theory (Lerner, 1978), suggesting that social comparisons should be related to OCB through both motivational and affective channels. In line with these theories, we present a model outlining direct (motivational) and indirect (affective) effects of social comparisons on OCB, positing belief in a just world as a moderator of the motivational effects of social comparisons (see Figure 1). Our hypotheses are subsequently tested using a daily diary design, where each participant completes daily measures over a period of time.

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Figure 1. Heuristic model of study hypotheses

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A diary study design is required as the variables and processes of interest are not enduring and stable, but instead are episodic and dynamic in nature; AET, in particular, emphasizes the dynamic relation between events, affect, and behavior (Weiss & Cropanzano, 1996). Moreover, OCB is best understood as a temporally dynamic state that fluctuates meaningfully over time: A person can perform many OCBs on one occasion, and none on a different one. Specifically, OCB fits within a three-component model of job performance alongside counterproductive behaviors and task behaviors (Rotundo & Sackett, 2002), and job performance behaviors are believed to be discrete and episodic in nature (e.g., Beal, Weiss, Barros, & MacDermid, 2005; Motowidlo, Borman, & Schmit, 1997). This means that job performance behaviors have considerable within-person variability and, as such, between-person designs will not adequately capture the full nature of the construct. Moreover, OCB has been specifically defined as affect-driven behavior (e.g., Dalal et al., 2009; Ilies et al., 2006; Spector & Fox, 2002), which according to AET should be examined intra individually because affect-driven behaviors are inherently highly variable and short in duration (Weiss & Cropanzano, 1996).

Recent empirical work provides evidence to support the conceptualization of OCB as an episodic behavior by demonstrating that it has substantial within-person variability and can be meaningfully predicted within-people (e.g., Dalal et al., 2009; Ilies et al., 2006). The fact that OCB has sizable within-person variability means that the same person will engage in OCB to varying degrees at different times. In order to examine OCB at the appropriate level of analysis, our study is a within-person examination that complements more traditional between-person examinations.

Organizational Citizenship Behavior

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

OCB research has a long history, spanning over a quarter of a century beginning with papers by Organ and colleagues (Bateman & Organ, 1983; Smith, Organ, & Near, 1983), which in turn was inspired by Barnard (1938) and Katz and Kahn (1966; see Organ et al., 2006, for a review). Although work on OCB has been examined under various rubrics including contextual performance (Borman & Motowidlo, 1993), prosocial organizational behavior (Brief & Motowidlo, 1986), and extra-role behavior (Van Dyne et al., 1995), Organ and colleagues (2006) suggest these perspectives commonly refer to discretionary employee behaviors that ultimately contribute to organizational functioning.

Given the benefits of high levels of OCB to organizations and employees, numerous studies have focused on the prediction of OCB (Zellars & Tepper, 2003). The vast majority of these studies have drawn upon social exchange theory as the basis for their predictions. In accordance with norms of reciprocity (Blau, 1964; Gouldner, 1960), OCB is typically viewed as employees disbursing positive behaviors in response to leaders or organizations fostering positive attitudes (e.g., job satisfaction, justice) and work environments (e.g., positive feedback, satisfying work, or supportive leadership; see Podsakoff, MacKenzie, Moorman, & Fetter, 1990, for a review). Indeed, a recent review of empirical research on OCB found virtually all studies reviewed invoked social exchange principles in justifying their predictions (Zellars & Tepper, 2003), or proposing moderators of the effects of social exchange (e.g., Kamdar, McAllister, & Turban, 2006).

More recently, however, researchers have begun to take a broader perspective on why individuals engage in OCB. For example, studies have begun to examine how impression management or prosocial motivations (e.g., Bolino, 1999; Rioux & Penner, 2001), personality (Ilies, Fulmer, Spitzmuller, & Johnson, 2009; Kamdar & Van Dyne, 2007), role perceptions (e.g., McAllister, Kamdar, Morrison, & Turban, 2007; Morrison, 1994; Tepper, Lockhart, & Hoobler, 2001; Van Dyne, Kamdar, & Joireman, 2008), and positive affect (Ilies et al., 2006) influence OCB levels. Such work has begun to answer calls for OCB researchers to move beyond social exchange frameworks, highlighting self-relevant motivational processes and affective influences as areas in need of development (Zellars & Tepper, 2003). Consistent with this work and to answer the call for studies investigating motivational frameworks beyond social exchange, we propose social comparisons as novel antecedents of whether individuals engage in OCB. Below, we introduce the concept of social comparisons and outline how social comparisons may influence OCB.

Social Comparisons

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

Introduced by Festinger (1954), the topic of social comparisons remains among the most fertile research fields today (Goodman & Haisley, 2007). Festinger originally postulated that humans possess a fundamental drive to evaluate their opinions and abilities and, in the absence of objective physical standards, will evaluate themselves against similar others (Festinger, 1954). This drive is theorized to be biologically rooted and evolutionarily adaptive insofar as it allows the individual to size up his/her group status and prevents excessive specialization and competition within groups (Beach & Tesser, 2000; Buunk & Mussweiler, 2001). In this respect, social comparisons perform an important function by allowing individuals to assess their relative position within groups; this knowledge subsequently assists the individual in successfully navigating the social environment.

Social comparison theory (Festinger, 1954) originally proposed a unidirectional upward drive whereby the individual looks to superior others for inspiration and self-improvement (Collins, 1996; Lockwood & Kunda, 1997). In other words, a basic assumption of Festinger's initial conceptualization of social comparisons was that individuals will be driven to compare upwards against superior others. However, subsequent research on social comparisons has found this is not always the case. In particular, while comparisons with those doing better can be informative, such comparisons can also be highly threatening to the individual, in that they also suggest the individual is doing poorly (relatively speaking) compared to others (Brickman & Bulman, 1977).

Such findings subsequently spurred research on downward comparisons, or comparisons with others who are worse off, as a method of gathering non-threatening information about the self (Wills, 1981). Following decades of research, we now know that individuals engage in both upward and downward comparisons, and that such comparisons occur on a daily basis (Olson & Evans, 1999; Wheeler & Miyake, 1992). Studies have shown that the two types of comparisons represent empirically separate constructs, with the frequency of upward and downward social comparisons being positively related (Buunk, Zurriaga, Gonzalez-Roma, & Subirats, 2003); interestingly, each comparison type typically has unique and often contradictory effects on outcomes such as well-being, job satisfaction, affective commitment, and job search behaviors (Brown, Ferris, Heller, & Keeping, 2007; Buunk & Gibbons, 2007; Suls & Wheeler, 2000).

While it is now widely accepted that individuals engage in both upward and downward comparisons in their daily life, whether or not the effects of such directional comparisons on an individual's emotions, self-evaluations, and behaviors are uniformly negative or positive has been debated. Intuitively, one would imagine that the self-relevant implications and emotional effects of upward comparisons would be negative, given they involve comparing oneself against better-off individuals; similarly, downward comparisons seem more likely to produce beneficial boosts to one's ego and affect (Wills, 1981). Such effects are termed contrast effects in that they suggest that comparisons, regardless of direction, emphasize the separateness (or contrast) between the comparer and the comparison target. As such, comparing upwards puts one in contrast to someone better off, while comparing downwards puts one in contrast to someone worse off. Yet research suggests that both upward and downward comparisons have the potential to produce beneficial or detrimental effects on mood, attitudes, and evaluations (see Collins, 1996, for a review). For example, an upward comparison can be inspiring if one believes they could achieve that status (Lockwood & Kunda, 1997), while a downward comparison may be depressing if one believes they could become like the comparison target (Mussweiler & Strack, 2000). These effects have been termed assimilation effects in that they highlight potential similarities between the comparer and the comparison target (Collins, 1996, 2000).

The environment is one important factor that can influence whether or not comparisons produce either assimilation or contrast effects (Crosby, 1976; Gilbert, Giesler, & Morris, 1995; Staple & Koomen, 2005). As such, competitive environments have been argued to facilitate contrast effects (Collins, 2000). Work by Mussweiler suggests one reason why this may be so. He has argued that social comparisons simultaneously give rise to assimilation and contrast mechanisms by activating knowledge about the self that is either consistent with the comparison target (i.e., promoting assimilation effects) or in contrast to the comparison target (i.e., promoting contrast effects; Mussweiler & Strack, 2000). However, the extent to which one mechanism dominates the other depends on the target: When the target is seen as someone separate from oneself (e.g., an out-group member), the individual is seen as a reference point against which oneself is contrasted against (promoting contrast effects; Mussweiler & Bodenhausen, 2002). Given competitive environments foster a sense of individual accomplishment in comparison to other individuals (Collins, 2000), competitive environments are hence more likely to produce contrast effects. Consistent with this, recent studies manipulating competitive versus cooperative environments (Staple & Koomen, 2005) or inducing participants to focus on themselves versus others (Stapel & Koomen, 2001) have found support for the prediction that competition breeds contrast effects.

Based on this, we argue that social comparisons in organizational settings are likely to produce contrast, not assimilation, effects. Organizations have long been conceptualized as fundamentally competitive and self-interested environments (Smith, 1776/1994) and hence are likely to cause one to focus on his or her own achievements in contrast to others. Supporting this perspective, prior research has found that exposure to organizational paraphernalia (e.g., boardroom tables) activates thoughts and behaviors associated with competition (Kay, Wheeler, Bargh, & Ross, 2004). As a result, contrast effects should be the typical outcomes associated with social comparisons in organizations (Brown et al. 2007), whereby upward comparisons generate negative outcomes and downward comparisons generate positive outcomes.1

In the present paper, we examine social comparisons as antecedents of OCB. While past research has not examined social comparisons with respect to OCB, a review of the social comparison literature suggests two manners in which social comparisons may influence OCB: Through direct and indirect effects.

Direct effects of social comparisons on OCB

A direct effect of social comparisons on OCB is suggested based on social comparisons' ability to increase the accessibility of self-relevant information (Mussweiler & Strack, 2000). As reviewed above, when comparing upwards or downwards against individuals, the targets of comparisons act as reference points against which one is evaluated. In line with contrast effects, comparing upwards should make negative information about the self accessible, while comparing downwards should render positive information about the self accessible. For example, if a contrast comparison with another employee indicates that he or she is a better performer or more advanced than oneself, information representing the self as deficient, unaccomplished, incompetent, or unworthy should be activated. A contrast comparison with an employee who is a poorer performer or otherwise worse off than oneself, however, should activate information representing the self as accomplished, competent, and worthy.

In activating such positive and negative self views, social comparisons are likely to have direct effects on OCB. Previous research supports the notion that priming information can have direct, unmediated effects on an individual's behavior (Bargh, Chen, & Burrows, 1996); indeed, such effects are argued to be pervasive and occur relatively automatically and unconsciously (Bargh & Williams, 2006). In particular, individuals are posited to behave in a manner consistent with the information that has been activated. For example, Bargh and colleagues (1996) found that exposing participants to materials that primed rude or elderly concepts resulted in participants being more likely to interrupt experimenters or move more slowly, consistent with stereotypes of rude and elderly individuals. Consistent with this, we argue that the self-relevant information activated by upwards and downwards social comparisons will motivate individuals to engage in less or more OCBs, respectively. That is, when an individual compares downwards, information associated with one's positive qualities is activated; given one of the major impetuses for engaging in OCB is the prosocial desire to be a “good soldier” (Grant & Mayer, 2009; Moon, Kamdar, Mayer, & Takeuchi, 2008; Organ, 1988; Rioux & Penner, 2001; cf. Bolino, 1999), we argue that such activation should result in a greater tendency to engage in OCB, or behaviors consistent with the “good self” (or “good soldier”) activated by downward comparisons. Similarly, upward comparisons activate information associated with perceiving oneself negatively such as being incompetent or unable, and hence one will be more likely to behave consistent with the “bad self” (or “bad soldier”) activated by upward comparisons.

To summarize, we contend that upward (downward) social comparisons render negative (positive) self-relevant information more accessible, which ultimately motivates individuals to engage in behaviors consistent with the activated information. More formally, we hypothesize the following:

Hypothesis. Hypothesis 1: Within-person, upward social comparisons will be negatively related to OCB.

Hypothesis. Hypothesis 2: Within-person, downward social comparisons will be positively related to OCB.

To this point, we have argued that social comparisons activate self-relevant information, which implicitly induces OCB. However, it is also possible that social comparisons may not be equally likely to activate self-relevant information for all individuals. In particular, we suggest that the extent to which individuals possess a belief in a just world (BJW) will moderate the direct effect of social comparisons on OCB.

Just-world theory (Lerner, 1978, 1980) states that people have a fundamental need to believe that the world is a fair and orderly place where people get what they deserve. Put simply, BJW reflects the extent to which one believes that “good things tend to happen to good people and bad things to bad people” (Furnham, 2003, p. 795). Although this need is thought to be universal (Lerner, 1980), research indicates that the magnitude of this belief differs across individuals (e.g., Dalbert, 1999; Lipkus, 1991). These individual differences, in turn, have been associated with stable differences in an individual's behaviors and beliefs (for reviews see Furnham, 2003; Hafer & Begue, 2005).

Notably, theory and empiricism suggests that differences in BJW should influence the extent to which self-relevant concepts are activated following outcomes. From a theoretical standpoint, given BJW suggests that an individual “gets what he or she deserves,” individuals who strongly endorse BJW will be more likely to view outcomes as carrying self-relevant information, as what one “gets” implies what the self “deserves.” That is, a positive outcome conveys to an individual who believes in a just world that he or she is a good person deserving of positive outcomes. However, individuals who do not believe in a just world view the world as characterized by randomness where events have no bearing whatsoever on the kind of person one is or is not (Lerner & Miller, 1978). Thus, outcomes carry no self-relevant implications.

Such a contention is consistent with past empirical work. For example, studies have shown that people who have a strong BJW are more likely to make internal (i.e., self-based) attributions, while people with a weak BJW are more likely to make external (i.e., non-self-based) attributions (Hafer & Correy, 1999). Similarly, Hafer and Olson (1998) found that strong BJW related to greater self-blame following poor grades, while Kiecolt-Glaser and Williams (1987) found that burn victims were more likely to blame themselves when they strongly believed in a just world. These studies suggest, then, that a strong BJW is associated with self-concept activation (see also Dalbert, 1998).

In the context of the current study, this would suggest that one's BJW should moderate the contrast effects of upward and downward social comparisons. That is, while upward and downward comparisons provide evidence that one is better or worse off than another, the outcomes of such comparisons should be less likely to activate self-relevant information (and self-consistent behavior) when one does not believe in a just world. Given outcomes are randomly obtained, being better or worse off in comparison to another could easily be the result of external circumstances, and is less likely to lead to the activation of associated self-schema. However, for individuals who have a strong BJW, the outcomes of such comparisons are intrinsically tied to the type of person one is. Thus, for those who believe in a just world, seeing that one is better or worse off than someone else will be more likely to activate the appropriate self-relevant knowledge and hence engender self-consistent behaviors.

Based on these arguments, we propose that BJW will act as a moderator of the direct effect of social comparisons on OCB: When one believes that the world is just, comparisons activate self-relevant information and influence OCB as hypothesized above; when one does not believe the world is just, comparisons are unlikely to activate self-relevant information and hence there should be an attenuated relation or no relation at all between social comparisons and OCB. More formally, we put forward the following cross-level moderation hypotheses:

Hypothesis. Hypothesis 3: BJW will moderate the effects of upward social comparisons, such that the negative relation between upward social comparisons and citizenship behaviors is stronger for those who believe the world is just.

Hypothesis. Hypothesis 4: BJW will moderate the effects of downward social comparisons, such that the positive relation between downward social comparisons and citizenship behaviors is stronger for those who believe the world is just.

Social Comparisons and AET

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

While to this point we have argued for direct motivational effect of social comparisons on OCB, research has also shown social comparisons can have a profound impact on an individual's positive affect (PA; Wheeler & Miyake, 1992). Upward comparisons tend to diminish PA as such comparisons make the individual appear less competent, important, or desired (Buunk et al., 2003; Lyubomirsky & Ross, 1997). On the other hand, downward comparisons tend to engender PA, as they make the individual appear more favorable in comparison to the target (Moore, 2007; Mussweiler & Strack, 2000; Smith, 2000).

As noted by Greenberg, Ashton-James, and Ashkanasy (2007), because directional social comparisons are closely intertwined with affective reactions, AET holds particular promise for understanding how social comparisons influence organizational behavior. According to AET, affect plays a key mediating role between events in the workplace and behaviors in the workplace. In particular, AET states that affect is engendered, in part, by affect-inducing events, or “a change in circumstances” (Weiss & Cropanzano, 1996, p. 31). Job-related examples of such events include acts of fellow employees, achieving or failing to achieve goals, or experiencing a lack of influence, power, or control (Basch & Fisher, 2000); more broadly, based on cognitive appraisal theories of emotion, an event is deemed to be affective in nature if it is appraised as having implications for the individual's goals and well-being (Frijda, 1993). Affect generated by events preoccupy individuals and influence their subsequent evaluations, cognitive processing, and behaviors (Heller & Watson, 2005; Weiss & Cropanzano, 1996); consequently, affect is posited to mediate the relation between workplace events and behaviors.

Given that social comparisons, by definition, alter the comparer's perceptions of his or her current circumstance (Wood, 1989) and inform the comparer of his or her relative standing, social comparisons are expected to function as affective events. Thus, consistent with AET, it stands to reason that in addition to the motivational (direct) effect of social comparisons on OCB, social comparisons are also likely to have a mediated effect (Mathieu & Taylor, 2006)2 on OCB through their influence on PA. Such a prediction presupposes that social comparisons are affective events insofar as they generate PA (as outlined above), and that PA in turn influences OCB. Indeed, PA renders individuals more likely to be cooperative, helpful, and generous (Isen & Baron, 1991; Toegel, Anand, & Kilduff, 2007); as such, it is not surprising that PA states have been found to act as an antecedent of OCB (e.g., George & Brief, 1992; Ilies et al., 2006; Lee & Allen, 2002). Thus, we hypothesize the following:

Hypothesis. Hypothesis 5: Within-person, PA will partially mediate the negative effect of upward social comparisons on OCB.

Hypothesis. Hypothesis 6: Within-person, PA will partially mediate the positive effect of downward social comparisons on OCB.

To summarize, we are utilizing a daily diary design to examine our hypotheses: Social comparisons, PA, and OCB are measured daily and are examined as intraindividual variables whereas BJW is a stable belief and is measured once as an interindividual variable. Figure 1 heuristically depicts our hypotheses. Although not depicted in the diagram we also controlled for daily job satisfaction and negative affect (NA) at the daily (intraindividual) level and conscientiousness, agreeableness, and the general frequency of participants' interactions with coworkers at the trait (interindividual) level. Past work (e.g., Ilies et al., 2006) suggests that job satisfaction plays an important role in the prediction of daily OCB making it important to control for in order to demonstrate the incremental predictive utility of PA as a mediating mechanism. Moreover, consistent with previous studies that have used NA as a control variable (e.g., Fritz & Sonnentag, 2005), we controlled for the effects of NA. At the between-person level, conscientiousness and agreeableness were controlled for because they have been identified as the most theoretically relevant personality variables to the study of OCB (Ilies et al., 2009). To account for potential role requirements or job differences, we also controlled for the amount of interaction participants had with their coworkers.

Method

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

Procedure and participants

Potential participants were recruited using recruitment posters placed in commuter areas (e.g., bus shelters), newspapers, and other public places (e.g., coffee shops) in a medium sized Canadian city. The advertisement provided information regarding the researchers' university affiliation and indicated that the researchers were seeking interested employed individuals to participate in an investigation of workplace attitudes and behavior. The recruitment poster also indicated that the study had received ethics approval from the university's ethics board and indicated that eligible participants could earn $28 dollars in compensation for their participation. Finally, the poster directed interested individuals to complete an initial online demographic survey where they provided an email address for the researchers to contact them.

Overall, 120 individuals completed the initial demographic survey and were invited to participate in the focal investigation; 99 individuals subsequently participated (83 per cent retention rate). Each individual was sent an e-mail with a unique identifier code and a link to a one-time survey which assessed the individual's BJW, agreeableness, and conscientiousness; participants also provided the researchers with a 14 day time period in which they had no scheduled absences from work (i.e., vacation) and would be free to complete the diary portion of the study.

An interval-contingent experience sampling methodology (Nezlek, 2001) was used in the daily diary phase of the research such that participants completed a daily survey at fixed intervals, in this case at the end of each workday. To ensure the proper timing of the daily surveys, participants were emailed a link to the daily survey at the end of their workday. As an additional check the time at which each survey was completed was examined to ensure that the surveys were completed on the appropriate day. All participants began their daily surveys on a Monday. The daily surveys contained measures of social comparisons, PA, NA, job satisfaction, and OCB. If every participant had completed every daily survey across the 14 days it would have resulted in 1386 data points (99 × 14). Because some participants did not complete every daily survey, we obtained 1076 data points, resulting in an overall response rate of 78 per cent across time and participants (1076/1386).3 At the completion of data collection, participants were compensated $28 dollars and were provided with feedback as to the purpose of the study.

Ninety-nine (65 per cent female) full-time employees from a diverse set of occupations (e.g., consultant, office clerk, graphic designer, operations manager) were recruited to participate in the present study. Participants were employed in a wide variety of industries including business and finance (13 per cent), technology (13 per cent), healthcare (13 per cent), education (10 per cent), and engineering/architecture (6 per cent). The mean age of participants was 32.07 years (SD = 8.10) and the average hours worked per week was 42 (SD = 6.20). Participants reported being employed in their current organization an average of 4.8 years (SD = 6.98), having worked in their present position for 2.78 years (SD = 4.00), and with their current supervisor for 2.31 years (SD = 2.18).

Measures

Daily organizational citizenship behaviors

We measured daily OCB using a 14-item scale adapted from Lee and Allen (2002). The original scale was slightly altered to measure OCB in a daily context. Specifically, participants were asked to, “Please indicate if you performed the activities listed below at work today.” Responses were made using a yes/no response scale. Responses were summed to generate a daily OCB count score for each participant.4 Sample items included, “Willingly gave your time to help others who had work-related problems” and “Assisted others with their duties” (α = 0.89).

Daily social comparisons

To assess daily social comparisons, we adapted a scale that was used by Brown et al. (2007) to measure the extent to which employees engaged in social comparisons, in general. In order to make the scale appropriate for a daily diary study we made three changes: (1) We shortened the scale, reducing redundancies across items; (2) we changed the response option from a Likert scale to a frequency response option by having participants explicitly report how many times they engaged in social comparisons; and (3) we included instructions that prompted participants to record the extent to which they engaged in social comparisons that day. Participants were asked to indicate the frequency with which they compared themselves to others who were better off and worse off in terms of salary, benefits, career progression, working conditions, and performance. Specific instructions presented to participants were as follows: “For each dimension, please indicate the frequency with which you compared yourself with others at work today. Please use the numbers to indicate the frequency of your comparisons.” For both upward and downward comparisons, participants recorded their responses separately for each dimension (e.g., salary, benefits, career progression, working conditions, and performance) along a 10-point frequency scale (0 = “0 times” to 10 = “10 times or more”). Responses were summed separately for the downward (α = 0.88) and upward social comparison scales (α = 0.90).5

Daily positive and negative affect

PA and NA were measured using the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). The PA subscale consists of 10 items (e.g., enthusiastic, proud) (α = 0.95). The NA subscale consists of 10 items (e.g., irritable, angry) (α = 0.87). Participants were instructed to indicate how they felt at work during that day using a 5-point Likert scale (1 = strongly disagree and 5 = strongly agree).

Belief in a just world

Participants' BJW was assessed using a 7-items scale developed by Dalbert (1999). Responses were given on a 7-point Likert scale ranging from 1 = strongly disagree to 7 = strongly agree. Sample items include, “Overall, events in my life are just” and “I believe that, by and large, I deserve what happens to me” (α = 0.87).

Daily job satisfaction

Daily job satisfaction was measured using a 5-item job satisfaction scale adapted for use on a daily basis (Heller & Watson, 2005). Participants were instructed to indicate their level of agreement to statements based on their thoughts and feeling about their job that day. Responses were made on a 5-point Likert scale (1 = strongly disagree and 5 = strongly agree). Sample items include, “I felt satisfied with my present job” and “The work day seemed like it would never end” (reverse coded) (α = 0.87).

Conscientiousness

Conscientiousness was measured using the 9-item conscientiousness subscale of the Big Five Inventory (BFI; John & Srivastava, 1999). Responses were made on a 5-point Likert scale ranging from 1 = Very uncharacteristic of myself to 5 = Very characteristic of myself. Sample items include, “I see myself as someone who does a thorough job” and “I see myself as someone who does things efficiently” (α = 0.82).

Agreeableness

Agreeableness was measured using the 9-item agreeableness subscale of the BFI (John & Srivastava, 1999). Responses were made on a 5-point Likert scale ranging from 1 = Very uncharacteristic of myself to 5 = Very characteristic of myself. Sample items include, “I see myself as someone who has a forgiving nature” and “I see myself as someone who likes to cooperate with others” (α = 0.77).

Interaction with coworkers

We measured how frequently participants interacted with their coworkers on a typical day by asking, “How often do you interact with other people in your organization (supervisor and work peers) during a typical work day?” Responses were made on a 5-point scale ranging from 1 = never to 5 = often.

Analyses

Because we collected data at both the intraindividual (daily measures of social comparisons, PA, NA, job satisfaction, and OCB) and interindividual (trait measures of BJW, agreeableness, conscientiousness, and frequency of interaction with coworkers) levels of analysis our data were multilevel and we tested our hypothesized relationships using multilevel regression. To do so we used Hierarchical Linear Modeling software (HLM 6.0; Raudenbush, Bryk, Cheong, & Condon, 2004). HLM allowed us to examine both intraindividual effects, referred to as Level 1, and the interindividual effects, referred to as Level 2.

To ensure that our Level 1 parameter estimates were not biased by individual differences, we centered all Level 1 predictors at each individual's mean (group-mean centering; Enders & Tofighi, 2007; Raudenbush & Bryk, 2002). In addition, to aid in the interpretation of the Level 2 coefficients, all Level 2 (interindividual) variables were grand-mean centered prior to running our analyses. The logic of doing so is similar to that of ordinary least squares regression: Because, for example, BJW does not have a meaningful zero point, centering at the mean provides an interpretable intercept (Enders & Tofighi, 2007). All the equations for the different models are provided in the Appendix.

Additionally, because our data is longitudinal in nature we utilized the hierarchical multivariate linear modeling (HMLM) option within the HLM software. HMLM was selected because it allowed us to model alternative error structures at Level 1. The ability to model alternative error structures is important in longitudinal designs because the dimension of time can create dependencies in data that are not due to the grouping variable, which if not taken into account can bias significance tests (Bliese & Ployhart, 2002; Raudenbush & Bryk 2002). Specifically, because the data are collected over time, the data are ordered. This means that errors from the daily (intraindividual) variables may not be independent even after accounting for the grouping variable (i.e., person) because measures that are taken closer in time can be more strongly related to each other than measures that are far apart (Bliese & Ployhart, 2002). Additionally, the variance of errors may change across time, becoming either larger or smaller, which can similarly cause estimation biases (Bliese & Ployhart, 2002). To account for these dependencies, we tested the fit of several different error structures6 using likelihood-ratio tests (Raudenbush & Bryk, 2002). In conducting these analyses, an unrestricted model consistently demonstrated the best fit. As a result, all the results presented herein are derived from models an unrestricted Level 1 error structure.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

Table 1 presents the means, standard deviations, and zero-order relations for all the variables included in our study.

Table 1. Zero-order relations between variables
 MeanSD123456789101112
  • Note: Correlations above the diagonal amongst the daily variables are between-person correlations and were computed by aggregating each variable across days within participants. Correlations below the diagonal amongst the daily variables are within-person correlations and were computed by running group centered single-predictor equations, with standardized variables in HMLM. Correlations with the trait variable are Pearson's coefficients and were computed using participants' aggregated daily scores. Coefficient alpha is reported on the diagonal and was computed for each day and then aggregated across days.

  • a

    n = 1076 observations (below diagonal).

  • b

    n = 99 participants. Gender is dummy coded 1 = males and 0 = females.

  • *

    p < 0.05.

Daily variablesa
 1. Upward comparison1.131.42(0.90)0.85*−0.34*−0.21*0.42*0.21*      
 2. Downward comparison0.771.170.43*(0.88)−0.17−0.070.49*0.26*      
 3. Job satisfaction3.650.86−0.10*0.01(0.87)0.75*−0.34*0.16      
 4. Positive affect2.871.08−0.05*0.12*0.52*(0.95)−0.110.29*      
 5. Negative affect1.350.530.10*0.05−0.24*−0.13*(0.87)0.05      
 6. Daily OCB2.381.040.020.07*0.16*0.22*−0.01(0.89)      
Trait variablesb
 7. Belief in a just world5.130.99−0.21*−0.080.40*0.39*−0.110.20*(0.87)     
 8. Agreeableness4.070.54−0.13−0.030.32*0.24*−0.26*0.150.33*(0.77)    
 9. Conscientiousness3.940.63−0.03−0.070.180.17−0.20*0.060.070.34*(0.82)   
 10. Age32.128.160.00−0.040.160.20*−0.21*0.130.030.040.15  
 11. Gender0.340.48−0.13−0.190.05−0.13−0.24*−0.10−0.020.080.24*0.10 
 12. Frequency of interaction4.620.58−0.18−0.180.130.090.03−0.030.090.05−0.04−0.050.09

Partitioning variance components

Prior to testing our hypotheses we estimated the systematic within- and between-person variance in each of our daily measures in order to assess whether there was sufficient within-person (daily) variance to proceed with our within-person and cross-level interaction hypothesis testing. To partition the variance into within- and between-person components, a null model (a model in which no predictors were entered at either level of analysis) was run on each of our six Level 1 variables. As shown in Table 2, the results indicate that between 33 and 48 per cent of the variance (far right column) in our variables was attributable to within-person variability, making it appropriate to proceed with a multilevel analysis.

Table 2. Partitioning the variance for PA, Daily OCB, and social comparisons
VariableIntercept (γ00)aWithin-person variance (σ2)Between-person variance (τ00)Percent of within-person varianceb
  • a

    γ00 = average intercept across participants which equates to the average level of the dependent variable in our sample.

  • b

    Per cent of within-person variance was as computed as σ2/(σ2 + τ00). OCB = Organizational citizenship behaviors.

  • *

    p < 0.05.

Positive affect2.90*0.380.8034
Daily OCB2.40*0.450.6043
Upward social comparison1.16*0.741.2737
Downward social comparison0.79*0.620.7844
Negative affect1.37*0.150.1648
Job satisfaction3.65*0.250.5133

Additionally, because our data were collected at the same time each day, we wanted to establish the discriminability of our daily focal constructs (upward social comparisons, downward social comparisons, PA, and daily OCB). To do so, we used multilevel confirmatory factor analyses (MCFA; Muthen, 1994). MCFA was chosen because we were interested in confirming the factor structure of our focal constructs at the daily level. Given the nested structure of our data, conventional confirmatory factor analysis was not appropriate because it would necessitate that we either aggregate our daily measures or simply ignore the nested structure. Aggregating is not sensible because it effectively discards the level of analysis we are interested in. Ignoring the nested structure is not effective either because having dependencies that go unaccounted for can create estimation biases (Muthen, 1994). MCFA addresses both of these issues by enabling researchers to confirm the structure nested data at different levels of analysis (see Dyer, Hanges, & Hall, 2005, for a review).

To conduct the MCFA we used Mplus 6.0 (Muthen & Muthen, 2010). We ran two models, a one-factor model with all items loading on a single construct and a confirmatory model whereby each item was set to load on its theoretically intended construct. The results of these analyses reveal that the confirmatory model was a better representation of the data than the single factor model. Specifically, the single factor model demonstrated poor fit by failing to meet conventional fit standards (RMSEA = 0.07; SRMR = 0.12) whereas the fit of the confirmatory model was a range that suggests good model fit (RMSEA = 0.04; SRMR = 0.04). Additionally, we established that the improved fit of the confirmatory model over the single factor model was statistically significant (Δχ2 = 3939.77, p < 0.05). Overall, the results of the MCFAs support the separation of our daily focal constructs.

Hypothesis testing

For consistency, all coefficients reported in the body of the text are unstandardized; however, standardized coefficients for linear effects are reported alongside the unstandardized coefficients in the tables. Hypothesis 1 predicted that upward social comparisons would be negatively related to daily OCB within-individuals, while Hypothesis 2 predicted that downward social comparisons would be positively related to daily OCB within-individuals. Hypotheses 3 and 4 predicted that participants' BJW would moderate the direct effects of social comparisons on daily OCB, such that they would be stronger at high levels of BJW compared to low levels. Consequently, Hypotheses 1–4 were tested simultaneously by regressing daily OCB on daily upward and downward social comparisons with BJW entered as a Level 2 predictor of daily OCB and of the two Level 1 slopes, creating two cross-level interactions. The results from this model are presented in Table 3. As can be seen, Hypothesis 1 was not supported in that upward comparisons were not negatively related to daily OCB (γ20 = 0.00, n.s.). However, downward comparisons were significantly positively related to daily OCB (γ10 = 0.05, p < 0.05), as predicted by Hypothesis 2. Support for Hypotheses 3 and 4 were found as BJW significantly moderated the effects of upward (γ21 = −0.06, p < 0.05) and downward (γ11 = 0.07, p < 0.05) comparisons on daily OCB. In addition, BJW was found to have a positive direct effect on daily OCB (γ01 = 0.16, p < 0.05).

Table 3. Hierarchical multivariate linear modeling results for social comparisons and belief in a just world predicting daily organizational citizenship behaviors
Independent variablesUnstandardized coefficientsStandard errortStandardized coefficients
  • Gender is a dummy coded variable: 1= male, 0 = female. BJW = belief in a just world.

  • *

    p < 0.05.

Intercept, γ002.60*0.0548.68 
Age, γ010.02*0.013.310.16*
Gender, γ020.190.121.650.09
Frequency of interaction with coworkers, γ03−0.030.09−0.35−0.02
Agreeableness, γ040.090.110.870.05
Conscientiousness, γ050.000.100.020.00
BJW, γ060.16*0.062.860.15*
Downward comparison, γ100.05*0.022.280.06*
 BJW, γ110.07*0.032.40 
Upward comparison, γ200.000.020.150.00
 BJW, γ21−0.06*0.02−2.82 

To probe the interactions, we plotted them and subjected the simple slopes to significance testing. The values for “high” were plotted and tested at one standard deviation above the mean and all the values for “low” were plotted and tested at one standard deviation below the mean (Cohen, Cohen, West, & Aiken, 2003). Visual inspection of the interactions reveals that the patterns are consistent with Hypotheses 3 and 4. Specifically, Figure 2 depicts the interaction between upward comparisons and BJW and shows that the effect of upward social comparisons on daily OCB is more negative at high levels of BJW than it is at low levels (supporting Hypothesis 3). Statistical testing of the simple slopes supports this conclusion, such that there is a significant negative relation (γ10 = −0.07, p < 0.05) between upward comparisons and daily OCB at high levels of BJW. Additionally, there was an unhypothesized significant positive effect (γ10 = 0.06, p < 0.05) at low levels of BJW.

thumbnail image

Figure 2. Cross-level interaction between upward social comparisons and belief in a just world (BJW) predicting daily OCB

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Figure 3 depicts the interaction between BJW and downward comparisons on daily OCB. The figure illustrates that there is a stronger positive relation between downward comparisons and daily OCB at high levels of BJW compared to low levels (supporting Hypothesis 4). Statistical testing of the simple slopes support this conclusion as the slope at high levels of BJW is positive and significant (γ20 = 0.10, p < 0.05) whereas the slope at low levels of BJW is non-significant (γ20 = −0.02, n.s.).

thumbnail image

Figure 3. Cross-level interaction between downward social comparisons and belief in a just world (BJW) predicting daily OCB

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Mediation analyses: The role of PA

In addition to investigating the direct and moderated effects of social comparisons on daily OCB, we also examined the indirect effects of social comparisons through PA on daily OCB. Specifically, Hypothesis 5 predicted that PA would mediate the negative effect of upward comparisons on daily OCB, while Hypothesis 6 predicted that PA would mediate the positive effect of downward comparisons on daily OCB. To test these hypotheses, we used the Sobel test (Sobel 1982, 1986).

To begin our meditational analyses, we needed to establish whether or not social comparisons were related to PA in the anticipated directions. To do so, we regressed PA on upward and downward comparisons simultaneously. The results of this analysis, presented in Table 4, indicate that upward comparisons are negatively related with PA (γ20 = −0.06, p < 0.05) and that downward comparisons are positively related to PA (γ10 = 0.10, p < 0.05) satisfying the condition that social comparisons relate to PA.

Table 4. Hierarchical multivariate linear modeling results for social comparisons predicting positive affect
VariablesUnstandardized coefficientsStandard errortStandardized coefficients
  • Gender is a dummy coded variable: 1 = male, 0 = female. BJW = belief in a just world.

  • *

    p < 0.05.

Intercept, γ003.10*0.0744.43 
Age, γ010.02*0.012.250.15*
Gender, γ020.240.151.590.11
Frequency of interaction with coworkers, γ030.24*0.121.960.13*
Agreeableness, γ040.32*0.152.220.16*
Conscientiousness, γ050.160.121.270.09
BJW, γ060.19*0.072.600.17*
Downward comparison, γ100.10*0.024.520.11*
Upward comparison, γ20−0.06*0.02−2.96−0.08*

Next, we examined whether PA was a significant predictor of daily OCB while controlling for the effects of social comparisons and BJW. To procure this information, we ran a fully specified model with upward comparisons, downward comparisons, BJW, PA, and all our control variables simultaneously predicting daily OCB. The results of this analysis, presented in Table 5, indicate that PA is a significant predictor of daily OCB (γ30 = 0.17, p < 0.05).

Table 5. Full model: Multivariate linear modeling results for social comparisons, belief in a just world, and positive predicting daily organizational citizenship behaviors
Independent variablesUnstandardized coefficientsStandard errortStandardized coefficient
  • Gender is a dummy coded variable: 1= male, 0 = female. BJW = belief in a Just world.

  • *

    p < 0.05.

Intercept, γ002.57*0.0550.26 
Age, γ010.02*0.012.990.16*
Gender, γ020.220.111.930.10
Frequency of interaction with coworkers, γ03−0.040.09−0.46−0.02
Agreeableness, γ040.040.100.380.02
Conscientiousness, γ050.030.090.340.20
BJW, γ060.21*0.053.900.20*
Downward comparison, γ100.030.021.370.03
 BJW, γ110.05*0.032.00 
Upward comparison, γ200.010.020.400.01
 BJW, γ21−0.07*0.02−3.44 
Positive affect γ300.17*0.035.320.18*
Negative affect, γ400.060.041.400.03
Job satisfaction, γ500.11*0.042.990.09*

After determining that social comparisons significantly predicted PA (in the expected directions), and that PA, in turn, significantly predicted daily OCB, we tested the significance of the indirect effects by conducting two Sobel (1982) tests: One for the indirect effect of upward comparisons (H5) and one for the indirect effect of downward comparisons (H6). The Sobel test for the indirect effect of upward comparisons on daily OCB was significant (t = −3.01, p < 0.05) indicating that upward social comparisons have a significant indirect effect on daily OCB through PA, supporting Hypothesis 5. Additionally, the Sobel test for the indirect effect of downward comparisons was also significant (t = 3.78, p < 0.05) indicating that downward comparisons have a significant indirect effect on daily OCB through PA, supporting Hypothesis 6.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

As OCB is one of the key components of overall individual job performance (Rotundo & Sackett, 2002), as well as an important contributor to the performance of the overall organization (Podsakoff & MacKenzie, 1997), investigating the antecedents of OCB remains an important priority for organizational researchers. Yet despite this importance, the field has not integrated new perspectives on motivational and affective antecedents of OCB (Zellars & Tepper, 2003), and has largely conceptualized OCB at a between-person level ignoring important variability that lies at the within-individual level. In the present study, we sought to rectify this situation by using an intraindividual design to examine two novel antecedents of OCB—upward and downward social comparisons—which should have both motivational and affective effects on OCB.

Consistent with our predictions, we found that social comparisons had both direct (motivational) and indirect (affective) effects on daily OCB. Specifically, with respect to direct effects, downward social comparisons were found to have a positive effect on daily OCB, especially for employees with a strong BJW. On the other hand, upward social comparisons were found to have a negative effect on OCB for those with a strong BJW. Together, these results are consistent with our predictions that directional social comparisons would exhibit contrast effects on employee OCB levels, and that these effects are particularly potent for those with strong just world beliefs. In line with AET, we also found that both upward and downward social comparisons had significant indirect effects on daily OCB through PA. Upward comparisons were associated with lower levels of PA and downward social comparisons were associated with increased PA. PA, in turn, was found to be a significant predictor of daily OCB when controlling for social comparisons, job satisfaction, and NA.

Finally, while our results were by and large supported, we unexpectedly found a positive relation between upward comparisons and OCB at low levels of BJW (see Figure 2). While this effect was not hypothesized, it has been argued that upward comparisons may also activate positive self-relevant knowledge (Mussweiler & Strack, 2000). Thus, it is possible that upward comparisons function differently as a function of BJW, such that upward comparisons activate negative self-relevant knowledge for those with high BJW (as we hypothesized) and activate positive self-relevant knowledge for those with low BJW. However, given the effect was not hypothesized and also was not consistent with the hypothesized results found for downward comparisons, we suggest caution in interpreting this result. Indeed, it would be fruitful for researchers to replicate the effect to demonstrate whether it is a chance occurrence or a robust effect.

Contributions to the OCB literature

By examining social comparisons as an antecedent of OCB, our paper provides several meaningful contributions to the OCB literature. First, our study investigates OCB as dynamic behavior that varies considerably from one time to another. By examining OCB on a daily basis we are able to identify intraindivdual processes that lead to within-employee fluctuations in this critical behavior, adding an answer to “under what circumstances” such a behavior will occur, beyond the traditional “who engages” in this behavior. Second, it is the first to integrate social comparisons with OCB; in so doing, we demonstrate a novel antecedent previously overlooked by OCB researchers. Third, examining social comparisons also allowed us to examine motivational and affective influences on OCB, two areas that have been sorely in need of explication in OCB research (Zellars & Tepper, 2003). In so doing, we drew on AET to posit mediating affective mechanisms underlying such effects; creating more theoretical precision, we also integrated research on BJW with social comparison research to posit moderating effects on the direct motivational effects of social comparisons, illustrating boundary conditions of when such effects should occur.

Finally, our results indicate that, in addition to its moderating effect on social comparisons, BJW had a direct effect on OCB. Although not hypothesized, this finding is consistent with past work that has indicated that strong just world beliefs can be an adaptive and helpful psychological resource for those who hold them (e.g., Dalbert, 2001). Specifically, just world beliefs have been positively associated with life satisfaction (e.g., Lipkus, Dalbert, & Siegler, 1996) and negatively related to anxiety and depression (e.g., Otto, Boos, Dalbert, Schöps, & Hoyer, 2006; Ritter, Benson, & Snyder, 1990). However, with respect to behavior, just world beliefs are argued to obligate people to act fairly (Dalbert, 2001). Our finding that BJW is positively related to OCB suggests that, in addition to facilitating well-being, in the workplace this obligation may be translated into OCB, whereby employees who are mindful of fairness are motivated to act as good organizational citizens.

We believe that our study validates calls to look at both motivation and affective processes underlying OCB, and can serve as a starting point for future studies. While we have focused on the motivational effects of social comparisons, other forms of motivation can likely be fruitfully applied to OCB. For example, promotion and prevention theories of motivation (Higgins, 1997) suggest that individuals differ in the extent to which they are sensitive to positive and negative information (promotion or prevention orientation, respectively), and these differences subsequently influence emotions and behaviors. Thus one would expect that upward (negative) and downward (positive) comparisons would have a larger effect on OCB for promotion and prevention oriented individuals, respectively. This represents but one approach to further integrating disparate theoretical viewpoints. Overall, we agree with the belief that research on OCB can only benefit by integrating new theoretical vantage points beyond typical frameworks such as social exchange (Zellars & Tepper, 2003).

Contributions to the social comparisons literature

Our results also contribute to the fledgling social comparison literature in organizational behavior (Greenberg et al., 2007). First, our study is the first to provide evidence that BJW interacts with social comparisons to influence the effects of such comparisons. In so doing, our study outlines a new and potentially important boundary condition on the effects of social comparisons. While social comparisons have been suggested to be an important antecedent of organizational attitudes and behaviors (Brown et al., 2007; Greenberg et al., 2007), the present study suggests that such claims may need to be qualified.

Second, our work also contributes to the social comparison literature by extending social comparison research to the organizational realm. Despite the fact that researchers have posited that social comparisons are commonplace for employees and exert considerable sway over their workplace behavior, there has been a dearth of organizational scholarship on the topic of social comparisons (Greenberg et al., 2007). Our hope is that our study serves to inspire organizational researchers to examine social comparisons in their own areas.

Limitations and future directions

While our study possessed a number of strengths, some limitations should be noted. For example, our hypotheses were tested using self-reported data, which may raise concerns regarding common method variance (CMV; Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Additionally, the questionnaires were presented to each participant in the same order across days and were not counterbalanced. This may have contributed to CMV by resulting in an increased potential for priming effects and context induced mood states to occur (Podsakoff et al., 2003). However, our finding that BJW acted as a moderator argues against the presence of CMV, as it is not readily apparent how CMV can strengthen the relation amongst variables only for people with high BJW (Evans, 1985). Moreover, recent work illustrates that self-ratings of OCB are accurate and valid indicators of OCB (e.g., Ilies et al., 2009). Additionally, an attractive property of within-individual (i.e., diary) analyses is that they reduce the impact of response biases (Beal & Weiss, 2003), which represent a main form of CMV (Podsakoff et al., 2003). Finally, our controlling for NA reduces this concern even further. In sum, we believe these steps considerably reduce the likelihood that CMV could account for our results, though they do not rule it out completely.

Another potential limitation is that while our study examined upward and downward comparisons, it did not examine lateral comparisons, or comparisons to others who are at a similar level. This choice was theoretically driven given our focus on the motivational and affective consequences associated with directional social comparisons, as such consequences are most likely when comparing to an individual who is better or worse off than oneself. Moreover, the majority of all social comparisons are either upwards or downwards in nature (Olson & Evans, 1999; Wheeler & Miyake, 1992). Thus, for our study lateral comparisons are both less relevant to our hypotheses and less likely to occur on a daily basis, and consequently were not assessed.

As an anonymous reviewer pointed out, one limitation of our data relates to the difficulty in infering causality. For example, it is possible that engaging in OCB can lead an individual to progress through the ranks more quickly, thus facilitating downward comparisons, rather than downward comparisons increasing OCB. However, past experimental work suggests that, at least initially, it is social comparisons which influence outcomes and not vice versa (e.g., Staple & Koomen, 2005).

While our study is premised on the automatic activation of self-knowledge by social comparisons, we did not directly assess this activation. However, priming effects are typically conceived as direct, automatic, and unconscious (Bargh et al., 1996); as such, they need to be assessed using techniques not suitable for diary studies, such as response time discrepancies in response to positive or negative words (indicative of the activation of positive or negative self-perception; Bargh & Tota, 1988). Thus, our results are best viewed as consistent with past studies and theorizing on the activation of self-knowledge by social comparisons, though also not conclusively demonstrating such automatic effects.

Additionally, we should note that while we have conceptualized the effects of social comparisons in terms of contrast effects (as compared to assimilation effects) given the competitive nature of most organizational settings, we recognize that not all organizations are competitive (e.g., not for profit, team-based, or volunteer organizations). As such, organizational cultures can be characterized as being relatively more cooperative or competitive (O'Reilly, Chatman, & Caldwell, 1991). Thus, a future research direction would be to test whether contrast or assimilation effects predominate within not for profit or volunteer organizations, or organizations with cooperative cultures. That being said, even within competitive organizations, one may expect individual differences to moderate the negative effects of upward social comparisons on OCB. For example, if an individual is particularly proactive (Bateman & Crant, 1993) or defines oneself in terms of their work performance (Ferris, Brown, Lian, & Keeping, 2009), such upward comparisons may spur the individual on to greater performance rather than lead to negative outcomes.

Lastly, as evidence by the standardized coefficients that are reported in Tables 3–5, it is apparent that the sizes of our effects are relatively small. Although the amount of variance that is explained in OCB (and PA) is relatively small, it should be noted that small effects should not be dismissed as unimportant (see Abelson, 1985; Prentice & Miller, 1992, for a review). In particular, because we are explaining OCB within employees within workdays, the cumulative effects of our predictors over the course of one's tenure at an organization is likely to be quite sizeable (Abelson, 1985). Additionally, because we are introducing new theory to the OCB literature, we do not think that our findings should be evaluated based only on effect sizes.

Practical implications

We believe the current data have important implications for understanding employee behavior insofar as they demonstrate that the extent to which employees engage in OCB on a given day is the result of both inter and intraindividual processes. With respect to interindividual effects, we see that employee' belief about the predictability of the world (i.e., justice beliefs) strongly influence how they behave day-to-day at work as well as how they respond to social information. Thus, our results suggest that managers may want to pay particular attention to their employees' just world beliefs and their exposure to potentially demoralizing or energizing comparison targets or events. For example, companies being acquired during mergers and acquisitions may view employees of the acquiring company as being better off, and hence be less likely to engage in OCB in the new company. Given this could adversely affect their performance evaluations in the new company (Rotundo & Sackett, 2002), managers should try to minimize upward comparisons by these employees. In this respect, previous research (Brown et al., 2007) has suggested that increased task autonomy and decreased job ambiguity are related to lower upward comparisons at work; thus, managers may wish to focus on increasing clarity and autonomy for such employees.

Our results regarding the intraindividual affective meditational pathway through which comparisons influence OCB levels also suggest another way in which managers may mitigate the effects of upward comparisons. In particular, our results (and those of other diary studies, e.g., Dalal et al., 2009; Ilies et al., 2006) demonstrate that PA has a strong relation to OCB, even when controlling for job satisfaction. Thus, interventions which foster PA in the workplace may help to counteract the negative effects of upward social comparisons and boost OCB levels overall. Recent work has highlighted emotional contagion processes through which leader emotional displays influence employee affect and performance (see Van Kleef, 2009, for a review); such work suggests that one simple way to influence employee PA levels is for leaders to simply act happier. Additionally, the job design literature suggests that employee interaction, social support, and employee interdependence can increase employees' PA levels (Humphrey, Nahrgang, & Morgeson, 2007); redesigning positions to increase such interactions may thus serve to foster employee PA.

Conclusion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

Because diary studies and investigations of OCB as a dynamic construct are relatively new to the field of Organizational Behavior, many conceptual and methodological questions remain to be answered. Our preliminary findings demonstrating that there is substantial intraindividual variability in OCB and that is variability is systematically related to social comparisons and PA further point to the importance of these investigations. Moreover, we discovered that BJW, a construct new to the study of work performance, is a significant determinant of OCB. This finding illustrates that there is still more to be done to understand what determines intraindividual and interindividual differences in OCB. We hope future research continues to address these questions and enhances our understanding of employee performance.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

This research was supported in part by grants from the Canadian Social Sciences and Humanities Research Council to all four authors. The authors thank Ivona Hideg for helpful comments on an earlier version of this paper.

  • 1

    While we suggest that organizations are primarily competitive environments, we recognize that this contention may not characterize all types of organizations (e.g., it may not hold for profit companies). However, even within such companies, employees compete for a fixed pool of resources (e.g., top positions, raises, etc.) and hence are likely to engender some level of competition. We return to this issue in our discussion of future research directions.

  • 2

    Indirect effects are said to refer to a causal sequence of variables where X predicts M and M predicts Y, whereas mediation refers to a total effect between two variables (X to Y) that is partially or fully explained by another variable (Mathieu & Taylor, 2006). Because we hypothesized that social comparisons would have a direct effects on daily OCB we used the label of mediation here.

  • 3

    Missing data at the item level was imputed with the participant's mean on the scale across days and missing data at the daily level was handled by the HMLM program. We conducted analyses to determine if the number of surveys participants responded to was related to our variables of interest (upward and downward comparisons, PA, BJW, and OCB) and control variables (NA, job satisfaction, agreeableness, age, gender, and amount of interaction with coworkers). Specifically, the number of surveys each participant completed was included as a variable in the dataset and used to predict each of our variables. Because we were testing for multiple effects we set alpha using a Bonferroni correction (0.05/12 = 0.004). Bonferroni corrections are appropriate when engaging in multiple atheoretical comparisons, in order to guard against Type I errors. Results of these analyses indicate that the number of surveys that participants completed was unrelated to our focal variables: downward comparisons (γ10 =−0.02, n.s), upward comparisons (γ10 = −0.04, n.s), PA (γ10 =−0.02, n.s), daily OCB (γ10 =0.02, n.s.), and BJW (r = −0.04, n.s.). As well, the number of daily surveys participants completed was unrelated to our control variables: NA (γ10 =−0.04, n.s), job satisfaction (γ10 =−0.01, n.s), agreeableness (r = 0.04, n.s.), conscientiousness (r = 0.08, n.s.), age (r = 0.20, n.s.), gender (r = 0.06, n.s.), and amount of interaction with coworkers (r = −0.01, n.s.).

  • 4

    Given that count data have the characteristic of being bounded at zero and are likely to be positively skewed we transformed the data using a square root transformation prior to conducting our analyses (Cohen et al., 2003).

  • 5

    As with responses on the OCB scale, responses to these scales were transformed using a square root transformation (Cohen et al., 2003).

  • 6

    We tested (a) homogeneous (i.e., errors are homogeneous and independent), (b) heterogeneous (i.e., error variances change across time), (c) correlated (autoregressive; i.e., errors are correlated across time), and (d) unrestricted (i.e., no restrictions are placed on error variances or correlations).

Appendix: Model Specifications

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

dailyOCBij = daily organizational citizenship behavior at time i for individual j

UCij = upward comparisons at time i for individual j

DCij= downward comparisons at time i for individual j

PAij = positive affect at time i for individual j

BJWj = belief in a just world for individual j

HMLM Equations for Tests of Hypotheses 1–4 (not including control variables)

Level 1:

  • equation image

Level 2:

  • equation image
  • equation image
  • equation image

Combined Model:

dailyOCBij = γ00 + γ01BJWj+ γ10UCij + γ11BJWj*UCij+ γ20DCij + γ21BJWj*DCij + r0j + r1j + r2j + eij

HMLM Equations for Tests of Hypotheses 5–6 (not including control variables)

First stage of mediation:

Level 1:

  • equation image

Level 2:

  • equation image
  • equation image
  • equation image

Combined model:

dailyOCBij = γ00 + γ10UCij+ γ20DCij+ r0j + r1j + r2j + eij

Full model (second stage of mediation)

Level 1:

  • equation image

Level 2:

  • equation image
  • equation image
  • equation image
  • equation image

Combined model:

dailyOCBij= γ00 + γ01BJWj+ γ10UCij + γ11BJWj*UCij + γ20DCij+ γ21BJWj*DCij + γ30PAij+ r0j + r1j + r2j + r3j + eij

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information
  • Abelson, R. P. (1985). A variance explanation paradox: When a little is a lot. Psychological Bulletin, 97, 129133.
  • Bargh, J. A., & Tota, M. E. (1988). Context-dependent automatic processing in depression: Accessibility of negative constructs with regard to self but not others. Journal of Personality and Social Psychology, 54, 925939.
  • Bargh, J. A., & Williams, E. L. (2006). The automaticity of social life. Current Directions in Psychological Science, 15, 14.
    Direct Link:
  • Bargh, J. A., Chen, M., & Burrows, L. (1996). Automaticity of social behavior: Direct effects of trait construct and stereotype activation on action. Journal of Personality and Social Psychology, 71, 230244.
  • Barnard, C. I. (1938). The functions of the executive. Oxford: Harvard University Press.
  • Basch, J., & Fisher, C. D. (2000). Affective events-emotions matrix: A classification of work events and associated emotions. In N. M.Ashkanasy, C. E. J.Hartel, & W. J.Zerbe (Eds.), Emotion in the workplace: Research, theory, and practice. Westport: Quorum Books.
  • Bateman, T. S., & Crant, J. M. (1993). The proactive component of organizational behavior: A measure and correlates. Journal of Organizational Behavior, 14, 103118.
  • Bateman, T. S., & Organ, D. W. (1983). Job satisfaction and the good soldier: The relationship between affect and employee “citizenship.” Academy of Management Journal, 26, 587595.
  • Beach, S. R. H., & Tesser, A. (2000). Self-evaluation maintenance and evolution. In J.Suls, & L.Wheeler (Eds.), Handbook of social comparison: Theory and research (pp. 123140). New York: Plenum.
  • Beal, D. J., & Weiss, H. M. (2003). Methods of ecological momentary assessment in organizational research. Organizational Research Methods, 6, 440464.
  • Beal, D. J., Weiss, H. M., Barros, E., & MacDermid, S. M. (2005). An episodic process model of affective influences on performance. Journal of Applied Psychology, 90, 10541068.
  • Blau, P. M. (1964). Exchange and power in social life. New York: Wiley.
  • Bliese, P. D., & Ployhart, R. E. (2002). Growth modeling using random coefficient models: Model building, testing, and illustration. Organizational Research Methods, 5, 362387.
  • Bolino, M. C. (1999). Citizenship and impression management: Good soldiers or good actors? Academy of Management Review, 24, 8298.
  • Borman, W. C., & Motowidlo, S. M. (1993). Expanding the criterion domain to include elements of contextual performance. In N.Schmitt, & W. C.Borman (Eds.), Personnel selection in organizations (pp. 7198). San Francisco: Jossey-Bass.
  • Brickman, P., & Bulman, R. (1977). Pleasure and pain in social comparisons. In J. M.Suls, & R. L.Miller (Eds.), Social comparison processes: Theoretical and empirical perspectives (pp. 149186). Washington, DC: Hemisphere.
  • Brief, A. P., & Motowidlo, S. J. (1986). Prosocial organizational behaviors. Academy of Management Review, 11, 710725.
  • Brown, D. J., Ferris, D. L., Heller, D., & Keeping, L. M. (2007). Antecedents and consequences of the frequency of upward and downward social comparisons at work. Organizational Behavior and Human Decision Processes, 102, 5975.
  • Buunk, A. P., & Gibbons, F. X. (2007). Social comparison: The end of a theory and the emergence of a field. Organizational Behavior and Human Decision Processes, 102, 321.
  • Buunk, B. P., & Mussweiler, T. (2001). New directions in social comparison research. European Journal of Social Psychology, 31, 467475.
  • Buunk, B. P., Zurriaga, R., Gonzalez-Roma, V., & Subirats, M. (2003). Engaging in upward and downward comparisons as a determinant of relative deprivation at work: A longitudinal study. Journal of Vocational Behavior, 62, 370388.
  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd edn). Mahwah, NJ: Lawrence Erlbaum Associates.
  • Collins, R. L. (1996). For better or worse: The impact of upward comparison on self-evaluations. Psychological Bulletin, 119, 5169.
  • Collins, R. L. (2000). Among the better ones: Upward assimilation in social comparison. In J.Suls, & L.Wheeler (Eds.), Handbook of social comparison: Theory and research (pp. 159171). New York: Plenum.
  • Crosby, F. A. (1976). A model of egoistical relative deprivation. Psychological Review, 83, 85113.
  • Dalal, R. S., Lam, H., Weiss, H. M., Welch, E. R., & Hulin, C. L. (2009). A within-person approach to work behavior and performance: Concurrent and lagged citizenship-counterproductivity associations, and dynamic relationships with affect and overall job performance. Academy of Management Journal, 52, 10511066.
  • Dalbert, C. (1998). Belief in a just world, well-being, and coping with an unjust fate. In L.Montada, & M.Lerner (Eds.), Responses to victimizations and belief in the just world (pp. 87105). New York: Plenum.
  • Dalbert, C. (1999). The world is more just for me that generally: About the personal belief in a just world scale's validity. Social Justice Research, 12, 7998.
  • Dalbert, C. (2001). The justice motive as a personal resource: Dealing with challenges and critical life events. New York: Kluwer/Plenum.
  • Dyer, N. G., Hanges, P. J., & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis techniques to the study of leadership. The Leadership Quarterly, 16, 149167.
  • Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12, 121138.
  • Evans, M. G. (1985). A Monte Carlo study of the effects of correlated method variance in moderated multiple regression analysis. Organizational Behavior and Human Decision Processes, 36, 305323.
  • Ferris, D. L., Brown, D. J., Lian, H., & Keeping, L. M. (2009). When does self-esteem relate to deviant behavior? The role of contingencies of self-worth. Journal of Applied Psychology, 94, 13451353.
  • Festinger, L. (1954). A theory of cognitive dissonance. Stanford: Stanford University Press.
  • Frijda, N. H. (1993). Moods, emotion, episodes, and emotions. In M.Lewis, & J. M.Haviland (Eds.), Handbook of emotions (pp. 381403). New York: Guildford Press.
  • Fritz, C., & Sonnentag, S. (2005). Recovery, health, and job performance: Effects of weekend experiences. Journal of Occupational Health Psychology, 10, 187199.
  • Furnham, A. (2003). Belief in a just world: Research progress over the past decade. Personality and Individual Differences, 34, 795817.
  • George, J. M., & Brief, A. P. (1992). Feeling good-doing good: A conceptual analysis of the mood at work-organizational spontaneity relationship. Psychological Bulletin, 112, 310329.
  • Gilbert, D. T., Giesler, R. B., & Morris, K. A. (1995). When comparisons arise. Journal of Personality and Social Psychology, 69, 227236.
  • Goodman, P. S., & Haisley, E. (2007). Social comparison processes in an organizational context: New directions. Organizational Behavior and Human Decision Processes, 102, 109125.
  • Gouldner, A. W. (1960). The norm of reciprocity: A preliminary statement. American Sociological Review, 25, 161178.
  • Grant, A. M., & Mayer, D. M. (2009). Good soldiers and good actors: Prosocial and impression management motives as interactive predictors of affiliative citizenship behaviors. Journal of Applied Psychology, 94, 900912.
  • Greenberg, J., Ashton-James, C. E., & Ashkanasy, N. M. (2007). Social comparison processes in organizations. Organizational Behavior and Human Decision Processes, 102, 2241.
  • Hafer, C. L., & Begue, L. (2005). Experimental research on just-world theory: Problems, developments and future challenges. Psychological Bulletin, 131, 128167.
  • Hafer, C. L., & Correy, B. L. (1999). Mediators of the relation between beliefs in a just world and emotional responses to negative outcomes. Social Justice Research, 12, 189204.
  • Hafer, C. L., & Olson, J. M. (1998). Individual differences in the belief in a just world and responses to personal misfortune. In L.Montada, & M.Lerner (Eds.), Responses to victimizations and belief in the just world (pp. 6586). New York: Plenum.
  • Heller, D., & Watson, D. (2005). The dynamic spillover of satisfaction between work and marriage: The role of time and mood. Journal of Applied Psychology, 90, 12731279.
  • Higgins, E. T. (1997). Beyond pleasure and pain. American Psychologist, 52, 12801300.
  • Humphrey, S. E., Nahrgang, J. D., & Morgeson, F. P. (2007). Integrating motivational, social, and contextual work design features: A meta-analytic summary and theoretical extension of the work design literature. Journal of Applied Psychology, 92, 13321356.
  • Ilies, R., Scott, B. A., & Judge, T. A. (2006). The interactive effects of personal traits and experienced states on intraindividual patterns of citizenship behavior. Academy of Management Journal, 49, 561575.
  • Ilies, R., Fulmer, I. S., Spitzmuller, M., & Johnson, M. D. (2009). Personality and citizenship behavior: The mediating role of job satisfaction. Journal of Applied Psychology, 94, 945959.
  • Isen, A. M., & Baron, R. A. (1991). Positive affect as a factor in organizational behavior. In L. L.Cummings, & B. M.Staw (Eds.), Research in organizational behavior (pp. 153). Greenwich, CT: JAI press.
  • John, O. P., & Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. In L. A.Pervin, & O. P.John (Eds.), Handbook of personality: Theory and research (pp. 102138). New York: Guilford Press.
  • Kamdar, D., & Van Dyne, L. (2007). The joint effects of personality and workplace social exchange relationships in predicting task performance and citizenship performance. Journal of Applied Psychology, 92, 12861298.
  • Kamdar, D., McAllister, D. J., & Turban, D. B. (2006). “All in a day's work”: How follower individual differences and justice perceptions predict OCB role definitions and behavior. Journal of Applied Psychology, 91, 841855.
  • Katz, D., & Kahn, R. L. (1966). The social psychology of organizations. New York: Wiley.
  • Kay, A. C., Wheeler, S. C., Bargh, J. A., & Ross, L. (2004). Material priming: The influence of mundane physical objects on situational construal and competitive behavioral choice. Organizational Behavior and Human Decision Processes, 95, 8396.
  • Kiecolt-Glaser, J. K., & Williams, D. A. (1987). Self-blame, compliance, and distress among burn patients. Journal of Personality and Social Psychology, 53, 187193.
  • Lee, K., & Allen, N. J. (2002). Organizational citizenship behavior and workplace deviance: The role of affect and cognitions. Journal of Applied Psychology, 87, 131142.
  • Lerner, M. J. (1978). “Belief in a just world” versus the “authoritarianism” syndrome… but nobody likes the Indians. Ethnicity, 5, 229237.
  • Lerner, M. J. (1980). The belief in a just world: A fundamental delusion. New York: Plenum Press.
  • Lerner, M. J., & Miller, D. T. (1978). Just world research and the attribution process: Looking back and ahead. Psychological Bulletin, 85, 10301051.
  • Lester, S. W., Meglino, B. M., & Korsgaard, M. A. (2008). The role of other orientation in organizational citizenship behavior. Journal of Organizational Behavior, 29, 829841.
  • Lipkus, I. (1991). The construction and preliminary validation of a global belief in a just world scale and the exploratory analysis of the multidimensional belief in a just world scale. Personality and Individual Differences, 12, 11711178.
  • Lipkus, I., Dalbert, C., & Siegler, I. (1996). The importance of distinguishing the belief in a just world for self versus for others: Implications for psychological well-being. Personality and Social Psychology Bulletin, 22, 666677.
  • Lockwood, P., & Kunda, Z. (1997). Superstars and me: Predicting the impact of role models on the self. Journal of Personality and Social Psychology, 73, 91103.
  • Lyubomirsky, S., & Ross, L. (1997). Hedonic consequences of social comparison: A contrast of happy and unhappy people. Journal of Personality and Social Psychology, 73, 11411157.
  • Mathieu, J. E., & Taylor, S. R. (2006). Clarifying conditions and decision points for meditational type inferences in Organizational Behavior. Journal of Organizational Behavior, 27, 10311056.
  • McAllister, D. J., Kamdar, D., Morrison, E. W., & Turban, D. B. (2007). Disentangling role perceptions: How perceived role breadth, discretion, instrumentality, and efficacy relate to helping and taking charge. Journal of Applied Psychology, 92, 12001211.
  • Moon, H., Kamdar, D., Mayer, D. M., & Takeuchi, R. (2008). Me or we? The role of personality and justice as other-centered antecedents to innovative citizenship behaviors within organizations. Journal of Applied Psychology, 93, 8494.
  • Moore, D. A. (2007). Not so above average after all: When people believe they are worse than average and its implications for theories of bias in social comparisons. Organizational Behavior and Human Decision Processes, 102, 4258.
  • Morrison, E. W. (1994). Role definitions and organizational citizenship behavior: The importance of the employee's perspective. Academy of Management Journal, 37, 15431567.
  • Motowidlo, S. J., Borman, W. C., & Schmit, M. J. (1997). A theory of individual differences in task and contextual performance. Human Performance, 10, 7183.
  • Mussweiler, T., & Bodenhausen, G. V. (2002). I know you are, but what am I? Self-evaluative consequences of judging in-group and out-group members. Journal of Personality and Social Psychology, 82, 1932.
  • Mussweiler, T., & Strack, F. (2000). The ‘relative-self’: Informational and judgmental consequences of comparative self-evaluation. Journal of Personality and Social Psychology, 79, 2338.
  • Muthen, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods and Research, 22, 376398.
  • Muthen, L. K., & Muthen, B. O. (2010). Mplus user's guide (6th edn). Los Angeles, CA: Muthen & Muthen.
  • Nezlek, J. B. (2001). Multilevel random coefficient analyses of event- and interval-contingent data in social and personality psychology research. Personality and Social Psychology Bulletin, 27, 771785.
  • O'Reilly, C. A., Chatman, J. A., & Caldwell, D. F. (1991). People and organizational culture: A profile comparison approach to assessing person-organization fit. Academy of Management Journal, 34, 487516.
  • Olson, B. D., & Evans, D. L. (1999). The role of the big five personality dimensions in the direction and affective consequences of everyday social comparisons. Personality and Social Psychology Bulletin, 25, 14981508.
  • Organ, D. W. (1988). Organizational citizenship behavior. Lexington, MA: Lexington.
  • Organ, D. W., & Ryan, K. (1995). A meta-analytic review of attitudinal and dispositional predictors of organizational citizenship behavior. Personnel Psychology, 28, 755802.
  • Organ, D. W., Podsakoff, P. M., & Mackenzie, S. B. (2006). Organizational citizenship behavior: Its nature, antecedents, and consequences. London: Sage.
  • Otto, K., Boos, A., Dalbert, C., Schöps, D., & Hoyer, J. (2006). Posttraumatic symptoms, depression, and anxiety of flood victims: The impact of the belief in a just world. Personality and Individual Differences, 40, 10751084.
  • Podsakoff, P. M., & MacKenzie, S. B. (1997). Impact of organizational citizenship behavior on organizational performance: A review and suggestion for future research. Human Performance, 10, 133151.
  • Podsakoff, P. M., MacKenzie, S. B., Paine, J. B., & Bachrach, D. G. (2000). Organizational citizenship behaviors: A critical review of the theoretical and empirical literature and suggestions for future research. Journal of Management, 26, 513563.
  • Podsakoff, P. M., MacKenzie, S. B., Lee, J., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879903.
  • Podsakoff, P. M., MacKenzie, S. B., Moorman, R. H., & Fetter, R. (1990). Transformational leader behaviors and their effect on followers' trust in leader, satisfaction, and organizational citizenship behaviors. The Leadership Quarterly, 1, 107142.
  • Prentice, D. A., & Miller, D. T. (1992). When small effects are impressive. Psychological Bulletin, 112, 160164.
  • Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd edn). Thousand Oaks, CA: Sage.
  • Raudenbush, S. W., Bryk, A. S., Cheong, Y. F., & Congdon, R. (2004). HLM 6: Hierarchical linear and nonlinear modeling. Chicago: Scientific Software International.
  • Rioux, S. M., & Penner, L. A. (2001). The causes of organizational citizenship behaviour: A motivational analysis. Journal of Applied Psychology, 86, 13061314.
  • Ritter, C., Benson, D. E., & Snyder, C. (1990). Belief in a just world and depression. Sociological Perspectives, 33, 235252.
  • Rotundo, M., & Sackett, P. R. (2002). The relative importance of task, citizenship, and counterproductive performance to global ratings of job performance: A policy-capturing approach. Journal of Applied Psychology, 87, 6680.
  • Smith, A. (1776/1994). An inquiry into the nature and causes of the wealth of nations. New York: Random House, Inc.
  • Smith, R. H. (2000). Assimilative and contrastive emotional reactions to upward and downward social comparisons. In J.Suls, & L.Wheeler (Eds.), Handbook of social comparison: Theory and research (pp. 173200). New York: Plenum.
  • Smith, C., Organ, D. W., & Near, J. P. (1983). Organizational citizenship behavior: Its nature and antecedents. Journal of Applied Psychology, 68, 653663.
  • Sobel, M. E. (1982). Asymptotic intervals for indirect effects in structural equations models. In S.Leinhart (Ed.), Sociological methodology (pp. 290312). San Francisco, CA: Jossey-Bass.
  • Sobel, M. E. (1986). Some new results on indirect effects and their standard errors in covariance structure models. Sociological Methodology, 13, 290312.
  • Spector, P. E., & Fox, S. (2002). An emotional-centered model of voluntary work behavior: Some parallels between counterproductive work behavior and organizational citizenship behavior. Human Resource Management Review, 12, 269292.
  • Stapel, D. A., & Koomen, W. (2001). I, we, and the effects of others on me: How self-construal level moderates social comparison effects. Journal of Personality and Social Psychology, 80, 766781.
  • Staple, D. A., & Koomen, W. (2005). Competition, cooperation, and the effects of others on me. Journal of Personality and Social Psychology, 88, 10291038.
  • Suls, J., & Wheeler, L. (2000). A selective history of classic and neo-social comparison theory. In J.Suls, & L.Wheeler (Eds.), Handbook of social comparison: Theory and research (pp. 322). New York: Plenum.
  • Tepper, B. J., Lockhart, D., & Hoobler, J. (2001). Justice, citizenship, and role definition effects. Journal of Applied Psychology, 86, 789796.
  • Toegel, G., Anand, N., & Kilduff, M. (2007). Emotion helpers: The role of high positive affectivity and high self-monitoring managers. Personnel Psychology, 60, 337365.
  • Van Dyne, L., Cummings, L. L., & McLean Parks, J. (1995). Extra-role behaviors: In pursuit of construct and definitional clarity (A bridge over muddied waters). In L. L.Cummings, & B. M.Staw (Eds.), Research in organizational behavior (pp. 215285). Greenwich, CT: JAI Press.
  • Van Dyne, L., Kamdar, D., & Joireman, J. (2008). In-role perceptions buffer the negative impact of low LMX on helping and enhance the positive impact of high LMX on voice. Journal of Applied Psychology, 93, 11951207.
  • Van Kleef, G. A. (2009). How emotions regulate social life: The emotions as social information (EASI) model. Current Directions in Psychological Science, 18, 184188.
    Direct Link:
  • Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 10631070.
  • Weiss, H. M., & Cropanzano, R. (1996). Affective events theory: A theoretical discussion of the structure causes and consequences of affective events at work. In L. L.Cummings, & B. M.Staw (Eds.), Research in organizational behavior (pp. 174). Greenwich, CT: JAI Press.
  • Wheeler, L., & Miyake, K. (1992). Social comparison in everyday life. Journal of Personality and Social Psychology, 62, 760773.
  • Wills, T. A. (1981). Downward comparison principles in social psychology. Psychological Bulletin, 90, 245271.
  • Wood, J. V. (1989). Theory and research concerning social comparisons of personal attributes. Psychological Bulletin, 106, 231248.
  • Wood, J. V. (1996). What is social comparison and how should we study it? Personality and Social Psychology Bulletin, 22, 520537.
  • Zellars, K. L., & Tepper, B. J. (2003). Beyond social exchange: New directions for organizational citizenship behavior theory and research. In J.Martocchio (Ed.), Research in personnel and human resources management (pp. 395424). Greenwich, CT: JAI Press.

Biographical Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

Jeffrey R. Spence is an Assistant Professor of Industrial/Organizational Psychology at the University of Guelph. His primary research interests include intraindividual processes, organizational citizenship behavior, workplace deviance, and employee performance appraisals.

Biographical Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

D. Lance Ferris is an assistant professor of organizational behaviour and human resource management at Singapore Management University. He received his Ph.D. in 2008 in industrial/organizational psychology from the University of Waterloo in Waterloo, Canada. His research interests focus on motivation, investigating self-enhancement/self-verification, approach/avoidance, and self-determination motivation processes in organizations. His work has been published in journals such as Journal of Applied Psychology, Organizational Behaviour and Human Decision Processes, Personnel Psychology, Journal of Management, Journal of Personality, and, as of this issue, Journal of Organizational Behaviour. In his spare time, he likes to write short author biographies wherein he refers to himself in the third person.

Biographical Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

Douglas J. Brown is Associate Professor of Industrial Organizational Psychology in the Department of Psychology at the University of Waterloo. Dr. Brown's primary research interests lie in the area of leadership and social cognition. He has published over 40 book chapters and articles in such journals as The Leadership Quarterly, Organizational Behavior and Human Decision Processes, Journal of Applied Psychology, Journal of Management, and Journal of Organizational Behavior. He is the co-author of the book Leadership Processes and Follower Self-Identity. Dr. Brown is currently an Associate Editor at Organizational Behavior and Human Decision Processes and is on the editorial boards of the Journal of Applied Psychology, The Canadian Journal of Behavioral Sciences, and Organizational Psychology Review.

Biographical Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Organizational Citizenship Behavior
  5. Social Comparisons
  6. Social Comparisons and AET
  7. Method
  8. Results
  9. Discussion
  10. Conclusion
  11. Acknowledgements
  12. Appendix: Model Specifications
  13. References
  14. Biographical Information
  15. Biographical Information
  16. Biographical Information
  17. Biographical Information

Daniel Heller is a senior-lecturer in the Faculty of Management at Tel Aviv University. His primary research interests are in the areas of personality dynamics, power, job satisfaction, and well-being.