《社会心理学》课程教学资源（文献资料）attitude&stereotype——Identifying Organizational Identification as a Basis for Attitudes and Behaviors - A Meta-Analytic Review

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Identifying Organizational Identification as a Basis for Attitudes and Behaviors: A Meta-Analytic Review Eun-Suk Lee Korea Advanced Institute of Science and Technology Tae-Youn Park Vanderbilt University Bonjin Koo Korea Advanced Institute of Science and Technology Organizational identification has been argued to have a unique value in explaining individual attitudes and behaviors in organizations, as it involves the essential definition of entities (i.e., individual and organizational identities). This review seeks meta-analytic evidence of the argument by examining how this identity-relevant construct functions in the nexus of attitudinal/behavioral constructs. The findings show that, first, organizational identification is significantly associated with key attitudes (job involvement, job satisfaction, and affective organizational commitment) and behaviors (in-role performance and extra-role performance) in organizations. Second, in the classic psychological model of attitude–behavior relations (Fishbein & Ajzen, 1975), organizational identification is positioned as a basis from which general sets of those attitudes and behaviors are engendered; organizational identification has a direct effect on general behavior above and beyond the effect of general attitude. Third, the effects of organizational identification are moderated by national culture, a higher-level social context wherein the organization is embedded, such that the effects are stronger in a collectivistic culture than in an individualistic culture. Theoretical and practical implications of the findings and future research directions are discussed. Keywords: organizational identification, attitude–behavior relations, culture, meta-analysis Supplemental materials: http://dx.doi.org/10.1037/bul0000012.supp Every entity needs to have a fundamental sense of identity— “Who am I?” or “Who are we?”—to appropriately and meaningfully relate to others and surrounding social contexts (Gioia, 1998; Jenkins, 2008). In a salient social domain in modern society (i.e., organizations; Haslam, 2004; Hogg & Terry, 2000), organizational identification reflects this sense of identity by capturing a psychological state wherein one defines one’s self by the same attributes that one believes define one’s organization (Dutton, Dukerich, & Harquail, 1994; Pratt, 1998). Organizational identification has often been highlighted as central because it involves the very essential definition of entities (i.e., individual and organizational identities), constituting a fundamental subtext based on which attitudes and behaviors in organizations are developed (Albert, Ashforth, & Dutton, 2000; Hogg & Terry, 2001; van Knippenberg & van Schie, 2000). Recognizing its importance, a large amount of research has revealed numerous correlates of organizational identification, and several qualitative reviews (Ashforth, Harrison, & Corley, 2008; Haslam & Ellemers, 2005; Pratt, 1998; van Dick, 2004) and a meta-analysis (Riketta, 2005) summarized those correlates. However, merely accumulating correlates does not necessarily offer evidence of the unique value of this identity-relevant construct (Ashforth et al., 2008). This study thus aims to provide systematic evidence of the implications of organizational identification by positioning it in the framework of attitude–behavior relations (Ajzen & Fishbein, 1977; Bentler & Speckart, 1981; Fishbein & Ajzen, 1975; Glasman & Albarracín, 2006), a classic theoretical lens in the psychology literature. By comparing alternative structural models, we examine how organizational identification functions in relation to work attitudes (job involvement, job satisfaction, and affective organizational commitment) and behaviors (in-role performance and extra-role performance), finally providing meta-analytic evidence that organizational identification uniquely affects behaviors in organizations, above and beyond the effects of attitudes. In doing so, we further extend the literature by examining whether and how the effects of organizational identification on attitudes/behaviors vary across different national cultural contexts. This article was published Online First May 18, 2015. Eun-Suk Lee, KAIST College of Business, Korea Advanced Institute of Science and Technology; Tae-Youn Park, Owen Graduate School of Management, Vanderbilt University; Bonjin Koo, KAIST College of Business, Korea Advanced Institute of Science and Technology. Eun-Suk Lee and Tae-Youn Park contributed equally to this work. We would like to thank Dolores Albarracín and the two anonymous reviewers whose comments greatly improved the quality of our arguments. We would also like to thank In-Sue Oh and the participants in the Academy of Management Annual Meeting and in the Organization/Strategy Seminar at KAIST College of Business for their insights and comments on drafts of this article. Correspondence concerning this article should be addressed to Eun-Suk Lee, KAIST College of Business, 85 Hoegi-ro Dongdaemun-gu, Seoul 130-722, Korea. E-mail: eunsuk@business.kaist.ac.kr This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Psychological Bulletin © 2015 American Psychological Association 2015, Vol. 141, No. 5, 1049 –1080 0033-2909/15/$12.00 http://dx.doi.org/10.1037/bul0000012 1049

Researchers have noted that the cultural value system espoused in a certain national context has critical implications for the effects of identity/identification in the organization (Baker, Carson, & Carson, 2009; Erez & Earley, 1993), but no cumulative evidence, to our knowledge, exists in the literature. Building upon the notion from cross-cultural research that national culture provides considerable inputs in shaping individual attitudes and behaviors (Gelfand, Erez, & Aycan, 2007; Taras, Kirkman, & Steel, 2010), we expect that the effects of organizational identification will vary depending on whether the national culture, wherein the organizational setting is embedded, concurrently values pursuing an identity overlap between an individual and a social collective (i.e., organization). In this study, we thus seek for meta-analytic evidence of how national culture moderates the relations between organizational identification and its attitudinal/behavioral outcomes. We believe that our consideration of national culture will substantially contribute to the organization identification literature by providing a comprehensive picture of organizational identification effects. The Effects of Organizational Identification As a dominant psychological approach to identity and identification, social identity theory explains how individuals construct their self-concepts from the identity of the collectives they belong to (Tajfel, 1978; Tajfel & Turner, 1985). Tajfel (1978) defined social identity as “that part of an individual’s self-concept which derives from his knowledge of his membership of a social group (or groups) together with the value and emotional significance attached to that membership” (p. 63). Social identities are shared by members and accentuate members’ perceived similarity. Members share the group’s prototypical traits, and thus depersonalize their self-concepts (Hogg, Terry, & White, 1995; Turner, Hogg, Oakes, Reicher, & Wetherell, 1987); through this process of categorizing the self into a more inclusive social entity, “I becomes we” (Brewer, 1991, p. 476). As a salient social domain in modern society, organizations provide a significant social identity (Haslam, 2004; Hogg & Terry, 2000). Organizational identification thus roots individuals in the organization, leading organizational attributes such as espoused values, goals, and norms to become salient and self-defining for individuals; through organizational identification, the identity boundary between individual and organization becomes blurred. In turn, an organizationally identified employee, as a “microcosm of the organization” (Ashforth et al., 2008, p. 333), is likely to have attitudes and take actions that benefit the whole organization rather than benefitting individual self-interest (Ashforth & Mael, 1989; Haslam & Ellemers, 2005; Pratt, 1998; van Knippenberg, 2000). To illustrate, when a Google employee describes herself as creative and innovative which are the attributes she ascribes to the Google organization (i.e., categorizing herself as a “Googler”), it reflects her organizational identification, and she is likely to think, feel, and behave in ways that are expected among prototypical Googlers. Below, we detail the theoretical rationales for how an individual’s work attitudes and behaviors are shaped by organizational identification. Attitudinal Outcomes Researchers have noted that organizational identification has significant impacts on individual attitudes in organizations. We focus on job involvement, job satisfaction, and affective organizational commitment, the three classic work attitudes in the literature (Brooke, Russell, & Price, 1988; Newman & Harrison, 2008; Newman, Joseph, & Hulin, 2010). Job involvement and job satisfaction. Job involvement refers to the “degree to which an employee psychologically relates to his or her job and to the work performed therein” (Cooper-Hakim & Viswesvaran, 2005, p. 244), and job satisfaction refers to an “evaluative state that expresses contentment with, and positive feelings about, one’s job” (Judge & Kammeyer-Mueller, 2012, p. 347). These two job attitude constructs are distinguishable in that job involvement reflects a cognitive belief state related to one’s job, while job satisfaction reflects an emotional state of liking the job that one performs (Brooke et al., 1988; Mathieu & Farr, 1991). Job involvement literature suggests that an individual tends to be more cognitively connected to one’s job when the job is perceived to be fulfilling one’s psychological needs (Kanungo, 1979, 1982). In this vein, researchers have proposed that individuals become more involved in their jobs when the jobs are designed to provide a sense of the meaningfulness—the sense that one’s contribution significantly influences the overall effectiveness of the organization (Brown, 1996; Hackman & Lawler, 1971; Hackman & Oldham, 1980). Along the same line of reasoning, individuals with high organizational identification are more likely to find their jobs meaningful because, with identity merging between individual and organization (van Knippenberg & Sleebos, 2006) or depersonalization (Brewer, 1991; Hogg et al., 1995), they are likely to sense that fulfilling their individual jobs simultaneously means contributing to the achievement of the organization’s objectives and missions. Accordingly, strong identifiers are more likely to be psychologically connected to or involved in their jobs, and several previous studies indeed have shown that organizational identification is positively associated with job involvement (e.g., Hassan, 2010; van Knippenberg & van Schie, 2000). We thus expect that organizational identification will increase job involvement. Organizational identification is also likely to enhance an individual’s emotional response to one’s job. Individuals have a basic need to view themselves positively (Allport, 1955; Steele, 1988) and actively pursue information to enhance their self-concepts (Baumeister & Jones, 1978; Tesser, 1988). For individuals with high organizational identification, the identities of the individual and the organization overlap, and thus they are inclined to seek positive aspects of their organization to attain a positive selfconcept (Bergami & Bagozzi, 2000; Dutton et al., 1994; Pratt, 1998). Their positive evaluation of the organization is, in turn, likely to lead them to feel satisfied with their jobs because job satisfaction is developed from one’s interpretation of the job circumstances (Brief, 1998) and strong identifiers tend to feel that they perform their jobs within the favorable job circumstance—the organization (van Dick et al., 2004a). In accordance with this logic, several previous studies have found that identification with the organization is positively related to the feeling of satisfaction with one’s job (e.g., van Dick et al., 2004a; van Dick, van Knippenberg, Kerschreiter, Hertel, & Wieseke, 2008; van Knippenberg This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1050 LEE, PARK, AND KOO

& van Schie, 2000). Hence, we expect that organizational identification will increase job satisfaction. Affective organizational commitment. Affective organizational commitment refers to an individual’s psychological bond with the organization constructed through an affective attachment to the organization and internalization of the organization’s values and goals (Judge & Kammeyer-Mueller, 2012). Affective organizational commitment bears a similarity to organizational identification because both regard an individual’s psychological attachment to the organization (O’Reilly & Chatman, 1986; Riketta & van Dick, 2005). However, commitment refers to a more general attitude constructed based on the perception of social exchange between individual and organization, two separate psychological entities; thus, it does not contain a self-defining nature, which is central in the concept of identification, thereby not reflecting psychological oneness (Ashforth & Mael, 1989) between individual and organizational identities (Ashforth et al., 2008; Cole & Bruch, 2006; Klein, Molloy, & Brinsfield, 2012; Pratt, 1998; van Knippenberg & Sleebos, 2006). Accordingly, researchers have suggested that it is reasonable to examine affective organizational commitment as an attitudinal outcome of organizational identification; as individuals develop a sense of oneness or identification with the organization, they build emotional bonds with and engagement in the organization, which leads them to be more committed to it (Bergami & Bagozzi, 2000; Meyer, Becker, & Vandenberghe, 2004; Meyer, Becker, & van Dick, 2006). In other words, identification is “the appropriation of identity” and commitment is “the binding to action” (Cheney & Tompkins, 1987, p. 9), which implies that possessing a social identity (i.e., identification) is a basis or a precursor for developing commitment to the corresponding collective (Meyer et al., 2006; Meyer & Herscovitch, 2001). In accordance with the empirical evidence supporting this theoretical view (e.g., Bergami & Bagozzi, 2000; Marique & Stinglhamber, 2011), we expect that organizational identification will increase affective organizational commitment. Behavioral Outcomes Previous research suggests that organizational identification also influences behaviors as well as attitudes in organizations. In-role performance. Individuals with high organizational identification are more likely to contribute to collective goals (i.e., organizational goals) by taking actions that benefit the whole organization (Haslam & Ellemers, 2005). One way of reifying behavioral responses to organizational identification is to successfully enact in-role behaviors that are required by formal job descriptions, directly serving the goals of the organization (Foote, 1951; van Knippenberg, 2000). Put differently, strong identifiers are likely to exert substantial individual efforts for the sake of organizational goals, and those efforts translate into their intrinsic motivation to perform well in their individual jobs, resulting in enhanced job performance (Haslam & Ellemers, 2005; van Knippenberg, 2000; van Knippenberg & van Schie, 2000). For instance, studies show that strong identifiers tend to share information and communicate with coworkers (Grice, Gallois, Jones, Paulsen, & Callan, 2006) and make choices that serve the organization’s strategic interests (Bartel, 2001; Tompkins & Cheney, 1985). Also, strong identifiers are more likely to engage in customer-oriented activities that critically contribute to organizational effectiveness (Farrell & Oczkowski, 2012; Homburg, Wieseke, & Hoyer, 2009). Based on all of this reasoning and evidence, we expect that organizational identification will increase in-role performance. Extra-role performance. Another notable behavioral outcome of organizational identification is extra-role performance— discretionary actions that are beyond formal job descriptions and not directly recognized by an organization’s formal reward system (Konovsky & Pugh, 1994; Podsakoff, MacKenzie, Paine, & Bachrach, 2000) such as employee voice behaviors (Van Dyne & LePine, 1998) and organizational citizenship behaviors (OCBs; Organ, 1997). For strong identifiers, voluntarily helping the organization achieve its goal (e.g., adhering to informal company rules, attending company meetings that are not mandatory) is important because the organization’s goal is theirs as well. In addition, for strong identifiers, other organizational members who comprise a significant part of their perceptions of what the organization is provide substantial meanings for their self-definitions (Sluss & Ashforth, 2007, 2008). Strong identifiers thus are likely to perceive that helping other organizational members through extra-role behaviors (e.g., willingly assisting others experiencing work-related problems, spending time helping newcomers) parallels helping themselves (Dukerich, Golden, & Shortell, 2002; van Dick, Grojean, Christ, & Wieseke, 2006). In sum, through organizational identification, they become good organizational citizens (Bergami & Bagozzi, 2000; van Dick et al., 2006). Previous studies have offered strong empirical support for this reasoning (Christ, van Dick, Wagner, & Stellmacher, 2003; Dukerich et al., 2002; Johnson, Morgeson, & Hekman, 2012; van Dick et al., 2006), and therefore we expect that organizational identification will increase extra-role performance. Uniqueness of organizational identification’s effects on behaviors. Those theoretical and empirical notions of the link between organizational identification and in-role/extra-role performance indicate that organizational identification influences behaviors not necessarily through attitudes. Some researchers have specifically argued that, different from attitudes which primarily capture relatively instrumental, ephemeral, or short-term motivators of behavior, identity and identification constitute relatively long-term or fundamental motivators (Charng, Piliavin, & Callero, 1988; Haslam & Ellemers, 2005; Sparks, 2000). In organizational settings, thus, when individuals identify with the organization, their identity label (Biddle, Bank, & Slavings, 1987) or identity standard (Stets & Burke, 2000) of a prototypical organizational member, as “agent or cause of behavior” (Burke & Reitzes, 1981, p. 83), is likely to lead them to exhibit behaviors that are favored in the specific organizational context (Terry & Hogg, 1996; Terry, Hogg, & White, 1999). In accordance with this notion, several empirical studies (e.g., Biddle et al., 1987; Charng et al., 1988) have shown that the effects of identity/identification on behaviors persist even after the effects of attitudes have been accounted for. However, other researchers have indicated that the effects of organizational identification on behaviors are not uniquely differentiated from those of attitudes because organizational identification conceptually overlaps with other attitude constructs—affective organizational commitment in particular (O’Reilly & Chatman, 1986; Riketta & van Dick, 2005). This alternative perspective comes from the notion that work attitudes are generally defined as cognitive and emotional evaluations of work experiences (Harrison, Newman, & Roth, 2006; Judge & KammeyerThis document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. THE EFFECTS OF ORGANIZATIONAL IDENTIFICATION 1051

Mueller, 2012) and organizational identification also involves evaluation of work experiences—an individual’s cognitive belief in and emotional attachment to the organizational membership (Ashforth et al., 2008; Edwards, 2005; Harquail, 1998). We test the validity of those two perspectives by formulating two alternative meta-analytic path models. According to the compatibility principle (Ajzen, 1988; Ajzen & Fishbein, 1977), attitudes lead to behaviors only when the measures of attitudes and behaviors are matched in their action, target, context, and time. Invoking this principle, researchers (Harrison et al., 2006; Newman et al., 2010) have shown that a general set of attitudes (i.e., a higher-order aggregate of work attitudes which connotes a broad evaluation of work experiences) provides maximal explanatory power when predicting a general set of behaviors (i.e., a higherorder aggregate of work behaviors broadly deemed effective in organizations) compared with when predicting each specific behavior separately. Accordingly, if there is a considerable conceptual overlap between organizational identification and other attitude constructs, a latent variable of general attitude encompassing job involvement, job satisfaction, affective organizational commitment, and organizational identification will be maximally predictive of a latent variable of general behavior which includes in-role performance and extra-role performance (Model 1 in Figure 1). However, if organizational identification is a unique construct that is distinctive from other attitude constructs, the other path model (Model 2 in Figure 2) that specifies organizational identification as a separate variable which functions as a basis influencing general behavior not only indirectly—through general attitude—but also directly—above and beyond the effect of general attitude—will have higher explanatory power than Model 1. National Culture as a Moderator of Organizational Identification Effects For a more comprehensive understanding of the attitudinal/ behavioral effects of organizational identification, we further examine the moderator of these effects: national culture. National culture shapes core values and norms shared and transmitted within the specific national context, thus providing the “collective programming of the mind” (Hofstede, 1984, p. 389) that controls individuals’ responses in the given context. According to culture– fit theory (Aycan, Kanungo, & Sinha, 1999; Kanungo & Jaeger, 1990), national culture, as a social context at the higher level, manifests its cultural value system in, and hence constraining, organizational policies and practices (Erez & Earley, 1993; Hofstede, 1983; Johns, 2006; Rabl, Jayasinghe, Gerhart, & Kühlmann, 2014), which in turn influence the attitudes and behaviors of individuals embedded in these layers of contexts (Gelfand et al., 2007; Taras et al., 2010). In this sense, by noting that “the validity of [management] theories may stop at national borders” (p. 82), Hofstede (1993) argued that national culture is a significant boundary condition of the phenomena around organizations and the individuals within them. Building on those previous notions, we expect that the effects of organizational identification on attitudes/ behaviors will be moderated by national culture; when pursuing the individual–organization identity connection is aligned with the cultural value system espoused in a specific national context, the organizational identification effects will be strengthened. Hofstede (1980, 2001) proposed five value dimensions that characterize cultural variability: individualism/collectivism, timeorientation, uncertainty-avoidance, power-distance, and masculinity/femininity. Among those five, previous theoretical and empirical considerations have suggested that the first three dimensions may have particular implications regarding organizational identification (Baker et al., 2009; Clugston, Howell, & Dorfman, 2000). Therefore, we take these three dimensions—individualism/collectivism, time-orientation, and uncertainty-avoidance—into consideration. Regarding individualism/collectivism, research shows that cultures differ in the extent to which they highlight an individual’s connectedness to collectives; individualistic culture prioritizes individual goals over the goals of collectives (e.g., an organization), whereas a collectivistic cultural value system makes less distinction between individual and collective goals (Hofstede, 1980, 2001; Triandis, 1995). Accordingly, in an individualistic culture, self-concept is defined in an independent way with an emphasis on an individual’s unique traits, and thus each individual is likely to value their independence in thinking, feeling, and acting as a unique entity. In contrast, in a collectivistic culture, self-concept is defined in an interdependent way with substantial influences of others in one’s social relationships, and thus individuals are likely to value attitudes and behaviors organized with reference to the social collectives to which they belong (Erez & Earley, 1993; Markus & Kitayama, 1991). In this vein, defining one’s self in terms of the organization, a significant social collective in modern Figure 1. Model 1: Organizational identification as a component of general attitude. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1052 LEE, PARK, AND KOO

society, is more congruent with the collectivistic than with the individualistic value system. Accordingly, we expect that organizational identification will have more salient effects on the work attitudes/behaviors of individuals in a collectivistic than in an individualistic culture. Supporting this, empirical evidence shows that psychological connection to the organization is more influential on work behaviors such as OCBs for those in a collectivistic culture than those in an individualistic culture (Felfe, Yan, & Six, 2008; Wasti, 2003). The other two dimensions, time-orientation and uncertaintyavoidance, are a less salient focus of empirical investigation, but they have implications for the effects of organizational identification. Time-orientation of a culture reflects a preference for past, present, or future thinking. In a short-term-oriented culture, individuals tend to pursue quick results and have weak propensities to save for the future. In a long-term-oriented culture, however, individuals exhibit a strong propensity to save and endure in attaining results (Hofstede, 2001; Hofstede & Bond, 1988). In terms of employment relationships, individuals in a short-termoriented cultural context are likely to seek immediate benefits by moving across organizations, whereas those in a long-termoriented cultural context may value long-term relationships with employing organizations, focusing on future achievements (Baker et al., 2009; Schalk & Soeters, 2008). Thus, we expect that in a long-term-oriented culture, having a deep psychological connection to an organization through organizational identification, in alignment with the cultural value system that highly regards longterm employment relationships, will have greater effects on work attitudes and behaviors than in a short-term-oriented culture. Uncertainty-avoidance reflects a society’s endurance for ambiguity and uncertainty. In an uncertainty-avoidance cultural context, individuals feel threatened by ambiguous situations and unpredictable environments (Hofstede, 1980), and thus are less inclined to leave their organizations to pursue job security and stabilized rules/values (Chew & Putti, 1995; Clugston et al., 2000). As a means of maintaining their present environments and positions, individuals in this context are likely to feel a sense of obligation to and identification with their current employer and pursue long tenure to minimize potential anxiety and loss (Baker & Carson, 2011; Schalk & Soeters, 2008). Based on this logic, we expect that, compared with a low uncertainty-avoidance culture, the organizational identification effects will be more salient in a high uncertainty-avoidance culture where the cultural value system supports the rationale for defining one’s self in terms of the stable social entity—the organization. Method Literature Search We employed multiple search strategies to identify all relevant English-written articles published before or during April, 2014. First, we searched the EBSCO, JSTOR, PROQUEST, ISI Web of Knowledge, PsycINFO, and Google Scholar databases using the keyword identification or identity in combination with organization or company and other keywords such as membership and categorization. Second, we looked through the reference sections of all qualitative and quantitative reviews on organizational identification (e.g., Ashforth et al., 2008; Edwards, 2005; Riketta, 2005). Third, using the cited reference search offered by the ISI Web of Knowledge, we searched among publications that had cited important articles in the field (e.g., Ashforth et al., 2008; Ashforth & Mael, 1989; Dutton et al., 1994; Mael & Ashforth, 1992; Pratt, 1998; Riketta, 2005). Fourth, we searched online for journals with organizational identification studies still in press (e.g., Psychological Bulletin, Journal of Applied Psychology, Academy of Management Journal, Organization Science, Administrative Science Quarterly, Personnel Psychology, Journal of Management, Journal of Organizational Behavior, Organizational Behavior and Human Decision Processes, International Journal of Human Resource Management). Finally, in an attempt to find unpublished manuscripts, we contacted authors who had recently Figure 2. Model 2: Organizational identification as a basis for general attitude and behavior. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. THE EFFECTS OF ORGANIZATIONAL IDENTIFICATION 1053

published in the area of organizational identification, and we also announced a call for unpublished manuscripts on organizational researchers’ e-mail list service such as the HR (human resources) Listserv and the OB (organizational behavior) Listserv. Those combined efforts yielded 341 published articles and 16 unpublished manuscripts and dissertations. Inclusion Criteria and Sample To be included in the meta-analysis, a study had to satisfy the following four criteria. First, the study had to address an organizational identification issue, not other types of identification issues, such as occupational identification, professional identification, and subgroup/team identification (e.g., Täuber & Sassenberg, 2012; Wann, Waddill, Polk, & Weaver, 2011). Second, the study had to be an empirical one that reported correlations between organizational identification and individual-level outcome variables. We thus excluded theory or review papers and empirical papers that used qualitative methods because they lacked the necessary information on the correlations between organizational identification and outcomes. Ninety-one articles were excluded for those two reasons. Third, the study had to report the correlation(s) between organizational identification and its attitudinal and/or behavioral outcome(s). Therefore, studies were excluded when they only include correlations between organizational identification and its antecedents (e.g., organizational prestige, perceived organizational support) or correlations between organizational identification and its outcomes other than attitudinal or behavioral ones (e.g., emotion, burnout, turnover intention). In this process, 99 articles were excluded. Fourth, the study had to measure organizational identification using the scales that emphasize an individual’s oneness perception or the self-defining nature of identification. A representative example is the Mael scale (Mael & Ashforth, 1992). This scale has long been known to measure the oneness perception of organizational identification, partly because of its association with the seminal article by Ashforth and Mael (1989), and thus has been the most widely used in the organizational identification literature (Haslam, 2004). The Mael scale includes items such as “When someone criticizes [name of organization], it feels like a personal insult,” and “When I talk about [name of organization], I usually say ‘we’ rather than ‘they.’” The scale developed by van Dick, Wagner, Stellmacher, and Christ (2004b) has also been widely used, as it contains the self-defining nature of identification. This scale includes items such as “I identify myself as a member of [name of organization],” and “Being a member of [name of organization] reflects my personality well.” Another exemplifying scale is the graphical Venn diagram scale which measures organizational identification as the degree of overlap between two circles that denote a respondent’s own identity and his or her organization’s identity (e.g., Bergami & Bagozzi, 2000). The studies included in our analysis, in which organizational identification was measured using the scales other than the Mael scale, are listed in Table 1. In some organizational identification scales (e.g., the Organizational Identification Questionnaire; Cheney, 1983), however, the operationalization of identification is similar to that of commitment, and thus they are not clearly distinguishable from organizational commitment scales such as the Organizational Commitment Questionnaire (Mowday, Steers, & Porter, 1979) and the Affective Commitment Scale (Allen & Meyer, 1990). Accordingly, we excluded studies using the identification scales similar to commitment scales, thus not adequately measuring the self-defining nature of identification. In this process, 18 articles were excluded from our meta-analysis. Table 1 also presents the list of those excluded studies. After applying all the inclusion criteria, we obtained an initial data set of 149 organizational identification– outcome correlations from 114 studies in 86 articles. The Appendix provides a summary of the studies and samples used in the meta-analysis, and the complete list of articles that were considered but ultimately excluded is in the online supplemental material. To calculate the overall correlation, we coded all possible zeroorder correlations from each study. Of the coded correlations, some of the correlations were nonindependent because they were computed from the same sample. Thus, when correlations were based on multiple measures of the same criterion in the same sample, such as intrinsic satisfaction and extrinsic satisfaction in Becker’s (1992) study, we combined the multiple measures into a composite using the composite formulas (Ghiselli, Campbell, & Zedeck, 1981, pp. 163–164). Fifty nonindependent correlations were combined for this reason. Yet, many studies still yielded more than one relevant correlation because we were interested in the relations between organizational identification and several different types of individual outcomes, such as job satisfaction, affective organizational commitment, and in-role performance. In such cases, adopting the approach used in the previous meta-analysis studies (e.g., Albarracín et al., 2005; Albarracín, Johnson, Fishbein, & Muellerleile, 2001; Baas, De Dreu, & Nijstad, 2008; Durantini, Albarracín, Mitchell, Earl, & Gillette, 2006), we allowed more than one correlation per study to be included in our final sample; that is, even after combining correlations for reasons of independence, we still used multiple correlations from one study if they concerned different types of outcomes—job satisfaction and in-role performance in Ashforth, Sluss, and Saks’ (2007) study, for example. Although multiple correlations were used from one study, we ensured that, in the analysis of the correlation between organizational identification and each specific outcome, we use only one correlation from one study, thus not violating the sample independence assumption (Cooper & Hedges, 1994). However, in the meta-analysis of the overall correlation between organizational identification and all outcomes, this approach could still violate the independence assumption. Hence, when we analyze this overall correlation, we used one correlation (i.e., the composite correlation) per study. Table 2 shows the stem-and-leaf display of the 114 independent correlations, and Figure 3 shows the funnel plot of the correlations. The funnel plot provides initial evidence that selection or publication bias is unlikely to be present because the distribution of sample is symmetrical and the form of a funnel centers on the mean effect size, with smaller variability as the sample size increases. We present more formal publication bias tests below. Coding of Studies The studies were coded independently by two coders for correlation, sample size, reliability estimates, type of organizational identification outcome, national culture, and study characteristics (e.g., data structure, publication status). The initial intercoder This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1054 LEE, PARK, AND KOO

agreement rates were high, ranging from 98% to 100% for the coding of job involvement, job satisfaction, affective organizational commitment, extra-role performance, national culture, data structure, and publication status. The initial intercoder agreement was somewhat lower for the coding of in-role performance (Cohen’s .92, p .001). Disagreements between raters were resolved by discussing coding criteria and further examination of the studies, which eventually resulted in an intercoder agreement rate of 100% for all coded information. Outcomes of organizational identification. Two categories were used to code the outcomes of organizational identification: attitudinal and behavioral outcomes. Attitudinal outcomes were coded using three subcategories: job involvement, job satisfaction, and affective organizational commitment. Behavioral outcomes were coded using two subcategories: in-role performance and extra-role performance. Some studies measured the constructs of in-role performance and extra-role performance using several different variable names. In such cases, we classified the variables into in-role and extra-role behaviors based on their definitions; performance behaviors were classified into in-role performance when they were required by formal job descriptions, directly serving the goals of the organization (van Knippenberg, 2000), while performance behaviors were classified into extra-role performance when they concerned discretionary actions beyond formal job descriptions (Podsakoff et al., 2000). For example, we coded variables such as productivity, job performance, customeroriented service behavior, and work effort into in-role performance, and coded variables such as organizational citizenship behavior, helping behavior, voice behavior, and safety performance into extra-role performance. We report all of our classification information in the Appendix. In addition, we coded the rater of performance variables because several researchers noted that self-reported measures can be affected by the self-serving bias (e.g., Borman, 1991; Spector, 1994). Table 1 Inclusion Decisions for the Studies Not Using the Mael Scale Organizational identification scale type Study Measure source Inclusion decision Newly developed scales since the Mael scale Gümüs et al. (2012) van Dick et al. (2004b) Included Michel et al. (2010) van Dick et al. (2004b) Included van Dick et al. (2004a) van Dick et al. (2004b) Included van Dick et al. (2006) Samples 1 to 7 van Dick et al. (2004b) Included van Dick et al. (2007) van Dick et al. (2004b) Included van Dick et al. (2008) van Dick et al. (2004b) Included Smidts et al. (2001) Smidts et al. (2001) Included Walumbwa et al. (2009) Smidts et al. (2001) Included Walumbwa et al. (2011) Smidts et al. (2001) Included Zhao et al. (2014) Smidts et al. (2001) Included Edwards & Peccei (2010) Edwards & Peccei (2007) Included Fuchs & Edwards (2012) Edwards & Peccei (2007) Included Peters et al. (2010) Doosje et al. (1995) Included Richter et al. (2006) Doosje et al. (1995) Included Norman et al. (2010) Avey et al. (2008) Included Christ et al. (2003) Christ et al. (2003) Included Johnson et al. (2012) Johnson et al. (2012) Included Stoner & Gallagher (2011) Stoner, Perrewé, & Hofacker (2011) Included Amiot et al. (2006) Terry & Hogg (1996) Included Hassan (2010) Tyler & Blader (2000) Included Graphical scales Bartel (2001) Bergami & Bagozzi (2000) Included Korschun et al. (2011) Bergami & Bagozzi (2000) Included Mayfield & Taber (2010) Shamir & Kark (2004) Included Wolfe (2007) Shamir & Kark (2004) Included Scales similar to organizational commitment scales Balfour & Wechsler (1991) Cheney (1983) Excluded Gautam et al. (2004) Cheney (1983) Excluded Ishii (2012) Cheney (1983) Excluded Johnson et al. (1996) Cheney (1983) Excluded Sass & Canary (1991) Cheney (1983) Excluded Scott et al. (1999) Cheney (1983) Excluded van Dick et al. (2006) Sample 10 Cheney (1983) Excluded Wolf (2009) Cheney (1983) Excluded Gould & Werbel (1983) Patchen (1970) Excluded Popoola (2005) Patchen (1970) Excluded Rotondi (1975) Patchen (1970) Excluded Jetten et al. (2002) Allen & Meyer (1996) Excluded Olkkonen & Lipponen (2006) Allen & Meyer (1990) Excluded O’Reilly & Chatman (1986) O’Reilly & Chatman (1986) Excluded Leavitt et al. (2011) O’Reilly & Chatman (1986) Excluded Kolodinsky et al. (2008) Efraty et al. (1991) Excluded Millward & Brewerton (1999) Millward & Brewerton (1999) Excluded Tyagi & Wotruba (1993) Not available Excluded This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. THE EFFECTS OF ORGANIZATIONAL IDENTIFICATION 1055

We distinguished in-role performance outcomes into self-reported, other-reported, and data-based. Similarly, we distinguished extrarole performance outcomes into self-reported and other-reported (Allen, Barnard, Rush, & Russell, 2000; Carpenter, Berry, & Houston, 2014). No study in our sample measured extra-role performance based on objective data. Moreover, we also distinguished extra-role performance by target: organizational citizenship behavior toward individuals (OCB-I) and toward the organization (OCB-O), following the previous notion of the distinctive characteristics of the two (Podsakoff, Whiting, Podsakoff, & Blume, 2009; Williams & Anderson, 1991). National culture. We coded national culture using the values provided by Hofstede, Hofstede, and Minkov (2010), as de Wit, Greer, and Jehn (2012) did in their meta-analysis. We first identified the geographical location in which the study was conducted. Example countries included in our study are the United States, Canada, Germany, China, France, the Netherlands, the Philippines, Thailand, Singapore, Pakistan, Australia, and Japan, to list a few (see the Appendix for all of the country information). After identifying the geographical locations, we assigned to each study the associated values of Hofstede et al.’s (2010) three cultural value dimensions: individualism/collectivism, long-term/short-term orientation, and uncertainty-avoidance. For example, the United States was coded 91 for individualism, 29 for long-termorientation, and 46 for uncertainty-avoidance. The same dimensions were coded 20, 118, and 30, respectively, for studies conducted in China. Study characteristics. We coded two aspects of study characteristics for additional exploratory moderator analyses. First, several researchers (e.g., Judge, Thoresen, Bono, & Patton, 2001) have noted that data structure, for example cross-sectional versus longitudinal, can influence correlations; cross-sectional data may present higher correlations than longitudinal data because of common method variance (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Thus, we coded data structure into three types: crosssectional data (concurrent measures of organizational identification and its outcomes), longitudinal data (time separation between the measurement of organizational identification and its outcomes), and panel data (correlations between average organizational identification across times and average outcomes across times). Second, the issue of publication bias, defined as the selective publication of studies that have statistically significant findings, has been an important issue for psychological science for at least three decades (e.g., Ferguson & Brannick, 2012; Rosenthal, 1979, 1995). To investigate whether publication bias exists in the organizational identification literature, we coded publication status into two categories: studies published in academic journals versus unpublished manuscripts and dissertations. Meta-Analysis Procedure All the correlations were first corrected for measurement error in the independent and dependent variables. We used the internal consistency coefficients reported in the respective study as the reliability estimates. When reliability estimates were available, we divided individual effect sizes by the square root of the reliability estimates of the two correlated variables, as recommended by Hunter and Schmidt (2004). Among the initial sample of 149 correlations, 12 correlations (8%) did not have the reliability estimate information for the organizational identification variable and 36 correlations (24%) did not have the reliability estimate information for the outcome variables. For studies that did not report a reliability estimate, we assigned them the average reliability estimate based on the estimates from other studies in our sample (Hunter & Schmidt, 2004). The artifact distribution of the reliability of organizational identification was a mean of .82 with a standard deviation of .07. The artifact distributions of the criterion variables’ reliabilities were mean .77 and standard deviation .11 for job involvement; mean .80 and standard deviation .09 for job satisfaction; mean .83 and standard deviation .05 for affective organizational commitment; mean .77 and standard deviation .11 for in-role performance; and mean .79 and standard deviation .09 for extra-role performance. We calculated meta-analytic correlations using a random effects model (Hunter & Schmidt, 2004) to consider heterogeneity among the studies. The random effects model assumes that sampling error plus variability in the population of the correlations (unique differences in the set of true population correlations) caused the variability among the organizational identification– outcome correlations. As an estimate of variability, we calculated 95% confidence intervals and 80% credibility intervals. A 95% confidence interval excluding zero indicates that one can be 95% confident Table 2 Stem and Leaf Display of 114 Correlations (r) Stem Leaf .1 .0 5,4 .0 1,2,3,3,3,4,5,5,5,5,6,8,8,9,9,9 .1 1,2,3,4,5,5,6,8,8,8,8,9,9 .2 0,0,0,0,0,0,0,1,2,2,2,3,3,3,4,4,4,5,5,5,6,6,7,7,7,8,8,9,9,9,9,9 .3 0,0,1,1,1,1,2,2,3,3,3,3,3,4,4,4,5,6,6,6,6,6,6,7,7,8,8,9,9,9 .4 0,0,0,1,1,1,1,1,1,2,3,3,3,3,4,4,5,6,6,6,7,7,8,8,8,8,8,9,9 .5 0,0,0,0,1,1,1,2,2,2,3,3,3,4,5,6,6,7,7,8,8,8 .6 1,3,5,6,6 .7 3 .8 Figure 3. Funnel plot of 114 independent correlations (r). This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1056 LEE, PARK, AND KOO

that the average true correlation is different from zero; thus, a maximum of 2.5% are larger than the upper bound of the interval and fewer than 2.5% are smaller than the lower bound. A credibility interval indicates whether the correlations reported are generalizable to other samples. For example, an 80% credibility interval excluding zero indicates that at least 80% of the correlations reported are different from zero. In addition, we conducted homogeneity analysis (Lipsey & Wilson, 2001), which tests whether it is reasonable to assume that all effect sizes are estimating the same population mean, using two indices: the Q-statistic, which indicates the level of variance across study results relative to the sampling error variance (Hedges & Olkin, 1985), and the I-squared (I 2 ) statistic, another indicator of homogeneity statistic (Higgins, Thompson, Deeks, & Altman, 2003). The Q-statistic indicates whether a statistically significant level of variability exists in correlations across studies, by calculating the categorical model results for the between-groups goodness-of-fit statistic (QB) and the within-group goodness-of-fit statistic (QW; Field, 2001; Hedges & Olkin, 1985; Lipsey & Wilson, 2001). The I 2 indicates the ratio of true heterogeneity to total variation in observed effect sizes, which ranges from 0% to 100% with higher values indicating greater heterogeneity of effect sizes and higher likelihood of moderators. Compared with the Q-statistic, the I 2 is known to be less affected by the scaling of the measures or the number of the studies included (Borenstein, Hedges, Higgins, & Rothstein, 2009). However, the I 2 should also be interpreted with caution because it depends on the size of individual studies (Higgins & Thompson, 2002). Finally, we created a correlation matrix using the meta-analytic correlations and conducted fixed-effect meta-analytic structural equation modeling (MASEM; Viswesvaran & Ones, 1995) to test our hypothesized path models (in Figures 1 and 2). In addition, to test the moderating effect of national culture on the relations between organizational identification and its outcomes, we conducted a random-effects weighted least square (WLS) regression analysis using the meta-regression SPSS syntax developed by Lipsey and Wilson (2001). Results Relations Between Organizational Identification and Outcomes Table 3 presents the analysis of the relations between organizational identification and its attitudinal/behavioral outcomes using the available correlations. The top panel of Table 3 reports the meta-analysis results using all available independent correlations (k 114; N 36,526). The average corrected correlation between organizational identification and all attitudinal/behavioral outcomes across all studies was positive ˆ .41), and the 95% confidence interval did not include zero (95% CI [.37, .45]). However, the corrected correlation showed large variance; the homogeneity of effect size tests was significant across the analyses (QW 1587.13, p .01). This indicates that the use of a random effects model is justifiable. It also indicates that moderators may be present for the associations between organizational identification and outcomes. The second panel of Table 3 presents the tests of the correlations between organizational identification and outcomes by outcome type: attitudinal outcomes and behavioral outcomes. The betweengroups goodness-of-fit statistic QB showed that the correlations between organizational identification and outcomes were significantly different across outcome types (QB(1) 17.96, p .01). Specifically, the results revealed that the size of the correlation between organizational identification and behavioral outcomes ˆ .35, 95% CI [.32, .39]) was smaller than that between organizational identification and attitudinal outcomes ˆ .49, 95% CI [.44, .54]). The third and fourth panels of Table 3 present the organizational identification correlations with detailed outcomes within each outcome type. The third set of results in Table 3 shows that organizational identification was significantly and positively related to job involvement ˆ .50, 95% CI [.39, .62]), job satisfaction ˆ .45, 95% CI [.40, .50]), and affective organizational commitment ˆ .64, 95% CI [.55, .72]). The fourth set of results in Table 3 reports the tests of the relations between organizational identification and behavioral outcomes. The QB indicates that the correlations between organizational identification and behavioral outcomes were significantly different across performance types (QB(1) 19.64, p .01). Specifically, the correlation between organizational identification and in-role performance was significant and positive ˆ .27, 95% CI [.20, .34]) and was smaller than the correlation between organizational identification and extra-role performance ˆ .42, 95% CI [.36, .48]). We further classified both performance outcomes based on the rater of performance. The relation between organizational identification and in-role performance was relatively high when in-role performance was self-rated ˆ .33, 95% CI [.23, .38]) and low when in-role performance was rated based on objective data ˆ .19, 95% CI [.03, .34]). The relation between organizational identification and extra-role performance was higher when extra-role performance was measured using self-rated measures ˆ .48, 95% CI [.43, .52]) than when it was measured using other-rated measures ˆ .29, 95% CI [.18, .39]) and the difference between the two was statistically significant (QB(1) 10.38, p .01). In addition, we also examined whether the relation between organizational identification and extra-role performance differed by target—OCB-I and OCB-O—and the results showed that they were not significantly different (QB(1) 2.02, ns). The fifth panel of Table 3 shows how the organizational identification– outcome correlations change depending on data structure—the study design used to collect the data. The results indicated that data structure did not significantly moderate the relations between organizational identification and its outcomes (QB(2) 2.09, ns). Positioning of Organizational Identification in General Attitude–Behavior Relations We used MASEM (Viswesvaran & Ones, 1995) to test how organizational identification functions in the nomological network of attitudinal and behavioral variables. To conduct the MASEM analysis, we first constructed the matrix of metaThis document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. THE EFFECTS OF ORGANIZATIONAL IDENTIFICATION 1057

analytic correlations among all of the study variables (see Table 4). We then entered this meta-analytic correlation matrix into an SEM analysis using AMOS (Version 18; Arbuckle, 2009). As the sample sizes across the various cells of the matrix were not identical, we calculated the harmonic mean of the sample sizes and used it for the SEM analyses (Viswesvaran & Ones, 1995). The harmonic mean is a more conservative parameter estimate than the arithmetic mean because it assigns much less weight to large sample sizes. We used five model fit indices—chi-square (2 ), the comparative fit index (CFI), the Tucker-Lewis index (TLI; also known as the non-normed fit index, Tucker & Lewis, 1973), the root-mean-square error of approximation (RMSEA), and the standardized root-mean-square residual (SRMR)—to investigate the viability of the structural models. Desirable model fit is associated with a CFI greater than .90, a TLI greater than .90, an RMSEA less than or equal to .08, and an SRMR less than .10 (Kline, 2005). Table 5 presents the comparison of two alternative models that position organizational identification differently in the attitude– behavior relations. First, we tested the model of organizational identification as a component of general attitude that treats organizational identification as constituting a general set of attitudes along with other types of attitudes (job involvement, job satisfaction, and affective organizational commitment; Model 1 in Figure 1). The MASEM results show that Model 1 did not fit the data particularly well (2 [8] 647.42, CFI .95, TLI .90, RMSEA .11, SRMR .04). Next, we tested the model of organizational identification as a basis for general attitude and behavior that treats organizational identification not as a part of general attitude but as an independent predictor of both general attitude and general behavior (Model 2 in Figure 2). When Model 2 was estimated, all of the fit indices reached acceptable levels (2 [7] 344.21, CFI .97, TLI .94, RMSEA .08, SRMR .03). In addition, to further compare the two models, we utilized Akaike’s information criterion (AIC; Akaike, 1974), which is generally used in SEM to compare non-nested models estimated using the same data (Henson, Reise, & Kim, 2007; Kline, 2005). The AIC for Model 2 (372.21) was smaller than that for Model 1 (673.42). As a lower AIC value indicates a better fit, this result indicates that Model 2 fit the data better than Model 1. Table 3 Meta-Analysis of Bivariate Relations Between Organizational Identification and Outcome Variables Variable kNr SDr ˆ SD 95% CI 80% CV I 2 QB QW All outcomes All independent correlations 114 36,526 .34 .21 .41 .21 [.37, .45] [.14, .69] 93% 1587.13 Outcome type 17.96 150.78 Attitudinal outcomes 55 18,084 .41 .14 .49 .22 [.44, .54] [.25, .73] 0% 46.90 Behavioral outcomes 94 43,754 .29 .19 .35 .19 [.32, .39] [.11, .60] 10% 103.88 Attitudinal outcomes 13.97 55.71 Job involvement 6 3,939 .41 .12 .50 .15 [.39, .62] [.31, .69] 42% 8.68 Job satisfaction 37 11,216 .37 .12 .45 .18 [.40, .50] [.22, .68] 0% 32.25 Affective organizational commitment 12 2,929 .52 .14 .64 .17 [.55, .72] [.42, .86] 26% 14.77 Behavioral outcomes 19.64 94.29 In-role performance 41 13,870 .22 .13 .27 .26 [.20, .34] [.06, .60] 27% 39.78 In-role performance by rater 2.66 40.43 Self-rated 20 8,468 .27 .13 .33 .18 [.23, .38] [.13, .53] 14% 22.16 Other-rated 16 3,315 .18 .16 .23 .16 [.14, .31] [.03, .43] 5% 15.83 Data-based 5 2,087 .09 .13 .19 .18 [.03, .34] [.04, .42] 0% 2.44 Extra-role performance 53 14,459 .35 .15 .42 .22 [.36, .48] [.18, .66] 5% 54.52 Extra-role performance by rater 10.38 48.75 Self-rated 39 9,928 .38 .12 .48 .19 [.43, .52] [.27, .68] 0% 34.66 Other-rated 9 1,753 .24 .12 .29 .15 [.18, .39] [.08, .49] 21% 14.09 Extra-role performance by target 2.02 22.94 OCB-I 5 927 .23 .18 .27 .20 [.09, .45] [.01, .53] 0% 1.34 OCB-O 18 4,089 .34 .17 .42 .21 [.32, .51] [.15, .69] 21% 21.60 Study characteristics Data structure 2.09 149.41 Cross-sectional 138 59,419 .34 .12 .41 .23 [.38, .45] [.16, .67] 0% 140.33 Longitudinal 10 2,275 .26 .16 .32 .19 [.19, .44] [.05, .58] 0% 9.08 Panela 1 144 .36 .17 .39 .21 [.01, .79] [.13, .65] — — Publication status .70 149.67 Academic journal articles 140 44,188 .34 .12 .41 .24 [.38, .44] [.15, .67] 3% 143.56 Unpublished manuscripts/dissertations 9 2,225 .29 .18 .35 .21 [.22, .48] [.09, .61] 0% 6.12 Note. k number of correlations from independent samples; N total sample size for all studies combined; r sample-size weighted mean correlation; SDr sample-size weighted observed standard deviation of correlation; ˆ mean true-score correlation corrected for measurement error in both predictor and criterion measures; SD standard deviation of the true-score correlation corrected for measurement error in both predictor and criterion measures; 95% CI lower and upper limits of 95% confidence interval; 80% CV lower and upper limits of 80% credibility interval; I 2 homogeneity statistic; QB homogeneity statistic Q between groups; QW homogeneity statistic Q within group; OCB-I organizational citizenship behavior toward individuals; OCB-O organizational citizenship behavior toward the organization. a The meta-analytic correlation in this row may not be meaningful because k is less than 3, but we decided to report this for informational purposes. p .01. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1058 LEE, PARK, AND KOO

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