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(a) Research question and key hypotheses If the research has six hypotheses or less, please present all of them. If the research has more than six hypotheses, you can only present the hypotheses that you think are important and interesting.
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Reading the article attached please explain as a speech and as a report two different sections but with the same content. Speech should be no longer than 2.5 mins
(a) Research question and key hypotheses If the research has six hypotheses or less, please present all of them. If the research has more than six hypotheses, you can only present the hypotheses tha
Rating Leniency and Halo in Multisource Feedback Ratings: Testing Cultural Assumptions of Power Distance and Individualism-Collectivism Kok-Yee Ng, Christine Koh, Soon Ang, Jeffrey C. Kennedy, and Kim-Yin Chan Nanyang Technological University This study extends multisource feedback research by assessing the effects of rater source and raters’ cultural value orientations on rating bias (leniency and halo). Using a motivational perspective of performance appraisal, the authors posit that subordinate raters followed by peers will exhibit more rating bias than superiors. More important, given that multisource feedback systems were premised on low power distance and individualistic cultural assumptions, the authors expect raters’ power distance and individualism-collectivism orientations to moderate the effects of rater source on rating bias. Hierarchical linear modeling on data collected from 1,447 superiors, peers, and subordinates who provided develop- mental feedback to 172 military officers show that (a) subordinates exhibit the most rating leniency, followed by peers and superiors; (b) subordinates demonstrate more halo than superiors and peers, whereas superiors and peers do not differ; (c) the effects of power distance on leniency and halo are strongest for subordinates than for peers and superiors; (d) the effects of collectivism on leniency were stronger for subordinates and peers than for superiors; effects on halo were stronger for subordinates than superiors, but these effects did not differ for subordinates and peers. The present findings highlight the role of raters’ cultural values in multisource feedback ratings. Keywords:multisource feedback, culture, power distance, individualism-collectivism, rating bias Organizations routinely use subjective performance ratings for administrative as well as developmental purposes. However, these ratings are often challenged for their validity because “bias per- vades the typical rating” (Wherry & Bartlett, 1982, p. 550). Instead of measuring ratees’ performance, “ratings were stronger reflec- tions of raters’ overall biases” (Lance, 1994, p. 768). Two biases that are ubiquitous in performance ratings are (a) leniency, defined as the tendency for raters to assign higher ratings and (b) halo— raters’ failure to differentiate among different dimensions of the ratee’s behaviors (Murphy & Balzer, 1989; Saal, Downey, & Lahey, 1980). As a result of these biases, Murphy and Cleveland (1995) noted that “it is not unusual to find that 80% to 90% of all employees are rated as ‘above average’” (p. 275). Rating biases are likely to be even more prevalent in multi- source feedback (MSF) systems, which have become very popular in organizations in and outside the United States. This is because unlike conventional feedback systems that rely on superiors’ rat- ings alone, MSF involves ratings from peers and subordinates. Ratings from these nontraditional sources of feedback are rela- tively less understood (Mount & Scullen, 2001), and MSF scholars have warned that these raters may not be willing to provide honestfeedback because of the risk of potential repercussions from ratees (Kudisch, Fortunato, & Smith, 2006; Murphy & Cleveland, 1995; Westerman & Rosse, 1997). This suggests that peers and subor- dinates could be more likely to inflate their ratings (leniency) across multiple behavioral dimensions (halo) in order to avoid consequences of negative feedback. Furthermore, rating biases could be exacerbated when raters possess cultural beliefs that are inconsistent with the practice of giving upward or lateral feedback (Leslie, Gryskiewicz, & Dalton, 1998). This concern stems from the widespread recognition that MSF, as a practice that originated in the United States, is premised on underlying assumptions of individualistic and low-power dis- tance values (Fletcher & Perry, 2001; Leslie et al., 1998; Shipper, Hoffman, & Rotondo, 2007; Stone-Romero & Stone, 2002; Varela & Premeaux, 2008). For instance, seeking (or providing) “objec- tive” feedback on an individual’s behaviors is based on individu- alistic values that emphasize personal striving and self- assertiveness (De Luque & Sommer, 2000; Morrison, Chen, & Salgado, 2004; Stone-Romero & Stone, 2002). Involving peers and subordinates also signals a redistribution of evaluative powers away from the superior and, hence, is more compatible with low-power distance values that are less sensitive to status and hierarchy (Leslie et al., 1998; Shipper et al., 2007). These argu- ments suggest that raters, particularly peers and subordinates, may be even more prone to rating biases when their power distance and individualism-collectivism value orientations are inconsistent with the premise of MSF. Surprisingly, even though concerns relating to nontraditional sources of feedback and culture have been raised in the MSF literature, no empirical study has examined both of these issues simultaneously. As rating bias can undermine the quality of MSF ratings (Antonioni & Woehr, 2001), understanding how different This article was published Online First April 11, 2011. Kok-Yee Ng, Soon Ang, Jeffrey C. Kennedy, and Kim-Yin Chan, Division of Strategy, Management and Organization, Nanyang Technolog- ical University, Singapore; Christine Koh, Division of Information Tech- nology and Operations Management, Nanyang Technological University. Correspondence concerning this article should be addressed to Kok-Yee Ng, Center for Innovation Research in Cultural Intellegence, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798. E-mail: [email protected] Journal of Applied Psychology© 2011 American Psychological Association 2011, Vol. 96, No. 5, 1033–10440021-9010/11/$12.00 DOI: 10.1037/a0023368 1033 raters (especially peers and subordinates) and their cultural value orientations affect rating behaviors will offer important insights to organizations adopting MSF in the global workplace. In addressing this research question, we aim to close two major gaps in the existing research. First, research has shown that rater effects account for substan- tially more variance in MSF ratings than ratee effects, particularly for peer and subordinate ratings (Greguras & Robie, 1998; Scullen, Mount, & Goff, 2000). According to Scullen et al. (2000), rater effects were 2.08 times larger than ratee effects for peer ratings, 1.86 times larger for subordinate ratings, and only 1.21 times larger for boss ratings. These findings highlight the importance of rater idiosyncratic effects but do not specify what rater attributes are likely to affect MSF ratings. We address this gap by focusing on raters’ power distance and individualism-collectivism value orientations because they are relevant to the cultural assumptions of MSF, and to respond to the increasing use of MSF in today’s diverse and global workplace (Atwater, Wang, Smither, & Fleenor, 2009). Although power distance and individualism-collectivism origi- nated as constructs that distinguish people across cultures (e.g., Hofstede, 2001), more recent research has argued that there is substantial within-culture variation in value orientations arising from regional, ethnic, religious, and generational differences (Hof- stede, 2001; Kirkman, Lowe, & Gibson, 2006). This has prompted a growing number of researchers to examine power distance and individualism-collectivism as individual-differences constructs that vary within a single culture (e.g., Chan & Drasgow, 2001; Farh, Hackett, & Liang, 2007; Ilies, Wagner, & Morgeson, 2007; Kirkman, Chen, Farh, & Chen, 2009; Ng & Van Dyne, 2001). Consistent with these studies, we examine power distance and individualism-collectivism as individuals’ beliefs about desirable end states that will affect their rating behaviors in the context of MSF. Second, existing research comparing rating biases across differ- ent rater sources have produced inconsistent findings. For instance, several studies found peer ratings to be more lenient than super- visor ratings (Schneier, 1977; Springer, 1953; Zedeck, Imparto, Krausz, & Oleno, 1974), but others did not find significant differ- ences across the different groups of raters (e.g., Harris & Schau- broeck, 1988; Holzbach, 1978; Klimoski & London, 1974; Tsui, 1984; Wohlers, Hall, & London, 1993). Findings on halo are likewise mixed. For example, whereas Lawler (1967) found peer ratings to exhibit comparable halo effects as superior ratings, Klimoski and London (1974) found that halo effect was stronger for peer than for superior ratings. In all these studies, comparisons of ratings across rater source were based on aggregate ratings pooled within each rater source (i.e., comparing aggregated supe- rior ratings against aggregated peer and aggregated subordinate ratings). This aggregate approach offers less precise findings for understanding raters’ rating bias because it does not take into account (a) individual raters’ idiosyncracies, which have been found to account for a major portion of MSF ratings (Mount, Judge, Scullen, Sytsma, & Hezlett, 1998; Scullen et al., 2000) and b) the nonindependence of MSF ratings, because multiple obser- vations are provided to a common ratee (i.e., ratee effects). As advocated by Murphy and Cleveland (1995), we examine rater bias at the individual rater level, rather than at the aggregate level. We use a nested rating design in which raters were nestedwithin ratee (i.e., each ratee received ratings from at least one superior, three peers, and three subordinates). This allows us to more rigorously assess how, for the same target of observation (i.e., ratee), individual raters’ biases differ as a function of their hierarchical level and cultural value orientations. We adopt hier- archical linear modeling to focus on individual raters’ biases (Level 1) while controlling for common ratee effects (Level 2). By addressing the methodological weaknesses in prior studies, our study aims to offer more conclusive insights on the effects of rater source on rating biases. Below, we develop our research hypotheses and report our study comprising 1,447 superiors, peers, and subordinates who provided ratings on 172 ratees in an MSF program conducted for leadership development purposes. Rater Source on Rating Bias Research and anecdotal evidence have shown that a major cause of rating biases is raters’ motivation (Harris, 1994; Murphy & Cleveland, 1995; Spence & Keeping, 2010). This perspective recognizes that raters are not “passive measurement instruments” whose sole interest is to provide accurate measures of ratees’ performance (Murphy & Cleveland, 1995, p. 215). Rather, rating behaviors are often consciously or unconsciously guided by raters’ goals. Two rater goals that are widely documented in the literature are (a) helping ratees improve their performance (Murphy & Cleveland, 1995; Wong & Kwong, 2007) and (b) averting negative consequences for oneself, and/or for the relationship with the ratee (Harris, 1994; Murphy & Cleveland, 1995; Spence & Keeping, 2010). These two goals work in conflict to affect rating behaviors. Wong and Kwong (2007) showed that raters who are motivated to help ratees improve their performance by identifying their strengths and weaknesses are more likely to provide ratings with less leniency and less halo. However, raters who are motivated to avoid negative outcomes are more likely to give ratings with greater leniency and halo. In the context of a developmental MSF, the anonymity of response and the absence of administrative consequences for the ratees should ideally encourage raters to help their ratees improve their performance. In reality, however, raters are still likely to be concerned with potential negative consequences of providing ac- curate feedback (Spence & Keeping, 2010). This is because unfa- vorable feedback, even when provided for developmental pur- poses, has been found to arouse anger and discouragement in ratees (Brett & Atwater, 2001), which could adversely affect raters. Mount and Scullen (2001) also observed that subordinates, in particular, are likely to “feel intimidated or uncomfortable about rating the boss, even though assurances have been made that the ratings are confidential and anonymous” (p. 157). Hence, raters asked to provide developmental MSF generally have conflicting goals. We contend that the degree of conflict between helping ratees improve and avoiding negative outcomes differs across raters with different hierarchical relationships with the ratee. A key organiza- tional feature that distinguishes superior, peer, and subordinate raters is their level ofposition power, defined as the amount of influence one has over the other arising from one’s formal position in the organization (Bass, 1960). Position power can be further described as comprising reward, coercive, and legitimate power 1034 NG, KOH, ANG, KENNEDY, AND CHAN (French & Raven, 1959; Yukl & Falbe, 1991), all of which can affect raters’ motivation and rating behaviors. Specifically, raters who possess greater reward and coercive power should have less concern for providing candid feedback because they control more organizational resources than the ratees (e.g., Bettenhausen & Fedor, 1997; Kudisch et al., 2006; Murphy & Cleveland, 1995). This should help mitigate raters’ leniency arising from fear of negative consequences (Spence & Keeping, 2010). Raters with greater legitimate power to develop their ratees should be more motivated to help their ratees improve, because doing so is aligned with the expectations of members of their role set (Pfeffer & Salancik, 1975). This should encourage raters to provide feedback that will help ratees discern their strengths and weaknesses, thus resulting in ratings with less halo. Taken together, we propose that superiors, compared with peers and subordinates, are least concerned with negative outcomes and most motivated to help their ratees improve. This is because superiors, by virtue of their reward and coercive power, should be less concerned with negative consequences compared with peer and subordinate raters (Kudisch et al., 2006). Moreover, compared with peers and subordinates, superiors have greater legitimate power to help their employees improve their performance through useful feedback (Kudisch et al., 2006; London, 2003; Westerman & Rosse, 1997). Therefore, we expect superiors to exhibit the least leniency and halo in their ratings. In contrast, subordinates have the weakest reward and coercive power because they are dependent on their superior ratees for important resources at work that include tangible resources such as rewards and job opportunities, as well as intangible resources such as information and advice (Yukl & Falbe, 1991). As a result, subordinates are hesitant to provide feedback that may invoke negative emotions from their ratees (cf. Brett & Atwater, 2001), which could lead to negative consequences such as administrative reprisals or the withholding of valued resources (Bettenhausen & Fedor, 1997; Kudisch et al., 2006; Murphy & Cleveland, 1995). In addition, subordinates are likely to feel the least legitimate to provide feedback to their superiors for improvement, because upward ratings seriously violate the status hierarchy inherent in organizational structures (Westerman & Rosse, 1997). Hence, we expect subordinates’ ratings to display greatest leniency and halo. Peers should be more concerned than superiors with potential negative consequences of unfavorable feedback because of their mutual dependence on each other for resources such as informa- tion and cooperation (Fedor, Bettenhausen, & Davis, 1999). Com- pared with superiors, peers are also less likely to feel responsible for their peers’ development. Fedor et al. (1999) noted that peer appraisals can be perceived as additional responsibilities that go beyond one’s psychological contract of their job and employment relationships. However, compared with subordinates, peers pos- sess greater reward and coercive power to the extent that peers can choose to provide or withhold intangible resources such as infor- mation, cooperation, and harmony due to their equal position power in the organization. Peers are also likely to feel more legitimate than subordinates to help their ratees identify their strengths and weaknesses because of their level of proximity and interdependence with the ratees (Fedor et al., 1999). Hence, we expect peers to exhibit more bias than superiors, but less bias than subordinates, in their MSF ratings.Hypothesis 1 (H1):Compared with superiors, subordinates are more likely to show rating bias in terms of (a) leniency and (b) halo. Hypothesis 2 (H2):Compared with superiors, peers are more likely to show rating bias in terms of (a) leniency and (b) halo. Hypothesis 3 (H3):Compared with peers, subordinates are more likely to show rating bias in terms of (a) leniency and (b) halo. Next, we argue that raters’ cultural value orientations will fur- ther accentuate the effects of rater source on rating leniency and halo. Moderating Effects of Cultural Value Orientations Value orientationsrefer to an individual’s beliefs about desir- able end states that guide selection or evaluation of behavior and events (Schwartz & Bilsky, 1987). By specifying what is right and wrong, cultural value orientations guide individuals to select cer- tain behaviors over others according to their internalized criteria and goals (Erez & Earley, 1993). Below, we consider how indi- vidual differences in power distance and individualism- collectivism, two cultural assumptions underlying MSF, moderate effects of rater source on rating leniency and halo. Power Distance Value Orientation Power distancedescribes the extent to which individuals accept social stratification and unequal distribution of power in the soci- ety. Individuals with high power distance believe that they should respect and obey those with authority and power, and adhere more to organizational hierarchy than individuals with low power dis- tance (Hofstede, 2001). Consequently, individuals with high power distance are more conscious of status differences and how their behaviors should properly reflect these differences during interac- tions. However, those with low power distance are less attuned to distinctions arising from status positions and value equal partici- pation in decisions (Atwater et al., 2009). Power distance has direct implications for MSF. Several schol- ars have suggested that because of the acceptance of unequal power distribution by employees in high-power distance cultures, soliciting feedback from individuals with lower position and less power is seen as a severe violation of the status hierarchy (Fletcher & Perry, 2001; Shipper et al., 2007). Shipper et al. (2007), for instance, in comparing participants’ reactions to their MSF ratings, found that those from countries with high power distance, such as Malaysia, reported lower commitment and higher tension com- pared with participants from low-power distance countries such as Ireland. Interestingly, no research has focused on the effects of power distance from the rater’s perspective. Building on our earlier arguments that superiors, peers, and subordinates will display differing degrees of leniency and halo because of different moti- vation, we argue that raters’ power distance value orientation will further moderate the relationship between rater source and rating bias. Specifically, we expect that the influence of power distance values on rating leniency and halo will be stronger for subordinates than for superiors. Subordinates with high power distance, being 1035 RATING LENIENCY AND HALO IN MSF more sensitized to status markers than their low-power distance counterparts (Earley, 1999; Ng & Van Dyne, 2001), are likely to perceive a greater psychological distance between themselves and their superiors in terms of reward, coercive, and legitimate power (Antonakis & Atwater, 2002). Furthermore, high-power distance subordinates are concerned with managing “face” issues to main- tain and cultivate their social networks with people from higher social positions (Kim & Nam, 1998). To these individuals, pro- viding negative feedback to one’s superior causes the superior to lose “face” and threatens the social order (Bond, Wan, Leung, & Giacalone, 1985; Kim & Nam, 1998). Taken together, we argue that high power distance will accentuate subordinates’ motivation to avoid negative consequence, and attenuate subordinates’ moti- vation to help ratees improve, so that high-power distance subor- dinates will display greater leniency and halo than their low-power distance counterparts. In comparison, superiors’ motivation to provide feedback should be less affected by raters’ power distance values, because providing feedback to help subordinates improve is a typical and legitimate role for superiors. This argument is supported by Scul- len et al.’s (2000) finding that across all rater sources, superiors’ ratings demonstrated the least idiosyncratic effects. Likewise, compared with subordinates, we propose that peers’ power distance will have less effect on their motivation to give feedback, and hence on their rating bias. This is because there is no substantial power difference between peers and their ratees to trigger the effect of power distance orientation. Given that concern for “face protection” is less salient for individuals with equal or more power than the target (Kim & Nam, 1998), we do not expect the effect of power distance on rating leniency and halo to differ for peers and superiors. Hypothesis 4 (H4):Power distance moderates the relationship between rater source and rating bias such that power distance will exert a greater positive impact on subordinates’ rating bias in terms of (a) leniency and (b) halo, compared with superiors. Hypothesis 5 (H5):Power distance moderates the relationship between rater source and rating bias such that power distance will exert a greater positive impact on subordinates’ rating bias in terms of (a) leniency and (b) halo, compared with peers. Individualism-Collectivism Value Orientation Individualism-collectivism describes how an individual sees him- or herself in relation with the collective (Hofstede, 2001). Individualists view the self as independent of others, focus on personal goals, act on personal beliefs and values, and emphasize task outcomes, whereas collectivists construe the self as an inter- dependent entity, adopt group goals, act according to social norms, and stress good interpersonal relationships (Markus & Kitayama, 1991; Triandis, 1995). Related to the emphasis on harmony and relationship, collectivists are concerned with maintaining the face of others in their group, and hence strive to avoid or prevent the embarrassment of others. However, individualists are more con- cerned with preserving their own face. Taken together, these attributes of individualism-collectivism suggest that collectivists,being more concerned with how their behaviors affect relation- ships and group harmony, may be more motivated to avoid the negative social consequences of giving negative feedback than to provide feedback to help ratees improve. Of greater interest in our study is how ratings by superiors, peers, and subordinates are influenced by their individualism- collectivism value orientation. We argue that individualism- collectivism orientation will affect ratings of subordinates and peers more than that of superiors. As with our earlier arguments, superiors’ formal power should provide a stronger motivation for giving accurate feedback to help ratees improve, which will min- imize the effects of individual differences in individualism- collectivism on rating leniency and halo (cf. Scullen et al., 2000). Compared with superiors, we expect subordinates’ collectivistic value orientation to exert a stronger and positive effect on their rating leniency and halo. Because collectivistic subordinates tend to prefer personalized relationships with their superior more than individualists (Hogg et al., 2005), they are more motivated to avoid damaging their relationship with their superior than to provide accurate feedback to help their superior improve. Furthermore, given that collectivists are generally less driven than individualists to act in ways that are consistent with their private thoughts (Markus & Kitayama, 1991), we expect collectivistic subordinates to have less motivation to provide accurate feedback, compared with their individualistic counterparts. Likewise, we expect peers’ collectivistic value orientation to exert a stronger and positive effect on their ratings compared with superiors. Compared with superiors, peer raters are likely to ex- perience a greater dilemma when providing accurate feedback (Antonioni & Park, 2001). Although accurate feedback will help peer members develop and perform better, which in turn will help the team, accurate and unfavorable feedback can damage working relationships and weaken the team’s social climate (de Nisi & Mitchell, 1978; Drexler, Beehr, & Stetz, 2001). Therefore, we argue that collectivistic peers are more motivated to avoid negative social consequences of candid feedback, whereas individualistic peers are more motivated to help their team members improve in order to enhance self and team performance. Thus, we expect collectivistic peers to display more leniency and halo than indi- vidualistic peers (Atwater et al., 2009; Hofstede, 2001). Hypothesis 6 (H6):Individualism-collectivism moderates the relationship between rater source and rating bias such that individualism-collectivism will exert a greater positive im- pact on subordinates’ rating bias in terms of (a) leniency and (b) halo, compared with superiors. Hypothesis 7 (H7):Individualism-collectivism moderates the relationship between rater source and rating bias such that individualism-collectivism will exert a greater positive im- pact on peers’ rating bias in terms of (a) leniency and (b) halo, compared with superiors. Method Participants and procedure.The present hypotheses were tested using MSF ratings collected for developmental purposes in the Singapore Armed Forces. According to the GLOBE’s study of 62 societies (House, Hanges, Javidan, Dorfman, & Gupta, 2004), Singapore ranks 17th on ingroup collectivism and 42nd on power 1036 NG, KOH, ANG, KENNEDY, AND CHAN distance. Despite the relatively high collectivism score, significant within-country variation in individuals’ value orientations can be expected. This is because Singapore is a multiracial, multicultural, multireligious, and multilingual society. Most people speak at least two languages—English and their native tongue (Mandarin, Ma- lay, or Tamil)—and are generally bicultural, endorsing a mix of traditional Asian and Western values (Chen, Ng, & Rao, 2005). Moreover, Singapore has a long history of significant foreign investment by businesses from the United States and European Union countries, resulting in a cultural heritage that “reflects values of both the East and the West” (Li, Ngin, & Teo, 2007, p. 950). Participants were military officers attending a 9-month leader- ship program. As part of the program, participants obtained MSF from their direct superior(s), peers, and subordinates in their units. In addition to providing feedback on ratees’ leadership behaviors, observers also provided information on their own cultural value orientations (power distance and individualism-collectivism) and demographics. The final sample comprises 172 ratees who had fulfilled the organization’s specified rating requirements (at least one superior, three peers, and three subordinates). In total, 1,447 observer ratings were obtained. On average, each ratee received 8.7 ratings (ranging from 7 to 14), with an average of 1.3 superior (ranging from 1 to 2), 3.6 peer (ranging from 3 to 6), and 4.1 subordinate (ranging 3 to 8) ratings. Ratees were predominantly male (94%), with an average age of 33.4 years (SD 1.5) and have spent an average of 2.6 years (SD 2.0) in the current unit within the organization. Raters were also mostly male (90%), with an average age of 33.8 years (SD 7.2) and have spent an average of 3.7 years (SD 4.7) in the unit within the organization. Measures. Rating leniency.In field research where true scores of perfor- mance are not available, rating leniency is operationalized by the level of ratings, with higher ratings demonstrating greater leniency (e.g., Bernardin, Cooke, & Villanova, 2000; Heidemeier & Moser, 2009; Mount, 1984; Tsui & Barry, 1986). Consistent with these studies, leniency is operationalized with the average rating that raters provide on ratees’ leadership skills. These leadership skills were assessed using an instrument developed by the organization for their leadership development program. The instrument mea- sures six critical skills covering conceptual, task, and relational aspects of leadership that are important to the organization. Raters were presented with a total of 119 behavioral statements and asked to rate how accurately each statement described the ratee (1 not at all,7 to a very great extent). Cronbach’s alpha for the six scales all exceeded 0.80 (ranging from 0.84 to 0.90). Consistent with existing research (e.g., Brett & Atwater, 2001), the six scales were aggregated to obtain an overall leadership rating (Cronbach’s 0.97). Rating halo.Consistent with previous studies (e.g., Vance, Winne, & Wright, 1983; Wong & Kwong, 2007), rating halo is operationalized as the standard deviation of the six scales, with lower variability representing greater halo. Rater source.Rater source was coded using two dummy vari- ables, subordinates (1 subordinate, 0 not subordinate) and peers (1 peer, 0 not peer), with superiors being the omitted reference category. The superior is chosen as the reference source, as research shows that superior ratings tend to be the most valid (Scullen et al., 2000).Power distance.Power distance was measured with three items adapted from Dorfman and Howell (1988) (1 strongly disagree,7 strongly agree; Cronbach’s 0.81). A sample item was “I believe it is important to respect the decisions made by those who have more power.” The higher the score, the greater the power distance. Individualism-collectivism.Individualism-collectivism was measured with three items adapted from Earley (1993) (1 strongly disagree,7 strongly agree; Cronbach’s 0.94). A sample item was “I prefer to work in a group rather than by myself.” The higher the score, the greater the collectivism. Controls.Research on relational demography suggests that ratees who share similar demographic attributes (e.g., age, gender, job and company tenure) as raters tend to be rated more positively (Tsui & O’Reilly, 1989). Thus, both raters’ and ratees’ age (mea- sured in years), gender (coded as 1 male, 2 female), and tenure in the organizational unit (in years) were controlled for in the analyses. In addition, raters’ liking for the ratee was controlled for, given that research has found raters’ affect for ratees to be a significant predictor of rating bias (e.g., Antonioni & Park, 2001; Tsui & Barry, 1986). Liking was measured with three items adapted from Tsui and Barry (1986) (1 not at all well,5 to a very great extent; Cronbach’s 0.80). A sample item was “How well do you like this person?” Analyses.Before the hypotheses were tested, the discrimi- nant validity of the measures was examined using confirmatory factor analysis (CFA) with LISREL 8 (Jreskog & Sörbom, 2006). Results of the proposed four-factor structure (leadership rating, power distance, individualism-collectivism, and liking) demon- strated good fit with the data, 2(84,N 1,477) 526.37,p .00; root-mean-square error of approximation (RMSEA .060); standardized root-mean-square residual (SRMR .030); non- normed fit index (NNFI) .98; comparative fit index (CFI) .98. All items loaded significantly on their predicted constructs, with standardized factor loadings ranging from .68 to .98. Composite reliabilities all exceeded 0.70 (rating .97; power distance .81; collectivism .95; and liking .80). Relative fit of the hypothesized four-factor model was further compared with several alternate models. Results showed that the four-factor model demonstrated better fit compared with (a) a three-factor model that combined leadership rating and liking, 2(87–84 3,N 1,447) 1325.99,p .001; (b) a two-factor model that combined leadership rating and liking as one factor, and power distance and collectivism as another factor, 2(89–84 5,N 1,447) 2640.07,p .001; (c) a two-factor model that combined power distance, collectivism, and liking as one factor, 2(89–84 5,N 1,447) 3225.98,p .001; and (d) a one-factor model in which all items loaded on a single factor, 2(90–84 6,N 1,447) 6746.25,p .001. Taken together, the fit indices of the nested models show that leadership rating, individualism-collectivism, power distance, and liking were distinct constructs. The hypotheses were tested using hierarchical linear modeling (HLM) (Bryk & Raudenbush, 1992). The data are inherently nested in nature, with each ratee being rated by multiple raters. This gives rise to the possibility of nonindependence of data, which violates an underlying assumption of ordinary least squares estimation. HLM addresses this by maintaining the appropriate level of analysis (Hofmann, 1997) and allows the examination of 1037 RATING LENIENCY AND HALO IN MSF the effect of Level 1 (rater) predictors while controlling for Level 2 (ratee) effect. All Level 1 variables were group mean centered because the primary interest involves only Level 1 predictors, as this “removes all between-cluster variation from the predictor and yields a ‘pure’ estimate of the pooled within-cluster (i.e., level 1) regression coefficient” (Enders & Tofighi, 2007, p. 128). Sensi- tivity analysis with grand mean centering showed a similar pattern of results. Following recommended practice (Kreft & de Leeuw, 1998), a null model with no predictors was first specified to test whether there is significant variation between ratees in rating leniency and halo, a necessary precondition for supporting the present hypoth- eses. Next, controls were added for both Level 1 (rater age, gender, organizational unit tenure, liking) and Level 2 (ratee age, gender, organizational unit tenure) equations in Step 1, rater source (peer and subordinate vs. superior) in Step 2, and cultural values and the interaction terms between cultural values and rater source in Step 3. Results are reported in the final step of the present analyses. The ttests associated with the estimated parameters provide a direct test of the present hypotheses. The effect size of each step was computed by comparing each step’s new value of 2(within-group variance) with the 2of the null model: R Level 1 model2 ) ( null model2 current model2 )/ null model2 . This ratio represents the percentage of the Level 1 (rater) vari- ance in the dependent variable accounted for by the added predic- tors (Bliese, 2002; Bryk & Raudenbush, 1992; Hofmann, 1997). Results Table 1 presents descriptives, correlations, and internal consis- tencies of all variables. Table 2 presents the results of our HLM analyses. Results of our null models for leniency and halo showed that there was significant between-ratee variance atp .01 (ICC for leniency .175; ICC for halo .050). Hence, the prerequisitecondition of systematic between-ratee variance in the dependent variables was satisfied. Not surprisingly, results of Models 3 and 6 showed that raters who had greater liking for their ratees showed more leniency ( 0.44,p .01) and halo ( 0.03,p .01). All the other controls were not significantly related to either leniency or halo. H1–H3 predicted that rater source will exert a main effect on rating leniency and halo. Specifically, H1 and H2, respectively, predicted that subordinates and peers will show more rating bias than superiors in terms of leniency (H1a, H2a) and halo (H1b, H2b). Results of Model 3 showed that, compared with superiors, subordinates ( 0.26,p .01) and peers ( 0.11,p .01) were more lenient, thus supporting H1a and H2a. Results of Model 6 showed that, compared with superiors, subordinates exhibited greater halo ( 0.02,p .01). However, the effect for peers was not significant ( 0.01,ns). Hence, H1b was supported but not H2b. H3 predicted that subordinates will show more leniency (H3a) and halo (H3b) than peers. Given that both peers and subordinates were included categories in our equation, we compared the two regression coefficients ( sub and peer ) using the contrast test in HLM (Hox, 2002; Raudenbush & Bryk, 2002). A contrast test is essentially a composite hypothesis that tests whether the two regression coefficients are equal (i.e., sub peer ) and is based on an asymptotic chi-square test. A benefit of using the contrast test is the “protection against heightened probability of Type I errors that arises from performing many univariate tests” (Raudenbush & Bryk, 2002, p. 60). Results of the contrast test showed that the difference in the two coefficients for leniency was significant, 2(1,N 1,447) 58.25,p .01, indicating that subordinates gave more lenient ratings than peers. Likewise, comparison of peers’ and subordi- nates’ coefficients for halo was significant, 2(1,N 1,447) 9.61,p .01, indicating that subordinates showed greater rating halo compared with peers. Hence, H3a and H3b were supported. Table 1 Means, Standard Deviations, Scale Reliabilities, and Intercorrelations Among Variables a VariableMSD12345678910111213 1. Rating leniency 5.57 0.77 (.97) 2. Rating halo 0.32 0.19 .43 — 3. Collectivism (IC) 5.32 1.48 .10 .04 (.94) 4. Power distance (PD) 3.95 1.34 .05 .03 .28 (.81) 5. Peer b 0.41 0.49 .14 .07 .02 .01 — 6. Subordinate b 0.45 0.50 .18 .08 .09 .05 .75 — 7. Rater age 33.78 7.21 .00 .06 .04 .04 .03 .21 — 8. Rater gender c 1.10 0.30 .06 .03 .05 .04 .02 .05 .09 — 9. Rater org. tenure 3.66 4.73 .05 .07 .02 .00 .12 .15 .39 .13 — 10. Liking 3.68 0.65 .38 .12 .16 .07 .05 .12 .18 .12 .07 (.80) 11. Ratee age 33.44 1.46 .05 .05 .05 .05 .01 .00 .10 .07 .04 .07 — 12. Ratee gender c 1.06 0.23 .06 .01 .03 .03 .00 .01 .02 .02 .02 .00 .04 — 13. Ratee org. tenure 2.62 2.04 .05 .03 .04 .01 .00 .01 .08 .01 .28 .08 .16 .01 — Note. Reliability coefficients are in parentheses along the diagonal. Correlations between ratee-level variables (11–13) and rater-level variables are calculated by assigning the same ratee score to all raters rating the ratee (N 1,447). Intercorrelations between the ratee-level variables are calculated at the ratee level (N 172). org. organizational. aN 1,447. bRater type was coded using two dummy variables—subordinate (1 yes, 0 no) and peer (1 yes, 0 no), with superior being the omitted reference category. cGender was coded as 1 male, 2 female. p .05. p .01. 1038 NG, KOH, ANG, KENNEDY, AND CHAN The next two hypotheses, respectively, proposed that subordi- nates’ power distance will exert a stronger positive impact on their ratings compared with superiors (H4a: leniency; H4b: halo) and peers (H5a: leniency; H5b: halo). Results demonstrate that the interaction terms between subordinate and power distance in pre- dicting leniency (Model 3: 0.07,p .01) and halo (Model 6: 0.02,p .01) were significant. Specifically, the effects of power distance on both leniency and halo were significantly stron- ger for subordinates than for superiors. Thus, H4a and H4b were supported. To test whether subordinates’ power distance exerted a stronger influence on ratings compared with peers (H5), we similarly de- fined a contrast between the two regression coefficients (i.e., PD sub PD peer ). Results of the contrast test for both leniency and halo showed that the Subordinate Power Distance Effect was significantly stronger than the Peer Power Distance Effect in predicting leniency, 2(1,N 172) 4.61,p .05, and halo, 2(1,N 172) 6.28,p .05. Thus, H5a and H5b were supported. As we expected, the interaction term between peers and power distance was not significant for both leniency (Model 3: 0.03, ns) and halo (Model 6: 0.00,ns), suggesting that the effect of power distance on ratings did not differ between peers and supe- riors. The last two hypotheses, respectively, proposed that subordi- nates’ (H6) and peers’ (H7) individualism-collectivism will exert a stronger positive impact on their leniency (H6a, H7a) and halo (H6b, H7b) compared with superiors. Results demonstrate that the interaction terms between individualism-collectivism and subordi- nates were significant for both leniency (Model 3: 0.08,p .01) and halo (Model 6: 0.03,p .01), thus suggesting thatthe effect of individualism-collectivism was stronger for subordi- nates’ ratings than for superiors’ ratings. Hence, H6a and H6b were supported. For peers, the interaction term between individualism-collectivism and peers was significant for leniency (Model 3: 0.05,p .05) but not for halo (Model 6: 0.02, ns). Hence, H7a was supported but not H7b. Although not hypothesized, we tested whether the effect of individualism-collectivism on rating bias was stronger for subor- dinates than for peers. Results of the contrast tests for both leni- ency and halo showed that the Subordinate Individualism- Collectivism terms were not significantly different from the Peer Individualism-Collectivism terms for both leniency, 2(1, N 172) 1.80,p ns, and halo, 2(1,N 172) 1.33,p ns, suggesting that the effect of individualism-collectivism on ratings did not differ between subordinates and peers. The main and interaction effects of rater cultural value orienta- tions explained an additional 8% of variance for leniency and 17% for halo. Overall, our hypothesized model accounted for 27% of the within-ratee (i.e., Level 1) variance in MSF ratings for leniency and 23% for halo. Figure 1 illustrates the general form of interaction between rater source and rater value orientations on leniency and halo. Discussion Our study examines a long-standing concern that nontraditional sources of feedback may be more susceptible to rating bias such as leniency and halo (Kudisch et al., 2006; Murphy & Cleveland, 1995; Westerman & Rosse, 1997). More important, we provide timely insights to the cultural assumptions of MSF by examining the moderating impact of raters’ power distance and Table 2 HLM Results Predicting Rating Leniency and Halo VariableLeniency Halo Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Level 1 (Rater) Intercept 5.58 5.58 5.58 0.32 0.32 0.32 Age 0.01 0.00 0.00 0.00 0.00 0.00 Gender 0.02 0.03 0.03 0.02 0.02 0.02 Org. tenure 0.02 0.00 0.00 0.00 0.00 0.00 Liking 0.40 0.44 0.44 0.03 0.04 0.03 Peer 0.11 0.11 0.01 0.01 Subordinate (Sub) 0.25 0.26 0.02 0.02 Power distance (PD) 0.01 0.00 Collectivism (IC) 0.04 0.01 PD Peer 0.03 0.00 PD Sub 0.07 0.02 IC Peer 0.05 0.02 IC Sub 0.08 0.03 Level 2 (Ratee) Age 0.02 0.02 0.02 0.00 0.00 0.00 Gender 0.19 0.19 0.21 0.01 0.01 0.01 Org. tenure 0.02 0.02 0.02 0.00 0.00 0.00 Level 1 variance explained (R Level 12 )a 0.13 0.19 0.27 0.04 0.06 0.23 Note. N(Level 1) 1,447;N(Level 2) 172. Entries corresponding to the predicting variables are estimations of the fixed effects (standard errors not shown). HLM hierarchical linear modeling; Org. Organizational. aAll Level 1 variables were group mean centered. All Level 2 variables were grand mean centered. p .05. p .01. 1039 RATING LENIENCY AND HALO IN MSF individualism-collectivism orientations on rating leniency and halo. Results of our HLM analyses provide important verifications as well as novel insights that can contribute to the science and practice of MSF, in the following ways. First, our study generally supports our first three hypotheses that rater source exerts a systematic effect on rating leniency and halo. As expected, our research shows that subordinates consistently display more leniency and halo in their ratings compared with peers and superiors. This finding corroborates with anecdotes of subordinates’ hesitation to violate status hierarchy with upward feedback (Kudisch et al., 2006; Westerman & Rosse, 1997). Re- sults for peers’ ratings are more mixed and potentially interesting. Our study supports the ordered effects for peers’ leniency (subor- dinates peers superiors) but not for peers’ halo (subordi- nates peers superiors). This pattern of findings seems to suggest that of the three rater sources, peers, who are in between superior and subordinate raters, face the greatest conflict between avoiding negative consequences versus helping ratees improve their performance. This dilemma appears to result in a creative rating pattern that seeks to avoid negative social consequences (through giving lenient feedback) and, at the same time, helps ratees identify their strengths and weaknesses to improve (through giving more discriminant feedback, i.e., less halo). Second, we found clear support for our proposed moderating effects of power distance on rater source and rating behaviors. Consistent with H4, power distance exerts the strongest impact on subordinates’ rating leniency and halo. These findings suggest that subordinates with high power distance are most susceptible to rating bias, because they are more likely than others to perceive that upward feedback violates the subordinate-superior status hi- erarchy. Compared with subordinates, superiors’ and peers’ ratings were less affected by raters’ power distance. This could be due to the fact that status difference—an important condition to activate power distance—is not as salient for peer and superior raters. Third, and consistent with our final hypothesis, the effects of individualism-collectivism on rating leniency and halo were stron- ger for subordinates than for superiors. We expect individualism- collectivism to have the least impact on rating leniency and halo for superiors because of their formal power, and our results support this argument. Results for peers are mixed. Compared with supe-riors, peers’ individualism-collectivism value exerts a stronger effect on rating leniency, but not on halo. This finding could imply that whereas collectivistic peers are more motivated to avoid damaging relationships with ratees than individualistic peers (and hence, provided more lenient ratings), both collectivistic and in- dividualistic peers are equally motivated to provide feedback that helps ratees identify their strengths and weaknesses (and hence, did not differ on halo). In summary, our results show that rater characteristics play an important role in affecting MSF ratings. In our study, 83% of the total variance in leniency, and 95% of the total variance in halo, reside at Level 1 (i.e., rater level), rather than at Level 2 (i.e., ratee level). This is consistent with Scullen et al.’s (2000) conclusion that rater effects account for more variance in MSF ratings than ratee effects. More important, our study shows that raters’ hierar- chical level, collectivism, and power distance values together explain 14% of Level 1 variance in leniency and 19% of Level 1 variance in halo. Specifically, our results largely support our prediction that peers’ and subordinates’ ratings are more likely to be influenced by their power distance and individualism- collectivism value orientations, compared with superiors. Subor- dinates, in particular, are the most susceptible to rating biases when they possess value orientations that are inconsistent with the premise of MSF. Peers’ ratings are less different from superiors’, especially when it concerns halo. Our findings also corroborate Scullen et al.’s conclusion that rater biases accounted for more variance in subordinate ratings than in either superior or peer ratings. Our study contributes to Scullen et al.’s study by showing that power distance and individualism-collectivism are specific idiosyncratic attributes that can explain meaningful variance in subordinates’ upward ratings in MSF. They also provide important empirical evidence that sheds some light on the cultural assump- tions, and hence, cultural boundaries of MSF. Theoretical implications and future research directions. Findings of this study have several implications for future research on MSF ratings in a global work environment. First, our present findings are based on MSF ratings gathered for developmental purposes. Future research should examine how the purpose of MSF would affect the results reported in this study. For instance, existing studies have found that ratings collected for administrative purposes are more prone to rating bias than those collected for developmental purposes (Farh, Cannella, & Bedeian, 1991; Harris, Smith, & Champagne, 1995; Jawahar & Williams, 1997). This is because, compared with developmental ratings, administrative rat- ings carry more important stakes for the ratees (e.g., no pay increase) that are likely to accentuate potential repercussions on the raters (e.g., retaliatory behaviors or decreased motivation to perform). This argument implies that MSF conducted for admin- istrative purposes could present a “strong” situation that dimin- ishes interindividual differences in promoting rating bias, thus suggesting that the effects of rater source and rater cultural value orientations could be dampened. Second, our present findings on interaction effects involving rater’s cultural values highlight the possible cultural boundaries of the usefulness of MSF. Echoing the recent recommendation by Gelfand, Erez, and Aycan (2007) for future research on cross- cultural organizational behavior to move beyond individualism- collectivism, we urge future studies to examine other cultural values that are relevant to predicting rating leniency and halo. For Rating Leniency/Halo Rater Power Distance/ Rater Collectivism Low High Low High Superior Peer Subordinate Figure 1.General form of interaction between rater source and rater’s power distance/collectivism on rating leniency and halo. 1040 NG, KOH, ANG, KENNEDY, AND CHAN instance, future research could examine raters’ social axioms, defined as individuals’ general beliefs about themselves and their environment (Leung et al., 2002), to augment our existing under- standing of value-based cultural dimensions. In particular, the social axiom of societal cynicism, which describes individuals’ mistrust of people and social institutions, could affect raters’ views toward MSF, and hence, influence their willingness to provide accurate ratings. Third, future research could assess raters’ motivation (e.g., Murphy, Cleveland, Skattebo, & Kinney, 2004; Wong & Kwong, 2007) as a set of mediating mechanisms that explain the effects of rater source and cultural values on rating behaviors. This will empirically ascertain, for instance, whether subordinates with high collectivistic and power distance orientations give more lenient and less differentiated ratings because they are more motivated to avert negative consequences and less motivated to provide feed- back that will help ratees improve. Having a more in-depth under- standing of the underlying mechanisms can in turn offer more precise insights on the interventions that are needed to encourage accurate feedback, thus ensuring that the purpose of MSF is realized. Strengths and limitations.Our study has several method- ological strengths. First, direct assessment of raters’ cultural value orientations is rare in MSF studies because of concerns of rater survey fatigue and nonparticipation. This could be why even though scholars have highlighted the critical role of culture in MSF more than a decade ago (London & Smither, 1995), systematic empirical research on the topic is scarce. The few empirical studies on culture and MSF (Atwater et al., 2009; Entrekin & Chung, 2001; Heidemeier & Moser, 2009; Shipper et al., 2007) did not directly assess raters’ or ratees’ value orientations but instead examined group differences based on Hofstede’s (2001) or GLOBE’s (House et al., 2004) societal level scores for power distance and individualism-collectivism. Our study, by assessing raters’ cultural values at the individual level of analysis, acknowl- edges important intracultural variation in value orientations (Hof- stede, 2001; Kirkman et al., 2006), and also offers a unique opportunity to examine the psychological impact of culture on MSF participants. Second, our nested design and our HLM analyses enable us to test our hypotheses at the level of the individual rater, and at the same time account for ratee effects. Our study also presents a novel application of HLM in the study of rater bias. As such, this article advances a methodological improvement over previous research that has examined mean rating level differences across the three rater sources usingttests or analysis of variance. As with most MSF research, restriction in variance in perfor- mance is likely to have attenuated relationships in our model (Lebreton, Burgess, Kaiser, Atchley, & James, 2003). This is particularly true for our study conducted with a sample of military leaders undergoing a leadership development program. In spite of such restriction, and the conventional belief that ratings should be determined largely by ratee’s performance, our ability to explain a significant amount of variance in MSF ratings using raters’ attri- butes such as hierarchical level, collectivism, and power distance suggests that these effects are pervasive and nontrivial (Prentice & Miller, 1992). Furthermore, the practical significance of these effects is accentuated when MSF is used for administrative pur- poses with high-stakes consequences.Our sampling from one organization in Singapore raises the issue of external generalizability. However, we note that an ad- vantage of sampling from one organization is that systematic organizational factors that could affect rating behaviors, such as feedback environment, are kept constant. Sampling from one cul- ture also mitigates the problem of measurement equivalence, as research has found that performance ratings across cultures are not completely invariant (e.g., Ployhart, Wiechmann, Schmitt, Sacco, & Rogg, 2003). Nonetheless, future research should replicate our design in different organizational settings and different cultures to ascertain the generalizability of results obtained in our present study. Future studies that plan to sample more widely from mul- tiple organizations will need to take into account differences in the social context of the appraisal that could influence results (Levy & Williams, 2004). Practical implications.Our study on rating leniency and halo in MSF ratings has important implications for organizations. MSF research has shown that managers who receive unfavorable feed- back are more likely to improve than those who receive favorable feedback (Reilly, Smither, & Vasilopoulos, 1996; Walker & Smither, 1999). This suggests that when raters provide inflated feedback, they are less likely to “jolt” ratees to improve them- selves. Moreover, when raters provide ratings that vary little across behavioral dimensions, they offer fewer insights to ratees on their strengths and weaknesses. Our study shows specifically that cul- tural profiles characterized by collectivistic and high-power dis- tance values could pose potential challenges to the value of MSF. We suggest two complementary sets of recommendations to ad- dress some of these challenges. Our first set of recommendations focuses on the raters. As the influence of culture on rating behaviors is often implicit, raters can first be made aware of how their cultural values, in conjunction with their organizational role vis-a` -vis the ratee, may shape their rating tendencies. Such cultural self-awareness, an important as- pect of cultural intelligence (Ang et al., 2007), can be coupled with rater training to develop a shared understanding of the nature of feedback that is useful for ratees to improve themselves. For instance, Murphy and Cleveland (1995) suggest that “frame-of- reference” training that is traditionally used to help raters differ- entiate performance levels in their ratees can be applied to help raters identify what rating behaviors are appropriate versus inap- propriate when providing feedback. This helps to reduce the in- fluence of raters’ idiosyncratic effects on rating behaviors. In addition, raters providing consistently high ratings across items could be prompted by the computerized MSF system for narrative justification of these ratings. Holding raters accountable for their performance ratings in this way has been shown to increase accu- racy (Mero & Motowidlo, 1995). Our second set of recommendations focuses on the recipients of MSF. During debriefing sessions, MSF recipients should be en- couraged to consider the possibility of leniency and halo when acting on the feedback they receive. This is especially important in situations in which cultural factors are likely to be salient (e.g., in high-power distance and collectivistic cultures). For instance, re- cipients should be advised to pay attention to the relatively lower scores, as well as small differences between scale scores. In addition, including instrument norms in MSF reports can help recipients compare their scores with organizational benchmarks to identify areas for improvement. 1041 RATING LENIENCY AND HALO IN MSF Conclusion.Involving peers and subordinates in the feedback process is a distinctive hallmark of MSF. Underlying the involve- ment of these nontraditional sources of feedback is the implicit assumption of low power distance and individualistic values. This prompted us to examine whether peers and subordinates with high power distance and collectivistic orientations are more susceptible to rating bias than superiors. Our results show that the joint effects of rater source and cultural value orientations in predicting rating leniency and halo are substantial, thus highlighting the importance of considering cultural assumptions when implementing MSF. Besides contributing new theoretical insights to the MSF literature, our study also highlights the methodological importance of using HLM to control for ratee effects in order to yield more robust results. Practically, our findings underscore the importance of ensuring that organizational members, particularly subordinates and peers with high power distance and collectivistic values, are ready for MSF. References Ang, S., Van Dyne, L., Koh, S. K., Ng, K. Y., Templer, K. J., Tay, C., & Chandrasekar, N. A. (2007). Cultural intelligence: An individual differ- ence with effects on cultural judgment and decision making, cultural adaptation, and task performance.Management and Organization Re- view, 3,335–371. doi:10.1111/j.1740-8784.2007.00082.x Antonakis, J., & Atwater, L. (2002). Leader distance: A review and a proposed theory.Leadership Quarterly, 13,673–704. doi:10.1016/ S1048-9843(02)00155-8 Antonioni, D., & Park, H. (2001). The relationship between rater affect and three sources of 360-degree feedback ratings.Journal of Management, 27,479 – 495. doi:10.1177/014920630102700405 Antonioni, D., & Woehr, D. J. (2001). Improving the quality of multisource rater performance. In D. Bracken, C. Timmreck, & A. Church (Eds.), Handbook of multisource feedback(pp. 114 –129). San Francisco, CA: Jossey-Bass. Atwater, L. E., Wang, M., Smither, J. W., & Fleenor, J. W. (2009). Are cultural characteristics associated with a relationship between self and others’ ratings of leadership?Journal of Applied Psychology, 94,876 – 886. doi:10.1037/a0014561 Bass, B. M. (1960).Leadership, psychology, and organizational behavior. New York, NY: Harper. Bernardin, H. J., Cooke, D. K., & Villanova, P. (2000). Conscientiousness and agreeableness as predictors of rating leniency.Journal of Applied Psychology, 85,232–236. doi:10.1037/0021-9010.85.2.232 Bettenhausen, K. L., & Fedor, D. B. (1997). Peer and upward appraisals: A comparison of their benefits and problems.Group and Organization Management, 22,236 –263. doi:10.1177/1059601197222006 Bliese, P. D. (2002). Multilevel random coefficient modeling in organiza- tion research: Examples using SAS and S-PLUS. In F. Drasgow & N. Schmitt (Eds.),Measuring and analyzing behavior in organizations: Advances in measurement and data analysis(pp. 401– 445). San Fran- cisco, CA: Jossey-Bass. Bond, M. H., Wan, K., Leung, K., & Giacalone, R. A. (1985). How are responses to verbal insult related to cultural collectivism and power distance?Journal of Cross-Cultural Psychology, 16,111–127. doi: 10.1177/0022002185016001009 Brett, J. F., & Atwater, L. E. (2001). 360 ofeedback: Accuracy, reactions, and perceptions of usefulness.Journal of Applied Psychology, 86,930 – 942. doi:10.1037/0021-9010.86.5.930 Bryk, A. S., & Raudenbush, S. W. (1992).Hierarchical linear models: Applications and data analysis methods.Newbury, CA: Sage Publica- tions. Chan, K. Y., & Drasgow, F. (2001). Toward a theory of individualdifferences and leadership: Understanding the motivation to lead.Jour- nal of Applied Psychology, 86,481– 498. doi:10.1037/0021- 9010.86.3.481 Chen, H., Ng, S., & Rao, A. R. (2005). Cultural differences in consumer impatience.Journal of Marketing Research, 42,291–301. doi:10.1509/ jmkr.2005.42.3.291 De Luque, M. F. S., & Sommer, S. M. (2000). The impact of culture on feedback-seeking behavior: An integrated model and propositions. Academy of Management Review, 25,829 – 849. doi:10.2307/259209 de Nisi, A. S., & Mitchell, J. L. (1978). An analysis of peer ratings as predictors and criterion measures and a proposed new application.Acad- emy of Management Review, 3,369 –374. doi:10.2307/257678 Dorfman, P. W., & Howell, J. P. (1988). Dimensions of national culture and effective leadership patterns: Hofstede revisited. In J. L. C. Cheng & R. B. Peterson (Eds.),Advances in international comparative manage- ment(Vol. 3, pp. 127–150). Stamford, CT: JAI Press. Drexler, J. A., Beehr, T. A., & Stetz, T. A. (2001). Peer appraisals: Differentiation of individual performance on group tasks.Human Re- source Management, 40,333–345. doi:10.1002/hrm.1023 Earley, P. C. (1993). East meets West meets Mideast: Further explorations of collectivistic and individualistic work groups.Academy of Manage- ment Journal, 36,319 –348. doi:10.2307/256525 Earley, P. C. (1999). Playing follow the leader: Status-determining traits in relation to collective efficacy across cultures.Organizational Behavior and Human Decision Processes, 80,192–212. doi:10.1006/ obhd.1999.2863 Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue.Psycho- logical Methods, 12,121–138. doi:10.1037/1082-989X.12.2.121 Entrekin, L., & Chung, Y. W. (2001). Attitudes towards different sources of executive appraisal: A comparison of Hong Kong Chinese and Amer- ican managers in Hong Kong.International Journal of Human Resource Management, 12,965–987. Erez, M., & Earley, P. C. (1993).Culture, self-identity, and work.New York, NY: Oxford University Press. Farh, J.-L., Cannella, A. A., Jr., & Bedeian, A. G. (1991). The impact of purpose on rating quality and user acceptance.Group and Organization Management, 16,367–386. doi:10.1177/105960119101600403 Farh, J. L., Hackett, R. D., & Liang, J. (2007). Individual-level cultural values as moderators of perceived organizational support-employee out- come relationships in China: Comparing the effects of power distance and traditionality.Academy of Management Journal, 50,715–729. Fedor, D. B., Bettenhausen, K. L., & Davis, W. (1999). Peer reviews: Employees’ dual roles as raters and recipients.Group and Organization Management, 24,92–120. doi:10.1177/1059601199241006 Fletcher, C., & Perry, E. L. (2001). Performance appraisal and feedback: A consideration of national culture and a review of contemporary research and future trends. In N. Anderson, D. S. Ones, H. K. Sinangil, & C. Viswesvaran (Eds.),Handbook of industrial, work and organizational psychology(Vol. 1, pp. 125–144). Thousand Oaks, CA: Sage. French, J. R. P., Jr., & Raven, B. H. (1959). The bases of social power. In D. Cartwright (Ed.),Studies in social power(pp. 150 –167). Ann Arbor, MI: Institute for Social Research. Gelfand, M. J., Erez, M., & Aycan, Z. (2007). Cross-cultural organizational behavior.Annual Review of Psychology, 58,479 –514. doi:10.1146/ annurev.psych.58.110405.085559 Greguras, G. J., & Robie, C. (1998). A new look at within-source interrater reliability of 360-degree feedback ratings.Journal of Applied Psychol- ogy, 83,960 –968. doi:10.1037/0021-9010.83.6.960 Harris, M. M. (1994). Rater motivation in the performance appraisal context: A theoretical framework.Journal of Management, 20,737–756. doi:10.1016/0149-2063(94)90028-0 Harris, M. M., & Schaubroeck, J. (1988). A meta-analysis of self-boss, 1042 NG, KOH, ANG, KENNEDY, AND CHAN self-peer, and peer-boss ratings.Personnel Psychology, 41,43– 62. doi: 10.1111/j.1744-6570.1988.tb00631.x Harris, M. M., Smith, D. E., & Champagne, D. (1995). A field study of performance appraisal purpose: Research versus administrative-based ratings.Personnel Psychology, 48,151–160. doi:10.1111/j.1744- 6570.1995.tb01751.x Heidemeier, H., & Moser, K. (2009). Self– other agreement in job perfor- mance ratings: A meta-analytic test of a process model.Journal of Applied Psychology, 94,353–370. doi:10.1037/0021-9010.94.2.353 Hofmann, D. A. (1997). An overview of the logic and rationale of hierar- chical linear models.Journal of Management, 23,723–744. doi: 10.1177/014920639702300602 Hofstede, G. (2001).Culture’s consequences.Beverly Hills, CA: Sage. Hogg, M. A., Martin, R., Epitropaki, O., Mankad, A., Svensson, A., & Weeden, K. (2005). Effective leadership in salient groups: Revisiting leader-member exchange theory from the perspective of the social identity theory of leadership.Personality and Social Psychology Bulle- tin, 31,991–1004. doi:10.1177/0146167204273098 Holzbach, R. L. (1978). Rater bias in performance ratings: Superior, self and peer ratings.Journal of Applied Psychology, 63,579 –588. doi: 10.1037/0021-9010.63.5.579 House, R., Hanges, P., Javidan, M., Dorfman, P., & Gupta, V. (2004). Culture, leadership, and organizations: The GLOBE study of 62 soci- eties.Thousand Oaks, CA: Sage. Hox, J. J. (2002).Multilevel analysis: Techniques and applications.Mah- wah, NJ: Lawrence Erlbaum. Ilies, R., Wagner, D. T., & Morgeson, F. (2007). Explaining affective linkages in teams: Individual differences in susceptibility to contagion and individualism-collectivism.Journal of Applied Psychology, 92, 1140 –1148. doi:10.1037/0021-9010.92.4.1140 Jawahar, I. M., & Williams, C. R. (1997). When all the children are above average: The performance appraisal purpose effect.Personnel Psychol- ogy, 50,905–925. doi:10.1111/j.1744-6570.1997.tb01487.x Jöreskog, K. G., & Sörbom, D. (2006).Windows LISREL 8.8.Chicago, IL: Scientific Software. Kim, J. Y., & Nam, S. H. (1998). The concept and dynamics of face: Implications for organizational behavior in Asia.Organization Science, 9,522–534. doi:10.1287/orsc.9.4.522 Kirkman, B. L., Chen, G., Farh, J., & Chen, Z. X. (2009). Individual power distance orientation and follower reactions to transformational leaders: A cross-level, cross-cultural examination.Academy of Management Journal, 52,744 –764. Kirkman, B. L., Lowe, K. B., & Gibson, C. B. (2006). A quarter century ofCulture’s Consequences: A review of empirical research incorporating Hofstede’s cultural values framework.Journal of International Business Studies, 37,285–320. doi:10.1057/palgrave.jibs.8400202 Klimoski, R. J., & London, M. (1974). Role of the rater in performance appraisal.Journal of Applied Psychology, 59,445– 451. doi:10.1037/ h0037332 Kreft, I., & de Leeuw, J. (1998).Introducing multilevel modeling.Thou- sand Oaks, CA: Sage. Kudisch, J. D., Fortunato, V. J., & Smith, A. F. R. (2006). Contextual and individual difference factors predicting individuals’ desire to provide upward feedback.Group and Organization Management, 31,503–529. doi:10.1177/1059601106286888 Lance, C. E. (1994). Test of a latent structure of performance ratings derived from Wherry’s (1952) theory of ratings.Journal of Manage- ment, 20,751–771. Lawler, E. E., III. (1967). The multitrait-multirater approach to measuring managerial job performance.Journal of Applied Psychology, 51,369 – 381. doi:10.1037/h0025095 Lebreton, J. M., Burgess, J. R. D., Kaiser, R. B., Atchley, E. K., & James, L. R. (2003). The restriction of variance hypothesis and interrater reli- ability and agreement: Are ratings from multiple sources really dissim-ilar?Organizational Research Methods, 6,80 –128. doi:10.1177/ 1094428102239427 Leslie, J. B., Gryskiewicz, N. D., & Dalton, M. A. (1998). Understanding cultural influences on 360-degree feedback process. In W. W. Tornow & M. London (Eds.),Maximizing the value of 360-degree feedback: A process for successful individual and organizational development(pp. 196 –216). San Francisco, CA: Jossey-Bass. Leung, K., Bond, M. H., Reimel de Carrasquel, S., Mun˜ oz, C., Herna´ ndez, M., Murakami, F., . . . Singelis, T. M. (2002). Social axioms: The search for universal dimensions of general beliefs about how the world func- tions.Journal of Cross-Cultural Psychology, 33,286 –302. doi:10.1177/ 0022022102033003005 Levy, P. E., & Williams, J. R. (2004). The social context of performance appraisal: A review and framework for the future.Journal of Manage- ment, 30,881–905. doi:10.1016/j.jm.2004.06.005 Li, J., Ngin, P. M., & Teo, A. C. Y. (2007). Culture and leadership in Singapore: Combination of the East and the West. In J. Chhokar, F. C. Brodbeck, & R. J. House (Eds.),Culture and leadership across the world: The GLOBE book of in-depth dtudies of 25 societies(pp. 947– 968). Mahwah, NJ: Lawrence Erlbaum Associates. London, M. (2003).Job feedback: Giving, seeking, and using feedback for performance improvement.Mahwah, NJ: Lawrence Erlbaum. London, M., & Smither, J. W. (1995). Can multisource feedback change percep- tions of goal accomplishment, self-evaluations, and performance-related out- comes? Theory-based applications and direction for research.Personnel Psy- chology, 48,803– 839. doi:10.1111/j.1744-6570.1995.tb01782.x Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation.Psychological Review, 98,224 – 253. doi:10.1037/0033-295X.98.2.224 Mero, N. P., & Motowidlo, S. J. (1995). Effects of rater accountability on the accuracy and the favorability of performance ratings.Journal of Applied Psychology, 80,517–524. doi:10.1037/0021-9010.80.4.517 Morrison, E. W., Chen, Y.-R., & Salgado, S. R. (2004). Cultural differ- ences in newcomer feedback seeking: A comparison of the United States and Hong Kong.Applied Psychology: An International Review, 53, 1–22. doi:10.1111/j.1464-0597.2004.00158.x Mount, M. K. (1984). Psychometric properties of subordinate ratings of managerial performance.Personnel Psychology, 37,687–702. doi: 10.1111/j.1744-6570.1984.tb00533.x Mount, M. K., Judge, T. A., Scullen, S. E., Sytsma, M. R., & Hezlett, S. A. (1998). Trait, rater and level effects in 360-degree performance ratings.Personnel Psychology, 51,557–576. doi:10.1111/j.1744-6570.1998.tb00251.x Mount, M. K., & Scullen, S. E. (2001). Multisource feedback ratings: What do they really measure? In M. London (Ed.),How people evaluate others in organizations(pp. 155–176). Mahwah, NJ: Lawrence Erlbaum. Murphy, K. R., & Balzer, W. K. (1989). Rater errors and rating accuracy. Journal of Applied Psychology, 74,619 – 624. doi:10.1037/0021- 9010.74.4.619 Murphy, K. R., & Cleveland, J. N. (1995).Understanding performance appraisal: Social, organizational, and goal-based perspectives.Thou- sand Oaks, CA: Sage. Murphy, K. R., Cleveland, J. N., Skattebo, A. L., & Kinney, T. B. (2004). Raters who pursue different goals give different ratings.Journal of Applied Psychology, 89,158 –164. doi:10.1037/0021-9010.89.1.158 Ng, K. Y., & Van Dyne, L. (2001). Individualism-collectivism as a boundary condition for effectiveness of minority influence in decision making.Organizational Behavior and Human Decision Processes, 84, 198 –225. doi:10.1006/obhd.2000.2927 Pfeffer, J., & Salancik, G. R. (1975). Determinants of supervisory behav- iors: A role set analysis.Human Relations, 28,139 –154. doi:10.1177/ 001872677502800203 Ployhart, R. E., Wiechmann, D., Schmitt, N., Sacco, J. M., & Rogg, K. (2003). The cross-cultural equivalence of job performance ratings.Hu- man Performance, 16,49 –79. doi:10.1207/S15327043HUP1601_3 1043 RATING LENIENCY AND HALO IN MSF Prentice, D. A., & Miller, D. T. (1992). When small effects are impressive. Psychological Bulletin, 112,160 –164. doi:10.1037/0033- 2909.112.1.160 Raudenbush, S. W., & Bryk, A. S. (2002).Hierarchical linear models: Applications and data analysis methods.Thousand Oaks, CA: Sage. Reilly, R. R., Smither, J. W., & Vasilopoulos, N. L. (1996). A longitudinal study of upward feedback.Personnel Psychology, 49,599 – 612. doi: 10.1111/j.1744-6570.1996.tb01586.x Saal, F. E., Downey, R. G., & Lahey, M. A. (1980). Rating the ratings: Assessing the psychometric quality of rating data.Psychological Bulle- tin, 88,413– 428. doi:10.1037/0033-2909.88.2.413 Schneier, E. C. (1977). Operational utility and psychometric characteristics of behavioral expectations scales: A cognitive reinterpretation.Journal of Applied Psychology, 62,541–548. doi:10.1037/0021-9010.62.5.541 Schwartz, S. M., & Bilsky, W. (1987). Toward a universal psychological structure of human values.Journal of Personality and Social Psychol- ogy, 53,550 –562. doi:10.1037/0022-35184.108.40.2060 Scullen, S. E., Mount, M. K., & Goff, M. (2000). Understanding the latent structure of job performance ratings.Journal of Applied Psychology, 85, 956 –970. doi:10.1037/0021-9010.85.6.956 Shipper, F., Hoffman, R. C., & Rotondo, D. M. (2007). Does the 360 feedback process create actionable knowledge equally across cultures? Academy of Management Learning and Education, 6,33–50. Spence, J. R., & Keeping, L. M. (2010). The impact of non-performance information on ratings of job performance: A policy-capturing approach. Journal of Organizational Behavior, 31,587– 608. doi:10.1002/job.648 Springer, D. (1953). Ratings of candidates for promotion by co-workers and supervisors.Journal of Applied Psychology, 64,124 –131. Stone-Romero, E. F., & Stone, D. L. (2002). Cross-cultural differences in responses to feedback: Implications for individual, group, and organi- zational effectiveness.Research in Personnel and Human Resources Management, 21,275–331. doi:10.1016/S0742-7301(02)21007-5 Triandis, H. C. (1995).Individualism and collectivism.Boulder, CO: Westview Press. Tsui, A. S. (1984). A role set analysis of managerial reputation.Organi- zational Behavior and Human Performance, 36,64 –96. doi:10.1016/ 0030-5073(84)90037-0 Tsui, A. S., & Barry, B. (1986). Interpersonal affect and rating errors. Academy of Management Journal, 29,586 –599. doi:10.2307/256225Tsui, A., & O’Reilly, C. A., III. (1989). Beyond simple demographic effects: The importance of relational demography in superior- subordinate dyads.Academy of Management Journal, 32,402– 423. doi:10.2307/256368 Vance, R. J., Winne, P. S., & Wright, E. S. (1983). A longitudinal examination of rater and ratee effects in performance ratings.Personnel Psychology, 36,609 – 620. doi:10.1111/j.1744-6570.1983.tb02238.x Varela, O. E., & Premeaux, S. F. (2008). Do cross-cultural values affect multisource feedback dynamics? The case of high power distance and collectivism in two Latin American countries.International Journal of Selection and Assessment, 16,134 –142. doi:10.1111/j.1468- 2389.2008.00418.x Walker, A. G., & Smither, J. W. (1999). A five-year study of upward feedback: What managers do with their results matter.Personnel Psy- chology, 52,393– 423. doi:10.1111/j.1744-6570.1999.tb00166.x Westerman, J. W., & Rosse, J. G. (1997). Reducing the threat of rater nonpartici- pation in 360-degree feedback systems: An exploratory examination of ante- cedents to participation in upward ratings.Group and Organization Manage- ment, 22,288 –309. doi:10.1177/1059601197222008 Wherry, R. J., Sr., & Bartlett, C. J. (1982). The control of bias in ratings: A theory of rating.Personnel Psychology, 35,521–551. doi:10.1111/ j.1744-6570.1982.tb02208.x Wohlers, A. J., Hall, M. J., & London, M. (1993). Subordinates rating managers: Organizational and demographic correlates of self- subordinate agreement.Journal of Occupational and Organizational Psychology, 66,263–275. Wong, K. F. E., & Kwong, J. Y. Y. (2007). Effects of rater goals on rating patterns: Evidence from an experimental field study.Journal of Applied Psychology, 92,577–585. doi:10.1037/0021-9010.92.2.577 Yukl, G., & Falbe, C. M. (1991). Importance of different power sources in downward and lateral relations.Journal of Applied Psychology, 76, 416 – 423. doi:10.1037/0021-9010.76.3.416 Zedeck, S., Imparto, N., Krausz, M., & Oleno, T. (1974). Development of behaviorally anchored rating scales as a function of organizational level. Journal of Applied Psychology, 59,249 –252. doi:10.1037/h0036521 Received December 14, 2009 Revision received January 12, 2011 Accepted January 24, 2011 1044 NG, KOH, ANG, KENNEDY, AND CHAN