Abusive Supervisory Reactions to Coworker Relationship Conflict

The Leadership Quarterly 22 (2011) 1010–1023 Contents lists available at ScienceDirect The Leadership Quarterly j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / l e a q u a Abusive supervisory reactions to coworker relationship con? ict Kenneth J. Harris a,? , Paul Harvey b, K. Michele Kacmar c

Indiana University Southeast, School of Business, 4201 Grant Line Road, New Albany, IN 47150, USA Management Department, Whittemore School of Business and Economics, University of New Hampshire, USA Department of Management and Marketing, Culverhouse College of Commerce and Business Administration, 143 Alston Hall, Box 870225, The University of Alabama, Tuscaloosa, Alabama 35487-0225, USA b c a a r t i c l e i n f o a b s t r a c t This study extends research on abusive supervision by exploring how supervisor reports of conflict with their coworkers are related to abusive behaviors and resulting outcomes.

We utilize research on displaced aggression, conflict, and leader–member exchange (LMX) theory to formulate our hypotheses. Results from two samples of 121 and 134 matched supervisor– subordinate dyads support the idea that supervisors experiencing coworker relationship conflict are likely to engage in abusive behaviors directed toward their subordinates and that LMX quality moderates this relationship. Additionally, abusive supervision was associated with decreased work effort and organizational citizenship behaviors (OCB).

We will write a custom essay sample on
Abusive Supervisory Reactions to Coworker Relationship Conflict
or any similar topic only for you
Order now

Research also suggests that these forms of abuse are alarmingly common in modern organizations (Namie & Namie, 2000; Tepper, 2007). The purpose of this study is to develop and test a conceptual model that expands our knowledge of antecedents, moderators, and consequences of abusive supervision. We also build on past research showing that supervisors’ relationship con? icts can “trickle down” to subordinates in the form of abusive behaviors (Aryee, Chen, Sun, & Debrah, 2007). Speci? cally, we test the notion that supervisors who experience relationship con? ct, de? ned as interpersonal “tension, animosity, and annoyance” (Jehn, 1995, p. 258), with their coworkers respond by abusing subordinates. The proposed relationship between supervisor-level coworker relationship con? ict and abusive supervision is rooted in the notion of displaced aggression, which occurs when the reaction to an unpleasant outcome or behavior from one source is redirected to a second source (Miller, Pedersen, Earlywine, & Pollock, 2003; Tedeschi & Norman, 1985).

Consistent with Tepper (2007), we argue that the relatively weak retaliatory power of subordinates, as compared to coworkers, increases the likelihood that relationship con? ict-driven frustration will be vented at subordinates. We qualify this assumption, however, by arguing that supervisors who experience coworker relationship con? ict will not behave abusively toward all of their subordinates. We explore ? Corresponding author. E-mail addresses: [email protected] edu (K. J. Harris), Paul. [email protected] edu (P. Harvey), [email protected] ua. edu (K. M. Kacmar). 1048-9843/$ – see front matter © 2011 Elsevier Inc.

All rights reserved. doi:10. 1016/j. leaqua. 2011. 07. 020 K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 1011 this idea by examining leader–member relationship (LMX) quality as a moderator of the relationship between supervisors’ levels of coworker relationship con? ict and abusive supervision. Finally, we advance the extant research by investigating two supervisorrated employee outcomes (work effort, and organizational citizenship behaviors (OCB)), one of which has not previously been examined in the context of abusive supervision.

These outcomes were chosen as they extend the literature and we were interested in actual behaviors directed toward the job/task (work effort and task-focused OCB). We examine these relationships, shown in Fig. 1, in two separate samples of matched supervisor–subordinate dyads. Thus, the current study makes several contributions to the literature. First, we examine the in? uence of con? ict between supervisors on subordinate reports of abusive supervision. Examining this relationship is important because although coworker relationship con? cts have negative outcomes, studies have yet to investigate how supervisors experiencing these con? icts treat their subordinates. Second, we investigate LMX quality as a relationship variable that changes how supervisor reports of coworker relationship con? ict and abusive supervision are related. Third, we extend the nomological network of abusive supervision by examining the outcomes of work effort and OCB. Finally, we investigate the potential for abusive supervision to mediate the associations between supervisor reports of coworker relationship con? ict and distal consequences.

Thus, this study takes a ? rst step toward explaining how (through the intermediary mechanism of abusive supervision) supervisors’ experiences of coworker relationship con? ict ultimately impact important job outcomes. 2. Abuse as a displaced response to coworker relationship con? ict Abusive supervision is de? ned as prolonged hostile treatment toward subordinates, excluding physical violence (Tepper, 2000). Research indicates that supervisors who perceive that they are victims of interactional or procedural injustice, both of which may be associated with coworker relationship con? ct (Fox, Spector, & Miles, 2001), are relatively more likely than others to abuse their subordinates (Aryee, Chen, Sun, & Debrah, 2007; Tepper, Duffy, Henle, & Lambert, 2006). Tepper, Duffy, Henle, and Lambert (2006) argued that this trickle-down effect, in which supervisors’ frustrations are channeled into abusive behaviors targeted at subordinates, may occur because subordinates are a relatively safe target toward which supervisors can vent their frustrations (Tepper, Duffy, Henle, & Lambert, 2006).

This argument suggests abusive supervision may be a response to frustrating workplace events such as coworker relationship con? ict. Coworker con? ict has been linked to undesirable emotional states and can negatively impact interpersonal relationships (e. g. , Bergmann & Volkema, 1994; Deutch, 1969). Emotion research suggests that the anger and frustration associated with interpersonal con? ict can promote verbal (e. g. , shouting) and behavioral (e. g. , theft, sabotage, violence) aggression toward those who stimulate the con? ct (e. g. , Ambrose, Seabright, & Schminke, 2002; Dollard, Doob, Miller, Mowrer, & Sears, 1939; Fox & Spector, 1999; Greenberg, 1990; Spector, 1975). Many of these behaviors, with the exception of physical violence, would fall under Tepper’s (2000) de? nition of abusive supervision if aimed at subordinates. Drawing on ? ndings from research on displaced aggression we argue that, due to the relative power of supervisors’ coworkers, these relationship con? ict-driven behaviors might, in fact, be targeted at subordinates.

Displaced aggression occurs when individuals experience mistreatment from one party and respond by mistreating a second party (Hoobler & Brass, 2006, Miller, Pedersen, Earlywine & Pollock, 2003, Twenge & Campbell, 2003). Several triggers of displaced aggression have been identi? ed, including social rejection (Twenge & Campbell, 2003) and negative feedback (Bushman & Baumeister, 1998). Hoobler and Brass (2006) also showed that abusive supervision at work can promote displaced aggression toward family members at home. We examine abusive supervision as a form of displaced aggression ather than a predictor, although both conceptualizations are logical. Displaced aggression is often triggered by unpleasant workplace events (e. g. , Miller, Pedersen, Earlywine & Pollock, 2003) and abusive supervision ? ts this criteria. We argue that abusive supervision also can ? t the criteria of displaced aggression if it is triggered by events beyond the control of subordinates, such as the abusers’ coworker relationship con? ict. Thus, abusive supervision can likely be both a cause of displaced aggression and a type of displaced aggression.

Note: Dashed lines represent hypothesized mediated linkages Supervisor-Rated Subordinate Work Effort Supervisor-Rated Coworker Conflict Abusive Supervision Supervisor-Rated Subordinate TaskFocused OCB Moderator: Leader-Member Exchange Fig. 1. Hypothesized model. 1012 K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 As Tepper, Duffy, Henle and Lambert (2006) argued, abusive supervision can be used as a means for venting frustration because subordinates have relatively low levels of retaliatory power and, therefore, serve as a lower-risk target for venting behaviors than do employees in positions of greater hierarchical power.

Victim precipitation research also supports this logic, indicating that displaced aggression is often targeted at those who are unable or unwilling to defend themselves, as is likely the case among subordinates who can be disciplined and terminated by their supervisors (e. g. , Aquino, 2000). This desire to vent frustration at individuals who are unassociated with the initial con? ict, similar to the anecdotal notion of “kicking the dog” after a bad day at work, can be understood in the context of displaced aggression. Coworker relationship con? ct is a potent source of stress and frustration (Thomas, 1976, 1992) and, because these are unpleasant, individuals are motivated to engage in coping behaviors that will diminish their presence (Kemper, 1966). These emotion-driven coping behaviors can often take the form of hostile behaviors such as sabotage (Ambrose, Seabright & Schminke, 2002) and verbal assaults (Douglas & Martinko, 2001). Thus, coworker relationship con? ict may trigger aggressive behaviors (e. g. , yelling at others) that serve a coping function. Thomas (1976) noted, however, that the relative power of the parties to a con? ct in? uences the manner in which both parties will respond. When legitimate power levels are equal, as in the case of coworkers, hostile responses are likely to be met with retaliation although it is possible that the target of retaliation will respond with additional hostility, creating an escalating cycle of con? ict. Subordinates, on the other hand, are often reluctant to respond in kind to hostile supervisor behaviors for fear of losing their jobs. The fact that subordinates are not the cause of the supervisor’s frustration, that is, the frustration is caused by supervisors’ con? ct with their coworkers, may have little impact on the behavioral response if the behavior is largely motivated by emotion as opposed to logic. That is, the desire to vent anger over coworker relationship con? ict using a safe target may override concerns that subordinates are not the logical targets for retaliation, given that they are not the cause of the con? ict. Based on these arguments, we predict: Hypothesis 1. Supervisors’ reports of coworker relationship con? ict are positively associated with abusive supervisory behaviors, as rated by subordinates. 2. 1. The moderating in? ence of LMX relationship quality Thomas (1976, 1992) argued that a conceptualization process occurs between the con? ict experience and the behavioral outcome in which information is processed and behavioral options are evaluated. Although this cognitive process is likely to incorporate a wide range of information, we argue that an evaluation of relationships with subordinates is particularly relevant when behaviors toward these individuals are concerned. LMX theory suggests that the quality of leader–member relationships varies from high to low (Dienesch & Liden, 1986; Graen & Uhl-Bien, 1995).

Subordinates in high quality exchanges are seen more favorably and receive advantages from their supervisors that their low quality LMX counterparts do not (e. g. , Liden, Sparrowe, & Wayne, 1997). As such, members in high quality exchanges receive preferential treatment from supervisors who are motivated to maintain these productive relationships. We expect that supervisors who experience high levels of coworker relationship con? ict may become abusive toward subordinates, but will be selective in choosing which subordinates to target. Abusive supervisory behaviors generally have a negative effect on ictims’ levels of motivation and attitudes toward their jobs (e. g. , Duffy, Ganster & Pagon, 2002; Schat, Desmarais, & Kelloway, 2006). Although it can be argued that effective managers would not want to risk these consequences with any employees, LMX theory would suggest that supervisors are especially motivated to maintain effective relationships with their high quality LMX subordinates. We argue, therefore, that supervisors who are frustrated by coworker relationship con? ict and who choose to react in an abusive manner will generally choose low quality LMX subordinates as their targets.

Put differently, we expect that when con? ict-driven abuse occurs, members in low quality exchanges will experience it more strongly and frequently than members in high quality exchanges. Justice and victim precipitation theories provide additional support for this argument (e. g. , Aquino, 2000; Bies & Moag, 1986). From a justice perspective, instead of perceiving members of low quality LMX relationships as less risky targets for abuse, it can also be argued that supervisors ? nd it easier to justify abuse toward these employees. Members of low quality exchanges are often characterized by relatively low performance levels (e. . , Deluga & Perry, 1994; Liden, Wayne, & Stilwell, 1993), and it might be argued that supervisors who use abusive behaviors to cope with relationship con? ict-driven frustration will feel most justi? ed in focusing on these employees. That is, supervisors might rationalize the abuse by convincing themselves that relatively lowperforming subordinates in low quality LMX relationships deserve the abusive behavior. Victim precipitation research also suggests that several characteristics common among low quality LMX subordinates make them likely targets of abuse.

Although provocative and threatening behaviors have been linked to retaliatory aggression (e. g. , Aquino & Byron, 2002; Tepper, 2007), more salient to our focus on leader–member relationships is the precipitation research indicating that abusive individuals often target those who are seen as weak or defenseless. Individuals who are hesitant to defend themselves or view themselves or their situations negatively appear to draw the attention of aggressive individuals (Aquino, 2000; Olweus, 1978; Rahim, 1983; Tepper, 2007).

As discussed above, the hierarchical nature of their relationship likely promotes the former tendency among subordinates, making them relatively safe targets for abuse. Members in low quality exchanges, in particular, might be unwilling to further jeopardize their relationship with their supervisors by retaliating against abuse and might also internalize their undesirable status, promoting the negative perceptions of their workplace competence and situation (e. g. , Ferris, Brown, & Heller, 2009) that can provoke victimization.

Similar to our arguments concerning displaced abuse of subordinates, victim precipitation research suggests that these aggressors might wish to engage in abusive behavior as a means to K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 1013 preserve their social standing and bolster perceptions of their control over a situation (e. g. , Baumeister, Smart, & Boden, 1996; Felson, 1978). As such, this line of research reinforces the notion that subordinates might be targeted for displaced abuse and suggests that low quality LMX subordinates are especially likely to be viewed as vulnerable, and therefore relatively safe, targets.

Based on these arguments, we predict: Hypothesis 2. The relationship between supervisor-reported coworker relationship con? ict and member-reported abusive supervision is moderated by LMX, such that the positive relationship is stronger when LMX relationship quality is lower. 2. 2. Outcomes of abusive supervision The outcome portion of our conceptual model, shown in Fig. 1, examines the effects of abusive supervisory responses to coworker relationship con? ict on work effort and OCB. While we do not posit that abusive supervision is the only factor mediating the relationships between supervisors’ coworker relationship con? ct and these outcomes, we argue that abuse can serve as an explanatory mechanism and explain a relevant amount of variance in each consequence. Abusive supervision is a negative workplace event that, like con? ict, can have negative attitudinal and behavioral consequences (Tepper, 2007; Tepper, Henle, Lambert, Giacalone, & Duffy, 2008; Tepper, Moss, Lockhart, & Carr, 2007). It has been argued that these outcomes are caused by the stress and emotional strain associated with abuse from individuals in a position of power (e. g. Duffy, Ganster & Pagon, 2002; Harvey, Stoner, Hochwarter & Kacmar, 2007; Tepper, 2000). Further, Duffy, Ganster and Pagon (2002) found evidence suggesting that abuse promotes diminished self-ef? cacy. As we discuss in the following sections, each of these consequences of abusive supervision can be logically linked to the outcomes depicted in Fig. 1. 2. 2. 1. Work effort Because abusive supervision can diminish victims’ con? dence in their abilities (Duffy, Ganster & Pagon, 2002), it follows that motivation to exert high levels of effort at work will likely decrease in response to abuse.

Abusive supervisors, who by de? nition are consistent in their abuse (Tepper, 2000), might eventually wear employees down with a steady onslaught of aggressive behavior (e. g. , yelling, criticizing), reducing their con? dence and motivation. Similarly, it may be that over time abusive supervision promotes emotional exhaustion (Harvey, Stoner, Hochwarter & Kacmar, 2007; Tepper, 2000), a condition characterized by diminished emotional and physical coping abilities and closely associated with job burnout (Brewer & Shapard, 2004; Cropanzano, Rupp, & Byrne, 2003).

Harvey, Stoner, Hochwarter and Kacmar (2007) argued that this relationship was likely due to the persistent assault on employees’ feelings and ef? cacy perceptions (Savicki & Cooley, 1983) associated with abusive supervision. When emotional exhaustion occurs, individuals demonstrate diminished motivation and a reduced ability to handle stressful work events, promoting a reduction in work effort (Brewer & Shapard, 2004; Kahill, 1988; Leiter & Maslach, 1988).

Using a different lens to view the abuse–work effort association, employees might also view abusive supervision as a form of psychological contract breach, as subordinates generally do not expect to be abused by those given the authority to supervise them (Tepper, 2000). When employees perceive that a breach has taken place, they often feel less compelled to ful? ll their obligation to exert high levels of work effort (Harris, Kacmar & Zivnuska, 2007). 2. 2. 2. Citizenship behaviors The ? nal outcome depicted in Fig. 1 concerns the negative in? ence of coworker relationship con? ict-driven abuse and subordinates’ propensity to engage in OCB. This predicted relationship is based on research indicating that abusive supervision is associated with factors, including decreased organizational commitment, poor work-related attitudes, and injustice perceptions (Aryee, Chen, Sun & Debrah, 2007; Duffy, Ganster & Pagon, 2002; Schat, Desmarais, & Kelloway, 2006; Zellars, Tepper & Duffy, 2002), that can inhibit citizenship behaviors (Ambrose, Seabright & Schminke, 2002; Zellars, Tepper & Duffy, 2002).

Victims of abusive supervision often feel that they have been treated unjustly (Tepper, 2000), a perception that is associated with reduced levels of OCB (Moorman, 1991). As Judge, Scott, and Ilies (2006) argued, unjust treatment is likely to qualify as a negative affective event and can therefore provoke a retaliatory behavioral response. One such response could logically be the withholding of citizenship behaviors, which are not a requirement of the job and could run counter to the goal of retaliation by making the supervisor’s job easier (e. g. , Zellars, Tepper & Duffy, 2002).

In support of this reasoning, additional research indicates that abusive supervision motivates retaliatory behaviors such as workplace deviance and aggression that run contrary to the notion of citizenship behavior (Dupre, Inness, Connelly, Barling, & Hoption, 2006; Schaubhut, Adams, & Jex, 2004). Based on these arguments, we predict: Hypothesis 3. Abusive supervision is negatively related to supervisor reports of subordinate work effort and organizational citizenship behaviors. 2. 3. The mediating role of abusive supervision We have argued that relationship con? ct between supervisors and their coworkers is associated with abusive supervisory behaviors, and that such behaviors have negative implications for victims’ levels of work effort and OCB. Implicit in this line of reasoning is the notion that coworker relationship con? ict at the supervisor level is ultimately associated with decreased levels of 1014 K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 effort and OCB at the subordinate level, and that abusive supervision acts a mediator between these variables. More speci? ally, the negative effects of supervisors’ relationship con? ict with their coworkers are predicted to manifest themselves in the form of abusive behaviors that negatively affect employees’ attitudes and behaviors, promoting negative subordinate outcomes. Thus, while a relationship between a supervisor’s level of coworker relationship con? ict and subordinates’ levels of effort and OCB may seem somewhat abstract, we suggest that coworker relationship con? ict-driven abusive supervision provides an intermediary link between these variables.

Based on these arguments, we predict: Hypothesis 4. Abusive supervision mediates the negative relationships between supervisor-rated coworker relationship con? ict and work effort and organizational citizenship behaviors. 3. Method 3. 1. Samples and procedures The samples utilized in this study were from two different divisions of a state government. The division in Sample 1 was responsible for handling disease related issues (e. g. , STDs, immunizations, tuberculosis), whereas the division in Sample 2 handled environmental health related issues (e. g. , radiation, clean water).

To begin the data collection efforts, the director of each division sent an email to all employees in their branch. The email informed the potential respondents of the study’s purpose, that participation was voluntary, and that the results would be con? dential. After this email, the researchers sent a personalized message again explaining the goal of the survey, the con? dentiality of responses, and a web link to the survey. Respondents were asked to complete the survey during the next month. Respondents were required to provide their supervisor’s name to match supervisor–subordinate responses.

At the same time, supervisors were asked to provide ratings on each of their direct reports. In Sample 1, eliminating responses with missing data or those that were unable to be matched (i. e. , we received a subordinate response, but not a matching supervisor response) resulted in a sample size of 121 (58% response rate). Subordinates were 68% female, the average age was 41. 68 years, the average job tenure was 3. 38 years, and their average organizational tenure was 5. 22 years. In total, 28 supervisors provided ratings, resulting in an average of 4. 32 ratings per supervisor.

For the supervisors, the demographic breakdown was 57% female, the average age was 47. 91 years, the average job tenure was 4. 79 years, and their average organizational tenure was 7. 73 years. After the elimination of unusable responses in Sample 2, our usable sample size was 134 (64% response rate). Participants in Sample 2 were 60% male, had an average age of 46. 04 years, average job tenure of 7. 04 years, and average organizational tenure of 11. 51 years. Forty-four supervisors provided ratings, which resulted in an average of 3. 05 ratings per supervisor.

The demographic breakdown for the supervisors was 75% male, an average age of 49. 29 years, average job tenure of 9. 64 years, and average organizational tenure of 16. 26 years. 3. 2. Measures Unless otherwise noted, a 5-point Likert scale (anchors: “strongly disagree” (1) to “strongly agree” (5)) was used for all survey items. Scales were coded with high values representing high levels of the constructs. 3. 3. Subordinate measures 3. 3. 1. Abusive supervision In both samples abusive supervision was measured with six items from Tepper’s (2000) measure.

We were unable to use the full 15-item measure due to management concerns about the survey’s overall length. Thus, we had experts in the area look at the content of each of the items, and we chose 6 items that best captured the full range of abusive supervisory behaviors. The items we chose were “My supervisor makes negative comments about me to others,” “My supervisor gives me the silent treatment,” “My supervisor expresses anger at me when he/she is mad for another reason,” “My supervisor is rude to me,” “My supervisor breaks promises he/she makes,” and “My supervisor puts me down in front of others. In an effort to establish the validity of our shortened scale, we compared our reduced scale to the full measure using the data from the Tepper (2000) article. 1 We found that the full 15-item scale was correlated with our 6-item scale at . 96. The Cronbach alpha for the scale was . 90 for Sample 1 and . 92 for Sample 2. 3. 3. 2. Leader–member exchange We used Liden and Maslyn’s (1998) 12-item leader–member exchange multidimensional scale to measure exchange quality in both samples. A sample item included “My supervisor would defend me to others in the organization if I made an honest mistake. The Cronbach alpha for the scale was . 94 for Sample 1 and . 92 for Sample 2. 1 We thank Ben Tepper for allowing us to use his original data for this correlation. K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 1015 3. 4. Supervisor measures 3. 4. 1. Coworker relationship con? ict In both samples supervisors rated their relationship con? icts with their coworkers using the 4-item Jehn (1995) scale. A sample item included “Is there tension among your coworkers? ” These questions were included in a section of the survey here the supervisors were answering questions about their attitudes, behaviors, and relationships with their coworkers. This section was separate from the section where supervisors commented on their subordinates, thus making it clear that these relationship con? ict questions were focused on coworkers at their level in the organization (e. g. , managers’ relationship con? icts with other managers). The response scale for this construct was “Not at all (1)” to “To a very great extent (5)”. The Cronbach alpha for the scale was . 95 for Sample 1 and . 94 for Sample 2. 3. 4. 2.

Work effort In both samples supervisors rated subordinates’ work effort using Brown and Leigh’s (1996) 5-item scale. A sample item was “When there’s a job to be done, this subordinate devotes all his/her energy to getting it done. ” The Cronbach alpha for the scale was . 93 for Sample 1 and . 94 for Sample 2. 3. 4. 3. Organizational citizenship behaviors Supervisors responded to Settoon and Mossholder’s (2002) 6-item scale to measure subordinate task-focused OCB in both samples. A sample item was “This subordinate assists coworkers with heavy work loads even though it is not part of the job. The Cronbach alpha for the scale was . 84 for Sample 1 and . 81 for Sample 2. 3. 5. Control variables We controlled for four variables, all measured from the subordinate, in an effort to minimize potentially spurious relationships. The variables we controlled for were age (measured in years), job tenure (measured in months), organizational tenure (measured in months), and supervisor–subordinate relationship tenure (measured in months). 3. 6. Analytical approach In both samples in this study, supervisors’ coworker relationship con? ict responses were used as predictors of subordinate outcomes (i. . , cross-level main effect). Thus, a single supervisor coworker relationship con? ict rating was used as the predictor variable for multiple subordinates. As a result, for these variables there was no within-supervisor variance and all of the variance was between supervisors (i. e. , ICCs were 1. 00). Additionally, supervisors provided ratings on certain scales (e. g. , work effort and OCB) for multiple subordinates, thus resulting in a supervisor effect (e. g. , ICC1s for OCB of . 11 in sample 1 and . 13 and sample 2, and ICC2s of . 48 in sample 1 and . 51 in sample 2).

To account for the supervisor-level effect in our data, hierarchical linear modeling (HLM: Raudenbush, Bryk, Cheong, & Congdon, 2004) with grand-mean centering was used to carry out our analyses. In the HLM analyses involving supervisor-rated coworker relationship con? ict, this variable was included as a Level 2 variable (Raudenbush, Bryk, Cheong & Congdon, 2004). To test Hypotheses 1–2, there were four steps. In the ? rst step, we entered the four control variables. In the second step we entered the Level 2 variable of supervisor-rated coworker relationship con? ict, and it was here that we tested Hypothesis 1.

In the third step, we entered the Level 1 moderator variable, LMX. In the fourth step, we entered the cross-level interaction term formed between supervisor-rated coworker relationship con? ict and LMX. It was in this step that we tested Hypothesis 2. To test the abusive supervision-outcome and mediation hypotheses (3 and 4), we conducted Baron and Kenny’s (1986) threestep procedure. The HLM equations are available from the ? rst author request. 4. Results The means, standard deviations, and correlation matrix for the variables in this study are provided in Table 1 for Sample 1 and Table 2 for Sample 2.

In both samples abusive supervision was signi? cantly correlated with supervisor reports of coworker relationship con? ict, as well as our dependent variables. Given that a few of the correlations between our focal variables were high, we elected to run a series of con? rmatory factor analyses (CFA) on the scales used in our study to ensure that they were independent and that the items produced the expected factor structures. These analyses were run on both samples separately. To conduct our CFAs, we used LISREL 8. 80, a covariance matrix as input, and a maximum-likelihood estimation.

We elected to conduct our CFA analyses using composite indicators rather than items due to the large number of items and our moderate sample sizes. To create our composite indicators, we assigned items based on factor loadings from an exploratory factor analysis (Bagozzi & Heatherton, 1994; Eddleston, Viega, & Powell, 2006). Speci? cally, for our four-item scales we combined the two items with the highest and lowest factor loadings to the ? rst indicator and the remaining two items to the second indicator. For the ? ve-item scales we created the ? st indicator as described above and included the remaining three items on the second indicator. For our six-item scale we paired the highest and lowest loading item to create the ? rst indicator and then repeated this process for the remaining two indicators. Finally, for the LMX scale we used the four subscales (loyalty, contribution, professional respect, and affect) as composite indicators. Our approach resulted in 15 indicators for our 6 scales. 1016 K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 Table 1 Means, standard deviations, and intercorrelations among study variables in Sample 1.

Variable 1. Abusive supervision 2. Sup. coworker con? ict 3. Leader–member exchange (LMX) 4. Work effort 5. OCB 6. LMX affect 7. LMX contribution 8. LMX loyalty 9. LMX professional respect 10. Age 11. Job tenure 12. Organizational tenure 13. Relationship tenure Mean 1. 31 3. 03 3. 92 4. 03 3. 87 3. 86 4. 10 3. 69 4. 03 41. 68 3. 38 5. 22 1. 99 SD . 57 1. 02 . 77 . 79 . 72 . 97 . 68 . 84 1. 09 11. 1 3. 88 5. 23 2. 02 1 . 77 . 21? ? . 67?? ? . 27?? ? . 29?? .60?? .36?? .69?? .62?? .10 . 10 . 05 . 25?? 2 . 95 ? .11 ? .20? ? . 18? ? . 05 . 04 . 19? ? . 14 . 01 . 23? .01 . 17 3 4 5 6 7 8 9 10 11 12 .76 . 3?? .35?? .91?? .77?? .83?? .90?? ? . 00 . 05 . 08 ? .00 .86 . 40?? .28?? .22? .35?? .28?? .03 ? .00 . 10 . 00 .65 . 27?? .22? .33?? .35?? .01 ? .03 . 05 . 12 .92 . 62?? .68?? .79?? ? . 02 . 11 . 11 . 04 .75 . 56?? .58?? .11 . 05 . 11 . 04 .74 . 64?? ? . 04 ? .01 . 05 ? .11 .94 ? .03 . 02 . 01 . 02 – . 35?? .39?? .26?? – . 69?? .48?? – . 49?? Note: Values in italics on the diagonal are the square root of the average variance explained which must be larger than all zero-order correlations in the row and column in which they appear to demonstrate discriminant validity (Fornell & Larcker, 1981).

N = 121. ? p b . 05. ?? p b . 01. We began by estimating a six-factor solution, with each factor representing a scale in our study. Fit indices, shown in Table 3, indicate that the six-factor model ? t the data. To verify that the six-factor structure was the best representation of our data, we estimated three alternative models and compared them to our baseline model via chi-square difference tests. The alternative models estimated included two ? ve-factor models and a unidimensional model. The alternative models were created by combining scales that had strong correlations to form a larger factor.

The ? rst alternative model combined abusive supervision and LMX into one factor while the second combined OCB and work effort. A description of each alternative model and the CFA results are offered in Table 3. As shown in Table 3, the chi-square difference test results support the six-factor structure as originally designed. To further explore the discriminant validity of our scales we followed the procedure outlined by Fornell and Larcker (1981) and calculated the square root of the average variance explained for each of the scales in our study.

This value, which we present on the diagonal in Tables 1 and 2, represents the variance accounted for by the items that compose the scale. To demonstrate discriminant validity, this value must exceed the corresponding latent variable correlations in the same row and column. If this condition is met, then we have evidence that the variance shared between any two constructs is less than the average variance explained by the items that compose the scale (i. e. , discriminant validity). As shown in Tables 1 and 2, this condition is met for all of the scales used in our study.

The HLM results predicting abusive supervision are shown in Tables 4 (for Sample 1) and 5 (for Sample 2) and the HLM results investigating abusive supervision as a mediator and/or predictor are provided in Tables 6 and 7. First describing our interaction results in Table 4, step 1 reveals that relationship tenure (? = . 08, p b . 05) was the only control variable signi? cantly associated with abusive supervision. Step 2 shows that supervisor reports of coworker relationship con? ict are positively and signi? cantly related to abusive supervision (? = . 09, p b . 05).

This result provides support for Hypothesis 1 in Sample 1. Step 3 in this analysis shows that LMX was negatively associated with abusive supervision (? = ?. 48, p b . 01). Finally, step 4 shows that the interaction term between supervisor reports of coworker relationship con? ict and LMX was negatively and signi? cantly related to abusive Table 2 Means, standard deviations, and intercorrelations among study variables in Sample 2. Variable 1. Abusive supervision 2. Sup. coworker con? ict 3. LMX12 (overall) 4. Work effort 5. OCB 6. LMX affect 7. LMX contribution 8. LMX loyalty 9.

LMX professional respect 10. Age 11. Job tenure 12. Organizational tenure 13. Relationship tenure Mean 1. 32 2. 42 4. 04 4. 31 4. 31 4. 04 4. 15 3. 78 4. 19 45. 86 6. 55 11. 16 6. 08 SD . 58 . 76 . 60 . 73 . 67 . 78 . 56 . 78 . 95 6. 89 2. 66 4. 37 2. 12 1 . 92 . 15? ? . 55?? ? . 26?? ? . 21? ? . 53?? .05 ? .52?? ? . 57?? .04 . 02 . 01 ? .01 2 . 94 ? .04 ? .03 ? .19? ? . 03 ? .06 ? .02 ? .02 ? .15 ? .09 ? .07 . 00 3 4 5 6 7 8 9 10 11 12 .92 . 09 . 05 . 84?? .53?? .83?? .86?? ? . 07 . 08 . 05 . 07 .87 . 72?? ? . 01 ? .03 . 18? .11 ? .03 ? .00 . 03 ? .02 .85 . 01 ? .13 . 09 . 13 ? .13 . 1 ? .05 . 07 .88 . 28?? .56?? .69?? ? . 10 . 05 ? .03 . 00 .71 . 38?? .22? .08 . 16* . 18? .15 .84 . 59?? ? . 08 . 03 . 03 . 01 .95 ? .06 . 04 . 01 . 08 – . 14 . 23?? .18? – . 61?? .27?? – . 26?? Note: Values in italics on the diagonal are the square root of the average variance explained which must be larger than all zero-order correlations in the row and column in which they appear to demonstrate discriminant validity (Fornell & Larcker, 1981). N = 134. ? p b . 05. ?? p b . 01. K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 Table 3 Alternative model test results.

Model Sample 1 (N = 121) Baseline 6-factor model 5-factor combining abuse and LMX 5-factor combining work effort and OCB 1-factor Sample 2 (N = 134) Baseline 6-factor model 5-factor combining abuse and LMX 5-factor combining work effort and OCB 1-factor X2 102 196 127 706 df 75 80 80 90 X2diff dfdiff CFI . 98 . 95 . 97 . 59 NFI . 95 . 91 . 94 . 57 1017 RMSEA . 048 . 093 . 059 . 200 94??? 25??? 604??? 5 5 15 112 276 224 1177 75 80 80 90 164??? 112??? 1065??? 5 5 15 .98 . 93 . 93 . 47 .94 . 89 . 89 . 46 .056 . 125 . 107 . 280 Note: Abuse = abusive supervision, LMX = leader–member exchange, OCB = organizational citizenship behaviors. ?? p b . 001. supervision (? = ?. 12, p b . 01). Overall, the results in Table 5 (Sample 2) are similar. In step 1 none of the control variables were signi? cantly associated with the outcome, but in step 2, supervisor reports of coworker relationship con? ict were positively and signi? cantly related to abusive supervision (? = . 11, p b . 05), again supporting Hypothesis 1. Step 3 in Table 5 shows that LMX was negatively associated with abusive supervision (? = ?. 54, p b . 01). In the ? nal step, the supervisor reported coworker relationship con? ict ? LMX interaction term was negatively and signi? antly related to abusive supervision (? = ? .29, p b . 05). To determine support for our interaction hypothesis, we graphed the two signi? cant moderating effects. We did so by plotting two slopes, one at one standard deviation below and one at one standard deviation above the mean (Stone & Hollenbeck, 1989). Figs. 2 (for Sample 1) and 3 (for Sample 2) illustrate the signi? cant interactions and show that the positive relationships between supervisor reports of coworker relationship con? ict and abusive supervision were stronger when LMX relationship quality was lower.

Additionally, we calculated simple slopes for each of our interactions. In sample 1, we found that the slope of the low LMX line was signi? cant (t = 2. 00, p b . 05), whereas the slope of the high LMX line was not signi? cant. Similar to sample 1, in sample 2 the slope of the low LMX was signi? cant (t = 2. 11, p b . 05), but the slope of the high LMX line was not signi? cant. In total, these results provide support for Hypothesis 2 in both samples. Tables 6 and 7 provide the results of our mediation analyses. First discussing the results from Sample 1 shown in Table 6, supervisor-reported coworker relationship con? ct was signi? cantly related to abusive supervision (? = . 09, p b . 05) (which ful? lls one of Baron and Kenny’s (1986) mediation requirements) and to OCB (? = ? .08, p b . 10) and work effort (? = ?. 14, p b . 05) (ful? lling another mediation requirement). Steps 2c and 3c show that when both supervisor reports of coworker relationship con? ict and abusive supervision are entered into the equation, the coworker relationship con? ict variable is no longer signi? cant. In particular, the gammas for supervisor-reported coworker relationship con? ict predicting OCB dropped from ?. 08 to ?. 6 and for predicting work effort dropped from ?. 14 to ? .11. However, abusive supervision is signi? cantly and positively related to OCB (? = ?. 37, p b . 01) and signi? cantly and negatively related to work effort (? = ?. 27, p b . 05). Thus, Hypothesis 3 is supported in Sample 1. In terms of the mediation results, the results from Baron and Kenny’s (1986) three-step procedure show that abusive supervision fully mediated the relationship between supervisor-rated coworker relationship con? ict and OCB and partially mediated the relationship with work effort. Thus, Hypothesis 4 was supported in Sample 1.

Table 4 Hierarchical linear modeling results predicting abusive supervision in Sample 1. Step 1 Control variables: Age Job tenure Organizational tenure Relationship tenure Independent variable Sup-rated coworker con? ict (A) Moderator: LMX (B) Interaction term: A? B ? R2 . 00 . 00 ? .01 . 08? Step 2 . 00 ? .00 ? .01 . 07 . 09? Step 3 . 00 . 00 ? .00 . 07? .05? ? . 48?? Step 4 . 00 ? .00 ? .00 . 06? .05 ? .46?? ? . 12?? .02 .02 .02 .45 Note: Sup-rated coworker con? ict = supervisor-rated coworker relationship con? ict, LMX = leader–member exchange. N = 121. ? p b . 05. ?? p b . 01. 018 K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 Table 5 Hierarchical linear modeling results predicting abusive supervision in Sample 2. Step 1 Control variables: Age Job tenure Organizational tenure Relationship tenure Independent variable Sup-rated coworker con? ict (A) Moderator: LMX (B) Interaction term: A? B ? R2 . 00 . 00 ? .00 ? .00 Step 2 . 01 .00 ? .00 ? .00 . 11? Step 3 ? .00 . 00 ? .00 . 00 . 09? ? . 54?? Step 4 . 00 . 00 ? .00 . 00 . 13? ? . 55?? ? . 29?? .05 .01 .01 .35 Note: Sup-rated coworker con? ict = supervisor-rated coworker relationship con? ct, LMX = leader–member exchange. N = 134. ? p b . 05. ?? p b . 01. Next we turn to the HLM results presented for Sample 2 in Table 7. This table shows that supervisor-reported coworker relationship con? ict was signi? cantly related to abusive supervision in step 1b (which passes Baron and Kenny’s (1986) ? rst step) and OCB (in step 2b), but not work effort (in step 3b). These results pass the ? rst two steps for mediation for OCB, but not work effort. Table 7 also reveals that abusive supervision is negatively and signi? cantly related to OCB (? = ?. 26, p b . 05) in step 2c, and signi? antly and negatively related to work effort (? = ?. 39, p b . 01) in step 3c. Thus, Hypothesis 3, which was supported in Sample 1, is also supported in Sample 2. Step 2c shows that when both supervisor reports of coworker relationship con? ict and abusive supervision are entered into the equation, the coworker relationship con? ict variable is no longer a signi? cant predictor of OCB. In terms of the mediation results, the results from Baron and Kenny’s (1986) three-step procedure show that abusive supervision mediated the relationship between supervisor-rated coworker relationship con? ct and OCB, but not work effort. Thus, Hypothesis 4, which was supported for both dependent variables in Sample 1, was only supported for OCB in Sample 2. 5. Discussion The purpose of this study was to further our knowledge of the predictors and outcomes of abusive supervision. We pursued this goal by examining supervisor reports of relationship con? ict with their coworkers as a predictor of subordinate-rated abusive supervision, and LMX quality as a situational variable in? uencing this relationship. Additionally, we examined the outcomes of supervisor-rated OCB nd work effort and found that abusive supervision fully mediated the relationships between supervisor reports of coworker relationship con? ict and OCB in both samples and the outcomes of work effort in one sample. Returning to our theoretical arguments, we found that displaced aggression and LMX theories provide useful lenses for discussing predictors and outcomes of abusive supervision. Coworker relationship con? ict at any level is a potent source of stress and frustration as it impedes the achievement of goals and the attainment of desired outcomes (e. g. , Thomas, 1976).

Like past abusive supervision research (Tepper, Duffy, Henle & Lambert, 2006), our results suggest that some supervisors will resort to abusive behaviors against their employees as a means of coping with these consequences. This study advances existing research by explicitly examining situations where subordinates are not the logical target of retaliation (i. e. , they are not the source of the con? ict). Because subordinates are an easy and accessible target, however, having less power and less of an ability to retaliate, they make relatively safe candidates for abuse from frustrated supervisors.

Table 6 Hierarchical linear modeling mediation results in Sample 1. DV = abusive supervision Step 1a Age Job tenure Organizational tenure Relationship tenure Supervisor-rated coworker relationship con? ict Abusive supervision Note: OCB = organizational citizenship behaviors. N = 121. ? p b . 05. ?? p b . 01. .00 . 00 ? .01 . 08? Step 1b . 00 ? .00 ? .01 . 07 . 09? Step 2a . 00 ? .02 . 00 . 05 DV = OCB DV = work effort Step 2b . 00 ? .01 ? .00 . 05 ? .08+ Step 2c . 00 ? .01 ? .00 . 07 ? .06 ? .27? Step 3a ? .00 ? .02 . 02 . 00 Step 2b ? .00 ? .01 . 02 . 01 ? .14? Step 3c . 0 ? .01 . 01 . 04 . 11 ? .37?? K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 Table 7 Hierarchical linear modeling mediation results in Sample 2. DV = abusive supervision Step 1a Age Job tenure Organizational tenure Relationship tenure Supervisor-rated coworker relationship con? ict Abusive supervision Note: OCB = organizational citizenship behaviors. N = 134. ? p b . 05. ?? p b . 01. .00 . 00 ? .00 ? .00 Step 1b . 01 . 00 ? .00 ? .00 . 11? Step 2a ? .01 ? .00 . 00 . 00 DV = OCB DV = work effort 1019 Step 2b ? .01 ? .00 . 00 . 00 ? .13? Step 2c ? .01 . 0 ? .00 . 00 ? .09 ? .26? Step 3a ? .00 ? .00 . 00 ? .00 Step 3b ? .00 ? .00 . 00 ? .00 ? .03 Step 3c . 00 ? .00 . 00 ? .00 . 02 ? .39?? Additionally, when supervisors experience coworker relationship con? ict, our results indicate that they are most likely to abuse subordinates with whom they have low quality LMX relationships. This ? nding appears to support our argument that supervisors will focus their abusive behaviors on those employees in low quality exchanges in order to shield their high quality relationships from the detrimental effects of abusive supervision.

In this way, supervisors may reason that abusive behaviors allow them to vent frustration while minimizing the negative in? uence of this coping behavior on their most valued employees. Naturally, there are ? aws in this method of coping, most notably that the performance levels of abused employees will likely suffer, causing added strain and frustration for other employees and the supervisors themselves. Among supervisors who make the problematic choice to cope through abuse, however, it appears that employees in low-quality relationships are the most likely targets.

We also extended abusive supervision research with our ? ndings indicating that this variable is related to the outcomes of OCB and work effort. These ? ndings are noteworthy as they extend the nomological network of outcomes related to abusive supervision, and because both outcomes were supervisor-rated, which helps to minimize common source bias concerns (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Additionally, in sample 1 we found that abusive supervision served as an intermediary mechanism explaining the relationships between supervisor reports of coworker relationship con? ct and both consequences examined, and that there was also mediation on the outcome of OCB in sample 2. These results are important as they begin to answer the questions related to how situational supervisor variables, such as coworker relationship con? ict, ultimately are translated into subordinate outcomes. Surprisingly, we did not ? nd support for the work effort mediation hypothesis in Sample 2. A post hoc explanation for these insigni? cant ? ndings may relate to the demographic composition of the samples. Sample 2 was different from Sample 1 for both subordinates and supervisors.

It was primarily male, the average age was higher, and average job and organizational tenure were both more than double (except for supervisor job tenure) those in the ? rst sample. Although it is possible to deduce explanations as to how these differences might have in? uenced our results, such atheoretical logic would be overly speculative. Thus, as we suggest below, we encourage replicative research in additional samples that would allow for a more systematic assessment of these, or other, sample-speci? c characteristics. 5. 1. Contributions These ? dings make several contributions to the extant research on abusive supervision and LMX relationships. First, they build support for the notion of displaced abusive supervision and undermine a potential alternative explanation. In Tepper’s (2007) review of abusive supervision literature, he concluded that supervisors’ perceptions of organization-level factors, such as Fig. 2. Moderating effect of LMX on the relationship between supervisor-rated coworker relationship con? ict and abusive supervision in Sample 1. 1020 K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023

Fig. 3. Moderating effect of LMX on the relationship between supervisor-rated coworker relationship con? ict and abusive supervision in Sample 2. injustice and contract violation, can trigger abuse toward individual targets (i. e. , subordinates). He argued that this phenomenon might be explained by displaced aggression logic, in that subordinates serve as safe abuse targets even if the abuse is unlikely to resolve the perceptions triggering the desire to be abusive. An alternative, although somewhat tenuous, explanation is that these negative perceptions in? ence animosity toward the overall organization and that supervisors justify the abuse of subordinates who are seen as complicit in the perceived negative aspects of the organization. Our ? ndings suggest that this alternative basis of justi? cation would not adequately explain displaced abusive supervision. Looking beyond generalized organizational perceptions, we found that even frustration stemming from speci? c, identi? able non-subordinate sources (i. e. , supervisors’ coworkers) might translate into abuse toward subordinates.

This suggests that abusive supervision may serve as a “self-defeating” coping mechanism (e. g. , Baumeister & Scher, 1988), akin to mechanisms such as problem drinking and procrastination, in that it seeks short-term stress-reduction (e. g. , through emotional venting) in a harmful way that does not address the true source of the underlying problem (e. g. , con? ict with peers). We also expand on Tepper’s conclusion, again stemming from his 2007 review of abusive supervision research, that subordinate characteristics in? uence the likelihood that they will experience abuse.

As in the present study, Tepper (2007) cited victimization research to argue that subordinates who appear overly provocative or passive put themselves at a heightened risk for abuse. Expanding on the latter idea, we argued and observed that employees in low quality LMX relationships, who we expect demonstrate relatively high levels of passivity and vulnerability, report higher levels of abuse. This suggests that instead of identifying each of the potential subordinate characteristics that can incite abuse, a more parsimonious approach might be to look at broad relationship variables such as LMX that can be viewed as re? cting the aggregate impact of these individual characteristics. This conclusion also adds to LMX research by revealing an additional consequence of low-quality LMX relationships. In addition to the wide body of research showing that low-quality LMX subordinates experience outcomes such as fewer rewards, lower resource levels, and reduced job satisfaction (e. g. , Liden, Sparrowe & Wayne, 1997), this study suggests a more serious potential consequence in the form of victimization by abusive supervisors.

Additionally, our results, and the fact that most were replicated across the two samples, demonstrate the utility of multi-level models for predicting employee consequences of abusive supervision. Abusive supervision is an inherently multi-level phenomenon and this study shows that insights into some causes of abuse, such as con? ict levels between supervisors, exist that cannot be assessed from subordinate self-reports. Similarly, it identi? es supervisor-rated subordinate outcomes of abusive supervision (effort levels and OCB) that are dif? cult to assess with self-reports due to social desirability and common source bias concerns.

Further, these supervisor-rated effects provide some indication that abusive supervisors are at least indirectly aware of the selfdefeating consequences of abuse. Our data do not tell us whether supervisors consciously related their abuse to lower levels of employee effort and citizenship behavior. Their awareness of lower levels among the abused subordinates, however, suggests that a degree of denial would be necessary for the supervisors to overlook these cause–effect relationships. Although existing research has not, to our knowledge, explicitly stated that supervisors are unaware of the consequences of abusive behavior, this ? ding suggests that future research on preventing abuse might bene? t from focusing not on why supervisors view the behavior as acceptable, but why they engage in it despite an apparent awareness of these consequences. 5. 2. Limitations In addition to the aforementioned strengths and contributions, there are limitations that we must acknowledge to properly interpret the study’s results. First we acknowledge that the theoretical framework we have developed is not the only logical explanation for the hypothesized and observed relationships.

For example, it is plausible that the link between supervisors’ coworker relationship con? ict and abusive supervision is less cognitive than we have argued. Instead of selectively choosing subordinates as a low-risk target for venting frustration, it might be that some supervisors simply possess traits that predispose K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 1021 them toward con? ict and abusive behaviors (with higher levels of abuse directed at low quality members). Examples of such traits might include negative affectivity or hostile attribution styles (Douglas & Martinko, 2001).

An investigation of these possibilities would be useful in forming a more comprehensive understanding of the empirical relationships observed in the present study. In terms of methodological limitations, survey length constraints required us to use a reduced version of the abusive supervision scale. Even though we chose items that tapped into the full set of behaviors and found an extremely high correlation between our shortened measure and the full scale, this may still be viewed as a limitation. Another limitation is that we were unable to measure causality.

Thus, there is the potential that our relationships actually have reverse causality or that variables predict each other in a recursive manner. This is particularly true regarding the association between LMX perceptions and abusive supervision. Our results suggest that supervisors are more abusive toward some employees than others and that this difference is associated with variations in subordinates’ LMX scores. It can be argued, and is indeed very likely, that an abused employee would report lower LMX scores because of the abuse.

The ? nding that supervisors are selective in their abuse targets suggests that some criterion is evaluated before targets are chosen and we have argued that preexisting LMX relationship qualities could serve as this criterion. Our design does not allow us to make this claim de? nitively, however. Similarly, it may be that abusive supervision is not the predictor of work effort, but that insuf? cient effort by subordinates promotes higher levels of abusive supervision or that both variables in? uence each other in a cyclical manner.

We are particularly sensitive to the argument that there may be a feedback loop between abusive supervision and the outcome variables, such that abuse reduces subordinates’ effort and citizenship levels, and this reduction provokes further abuse, although the design of the study did not allow us to test this possibility. Along a similar line, it could be that abusive supervision toward subordinates is actually the cause of the supervisors’ con? ict among peers. We hope that future studies will be designed to better answer these causality questions.

There are also limitations associated with the sampling of public, white-collar organizations. Different organizations (e. g. , private, military, blue-collar) have different rules and norms governing behavior and it is likely that the abusive supervisory behaviors studied would be more or less permissible, and therefore more or less common, in different organizational settings. 5. 3. Directions for future research This study’s ? ndings suggest a number of directions for future research. First, we hope future researchers will examine our hypotheses in other, more diverse samples.

Although we examined two separate organizations, it is necessary to examine additional samples to better establish the generalizability or boundary conditions of our relationships. A second suggestion is to examine the relationships in this study with a longitudinal research design. The extant research on abusive supervision, including this study, has primarily relied on cross-sectional designs. Although telling, these studies leave out situations and behaviors that impact subordinates over time. In the case of both supervisor reports of coworker relationship con? ct and abusive supervision, it may be that supervisors and subordinates learn to cope with these situations, and become accustomed to them. Conversely, it could be that these situations and behaviors become worse as they accumulate over time (Harris, Kacmar, & Witt, 2005) as argued by Tepper (2000) and as noted in our discussion of cyclical relationships between abuse and behavioral outcomes in the previous section. Another avenue for future research is to conduct additional multi-level investigations to determine how supervisor experiences and situations impact their subordinates.

In this study we examined supervisor reports of coworker relationship con? ict, but it also would be interesting to investigate the effect of supervisors’ supervisor relationship con? ict, abusive supervision, LMX, team member exchange, and perceived organizational support (Erdogan & Enders, 2007; Tangirala, Green, & Ramanujam, 2007) as these variables are likely to have “trickle-down” effects on employee outcomes. Additionally, the aforementioned implication that supervisors might be aware of the consequences of abusive supervision suggests that a multilevel, or at least supervisor-level, focus on understanding the justi? ation process might provide insight into interventions for preventing such behavior. It would also be interesting to investigate personality characteristics, such as Machiavellianism, entitlement, and narcissism, of supervisors and subordinates and how these variables are related to abuse (Harvey & Harris, 2010; Kiazad, Restubog, Zagenczyk, Kiewitz, & Tang, 2010). Finally, we examined LMX from the perspective of the member, but it would be insightful to investigate leader reports of the LMX quality with their subordinates and how this rating interacts with supervisor coworker con? ict. 5. 4. Practical implications Before discussing speci? practical implications from this study, it should be noted that the overarching implication from this and most of the existing body of research on abusive supervision is that abusive supervision is detrimental to all parties. It is stressful for victims and hurts organizational performance and a supervisor’s effectiveness by negatively affecting desirable outcomes (see Tepper, 2007) such as increased levels of effort and OCB. Employees may feel intimidated and afraid to report the behavior of abusive supervisors, however, making it dif? cult for organizational leaders to identify and eliminate these abusive managers.

Because of the dif? culty in reducing existing levels of abuse, preventative techniques for reducing the likelihood of abusive supervision are advisable. The results of this study suggest that one such technique is for organizational leaders to observe and mediate con? icts between supervisory employees, thereby removing an antecedent of abusive behaviors. Additionally, because the supervisors in our study were more likely to abuse employees with whom they shared low-quality relationships, an organization-wide focus on the development of strong leader–member relationships might foster a climate where there are few 022 K. J. Harris et al. / The Leadership Quarterly 22 (2011) 1010–1023 desirable targets for abuse. We acknowledge that neither of these suggestions (i. e. , mediating supervisor con? icts and promoting strong leader–member relationships) are simple tasks. We suggest, however, that a continuous focus on these goals would consume far less time and energy than dealing with the consequences of abusive supervision. 6

Custom writing services

×

Hi there, would you like to get such a paper? How about receiving a customized one? Check it out