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ABUSIVE SUPERVISION AND WORK PERFORMANCE:
THE MODERATING ROLE OF ABUSIVE SUPERVISION
VARIABILITY
LIAN ZHOU
Guangdong University of Technology
I drew on situational strength theory to develop and test a cross-level contingent model
to explain how the dispersion-based conceptualization of group-level abusive supervision
(i.e., abusive supervision variability) affects subordinates’ work performance. Analysis of
multisource, longitudinal data of 242 supervisor–subordinate dyads from 82 groups showed
that abusive supervision was negatively related to job performance and organizational
citizenship behaviors (OCB). Further, results of moderated path analysis showed abusive
supervision variability augmented the negative impacts of abusive supervision on job
performance and OCB, such that these negative relationships would be stronger when the
variability of abusive supervision was low as opposed to high. I discuss the implications of
abusive supervision variability as it relates to understanding the impact of abusive supervision
on subordinates’ performance.
Keywords: abusive supervision, abusive supervision variability, job performance, subordinate,
organizational citizenship behavior.
Abusive supervision, defined as “the extent to which their supervisors engage
in the sustained display of hostile verbal and nonverbal behaviors, excluding
physical contact” (Tepper, 2000, p. 178), has received increasing attention
because of its detrimental consequences for individuals and organizations (Farh
& Chen, 2014). Researchers have begun to extend the individual-level emphasis
SOCIAL BEHAVIOR AND PERSONALITY, 2016, 44(7), 1089–1098
© 2016 Scientific Journal Publishers Limited. All Rights Reserved.
http://dx.doi.org/10.2224/sbp.2016.44.7.1089
1089
Lian Zhou, School of Management, Guangdong University of Technology.
This research was supported by the Natural Science Foundation of Guangdong Province
(2016A030310343) and the Youth Fund of Guangdong University of Technology (16ZS0043).
The author wishes to extend special thanks to Professor Jun Liu of Renmin University of China for
sharing survey data, for which the research was funded by the National Natural Science Foundation
of China (Project 70972025).
Correspondence concerning this article should be addressed to Lian Zhou, School of Management,
Guangdong University of Technology, Yinglong 510520, Guangzhou, People’s Republic of China.
Email: zhouliansd@gmail.com
ABUSIVE SUPERVISION AND PERFORMANCE
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in the abusive supervision literature by conceptualizing abusive supervision
from a multilevel perspective (Hannah et al., 2013). Despite prominent findings
about the average level of abusive supervision in group settings, scholars have
yet to explore the dispersion-based conceptualization (Chan, 1998) of abusive
supervision variability, which is defined as “the group-level phenomenon that
occurs when a supervisor engages in differential abusive treatment toward
subordinates in the same group” (Ogunfowora, 2013, p. 1106). In addition,
scholars have started to note the interactive effects of own abusive supervision
(i.e., subordinates’ own experience of being abused by the supervisor) and peer
abusive supervision (i.e., the extent to which coworkers are abused by the same
supervisor) on individuals’ work performance, such that the negative relationship
between own abusive supervision and work performance is stronger when peer
abusive supervision is low rather than high (Peng, Schaubroeck, & Li, 2014).
However, the role of abusive supervision variability in the shaping of individuals’
responses to abusive supervision has not yet been considered.
My aim was to address this gap by using situational strength theory (Mischel,
1973) for developing a cross-level framework to examine the contingent effect
of abusive supervision variability on the individual-level relationship between
abusive supervision and work performance. Specifically, I argued that little
variability in abusive supervision would foster a situation of strong interactional
(in)justice (Ogunfowora, 2013) which, in turn, would facilitate the negative
impact of abusive supervision on subordinates’ work performance according to
social exchange theory (Blau, 1964).
In my research I sought to contribute to the existing literature in two ways.
First, this research could broaden understanding of the multilevel nature of
abusive supervision by considering group-level abusive supervision variability
based on the dispersion model. Second, my research extends previous studies of
abusive supervision–work outcome relationships by examining the moderating
role of abusive supervision variability from the situational strength perspective.
Theoretical Development and Hypotheses
Abusive Supervision and Work Performance
In justice theory (Bies & Moag, 1986) it is proposed that subordinates tend
to experience interpersonal injustice when they perceive mistreatment from
their supervisor (Tepper, 2000). Thus, subordinates might be motivated to
restore equity by reducing their effort in their tasks at work. They may withhold
organizational citizenship behaviors (OCBs) or their performance may become
worse (Xu, Huang, Lam, & Miao, 2012).
In a recent study in which conservation of resources (COR; Hobfoll, 1989)
theory was employed, it was argued that abusive supervision can be conceptualized
as a workplace stressor that threatens subordinates’ valued personal resources
ABUSIVE SUPERVISION AND PERFORMANCE 1091
(Whitman, Halbesleben, & Holmes, 2014). Researchers have suggested that such
resource loss and psychological distress could lead to a negative impact on work
behaviors (Aryee, Sun, Chen, & Debrah, 2008). For example, subordinates might
expend time and energy to cope with the abusive behavior rather than devoting
themselves to job tasks. In addition, people may use their personal resources to
exert control over the abusive situation, for example, withholding discretionary
behaviors, such as OCBs. Thus, I proposed:
Hypothesis 1a: Abusive supervision will be negatively related to job performance.
Hypothesis 1b: Abusive supervision will be negatively related to organizational
citizenship behaviors.
Moderating Role of Abusive Supervision Variability
As described, a supervisor may display differential abusive treatment toward
subordinates in the same work unit (Tepper, Moss & Duffy, 2011). Specifically,
in groups with low variability in abusive supervision, subordinates share similar
interactional (in)justice perceptions. Yet members in groups with high abusive
supervision variability have reported varied levels of perceptions of interactional
(in)justice from the supervisor (Ogunfowora, 2013). Thus, in groups with low
variability in abusive supervision, strong situations (i.e., aspects of the situation
lead people to perceive events the same way) are created in which group members
tend to interpret, and respond to, the abusive supervision in a similar way, such as
reducing their effort at work (Mischel, 1973; Schneider, Salvaggio, & Subirats,
2002). In contrast, following the reasoning on which COR theory is based, high
abusive supervision variability (a situation of perception of weak interactional
[in]justice) provides group members with ambiguous signals about whether or
not resource investment, such as OCBs, is a worthwhile endeavor (Campbell,
Perry, Maertz, Allen, & Griffeth, 2013). Because of the power differential
between supervisors and subordinates, subordinates are, therefore, unlikely to
retaliate against the abusive supervisor by reducing their work effort when there
is high variability in the abusive supervision. Thus, I proposed:
Hypothesis 2a: Abusive supervision variability will moderate the relationship
between abusive supervision and job performance: The negative relationship will
be stronger when there is little variability in the abusive supervision.
Hypothesis 2b: Abusive supervision variability will moderate the relationship
between abusive supervision and occupational citizenship behaviors: The
negative relationship will be stronger when there is little variability in the abusive
supervision.
Method
Participants and Procedure
Participants were supervisor–subordinate dyads employed by six manufacturing
ABUSIVE SUPERVISION AND PERFORMANCE
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companies in China. Given the sensitive nature of abusive supervision, I obtained
access to the participating companies through personal networks in order to
collect high quality data. According to Cooke (2009), surveys targeted at firms
with good quality access (i.e., convenience sampling through personal networks)
yield a high response rate. Surveys were distributed to 128 supervisors and
their 338 subordinates. On the cover page of the survey there was an assurance
that participation was voluntary and that participants’ anonymity would be
safeguarded. Each respondent was asked to seal the completed survey form
in the envelope provided and return it directly to the researcher. I received 82
supervisors-rating (response rate = 64.1%) and 242 subordinates-rating survey
forms (response rate = 71.6%). Among the subordinates, 68.2% were men, and
the average age of the subordinates was 33.41 years (SD = 6.74, range = from 26
to 63 years). About half of the subordinates had been employed for over 5 years.
Data were collected at two time points with a 9-month interval between
collections. At Time 1, supervisors rated job performance and OCBs of each
subordinate, and subordinates completed a measure of abusive supervision survey
as well as providing their demographic information. At Time 2, supervisors
assessed their subordinates’ job performance and OCBs.
Measures
As the scales were originally written in English, I invited two bilingual scholars
fluent in Mandarin and English to translate them into Chinese and then another
bilingual scholar translated them back into English. The response format was
a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).
Abusive supervision. I measured abusive supervision using Tepper’s (2000)
15-item scale. A sample item is: “My unit supervisor reminds me of my past
mistakes and failures.” This scale has shown good reliability and validity with a
Chinese population (Xu et al., 2012) and had a Cronbach’s alpha coefficient of
.96 in my study.
Abusive supervision variability. Following Chan’s (1998) dispersion model
and a prior abusive supervision variability measure (Ogunfowora, 2013), I op-
erationalized abusive supervision variability for each group by calculating the
standard deviation of individual abusive supervision ratings within each group.
Supervisor-rated work performance. This was a measure of job performance
and OCBs, which were assessed using the five-item job-performance scale
developed by Williams and Anderson (1991) and the 14-item OCB scale
developed by Hui, Law, and Chen (1999). A sample item of job performance is:
“This subordinate always adequately completes assigned duties.” A sample item
of OCBs is: “This subordinate is willing to assist new colleagues in adjusting to
the work environment.” In my study, these two subscales had Cronbach’s alpha
coefficients of .85 and .86, respectively.
ABUSIVE SUPERVISION AND PERFORMANCE 1093
Control variables. Subordinates’ gender and tenure were controlled. The effect
of Time 1 job performance and OCBs were also controlled because Tepper et al.
(2011) suggested that subordinates’ performance was related to their perceptions
of abusive supervision.
Confirmatory Factor Analysis
In order to examine the distinctiveness of all measures, we conducted
confirmatory factor analysis by calculating comparative fit index (CFI),
Tucker-Lewis index (TLI), and root mean square error of approximation
(RMSEA), and found support for a three-factor model with significant factor
loadings, 2 (512, N = 242) = 1007.39, CFI = .90, TLI = .90, RMSEA = .06.
An alternative two-factor model was tested by combining job performance and
OCBs into a factor. The fit of the two-factor model was significantly worse than
that of the three-factor model (Δ2 (2, N = 242) = 132.77, p < .01).
Analytic Strategy
Data in the present research were hierarchical, with the subordinates nested in
work groups. Thus, I used hierarchical linear modeling (HLM) with the software
HLM 6.08 to estimate the hypothesized model.
Results
Table 1 shows the means, standard deviations, reliabilities, and correlations
among the study variables.
Table 2 shows the HLM results. Abusive supervision was hypothesized to
be negatively related to job performance and OCBs in Hypotheses 1a and 1b,
respectively. Results in Model 2 show that abusive supervision was negatively
related to job performance ( = -.29, p < .01). Results in Model 4 show that
abusive supervision was negatively related to OCBs ( = -.14, p < .01). Thus,
Hypotheses 1a and 1b were supported.
A cross-level interaction between abusive supervision and abusive supervision
variability was proposed in predicting job performance and OCBs in Hypotheses
2a and 2b, respectively. I regressed the slope estimates for individual-level
abusive supervision on abusive supervision variability to test this interaction.
For job performance, results of Model 3 show that the cross-level interaction
was significant ( = .42, p < .01). I plotted this interaction and conducted simple
slope tests (Aiken & West, 1991). Figure 1 shows that, compared to high abusive
supervision variability, = -.51, p < .01, the negative relationship between
abusive supervision and job performance was stronger when abusive supervision
variability was low, = -.87, p < .01. For OCBs, the results of Model 6 revealed
that the cross-level interaction was significant ( = .18, p < .05). Figure 2 shows
that, compared to high abusive supervision variability, = -.26, p < .01, the
negative relationship between abusive supervision and OCBs was stronger when
ABUSIVE SUPERVISION AND PERFORMANCE
1094
Table 1. Means, Standard Deviations, Reliabilities, and Correlations among Study Variables
Individual-level variables M SD 1 2 3 4 5 6 7
1. Gender 0.68 0.47 —
2. Tenure 8.11 7.08 -.05 —
3. Job performance, Time 1 3.83 0.68 .07 .16* (.86)
4. OCB, Time 1 3.84 0.53 .09 .10 .53** (.89)
5. Abusive supervision, Time 1 2.60 0.95 -.09 -.18** -.30** -.32** (.96)
6. Job performance, Time 2 3.83 0.67 .04 .25** .42** .36** -.36** (.85)
7. OCB, Time 2 3.82 0.44 .13* .29** .24** .45** -.39** .62** (.86)
Group-level variable M SD 1 2
1. Size 3.00 1.02 —
2. Abusive supervision variability 0.66 0.43 .26* —
Note. OCB = organizational citizenship behavior; Numbers in parentheses are coefficient alphas. * p < .05, ** p < .01.
ABUSIVE SUPERVISION AND PERFORMANCE 1095
Table 2. Hierarchical Linear Modeling Results: Main and Interactive Effects
Variables Job performance, Time 2 OCB, Time 2
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Intercept 3.64** 3.71** 4.10** 3.79** 3.78** 4.22**
Individual-level variables
Gender -0.02 -0.01 -0.01 0.08 0.09 0.10
Tenure 0.02 0.01 0.01 0.01 0.01 0.01*
Job performance, Time 1 0.10 0.09 0.08 -0.13* -0.13* -0.11*
OCB, Time 1 0.38** 0.20 0.22† 0.42** 0.31** 0.25**
Abusive supervision -0.29** -0.69** -0.14** -0.34**
Group-level variables
Group size 0.06 0.04 0.06 0.01 0.01 0.03
Abusive supervision variability 0.11 0.04
Group-level abusive supervision -0.21* -0.21**
Group-level abusive supervision × Abusive supervision variability 0.25 0.16
Cross-level interactions
Abusive supervision × Abusive supervision variability 0.42** 0.18*
R2 .07 .07 .09 .01
Note. OCB = organizational citizenship behavior; * p < .05, ** p < .01.
ABUSIVE SUPERVISION AND PERFORMANCE
1096
abusive supervision variability was low, = -.42, p < .01. Hypotheses 2a and 2b
were supported.
Job performance
Abusive supervision
Low High
5
4
3
2
1
High abusive supervision variability
Low abusive supervision variability
Figure 1. Interactive effect of abusive supervision and abusive supervision variability on job
performance.
Occupational citizenship behavior
Abusive supervision
Low High
5
4
3
2
1
High abusive supervision variability
Low abusive supervision variability
Figure 2. Interactive effect of abusive supervision and abusive supervision variability on
organizational citizenship behavior.
Discussion
The main goal of my research was to investigate the contingent effect of
abusive supervision variability on the individual-level relationship between
abusive supervision and work performance. My findings have several theoretical
implications. First, the results demonstrate that, among the group of participants
ABUSIVE SUPERVISION AND PERFORMANCE 1097
in my study, abusive supervision was a collective phenomenon with consequences
for the group members (Farh & Chen, 2014). Specifically, my findings support
the dispersion-based conceptualization of group-level abusive supervision
variability as an important and meaningful construct from the perspective of
situational strength theory (Ogunfowora, 2013).
Second, based on previous research of the negative impact of abusive
supervision on subordinates’ performance (Xu et al., 2012), my findings further
revealed that these relationships are contingent on group-level variability of
abusive supervision. It appears that little variability in abusive supervision
fosters a strong situation of interactional (in)justice (i.e., aspects of the situation
lead people to perceive events in the same way) where subordinates are likely
to interpret, and respond to, the abusive supervisor in the same way, such as
reducing their work effort to restore equity in the social exchange process (Blau,
1964). However, I suggest that it is worth considering to what extent this finding
is culturally specific. The Chinese subordinates who were the participants in my
study are characterized by a high level of values based on tradition and power
distance orientation. They were less likely to perceive abusive supervision
as unfair and attribute their mistreatment to their own unfavorable qualities
(Martinko, Harvey, Brees & Mackey, 2013). In contrast, subordinates tend to
believe the leader is, indeed, abusive in a situation of little variability in abusive
supervision (Peng et al., 2014), and they were likely to seek a fair exchange with
the abusive supervisor by reducing work effort.
In practice, supervisors should pay attention to the potential influence of
abuse on intraunit social interactions given that the situation of a low level of
variability in abusive supervision can foster a perception of strong interactional
(in)justice. Moreover, management feedback such as seeking feedback from all
subordinates about their supervisor is helpful to decide if the supervisor should
receive disciplinary or developmental action (Hannah et al., 2013).
One limitation of my study was the operationalization of abusive supervision
variability. A more appropriate approach is to ask each subordinate to report the
extent to which the supervisor is equally or differently abusive toward group
members (Ogunfowora, 2013). A second limitation of my study is that I did not
examine the process of abusive supervision variability on subordinates’ outcomes.
Future researchers could explore possible mediators that may moderate the effect
of abusive supervision variability on subordinates’ outcomes.
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