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LEADER PERSONALITY, ABUSIVE SUPERVISION AND EMPLOYEE OUTCOMES:

AN INTEGRATIVE MODEL

Dongyuan Wu

A DISSERTATION

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Michigan State University

In partial fulfillment of the requirements

for the degree of

Human Resources and Labor Relations—Doctor of Philosophy

2020

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ABSTRACT

LEADER PERSONALITY, ABUSIVE SUPERVISION AND EMPLOYEE OUTCOMES: AN

INTEGRATIVE MODEL

Dongyuan Wu

In this study, I propose an integrative model that examines both antecedents and

outcomes of abusive supervision. I integrate personality theory into the abusive supervision

literature, examining how both widely and narrowly defined leader personality traits are

associated with abusive supervision. In addition, I investigate how employees’ power distance

orientations and job type (white-collar and blue-collar) impact the abusive supervision-outcome

linkage and potential underlying mechanisms. I tested this model using a sample of 1,009

workers from 136 work teams in four organizations in China. The study used a three-wave time-

lagged design and obtained responses from individual employees and their team leaders. The

results overall provide support for the proposed model and several of the hypotheses. The results

indicate that leader agreeableness is an important predictor of abusive supervision and that

ethical climate moderates the relationship between leader narcissism and abusive supervision.

Regarding the relationship between abusive supervision and employee outcomes, this study

supports that interactional justice is an important mediator. In addition, the findings show that the

indirect effects via interactional justice are different for white-collar and blue-collar employees,

highlighting the importance of considering job type as a key boundary condition in future

studies. In contrast to prior research, this study does not provide strong evidence for the

moderating role of power distance orientation on the relationship between abusive supervision

and employee outcomes. Theoretical contributions and future directions are discussed.

DONGYUAN WU

2020

ACKNOWLEDGEMENTS

I would like to express my gratitude to everyone who made my dream of becoming an

organizational researcher come true. This would not have been possible without the support from

all of you.

I would like to give special thanks to my advisor, Dr. James Dulebohn. During my five

years in the doctoral program, Professor Dulebohn spent a lot of time advising me. I benefited

greatly from our formal meetings and informal conversations. Importantly, his enthusiastic

attitude toward research highly impacts me and makes me passionate about doing research. I

deeply believe that doing organizational research is a lot of fun and meaningful to the world. I

also would like to thank my other dissertation committee members, Dr. Mark Roehling, Dr. John

Schaubroeck, Dr. Jason Huang, and Dr. Chenwei Liao. I appreciate that they always keep their

doors open to me whenever I have research questions for my dissertation and other research

projects. Their insights and guidance greatly improved my critical thinking and passion toward

research.

I would like to thank other faculty members, especially those in our Ph.D. committee, in

our department. They sincerely care for our well-being and make us feel supported and valued.

At Michigan State University, I benefited from taking Ph.D. level classes from other departments

including management, psychology, and education. The opportunity to take classes outside of

our department greatly broadened my views and enhanced my scientific thinking.

I also thank my friends from my department, Department of Geography, and Department

of Psychology. The gatherings with them added additional happiness to my life at MSU.

Finally, I would like to thank my husband and my best friend, Jiang Chang, for his

unconditional support and love. It is unbelievable that we become alumni again after high school.

Along the way of growing up as researchers, we support each other and provide each other with

the strongest encouragement. I thank my son, An Chang, who adds an additional dimension and

role to my life and always gives me amazing love. I thank my family members for their

encouragement and instrumental support along the way.

TABLE OF CONTENTS

LIST OF TABLES .................................................................................................................................. viii

LIST OF FIGURES .................................................................................................................................. ix

CHAPTER 1 INTRODUCTION ............................................................................................................. 1

1.1 Overview / Statement of the Problem ................................................................................ 1

1.2 Purpose and Contribution of the Research ........................................................................ 4

1.3 Organization of the Research ............................................................................................ 6

CHAPTER 2 LITERATURE REVIEW ................................................................................................. 7

2.1 Abusive Supervision .......................................................................................................... 7

2.1.1 Conceptualization of Abusive Supervision ............................................................. 7

2.1.2 Nomological Network of Abusive Supervision ...................................................... 9

2.2 Leader Personality and Abusive Supervision .................................................................. 10

2.2.1 Two Approaches to Examining Personality .......................................................... 12

2.2.2 Trait Activation Theory and Situational Factors ................................................... 16

2.3 Abusive Supervision and Cultural Values ....................................................................... 18

2.3.1 Implicit Leadership Theory and Cultural Values .................................................. 21

2.3.2 Level of Analysis for Cultural Values................................................................... 22

2.3.3 Justice as A Mediator ............................................................................................ 25

2.4 Abusive Supervision and Job Type ................................................................................. 26

CHAPTER 3 MODEL AND HYPOTHESIS DEVELOPMENT ..................................................... 28

3.1 Antecedents to Abusive Supervision ............................................................................... 30

3.1.1 Leader Personality and Abusive Supervision ....................................................... 30

3.1.2 Trait-Relevant Situational Factor as A Moderator ................................................ 35

3.2. Outcomes to Abusive Supervision ................................................................................. 37

3.2.1 Power Distance Orientation as A Moderator ........................................................ 37

3.2.2 Job Type as A Moderator ...................................................................................... 42

3.2.3 Interactional Justice as a Mediator ........................................................................ 46

3.2.4 A Moderated Mediation Model ............................................................................. 47

CHAPTER 4 METHOD .......................................................................................................................... 49

4.1 Participants and Procedures ............................................................................................. 49

4.2 Measures .......................................................................................................................... 50

4.2.1 Time 1 Survey ....................................................................................................... 50

4.2.2 Time 2 Survey ....................................................................................................... 52

4.2.2 Time 3 Survey ....................................................................................................... 52

4.3. Analytical Approaches ................................................................................................... 53

4.3.1 Data Screening and Preparation ............................................................................ 54

4.3.2 Descriptive Data, Correlation Analysis, and Reliability Analysis ........................ 54

4.3.3 Regression and Moderation Analysis .................................................................... 54

vii

4.3.4 Measurement Model, Hierarchical Linear Modeling Analysis, and Structural

Model ............................................................................................................................. 55

CHAPTER 5 RESULTS ......................................................................................................................... 58

5.1 Data Aggregation, Descriptive Data, and Correlations ................................................... 58

5.2 Antecedents to Abusive Supervision ............................................................................... 58

5.2.1 Regression and Moderation Analysis .................................................................... 58

5.3 Outcomes to Abusive Supervision .................................................................................. 64

5.3.1 Moderation Analysis for Power Distance Orientation and Job Type.................... 64

5.3.2 Multilevel Confirmatory Factor Analysis ............................................................. 68

5.3.3 Multilevel Moderated Mediation Model ............................................................... 69

CHAPTER 6 DISCUSSION ................................................................................................................... 74

6.1 The Role of Leader Personality in Abusive Supervision ................................................ 74

6.2 Ethical Climate and Trait Activation Theory .................................................................. 77

6.3 The Relative Importance of Power Distance Orientation and Job Type ......................... 79

6.4 Generalizability Issues of Current Research with a Focus on White-Collar Employees 80

6.5 Strengths, Limitations, and Future Directions ................................................................. 81

6.6 Conclusions ..................................................................................................................... 85

APPENDIX ............................................................................................................................................... 86

REFERENCES ......................................................................................................................................... 91

viii

LIST OF TABLES

Table 1. Means, SDs, reliabilities, and correlations ..................................................................... 60

Table 2. Regression analyses predicting abusive supervision ...................................................... 62

Table 3. HLM analyses for power distance orientation and job nature as moderators ................. 65

Table 4. Indirect effects from abusive supervision to outcomes through interactional justice ..... 71

Table 5. Moderated indirect effects from abusive supervision to outcomes through interactional

justice by power distance orientation ............................................................................................ 72

Table 6. Moderated indirect effects from abusive supervision to outcomes through interactional

justice by job type ......................................................................................................................... 73

LIST OF FIGURES

Figure 1. Conceptual model ..........................................................................................................29

Figure 2. The relationship between leader narcissism and abusive supervision with ethical

climate as a moderator ..................................................................................................................63

Figure 3. The relationship between abusive supervision and job performance with power distance

orientation as a moderator ..............................................................................................................66

Figure 4. The relationship between abusive supervision and interactional justice with job type as

a moderator ....................................................................................................................................67

Figure 5. The relationship between abusive supervision and deviance with job type as a

moderator .......................................................................................................................................68

Figure 6. A moderated mediation model .......................................................................................70

CHAPTER 1 INTRODUCTION

1.1 Overview / Statement of the Problem

A primary focus in the leadership literature is on the positive influence that leaders may

have on their followers (Hoch, Bommer, Dulebohn, & Wu, 2018; Yukl, 1989). Examples of

these positive leadership forms include transformational leadership, transactional leadership

(Bass, 1985), consideration and initiating structure (Fleishman, 1995), and, more recently, ethical

leadership (Brown, Treviño, & Harrison, 2005), and servant leadership (Greenleaf, 2002).

However, within the past three decades, other groups of researchers have turned their attention to

destructive supervisory behaviors. To label these negative leader behaviors, researchers have

developed a few constructs, such as workplace bullying (Hoel, Rayner, & Cooper, 1999),

supervisor aggression (Neuman & Baron, 1998), petty tyranny (Ashforth, 1994), and abusive

supervision (Tepper, 2000). Among these constructs, researchers have given more attention to

abusive supervision. According to Tepper (2000), abusive supervision refers to “subordinates'

perceptions of the extent to which supervisors engage in the sustained display of hostile verbal

and nonverbal behaviors, excluding physical contact” (p. 178).

Research on abusive supervision has primarily focused on its negative effects on

outcomes at different levels. Empirical studies have indicated that abusive supervision has a

negative impact on employee attitudes (Tepper, Henle, Lambert, Giacalone, & Duffy, 2008;

Harvey, Stoner, Hochwarter, & Kacmar, 2007) and employee behaviors (Harris, Kacmar, &

Zivnuska, 2007; Zellars, Tepper, & Duffy, 2002; Mitchell & Ambrose, 2007; Tepper, Henle,

Lambert, Giacalone, & Duffy, 2008). Research also has indicated that the negative effects of

abusive supervision occur at the team level, decreasing team creativity (Liu, Liao, & Loi, 2012)

and team proactive behavior (Rousseau & Aube, 2018). Within organizations, it has been

estimated that abusive supervision affects 13.6% of workers in the United States, resulting in a

cost estimate of $23.8 billion annually for U.S. corporations (Tepper, 2007; Tepper, Duffy,

Henle, & Lambert, 2006).

Besides outcomes, researchers have also paid some attention to the antecedents of

abusive supervision. The major groups of antecedents include subordinate personality (e.g.,

Brees, 2012), subordinate behaviors (e.g., Walter, Lam, Van Der Vegt, Huang, & Miao, 2015),

supervisor experience with abusive supervision (Taylor, Griffith, Vadera, Folger, & Letwin,

2019), family aggression (Garcia, Restubog, Kiewitz, Scott, & Tang, 2014), as well as team

climates (Mawritz, Dust, & Resick, 2014; Taylor, 2004).

Although some studies have focused on subordinate personality, very few studies have

focused on leader personality traits to examine their association with leaders’ perpetration of

abusive supervision. Yet, leadership scholars traditionally have examined how leader personality

traits relate to leadership behaviors for other leadership styles, such as transformational

leadership (e.g., Bono & Judge, 2004; Judge & Bono, 2000), ethical leadership (e.g., Kalshoven,

Den Hartog, & De Hoogh, 2011; Walumbwa & Schaubroeck, 2009), and servant leadership (e.g.,

Washington, Sutton, & Field, 2006). These studies help answer the question of “what makes a

leader great?” (Judge & Bono, 2000). Regarding abusive supervision, researchers know very

little about why some leaders engage in these behaviors while others do not.

Therefore, it is important to study subordinates’ perceptions of whether leaders with

certain personality traits are more likely to be abusive. By exploring this question, I respond to

Tepper’s (2007) call for future research to devote more attention to supervisor-level factors, such

as personality traits. Furthermore, based on trait activation theory (Tett & Guterman, 2000), I

argue that certain situational factors may strengthen the relationship between personality traits

and abusive supervision. Identifying personality traits as antecedents and situational factors as

moderators has the potential to help organizations select and develop non-abusive leaders and

foster more positive working relationships.

Additionally, in the global context, it is important to acknowledge how cultural values

impact the effectiveness of leader behaviors. Tepper (2007) proposed that people from high

power distance countries, such as Japan and China, may find abusive supervision more

acceptable than people from low power distance countries, such as the United States and

Sweden. Tepper called for future researchers to examine the role of cultural values in abusive

supervision. Responding to this call, some studies have explored how power distance orientation

moderates the relationship between abusive supervision and outcomes (e.g., Lian, Ferris, &

Brown, 2012; Lin, Wang, & Chen, 2013; Vogel et al., 2015). The findings of these studies have

indicated that people with low power distance orientations tend to view abusive supervision as

less fair than people with high power distance orientations. Moreover, for people with low power

distance orientation, abusive supervision tends to exhibit a more negative impact on trust, job

satisfaction, and work effort.

However, additional research is needed to address the role of cultural values in abusive

supervision. Existing studies on cultural values have only examined a limited number of

employee attitudes and behaviors. Thus, it is not clear how cultural values moderate the

relationship between abusive supervision and important employee behaviors, such as job

performance, organizational citizenship behavior (OCB), and creativity. In addition, more

research should examine the underlying mechanisms that explain why the abusive supervision-

outcome linkage differs among people with different cultural values.

In this study, I also investigate the role of job type, either white-collar or blue-collar, as a

moderator for the relationship between abusive supervision and employee outcomes. The abusive

supervision literature has ignored job type as a moderator and has heavily relied on white-collar

samples (e.g., Liu et al., 2012; Shoss, Eisenberger, Restubog, & Zagencyzk, 2013; Vogel et al.,

2015). It is important to examine the role of job type to extend our understanding of abusive

supervision. The results would shed light on the generalizability of existing findings on different

occupations. In addition, abusive supervision researchers have typically studied cultural values

by themselves, ignoring the influences of other factors such as job type (e.g., Lian et al., 2012;

Vogel et al., 2015). In other words, how employees respond to abusive supervision is not simply

influenced by their cultural values, such as the power distance orientation they hold, but also by

the nature and characteristics of their jobs. Therefore, by examining both cultural values and job

type as moderators simultaneously, I examine the relative importance of cultural values and job

type on employees’ responses to abusive supervision.

1.2 Purpose and Contribution of the Research

The overarching purpose of this dissertation is twofold: (1) to integrate personality theory

into the abusive supervision literature, examining how leader personality trait antecedents are

associated with abusive supervision, and (2) to investigate how employees’ power distance

orientations and job type impact the abusive supervision-outcome linkage and potential

underlying mechanisms. By addressing the above two questions, I test an integrated model that

includes both antecedents and outcomes of abusive supervision, as well as potential moderation

and mediation mechanisms.

In my dissertation, I contribute to the leadership literature in several ways. First, I include

both widely and narrowly defined personality traits of leaders as antecedents of abusive

supervision and therefore examine the predictive power of personality on abusive supervision.

This approach expands the field’s understanding of leader personality traits represent one group

of understudied antecedents. Personality antecedents may be uniquely suited for predicting

abusive supervision because as a form of nonphysical aggressive behaviors, abusive supervision

reflects leaders’ deep-seated values and behavioral tendencies. Second, I include a trait-relevant

situational factor—ethical climate—to examine whether it moderates the personality-abusive

supervision linkage. It is possible that certain situational factors may encourage personality

expression in terms of abusive behaviors. In this way, I integrate trait activation theory with

abusive supervision.

Third, I examine how employee power distance orientation moderates the relationship

between abusive supervision and outcomes, which include key employee behaviors such as job

performance, OCB, creativity, and deviance. Generally, researchers assume that people with a

high power distance orientation have less intensive responses to abusive supervision than their

low power counterparts (Martinko, Harvey, Brees, & Mackey, 2013; Tepper, 2007). However,

Lian et al. (2012) found that for people with a high power distance orientation, the relationship

between abusive supervision and deviance is stronger than for people with a low power distance

orientation. Thus, it is important to examine how power distance orientation impacts the abusive

supervision-outcome linkage.

Fourth, I examine how employee job type moderates the relationship between abusive

supervisor and outcomes, and thereby extend our understanding of abusive supervision.

Collectively, these additions improve our understanding of the relative influence of cultural

values and job type on employees’ responses to abusive supervision. Fifth, based on the

organizational justice theory (Tyler & Bies, 1990), I include interactional justice as a potential

mediator to examine whether it helps explain the relationships among abusive supervision,

power distance orientation, job type, and outcomes. This moderated mediation model reveals the

underlying mechanisms of moderated relationships by power distance orientation and job type.

1.3 Organization of the Research

The dissertation is organized as follows. In Chapter 2, I present a review of the abusive

supervision literature and identify gaps in the literature. In Chapter 3, I present my dissertation

that delineates (1) the potential role of leader personality traits as propositional predictors of

abusive supervision and a trait-relevant situational factor as a moderator, as well as (2) power

distance orientation and job type as moderators for the abusive supervision-outcome linkage and

potential mediator for such a linkage. For each relationship in this model, I describe its

theoretical basis and corresponding hypothesis. In Chapter 4, I detail the method I use to test my

proposed theoretical model and hypotheses. In Chapter 5, I present the results of my hypothesis

testing. In Chapter 6, I discuss the implications of these findings and offer directions for future

research.

CHAPTER 2 LITERATURE REVIEW

2.1 Abusive Supervision

2.1.1 Conceptualization of Abusive Supervision

Leadership scholars have studied positive forms of leadership, such as transformational

leadership and transactional leadership, to reveal how supervisors can positively influence

subordinates and organizations (Bass, 1985). However, in recent decades, researchers have

turned their attention to examine destructive supervisory behaviors, including sexual harassment,

physical violence, and nonphysical aggressive behavior (Ashforth, 1997; Duffy, Ganster, &

Pagon, 2002; Schat, Desmarais, & Kelloway, 2006). Among the identified behaviors,

nonphysical behaviors, such as gossiping, withholding information, public ridicule, and

ostracism have been most commonly studied. To study these nonphysical hostile behaviors,

Tepper (2000) formally proposed the construct of “abusive supervision” to refer to

“subordinates' perceptions of the extent to which supervisors engage in the sustained display of

hostile verbal and nonverbal behaviors, excluding physical contact” (p. 178). After Tepper

(2000) published this seminal paper on abusive supervision, many researchers began to pay

attention to this new construct of negative leadership and conduct empirical research to examine

its nomological networks (Martinko et al., 2013).

Before Tepper (2000) proposed the construct of abusive supervision, in the workplace

hostility and aggression literature scholars had proposed a few related constructs such as

workplace bullying (Hoel et al., 1999), supervisor aggression (Neuman & Baron, 1998), and

petty tyranny (Ashforth, 1997). However, abusive supervision is different from these constructs

and covers different content domains. For example, workplace bullying occurs when individuals

experience repeated exposure to hostile actions, such as attacks, abuse, and social isolation, in

the workplace (Hoel et al., 1999). This form of bullying is different from abusive supervision as

it does not necessarily involve a downward target, and its perpetrators can possibly be coworkers

and subordinates. In addition, bullies aim to cause harm, whereas abusive supervision does not.

Abusive supervision does not encompass content other than hostility and does not have specific

aim. Moreover, abusive supervision is different from aggression. While abusive supervision

reflects indifference and willful hostility and may or may not be deviant (Tepper, 2000),

aggression involves deviant, physical and nonphysical behaviors that cause harm (Neuman &

Baron, 1998).

Tepper (2007) summarized how abusive supervision is different from the existing

constructs in four key ways. First, abusive supervision has a downward target—subordinates.

Second, it excludes physical hostility but includes both verbal and nonverbal hostility. Third, it

solely focuses on hostility. Fourth, it does not refer to any intended outcomes. Besides these

differences, Tepper (2007) further emphasized that abusive supervision is a construct based on

subordinates’ subjective assessment of leaders’ sustained and willful display of nonphysical

hostility. A comprehensive review indicates that until now, abusive supervision has attracted

more empirical examination than other constructs detailing destructive supervisor behaviors.

Since I am interested in the supervisor-subordinate relationship specifically from a “dark” side, I

find that abusive supervision is the most appropriate construct.

Researchers have primarily and consistently operationalized abusive supervision with the

most widely used unidimensional scale developed by Tepper (2000). Tepper (2000) drew on

instruments that measure nonphysical abuse in other relationships, such as dating (Raymond &

Bruschi, 1989), domestic abuse (Shepard & Campbell, 1992), and other management literature

on nonphysical abusive behaviors (e.g., Robinson & Bennett, 1995). He identified an initial list

of 20 items. After performing a content analysis of these 20 items, Tepper interspersed these

items with 20 other items adapted from physical abuse measures and created a checklist. He

eventually kept 15 items that use a 5-point Likert scale. An example of an item in this scale is

“(Boss) Tells me my thoughts or feelings are stupid.”

2.1.2 Nomological Network of Abusive Supervision

As indicated by review papers and meta-analytical studies, researchers have a strong

interest in abusive supervision. In Tepper’s 2007 review, he found 20 articles on abusive

supervision published since 2000. Whereas in a more recent review, Martinko et al. (2013)

identified 62 new studies in the six years since Tepper’s review. In a recent meta-analysis,

Mackey, Frieder, Brees, and Martinko (2017) found 112 relevant studies based on a search

conducted in March 2014. These primary studies and reviews have presented a large

nomological network of abusive supervision that includes antecedents, attitudinal and behavioral

outcomes, moderators, and mediators as explanatory mechanisms. I summarize the research on

abusive supervision, focusing on major findings across the literature. However, this review is not

intended to be an inclusive discussion of all published and unpublished studies.

Research on abusive supervision has mostly focused on outcomes at multiple levels

(Martinko et al., 2013; Tepper, 2007). Overall research has found that abusive supervision is

related to undesirable employee outcomes, such as perceptions of injustice (Tepper, 2000),

decreased job satisfaction (Lin et al., 2013), decreased organizational commitment (Tepper et al.,

2008), psychological distress (Harvey et al., 2007), deviance (Mitchell & Ambrose, 2007;

Tepper et al., 2008), as well as low levels of OCBs (Zellars et al., 2002) and job performance

(Harris et al., 2007). A cross-over effect of abusive supervision is that it also has a negative

impact on employees’ well-being outside of the workplace. For example, research has shown

that abusive supervision is related to work-to-family conflict (Carlson, Ferguson, Hunter, &

Whitten, 2012), less family satisfaction (Carlson, Ferguson, Perrewé, & Whitten, 2011), and

family undermining (Wu, Kwong Kwan, Liu, & Resick, 2012). At the team level, abusive

supervision is negatively associated with team creativity (Liu et al., 2012) and team proactive

behavior (Rousseau & Aube, 2018). At the organization level, abusive supervision is related to

more deviance behavior toward the organization (Detert, Treviño, Burris, & Andiappan, 2007;

Mitchell & Ambrose, 2007) and economic cost (Tepper et al., 2006).

Research also has identified antecedents of abusive supervision at multiple levels (Zhang

& Bednall, 2016). At the subordinate level, abusive supervision is related to subordinate

personality (Brees, 2012), core self-evaluation (Wu & Hu, 2009), hostile attribution bias (Brees,

2012), and poor job performance (Walter et al., 2015). At the supervisor level, abusive

supervision is related to leaders’ previous experience with abusive supervision (Taylor et al.,

2019) and family aggression (Garcia et al., 2014). Lastly, at the team level, abusive supervision

is related to a hostile climate (Mawritz et al., 2014) and unethical climate (Taylor, 2004).

2.2 Leader Personality and Abusive Supervision

To date, a literature review indicates that the abusive supervision research on personality

has been mostly from the subordinate perspective. Defined as a subordinate’s subjective

assessment, abusive supervision can be colored by the subordinate’s personality (Brees,

Martinko, & Harvey, 2016; Tepper, 2007). Primary studies have examined how subordinates

with different personalities view abusive supervision differently. For example, research has

indicated that perceived abusive supervision was positively related to neuroticism and negatively

related to conscientiousness (Wang, Harms, & Mackey, 2015), and positively related to negative

affectivity and trait anger (Brees et al., 2016). Researchers have also has examined how

subordinate personality moderates the relationship between abusive supervision and outcomes.

In one example, Nandkeolyar, Shaffer, Li, Ekkirala, and Bagger (2014) found that the

relationship between abusive supervision and job performance was weaker when employees

were high in conscientiousness. A meta-analysis on abusive supervision indicates that most

studies that examined personality have focused on the Big Five, positive affect and negative

affect, and concluded that personality variables have weak to moderate associations with abusive

supervision (Mackey et al., 2017).

Surprisingly, only a few studies have examined how leader personality has an impact on

abusive supervision, and this represents an understudied area (Zhang & Bednall, 2016).

Although it is interesting to see how the personality of subordinates colors their perceptions of

abusive supervision, it is important to study how the personality of supervisors is related to their

abusive supervision behaviors because supervisors are the perpetrators. The relationship between

leader personality variables and abusive supervision helps answer why some leaders actively

engage in abusive supervision behaviors while others do not. Results from a limited number of

studies have examined leader personality variables including the Big Five, the dark triad,

positive and negative affect, and HEXACO (honesty-humility, emotionality, extraversion,

agreeableness, conscientiousness, and openness to experience) personality. They indicated that

abusive supervision is related to supervisor negative affect (Pan & Lin, 2018), Machiavellianism

(Wisse & Sleebos, 2016; Kiazad, Restubog, Zagenczyk, Kiewitz, & Tang, 2010), narcissism

(Waldman, Wang, Hannah, Owens, & Balthazard, 2018), conscientiousness in the Big Five

(marginally significant in correlation analysis, Camps, Stouten, & Euwema, 2016), and

agreeableness and honesty-humility in the HEXACO personality framework (Breevaart & de

Vries, 2017). McGinnis (2010) examined the relationship between MBTI personality and

abusive supervision but did not find any relationship between them. In addition, one study also

examined and supported the moderator roles of neuroticism, conscientiousness, and

agreeableness between supervisor role overload and abusive supervision via frustration (Eissa &

Lester, 2017).

However, with few existing studies on leader personality, we cannot be confident in

drawing overarching conclusions from the results. More research is needed to examine how

leader personality traits, both broadly and narrowly defined traits, are associated with abusive

supervision and how these relationships are moderated by situational factors.

2.2.1 Two Approaches to Examining Personality

The Big Five Model. Researchers have recognized and appreciated the important role of

personality in explaining individual behaviors. As an important aspect of individual differences,

personality is usually stable overall time and across situations (Hough, Oswald, & Ock, 2015).

Among different personality theories, the Big Five model has dominated research and applications

(Hough et al., 2015). A search of “Big Five” in Google Scholar as of March 2019 shows 4.4 million

results which include a large number of highly cited meta-analytical studies, such as personality

and job performance (Barrick & Mount, 1991), personality and leadership (Bono & Judge, 2004),

personality and entrepreneurial status (Zhao & Seibert, 2006), personality and job satisfaction

(Judge, Heller, & Mount, 2002). Although some researchers are concerned with the precise

meaning of the five personality factors, it is widely agreed upon which traits define each factor

(Barrick & Mount, 1991).

The first dimension is extraversion which is associated with traits such as sociability,

gregariousness, assertiveness, talkativeness, and high energy. The second dimension is

neuroticism or emotional stability, which is associated with anxiety, depression, and anger. The

third dimension is agreeableness, which indicates a tendency to be courteous, flexible, trusting,

cooperative, and tolerant. The fourth dimension is conscientiousness, which refers to being

dependable, responsible, hard-working, and achievement-oriented. The fifth dimension is

openness to experience, which is associated with a tendency to be imaginative, cultured, curious,

and intelligent (Barrick & Mount, 1991). Although there is no uniform agreement among

researchers on this broad and inclusive framework of personality, one advantage of using the Big

Five framework is that it enables the ability to refer and contribute to the cumulative results across

studies.

In general, research has supported the relationship between the Big Five and leadership

behaviors. For example, the Big Five traits are associated with transformational leadership and

transactional leadership, with extraversion as the strongest and most consistent predictor of

transformational leadership (Judge & Bono, 2004). For ethical leadership, conscientiousness and

agreeableness are significant predictors because these two traits are associated with being

responsible and caring (Kalshoven et al., 2011). For servant leadership, leader agreeableness is

positively associated with followers’ ratings of servant behaviors (Washington et al., 2006). A

comprehensive meta-analysis on LMX has indicated that leaders high in agreeableness and

extraversion tend to develop high-quality relationships with followers (Dulebohn, Bommer,

Liden, Brouer, & Ferris, 2012). Overall, these relationships are small to medium in magnitude.

However, only a few studies have examined the relationship between Big Five

personality dimensions of supervisors and abusive supervision, and as a dominant personality

framework, the Big Five deserves more attention to contribute to cumulative understanding. The

existing studies on the Big Five and abusive supervision provide limited and confusing results.

For example, research has supported that the neuroticism and agreeableness dimensions appear

to be particularly associated with aggressive behaviors (Costa, McCrae, & Dembroski, 1989;

Gleason, Jensen-Campbell, & Richardson, 2004; Graziano, Jensen-Campbell, & Hair, 1996;

Miller, Lynam, & Leukefeld, 2003; Suls, Martin, & David, 1998). However, using the Big Five,

Camps and his colleagues (Camps et al., 2016) found only a marginally significant correlation

between consciousness and abusive supervision. This is contrary to expectations, especially since

the results did not indicate a significant relationship between neuroticism, agreeableness and

abusive supervision. It would be interesting to explore whether the Big Five are useful in

predicting abusive supervision behaviors. The results from such studies would be beneficial to

both the research and practice.

Narrowly Defined Personality Traits. As personality research has progressed, researchers

have pointed out that the Big Five is not comprehensive, indicating that some important constructs

such as those related to honesty and interpersonal interaction are missing from this framework

(Hough et al., 2015). In addition, researchers have noticed that the Big Five only have small to

moderate predictive validity in outcomes (e.g., Bono & Judge, 2004). In response to such criticisms

for the Big Five, researchers have begun to pay attention to more narrowly defined personality

variables such as positive and negative affect, the dark triad, and trait anger with the hope of better

understanding the relationship between personality and important life and work outcomes.

Research using these personality variables has yielded fruitful results. For example,

Bettencourt, Talley, Benjamin, and Valentine (2006) examined how narrowly defined personality

traits, such as trait aggression, and trait irritability, are associated with aggressive behaviors, and

found moderate to strong relationships, supporting the predictive validity of these personality traits.

Hershcovis, et al. (2007) conducted a meta-analysis on the predictors of workplace aggression and

found out that individual personality including negative affectivity and trait anger have moderate

relationships with both individual and organization targeted aggressive behaviors. In addition,

negative affectivity and trait anger generally have stronger relationships with aggression than

situational factors such as injustice, job dissatisfaction, interpersonal conflict, situational

constraints, and poor leadership. In a meta-analysis, O’Boyle and his colleagues (O’Boyle, Forsyth,

Banks, & McDaniel, 2012) found that across studies Machiavellianism and psychopathy are

negatively associated with job performance, and the three components of the dark triad are all

associated with deviance behaviors. In sum, empirical studies have supported the predictive

validity of these narrowly defined personality traits in explaining outcomes.

Unfortunately, existing studies have ignored some narrowly defined yet important

personality variables, such as trait aggressiveness, and the dark triad. Results from meta-analysis

have supported the predictive power of narrowly defined personality variables (Judge, Rodell,

Klinger, Simon, & Crawford, 2013), as well as the relationship between these dark personality

variables and aggressive behaviors in general (Bettencourt et al., 2006). Research indicates that

some personality variables, such as trait aggressiveness and trait irritability have strong

relationships with aggressive behavior across conditions, and others have moderate relationships

with aggressive behavior under certain conditions (Bettencourt et al., 2006). Hershcovis et al.

(2007) found that trait anger and negative affectivity have moderate relationships with workplace

aggression, and these effects are stronger than most of the situational antecedents.

Therefore, it would be interesting to examine whether these narrowly defined personality

variables have high predictive validity for abusive supervision. I expect that trait aggressiveness

and the dark triad are predictive of abusive supervision, which is one type of aggressive and

hostile behavior characterized by nonphysical and a downward direction in the workplace.

2.2.2 Trait Activation Theory and Situational Factors

Although personality can explain behaviors, it also interacts with situations. Interactionist

psychology acknowledges that individuals can behave similarly across situations, and situations

can cause different people to behave in a similar way (Tett & Guterman, 2000). To explain this

long-standing debate regarding traits and situations as sources of behavioral variance, Tett and

Guterman (2000) proposed trait activation theory. They argued that the principle of trait activation

reconciles the trait-situation relationship by holding that “the behavioral expression of a trait

requires arousal of that trait by trait-relevant situational cues.” They further explained that this

theory offers a link to classic behaviorism (i.e., stimulus-response theory) by framing traits as

differential response tendencies. To incorporate the role of situation in explaining behaviors, they

defined personality traits as “intraindividual consistencies and interindividual uniquenesses in

propensities to behave in identifiable ways in light of situational demands” (p. 398). An example

they discussed is the relationship between trait aggression and aggressive behaviors. People high

in aggression do not always behave aggressively, they exhibit aggressive behaviors only in certain

situations. With aggression-inducing stimuli, people high in aggression will show a quicker and

stronger response or greater sensitivity to weak situational cues. This indicates that personality

expression in behavior varies by situation type, and trait activation is a process underlying trait

expression. This theory is in line with interactionism’s perspective that the expressions of

personality traits require trait-relevant situations (Kenrick & Funder, 1988).

One testable hypothesis based on the trait activation theory is “behavioral predictions based

on trait measures should improve with knowledge of situation trait relevance” (Tett & Guterman,

2000). Researchers have tested this hypothesis and have provided general support for this theory.

For example, Tett and Burnett (2003) proposed a theoretical model for a relationship between

personality-job performance based on trait activation theory that calls for the consideration of

situational factors. This model has received empirical support, such that extraversion may better

predict job performance in jobs requiring social skills (e.g., Judge & Zapata, 2015). A meta-

analysis on the relationship between personality and aggressive behavior indicated that some

personality variables such as trait anger and Type A personality better predict aggressive behaviors

in the provoking condition, such as stressful actions or situations than the neutral condition

(Bettencourt et al., 2016).

In the field of leadership, researchers have also been aware of the importance of

situational factors when examining the role of personality. Specifically, situational factors refer

to “aspects of the social context that are perceived by people and are largely influenced by

other members of the organization” (Hershcovis et al., 2007). Judge and his colleagues (Judge,

Bono, Ilies, & Gerhardt, 2002) called future research to focus on the many situational factors that

may moderate the validity of personality in predicting leadership; their proposal received support

from empirical research. For example, De Hoogh, Den Hartog, and Koopman (2005) examined

how the perceived dynamic work environment moderated the relationship between the Big Five

and charismatic and transactional leadership. They found that perceived dynamic work

environment moderated the relationship between all five personality factors except extraversion

and the leadership forms. In a study of military leaders and their supervisors, Ng, Ang, and Chan

(2008) found that job demands and job autonomy moderated the relationship between leader

neuroticism, extraversion, conscientiousness, and leader effectiveness through leadership self-

efficacy. From the employee perspective, Greenbaum, Hill, Mawritz, and Quade (2017) studied

the relationship between employee Machiavellianism and unethical behavior and supported that

abusive supervision was a trait activator for Machiavellianism.

In summary, the trait activation theory has received significant empirical support that

warrants integrating this theory in the study of abusive supervision. However, the existing

studies have failed to sufficiently account for context factors as moderators for the relationship

between supervisor personality and abusive supervision as trait activation theory has suggested.

Until now, researchers have only examined how employee organization-based self-esteem

(Kiazad et al., 2010), leader-member exchange (LMX) (Pan & Lin, 2018), and supervisor’s

perceived position power (Wisse & Sleebos, 2016) moderate the relationship between

personality variables and abusive supervision. However, more situational factors need to be

examined.

As proposed by Tett and Burnett (2003), trait-relevant cues in the workplace can be

multilevel, including organizational, social and task level cues. To be specific, organizational

level factors can include organizational climate, culture, structure. Social factors capture trait-

relevant cues that are embedded in interaction with others. Examples of these are needs and

expectations from supervisors and peers regarding effort and communication, and related social

behaviors. At the task level, situational factors stem from the nature of the work itself and

include day-to-day tasks, responsibilities, and procedures of the job. Examining the interaction

between leader personality and trait-relevant cues in explaining abusive supervision could

provide new insights into the literature.

2.3 Abusive Supervision and Cultural Values

With the surge of research on how cultural values impact human behaviors (e.g.,

Hofstede, 1980a), leadership scholars began to study leadership from a cross-cultural perspective

(e.g., Jung, Bass, & Sosik, 1995; Resick, Hanges, Dickson, & Mitchelson, 2006; Walumbwa,

Lawler, & Avolio, 2007). Hofstede’s seminal book on cultural dimensions (1980b) provides a

useful framework to broaden our understanding of how leadership works cross-culturally.

Leadership scholars have shown great interest in examining how cultural values influence the

effectiveness of different leadership forms. Leadership researchers have examined how cultural

values, especially individualism-collectivisms and power distance orientation, have an impact on

leadership behaviors, such as transformational leadership (e.g., Dulebohn, Wu, Liao, & Hoch,

2017; Kirkman, Chen, Farh, Chen, & Lowe, 2009), servant leadership (e.g., Hale & Fields, 2007;

Schaubroeck, Lam, & Peng, 2011), and abusive supervision (Vogel et al., 2015; Wang, Mao,

Wu, & Liu, 2012).

Many researchers have called for future research on abusive supervision from a cultural

perspective (Mackey et al., 2017; Martinko et al., 2013). Because abusive supervision was

proposed in the U.S., many initial studies were conducted in Western cultures. Similarly, even

after Tepper’s (2007) call for cross-cultural studies, a meta-analysis indicated that only a few

studies incorporated national culture in studies of abusive supervision (Mackey et al., 2017).

Some of these studies simply noted the potential influence of cultural differences in their

introductions and discussions, but they did not further explore the potential impact of these

differences empirically (e.g., Jian, Kwan, Qiu, Liu, & Yim, 2012; Lee, Yun, & Srivastava, 2013;

Rafferty & Restubog, 2011).

Among the varied cultural values or dimensions, one particularly relevant cultural

dimension is power distance, which captures “The extent to which the less powerful members of

institutions and organizations within a country expect and accept that power is distributed

unequally” (Hofstede, 2001, p. 98). To distinguish between power distance at country and

individual levels, I use the term power distance orientation to indicate an individual-level

construct following practices used by other researchers (e.g., Kirkman et al., 2009; Lian et al.,

2012). Empirically, Lian et al. (2012) found that how individual power distance orientation

moderates the relationship between abusive supervision and its outcomes depends on the nature

of outcomes. Subordinates with higher power distance orientation have been found to be more

likely to show deviant behaviors and less likely to have injustice perceptions with abusive

superiors than subordinates with lower power distance orientation. However, Hon and Lu (2016)

found that for employees with low power distance orientation, they were more likely to exhibit

abusive behaviors with abusive supervisors. These two studies found contradictory results

regarding whether power distance orientation strengthens or weakens the relationship between

abusive supervision and employee deviant behaviors.

In addition, Vogel and his colleagues (Vogel et al., 2015) examined whether abusive

supervision behaviors are perceived similarly by subordinates across different cultures. They

found out that the negative effects of abusive supervision were stronger for subordinates within

the Anglo than the Confucian Asian culture and subordinates from Anglo culture perceived

abusive supervision as less fair. These differences can be explained by subordinates’ power

distance orientation in these cultures. In another study, with a Chinese sample, researchers found

that abusive supervision had a stronger negative relationship with interactional justice for

employees with low power distance orientation than for employees with high power distance

orientation (Wang et al., 2012). Similarly, Lin et al.’s (2013) findings supported the moderating

role of power distance with two Chinese samples. They found that the negative relationships of

abusive supervision with employee psychological health and job satisfaction were weaker for

employees with higher power distance orientation. Besides power distance, researchers have

examined other cultural dimensions such as traditionalism (Liu, Kwong Kwan, Wu, & Wu,

2010), achievement orientation, and benevolence (Kernan, Watson, Chen, & Kim, 2011). In

almost all these studies, cultural values were modeled as moderators to examine whether cultural

values influence the relationship between abusive supervision and its correlates.

However, because few abusive supervision studies have included cultural values,

researchers believed that “opportunity for future research to investigate the impact of cultural

differences on abusive supervision causes, perceptions, and reactions remains largely untapped”

(Martinko et al., 2013). A review of the literature indicates that more research needs to be done.

2.3.1 Implicit Leadership Theory and Cultural Values

Researchers have used implicit leadership theory to explain why cultural values may

influence the acceptance and effectiveness of leadership (Den Hartog et al., 1999; House,

Javidan, Hanges, & Dorfman, 2002). Implicit leadership theory argues that people have their

own ideas about the nature of leaders and leadership, and they have their own beliefs and

expectations about how leaders should behave in general (Eden & Leviathan, 1975). With a

leader prototype (i.e., a collection of characteristic traits or attributes) in mind, people match the

perceived attributes of potential leaders to their internal prototypes (Foti & Luch, 1992). The fit

between the perceived individual and the leadership prototype is associated with the likelihood

of perceiving that person as a leader (Offermann, Kennedy, & Wirtz, 1994; Foti & Luch, 1992).

Researchers have identified tyranny, including characteristics such as pushy, conceited,

dominant, and manipulative, as a negative prototype of implicit leadership theory (Epitropaki &

Martin, 2004; Offermann et al., 1994).

Research has suggested that people with different cultural orientations perceive and react

to authority differently (Kirkman et al., 2009). For example, individuals with high power

distance orientation accept the power differences between leaders and subordinates and believe

that people in leader positions deserve respect, trust, and deference, as well as accept

subordinates’ limitations in the decision-making process (Javidan, Dorfman, de Luque, & House,

2006; Kirkman et al., 2009). Therefore, it is possible that people with high power distance

orientation find abusive supervision more acceptable and respond less intensively (Tepper,

2007).

Consistent with Tepper’s (2007) expectation, empirical studies have found that people

with high power distance orientation tend to respond less intensively than people with low power

distance (Lian et al., 2012; Vogel et al., 2015; Wang et al., 2012). One exception is interpersonal

deviant behavior. Lian et al. (2012) found that based on social learning theory, when power

distance orientation is high, abusive supervision is related to more deviant behaviors via the

perception of the likelihood of rewards. This does not indicate that employees with high power

distance react intensively with abusive supervision, rather it is because people with high power

distance tend to treat their leaders as role models and are more likely to mimic their leaders’

behaviors. However, it is not clear whether this unexpected pattern is stable or not considering

opposite conclusions from another study conducted by Hon and Lu (2016). They found that

employees with lower power distance orientations are more likely to exhibit abusive behaviors

when they experience abusive supervision. It is also not clear whether this unexpected pattern for

deviant behaviors generalizes to other behaviors such as job performance, OCB, and creativity.

In my model, I examine both attitudinal outcomes, such as trust, psychological safety, and

behavioral outcomes such as job performance, OCB, creativity, and deviance.

2.3.2 Level of Analysis for Cultural Values

Hofstede initially developed his cultural framework to measure cultural values at the

country level (1980b). With numerous theoretical advancements in the field of cross-cultural

studies, a growing number of studies have argued that “country” may not be the most appropriate

unit of analysis for these studies (Fischer, 2009; Kirkman, Lowe, & Gibson, 2006; Taras, Steel,

Kirkman, 2016). Research has found that cultural values also vary significantly at the individual,

group, organizational, socioeconomic status, state, and religious levels within countries (Daniels

& Greguras, 2014; Dheer, Lenartowicz, Peterson, & Petrescu, 2014; Greenfield, 2014). In

addition, contrary to the static views of culture, dynamic views have produced research on

cultural frameshifting, which argues that in the global world individuals can dynamically

integrate elements from other cultures and dissociate from elements of their culture (e.g., Benet-

Martínez, Leu, Lee, & Morris, 2002; Hong, Morris, Chiu, & Benet-Martínez, 2000). With these

advancements, researchers have called for additional future research to study culture beyond the

national level (Gelfand, Aycan, Erez, & Leung, 2017).

In addition, it is important to conduct studies at more micro-levels to avoid the ecological

fallacy which refers to incorrectly generalizing results found at the group level to individuals that

belong to that group (Robinson, 1950). Relatedly, Hofstede (2001) cautioned that researchers

should not generalize results found at the individual level to the group level to avoid reverse

ecological fallacy. Besides the conceptual differences of relationships at different levels, the

reason to avoid the ecological fallacy is also that the relationship between two constructs can

vary at different levels. For example, Spector et al. (2001) found no relation between

collectivism and job satisfaction at the country level whereas Kirkman and Shapiro (2001) found

a positive relation between collectivism and job satisfaction at the individual level. Therefore, it

is important to consider the level of measurement and analysis when making theoretical

expectations and drawing inferences from results (Daniels & Greguras, 2014; Gelfand, Erez, &

Aycan, 2007; Kirkman et al., 2006).

In my model, I measure power distance orientation and conduct analysis at the individual

level and use scales that are specifically designed to measure individual cultural values (i.e.,

Dorfman & Howell, 1988). This practice is in line with most cross-cultural studies conducted in

the field of human resources, organizational behavior, and industrial psychology. For example,

Tsui, Nifadkar, and Ou (2007) found that among the studies they reviewed 84% investigated

cultural values at the individual level. In a meta-analysis, Tara, Kirkman, and Steel (2010) found

that 76% of the data points were at the individual level. In addition, Kirkman et al. (2006) in his

review highlighted the importance of direct measurement of cultural values at the individual

level rather than using country scores as proxies when the study is at the individual level. Most

importantly, the focus on the individual level can be employed to better answer my research

questions which examine how cultural values influence employee attitudes and behaviors in the

workplace at the employee level.

In addition, although some meta-analytical studies incorporated power distance

orientation as a moderator in the analysis for several outcomes, results cannot be fully

generalized to the individual level. In one study, Park, Hoobler, Wu, Liden, Hu, and Wilson

(2017) assigned cultural values to each sample based on the country where the sample was

drawn as a proxy, and then dichotomized the power distance values and conducted subgroup

analysis. Similarly, Zhang and Liao (2015) used geographic regions as a proxy for cultural

values and conducted subgroup analysis for samples from Asia and samples from North

America. Although this approach is appropriate for meta-analysis considering that this is one of

the few ways that they could assign cultural values to each sample, there are some concerns with

this practice. As Daniels and Greguras (2014) discussed, countries differ on variables other than

cultural values, such as language, economic development, government systems, etc. Therefore, it

is impossible to disentangle the influences of other factors in these cases. With some insights

from the meta-analysis, it is still important to conduct studies at the individual level to examine

the corresponding research questions.

2.3.3 Justice as A Mediator

Much of the existing cross-cultural research on abusive supervision has not addressed

potential mechanisms through which abusive supervision and cultural values relate to outcomes.

Little is known about why and how abusive supervision and individual cultural values affect

individual attitudes and behaviors within cultures. Mediators in such a moderated mediation

model may help explain why the interaction effects exist. Until now, researchers have only

examined the likelihood of rewards, turnover intention, and feelings of shame as mediators in

studies with cultural values as moderators. For example, Lian et al. (2012) examined the

likelihood of rewards as a mediator based on the social learning theory and found an indirect

positive relation of abusive supervision and interpersonal deviance through the likelihood of

rewards is stronger for individuals with higher power distance orientation. In another study,

Richard, Boncoeur, Chen, and Ford (2018) found that the indirect relationship between abusive

supervision and interpersonal aggression via turnover intentions was stronger for high power-

distance-oriented individuals when the HR support climate was perceived low. Daniels (2015)

studied the relationship between abusive supervision and in-role performance and OCB, and

examined feelings of shame as a mediator and power distance as the second-stage moderator

(i.e., moderator for the relationship between mediator and outcomes), and found that the indirect

effects at different levels of feelings of shame were only different for in-role performance but not

OCB. However, they did not study how power distance moderates the direct relationship

between abusive supervision and in-role performance, and OCB.

In response, I include interactional justice as a theory-based mediator to help explain why

abusive supervision and power distance orientation affect employee behaviors. Interactional

justice has been the primary mediator that explains how abusive supervision could have an

impact on outcomes (Aryee, Chen, Sun, & Debrah, 2007; Tepper, 2000; Vogel et al., 2015). This

responds to a call for future research to focus on the mediation mechanisms. The justice mediator

could help explain the underlying mechanisms of the influence of the interaction between

abusive supervision and power distance orientation on outcomes.

2.4 Abusive Supervision and Job Type

Scholars have dichotomized occupations in terms of white-collar and blue-collar

employees. Following the definitions from previous research, we define white-collar employees

as professional and semi-professional employees who have more job autonomy and more

challenging tasks, and blue-collar employees as those who perform physical work and have

relatively restricted career paths (Hu, Kaplan, & Dalal, 2010; Toppinen-Tanner, Kalimo, &

Mutanen, 2002). Research has also revealed the differences between white-collar and blue-collar

employees regarding their expectations and preferences in the workplace. For example, scholars

have indicated that compared with blue-collar employees, white-collar employees care more

about the intrinsic values of their jobs but care less about extrinsic values (Harris & Locke, 1974;

Locke, 1973; Weaver, 1975) and have different conceptualizations of job satisfaction facets (Hu,

Kaplan, & Dalal, 2010). More specifically, with a national sample from Wright, Bengtsson, and

Frankenberg (1994) discussed the differences in aspects of the physical work environment,

medical symptoms, psychological stress, job satisfaction, and life satisfaction between white-

collar and blue-collar employees. Other empirical studies using physiological methods have

indicated that organizational justice only has an independent impact on white-collar employees

but not blue-collar employees (Herr, Bosch, Loerbroks, et al., 2015; Herr, Bosch, van Vianen, et

al., 2015). Overall, research has supported that white-collar and blue-collar employees not only

differ in their job characteristics but also differ in their expectations and preferences.

Similar to the literature on other constructs in the organizational behavior field (e.g.,

organizational commitment, Riketta, 2002), the literature on abusive supervision has not paid

much attention to the influence of job type. Most studies on abusive supervision have relied on

white-collar samples to draw conclusions (e.g., Liu et al., 2012; Shoss et al., 2013; Vogel et al.,

2015). For the few studies that have used blue-collar employees as samples, they did not

examine the role of job type either (e.g., Bamberger & Bacharach, 2006; Haar, Fluiter, &

Brougham, 2016; Lin et al., 2013; Kluemper, Mossholder, Ispas, Bing, Iliescu, & Ilie, 2019).

Without discussing the role of job type as a boundary condition, researchers have implicitly

assumed that findings based on white-collar samples are generalizable to blue-collar employees.

This can be problematic and may limit our understanding of abusive supervision.

In order to deal with this concern, I include two categories of job type, white-collar and

blue-collar, as a moderator. I examine both how job type moderates the relationship between

abusive supervision and whether the mediation mechanisms are the same or not for white-collar

and blue-collar employees.

CHAPTER 3 MODEL AND HYPOTHESIS DEVELOPMENT

The purpose of this dissertation is to contribute to the literature on abusive supervision by

developing and testing a moderated mediation model. Overall, the model examines whether

leaders with certain personality traits are more likely to exhibit abusive supervision behaviors,

how cultural value and job type influence the abusive supervision and outcome relationship, and

how underlying mechanisms explain such relationships. As described in Chapter 3, I develop a

model that examines both antecedents and outcomes of abusive supervision. Specifically, this

model incorporates leader personality dimensions as antecedents to abusive supervision. Based

on trait activation theory, I propose that situational relevant factors moderate the leader

personality-abusive supervision linkage. For outcomes, I incorporate cultural dimensions as

proposed by Hofstede (1980b) and use justice theory (Bies & Moag, 1986) to explain the abusive

supervision-outcome relationship. I focus on how power distance orientation as a cultural value

moderates the relationship between abusive supervision and outcomes, as well as how the justice

mechanism mediates the relationship between abusive supervision and outcomes. To examine

the generalizability of research findings based on white-collar employees and to study the

relative importance of cultural values, I also examine job type as a moderator.

As presented in Figure 1, the first component in my model is leader personality that

includes agreeableness, neuroticism, trait aggressiveness, narcissism, Machiavellianism, and

psychopathy. These personality traits represent antecedents of abusive supervision. The second

component in my model is ethical climate, a hypothesized moderator for the relationship

between leader personality traits and abusive supervision. The third component is abusive

supervision, the key construct of interest in my dissertation. The fourth and fifth components are

power distance orientation and job type, hypothesized to moderate the relationship between

abusive supervision and employee outcomes. The sixth component is interactional justice, a

variable hypothesized to mediate the relationship between abusive supervision and outcomes.

The last component is employee outcomes, including job performance, OCB, creativity, and

deviance.

In this chapter, I describe each hypothesis based on my model. I first develop hypotheses

concerning how leader personality traits, including both broadly and narrowly defined

personality variables, are associated with abusive supervision. Based on trait activation theory, I

hypothesize that ethical climate moderates the above-discussed relationships. Next, I hypothesize

that power distance orientation and job type moderate the influence of abusive supervision on

employee outcomes and that the relationship between abusive supervision and outcomes are

mediated by interactional justice as an underlying mechanism. Finally, I hypothesize that power

distance orientation and job type moderate these mediation effects in this moderated mediation

model.

Figure 1. Conceptual model

This model contributes to the abusive supervision literature in three ways. First, my

review of the literature on abusive supervision in Chapter 2 indicates that extant research has

largely ignored why some leaders engage in abusive supervision. This model integrates both

individual (leader) personality traits and situational factors, based on trait activation theory to

explore this understudied question. I expect that leaders high on certain personality traits will

tend to exhibit abusive behaviors and some situational factors can strengthen/weaken such

positive relationships. Second, this model integrates individual cultural orientation as a boundary

condition and tests how it moderates the relationship between abusive supervision and outcomes

including job performance, OCB, creativity, and deviance. To investigate the influence of

cultural value, I integrate the justice mechanism to explain how abusive supervision and

individual cultural orientation interactively influence employee outcomes. Third, my proposed

model integrates job type as a boundary condition to examine potential differences between

white-collar and blue-collar employees regarding how abusive supervision influences employee

behaviors. The inclusion of job type as a moderator also helps test the relative influence of power

distance orientation.

3.1 Antecedents to Abusive Supervision

In this section, I describe the relationship between leader personality variables and

abusive supervision, as well as the moderation effects of ethical climate.

3.1.1 Leader Personality and Abusive Supervision

As discussed in Chapter 2, leader personality represents one group of understudied

antecedents in the abusive supervision literature in the past. Research has generally supported the

relationship between leader personality and leadership behaviors (e.g., Bono & Judge, 2004;

Dulebohn et al., 2012). Revealing the relationship between personality and abusive supervision

can help researchers gain a better understanding of what traits make a leader abusive. In addition,

researchers have also noted that the associations between widely defined personality variables,

represented by the Big Five, and leadership behaviors are usually weak. This has caused scholars

to suggest that future research should focus on more narrowly defined personality traits (Bono &

Judge, 2004). Research has also supported the better predictive validity of lower-order

personality traits in explaining some behaviors (Judge et al., 2013).

As presented in Figure 1, I examine both widely defined personality traits, including

neuroticism, agreeableness, and narrowly defined personality traits, including trait

aggressiveness, and the dark triad. These personality variables are antecedents to abusive

supervision as depicted in Figure 1.

Neuroticism and agreeableness. It is reasonable to believe that people have different

propensities to display aggressive behaviors (Tedeschi & Felson, 1994). Recent studies have

focused on personality traits rather than situational factors to explain why people engage in

aggressive behaviors (Bettencourt et al., 2006). Neuroticism and agreeableness in the five-factor

model (Costa & McCrae, 1992) appear to be particularly related to aggressive behaviors (Costa

et al., 1989; Gleason et al., 2004; Graziano et al., 1996; Miller et al., 2003; Suls et al., 1998).

Agreeableness is associated with the motives to maintain positive relationships with other people

(Gleason et al., 2004). The opposite of agreeableness is antagonism, which is associated with

hostility and irritability— “they need to oppose, to attack, or to punish others” (Costa et al.,

1989, p. 45). Antagonistic people tend to mistrust, lack concern for others, and may exclude

those who are disliked or inferior. Neuroticism is different from antagonism and is characterized

by a tendency to experience negative affectivity, psychological stress, and unstable emotions

(Costa et al., 1989). Although both agreeableness and neuroticism are related to aggression and

hostility, Costa et al. (1989) distinguished between them and stated that “whereas neurotic

hostility is exemplified by frequent and strong experiences of anger…antagonistic hostility is

exemplified by cynicism, callousness, and lack of cooperation” (p. 53). In the workplace, I

expect that leaders high in neuroticism, low in agreeableness, tend to display more abusive

supervision behaviors.

Trait aggressiveness. Besides widely defined traits, researchers also have studied a

variety of specific personality traits without reference to these major dimensions in the Big Five.

Research has found that trait aggressiveness is an important antecedent to aggressive behaviors

and has moderate to strong relationships with aggressive behaviors in general (Bettencourt et al.,

2006). Trait aggressiveness refers to one’s propensity to engage in physical and verbal

aggression, to hold hostile cognitions, and to express anger (Buss & Perry, 1992). Trait

aggression includes four dimensions: Physical aggression, verbal aggression, anger, and hostility.

In the workplace, researchers have found that trait anger, a dimension of trait aggressiveness,

shows a moderate to strong relationship with interpersonal targeted aggression (Hershcovis et al.,

2007). Kant, Skogstad, Torsheim, and Einarsen (2013) warned people to beware of angry

leaders. They found that leaders high in trait anger are more likely to display petty tyranny,

which refers to a leader’s use of power and authority oppressively, capriciously, and vindictively

(Ashforth, 1997). Similarly, researchers have found that trait aggressiveness is related to

workplace interpersonal deviance and that it interacts with interactional justice and race in

explaining deviance (Aquino, Galperin, & Bennett, 2004). In the organizational context, it is

expected that leaders high in trait aggressiveness are more likely to use abusive supervision

behavior, one of the nonphysical aggressive behaviors, as a way to express anger.

Dark triad. Besides focusing on the personality traits that are related to general

aggressive behaviors, three other aversive personality traits also deserve attention. Among the

socially aversive personalities, the dark triad, including Machiavellianism, narcissism, and

psychopathy, has attracted the most empirical attention (Paulhus & Williams, 2002). These three

personality traits all have a long history in the clinical and philosophical literature and migrated

to the management literature with the publications of classic questionnaires in the 1970s and

1980s (Furnham, Richards, & Paulhus, 2013).

First, the Machiavellian personality is defined by three sets of interrelated values: “an

avowed belief in the effectiveness of manipulative tactics in dealing with other people, a cynical

view of human nature, and a moral outlook that puts expediency above principle” (O’Boyle et

al., 2012). People high in Machiavellian characteristics usually hold a negative view of people

and are more likely to make ethically suspect choices such as cheating, lying, and betraying

others, but they do not engage in extremely negative forms of antisocial behaviors such as

violent crimes (Jones & Paulhus, 2009; Kish-Gephart, Harrison, & Trevino, 2010). Second,

narcissism is characterized by extreme self-aggrandizement and is not necessarily a bad thing.

Most people possess some level of narcissism that colors their perceptions and behaviors

(Rhodewalt & Peterson, 2009). Different from healthy self-respect and confidence, narcissists

exaggerate their achievements, block criticism, and refuse to compromise (Campbell, 1999;

Resick, Whitman, Weingarden, & Hiller, 2009). They also appear arrogant, aggressive, and less

likable (Buffardi & Campbell, 2008). Research also indicates that with the perception of ego

threat, narcissists are likely to respond aggressively (Bushman, Baumeister, Thomaes, Ryu,

Begeer, & West, 2009). Third, people with psychopathy are characterized by a lack of empathy

and concern for other people and social norms, impulsivity, emotional coldness, and engagement

in antisocial behaviors including criminal activities to achieve their ends (Hare & Neumann,

2009). Although all aversive, these three personality traits are overlapping but distinct constructs.

The correlations among these three traits are usually positive and from moderate to strong, but

they are differentially correlated with other constructs, such as the Big Five, and cognitive ability

(Furnham et al., 2013; O’Boyle et al., 2012; Paulhus & Williams, 2002).

Researchers have identified five major outcome domains for the dark triad, one of which

is workplace behavior. The dark triad is often associated with the notions of “toxic leadership”

and “bad bosses” (Furnham et al., 2013). Research has indicated that psychopathy is positively

related to passive leadership behaviors and is negatively related to consideration (Westerlaken &

Woods, 2013). In addition, leaders high in Machiavellianism and psychopathy have detrimental

effects on subordinates' career satisfaction and job satisfaction (Volmer, Koch, & Goritz, 2016).

From a theoretical perspective, researchers have explained how narcissistic leaders’ cognitive

processes can contribute to abusive supervision (Keller Hansbrough & Jones, 2014). A recent

meta-analysis indicates that the three traits in the dark triad are all associated with

counterproductive work behaviors (O’Boyle et al., 2012). Therefore, I expect a positive

relationship between the dark triad and abusive supervision.

Based on the above, I hypothesize the relationship between leader personality variables

and abusive supervision:

Hypothesis 1: Abusive supervision is negatively associated with leader (a) agreeableness,

and positively associated with leader (b) neuroticism, (c) trait aggressiveness, (d) narcissism, (e)

Machiavellianism, and (f) psychopathy.

3.1.2 Trait-Relevant Situational Factor as A Moderator

Tett and Burnett (2003) proposed trait activation theory to explain the relationship

between personality and situation in explaining behaviors. They argued that the expressions of

personality traits require trait-relevant situations. In the model presented in Figure 1, I include

one trait-relevant situation factor, ethical climate, as a moderator for the relationship between

these “negative” personality traits and abusive behaviors. Based on the typology proposed by

Howell, Dorfman, and Kerr (1986), I hypothesize that this moderator works as a neutralizer.

Ethical climate. I conceptualize the ethical climate at the organization level consistent

with its conceptualization and published studies (e.g., Martin & Cullen, 2006; Victor & Cullen,

1988). The study on work climate has more than half a century of history and has demonstrated

that work climate exerts an influence on people’s work in the organization and the organization

as a whole (Kuenzi & Schminke, 2009). Schneider and Reichers (1983) defined work climates as

a set of shared perceptions regarding the policies, practices, and procedures that an organization

or group rewards, supports, and expects. According to Victor and Cullen (1988), an ethical work

climate encompasses the perceptions that help to answer “What should I do?” and reflects the

normative patterns perceived by members in the organization with some degree of consensus. In

their seminal article, they contended that organizations develop different ethical climates that in

turn influence employees’ moral behaviors beyond individual characteristics.

Researchers have identified five facets of ethical climates: Caring, law and code, rules,

instrumental, and independence (Victor & Cullen, 1988). Among the five facets, caring is the

one that characterizes benevolence and interpersonal relationships. Specifically, a caring ethical

climate is an affective climate that is concerned with interpersonal and social relations among

employees and subsumes four dimensions such as participation, cooperation, warmth, and social

rewards (Ostroff, 1993). The affective climate is one type of ambient stimulus that is available to

all group members and can shape their behaviors (Hackman, 1992). With a caring climate,

individuals perceive that decisions should be made based on the consideration of other people’s

well-being (Martin & Cullen, 2006).

Ethical climate can be considered as a trait-relevant situational factor for these above-

discussed personality traits, including agreeableness, neuroticism, trait aggressiveness, and the

dark triad. Results from empirical studies have supported that ethical climate has an impact on

employees’ attitudes and behaviors. Meta-analysis has supported the positive influence of caring

ethical climate on employee satisfaction, commitment, and well-being (Martin & Cullen, 2006).

Through ethical climate, employees assess and diagnose their working environments by

understanding what they should do and identifying what are unethical issues within their

organizations (Cullen, Parboteeah, & Victor, 2003). In addition, Wang and Hsieh (2014) found

that with a perception of low ethical climate, the relationship between perceived psychological

contract breach and acquiescent silence is stronger.

The positive effects of ethical climate can be understood from the social information

processing theory (Salancik & Pfeffer, 1978). Individuals look around for cues regarding

behavioral expectations and then adjust their behaviors accordingly. An unethical climate signals

to supervisors that treating subordinates with less caring is acceptable and is less likely to be

punished. Based on trait activation theory (Tett & Burnett, 2000), I expect that a lower level of

ethical climate serves as a provocation condition that signals the existence and acceptance of

hostile behaviors, and to some extent, it strengthens the association between these negative

personality traits and abusive supervision. Therefore, I hypothesize:

Hypothesis 2: Ethical climate moderates the relationship between abusive supervision and

leader (a) agreeableness, (b) neuroticism, (c) trait aggressiveness, (d) narcissism, (e)

Machiavellianism, and (f) psychopathy, such as these relationships are stronger when the ethical

climate is low.

3.2. Outcomes to Abusive Supervision

In this section, I describe the relationship between abusive supervision and employee

outcomes, as well as their moderators and mediator as presented in Figure 1. First, I expect that

individual power distance orientation and job type moderated the relationship between abusive

supervision and outcomes. Next, I expect the indirect effects of abusive supervision on outcomes

via interactional justice. Finally, I expect moderated mediation relationships based on the above-

discussed logic with power distance orientation and job type as moderators.

3.2.1 Power Distance Orientation as A Moderator

In this section, I describe how power distance orientation moderates the relationship

between abusive supervision and interactional justice, job performance, OCB, creativity, and

deviance.

Interactional justice. Researchers have identified interactional justice as the third type of

justice after distributive justice and procedural justice (Cropanzano, Prehar, & Chen, 2002).

Interactional justice refers to the quality of interpersonal interaction and is most likely to occur

when supervisors treat employees with interpersonal respect and dignity and necessary

explanations (Bies & Moag, 1986; Bies, 1989). As organization representatives, leaders largely

determine employees’ perception of interactional justice (Cohen-Charash & Spector, 2001).

Compared with distributive justice and procedural justice, interactional justice is especially

predictive of employee reactions to supervisors and to the immediate work environment

(Malatesta & Byrne, 1997; Masterson, Lewis, Goldman, & Taylor, 2000). Tepper (2000)

explained the negative effects of abusive supervision on employee attitudes and behaviors based

on the justice theory. He argued that abusive supervision is perceived by employees as

interpersonally unfair, and such perception, in turn, affects employees’ job satisfaction,

commitment, and turnover decision. This association has been supported by empirical studies,

indicating that abusive supervision negatively affects the perception of interactional justice

(Aryee et al., 2007; Rafferty & Restubog, 2011; Tepper, 2000).

However, this negative relationship between abusive supervision and interactional justice

is moderated by individual power distance orientation. Research has demonstrated that for

individuals with low power distance orientation, the relationship between abusive supervision

and interactional justice is stronger (Lian et al., 2012; Vogel et al., 2015; Wang et al., 2012). This

is because justice perception is inherently based on norms and values (Cropanzano, Byrne,

Bobocel, & Rupp, 2001) which are associated with prevailing cultural standards. It has been

argued that although concerns about justice are universal, justice standards can be highly

particularistic (Greenberg, 2001). Specifically, what people believe to be fair depends on their

repeated exposure to validated opinions regarding what is considered to be fair, and such

repeated exposure shapes their expectations of fairness that serve as their basis of assessment

(Greenberg, 2001). This explains that people may have different fairness perceptions because

they have different values and norms. Among values and norms, power distance orientation is a

relevant one (Hofstede, 1980b). People with high power distance orientation may find abusive

supervision more acceptable because they believe that people in authority are superior and

deserve compliance from subordinates, whereas people with low power distance may find

abusive supervision unfair because they think they should be treated with respect and dignity

regardless of the relative status in the organization. Therefore, I hypothesize:

Hypothesis 3: Power distance orientation moderates the negative relationship between

abusive supervision and interactional justice, such that this relationship is stronger when power

distance orientation is low.

Job performance. Research has found that abusive supervision negatively affects job

performance (Harris et al., 2007; Shoss et al., 2013; Xu, Huang, Lam, & Miao, 2012).

Researchers have explained this negative relationship using social exchange theory. In other

words, both supervisors and subordinates bring resources to the workplace for exchange. When

subordinates have a poor relationship with supervisors, supervisors may not provide them with

valuable resources and support, making them not willing to fully contribute to the organization.

In addition, based on the conservation of resources theory, subordinates may perceive a threat in

terms of resource loss and low anticipated return of effort with abusive supervision. As a result,

they withdraw their efforts from work (Harris et al., 2007; Xu et al., 2012). In addition, this

negative relationship varies with power distance orientation. For subordinates with high power

distance orientation, they may not associate abusive supervision with the potential loss of

resources or consider abusive supervision as something that indicates a poor relationship.

Therefore, they may not restrain their efforts in the work as much as subordinates with low

power distance orientation do. Therefore, I hypothesize:

Hypothesis 4: Power distance orientation moderates the relationship between abusive

supervision and job performance, such that this negative relationship is weaker when power

distance orientation is high.

OCB. Different from job performance, OCB refers to individual behaviors that go beyond

role descriptions but benefit organizational operations (Organ & Ryan, 1995). Research indicates

that abusive supervision also decreases OCB (Aryee et al., 2007; Zellars et al., 2002). Research

has found that employees are more likely to express their attitudes in extra-role behaviors which

they have greater discretion than in-role behaviors (Organ, 1977; Smith, Organ, & Near, 1983).

When subordinates perceive their supervisors as less supportive, they are likely to withhold their

engagement in OCB. Power distance orientation may moderate this negative relationship. I

expect that abusive supervision influences OCB for employees with low power distance

orientation to a great extent. Besides the values associated with power distance, research has

found that people from different cultures have different definitions of OCB. Lam, Hui, and Law

(1999) found that participants from Hong Kong and Japan, with cultures of high power distance,

were more likely to define some categories of OCB as their required job roles than participants

from U.S. and Australia. Therefore, abusive supervision is likely to have a smaller influence on

OCB for people with high power distance orientation. Therefore, I hypothesize:

Hypothesis 5: Power distance orientation moderates the relationship between abusive

supervision and OCB, such that this negative relationship is weaker when power distance

orientation is high.

Creativity. Employee creativity refers to the generation of novel and useful ideas and is

often the starting point for organizational innovation (Zhou & George, 2001). Among the

influential factors of creativity, leaders have been proposed to be an important situational factor

that can cultivate or hinder employee creativity (e.g., George, 2007; Gong, Huang, & Farh, 2009;

Oldham & Cummings, 1996). Research has demonstrated that abusive supervision, as a

destructive leadership style, can hinder employee creativity (e.g., Liu et al., 2012; Zhang, Kwan,

Zhang, & Wu, 2014). Further, this negative relationship may be moderated by power distance

orientation. Researchers have had discussions on how culture can have an impact on creativity

and innovation. For example, Ahmed (1998) summarized that freedom and risk-taking can

promote employee creativity. However, for employees with high power distance orientation, they

tend to behave submissively and are more fearful of their leaders. As a result, they tend to

perceive that they do not have much latitude in executing their own work and are less likely to

take risks such as expressing novel ideas at work. In one empirical study, Farmer, Tierney, and

Kung-McIntyre (2003) found that being exposed to U.S. culture (low power distance) could

increase the creativity of Taiwanese employees because the educational system in the U.S. tends

to stimulate personal expression rather than mimetic learning (Gardner & Hatch, 1989).

Therefore, I hypothesize:

Hypothesis 6: Power distance orientation moderates the relationship between abusive

supervision and creativity, such that this negative relationship is stronger when power distance

orientation is high.

Deviance. Research indicates that abusive supervision is positively associated with

employee deviant behaviors (e.g., Michell & Ambrose, 2007; Tepper, Carr, Breaux, Geider, Hu,

& Hua, 2009). Bennett and Robinson (2003) found that negative work experiences such as

perceptions of frustration and injustice are primary antecedents of deviance. With abusive

supervision, subordinates are likely to have a feeling of frustration and injustice perceptions. As

a result, they may retaliate against their supervisors with destructive behaviors such as deviance.

However, the limited empirical studies have indicated contradictory results regarding how power

distance orientation moderates the relationship between abusive supervision and deviance. Some

researchers found that this positive relationship between abusive supervision and deviance is

stronger for people with low power distance orientation (Hon & Lu, 2016), whereas other

researchers argued that this positive relationship between abusive supervision and deviance is

stronger for people with high power distance orientation based on social learning theory (Lian et

al., 2012).

Hofstede (2001) used “fear of disagreement” in measuring power distance at the country

level. This indicates that people in high power distance countries consider their supervisors as

more fearful. When subordinates are treated with an injustice like abusive supervision, they are

fearful and try to avoid subsequent actions that may trigger future abuse (Kiewitz, Restubog,

Shoss, Garcia, & Tang, 2016; Kish-Gephart, Detert, Treviño, & Edmondson, 2009). In addition,

related research on traditionality, a cultural value correlated with power distance orientation,

indicates that traditional Chinese values encourage forgiveness, which may discourage retaliation

to the source of injustice especially authority or other negative reactions to other parties (Liu,

Kwong Kwan, et al. 2010; Wu, Zhang, Chiu, Kwan, & He, 2014). Therefore, I argue that people

with high power distance orientation are less likely to display deviance under abusive

supervision than people with low power distance orientation. Therefore, I hypothesize:

Hypothesis 7: Power distance orientation moderates the relationship between abusive

supervision and deviance, such that this positive relationship is weaker when power distance

orientation is high.

3.2.2 Job Type as A Moderator

In this section, I describe how job type, either white-collar or blue-collar, moderates the

relationship between abusive supervision and interactional justice, job performance, OCB,

creativity, and deviance. Although in Figure 1, I indicate that interactional justice mediates the

relationship between abusive supervision and job performance, OCB, creativity, and deviance, in

this section, I am interested in how job type also moderates the total effects between abusive

supervision and outcomes including job performance, OCB, creativity, and deviance.

Interactional justice. Research has indicated that the social exchange process is more

central to white-collar employees, whereas the economic exchange process is more central to

blue-collar employees (Herr, Bosch, van Vianen et al., 2015; Littek & Heisig, 1989). Overall,

white-collar employees care more about the intrinsic values of their jobs, and blue-collar

employees care more about the monetary rewards of their jobs (e.g., Harris & Locke, 1974;

Locke, 1973; Weaver, 1975). Specifically, white-collar employees tend to have better work

experiences than blue-collar employees, such as having higher job satisfaction (e.g., Fisk &

Friesen, 2012), higher interactional justice (e.g., Inoue et al., 2009), higher supervisor social

support (e.g., Morris et al., 1999), and higher work engagement (e.g., Kanten & Sadullah, 2012).

As some researchers have argued, in a relationship where social exchange is expected, “a

violation of justice standard should have more serious ramifications than when the relationship is

less communal” (Cropanzano, Rupp, Mohler, & Schminke, 2001).

Research has demonstrated that white-collar and blue-collar employees have different

justice expectations and are influenced by justice to different extents. For example, Herr and his

colleagues found that justice perceptions were only related to chronic heart disease and

musculoskeletal pain for white-collar employees but not blue-collar employees (Herr, Bosch,

Loerbroks, et al., 2015; Herr, Bosch, van Vianen, et al., 2015). Therefore, when white-collar

employees experience abusive supervision, they are more likely to consider it as a violation of

justice standards and less acceptable. Therefore, I hypothesize:

Hypothesis 8: Job type moderates the relationship between abusive supervision and

interactional justice, such that this negative relationship is stronger for white-collar employees

than for blue-collar employees.

Job performance. Researchers have argued that because white-collar employees have

more job autonomy than blue-collar employees, white-collar employees may translate their

attitudes into behaviors more easily than blue-collar employees (Randall, 1990). Meta-analytical

results have also supported the stronger relationship between attitudes and job performance for

white-collar employees than blue-collar employees (Riketta, 2002). In addition, as white-collar

employees have different job preferences from blue-collar employees, they also have different

expectations regarding their workplace treatment (Hu et al., 2010; Weaver, 1975). They expect

to be treated by their supervisors with dignity and respect. Therefore, I expect that when white-

collar employees experience abusive supervision, they are more likely to feel dissatisfied and

decrease their work efforts. Therefore, I hypothesize:

Hypothesis 9: Job type moderates the relationship between abusive supervision and job

performance, such that this negative relationship is stronger for white-collar employees than for

blue-collar employees.

OCB. Compared with in-role behaviors, employees are more likely to express their

attitudes in extra-role behaviors toward which they have greater discretion (Organ, 1977; Smith

et al., 1983). Researchers have demonstrated in a meta-analysis that job satisfaction is related to

OCB to a stronger extent for professional employees than for nonprofessional employees (rc

= .41 vs. .20; Petty, McGee, & Cavender, 1984). This indicates that white-collar employees’

OCBs are more sensitive to their job attitudes. When they are satisfied with their jobs, they are

more likely to exhibit more extra-role behaviors. Therefore, when white-collar employees

experience abusive supervision, they are more likely to express their dissatisfaction by

decreasing their extra-role behaviors. Therefore, I hypothesize:

Hypothesis 10: Job type moderates the relationship between abusive supervision and

OCB, such that this negative relationship is stronger for white-collar employees than for blue-

collar employees.

Creativity. Employees are more likely to exhibit creative behaviors when they have

intrinsic motivation (e.g., Da Costa, Páez, Sánchez, Garaigordobil, & Gondim, 2015; Zhang &

Bartol, 2010). Compared with blue-collar employees, white-collar employees typically view

themselves as valuable and consider having a sense of accomplishment as an important aspect in

their jobs (Weaver, 1975; Locke, 1973; Centers & Bugental, 1966). Therefore, when abusive

supervision happens, white-collar employees are more likely to have decreased intrinsic

motivation and withdraw their creative behaviors. Therefore, I hypothesize:

Hypothesis 11: Job type moderates the relationship between abusive supervision and

creativity, such that this negative relationship is stronger for white-collar employees than for

blue-collar employees.

Deviance. Because white-collar employees have different job preferences from blue-

collar employees (Hu et al., 2010; Weaver, 1975), their tolerance levels of abusive supervision

are lower. When supervisors violate the professionalism expected in the white-collar occupations

by treating employees without dignity and respect, white-collar employees would likely react

more intensively and negatively. Therefore, I expect that the positive relationship between

abusive supervision and deviance is stronger for white-collar employees. Therefore, I

hypothesize:

Hypothesis 12: Job type moderates the relationship between abusive supervision and

deviance, such that this positive relationship is stronger for white-collar employees than for blue-

collar employees.

3.2.3 Interactional Justice as a Mediator

In this section, I focus on the mediated relationship between abusive supervision and

outcomes via interactional justice as presented in Figure 1.

Interactional justice. Research has indicated that interactional justice is a significant

predictor of employee attitudes and behaviors. When employees feel they are being treated with

respect and dignity, they are more likely to have a higher level of job satisfaction, better job

performance, more OCB, and less deviant behaviors (e.g., Cohen-Charash & Spector, 2001;

Colquitt, 2001; Colquitt et al., 2013). Interactional justice has been viewed as a primary mediator

and underlying mechanism explaining why abusive supervision is detrimental to employees (e.g.,

Aryee et al., 2007; Tepper, 2000; Lian et al., 2012).

Tepper (2000) was the first scholar to propose the construct of abusive supervision and

set forth a justice-based model that posits interactional justice as a key mediator for the

relationship between abusive supervision and employee outcomes. He argued that abusive

supervision is a significant source of interactional injustice, and the justice perception, in turn,

translates the negative effects of abusive supervision into negative attitudes and behaviors. Aryee

et al. (2007) using a sample of 47 supervisors and 178 subordinates from a telecommunication

company demonstrated that subordinates’ perceptions of interactional justice, but not procedural

justice, fully mediated the relationship between abusive supervision and employee work

outcomes. In addition, leadership scholars have demonstrated justice perceptions as mediators

for other leadership forms and outcomes, such as transformational leadership (e.g., Cho &

Dansereau, 2010; Pillai, Schriesheim, & Williams, 1999), servant leadership (e.g., Mayer,

Bardes, & Piccolo, 2008; Walumbwa, Hartnell, & Oke, 2010), ethical leadership (e.g., Zehir,

Akyuz, Eren, & Turhan, 2013). The overall argument is that justice explains the reciprocal nature

of the leader-follower relationship and is one of the most important mediators that can explain

the influence of leadership on subordinates (van Dierendonck, 2011). Therefore, I hypothesize:

Hypothesis 13: Interactional justice mediates the negative relationship between abusive

supervision and job performance, OCB, creativity and the positive relationship between abusive

supervision and deviance.

3.2.4 A Moderated Mediation Model

The logic I have outlined implies a moderated mediation relationship that the mediator

can explain the predictivity of the interactive relationship between abusive supervision and

power distance orientation in outcomes (Edwards & Lambert, 2007). A moderated mediation

model tests whether a moderating effect is transmitted through a mediator variable (Baron &

Kenny, 1986). In other words, in a moderated mediation model, the indirect effect through a

mediator varies at different levels of the moderator. This moderated mediation model can

provide insight into the “black box” regarding how cultural values and job type together with

abusive supervision influence outcomes (Kirkman et al., 2006). Therefore, I hypothesize:

Hypothesis 14: Power distance orientation moderates the indirect relationship between

abusive supervision and job performance, OCB, creativity, and deviance via interactional justice,

such that the indirect effects are weaker when power distance orientation is high.

Hypothesis 15: Job type (white-collar vs. blue-collar) moderates the indirect relationship

between abusive supervision and job performance, OCB, creativity, and deviance via

interactional justice, such that the indirect effects are stronger for white-collar employees.

CHAPTER 4 METHOD

4.1 Participants and Procedures

I recruited participants from organizations in China. I collected data using surveys from

both supervisors and subordinates with three waves in multiple medium companies. I used one

month as the time interval between every two consecutive waves. The use of multiple sources

and multiple wave data helped mitigate issues of common method bias. I also intended to collect

data at multiple levels, with subordinates at level 1, and leaders at level 2, and measure variables

at both levels. These structured data enabled me to examine the influence of leader behaviors on

individual attitudes and behaviors.

I estimated the sample size following the procedures outlined by Scherbaum and Ferreter

(2009). The power analysis indicated that I needed to have complete data from 80 leaders and

320 employees to have at least a statistical power of 80%. In total, my sample include survey

data from 1009 employees and 136 leaders, a much larger sample size than the required

minimum sample size. The team size ranges from 3 to 10 employees per team. On average, each

team has 7.26 employees. These employees and leaders were from four companies, including

two urban designing and architecture companies, one high-tech company, and one textile

company. The average age of leaders was 42.13 (SD = 6.65) and 36% were females. The average

age of employees was 37.44 (SD = 8.69) and 62% were females.

All the scales I used have been previously developed and validated. Participants

answered the survey items using Likert scales. I received approval by MSU IRB regarding my

study and survey instruments prior to collecting data. The use of multi-wave data collection also

helped reduce survey fatigue and increased the quality of the data collection. To be specific, in

the first wave, for leaders I measured leader personality variables, ethical climate in their

organizations, and their own demographic information; for subordinates, I measured their

perceptions of abusive supervision and their demographic variables. In the second wave, I only

collected data from subordinates. I measured interactional justice, and power distance

orientation. In the third wave, I only collected data from leaders. I measured their evaluations of

their subordinates’ behavioral outcomes. At the beginning of each survey, I asked the

participants to read and sign the voluntary consent form. Participants were offered small gifts or

cash as incentives to participate in the survey for each wave of the survey completed.

4.2 Measures

All measures were assessed with 5-point Likert scales with anchors of “1 = strongly

disagree” and “5 = strongly agree” unless noted otherwise. Participants needed to indicate to

what extent they agree with each statement or survey item using this 5-point Likert scale. All the

Cronbach alphas are found to be acceptable.

4.2.1 Time 1 Survey

I measured the variables listed below in the first wave from the supervisors.

Leader agreeableness and neuroticism. I measured leader agreeableness, neuroticism,

and conscientiousness from the Big Five Inventory developed by John, Donahue, & Kentle

(1991). This scale allows an efficient and flexible assessment of the five dimensions when

individual facets of the big five are not the primary focus. This scale shows good psychometric

properties. Agreeableness has 9 items, neuroticism has 8 items, and conscientiousness has 9

items. An example item for agreeableness is “Is considerate and kind to almost everyone” (α

is .70), and an example item for neuroticism is “Worries a lot” (α is .78). Leaders needed to

indicate to what extent they think each item is descriptive of themselves.

Leader trait aggression. I use a refined version of self-report Aggression

Questionnaire (Bryant & Smith, 2001) to measure leader trait aggression. This refined version

has 12 items including three items from each of the four dimensions originally included by Buss

and Perry (1992). This shortened scale shows better CFA results than the original scale

developed by Buss and Perry (1992) and good reliabilities from .72 to .80 for each dimension.

One example item is “My friends say that I'm somewhat argumentative.” Leaders needed to

indicate to what extent each item is descriptive of themselves.

Leader dark triad. I used the scale developed by Jonason and Webster (2010) to measure

leader narcissism, Machiavellianism, and psychopathy. This is a shortened version of the original

scales developed to measure these three personality variables. This scale includes three items for

each, and the reliabilities are acceptable, with .83 for narcissism (e.g., “I tend to want others to

admire me”), .81 for Machiavellianism (e.g., “I tend to manipulate others to get my way”,

and .70 for psychopathy (e.g., “I tend to be cynical”).

Ethical climate. To measure supervisors’ perceptions of the ethical climate in their

organization, I used the caring dimension of ethical work climate questionnaire developed by

Victor and Cullen (1988). An example item is “What is best for everyone in the company is the

major consideration here.” This scale has acceptable reliability, with α = .71.

Control variables. I measured the age, gender, education level, and department tenure as

control variables for supervisors as these variables may influence relational perceptions (Tsui

and O’Reilly, 1989).

I measured the variables listed below in the first wave from the subordinates.

Abusive supervision. I used the 15-item scale developed by Tepper (2000) to measure

subordinate’s perception of abusive supervision. One example is “(My supervisor) Ridicules

me.” This scale has good reliability, with α = .91. For this scale, 1 indicates never, 2 indicates

seldom, 3 indicates occasionally, 4 indicates moderately often, and 5 indicates very often.

Job type. I collected this variable by asking the job position that each participant had, and

then categorized all the answers into two categories, white-collar, or blue-collar. All the

subordinates remained in the same positions during the entire survey time window.

Control variables. I measured the age, gender, education level, dyadic tenure, as control

variables for subordinates as these variables may influence relational perceptions (Tsui and

O’Reilly, 1989).

4.2.2 Time 2 Survey

I measured the variables listed below in the second wave from the subordinates.

Power distance orientation. I measured subordinate’s power distance orientation using

the 6-item scale developed by Dorfman and Howell (1988). This scale was designed specifically

to measure cultural values at the individual level. One example item is “Employees should not

disagree with management decisions” (α = .76).

Interactional justice. I measured subordinate’s perception of interactional justice based

on their interaction with their direct leaders using the 9-item scale developed by Colquitt (2001).

An example item is “Has he/she treated you in a polite manner?” This scale has good validity

and reliability (α = .91).

4.2.2 Time 3 Survey

I measured the variables listed below in the third wave from the supervisors.

Job performance. I asked leaders to evaluate the job performance for each of their

subordinates using the 4-item scale developed by Liden, Wayne, and Stilwell (1993). An

example item is “What is your personal view of your subordinate in terms of his or her overall

effectiveness?” This scale has good reliability (α = .85).

OCB. I asked leaders to evaluate the OCB for each of their subordinates using the 16-

item scale developed by Lee and Allen (2002). An example item is “(This subordinate) Help

others who have been absent.” This scale has good reliability of .92.

Creativity. I asked leaders to evaluate the creativity for each of their subordinates using 5

items from the scale developed by Zhou and George (2001). An example item is “(This

subordinate) Suggests new ways to achieve goals or objectives.” This scale has good reliability

(α = .89).

Deviance. I asked leaders to evaluate the deviant behaviors for each of their subordinates

using the scale developed by Bennett and Robinson (2000). An example item is “(This

subordinate) Made fun of someone at work.” This scale has good reliability (α = .85). For this

scale, I used a 5-point Likert scale to measure the frequency of deviant behaviors. 1 indicates

never, 2 indicates seldom, 3 indicates occasionally, 4 indicates moderately often, and 5 indicates

very often.

4.3. Analytical Approaches

With my integrated model, I examined both the antecedents of abusive supervision and

outcomes of abusive supervision. Because I was interested in questions such as what personality

traits were predictive of abusive supervision and what were the consequences of abusive

supervision, I conducted the analyses in two steps using appropriate approaches. For example, I

examined the relationship between antecedents and abusive supervision with regression analysis.

For the relationship between abusive supervision and outcomes, I adopted HLM to consider the

data dependence issue within teams and use path analysis to examine the mediation and

moderated mediation effects. In addition, in my dissertation I was not interested in how leader

personality traits influenced employee outcomes through abusive supervision. Therefore, it was

more appropriate to conduct analyses separately to examine the antecedent-abusive supervision

relationship and abusive supervision-outcome relationship than testing the theoretical model all

together and treating abusive supervision as a mediator.

4.3.1 Data Screening and Preparation

Before conducting the analyses, I wanted to make sure the data were usable and of good

quality. First, I checked for missing data. Because I used paper and pencil surveys and collected

data face-to-face with the help of human resource employees, all the surveys were largely

complete. If some participants only missed some items, I used the average of the corresponding

scale of that item to replace the missing value of that item. Second, I checked the frequency and

distribution of each item and each variable. If a variable was not normally distributed, I checked

whether the skewed distribution had an impact on any analysis used. Checking the frequency and

distribution of variables also revealed possible data entry errors.

4.3.2 Descriptive Data, Correlation Analysis, and Reliability Analysis

I first calculated the mean and standard deviation of each variable. In addition, I also

reported the zero-order correlations for all variables and Cronbach’s α for the reliability of each

scale.

4.3.3 Regression and Moderation Analysis

I used moderated regression analysis as the main statistical procedure for examining the

relationship between leader personality traits and abusive supervision, as well as the proposed

moderating effect of ethical climate. Moderation regression analysis allows for a comparison

between alternative models with and without interaction terms, where an interaction effect only

exists if the interaction term contributes significantly to the variance explained in the dependent

variable over the main effects of the independent variables (Aiken, West, & Reno, 1991). I

centered predictors and moderators before creating the interaction terms and graphed

interaction(s) following procedures set forth by Aiken et al. (1991).

4.3.4 Measurement Model, Hierarchical Linear Modeling Analysis, and Structural Model

I used the analytical approaches described below to examine the relationship between

abusive supervision and employee outcomes, as well as the proposed moderators and mediator.

Before conducting the path analysis, I conducted multilevel confirmatory factor analyses

on survey items to determine whether my measurement model captured distinct constructs. I

performed these analyses in Mplus 8.2 (Muthén & Muthén, 2017), with the raw data entered. I

first specified a model in which all the items loaded on their corresponding hypothesized latent

constructs. I compared the above model to the two-factor model in which all the items loaded

either on one attitudinal latent construct or on a behavioral outcome. In addition, a chi-square

difference test indicated whether the hypothesized two-factor model provided a better fit to the

observed data than the one-factor model. Besides comparing the models, I also used the

following indices to evaluate the model fit, including the chi-square test, standardized root mean

square residual (SRMR), root mean square error of approximation (RMSEA), and the

comparative fit index (CFI). An SRMR of less than .09, an RMSEA less than .08, and a CFI

greater than .90 indicate that the model fits the data well (Baumgartner & Homburg, 1996; Hu &

Bentler, 1999; Iacobucci, 2010).

The nested structure of my data, with employees nested within supervisors, violates the

independence assumption of traditional ordinary least squares (OLS). The use of OLS in my

situation may result in biased estimation of standard error (Hofmann, 1997). Since hierarchical

linear modeling (HLM) is an appropriate statistical-based analytical tool for dealing with non-

independence problems caused by nested data, I used HLM 7.0 (Raudenbush & Bryk 2002) to

test the cross-level main effect and moderation effect hypotheses and to obtain a robust standard

error and estimates of greater accuracy.

The HLM approach is a two-stage strategy that investigates variables occurring at two

levels of analysis (Hofmann, Griffin, & Gavin, 2000). The outcome of this first stage is intercept

and slope terms estimated separately for each group. These intercept and slope estimates from

the level 1 analysis are then used as outcome variables in the level 2 analysis. In my data set, the

employee is at level 1 and the supervisor or working team is at level 2. Although the level 1 and

level 2 equations are discussed separately, it should be noted that they are estimated

simultaneously. The key terms are fixed effects, random effects, and variance components. Fixed

effects are parameter estimates that do not vary across groups. The variance of the level 1

residuals and the variance-covariance of the level-2 residuals comprise the variance components.

The HLM procedure uses the EM algorithm to produce maximum-likelihood estimates of the

variance components. Random coefficients are those that are allowed to vary across groups. The

HLM procedure does not provide any statistical tests for these parameters.

Centering is another important issue in HLM data analysis. The choice between grand-

mean centering or group-mean centering depends on what research question is of interest

(Enders & Tofighi, 2007). For hypotheses regarding the relationship between abusive

supervision, individual cultural values, and outcomes, because level-1 predictor, abusive

supervision, was of substantial interest, the use of group-mean centering made the results easier

to interpret.

Several hypotheses are associated with the moderation effects in HLM. The basic logic

and procedure of examining the moderation effects in HLM are similar to that in OLS regression.

Researchers have outlined specific steps of examining moderation effects in HLM (Preacher,

Curran, & Bauer, 2006). With the statistical software HLM 7.03, it is possible to generate output

regarding the variances and covariances among the predictors in the model. I would need these

statistics in calculating the simple slopes of each regression line.

I used the structural model to test the hypotheses for the mediation and moderated

mediation between abusive supervision and outcomes. Because of the multilevel nature of the

data, I used multilevel structural equation modeling (MSEM) as recommended by Preacher,

Zyphur, and Zhang (2010). I performed these analyses in Mplus 8.2 (Muthén & Muthén, 2017),

with the raw data entered. The output from Mplus included the path coefficient, indirect effects,

and moderated mediation effects. I used the fit indexes described above to evaluate the model fit

in this analysis.

CHAPTER 5 RESULTS

In this chapter, I present the results of my dissertation. I first report the descriptive data

and correlations among variables at both the employee and team level. Then I report the

analytical results for antecedents and outcomes separately.

5.1 Data Aggregation, Descriptive Data, and Correlations

Based on the analytical needs, I only aggregated one variable from the employee level to

the leader level. Specifically, each leader’s abusive supervision rating was obtained by

aggregating the ratings from employees supervised by that leader. The ICC of abusive

supervision was .37, supporting the use of aggregated values of employee ratings as each

leader’s abusive supervision behavior rating. I used the approach outlined by Croon and van

Veldhoven (2007) to compute the adjusted group means of abusive supervision ratings as the

team leader’s abusive supervision score based on employees’ ratings of their own leaders. As

Croon and van Veldhoven (2007) have discussed, using the adjusted group means provides more

accurate results and unbiased estimates than simply using the arithmetic means.

I conducted the analysis using SPSS and present the results in Table 1. Along the

diagonals, I report Cronbach alphas for each scale.

5.2 Antecedents to Abusive Supervision

5.2.1 Regression and Moderation Analysis

Hypothesis 1 stated that leader personality variables are correlated with abusive

supervision. Hypothesis 2 stated that ethical climate moderates the relationship between abusive

supervision and leader personality, such that these relationships are stronger when ethical climate

is low. Table 2 presents the results for the regression and moderation analysis. I tested the above

hypotheses in a stepwise approach in SPSS. In Model 1, I included demographic variables as

control variables. In Model 2, I added personality variables and ethical climate as predictors to

test the main effects of personality variables. In Model 3, I added the interaction terms between

personality variables and ethical climate. To facilitate the interpretation of results, I centered the

personality variables and ethical climate and created the interaction terms before I ran the

analysis (Aiken et al., 1991).

Table 1. Means, SDs, reliabilities, and correlations

Mean SD 1 2 3 4 5 6 7 8 9 10 11

1. Leader Age 42.13 6.65

2. Leader Gender .36 .48 .09

3. Leader Education 2.15 1.15 -.70* -.33*

4. Leader Tenure dept 129.38 133.76 .52* .22* -.61*

5. Leader Agreeableness 4.03 .50 .21* .05 -.26* .05 (.70)

6. Leader Neuroticism 2.21 .61 -.36* -.11 .26* -.13 -.54* (.78)

7. Leader Aggressiveness 2.24 .58 -.11 -.06 .17 -.10 -.54* .51* (.77)

8. Leader Machiavellianism 1.68 .74 -.28* -.23* .44* -.14 -.52* .46* .47* (.81)

9. Leader Psychopathy 1.54 .61 -.04 -.08 .09 .00 -.39* .23* .44* .43* (.69)

10. Leader Narcissism 2.70 .98 -.24* -.15 .34* -.21* -.22* .23* .32* .39* .21* (.83)

11. Leader Ethical climate 3.90 .58 .17 .04 -.20* .12 .45* -.13 -.16 -.27* -.24* -.17* (.71)

12. Leader Abusive supervision 1.45 .54 .25* .09 -.29* .44* -.37* .12 .09 .12 .20* -.02 -.25*

13. Follower Age 37.44 8.69 .52* .16* -.64* .45* .16* -.21* -.13* -.30* -.04 -.18* .10*

14. Follower Gender .62 .49 .20* .34* -.31* .25* .14* -.22* -.20* -.14* -.11* -.13* .10*

15. Follower Education 1.70 .99 -.62* -.31* .85* -.53* -.23* .29* .18* .37* .11* .21* -.18*

16. Follower Tenure dyadic 57.48 68.09 .33* .01 -.35* .36* .05 .00 .01 -.12* .09* -.06 .07*

17. Follower Interactional justice 4.05 .63 -.07* -.01 .01 -.07* .20* -.03 -.09* -.05 -.07* -.07* .16*

18. Follower Power distance

orientation 2.82 .73

.11* .05 -.20* .05 .06* -.09* -.02 -.11* -.07* .02 .04

19. Follower Job type .68 .47 .64* .25* -.88* .55* .26* -.29* -.18* -.43* -.12* -.22* .20*

20. Follower Job performance 3.95 .72 -.07* .05 .08* -.10* .14* -.19* -.07* -.11* -.02 .01 .12*

21. Follower OCB 3.56 .70 -.20* .03 .24* -.23* .05 -.10* -.06* .01 .08* .11* .15*

22. Follower Creativity 3.27 .84 -.17* .07* .18* -.26* -.01 .03 -.03 .09* .13* .05 .12*

23. Follower Deviance 1.29 .36 .11* -.07* -.08* .09* -.28* .20* .14* .13* .09* .00 -.12*

Table 1. (cont’d.)

12 13 14 15 16 17 18 19 20 21 22 23

12. Follower Abusive supervision (.87)

13. Follower Age .19*

14. Follower Gender -.04 .17*

15. Follower Education -.18* -.67* -.35*

16. Follower Tenure dyadic .16* .44* .02 -.36*

17. Follower Interactional justice -.19* -.05 -.01 .06 -.10* (.90)

18. Follower Power distance

orientation .15* .20* .03 -.21* .14* -.12* (.77)

19. Follower Job type .19* .67* .32* -.92* .36* -.05 .24*

20. Follower Job performance -.20* -.03 .05 .03 -.01 .10* -.09* -.02 (.85)

21. Follower OCB -.13* -.20* -.04 .20* -.08* .10* -.14* -.19* .56* (.92)

22. Follower Creativity -.04 -.21* -.04 .16* -.13* .12* -.14* -.15* .40* .60* (.89)

23. Follower Deviance .22* .12* -.05 -.08* .08* -.17* .09* .09* -.47* -.38* -.18* (.85)

Note. Gender: female = 1, male = 0. Job type: white-collar = 0, blue-collar = 1.

The sample size for variable 1-11 is 136, the sample size for variable 12-23 is 1009.

Table 2. Regression analyses predicting abusive supervision

Model 1 Model 2 Model 3 Model 4

Control variables

Age .00 .06 .08 .06

Gender -.02 -.02 .02 .01

Education -.04 -.21 -.20 -.22

Tenure .41* .32* .33* .33

Main effects

Agreeableness -.39* -.34* -.35*

Neuroticism .04 .10 .07

Aggressiveness -.15 -.15 -.14

Machiavellianism .04 .07 .07

Psychopathy .06 .04 .05

Narcissism .03 -.03 -.04

Ethical climate (EC) -.15 -.20* -.19*

Interaction effects

Agreeableness*EC .07

Neuroticism*EC .07

Aggressiveness*EC -.19

Machiavellianism*EC .10

Psychopathy*EC .05

Narcissism*EC .19* .21*

F 7.70* 7.57* 6.00* 7.95*

R2 .19 .40 .46 .44

△R2 .21* .06* .04*

Note. Standardized coefficients are reported; n = 136.

* p < .05

Results indicated in Table 2 partially supported Hypothesis 1. Leader agreeableness was

the only personality predictor that was significantly associated with abusive supervision (b =

-.39, p < .05). In other words, less agreeable leaders were more likely to be perceived as abusive

supervisors. All other personality predictors were not significantly associated with abusive

supervision.

Results in Table 2 failed to support Hypothesis 2. As indicated in Model 3 in Table 2,

ethical climate only moderated the relationship between narcissism and abusive supervision (b

= .19, p < .05). Because all other interaction terms were not significant, I ran a reduced model

that only included the interaction term between leader narcissism and ethical climate. I present

the results in Model 4. Consistent with Model 3, in Model 4 the interaction effect between

narcissism and ethical climate was significant (b = .21, p < .05). To better understand the

moderation effect, I plotted the interaction relationship between narcissism and ethical climate in

Figure 2 following the approach outlined by Aiken et al. (1991). Specifically, I drew the two

regression lines for the relationship between narcissism and abusive supervision at two levels of

ethical climate, namely +1 SD above the mean of ethical climate and -1 SD below the mean of

ethical climate. I also reported the simple slopes for these two regression lines. The results

showed that when leaders perceived high ethical climates, the relationship between narcissism

and abusive supervision was positive (b = .06, p < .05). Whereas when leaders perceived low

ethical climates, the relationship between narcissism and abusive supervision was negative (b =

-.08, p < .05). Because the interaction pattern was contrary to Hypothesis 2, Hypothesis 2 was

not supported.

Figure 2. The relationship between leader narcissism and abusive supervision with ethical

climate as a moderator

5.3 Outcomes to Abusive Supervision

Because employees were nested within teams, data at the individual level may not be

independent. As a result, using HLM is more appropriate than OLS in this situation. To test the

necessity of using HLM, I first analyzed the ICC for interactional justice, job performance, OCB,

creativity, and CWB. Results indicated that the ICC for interactional justice was .25, the ICC for

job performance was .53, the ICC for OCB was .73, the ICC for creativity was .65, and the ICC

for deviance was .60. These ICC values were considered large (Bliese, 2000; James, 1982),

indicating that the variances were significant at both the individual and the team level. Therefore,

I decided to use HLM that considers the data dependence issue at the employee level

(Raudenbush & Bryk, 2002). As a result, all the following analyses were based on HLM.

5.3.1 Moderation Analysis for Power Distance Orientation and Job Type

Hypotheses 3 to 7 stated that power distance orientation moderated the relationship

between abusive supervision and interactional justice, job performance, OCB, creativity, and

deviance, such that these relationships were stronger for employees with low power distance

orientations. Hypotheses 8 to 12 stated that job type moderated the relationship between abusive

supervision and interactional justice, job performance, OCB, creativity, and deviance, such that

these relationships were stronger for white-collar employees than blue-collar employees. To test

the above hypotheses, I used HLM 7.03 to conduct the corresponding analyses. Specifically, I

tested five models separately with interactional justice, job performance, OCB, creativity, and

deviance as outcomes, and power distance orientation and job type as predictors simultaneously

for each model. I tested the two moderators simultaneously because I was interested in their

relative importance in impacting how abusive supervision was associated with each outcome.

Because abusive supervision and the two moderators were all at the employee level, I group-

mean centered them and created the interaction terms before I conducted the analysis (Enders &

Tofighi, 2007).

Table 3. HLM analyses for power distance orientation and job nature as moderators

Interactional

justice

Job

performance

OCB Creativity Deviance

Intercept 3.87** 3.97** 3.56** 3.24** 1.13**

Control variables

Age (γ10) .00 .00 .00 .00 .00

Gender (γ20) .00 -.03 -.01 -.05 -.01

Education (γ30) .04 .00 .05 .08 .02

Tenure (γ40) .00 .00 .00 .00 .00

Main effects

Abusive

supervision (AS)

(γ50)

-.64** -.20* -.09 -.02 .13**

Power distance

orientation (PDO)

(γ60)

-.02 .00 .01 .05 .01

Job nature (γ70) -.01 -.02 -.20 -.14 .09

Interaction effects

AS*PDO (γ80) -.02 .15* -.02 .05 -.02

AS*Job nature

(γ90) .58** .10 .03 -.05 -.11*

Note. Unstandardized coefficients are reported; N employee = 1009, N team = 136.

** p < .01;

* p < .05.

Table 3 presents the results for the HLM analyses for power distance orientation and job

type as moderators. Among Hypotheses 3 to 7, only Hypothesis 4 was supported. Namely, power

distance orientation moderated the relationship between abusive supervision and job

performance (γ10 = .15, p < .05). To visualize the interaction effect, I plotted a figure in Figure

3. Following the steps outlined in Aiken et al. (1991) and Preacher et al. (2006), I drew two

regression lines for the relationship between abusive supervision and job performance at two

levels of power distance orientation, +1 SD above the mean and -1 SD below the mean of power

distance orientation. The simple slope calculation indicated that for employees with low power

distance orientation, abusive supervision was negatively associated with job performance (γ =

-.28, p < .05). For employees with high power distance orientation, abusive supervision was not

associated with job performance (γ = -.11, n.s.).

Figure 3. The relationship between abusive supervision and job performance with power

distance orientation as a moderator

Among Hypotheses 8 to 12, Hypotheses 8 and 12 were supported. Consistent with

Hypothesis 8, the results indicated that job type moderated the relationship between abusive

supervision and interactional justice (γ10 = .58, p < .05). To visualize this interaction effect, I

plotted a figure in Figure 4. Similar to Figure 3, I drew two regression lines for the relationship

between abusive supervision and interactional justice for white-collar employees and blue-collar

employees separately. The simple slope calculation indicated that for white-collar employees,

abusive supervision was negatively associated with interactional justice (γ = -.64, p < .05). For

blue-collar employees, abusive supervision was not associated with interactional justice (γ =

-.06, n.s.).

Figure 4. The relationship between abusive supervision and interactional justice with job

type as a moderator

Consistent with Hypothesis 12, the results showed that job type moderated the

relationship between abusive supervision and deviance (γ10 = -.11, p < .05). To visualize this

interaction effect, I plotted a figure in Figure 5. I drew two regression lines for the relationship

between abusive supervision and deviance for white-collar employees and blue-collar employees

separately. The simple slope analysis indicated that for white-collar employees, abusive

supervision was positively associated with deviance (γ = .13, p < .05). For blue-collar

employees, abusive supervision was not associated with deviance (γ = .02, n.s.).

Figure 5. The relationship between abusive supervision and deviance with job type as a

moderator

5.3.2 Multilevel Confirmatory Factor Analysis

Before I ran the path analysis model, I ran multilevel confirmatory factor analyses for my

key variables, including abusive supervision, power distance orientation, interactional justice, job

performance, OCB, creativity, and deviance (Mehta & Neale, 2005). In the first model, I

included all the items used to measure these variables and modeled all the items to load on their

corresponding latent constructs. To make sure the multilevel CFA model could converge, I used

parcels to reduce the number of free parameters in the model (Little, Rhemtulla, Gibson, &

Schoemann, 2013). The model showed an acceptable fit to the data: χ2(982) = 1562.665; CFI =

0.952; RMSEA = .024; SRMR (within) = .033, and SRMR (between) = .076, and all loadings

were significant (p < .05). I compared this model with another model, in which I combined all

the attitudinal constructs including abusive supervision, power distance orientation, and

interactional justice as an overall attitudinal construct, as well as combined all the behavioral

variables including job performance, OCB, creativity, and deviance as an overall behavioral

construct. The alternative model provided a poor fit to the data: χ2(1052) = 6932.828; CFI

= .511; RMSEA = .478; SRMR (within) = .097 and SRMR (between) = .227. Thus, compared

with the first model, the second model was significantly worse (Δ χ2 (Δdf = 70) = 5370.163,

p > .05). These findings further supported the discriminant validity of the key variables in my

model.

5.3.3 Multilevel Moderated Mediation Model

Hypothesis 13 stated that interactional justice mediated the relationship between abusive

supervision and employee outcomes. Hypothesis 14 and 15 stated that power distance orientation

and job type moderated the above mediation effects, such that the mediation effects would be

different at different levels of the moderators. To test the mediation and moderated mediation

effects, I ran a path analysis model to test all these relationships simultaneously. Specifically, in

the model abusive supervision was the predictor, interactional justice was the mediator,

behaviors including job performance, creativity, OCB, and deviance were outcomes, power

distance orientation, and job type were moderators. In addition, I also included age, gender,

education, and dyadic tenure as control variables in this model. I conducted the analysis in Mplus

8.4.

Figure 6 presents the structural model with paths among these variables. This is a full

mediation model in which interactional justice carries the effects from abusive supervision and

passes such effects to employee outcomes. Overall, the fit of this model was acceptable. χ2 (df

= 20, n = 957) = 32.632, p < .05, CFI = .98, TLI = .94, RMSEA = .026, SRMRwithin = .047,

SRMRbetween = .020. As indicated by this model, most of the paths were significant, except for

the paths that were depicted using dashed lines. Figure 6 indicates that abusive supervision was

associated with interactional justice (β = -.64, p < .01). Interactional justice was associated with

all behavioral outcomes, including job performance (β = .09, p < .01), OCB (β = .07, p < .01),

creativity (β = .09, p < .01), and deviance (β = -.06, p < .01). In addition, job type moderated

the relationship between abusive supervision and interactional justice (β = .58, p < .01).

Unexpectedly, power distance orientation did not moderate this relationship as stated in

Hypothesis 14 (β = -.02, n.s.).

Note. N = 956.

Model fit: χ2 (df = 20, n = 957) = 32.632, p < .05, CFI = .98, TLI = .94,

RMSEA = .026, SRMR within

= .047, SRMR between

= .020.

Gender, age, education, and dyadic tenure are modeled as control variables.

Figure 6. A moderated mediation model

In sum, Hypothesis 13 received full support. Table 4 presents the mediation results. As

indicated in Table 4, the indirect effects from abusive supervision to job performance (indirect

effect = -.06, p < .05), creativity (indirect effect = -.05, p < .05), OCB (indirect effect = -.05, p

< .05), and deviance (indirect effect = .04, p < .05) via interactional justice were all significant.

Therefore, interactional justice fully mediated the relationship between abusive supervision and

all these behavioral outcomes.

Abusive

supervision

Creativity

Power distance

orientation

Interactional

justice

Job type

OCB

Job performance

Deviance

-.64**

-.02

-.01

-.02

.58**

.09**

.07**

-.06**

Table 4. Indirect effects from abusive supervision to outcomes through interactional justice

Dependent variable Indirect effect

Job performance -.06*

Creativity -.05*

OCB -.05**

Deviance .04**

Hypothesis 14 was not supported, indicating that the mediation effects from abusive

supervision to behavioral outcomes via interactional justice did not vary significantly among

employees with different power distance orientations. In other words, the differences in the

indirect effects were minimal for employees with different levels of power distance orientation.

Table 5 presents the results associated with Hypothesis 14.

Table 5. Moderated indirect effects from abusive supervision to outcomes through

interactional justice by power distance orientation

Dependent variable Job Type Indirect effect

Job performance Low PD Orientation -.06*

High PD Orientation -.06**

Difference .00

Creativity Low PD Orientation -.05*

High PD Orientation -.06*

Difference .00

OCB Low PD Orientation -.04**

High PD Orientation -.05*

Difference .00

Deviance Low PD Orientation .04**

High PD Orientation .04*

Difference .00

Hypothesis 15 received full support. As expected, the mediation effects from abusive

supervision to behavioral outcomes via interactional justice were different for white-collar

employees and blue-collar employees. Table 6 presents the results associated with Hypothesis

15. Specifically, the indirect effect from abusive supervision to job performance via interactional

justice was -.06 (p < .05) for white-collar employees, whereas such indirect effect was not

significant (indirect effect = -.01, n.s.) for blue-collar employees. This pattern also applied to

other behavioral outcomes. The indirect effect from abusive supervision to creativity via

interactional justice was -.05 (p < .05) for white-collar employees, whereas such indirect effect

was not significant (indirect effect = -.01, n.s.) for blue-collar employees. The indirect effect

from abusive supervision to creativity via interactional justice was -.05 (p < .05) for white-collar

employees, whereas such indirect effect was not significant (indirect effect = .00, n.s.) for blue-

collar employees. The indirect effect from abusive supervision to deviance via interactional

justice was .04 (p < .05) for white-collar employees, whereas such indirect effect was not

significant (indirect effect = .00, n.s.) for blue-collar employees. In sum, these results indicated

that interactional justice functioned as a mediator that explained the underlying mechanism of

why abusive supervision had an influence on outcome variables only for white-collar employees,

but not for blue-collar employees. In other words, for white-collar employees, abusive

supervision influenced interactional justice which further influenced employee behaviors.

However, this was not the case for blue-collar employees. For blue-collar employees,

interactional justice did not function as a mediator that explained the effects of abusive

supervision on outcomes. As a supplementary analysis. I also conducted analyses with

interpersonal justice rather than interactional justice. The results with interpersonal analyses were

similar to the analyses using interactional justice.

Table 6. Moderated indirect effects from abusive supervision to outcomes through

interactional justice by job type

Dependent variable Job Type Indirect effect

Job performance White-collar workers -.06*

Blue-collar workers -.01

Difference .05*

Creativity White-collar workers -.05*

Blue-collar workers -.01

Difference .05*

OCB White-collar workers -.05**

Blue-collar workers .00

Difference .04**

Deviance White-collar workers .04**

Blue-collar workers .00

Difference -.03**

CHAPTER 6 DISCUSSION

Overall, the results provide support for the proposed model and several of the hypotheses.

The results indicate that leader personality is an important predictor of abusive supervision and

that contextual factors moderate the relationship between leader personality and abusive

supervision. Regarding the relationship between abusive supervision and employee outcomes,

this study supports that interactional justice is an important mediator. In addition, the findings

show that there are different indirect effects between white-collar and blue-collar employees,

highlighting the importance of considering job type as a key boundary condition in future

studies. In contrast to prior research, this study does not provide strong evidence for the

moderating role of power distance orientation on the relationship between abusive supervision

and employee outcomes.

6.1 The Role of Leader Personality in Abusive Supervision

The results provide support for the role of leader personality traits as predictors of

abusive supervision. As indicated in Table 1, among the six examined personality variables, only

agreeableness (r = -.37, p < .05) and psychopathy (r = .20, p < .05) are correlated with abusive

supervision. Based on standards on the magnitude of effect size (Cohen, Cohen, Aiken, & West,

1983), leader agreeableness has a moderate to strong association with abusive supervision,

whereas psychopathy has a weak to moderate association with abusive supervision. Unlike

Mackey et al. (2017) who found weak to moderate associations between subordinate personality

traits and abusive supervision, this study indicates that certain leader personality traits (e.g.,

agreeableness) are possibly stronger predictors of abusive supervision. In the past, researchers

have focused more on the extent to which subordinate personality traits color employee

perceptions of abusive supervision (e.g., Brees et al., 2016; Tepper, 2007) and have largely

ignored the role of leader personality traits. In addition, the relationship between leader

agreeableness and abusive supervision found in this study is generally higher than the

relationship between personality traits (e.g., the big five) and other leadership behaviors such as

transformational leadership and transactional leadership (e.g., Bono & Judge, 2004). The results

of this study highlight the significant role of leader personality traits in abusive supervision

behaviors.

In addition to the correlation results, the regression analysis results further support the

important role of agreeableness, which is a broadly defined personality trait. In the regression

analysis, agreeableness was the only significant predictor among leader personality traits that

were included. This study indicates that a less agreeable supervisor is more likely to be an

abusive supervisor. This specific finding provides some evidence about the relative importance

of broadly defined and narrowly defined personality variables, indicating that the broadly

defined personality variables may have better predictive validity than narrowly defined

personality traits in explaining abusive supervision.

However, one study is not conclusive. In this study, I only examined agreeableness and

neuroticism as broadly defined personality traits and trait aggressiveness and the dark triad as

narrowly defined personality traits. Based on my review of the literature, no studies have

compared the predictive validity of narrowly versus broadly defined leader personality variables

in the context of abusive supervision. Most often, researchers only used either broadly or

narrowly defined personality variables as predictors in their studies (e.g., Waldman et al., 2018;

Wang et al., 2015). The idea of studying narrowly defined personality variables assumes that

such variables may capture specific aspects of personality and thus serve as stronger predictors

than widely defined variables in some cases (Hough et al., 2015). Therefore, I suggest additional

empirical research examine the relationship between leader personality and abusive supervision

and compare the relative importance of broadly defined and narrowly defined personality traits

with different operationalizations of personality traits.

This study also sheds light on the role of leader narcissism. Leadership researchers in the

past have paid some attention to narcissism, finding that it is an important antecedent of

leadership behaviors (e.g., Grijalva & Harms, 2014; Judge, LePine, & Rich, 2006), including

abusive supervision (Waldman et al., 2018). Based on trait activation theory, I hypothesized that

a low ethical climate serves as an activator, whereas a high ethical climate serves as a buffer

between leader narcissism and abusive supervision. Consistent with prior findings, this study

also supports the importance of narcissism. Although narcissism was not correlated with abusive

supervision, it interacted with ethical climate in predicting abusive supervision. Contrary to my

hypothesis, the moderation results indicated that in a high organizational caring ethical climate,

the relationship between narcissism and abusive supervision was positive, whereas in a low

organizational caring ethical climate, the relationship between narcissism and abusive

supervision was negative. These results, although unexpected, could be explained by Kristof’s

(1996) idea of fit between leader personality and organizational ethical climate. Kristof (1996)

defined the construct of person-organization fit and highlighted the importance of the

supplementary fit between employee personality and organizational climate. It is possible that

narcissistic leaders fit better in less caring ethical climates because of their tendency to behave

unethically and overemphasis on their own interests (Blair, Hoffman, & Helland, 2008). In a low

ethical context, followers perceive narcissistic leaders as less abusive because leaders’ behaviors

fit better with the organizational climate. In comparison, in a high ethical context, followers

perceive narcissistic leaders as more abusive because leaders’ narcissistic behaviors are more

salient to them as not caring. Interestingly, the results of this study are similar to the results in

Hoffman, Strang, Kuhnert, Campbell, Kennedy, and LoPilato (2013). With ethical leadership as

an outcome, Hoffman et al. (2013) found that leader narcissism was negatively related to ethical

leadership in a high ethical context, and such a relationship was not significant in a low ethical

context. Together, this study and Hoffman et al. (2013) support the fit perceptive of narcissism.

Namely, narcissist leaders fit better in a less ethical context and are generally rated more

negatively in a high ethical context.

Another contribution of this study is examining trait aggressiveness as a predictor in the

model. Research has supported that trait aggressiveness is an important antecedent to aggressive

behaviors and has moderate to strong relationships with aggressive behaviors in general

(Bettencourt et al., 2006). However, in the abusive supervision literature, trait aggressiveness is

seldom studied as a predictor. This study filled the gap by treating leader trait aggressiveness as a

predictor. The results indicated that trait aggressiveness was not correlated with abusive

supervision nor it was a significant predictor in the regression model. This may indicate that the

content domain of abusive supervision is significantly different from that of aggressive

behaviors. Although researchers have conceptualized aggressive behaviors as both physical and

verbal, a majority of the studies on aggressive behaviors have focused on physically aggressive

behaviors (Bettencourt et al., 2006). Therefore, it is understandable that trait aggressiveness is a

strong predictor for physical aggressive behaviors but not a strong predictor for non-physical

hostile behaviors in the workplace, namely abusive supervision behaviors.

6.2 Ethical Climate and Trait Activation Theory

In this study, I integrate the trait activation theory with the abusive supervision literature

(Tett & Guterman, 2000) and propose that ethical climate moderates the relationship between

leader personality and abusive supervision. Although the hypothesis related to trait activation

theory was not supported, results from this study still provided support for the relevance of

situational factors in the abusive supervision context. Overall, little empirical attention has been

devoted to understanding the boundary conditions of leader personality on abusive supervision

from the perspectives of situational factors. Some studies examined the boundary conditions

from the perspectives of individual differences, such as political skills (Waldman et al., 2018).

One exception is a study conducted by Wisse and Sleebos (2016) who found that the perceived

position power strengthened the relationship between leader Machiavellianism and abusive

supervision. In the future, I encourage researchers to devote more attention to examining theory-

based situational factors to provide a more thorough understanding of the relationship between

leader/follower personality and abusive supervision. For example, researchers in the future could

examine other dimensions of ethical climate including law and code, rules, instrumental, and

independence (Victor & Cullen, 1988). The caring dimension of ethical climate primarily

captures the interpersonal aspect of the ethical climate, and it is possible that other dimensions

function differently from the caring dimension. In addition, as a related construct, ethical culture

could also serve as a moderator based on the trait activation theory. According to Treviño,

Butterfield, and McCabe (1998), “the term "climate" suggests meteorological climate and

qualities such as temperature, humidity, precipitation, wind, and other atmospheric conditions

that can affect individuals (e.g., feelings),” whereas “the notion of "culture" evokes notions of

rules, codes, rewards, leadership, rituals, and stories-sensemaking devices that more explicitly

guide and shape behavior.” It is possible that ethical culture has a stronger influence on the

relationship between leader personality and abusive supervision than ethical climate because of

ethical culture’s stronger emphasis on rules and codes rather than atmospheric conditions.

6.3 The Relative Importance of Power Distance Orientation and Job Type

Different from the several published studies on power distance orientation, this study

does not provide much support for power distance orientation as a moderator. In this study,

power distance orientation was found to be only a significant moderator for the relationship

between abusive supervision and job performance, but not for other outcomes such as

interactional justice, OCB, creativity, and deviance. Nor was it a significant moderator in the

moderated mediation model. This is unexpected, especially since past research tended to support

that power distance orientation moderates the relationship between abusive supervision and

outcomes such as interactional justices and deviance. For example, research in the past has found

that for employees with low power distance orientation, their interactional justice perception is

more strongly influenced by abusive supervision (Lian et al., 2012; Vogel et al., 2015; Wang et

al., 2012). Findings in this study did not support power distance orientation as a moderator for

the relationship between abusive supervision and deviance, providing different results from prior

research (e.g., Lian et al., 2012).

However, as a moderator job type outperformed power distance orientation in this study.

Results indicate that job type strongly influences employees’ interactional justice and deviant

behaviors when they experience abusive supervision. White-collar employees tend to react more

strongly than blue-collar employees. When white-collar employees experience abusive

supervision, they are more likely to have decreased interactional justice perceptions and more

deviant behaviors. The moderated mediation model reveals that the mediation mechanisms for

white-collar and blue-collar employees are different as well. Interactional justice is found only to

mediate the relationship between abusive supervision and outcomes for white-collar employees

but not for blue-collar employees.

The purpose of including power distance orientation and job type as moderators and

testing them simultaneously is to test their relative importance. In the past, researchers typically

have studied power distance orientation by itself, assuming that power distance orientation

serves as a boundary condition and makes a difference regarding how employees respond to

abusive supervision (e.g., Lian et al., 2012; Lin et al., 2013). However, in the workplace setting,

how employees respond to their leaders is not solely determined by personal values. More likely,

it is also influenced by other contextual factors, such as what type of job they have. In sum,

future research should devote more attention to exploring whether power distance orientation and

other cultural values are important boundary conditions. The current study contributed to the

mixed findings in this area.

6.4 Generalizability Issues of Current Research with a Focus on White-Collar Employees

Similar to other areas in the organizational behavior field, the abusive supervision

literature has heavily relied on white-collar employees as the samples. The underlying

assumption appears to be that the job type does not matter, and results obtained from white-collar

employees are generalizable to other job types. However, the results of this study indicate that

there are significant differences regarding how white-collar and blue-collar employees respond

to abusive supervision. The results indicate that the extent to which abusive supervision

influences interactional justice perceptions is different for white-collar and blue-collar

employees. White-collar employees respond more intensively to abusive supervision than blue-

collar employees in terms of interactional justice perceptions and deviant behaviors. Also,

interactional justice only mediates the relationship between abusive supervision and employee

outcomes for white-collar employees but not blue-collar employees. This reveals that job type is

possibly an important boundary condition for abusive supervision. In the past, the role of job

type has been ignored, even though some studies have included blue-collar employees in their

samples, their purpose was to increase the generalizability of their results rather than specifically

examining differences between the groups (Bamberger & Bacharach, 2006; Harr et al., 2016; Lin

et al., 2013; Kluemper et al., 2019). The results from this study indicate that the role of job type

is possibly more important in influencing employee reactions to abusive supervision than

researchers have considered.

In addition, this study also challenges the generalizability of the current findings to non-

white collar employees. For example, Tepper (2000) specifically highlighted the role of

interactional justice and proposed a justice-based model for abusive supervision. Researchers

have proposed and supported that interactional justice is an important mediator that explains why

abusive supervision impacts employees (e.g. Aryee et al., 2007; Rafferty & Restubog, 2011).

However, this study demonstrates that interactional justice is not a mediator for blue-collar

employees. Therefore, I would suggest that future research examine the role of job type to test

whether it is a moderator for the relationship between abusive supervision and other important

constructs.

6.5 Strengths, Limitations, and Future Directions

There are several strengths of this study. First, because I believe abusive supervision is a

complex phenomenon, I used a complex model to study its antecedents and outcomes. At the

same time, I integrated multiple theories into abusive supervision literature. For antecedents, I

incorporated personality literature and the trait activation theory (Tett & Burnett, 2003) to the

abusive supervision literature, and thereby found support for leader personality as a key

predictor. This dissertation highlights the important role of leader personality, which represents

an understudied group of variables in the abusive supervision. In the future, researchers could

continue examining the role of leader personality to better understand why personality traits have

an impact on leaders’ abusive supervision behaviors.

Regarding outcomes, I tested job type that represents a traditionally ignored boundary

condition, in the relationship between abusive supervision and employees. The significant results

of job type challenge the current dominant focus on white-collar employees as well as the

generalizability of the current findings to other job types. At the same time, this study also tested

the relative importance of power distance orientation. Contrary to prior research findings (e.g.,

Lian et al., 2012), this study indicates that power distance orientation is not as important as prior

studies have indicated. Future research should continue to examine the role of power distance

orientation with more contextual factors considered at the same time.

Second, in this study, I was able to use appropriate statistical models to test the

corresponding hypotheses. Especially for the relationship between abusive supervision and

outcomes, I hypothesized that two moderators and one mediator influence the above-mentioned

relationships. Specifically, I hypothesized that interactional justice serves as the mediator, and

such mediated relationships are different for employees with different power distance orientation

and different job types. In other words, this model also answers the questions of whether

interactional justice serves as the mediator that could explain why abusive supervision interacts

with power distance and job type to explain the employee outcomes. To test these effects

simultaneously in a multilevel situation, I used a multilevel moderated mediation model to test

these moderated mediation effects to examine how abusive supervision influences employee

outcomes. By using this model, I was able to test all the related effects simultaneously rather

than using a piece-meal approach. This model considers mutual influences among these variables

and therefore provides more reliable results.

Third, I used a multiple-wave multilevel-source design to collect the data. I collected data

in three waves with a month time interval, and two data sources, from both supervisors and

subordinates. This data collection procedure helps mitigate the influence of common method bias

(Podsakoff, MacKenzie, & Podsakoff, 2012). In addition, to guarantee the quality of the data, I

also used all validated scales to measure the constructs and the obtained reliabilities are all

acceptable.

However, this dissertation is not free of limitations. Similar to all studies using cross-

sectional data, this study cannot draw conclusions on the casual relationships among variables.

Although in this study, I used a multiple-wave design to collect data, with the predictor,

mediator, and outcomes collected sequentially, I could not confidently establish casual directions

by ruling out other possibilities. In the future, researchers could use other approaches, such as

experiments, to draw conclusions based on casual relationships.

One limitation of this study is dichotomizing all jobs into white-collar vs. blue-collar

employees. Research on job classification has indicated that although most people generally

understand the distinction between “white-collar” and “blue-collar” and use these terms in their

daily lives, the distinction is not so clear especially when it comes to “low-level” white-collar

jobs (DeVault, 1990). “Low-level” white-collar employees, such as clerical and sales workers,

are wage employees that have little personal control and may work in similar employment

situations as employees traditionally labeled as blue collar. For the blue-collar employees in this

study, they are all from a textile manufacturing company and work in different departments that

are responsible for the different steps of producing textile products. They typically have six to

nine years of education and work on irregular shifts with very low wages doing repetitive tasks.

In contrast, in this study, white-collar employees include urban planning/designing employees

and employees working in key professional functional departments in companies such as human

recourses and finance. All these employees have very decent salaries and high education, usually

a bachelor’s degree or master’s degree. The distinction in my sample is very clear in terms of

white-collar vs. blue-collar, or professional vs. non-professional workers. This sample provides a

strong basis for revealing the potential differences among these two major job categories. In the

future, researchers should consider examining the influence of job types in more refined

categories and provide more detailed results.

Another limitation of this study is the use of samples from a single country. Because

power distance orientation is a key moderator in my model, ideally, I should collect data from

multiple cultures. Collecting data from a single country, namely China in my study, may raise

the concern that scores for power distance orientation have range restriction. Range restriction is

a phenomenon where the variance of a variable in a particular sample is smaller than the variance

of the variable in the large population (Cohen et al., 1983). Range restricted data may shrink the

obtained effect size in the analysis. However, when I compared the power distance orientation

data from this study to other studies that have used samples from multiple countries, I found that

the standard deviation in my sample (SD = .73) is very similar to the standard deviations from

those cross-cultural samples (e.g. SD = .70, Cavazotte, Hartman, & Bahiense, 2014; SD = .77,

Vogel et al., 2015). This may indicate that the power distance orientation is not range-restricted

in my sample.

In the context of globalization, researchers have noted the convergence of cultural values

among different countries (Sarala & Vaara, 2010; Ralston, Holt, Terpstra, & Kai-Cheng, 1997).

For example, the GLOBE project has found that the power distance orientations of people from

different cultures are quite similar to each other (GLOBE, 2004). With a 7-point Likert Scale, the

overall mean value across different cultures was 2.75. Specifically, the mean value in China was

3.1, the mean value in Thailand was 2.86, the mean value in the U.S. was 2.85, the mean value in

France was 2.76. This indicates that the cultural differences are not as large as previously

thought. Therefore, it is less likely that data from a single country in this study is associated with

severe range restriction issues. On the other hand, I also suggest future research to study abusive

supervision with data from multiple cultures to obtain a better understanding of the role of

cultural values such as power distance orientation.

6.6 Conclusions

This dissertation aims to understand the leader personality traits as antecedents and the

mechanisms regarding how abusive supervision influences employee outcomes. The findings

supported that leader personality, especially leader agreeableness is an important predictor.

Leader narcissism also has an impact on abusive supervision, and its effects depend on the

ethical climate perception. In addition, the results indicated that job type is an important

boundary condition for the abusive supervision-employee outcome relationships. Interactional

justice only mediates the abusive supervision-employee outcome relationships for white-collar

employees but not blue-collar employees. These results challenge the generalizability of prior

studies in the abusive supervision literature that has relied on white-collar employees as samples.

Moreover, the results indicated that power distance orientation is not as important as prior

research suggests, especially compared with other moderators such as job type examined in this

study. This is unexpected, but it may suggest that in the workplace, how employees respond to

abusive supervision is largely influenced by other factors and cultural values play a less

significant role.

APPENDIX

APPENDIX. Measures and Survey Items

Big five (John, Donahue, & Kentle, 1991)

How much do you agree with the following statements? I am generally…

Agreeableness

1 Is considerate and kind to almost everyone

2 Likes to cooperate with others

3 Is helpful and unselfish with others

4 Has a forgiving nature

5 Is generally trusting

6 Tends to find fault with others (RC)

7 Starts quarrels with others (RC)

8 Can be cold and aloof (RC)

9 Is sometimes rode to others (RC)

Neuroticism

1 Worries a lot

2 Can be tense

3 Gets nervous easily

4 Is depressed, blue

5 Can be moody

6 Remains calm in tense situations (RC)

7 Is emotionally stable, not easily upset (RC)

8 Is relaxed, handles stress well (RC)

Trait aggressiveness (Bryant & Smith, 2001)

How much do you agree with the following statements?

1 Given enough provocation, I may hit another person.

2 There are people who pushed me so far that we came to blows.

3 I have threatened people I know.

4 I often find myself disagreeing with people.

5 I can't help getting into arguments when people disagree with me.

6 My friends say that I'm somewhat argumentative.

7 I flare up quickly but get over it quickly.

8 Sometimes I fly off the handle for no good reason.

9 I have trouble controlling my temper.

10 At times I feel I have gotten a raw deal out of life.

11 Other people always seem to get the breaks.

12 I wonder why sometimes I feel so bitter about things.

Dark triad (Jonason & Webster, 2010)

How much do you agree with the following statements?

1 I tend to manipulate others to get my way.

2 I have used deceit or lied to get my way.

3 I have use flattery to get my way.

4 I tend to exploit others towards my own end.

5 I tend to lack remorse.

6 I tend to not be too concerned with morality or the morality of my actions.

7 I tend to be callous or insensitive.

8 I tend to be cynical.

9 I tend to want others to admire me.

10 I tend to want others to pay attention to me.

11 I tend to seek prestige or status.

12 I tend to expect special favors from others.

Ethical climate (Victor & Cullen, 1988)

1 What is best for everyone in the company is the major consideration here.

2 The most important concern is the good of all the people in the company as a whole.

3 Our major concern is always what is best for the other person.

4 In this company, people look out for each other's good.

5 In this company, it is expected that you will always do what is right for the customers and

public.

6 The most efficient way is always the right way in this company.

7 In this company, each person is expected above all to work efficiently.

Abusive supervision (Tepper, 2000)

How often does your direct leader treat you in the following ways:

1 Ridicules me

2 Tells me my thoughts or feelings are stupid

3 Gives me the silent treatment

4 Puts me down in front of others

5 Invades my privacy

6 Reminds me of my past mistakes and failures

7 Doesn't give me credit for jobs requiring a lot of effort

8 Blames me to save himself/herself embarrassment

9 Breaks promises he/she makes

10 Expresses anger at me when he/she is mad for another reason

11 Makes negative comments about me to others

12 Is rude to me

13 Does not allow me to interact with my coworkers

14 Tells me I'm incompetent

15 Lies to me

Power distance orientation (Dorfman & Howell, 1988)

How much do you agree with the following statements?

1 It is frequently necessary for a manager to use authority and power when dealing with

subordinates

2 Employees should not disagree with management decisions

3 A supervisor's use of authority and power is often necessary in order to assure that work

is done efficiently.

4 Social interaction with one's subordinates may decrease a manager's ability to be

objective in dealing with subordinates.

5 Managers should make most decisions without consulting subordinates

6 Managers should not delegate important tasks to employees.

Interactional justice (Colquitt, 2001)

The following items refer to (the authority figure who enacted the procedure). To what

extent:

1 Has (he/she) treated you in a polite manner?

2 Has (he/she) treated you with dignity?

3 Has (he/she) treated you with respect?

4 Has (he/she) refrained from improper remarks or comments?

5 Has (he/she) been candid in (his/her) communications with you?

6 Has (he/she) explained the procedures thoroughly?

7 Were (his/her) explanations regarding the procedures reasonable?

8 Has (he/she) communicated details in a timely manner?

9 Has (he/she) seemed to tailor (his/her) communications to individuals' specific needs?

Job performance (Liden et al., 1993)

How much do you agree with the following statements? This subordinate is…

1 Rate the overall level of performance that you observe for this subordinate

2 What is your personal view of your subordinate in terms of his or her overall

effectiveness?

3 Overall, to what extent do you feel your subordinate has been effectively fulfilling his or

her roles and responsibilities?

4 Overall, to what extent do you feel the subordinate is performing his job the way you

would like it to be performed?

OCB (Lee & Allen, 2002)

How much do you agree with the following statements? This subordinate is…

1 Help others who have been absent.

2 Willingly give your time to help others who have work-related problems.

3 Adjust your work schedule to accommodate other employees’ requests for time off.

4 Go out of the way to make newer employees feel welcome in the work group.

5 Show genuine concern and courtesy toward coworkers, even under the most trying

business or personal situations.

6 Give up time to help others who have work or nonwork problems.

7 Assist others with their duties.

8 Share personal property with others to help their work.

9 Attend functions that are not required but that help the organizational image.

10 Keep up with developments in the organization.

11 Defend the organization when other employees criticize it.

12 Show pride when representing the organization in public.

13 Offer ideas to improve the functioning of the organization.

14 Express loyalty toward the organization.

15 Take action to protect the organization from potential problems.

16 Demonstrate concern about the image of the organization.

Creativity (Zhou & George, 2001)

1 Suggests new ways to achieve goals or objectives.

2 Comes up with new and practical ideas to improve performance.

3 Promotes and champions ideas to others.

4 Exhibits creativity on the job when given the opportunity to.

5 Comes up with creative solutions to problems.

CWB (Bennett & Robinson, 2000)

How much do you agree with the following statements? This subordinate is…

1 Made fun of someone at work

2 Said something hurtful to someone at work

3 Cursed at someone at work

4 Played a mean prank on someone at work

5 Acted rudely toward someone at work

6 Publicly embarrassed someone at work

7 Spent too much time fantasizing or daydreaming instead of working

8 Taken an additional or longer break than is acceptable at your workplace

9 Come in late to work without permission

10 Neglected to follow your boss's instructions

11 Intentionally worked slower than you could have worked

12 Put little effort into your work

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