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Bauer, Jeremy Allen.
The role of discrete emotions in predicting counterproductive work behavior
h [electronic resource] /
by Jeremy Allen Bauer.
[Tampa, Fla] :
b University of South Florida,
Title from PDF of title page.
Document formatted into pages; contains 121 pages.
(M.A.)--University of South Florida, 2011.
Includes bibliographical references.
Text (Electronic thesis) in PDF format.
ABSTRACT: The current study investigates how discrete negative emotions are related to specific facets of counterproductive work behaviors (CWB). The sample consisted of 241 employees who reported their frequency of experiencing negative emotions and their frequency of committing CWBs in the workplace. For 103 employees, supervisor reports of employee CWB were also obtained. The findings provide evidence that a wide range of negative emotions are related to most of the sub facets of CWB. There was also some evidence that supervisor reports differ systematically from employee reports of CWB. The theoretical, methodological, and organizational implications are discussed.
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Spector, Paul .
x Occupational Psychology
t USF Electronic Theses and Dissertations.
The Role of Discrete Emotions in Predicting Counterproductive Work Behavior by Jeremy A. Bauer A thesis submitted in partial fulfillment of the requirements for the degree of Masters of Arts Department of Psychology College of Arts & Sciences University of South Florida Major Professor: Paul Spector, Ph.D. Russell E. Johnson, Ph.D. Jennifer Bosson, Ph.D. Date of Approval: January 14 th 2011 Keywords: affect, deviance, sabotage, withdrawal, theft, undermining, horseplay, a buse, anger, anxiety, shame, envy, jealousy, boredom Copyright 2011, Jeremy A. Bauer
Dedication I dedicate this thesis to my family and girlfriend who have supported me throughout my education. There endless patience and sacrifice have allowed me the freedom to focus on my work. I could not have done it without them. I would also like to thank Dr. Spector, Dr. Bosson, and Dr. Johnson for helping me to conduct this research project. Their knowledge and advice was essential i n crafting this manuscript. Similarly, their mentorship has helped to mold me as a professi onal. Thank you all!
i Table of Contents List of Tables ..................................................................................................................... iii List of Figures .................................................................................................................... vi Abstract ............................................................................................................................ viii Chapter One: Introduction ...................................................................................................1 Counterproductive Work Behavior ..........................................................................2 Affect in the Organization .......................................................................................5 Theoretical Lens: The Link Between Emotions and CWB ..................................11 Emotions Associated with Attributions .....................................................15 Workplace Anger ...........................................................................15 Workplace ShameÂ…Â…Â…Â…Â…Â…..Â…Â…Â…Â…Â…Â…Â…Â….. ..............18 Emotions Not Related to Attributions........................................................20 Workplace Envy.............................................................................20 Workplace Jealousy .......................................................................22 Workplace Anxiety ........................................................................24 Workplace Sadness ........................................................................25 Workplace Boredom ......................................................................27 Research Questions ........................................................................29 Chapter Two: Method ........................................................................................................31 Participants .............................................................................................................31 Procedure ...............................................................................................................31 Measures ................................................................................................................32 Anger, anxiety, and sadness .......................................................................33 Shame ........................................................................................................33 Envy and Jealousy......................................................................................34 Boredom .....................................................................................................34 Adjective List .............................................................................................35 CWB ........................................................................................................35 Chapter Three: Results .......................................................................................................37 Power Analysis ......................................................................................................37 Correlational Analysis ...........................................................................................37 Chapter Four: Discussion ...................................................................................................70 Comparing the Negative Emotions ........................................................................72 Comparison of Employee and Supervisor Data .....................................................74
ii Comparing the Two Sets of Emotion Measures ....................................................76 Limitations .............................................................................................................77 Conclusion ....................................................................................................Â…. ...78 List of References .....................................................................................................Â…. ...80 Appendix A: Extra Information .................................................................................Â… ...93 Appendix B: Survey Materials...........................................................................................99
iii List of Tables Table 1: Descriptive Statistics ............................................................................................38 Table 2: Correlation Matrix of Emotion and CWB Measures with Employee Data .....................................................................................................................................40 Table 3: Correlation Matrix of Supervisor Reported CWB ................................................42 Table 4: Supervisor Reported CWB Correlated with All Employee Reported Variables .............................................................................................................................43 Table 5: Comparison of the Anger and CWB Correlations Between Sources ...................45 Table 6: Comparison of the Anxiety and CWB Correlations Between Sources ................45 Table 7: Comparison of the Sadness and CWB Correlations Between Sources ................46 Table 8: Comparison of the Boredom and CWB Correlations Between Sources ..............46 Table 9: Comparison of the Envy and CWB Correlations Between Sources .....................47 Table 10: Comparison of the Jealousy and CWB Correlations Between Sources .............47 Table 11: Comparison of the Shame and CWB Correlations Between Sources ................48 Table 12: Comparison of Anger Scale Correlations with CWB .........................................48 Table 13: Comparison of Anxiety Scale Correlations with CWB ......................................49 Table 14: Comparison of Sadness Scale Correlations with CWB ......................................49 Table 15: Comparison of Boredom Scale Correlations with CWB ....................................50 Table 16: Comparison of Envy Scale Correlations with CWB ..........................................50 Table 17: Comparison of Jealousy Scale Correlations with CWB .....................................51 Table 18: Comparison of Shame Scale Correlations with CWB ........................................51
iv Table 19: Employee Reported Sabotage Regressed Onto Discrete Emotions .................... 53 Table 20: Employee Reported Abuse Regressed onto the Discrete Emotions ...................53 Table 21: Employee Reported Production Deviance Regressed onto the Discrete Emotions .............................................................................................................54 Table 22: Employee Reported Withdrawal Regressed onto the Discrete Emotions .............................................................................................................54 Table 23: Employee Reported Theft Regressed onto the Discrete Emotions ....................55 Table 24: Employee Reported Horseplay Regressed onto the Discrete Emotions .............55 Table 25: Employee Reported Social Undermining Regressed onto the Discrete Emotions .............................................................................................................56 Table 26: Supervisor Reported Sabotage Regressed onto the Discrete Emotions ..............56 Table 27: Supervisor Reported Abuse Regressed onto the Discrete Emotions ..................57 Table 28: Supervisor Reported Production Deviance Regressed onto the Discrete Emotions ..............................................................................................57 Table 29: Supervisor Reported Withdrawal Regressed onto the Discrete Emotions .............................................................................................................................58 Table 30: Supervisor Reported Theft Regressed onto the Discrete Emotions....................58 Table 31: Supervisor Reported Horseplay Regressed onto the Discrete Emotions ............59 Table 32: Supervisor Reported Social Undermining Regressed onto the Discrete Emotions .............................................................................................................59 Table 33: Boredom as a Moderator of the Anger-Theft Relationship Using Employee Data. ..................................................................................................60 Table 34: Boredom as a Moderator of the Anger-Sabotage Relationship Using Supervisor Data. .................................................................................................60 Table 35: Boredom as a Moderator of the Anger-Abuse Relationships Using Supervisor Data. .................................................................................................61 Table 36: Boredom as a Moderator of the Anger-Production Deviance Relationship Using Supervisor Data ..................................................................61
v Table 37: Boredom as a Moderator of the Anger-Social Undermining Relationship Using Supervisor DataÂ…Â…Â…Â…Â…Â…Â… ......................................62 Table 38: Shame as a Moderator of the Anger-Abuse Relationships Using Employee Data. ..................................................................................................62 Table 39: Shame as a Moderator of the Anger-Withdrawal Relationship Using Employee Data. ..................................................................................................63 Table 40: Shame as a Moderator of the Anger-Social Undermining Relationship Using Employee Data. ........................................................................................63 Table 41: Shame as a Moderator of the Anger-Theft Relationship Using Supervisor Data. .................................................................................................64
vi List of Figures Figure 1 Anger and Boredom Interacting to Predict Theft Using Employee Data. ............65 Figure 2: Anger and Boredom Interacting to Predict Sabotage Using Supervisor Data. ....................................................................................................................................65 Figure 3: Anger and Boredom Interacting to Predict Abuse Using Supervisor Data .....................................................................................................................................66 Figure 4: Anger and Boredom Interacting to Predict Production Deviance Using Supervisor Data ..................................................................................................66 Figure 5: Anger and Boredom Interacting to Predict Social Undermining Using Supervisor Data....................................................................................................67 Figure 6: Anger and Shame Interacting to Predict Abuse Using Employee Data ..............67 Figure 7: Anger and Shame Interacting to Predict Withdrawal Behaviors Usi ng Employee Data. ....................................................................................................68 Figure 8: Anger and Shame Interacting to Predict Social Undermining Usin g Employee Data. ..................................................................................................68 Figure 9: Anger and Shame Interacting to Predict Theft Using Supervisor Da ta. .............69 Figure 1A: Illustration of how the CWB and related constructs overlap ...........................94 Figure 2A: Reproduced stressor-emotion model from Spector & Fox (2005). ..................95 Figure 3A: A reproduction of Perrew & ZellarÂ’s (1999) appraisal-att ribution model...................................................................................................................................96 Figure 4A: Summary of Hypotheses and Proposed Analyses ............................................97 Figure 5A: Expected Relationships Among Study Variables .............................................98 Figure 1B: Workplace Boredom Scale ...............................................................................100 Figure 2B: STPI Anger & Anxiety .....................................................................................101
vii Figure 3B: State-Trait Depression Subscale (Speilberger, 1979) .......................................102 Figure 4B: Experience of Shame Scale (Andrews, Qian, and Valentine, 2002) ................103 Figure 5B: Envy and Jealousy Items ..................................................................................104 Figure 6B: Emotional Adjective List ..................................................................................105 Figure 7B: Counterproductive Work Behavior Checklist (CWB-C) ..................................106 Figure 8B: Bruursema (2007) Horseplay Items ..................................................................108 Figure 9B: Social Undermining (Duffy, 2002) ...................................................................109 Figure 10B: Instruction Booklet .........................................................................................111
viii Abstract The current study investigates how discrete negative emotions are related t o specific facets of counterproductive work behaviors (CWB). The sample consisted of 241 employees who reported their frequency of experiencing negative emotions a nd their frequency of committing CWBs in the workplace. For 103 employees, supervisor report s of employee CWB were also obtained. The findings provide evidence that a wide ran ge of negative emotions are related to most of the sub facets of CWB. There was a lso some evidence that supervisor reports differ systematically from employee r eports of CWB. The theoretical, methodological, and organizational implications are discussed.
1 Chapter One: Introduction Researchers have been interested in the organizational role of affect, otherw ise referred to as emotions, for at least the past 80 years (for an early exam ple see Hersey, 1932) and the subject has become increasingly popular since the 1990s (Ashkanasy & Ashton-James, 2005). Affect is also popular in the stress literature (e.g. Laza rus, 1999; Lee & Allen, 2002; Spector & Fox, 2002). Previous research has demonstrated the ability of affect to influence workplace behaviors and attitudes (e.g. Judge, S cott, & Ilies, 2006; Kaplan et al., 2009) as well as employee well being and physical hea lth (Lazarus & Folkman, 1984). One growing area of interest is the role of aff ect as a predictor of counterproductive workplace behaviors (CWB). CWBs are volitional acts that harm an organization or the organizationÂ’s stake holders (Spector & Fox, 2005). CWB is considered a facet of job performance (Sackett, 2002) which can have a devastating effect on the functioning of an organization (Hollinger & Clark, 1983). Unfortunately there are several methodological and conceptual issues that lim it the generalizability of this research. For instance, there is a dearth of studi es that maintain a high level of specificity. Affect can be conceptualized as several discre te emotions (e.g. anger, sadness, envy, shame, anxiety, boredom, and jealousy) and CWB is comprised of several facets (i.e. abuse, productions deviance, theft, sabotage, withdrawal, horse play, and social undermining). However, researchers rarely investigate the i nter-relationships between these more specific facets of each construct. The present paper contends t hat much information can be gained from examining discrete emotions and facets of C WB
2 as unique variables, rather than using a general measure or a composite score. B y maintaining this level of specificity, it is possible to determine if discr ete negative emotions relate differently to the facets of CWB. In line with the fidelit y-bandwidth notion (i.e., Hogan & Roberts, 1996), the current study examines the relationship between discrete negative emotions and specific dimensions of CWB. In the next section, I formally define CWB and discuss several of the fac ets that are expected to be related to discrete emotions. After this discussion sever al sections are dedicated to addressing the research related to organizational affect, foc using on several conceptual and methodological issues. The stressor-emotion-CWB process is r eviewed and each discrete emotion is linked to subsequent facets of CWB while accounting for the measurement issues. More specifically, I include a wide range of nega tive emotions that encompass several different bodies of literature and develop hypotheses t hat link them to CWB. Finally, I formally test the hypotheses with an empirical s tudy. Counterproductive Work Behavior Differences between CWB and other related terms (e.g. aggression, deviant behaviors, organizational retaliatory behavior, incivility, and bullying) have be en discussed at length (Spector & Fox, 2005). See Figure 1A for an illustration of how the constructs overlap (Raver, 2005). Examples of CWB include gossip, theft, verbal/physical abuse, and withdrawal. Previous measures of CWB have differ ent categorizations of the construct (e.g. Hollinger & Clark, 1983; Robinson & Bennett, 1995; Spector et al., 2006). Hollinger and Clark (1983) divided CWB into production deviance (deviant behavior in regards to how and when to work) and property deviance
3 (breaking organizational assets). Robinson and Bennett (1995) divided CWB based on the target (organizational vs. interpersonal) and the severity. Spector et al. ( 2006) developed a CWB checklist that categorized CWBs into five different categor ies that consist of abuse against others, production deviance, theft, withdrawal, and sabotage. Abuse is a set of aggressive behaviors that are direct and focused towards someone els e in the organization. Although these abusive behaviors are often verbal, physical abuse is also included in this facet of CWB. Threats, nasty comments, pushing, and mean pranks are all examples of abusive behavior. There are also some abusive behaviors that a re considered more covert. For instance, gossiping, ignoring a coworker, or blaming someone else for your mistakes are abusive behaviors but an employee is less l ikely to be caught or reprimanded. Although Spector et al. (2006) did not make the distinction between covert and overt abuse, it is an important distinction to make for the current study. Theft is considered stealing from the organization. Examples of theft a re taking resources home without permission from the employer and lying about the amount of time an employee has spent working. Withdrawal can be defined as working less t ime than the organization expects you to work. Examples of withdrawal are absence, tardiness, and taking longer breaks than the organization allows. Production deviance i s the purposeful failure to complete tasks correctly. Examples consist of not foll owing directions and working slower than expected. Similarly, sabotage is destroying physical property that belongs to the employer. Spector et al.Â’s (2006) five facet scale i s the most specific overall CWB scale that has been published. Since the goal of the current study is to investigate how discrete emotions pr edict specific types of CWB, I will adopt Spector et alÂ’s (2006) five facet conceptua lization of
4 CWB. However, this framework does not include some CWBs that are relevant to the current study. For instance, some employees could sabotage the progress of their coworkers by giving them misleading information or hindering the coworkerÂ’s pro gress in the organization. This behavior is considered an example of social undermining. Social undermining consists of behaviors that are intended to harm the reputation, success, and interpersonal relationships of the target employee (Duffy, Gans ter, & Pagons, 2002) Social undermining does not fit exclusively into one of the five facets of Spector et al.Â’s (2006) framework. Sabotage is damaging the employerÂ’s proper ties so the current examples would not formally be considered sabotage because they are focused at harming the progress of a coworker. The abuse against others facet c ontains some similar behaviors (i.e. made someone look bad in the organization, blamed someone for your mistake) but they are lumped together with other behaviors that should remain distinct for the current study (i.e. physical aggression, threat s, and insults). They also do not adequately represent the range of social undermining behaviors that are possible. Another CWB that Spector et al. (2006) did not include is horseplay. Horseplay is defined as a non-malicious behavior intended to make the work environment livelier or more entertaining (Bruursema, 2007). Some examples of horseplay are using the internet at work for non-work related purposes, engaging in non-malicious gossiping or joking for the purposes of entertainment, and wasting company resources solely fo r the purpose of entertainment. Although horseplay and production deviance overlap conceptually, there is a distinction between the constructs. It is possible for e mployees to complete all their work tasks correctly (i.e. not considered production deviance) a nd still
5 participate in gossiping or practical jokes (i.e. horseplay). Horseplay is a r elatively new facet of CWB but Bruursema (2006) has demonstrated that it is an important CWB to include when investigating certain emotions (i.e. Boredom). Affect in the Organization Three conceptual issues must be addressed before discrete emotions can be defined and linked to CWB. For instance, several terms are used to reflect the stabil ity of a feeling. Affect can be conceptualized at the state, trait, or mood level. Aff ect at the state level is a transient emotion that is typically dependent on a particular event. Measuring state affect tends to assess how the participant is feeling at the exact time of the study. Mood is conceptualized as an affective state that lasts for a longer period of time than state affect. Trait affect is considered a dispositional tendenc y to be in a particular emotional state (Ashkanasy & Ashton-James, 2005; Watson 2000). The trait level can be thought of as a temperament or a personality characteristic (Br ief & Weiss, 2002; Watson, 2000). Finally, affect can also be measured in particular contexts suc h as the workplace. Thus, it is important to address what level of stability you are investigating. Another conceptual issue is that affect spans several level s of specificity. Measurement of emotions at the general level combines several specific em otions into a broader category. Affect is often operationalized as a participantÂ’s sco re on positive affectivity (PA) and negative affectivity (NA) scales. At the trait level individuals high in NA have a tendency to experience global negative emotional states (e.g. anxi ety, depression, and hostility; Brief & Weiss, 2002; Watson & Clark, 1984) and individuals high in PA have a tendency to experience global positive emotional states (e.g pride and
6 happiness; Watson, Clark, & Tellegen, 1988). Affect measured at a more specific l evel of emotion maintains the distinction among individual emotions (e.g., anger and anxiety). Thus, it is also important to address what level of specificity you a re investigating. Based on the previous discussion, there are two dimensions (i.e. stability and specificity) that must be considered when conceptualizing affect. However, B riner and Kieffer (2005) reviewed the workplace affect literature and found that more t han 60% of affect-focused empirical articles fail to offer a clear and accura te definition of affect. Therefore, stability and specificity will be used to provide a clear defini tion of discrete emotions and mood. Discrete emotions can be described as a temporary (state leve l) affective reaction to some specific event (internal or external) that i s typically more intense than general affective terms such as mood (Gooty 2007; Lee & Allen, 2002). This definition identifies discrete emotions as being specific and occurring at the state level. Moods, however, are conceptualized as an affective state that does not require a specific event and lasts for a longer period of time than a discrete emotion. So, moods are more stable and less specific than discrete emotions. A final conceptual issue related to organizational affect is the difference b etween negative and positive discrete emotions. The current study focuses on negative emotions for several reasons. In general, the evidence seems to suggest that negative emotions are more highly related to aggressive and counterproductive behaviors than positive emotions (e.g. Bruursema, 2007, Judge, Scott, & Ilies, 2006, Lee & Allen, 2002, Spector & Fox, 2005). In addition, Hersey (1932) reported that negative emotional states lead to a decrease in productivity but positive emotional states did not lead to an increase in
7 productivity. Supporting previous research, Lee and Allen (2002) failed to find evidence that positive emotions predicted any workplace behaviors, including organizational citizenship behavior (OCB). They also mention Watson and ClarkÂ’s (1991, 1992) conclusion that positive emotions are less distinguishable than negative emotions. If positive emotions are less distinguishable than negative emotions, they should be les s helpful in differentially predicting specific types of CWBs because em otions that greatly overlap each other should have similar or identical relationships with other variables Thus, positive discrete emotions may not be an appropriate set of emotions to differentiate between specific types of CWB. Also, research has provided som e evidence that negative events can lead to stronger physiological and subjective affect ive reactions than positive events (Taylor, 1991). Hence, it is expected that negative emotions are more intense and have more serious implications for the organization. In addition to conceptual issues, there are also methodological issues that must be addressed before investigating the relationship between discrete emotions and CWB. For instance, the majority of research on organizational affect has not focus ed on discrete emotions (Brief & Weiss, 2002). Instead, a disproportionate amount of res earch has focused on more global aspects of affect (i.e. negative and positive affec t). Even studies claiming to measure emotions often do not clearly make the distinction. The research on NA and PA has demonstrated its utility (Bolger & Zuckerman, 1995), but it would be hard to argue that aggregating negative emotional states does not lead to a subsequent loss of information. For instance, sadness and anger do not predict the same behaviors (Chen & Spector, 1992; Lee & Allen, 2002). Thus, combining emotional states may not always be appropriate when there is evidence to suggest that they are
8 conceptually distinct in regards to predicting the outcome of interest. Specifica lly, patterns of appraisal and behavioral reactions have been found to differ among discret e reactions (e.g., Lee & Allen, 2002; Perrew & Zellars, 1999; Weiner, 1985). Des pite the importance of discrete emotions in predicting organizational outcomes (Lee & All en, 2002; Vecchio, 2000), Briner and Kieffer (2005) found that fewer than half of studies investigating emotions did not measure emotions at this level of specificity. T his lack of attention to discrete emotions is especially disconcerting because resea rch in this area has generally found that these discrete emotions are significant predictors of several organizational outcomes (e.g. Chen & Spector, 1992; Cohen-Charash & Mueller, 2007; Judge, Scott, & Ilies, 2006; Lee & Allen, 2002). This line of logic parallels the fi delitybandwidth issue in the personality literature (i.e., Hogan & Roberts, 1996). Global measure of personality were found to be better predictors of outcomes that we re measured at a global level, whereas, specific measures of personality a re better predictors of more specific organizational outcomes than global measures (Ashton, 1998). Applying this concept to emotions, more global measures (e.g. mood) should better predict global measures of organizational outcomes (i.e. counterproductive w ork behaviors; CWB) while specific measures (i.e. discrete emotions) should bett er predict specific organizational outcomes (e.g., sabotage, theft, gossip, and lateness). Another methodological issue, specific to research on affect, is the lack of studies that compare and contrast the effect of more than a few negative discrete emotions. Although at least 9 discrete negative emotions have been identified (Bruursema, 2007; Lazarus, 1999), there have been few studies besides Lee and Allen (2002) that have included more than one or two discrete emotions. Often, researchers
9 only include a specific family of negative emotions. For instance, aggression s tudies tend to include emotions that are believed to be intense and outward focused (i.e. anger & frustration; Chen & Spector, 1992). It is appropriate to measure frustration a nd anger in aggression studies because, theoretically, both emotions are elicited when the employee blames the environment for the emotion-eliciting event. The exter nal attribution of blame can then lead to outward focused behaviors such as aggression (Allred, 1995). Aggression towards the target is expected because it can serve as a deterrent for future aggravating events or because failures in self-regula tion can allow intense emotions (i.e. frustration and anger) to elicit strong behavioral rea ctions (i.e. aggression). Similarly, studies dealing with self-conscious emotions often focus exclusivel y on guilt, shame, jealousy or envy (see Tangney, 1999). These emotions are popular in the social psychology literature but they have been largely ignored in organizat ional research. Guilt is the dysphoric feeling associated with the recognition t hat one has violated a personally relevant moral or social standard (Kugler & Jones, 1992). Sha me can be considered a negative affective reaction that creates a negative glob al evaluation of the self (Hareli, Shomrat, & Biger, 2005). Guilt and shame are often studied toge ther because they are both inward focused emotions that share some conceptual overlap. These two emotions are often combined or confused for one another but the literature has established their independence (Tangney, 1999). Envy can be conceptualized as a negative emotion felt when a person lacks anotherÂ’s superior quality, achievement, or possession and either desires it or wishes that the other lacked it (Parrot & S mith, 1993). Jealousy is a negative emotion that is experienced when a person is worried about l osing
10 an important relationship to a rival. Jealousy and envy are often studied together becaus e both share a preoccupation with the resources available to another person. These emotions are also often confused but they are theoretically distinct (Parrott & Smith, 1993). Indeed, it appears that emotions tend to be studied together when there is some degree of overlap between the emotions (i.e. frustration & aggression, guilt & shame jealousy and envy). However, I will later argue that there is enough e vidence to include a wide range of discrete emotions in predicting certain organizational behaviors (i.e. CWB). As mentioned previously research tends to either focus on frustration or anger (e.g. Chen & Spector, 1992) or on self-conscious emotions (e.g. Tangney & Fisher, 1995). However, there is some evidence that each group of emotions has similar relationships with the same outcome variables (i.e. shame, anger, frustration, bore dom, and envy have all been related to aggression). In this case, it is not possible to det ermine which emotion is more important in predicting that particular behavior because ea ch group of emotions was measured separately. It is also impossible to investigat e how these emotions work in tandem to predict behavior in the organization. Because individuals are thought to be able to experience several emotions simultaneously (Lazarus & Cohen-Charash, 2001), and because employees experience a wide ran ge of emotions within the organization (Ashkanasy & Ashton-James, 2005), it is important t o investigate how all of these discrete emotions operate together within organiz ation. Finally, there are some studies that do measure several negative emotions but combine them into a single measure for analyses (e.g. Spector et al., 2006). For inst ance, the Job Affective Well Being Scale measures several discrete emoti ons but it is then
11 combined to form several different factors (i.e. positive versus negative, by hig h versus low arousal; Van Katwyk, Fox, Spector, & Kelloway, 2000). Although this approach is increasing the bandwidth of the measure it is also losing fidelity. That is, agg regation allows a single score to incorporate several factors (i.e. emotions), but it lose s predictive validity when trying to predict specific outcomes. Therefore, there is stil l a need for discrete negative emotion research that includes a wide array of emotions. Theoretical Lens: The Link Between Emotions and CWB Several streams of research imply that affect is related to CWB. One theor etical rationale is that pain motivates an individual to aggress against others (Berkowi tz, 1998). In this case, Berkowitz (1998) suggests that stressors (e.g. distressi ng conditions) elicit an intense negative affect that results in aggressive reactions. S ince many CWBs are considered aggressive, negative affect and CWBs should be related. Howe ver, this research tends to focus on feelings of anger or frustration and aggressive a cts. More recent research has extended the focus to include several types of emotions and CW B. Spector and Fox (2005) proposed a stressor-emotion model that illustrates how negativ e emotions can lead to CWB (See Figure 2A). In this model, environmental stressors l ead to perceived stressors. The perception of stressors then leads to a negative emotion which, in turn, leads to CWB (i.e. strain). The rationale in this model is that employe es are motivated to cease negative feelings. To do so, they may engage in dest ructive behaviors intended to make them feel better. Spector and Fox (2002) conceptualize this as a form of emotion-focused coping because it only makes the employee feel better temporarily, but usually does not solve the problem within the organization. The
12 research mentioned up to this point has addressed the stressor-emotion-CWB proces s at a global level. The next couple sections will include a more detailed review of t he stressor-emotion-behavior process. The transactional model of stress (Lazarus & Folkman, 1984) and research on attributions (e.g. Perrew & Zellars, 1999; Weiner, 1985) can be applied to the stress oremotion model in order to better understand how perceived stressors lead to a specifi c negative emotion. Lazarus and Folkman (1984) proposed a transactional theory of stress that illustrates how information from the environment leads to emotional reactions and behavior. They suggest a primary appraisal determines if the event is beneficial neutral, or threatening to the individual. If the primary appraisal determines that t he event is threatening, a more detailed secondary appraisal occurs to determine the avai lable coping resources, to ascribe blame for the stressor, and to calculate future e xpectations. According to Lazarus and Cohen-Charash (2001), these appraisals are combine d into core-relational themes that elicit a specific negative emotion. To preve nt experiencing these negative emotions, individuals then can engage in coping strategies (i.e ., problem or emotion focused coping) and behavioral reactions. The theory of attribution can further elaborate on this process. Attribution theory assumes that individuals devel op causal explanations of events in order to understand the world. Research has demonstrated that these attributions can predict aggressive behaviors, helping beha viors, and psychological adjustment to illness (i.e. Betancourt & Blair, 1992; Rudolph, Roes ch, & Greitemeyer, Weiner, 2004). The most common attributions generated in an attributional search are those of causality and controllability (Wong & W einer, 1981). The causal attribution determines if the stressful event is due to external (e nvironmental)
13 or internal factors (Weiner, 1985). For instance, a student failing a course ma y blame themselves for not studying correctly or they might blame the teacher fo r making the course too difficult. The control attribution determines if the cause of the stre ssor was controllable (Weiner, 1985). Following the above example, a student who attributes class failure to internal causes may attribute the failure to a lack of ability (not controllable) or to a lack of effort (controllable). Both Weiner (1985) and Perre w and Zellars (1999) have linked attribution theory to the transactional model of stress. Perrew and Zellars (1999) suggest that attributions of causality and controllabi lity initiate specific negative emotions which, in turn, affect the secondary appra isal and subsequent behaviors. See Figure 3A for an illustration of this process. It is impor tant to understand that these attributions can elicit some specific emotions (i.e. sham e, guilt, and anger) but they are not antecedents to all of the discrete emotions. Feeli ngs of anxiety and sadness can be generated by the primary appraisal before causa l and controllable attributions have been considered (Perrew & Zellars, 1999; Weiner 1985). It is also important to realize that emotions do not directly lead to a specific behavioral reaction. Emotions can only energize (i.e. motivate) subsequent behaviors. The next section will illustrate how many other factors can elicit or inhibit a beha vioral reaction to discrete emotions. In addition to emotions, there are many other mechanisms that can influence behavior. External factors could prevent an emotion based behavioral reaction. For instance, an employee would be unable to display physical aggression against a coworker if they work exclusively from home. Similarly, internal processes c an regulate behavior. Emotion regulation may occur when the emotional reaction would be
14 counterproductive to other motivations (i.e. goals and plans). For instance, displayi ng aggression in the workplace may lead to termination so an alternate reaction may b e chosen. Research on anger has found that employees commit less apparent forms of retaliatory behavior when they think about the potential consequences these behaviors may have on their reputation (Allred, 1995). Affective reactions do not have to be behavioral. Folkman and Lazarus (1984) also found that re-appraisal and coping processes can attenuate the relationship between emotion and behavior. If a person i s unable to be overtly aggressive, he or she may reinterpret the event as less sever e or engage in emotion based coping instead of risking termination. Although there are several factors influencing the relationship behavior, evidence still suggests that there is a relationship between emotions and behavior. This study will investigate the relationships of seven discrete negative emotions (i.e. anger, sadness, shame, anxiety, envy, jealousy, and boredom) with C WB. Specifically, predictions will be made regarding which emotions will be relat ed to different types of CWB (i.e. sabotage, theft, abuse, withdrawal, production deviance, horseplay, and social undermining). Research has found these emotions to be important when predicting organizational behavior. Also, these emotions were determined by a literature review to be the most commonly measured discrete negative emot ions. Guilt was not included in the current study because it is not expected to be related to CWB. The majority of the literature relates it to reparative actions such as O CB (Hareli, Shomrat, & Biger, 2005). Similarly, frustration was not included because it is often defined as a lesser form of anger so including it would be redundant. The attribut ion literature will be used to guide the predictions regarding the relationship betw een two of
15 the discrete emotions and CWB (i.e. anger and shame). The locus of the stressor and perceived controllability will be the two main attributions used to generate the se predictions. However, attribution theory is unable to make predictions for some emotions (i.e. boredom, anxiety, sadness, envy, and jealousy). In these cases, I w ill include relevant theory to generate expected relationships. Emotions associated with attributions. Workplace anger. Anger is a negative emotion that occurs when a threat is appraised as a Â“demeaning offense to me and mineÂ” (p. 96; Lazarus, 1999). It is considered a basic emotion (Carver & Harmon-Jones, 2009) that can vary from feeli ngs of irritation to rage (Glomb, 2002; Spielberger & Sydeman, 1994). Previous research has demonstrated that it is related to a higher level of distress (psychologica l and physical) and lasts for a longer period of time than other emotions (Cooper & Fara gher, 1993). Anger has also been more related to approach than avoidant behaviors (Carver & Harmon-Jones, 2009). According to Perrew and Zellars (1999), anger is elici ted when a stressor is due to an external source that is perceived as having control over the s tressor. Organizational examples of external sources consist of coworkers, supervisors and the organization as a whole. Unreasonable task demands, task difficulty, and procedural injustice are some organizational examples of stressors that may be percei ved as controllable. For instance, an organization that delegates promotions based on organizational tenure instead of job performance may elicit anger in some of the ir employees. An employee who fails to receive a promotion may appraise the encounte r
16 as stressful. This appraisal is then followed by an attributional search for c ausality. If the employee was performing better than other coworkers he or she is unlikely t o blame themselves for the failure. Instead, he or she may blame the organization for t he failure because the organization uses tenure as the basis for decisions regarding promot ions instead of productivity. The employee then conducts another attributional search to determine controllability. In this example, the employee may perceive th e organization as in control of their promotion policies. Thus, the employee is expected to experienc e anger because the promotion failure was preventable (i.e. controllable) and caused by the organization (i.e. external). Similar to most discrete emotions, anger is thought to energize behavioral reactions that are intended to reduce the amount of experienced negative emotions. To prevent further exposure to the stressor, and subsequent feelings of anger, employ eeÂ’s can engage in CWBs. For instance, an employee experiencing anger caused b y the organization could display withdrawal behaviors. The employee avoids exposure to the anger eliciting stressor by removing himself or herself from the cause of the stressor (i.e. the organization). More active CWBs (i.e. abuse, theft, production deviance, social undermining, and sabotage) also function to cease negative feelings. These acti ve CWBs can also restore a sense of equity (Skarlicki & Folger, 1997). Theft, for exa mple, may occur if employees are experiencing anger due to perceived injustice rela ted to pay. Similarly, these active CWBs can be focused towards the perceived cause of the stressor to serve as a deterrent against future exposure to the anger provoking event. For instance, if a coworker is the perceived cause of an employeeÂ’s angry feeling s, the employee might display abusive behaviors towards the coworker in order to deter the
17 coworker from making the employee angry again. In this example, the logic of de terring future exposure by targeting the perceived source is dependent on the attribution of controllability. It would not make sense to aggress against coworker if they coul d not have prevented the anger provoking event. Finally, these active CWBs can also le ad to a decrease in negative feelings even if they are not directed at the cause of t he stressor. In organizational settings, it is often risky to become aggressive or counterproduc tive. An employee can experience even more negative feelings when they are unable to re act towards the cause of the stressor. In this case, employees may displace th eir behavioral reactions (i.e. active CWBs) and focus them on an innocent colleague. The liter ature on displaced aggression investigates the mechanisms of this phenomenon but there is no consensus on how behavioral displacement works. However, one explanation is that directing these behavioral reactions towards an innocent is the result of rum ination (Marcus-Newall, Pedersen, Carlson, & Miller, 2000). When individuals are unable to resolve negative feelings they will often ruminate and focus on the negative em otions that are currently being experienced. Therefore, when the individual encounters t he innocent, they are more likely to associate the innocent with the negative feeli ngs. Thus, displaced aggression may be the result of an individual erroneously associating or labeling the innocent as the cause of the stressor. Although more research m ust be done before conclusions can be established, it is apparent that CWBs are one way in whic h employees react to feelings of anger within the organization. Specifica lly, I expect that feelings of anger will be related to withdrawal behaviors as well as more active CWBs Research is generally congruent with these expectations. Anger is consi dered the most important emotion in predicting negative workplace behaviors such as aggress ion
18 (e.g. Chen & Spector, 1992; Fitness 2000; Lazarus & Cohen-Charash, 2001). Barclay Skarlicki, and Pugh (2005) reported that anger and hostility (the disposition to be angr y at a specific target) were significantly related to retaliation a fter a layoff. Similarly, Douglas and Martinko (2001) reported that trait anger is related to workplace a ggression and attitudes towards revenge. Several other studies have also found anger to be rela ted to CWB and similar behaviors such as legal claiming, workplace deviance, and aggression (i.e. Fox & Spector, 1999; Fox, Spector, & Miles, 2001; Goldman, 2003; Lee & Allen, 2002). Therefore, based on the theoretical and empirical implications of previous research: Hyp1: Workplace anger will positively relate to withdrawal behaviors, theft production deviance, abuse, sabotage, and social undermining. Workplace shame. LazarusÂ’ core-relational theme for shame is a threat that indicates the individual is Â“failing to live up to an ego idealÂ” (p.96; Lazarus, 1991). Performance failures and morally incongruent behaviors are examples of eve nts that can elicit feelings of shame within the organization. Unlike guilt, feelings of shame often contain a fundamental threat to the self which can be strongly aversive (Tangney & Fischer, 1995; Tangney, Miller, Flicker, & Barlow, 1996). Indeed, shame is often considered a much more intense emotion than guilt because of the ego threat (Tangne y & Fischer, 1995). This threat to the self often stems from the failure to live up to a n ego ideal (Cohen-Charash & Lazarus, 2001). According to Perrew and Zellars (1999) and Weiner (1985), shame is elicite d by a stressor that is perceived as having an internal cause (i.e. the self) t hat is
19 uncontrollable. An organizational example of uncontrollable would be a lack of ability. This lack of controllability is expected to be particularly stressful for employees. Not only are they failing to perform at a sufficient level, but they do not have the abil ity to change the situation. Thus employees experiencing shame are placed into a toug h situation that leaves them with few avenues to prevent further exposure to the shami ng event. Therefore, employees experiencing feeling of shame are expected t o perceive withdrawal behaviors as the only way to escape the negative emotions. This is congruent with Perrew and ZellarÂ’s (1999) assertion that shame leads to emotion-f ocused coping such as withdrawal or cognitive reappraisal. Similarly, Liu and Perrew (2005) postulated that a lot of the shaming events in the organization (e.g. demotion) are oft en public knowledge and withdrawal is again the only response that may attenuate the feelings of shame. Also, some research has related shame to aggression (e. g. Tangney & Fisher, 1995), but the results have not always been consistent (e.g. Stuewig & Tangn ey, 2007). This relation is often attributed to shame displacement or cognitive reapprai sals. Shame displacement is synonymous with ascribing feelings of shame as due t o an external source. Stated simply, the experience of shame is so intense that it ca uses individuals to reappraise the situation and place blame on someone else. The person experiencing the feelings of shame will then lash out aggressively at the per son that they now perceive as causing the shaming event. Based on the literature, it is not cl ear if this external source is perceived as having control over the situation. I argue that t his shift of blame is a coping mechanism used to protect the individual from the debilitating eff ects of shame. The need for such a mechanism is highlighted by the fact that shame has been related to anxiety, depression, post-traumatic stress disorder, low self-es teem, and eating
20 disorders (Stuewig & Tangney, 2007). However, the externalization of blame may now fit an attributional pattern that is similar to anger (i.e. the threat is caus ed externally). Therefore, shame displacement, through cognitive reappraisal, may shift the t ype of emotion that the individual experiences. Instead of experiencing feelings of s hame that are related to ego threats, an individual can switch the blame to an external sour ce and experience anger instead. Although anger can also lead to negative consequences, i t does not place a focus on the inadequacies of the individual. Regardless of the underlying mechanisms, it is expected that: Hyp2: Shame will positively relate to withdrawal behaviors and aggressive behaviors (i.e. abuse, social undermining, and sabotage). Emotions not related to attributions. Workplace envy. LazarusÂ’ core-relational theme for envy is Â“wanting what someone else hasÂ” (p. 96; Lazarus, 1999). As the quality, achievement, or possession becomes more important to the self-concept of the envious, the reaction to the stress or becomes stronger and more intense (Cohen-Charash & Mueller, 2007). It is a common emotion in the workplace that can elicit counterproductive behaviors (Miner, 1990). In support of this assumption, organizational envy has been related to lower levels of organizational based self-esteem and higher intentions to quit (Vecchio, 2000). Within the workplace, job performance, compensation, and benefits can be sources of envy. To the envious, it is the discrepancy between the envied and their own job level that is causing the feelings of envy. In reality, this discrepancy could be c aused by
21 organizational policies, union negotiations, high performance by the envied employe e, or low performance by the envious employee. However, feelings of envy are as sociated with harming behaviors directed towards the envied (Cohen-Charash & Mueller, 2007). One explanation for this association is that feelings of envy may focus attenti on at the interpersonal level (Cohen-Charash & Mueller, 2007). Similarly, it is assume d that these harming behaviors are an attempt to attenuate the disparity between the en vied and enviousÂ’ job level. Harming behaviors directed towards the envied employee may se rve to attenuate the disparity because it can negatively impact the reputation of the envied employee. Thus, I expect that envy will predict aggressive workplace behavior s (i.e. Smith et al., 1994). Research on envy has found some empirical support for my expectations. CohenCharash & Mueller, (2007) reported dispositional and episodic envy to be related to harming behaviors (i.e. personal aggression and political deviance). Similarl y, Boone (2005) reported a positive relationship between envy and reactions that are dest ructive to the employee and the workplace. Also, envy has been related to schadenfreude, the enjoyment of misfortune of the envied person (Feather & Sherman, 2002; Smith & Kim, 2007). Since envy and schadenfreude are not socially desirable (Smith & Kim, 2007) and because employees take into account their reputation before committing some aggressive behaviors (Allred, 1995), envy should elicit aggressive behaviors that are more covert in nature as opposed to more overtly aggressive behaviors. Covert CWBs are considered CWBs that are not likely to be detected by the organization. Some examples are sabotage, gossip, and theft. Although I expect envy to be related to acti ve CWBs, envy has also been related to some withdrawal behaviors such as social loa fing
22 and propensity to quit (Duffy & Shaw, 2000; Vecchio, 2005). This may be due to the general tendency for employees to avoid negative emotions and may not be a unique function of envious feelings. Hyp 3: Envy will positively relate to theft, social undermining, and withdrawal behaviors. Workplace jealousy. Jealousy is different from envy in that it requires a social relationship and it often is more intense than feelings of envy (Boone, 2005). Another difference between the two emotions is that feelings of jealousy are based on the possibility of losing a relationship, whereas envy is based on potentially gaining something. LazarusÂ’ core-relational them for jealousy is Â“resenting a third party for a loss or threat to anotherÂ’s affection or favorÂ” (p.96; Lazarus, 1999). Unfortunately few studies have been done on jealousy in the organization (Vecchio, 2000) and romantic jealousy is often the focus of research (e.g. Mathes, Adams, & Davies, 1985 T angney, 1999). An organizational example of jealousy would be employees who fear that their relationship with the supervisor will suffer because of another employee-supervi sor relationship. The theoretical link between feelings of jealousy and CWB is similar to that of envy. Jealous employees are expected to be motivated to decrease their feeli ngs of jealousy. One way to do that would be to damage the threatening rival-target relationship. To destroy this relationship, jealous employees can engage in har ming behaviors directed toward the rival. By sabotaging, abusing, or undermining the rival the jealous employee is attempting to make the rival a less desirable emplo yee.
23 Conversely, the jealous employee is unlikely to engage in harming behavior direct ed toward the target (i.e. supervisor) because that would be counterproductive to their ow n relationship. Unfortunately, there has not been much organizational research conducted on feelings of jealousy. Most of the research either combines jealousy and envy or focuses exclusively on envy. This may be due to the relative abundance of feelings of env y when compared with feelings of jealousy (Boone, 2005). In my literature review, I w as only able to find jealousy to be related to withdrawal behaviors (Vecchio, 2000). This relationship is not surprising because withdrawing from the organization is one way t o prevent negative feelings that are experienced within the organization. However, som e social psychologists (e.g. DeSteno, Valdesolo, & Bartlett, 2006) have tested a link between jealousy and aggression. They created a jealousy manipulation that par alleled an organizational setting. A participant established a working relationship w ith a confederate while completing some tasks. After some time, another confedera te enters the room and also formed a relationship with the first confederate. The first confederate then stopped paying attention to the participant. After the manipulation, the experimenters administered a hot sauce task, a popular laboratory measure of aggression, where the participant had to decide how much hot sauce the experimenter should consume. Participants in the jealous condition allocated more hot sauce than participants in the control condition. Thus, this study appears to support the link between feelings of jealousy and aggression that might generalize to the workplace Hyp 4: Workplace jealousy will positively relate to social undermining, abuse, and withdrawal behaviors.
24 Workplace anxiety. Anxiety is a negative emotion that can be described as apprehension, concern, or worry (Lazarus & Lazarus, 1994). Similar to anger, it is al so considered a basic emotion but it is related to more avoidant than approach related behaviors (Carver & Harmon-Jones, 2009). This emotion is marked by a level of uncertainty in anticipating danger (Ohman, 1992). Organizational examples of anxi ety producing conditions are role ambiguity and role conflict. Both conditions serve to make goal obtainment more difficult. Thus, they can introduce doubt and worry (i.e. anxiety) related to the employeeÂ’s task performance. It is important to note that feeli ngs of anxiety due to organization stressors are likely to be experienced after e xposure to the stressor but before the subsequent negative outcome. An employee in an ambiguous role (i.e. stressor) may fear that he or she are not doing their job correctly (i.e feelings of anxiety) because poor performance can lead to termination (i.e. threat). If the e mployee is then terminated, no feelings of anxiety, in regards to the potential termination, a re expected because the outcome is already known. It is possible, however, for the employee to experience feelings of anxiety related to the possible consequenc es of being unemployed (i.e. capital restriction). Thus, feelings of anxiety tend to occur befor e the attribution-secondary appraisal process has occurred. However, anxiety is s till expected to be associated with CWB. Feelings of anxiety are related to the avoidance m otivational system (Carver & Harmon-Jones, 2009). This system is analogous to the flight par t of the fight-flight response to threatening events. If anxiety is an indicator of the avoidance motivational system, I would expect behavioral reactions to manifest as withdr awal behaviors.
25 Although some studies have assessed the relationship between trait level anxi ety and overall CWB (i.e. Fox & Spector, 1999; Fox, Spector, & Miles 2001), there have been few studies to specifically investigate the relationship between anxiet y at work and withdrawal behaviors. Unfortunately, the few studies that have assessed state anxiety and withdrawal have produced inconsistent results. Liu, Spector, and Jex (2005) reported a positive relationship between workplace anxiety and turnover intentions. However, Lee and Allen (2002) failed to find a relationship between workplace anx iety with workplace deviance when using the PANAS-X (Watson & Clark, 1994). This is a puzzling finding because the workplace deviance scale includes withdrawal behavi ors. Lee and AllenÂ’s (2002) results may be attributed to the use of coworker ratings of CWB. Research has demonstrated that self-report ratings of CWB may be more ac curate than coworker or supervisor reports (Fox, Spector, Goh, & Bruursema, 2007). Thus, there is some evidence that anxiety is related to overall CWB and at least one study tha t links anxiety to withdrawal intentions. Hyp 5: Anxiety will positively relate to withdrawal behaviors Workplace sadness. Sadness can be conceptualized as an inactive state in which a person has determined that there is no way to prevent the loss of something important to the self (Lazarus & Lazarus, 1994; Stearns, 1993). Indeed, LazarusÂ’ (1999) core-relational theme of sadness is Â“having experienced an irrevocable lossÂ” (p.96) Feelings of sadness often accompany a sense of hopelessness and resignation. Studies mea suring sadness often use the term depression (i.e. Park, Wilson, & Lee, 2004). These feelings are not equivalent to feelings associated with depressive disorders (Stearns, 1993) but
26 they are synonymous with general depressive feelings experienced by a normal healthy population. Therefore, being in a depressed mood is the same as being in a sad mood but being clinically depressed is not the same as being sad. In the current disc ussion, I will not be discussing research related to clinical depression. I will focus, instea d, on general feelings of sadness and depression. Similar to anxiety, sadness is another emotion that can occur before the attribution-secondary appraisal process (Weiner, 1985). An employee can ex perience feelings of sadness without determining blame or controllability. However the sad employee is still motivated to decrease these feelings of sadness. Avoidanc e is one way to attenuate feelings of sadness. For instance, employees can become sad during a company downsizing. These employees may respond by avoiding the issue and shifti ng their attention to more pleasant aspects of their life. Such refocusing of att ention can manifest as withdrawal behaviors. Unfortunately, there is a dearth of research that looks at the relationship betwe en sadness and CWB within the organization. In fact, Lee and Allen (2002) was the only organizational study that I found that investigated this relationship. There resul ts suggest that there is no relationship between sadness and CWB. However, these results m ay also be attributable to the use of coworker ratings. Despite the lack relevant resea rch on sadness and CWB, two studies have provided indirect evidence for a link between sadness and withdrawal behaviors. Specifically, Smith, Cronin, and Kessler (2008) found that group levels of employee sadness are negatively related to organizat ional loyalty. They conceptualized organizational loyalty as the inverse o f withdrawal intentions. Indeed, organizational commitment has been related to turnover (Cohen,
27 1993). Thus, sadness may affect organizational attitudes related to withdrawal behaviors. Another study, found that a mental health intervention in the organization significantly decreased the number of absences reported (Cooper, Sadri, Alli son, & Reynolds, 1995). However, the therapy addressed issues of anxiety and depression so I am unable to conclude that the effect is solely due to depression. Similarly, the a uthors did not indicate if the employees had been diagnosed with a depressive disorder or if the symptoms were less intense. Finally, sadness has been related to detachment f rom the provoking event (Parrott, 2001) which may also elicit withdrawal behaviors within the organization. Hyp6: Sadness will positively relate to withdrawal behaviors. Workplace boredom. Boredom is an Â“unpleasant affective state in which the individual feels a pervasive lack of interest in and difficulty concentrating o n the current activityÂ” (p. 386; Fisher, 1993). Boredom in the workplace has been associated with decreased job satisfaction (MacDonald & MacIntyre, 1997), increased depress ive thoughts, and higher levels of anxiety (i.e. Caplan et al., 1975; Kornhauser, 1965). Research using self-report measures has also demonstrated a link between bor edom and low levels of arousal (Russell, 1980; Warr, 1987, 1990). I expect that boredom is related to CWB because employees are motivated to decrease feelings of boredom. If the y are upset by the level of monotony in their job, then employees are expected to engage in non-job related behaviors to make the organization livelier. For instance, gossipi ng and horseplay may increase a bored employeeÂ’s level of arousal and attenuate fe elings of boredom. Thus, bored employees may commit CWBs for instrumental purposes. Some
28 clinical researchers have also linked boredom to feelings of anger (i.e., Lantz, 1988; McHolland, 1988). Simply put, they argue that boredom is a less intense form of anger. In support of this notion, boredom has been associated with aggressive behaviors (Dahlen, Martin, Ragan, & Kuhlman, 2004; Rupp & Vodanovich, 1997). Regardless of the underlying mechanism, boredom is expected to be related to all facets of CWB. Research related to boredom in the workplace is hard to interpret. As mentioned previously, boredom is a negative emotion in response to a lack of interest or focus related to the current task. This definition is difficult to operationalize beca use it is easy to confound with perceptions of environmental conditions. For instance, LeeÂ’s (1986) job boredom scale asks several questions concerning repetitiveness of jobs. These i tems appear to be assessing perceived monotony instead of feelings of boredom. Methodologically, confounding perceived monotony and feelings of boredom is problematic because the scale may be taping job conditions as well as boredom. Therefore, it is not clear if relationships with other variables (i.e. CWB) ar e due to feelings of boredom or monotonous conditions. In order to circumvent this issue, items should focus solely on feelings of boredom. Despite this limitation, previous studie s have generally supported a link between boredom and CWB. Research on the job-affective well-being scale (JAWS) reported a relationship between boredom and withdrawal behaviors (Spector et al., 2006). Dahlen, Martin, Ragan, and Kuhlman (2004) and Rupp and Vodanovich (1997) reported that boredom proneness (i.e. dispositional boredom) was related to aggressive behaviors. Similarly, Bruur sema (2007) reported that both trait boredom and job boredom are related to overall CWB.
29 Finally, some instances of sabotage in the organization have been attributed to feel ings of boredom in the workplace (Ambrose, Seabright, & Schminke, 2002). Hyp7: Boredom will positively relate to withdrawal behaviors, theft, production deviance, abuse, sabotage, social undermining and horseplay. Research question. All of these emotions can be experienced within the organization and they can often be experienced at the same time (Lazarus, 1999). Although there is not a lot of theory about how they may interact to predict CWB, it is a question that can be addressed by the current design of the study. Specifically, I will focus on two 2-way interactions that may be important. The first interaction that I will investigate is the combination of high levels of boredom and anger. Individuals experiencing high levels of boredom may also be more prone to ruminate because the y are not experiencing a high level of stimulation. Rumination may then exacerbat e feelings of anger and elicit a greater amount of CWBs when compared to individual s that are not ruminating. Thus, RQ1 : Boredom and anger will interact, such that, the relationship between anger and withdrawal, theft, production deviance, abuse, sabotage, and social undermining will be stronger when there are high levels of boredom than when there are low levels of boredom. The second interaction that I will investigate is between feelings of sha me and anger. Shame is an inward focused emotions and anger is an outward focused emotions (Perrew & Zellars, 1999). If participants experience inward and outwar d focused negative emotions simultaneously, they may experience higher levels of distres s than
30 individuals experiencing high levels of only outward or inward focused negative emotions (i.e. just anger or shame). Negative emotions in both facets (i.e. inward vs outward) may be overwhelming because being upset with yourself and coworkers l eaves little room for positive emotions and satisfaction. If an employee is only experi encing outward focused negative emotions they may still be able to experience feelings of pr ide related to the self. In this case, one facet (i.e. inward focus) is compensating for the distress in the other facet (i.e. outward focus). However, experiencing negati ve emotions in both facets may deplete resources related to coping, cognition, and attention. Without resources to regulate behavior, higher levels of CWB can be expected (e.g., Al lred, 1995). Thus, RQ2 : Shame and anger will interact, such that the relationship between anger and withdrawal, theft, production deviance, abuse, sabotage, and social undermining will be stronger when there is a high level of shame than when there is a low level of s hame.
31 Chapter 2: Method Participants The sample consists of 241 employed participants who were recruited from classes at a large public university in the southeastern U.S. For 103 of the partic ipants, supervisor data were also collected. The mean age of the sample was 23 (SD = 6.6, range 18-59). The majority (70%) of the participants was female. The employ ees worked an average of 26 hours per week (SD = 10.7) and had an average organizational tenure of 2.3 years (SD = 2.6). Participants were recruited from classes in the psychology and business departments. Extra-credit was provided when possible to compensate the employees for their participation. Procedure The study consists of an employee survey and a supervisor survey. The employee survey required about 15 minutes to complete while the supervisor survey required less than five minutes to complete. The employee survey includes al l of the discrete emotion measures as well as the CWB measures. CWB items wer e presented first. The supervisor survey includes only the CWB measures. Both surveys wer e made accessible electronically on a survey hosting website (i.e. surveymonkey.co m). The data were collected in two different ways. First, participants made a n appointment to come to a laboratory through an electronic research management website (i.e. SONA). Once in the laboratory, the employees generated an identifica tion code that
32 was later used to match the supervisor and employee data while maintaining anony mity. The participants then completed the employee survey electronically in the lab (See Appendix B). Once the participant had finished the survey, the first author sent t heir supervisor an invitation to also participate in the study. This email included the identification code and a link to the supervisor survey. The supervisorÂ’s were then fre e to complete the supervisor survey whenever they were available. The second method of data collection was to recruit participants in the classroom. The first author went to classes in the business and psychology departm ents and gave a short explanation of the studyÂ’s purpose, requirements, and instructions for participation. After the presentation, instructional handouts were distributed to int erested employees. The handouts consisted of instructions for both the employee and the supervisor (See Figure 10B). The participants were instructed to complete the electronic survey, write their unique identification code on the supervisor instructor page, and then to hand the supervisor instruction page to their supervisor. The supervisor instruction page included a brief explanation of the study, a link to the supervisor survey, and a unique identification code generated by the employee. Measures Many of the emotional measures were not designed for the workplace. Thus, slight changes to the directions of these scales were made to reflect the job context. All of the emotion scales have an agree vs. disagree response format. The response opt ions of these scales were altered to reflect a 5 point frequency response choice. Par ticipants were instructed to report how often they have experienced each feeling at work w ithin
33 the past month (See Figures 1B through 6B for a list of all scale items). This time frame was selected because it may be difficult for participants to remember emotional states longer than a month ago. This is congruent with other research related to discrete emotions (e.g., Spector, Dwyer, & Jex, 1988). Anger, anxiety, and sadness The 10 item state anger, the 10 item state anxiety, and the 10 item state depression subscales of the State-Trait Personalit y Inventory (STPI; Spielberger, 1979) were selected to assess workplace anger, anx iety, and sadness. Similar to other studies using the STPI (e.g. Spector, Dwyer, & Jex, 1988), the directions were tailored to reflect the current operationalization of discr ete anger, anxiety, and sadness. In the current study, the coefficient alphas were .92, .75, .80, respectively. Shame Andrews, Qian, and ValentineÂ’s Experience of Shame Scale (2002) was used for the current study. This measure is comprised of 25 items that assess shame related to personal habits, manner with others, the sort of person you are, personal ability, doing something wrong, saying something stupid, failure in performance, a nd body image issues. However, not all of these items are appropriate for the c urrent study. For instance, it is not clear if saying something stupid is really a shame i nducing event. Saying something stupid may be more related to feelings of guilt if self -monitoring is believed to be malleable. Similarly, failures in performance could be due to a l ack of ability (i.e. shame) or a lack of effort (i.e. guilt). Therefore, only subscal es that are clearly assessing shame (i.e. personal habits, manner with others, sort of per son you are,
34 personal ability, and body image issues) were included in the study. It could a lso be argued that body image issues should be considered separately because of the cli nical connotations associated with body image. However, it is likely that employee s can experience shame related to their body image in the workplace. Thus, shame rela ted to body image was also assessed. The coefficient alpha for the present study was .85. Envy and jealousy Vecchio (2000) used the only available, organizationally based, envy and jealousy scales. However, these scales would not be appropriate for the current study because some items contain other emotions besides envy and jealousy For instance, the item Â“I feel depressed when my supervisor speaks favorably about a nother employee,Â” assesses sadness. Thus, other scales were chosen to ensure that t he measures only focused on one particular emotion. A nine item variation of Cohen-CharashÂ’s (2005) Episodic Envy Scale was chosen to assess envy. This scale was altered bec ause the current study is only interested in the frequency of emotions in the workplace. However, the original items focused on a specific target of the emotions (e.g. I want to have what X has). The coefficient alpha of altered scale was .87. To assess jealousy, a six item jealousy scale was created specifically for this study. The items were based on the definition of jealousy and the coefficient alpha was .84. Boredom Unfortunately most of the current job boredom measures confound emotions and perceptions of the organization. Thus, 4 items were constructed to asses s boredom in the workplace. The coefficient alpha for the 4 items was .90.
35 Adjective list Finally, two item adjective measures (e.g. bored, disinterested) were included for each emotion to determine if the results would be similar wit h relatively smaller scales. CWB Three scales were used to measure CWB. For the employee survey, the response choices and the directions for the scales were altered to assess how often they have committed the behaviors within the last month. The supervisor survey, the response choices, and the directions for the scales were altered to assess how often they have observed the target employee commit the behaviors within the last month. First the 45-item CWB-checklist was used to assess the five factor dimensionality discussed in Spector et al., 2006. The three item sabotage scale (employee = .46; supervisor = .34), the three item production deviance scale (employee = .50; supervisor = .22), the four item withdrawal scale (employee = .69; supervisor = .55), and the five item theft scale (employee = .54; supervisor = .74) all had low levels of reliability. Conversely, the 16 item abuse scale (employ ee = .88; supervisor = .92) was reliable. Spector et al. (2006) reported similar reliabilities for these five facets of CWB. The second CWB scale was BruursemaÂ’s (2007) five item horseplay scale. It had coefficient alphas of .77 for the employee data and .79 for the supervisor data. Finall y, eight items of the Duffy, Ganster, and PagonÂ’s (2002) 13 items scale were use d to assess social undermining. Five items had to be removed because they were redundant wit h items from the CWB-checklist. The coefficient alphas for social undermining were .79
36 for the employee data and .75 for the supervisor data. See Figures 7B through 9B f or a list of CWB, horseplay, and social undermining items.
37 Chapter 3: Results A summary of my hypotheses and expectations can be found in Figure 4A and Figure 5A. Descriptive statistics and coefficient alphas of all variable s are reported in Table 1. This table includes the mean, standard deviation, observed range, and estima tes of internal consistency reliability (i.e. coefficient alpha) for all the emotional scales (i.e. full scales and short adjective scales),as well as, the CWB scales comple ted by the employee and the supervisor. Power Analysis Although all of the hypotheses are correlational, I wanted to have enough power to conduct multiple regressions. Thus, a power analysis was conducted to ensure there was enough power to detect the effects of interest. With an alpha level of .05, 7 possibl e independent variables, and a medium effect size (i.e., .15-.20), 103 cases are needed in order to have power above .80 (Cohen, 1988). Thus, the current study has enough power to conduct regressions. Correlational Analyses Correlational Analyses were conducted to investigate the relationships among the study variables. According to the results reported in Table 2, all seven of the e motion scales were significantly correlated with each other among the employe e data. The relationships varied greatly in magnitude.
38 Table 1 Descriptive Statistics (Means, Standard Deviation s, Ranges, and Internal Consistencies) Variable Mean SD Observed Range Coefficient Alpha Anger 18.5 8.7 6-45 0.92 Anxiety 21.9 7 9-50 0.75 Sadness 20.7 7.8 8-50 0.8 Envy 13.2 5.7 6-36 0.87 Jealousy 8.4 3.9 3-28 0.84 Boredom 11.8 5.1 4-20 0.9 Shame 18.9 7 12 -48 0.85 Anger-Adjectives 4.7 2.4 1-10 0.8 Anxiety-Adjectives 4.4 2.3 2-10 0.76 Sadness -Adjectives 3.5 2.1 1-10 0.82 Envy-Adjectives 3.1 1.7 1-10 0.76 Jealousy-Adjectives 2.7 1.4 2-10 0.64 Boredom-Adjectives 6.1 2.7 1-10 0.78 Shame Adjectives 2.6 1.3 1-10 0.67 Sabotage 1.2 0.36 1-3 0.46 Abuse 22.9 7.3 17 -67 0.88 Withdrawal 6.5 2.8 4-20 0.69 Theft 5.8 1.6 4-14 0.54 Production Deviance 3.8 1.5 2-10 0.5 Social Undermining 11.5 4.4 8-40 0.79 Horseplay 10.2 4.1 5-25 0.77 Sabotage Supervisor 3.3 0.75 2-7 0.34 AbuseSupervisor 20.6 6.2 17 -66 0.92 Withdrawal Supervisor 5.1 1.7 4-12 0.55 Theft Supervisor 5.1 0.86 4-11 0.74 Production DevianceSupervisor 3.4 1 2-8 0.22 Social UnderminingSupervisor 9.7 2.8 7-24 0.75 Horseplay Supervisor 7.7 3.3 5-20 0.79
39 For instance, the correlation coefficient for the relationship between jealousy and boredom was .23 while the correlation coefficient for the relationship between shame and envy was .65. In general, the emotion scales were highly interrelated. The seven correlational hypotheses were supported by the employee data (Table 2). H owever, almost all of the relationships between the seven emotions and the seven facets of C WB were significant. The only exception was the relationship between jealousy a nd sabotage (r = .11, p = n.s.). Some of the relationships that were not hypothesized were large. For instance, the correlation coefficient between envy and abuse was .52. Regarding the supervisor data, the first four hypotheses were only partially supported while hypotheses 5 and 6 were not supported (Tables 3 & 4). Hypothesis 7 was also only partially supported. Anger was significantly related to all the proposed relationships (i.e. sabotage, abuse, theft, withdrawal, production deviance, & social undermining) except withdrawal (r = .19, p = n.s.). Shame was related to abuse and social undermining but it was not related to withdrawal or sabotage. Envy was only significantly related to social undermining but was not related to withdrawal or theft. Jealousy was significantly related to abuse and social undermining but it was not related to withdrawal. Neither anxiety nor sadness was significantly related to w ithdrawal. Boredom was significantly related to all seven facets of CWB except theft and production deviance. To compare the correlations yielded between the employee and supervisor data t tests for dependent correlations were conducted for all relationships (Table s 5-11).
40 Table 2 Correlation Matrix of Emotion and CWB Measures with Employee Data 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 1. Anger 2. Anxiety .55* 3. Sadness .61* .64* 4. Boredo m .60* .31* .49* 5. Envy .63* .51* .56* .46* 6. Jealousy .31* .25* .24* .23* .51* 7. Shame .41* .42* .37* .33* .65* .51* 8. Anger Adjectives .80* .45* .55* .55* .62* .30* .37* 9. Anxiety-Adjectives .47* .58* .43* .37* .48* .23* .47* .53* 10. Sadness -Adjectives .55* .48* .67* .41* .62* .39* .57* .59* .55* 11. Envy-Adjectives .40* .36* .36* .32* .61* .55* .63* .43* .43* .51* 12. Jealousy-Adjectives .35* .34* .28* .18* .59* .65* .57* .33* .32* .53* .79* 13. Boredom-Adjectives .52* .17* .38* .74* .39* 0.11 .22* .55* .27* .37* .23* .17* 14. Shame-Adjectives .37* .35* .28* .19* .50* .43* .63* .40* .37* .60* .61* .67* .13* 15. Sabotage 23 .21* .16* .23* .20* 0.11 .24* .16* .13* .18* 0.13 0.08 .14* .18* 16. Abuse 53* .34* .37* 42* .52* 32* .44* .45* .29* .36* .32* .27* .33* .26* .39* 17. Withdrawal 26* .22* 21* 30* .30* .16* .36* .16* 0.12 .23* .19* .21* .23* .18* .30* .46* 18. Theft 40* .26* .26* 27* 32* .16* .32* .16* .20* .27* .20* .14* .18* 0.1 .47* .49* .56* 19. Production Deviance 25* .18* .21* .30* .23* .13* .19* .23* .20* .16* 0.21* .17* .22* .21* .31* .39* .40* .56* 20. Social Undermining .55* .34* .39* .43* .59* .39* .51* .50* .27* .47* .39* .41* .38* .43* .23* .67* .42* .38* .35* 21. Horseplay .50* .35* .40* .58* .48* .29* .35* .43* .30* .35* .28* .26* .51* .25* .34* .40* .38* .35* .24 .52* Note: N = 241; Bolded values are hypothesized relationships; *p < .05
41 In order to perform this analysis, the sample sizes were made equivalent by e xcluding cases that did not have supervisor data available. Thus the sample size for both the employee and supervisor data was 103. Except for 12 cases (See Tables 5, 8, 9, 10, and 11), the correlations computed with supervisor data were not significantly differe nt from the correlations computed with only the employee data. The majority of the differen ces were found when comparing the relationships between boredom, envy, and shame with the facets of CWB. These differences were largely due to higher correlatio ns among the employee data than the supervisor data. To compare the two sets of emotion scales (i.e. full scales vs. two item adje ctives scales), t tests for dependent correlations were conducted for all relati onships between the seven emotions and the seven sub facets of CWB (Tables 12-18). There were no significantly different correlations between the two forms of anxiety, sadn ess, and jealousy scales. However, the anger scales differed for abuse, withdrawal theft, and horseplay. The boredom scales differed for sabotage, abuse, and theft. The envy s cales differed for abuse, withdrawal, theft, social undermining, and horseplay. Finally, the shame scales differed for abuse, withdrawal, and theft. For all cases that have differences among the scales, the full scales yielded stronger correlations than the short adjective scales. Since the majority of the facets of CWB were significantly correl ated with the emotions, multiple regressions were conducted to determine which emotions wer e the best predictors of CWB (See Tables 19-31). Each facet of CWB was regress ed onto all seven emotions. The emotions were entered into the first step of the regression.
42 Table 3. Correlation Matrix of Supervisor Reported CWB. 1 2 3 4 5 6 7 1. Sabotage 2. Abuse .58* 3. Withdrawal .50* .32* 4. Theft .62* .43* .34* 5. Production Deviance .46* .44* .29* .21* 6. Social Und ermining .64* .75* .36* .42* .51* 7. Horseplay .46* .59* .61* .51* .24* .46* Note: Bolded values are hypothesized relationships; N = 103; P < .05
43 Table 4. Supervisor Reported CWB Correlated with All Employee Reported Variab les. Emp Variables Sup Sabotage Sup Abuse Sup Withdrawal Sup Theft Sup Prod. Dev. Sup Soc. Und. Sup Horse. Anger .38* .46* .19 .35* .21* .47* .25* Anxiety .14 .35* .02 .22* .23* .33* .22* Sadness .22* .36* .12 .19 .22* .36* .31* Boredom .24* .27* .22* .14 .12 .32* .27* Envy .15 .36* .05 .11 .09 .35* .24* Jealousy .13 .21* .03 .04 .03 .27* .1 Shame .02 .21* .11 .01 .03 .23* .21* Anger-Adjectives .27* .33* .18 .21* .13 .37* .29* Anxiety -Adjectives .04 .20* .02 .09 .04 .18 .24* Sadness Adjectives .18 .26* .15 .06 .09 .29* .27* Envy -Adjectives .11 .16 .05 .01 .06 .29* .13 Jealousy-Adjectives .16 .15 .03 .03 .04 .27* .06 Boredom-Adjectives .15 .24* .2 .09 .02 .21* .29* Shame-Adjectives .1 .05 .08 .01 .02 .20* .06 Emp Sabotage .24* .10 .34* .10 .05 .17 .26* Emp Abuse .25* .67* .23* .09 .21* .47* .44* Emp Withdrawal .05 .17 .15 .06 .00 .13 .05 Emp Theft .17 .36* .04 .08 .16 .27* .17 Emp Prod. Dev. .15 .05 .10 .19 .01 .14 .05 Emp Soc. Und. .25* .46* .20* .18 .14 .50* .33* Emp Horse. .14 .21* .10 .05 -.07 .13 .34* Note. Rows N = 241; Columns N = 102; Bolded values are hypothesized relationships; *p < .05
44 For the employee data, all of the regressions were statistically sig nificant. See Tables 1925 for overall model statistics (i.e. F values and R 2 values). Shame was a significant predictor of sabotage ( =.18, p < .05), abuse ( = .16, p < .05), withdrawal behaviors ( = .29, p < .05), theft ( = .19, p < .05), and social undermining ( = .20, p < .05). Anger was a significant predictor of abuse ( = .30, p < .05), theft ( = .33, p < .05), and social undermining ( = .27, p < .05). Envy was a significant predictor of abuse ( = .17. p < .05), horseplay ( = .18, p < .05), and social undermining ( = .26, p < .05). Boredom was a significant predictor of production deviance ( = .1, p < .05), withdrawal behaviors ( = .1, p < .05), and horseplay ( = .4, p < .05). Sadness was only a significant predictor of production deviance ( = -.2, P < .05) but the beta weight was not in the expected direction. Anxiety and jealousy did not predict any facet of CWB over and above the other emotions. Although a wide range of emotions predicted CWBs when using the employee reported CWB, the findings were not consistent with the results from the regress ion based on supervisor reported CWB. See Tables 26-32 for overall model statistics. Whe n investigating the supervisor data, emotions were not significant predictors of production deviance, withdrawal behaviors, or horseplay. However, anger was a signifi cant predictor of sabotage ( = .40, p < .05), abuse ( = .35, p < .05), theft ( = .44, p < .05), and social undermining ( = .34, p < .05). Similarly, shame was also a significant predictor of sabotage ( = -.27, P < .05) but the beta weight was not in the expected direction. Thus, anger and shame were the only significant predictor of the supervisor reported CWB To investigate the first research question, a moderated regression was conduc ted with the values for anger and boredom centered and then entered into the first step.
45 T a b l e 6 Comparison of the Anxiety and CWB Correlations Between Sources Employee Correlations Supervisor Correlations Comparison of Correlations Sabotage .10 .14 t-observed = -.33 Abuse .33* .35* t-observed = -.26 Withdrawal .18 -.02 t-observed = 1.6 Theft .26* .22* t-observed = .31 Production Deviance .08 .23 t-observed = -1.1 Social Undermining .30* .33* t-observed = -.32 Horseplay .25* .22 t-observed = .27 Note: = p < .05; Employee N = 102, Supervisor N = 102 Tabl e 5 Comparison of the Anger and CWB C Correlations Between Sources Employee Correlations Supervisor Correlations Comparison of Correlations Sabotage .12 .38* t observed = 2.3* Abuse .53* .46* t observed = 1.0 Withdrawal .28* .19 t observed = .72 Theft .39* .35* t observed = .33 Productio n Deviance .14 .21* t observed = -.51 Social Undermining .53* .47* t observed = .72 Horseplay .45* .25* t observed = 1.9 Note: n.s. = nonsignificant; Employee N = 102, Supervisor N = 102
46 T a b l e 7 Comparison of the Sadness and CWB Correlations Between Sources Employee Correlations Supervisor Correlations Comparison of Correlations Sabotage .14 .22* t-observed = -.66 Abuse .44* .36* t-observed = 1.1 Withdrawal .20* .11 t-observed = .70 Theft .31* .19 t-observed = .93 Production Deviance .08 .22* t-observed = -1.0 Social Undermining .44* .36* t-observed = .89 Horseplay .41* .31* t-observed = .96 Note: = p < .05; Employee N = 102, Supervisor N = 102 T a b l e 8 Comparison of the Boredom and CWB Correlations Between Sources Employee Correlations Supervisor Correlations Comparison of Correlations Sabotage .22* .24* t-observed = -.17 Abuse .47* .27* t-observed = 2.8* Withdrawal .39* .22* t-observed = 1.4 Theft .24* .14 t-observed = .76 Production Deviance .27* .12 t-observed = 1.1 Social Undermining .52* .32* t-observed = 2.3* Horseplay .63* .27* t-observed = 3.9* Note: = p < .05; Employee N = 102, Supervisor N = 102
47 T a b l e 9 Comparison of the Envy and CWB Correlations Between Sou rces Employee Correlations Supervisor Correlations Comparison of Correlations Sabotage .03 .15 t-observed = -.98 Abuse .51* .36* t-observed = 2.1* Withdrawal .39* .05 t-observed = 2.8* Theft .38* .11 t-observed = 2.1 Production Deviance .21* .09 t-observed = .87 Social Undermining .59* .35* t-observed = 2.9* Horseplay .41* .24* t-observed = 1.6 Note: = p < .05; Employee N = 102, Supervisor N = 102 T a b l e 1 0 Comparison of the Jealousy and CWB Correlations Between Sources Employee Correlations Supervisor Correlations Comparison of Correlations Sabotage .09 .13 t-observed = -.33 Abuse .28* .21* t-observed = .89 Withdrawal .13 .03 t-observed = .77 Theft .30* .04 t-observed = 2.0* Production Deviance .03 .03 t-observed = 0 Social Undermining .32* .27* t-observed = .53 Horseplay .17 .10 t-observed = .61 Note: = p < .05; Employee N = 102, Supervisor N = 102
48 T a b l e 1 1 Comparison of the Shame and CWB Correlations Between S ources Employee Correlations Supervisor Correlations Comparison of Correlations Sabotage .13 -.02 t-observed = 1.2 Abuse .38* .21* t-observed = 2.3* Withdrawal .40* .11 t-observed = 2.4* Theft .33* .01 t-observed = 2.5* Production Deviance .08 .03 t-observed = .35 Social Undermining .48* .23* t-observed = 2.8* Horseplay .33* .21* t-observed = 1.1 Note: = p < .05; Employee N = 102, Supervisor N = 102 T a b l e 1 2 Comparison of Anger Scale Correlations with CWB CWB Anger Correlations Anger Adjective Correlations Correlation Comparison Sabotage .23* .16* t-observed = 1.8 Abuse .53* .45* t-observed = 2.3* Withdrawal .26* .16* t-observed = 2.5* Theft .40* .16* t-observed = 6.7* Production Deviance .25* .23* t-observed = .50 Social Undermining .55* .50* t-observed = 1.5 Horesplay .50* .43* t-observed = 2.0* Note: = p < .05; N = 241
49 T a b l e 1 3 Comparison of Anxiety Scale Correlations with CWB CWB Anxiety Correlations Anxiety Adjective Correlations Correlation Comparison Sabotage .21* .13* t-observed = 1.4 Abuse .34* .29* t-observed = .90 Withdrawal .22* .12 t-observed = 1.7 Theft .26* .20* t-observed = 1.0 Production Deviance .18* .20* t-observed = -.34 Social Undermining .34* .27* t-observed = 1.3 Horesplay .35* .30* t-observed = .90 Note: = p < .05; N = 241 Table 14 Comparison of Sadness Scale Correlations with CWB CWB Sadness Correlations Sadness Adjective Correlations Correlation Comparison Sabotage .16* .18* t-observed = -.39 Abuse .37* .36* t-observed = .21 Withdrawal .21* .23* t-observed = -.39 Theft .26* .27* t-observed = -.20 Production Deviance .21* .16* t-observed = .97 Social Undermining .39* .47* t-observed = -1.7 Horesplay .40* .35* t-observed = 1.0 Note: = p < .05; N = 241
50 Table 15 Comparison of Boredom Scale Correlations with CWB CWB Boredom Correlations Boredom Adjective Correlations Correlation Comparison Sabotage .23* .14* t-observed = 2.0* Abuse .42* .33* t-observed = 2.1* Withdrawal .30* .23* t-observed = 1.6 Theft .27* .18* t-observed = 2.0* Production Deviance .30* .22* t-observed = 1.8 Social Undermining .43* .38* t-observed = 1.2 Horesplay .58* .51* t-observed = 1.9 Note: = p < .05; N = 241 Table 16 Comparison of Envy Scale Correlations with CWB CWB Envy Correlations Envy Adjective Correlations Correlation Comparison Sabotage .20* .13 t-observed = 1.2 Abuse .52* .32* t-observed = 4.1* Withdrawal .30* .19* t-observed = 2.0* Theft .32* .20* t-observed = 2.2* Production Deviance .23* .21* t-observed = .36 Social Undermining .59* .39* t-observed = 4.3* Horesplay .48* .28* t-observed = 4.0* Note: = p < .05; N = 241
51 Table 17 Comparison of Jealousy Scale Correlations with CWB CWB Jealousy Correlations Jealousy Adjective Correlations Correlation Comparison Sabotage .11 .08 t-observed = .56 Abuse .32* .27* t-observed = .98 Withdrawal .16* .21* t-observed = -.94 Theft .16* .14* t-observed = .37 Production Deviance .13* .17* t-observed = -.75 Social Undermining .39* .41* t-observed = -.41 Horesplay .29* .26* t-observed = .58 Note: = p < .05; N = 241 Table 18. Comparison of Shame Scale Correlations with CWB CWB Shame Correlations Shame Adjective Correlations Correlation Comparis on Sabotage .24* .18* t observed = 1.1 Abuse .44* .26* t observed = 3.6* Withdrawal .36* .18 t observed = 3.5* Theft .32* .10 t observed = 4.2* Production Deviance .19* .21* t observed = .37 Social Undermining .51* .43* t observed = 1.7 Horseplay .35* .25* t observed = 1.9 Note: = p < .05 ; N = 241
52 The interaction term was then entered into the second step. Each of the facets of CWB was entered individually as the dependent variable. See Tables 33-41 for the model statistics of the significant moderated regressions. For the employee da ta, the interaction term was only significant for theft ( = .15, p < .05). However, boredom and anger interacted to predict sabotage ( = .29, p < .05), abuse ( = .20, p < .05), production deviance ( = .29, p < .05), and social undermining ( = .27, p < .05) when investigating the supervisor reported CWB. For all instances, employees experiencing high l evels of boredom are associated with a higher frequency of CWBs as feelings of anger increase (See Figures 1-5). To investigate the second research question, a moderated regression was conducted with the values for anger and shame centered and then entered into the first step. The interaction term was then entered into the second step. Each of the facets of CWB was entered individually as the dependent variable. See Tables 33-41 for the m odel statistics of the significant moderated regressions. For the employee da ta, anger and shame interacted to predict abuse ( = .15, p < .05), withdrawal ( = .15, p < .05), and social undermining ( = .12, p < .05). However, the interaction term was only a significant predictor of theft ( = .39, p < .05) when investigating supervisor reported CWB. Based on the employee data, employees experiencing high levels of sha me reported higher amounts of CWBs as feelings of anger increased (See Fig ures 6-8). The interaction was in the opposite direction among the supervisor data. Employees experiencing high levels of shame were associated with lower amounts of the ft as feelings of anger increased (See Figure 9).
53 Table 19. Employee Reported Sabotage Regressed Onto Discrete Emotions Variable B SE B b Anxiety 0.07 0.05 0.13 Anger 0.03 0.04 0.07 Depression -0.04 0.04 -0.09 Jealousy -0.03 0.04 -0.05 Envy -0.01 0.5 -0.02 Shame 0.12* 0.06 .18* Boredom 0.04 .02 0.16 Model F 3.7* Model R 2 0.1 Note: N = 241; p < .05 Table 20. Employee Reported Abuse Regressed onto the Discrete Emotions Variable B SE B b Anxiety -.01 0.04 -.02 Anger 0.12* 0.03 .30* Depression -0.01 0.04 -.02 Jealousy 0.02 0.04 0.03 Envy .10* 0.05 .17* Shame 0.12* 0.06 .16* Boredom 0.04 0.02 0.11 Model F 18.8* R 2 Total 0.36 Note: N = 241; *p < .05
54 Table 21. Employee Reported Production Deviance Regressed onto the Discrete Emotions Variable B SE B b Anxiety 0.09 0.06 0.12 Anger 0.04 0.05 0.09 Depression -.12* 0.06 -0.2* Jealousy 0 0.06 0 Envy 0.05 0.07 0.07 Shame 0.04 0.08 0.04 Boredom 0.1* 0.03 .26* Model F 4.6* Model R 2 0.12 Note: N = 241; p < .05 Table 22. Employee Reported Withdrawal Regressed onto the Discrete Emotions Variable B SE B b Anxiety 0.06 0.09 0.05 Anger 0.02 0.07 0.03 Depression -0.04 0.08 -0.05 Jealousy -0.07 0.08 -0.07 Envy 0.04 0.1 0.04 Shame 0.38* 0.1 .29* Boredom 0.1* 0.04 .19* Model F 6.7* Model R 2 0.17 Note: N = 241; p < .05
55 Table 23. Employee Reported Theft Regressed onto the Discrete Emotions Variable B SE B b Anxiety 0 0.04 0 Anger .11* 0.03 .33* Depression 0 0.04 -0.01 Jealousy 0.01 0.04 0.02 Envy -0.02 0.04 -0.04 Shame .12* 0.05 .19* Boredom 0.01 0.02 0.02 Model F 8.0* Model R 2 0.19 Note: N = 241; p < .05 Table 24. Employee Reported Horseplay Regressed onto the Discrete Emotions Variable B SE B b Anxiety -0.05 0.08 -0.04 Anger 0.1 0.07 0.11 Depression 0.04 0.08 0.04 Jealousy 0.07 0.08 0.06 Envy .21* 0.1 .18* Shame 0.03 0.11 0.02 Boredom .26* 0.04 0.4* Model F 22.3* Model R 2 0.4 Note: N = 241; p < .05
56 Table 25. Employee Reported Social Undermining Regressed onto the Discrete Emotions Variable B SE B b Anxiety -0.06 0.05 -0.07 Anger 0.15* 0.04 0.27* Depression 0.0 0.05 -0.01 Jealousy 0.05 0.51 0.06 Envy .20* 0.06 .26* Shame 0.21* 0.7 0.20* Boredom .04* 0.03 0.09 Model F 26.2* Model R 2 0.44 Note: N = 241; p < .05 Table 26. Supervisor Reported Sabotage Regressed onto the Discrete Emotions Variable B SE B b Anxiety -0.03 0.05 -0.08 Anger .10* 0.04 0.40* Depression .02 0.43 .08 Jealousy 0.04 0.04 0.12 Envy -.01 0.05 -.03 Shame -.11* 0.05 -.27* Boredom 0.02 0.03 0.10 Model F 3.3* Model R 2 0.20 Note: N = 103; p < .05
57 Table 27. Supervisor Reported Abuse Regressed onto the Discrete Emotions Variable B SE B b Anxiety .04 0.06 0.09 Anger .12* 0.05 0.35* Depression .03 0.06 .07 Jealousy 0.01 0.07 0.01 Envy .07* 0.07 .15 Shame -.04 0.07 -.07 Boredom -.02 0.03 -.07 Model F 4.2* Model R 2 0.24 Note: N = 103; p < .05 Table 28. Supervisor Reported Production Deviance Regressed onto the Discrete Emotions Variable B SE B b Anxiety .07 0.07 0.15 Anger .05 0.05 0.15 Depression .04 0.06 .10 Jealousy -.01 0.06 -.02 Envy -.03 0.07 -.06 Shame -.05 0.08 -.08 Boredom -.00 0.04 -.01 Model F 1.1 Model R 2 0.08 Note: N = 103; p < .05
58 Table 29. Supervisor Reported Withdrawal Regressed onto the Discrete Emotions Variable B SE B b Anxiety -.14 0.09 -.24 Anger .09 0.07 0.21 Depression .06 0.08 .11 Jealousy -.01 0.08 -.02 Envy -.11 0.09 -.18 Shame .09 0.10 .12 Boredom .06 0.05 .17 Model F 1.5 Model R 2 0.1 Note: N = 103; p < .05 Table 30. Supervisor Reported Theft Regressed onto the Discrete Emotions Variable B SE B b Anxiety .03 0.03 0.11 Anger .07* 0.02 0.44* Depression -.01 0.03 -.05 Jealousy -.01 0.03 -.05 Envy -.01 0.03 -.05 Shame -.04 0.04 -.13 Boredom -.01 0.02 -.05 Model F 2.4* Model R 2 0.15 Note: N = 103; p < .05
59 Table 31. Supervisor Reported Horseplay Regressed onto the Discrete Emotions Variable B SE B b Anxiety -.03 0.13 -.03 Anger .03 0.10 0.5 Depression .17 0.12 .22 Jealousy -.03 0.11 -.03 Envy .02 0.13 .03 Shame .09 0.15 .08 Boredom .04 0.07 .08 Model F .18 Model R 2 0.12 Note: N = 103; p < .05 Table 32. Supervisor Reported Social Undermining Regressed onto the Discrete Emotions Variable B SE B b Anxiety .02 0.07 0.05 Anger .12* 0.05 0.34* Depression .03 0.06 .08 Jealousy 0.06 0.06 0.11 Envy .03 0.07 .06 Shame -.04 0.08 -.06 Boredom .01 0.04 .02 Model F 4.2* Model R 2 0.24 Note: N = 103; p < .05
60 Table 33. Boredom as a Moderator of the Anger-Theft Relationship Using Employee Data. Independent Variables Step 1 Step 2 B SE B B SE B Anger .12* .02 .38* .10* .03 .30* Boredom .01 .02 .04 .02 .02 .08 Anger X Boredom .04* .02 .15* R 2 .17 .02 Model R 2 .17 .18 Model F 23.4* 5.0* Note: p < .05. Table 34. Boredom as a Moderator of the Anger-Sabotage Relationship Using Supervisor Data. Independent Variables Step 1 Step 2 B SE B B SE B Anger .09* .03 .37* .05 .03 .18 Boredom 0 .02 .02 .02 .02 .13 Anger X Boredom .05* .02 .29* R 2 .14 .06 Model R 2 .14 .21 Model F 8.3* 8.5* Note: p < .05.
61 Table 35. Boredom as a Moderator of the Anger-Abuse Relationships Using Supervisor Data. Independent Variables Step 1 Step 2 B SE B B SE B Anger .17* .04 .47* .12* .05 .34* Boredom -.01 .03 -.02 .01 .03 .05 Anger X Boredom .05* .03 .20* R 2 .21 .03 Model R 2 .21 .24 Model F 13.2* 10.4* Note: p < .05. Table 36. Boredom as a Moderator of the Anger-Production Deviance Relationship Using Supervisor Data. Independent Variables Step 1 Step 2 B SE B B SE B Anger .08 .04 .22 .01 .05 .03 Boredom 0 .03 -.01 .02 .03 .09 Anger X Boredom .08* .03 .29* R 2 .05 .06 Model R 2 .05 .11 Model F 2.3 3.9* Note: p < .05.
62 Table 37. Boredom as a Moderator of the Anger-Social Undermining Relationship Using Supervisor Data. Independent Variables Step 1 Step 2 B SE B B SE B Anger .16* .04 .45* .10* .05 .27* Boredom .01 .03 .04 .04 .03 .14 Anger X Boredom .07* .03 .27* R 2 .23 .06 Model R 2 .23 .28 Model F 14.3* 12.7* Note: p < .05. Table 38. Shame as a Moderator of the Anger-Abuse Relationships Using Employee Data. Independent Variables Step 1 Step 2 B SE B B SE B Anger .17* .02 .42* .16* .02 .40* Shame .20* .04 .26 .17* .05 .22* Anger X Shame .07* .04 .12* R 2 .34 3.9 Model R 2 .34 .35 Model F 60.6* 42.2* Note: p < .05.
63 Table 39. Shame as a Moderator of the Anger-Withdrawal Relationship Using Employee Data. Independent Variables Step 1 Step 2 B SE B B SE B Anger .10* .05 .14* .08 .05 .11 Shame .40* .09 .30* .33* .09 .25* Anger X Shame .16* .07 .15* R 2 .14 .02 Model R 2 .14 .16 Model F 20.0* 15.1* Note: p < .05. Table 40 Shame as a Moderator of the Anger-Social Undermining Relationship Using Employee Data. Independent Variables Step 1 Step 2 B SE B B SE B Anger .23* .03 .41* .22* .03 .38* Shame .36* .06 .35* .31* .06 .31* Anger X Shame .10* .5 .12* R 2 .40 .01 Model R 2 .40 .41 Model F 79.0* 54.7* Note: p < .05.
64 Table 41. Shame as a Moderator of the Anger-Theft Relationship Using Supervisor Data Independent Variables Step 1 Step 2 B SE B B SE B Anger .07* .02 .42* .09* .02 .53* Shame -.05 .03 -.17 -.01 .03 -.04 Anger X Shame -.08* .02 -.39* R 2 .14 .11 Model R 2 .14 .25 Model F 8.2* 10.9* Note: p < .05.
65 Figure 1. Anger and Boredom Interacting to Predict Theft Using Employee Data. Figure 2. Anger and Boredom Interacting to Predict Sabotage Using Supervisor Data. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 LowHighTheftAnger Boredom +1 S.D. Boredom -1 S.D. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 LowHighSabotageAnger Boredom +1 S.D. Boredom -1 S.D.
66 Figure 3. Anger and Boredom Interacting to Predict Abuse Using Supervisor Data. Figure 4. Anger and Boredom Interacting to Predict Production Deviance Using Supervisor Data. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 LowHighAbuseAnger Boredom +1 S.D. Boredom -1 S.D. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 LowHighProduction DevianceAnger Boredom +1 S.D. Boredom -1 S.D.
67 Figure 5. Anger and Boredom Interacting to Predict Social Undermining Using Supervisor Data. Figure 6. Anger and Shame Interacting to Predict Abuse Using Employee Data. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 LowHighSocial UnderminingAnger Boredom +1 S.D. Boredom -1 S.D. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 LowHighAbuseAnger Shame +1 S.D. Shame -1 S.D.
68 Figure 7. Anger and Shame Interacting to Predict Withdrawal Behaviors Using Employee Data. Figure 8. Anger and Shame Interacting to Predict Social Undermining Using Employe e Data. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 LowHighWithdrawalAnger Shame +1 S.D. Shame -1 S.D. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 LowHighSocial UnderminingAnger Shame +1 S.D. Shame -1 S.D.
69 Figure 9. Anger and Shame Interacting to Predict Theft Using Supervisor Data. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 LowHighTheftAnger Shame +1 S.D. Shame -1 S.D.
70 Chapter 4: Discussion The results among the employee data supported all of the hypotheses. However, these results do not confirm my general expectations. More specifically, I expected the attributions of causality and controllability to differentiate between the ty pes of CWBs that the negative emotions predict. This was not the case. Almost all of the emoti ons were significantly related to all of the sub facets of CWB. In many cases, the une xpected relationships were as large, if not, larger than the expected relationships. Thus all of the negative emotions appear to be relevant to most of the facets of CWB. This does not support the expectations I generated using the attribution and appraisal theories, but it does support the overall stressor-emotion model (Spector & Fox, 2002). Even though my original logic was not supported, there may be post-hoc explanations for the current trends in the data. First, the high correlations among the study variables could be due to negative affectivity. Employees with high leve ls of negative affectivity may have a tendency to report high levels of distress and ne gative emotions (Watson et al., 1987). Having a general negative disposition when participating in the current study could, therefore, lead to over reporting of the frequency of negat ive emotions and negative workplace behaviors. Over reporting would artificially infl ate the correlation between the variables in this study. The current study did not control for negative affectivity because it is not clear that negative affectivity had a biasing effect on the data. It is, therefore, possible that negative affectivity could be affect ing the relationships. However, partialling negative affectivity out of the analyses is inappropriate due to the possible removal of substantive effects (Spector, Zapf, Che n, &
71 Frese, 2000). Thus, negative affectivity may influence the results but the current st udy is unable to investigate the issue. Job attitudes might also help to explain the results. According to the affective events theory (Weiss and Cropanzano, 1996), affective reactions can influence work attitudes. These attitudes can then influence judgment driven behaviors in the workpla ce. Specific to the current study, negative emotions could energize CWBs regardless of the type of negative emotions due to their effect on job related attitudes. Job satis faction is typically defined as an employeeÂ’s level of positive affect toward his or her job situation (Locke, 1976). It is, therefore, unlikely that an employee experiencing negative emotions in the workplace will have a positive emotional reaction to the job situation. Chen and Spector (1992) found negative relationships between trait anger and job satisfacti on. Similarly, both job satisfaction and trait anger were related to a host of CWBs (i.e. theft, interpersonal aggression, and sabotage) as well as turnover intentions. Thus, an employe e experiencing any type of negative emotions may become dissatisfied with the organization and more likely to withdrawal and aggress against the organization. Fut ure research should investigate the role of job attitudes as a mediator between negative emotions and CWBs. Comparing the Negative Emotions Since all emotions were found to be related to most of the facets of CWB, all seven of the negative emotions were entered into multiple regressions. These re gressions enabled the comparison of the emotions to determine how important each emotion was in relation to the other emotions. The analysis of the employee data better differ entiated
72 among the emotions and provided some support for my original expectations. The analyses revealed that anger, shame, envy, and boredom were the best predict ors of the CWB facets. In line with the original hypotheses, shame predicted sabotage, abus e, theft, social undermining, and withdrawal behaviors. Although shame is traditionally thou ght to be related to withdrawal, these findings suggest that shame can also predict aggr essive behaviors. This can be interpreted as indirect evidence of the shame displacem ent argument. Similarly, envy was a significant predictor of abuse, social undermi ning, and horseplay. These findings support the claim that feelings of envy can used to predict aggressive behaviors. Envy does appear to be related to covert aggression but feelings of envy are also important for predicting overtly aggressive behaviors (i.e. abus e). In regards to anger, the results also partially supported my original expectat ions. Although, anger was related to every sub facet of CWB, it was only a significant predict or of abuse, theft, and social undermining. Congruent with the literature, anger was a predictor of approach related behaviors (Carver & Harmon-Jones, 2007). Although all the negative emotions are important, some of the emotions are more important than others in predicting facets of CWB. When using the employee data, comparing the emotions revealed trends in the data that were more congruent with my expectations than t he correlation matrix. In some cases, comparing the emotions supported my expectations. However, the findings regarding boredom, sadness, anxiety, and jealousy were not anticipated. Boredom was expected to be related to aggressive behaviors but the results are not as impressive when compared to the other relevant emotions (i.e. anger, shame, and envy). Feelings of boredom were highly correlated with aggressive behaviors (i.e. abuse and
73 social undermining) but these feelings were not able to significantly predict a ggressive behaviors when combined with the other six emotions. Despite these surprising result s, boredom was a significant predictor of production deviance, withdrawal behaviors, and horseplay. Thus, boredom may not be the most important negative emotion when predicting aggressive behaviors, but it is important in predicting the less aggre ssive CWBs. There were also unexpected findings related to sadness. Contrary to expect ations, sadness was not a significant predictor of withdrawal behaviors. Boredom and shame appear to be the more important emotions in regards to withdrawal behaviors. However, sadness was a significant predictor of production deviance. Unfortunately, the bet a weight was not in the expected direction. Since the beta weight is negative but the correlation is positive (r = .21, p < .05), there is evidence to suggest the existence of a suppressor effect. Thus, sadness did not appear to be that important for any facet of CW B when compared with the other six emotions. Finally, jealousy and anxiety also did not predict any facet of CWB. One potential explanation could be that the other emotions were more important than jealousy or anxiety in predicting the sub facets of CWB. For instance, feelings of shame m ay be more important than feelings of anxiety when predicting withdrawal behaviors For anxiety, this rationale is plausible. Feelings of shame have direct implica tions for the ego (Tangney & Fischer, 1995) that may not be present in feelings of anxiety. Thus feelings of shame may be perceived as more aversive in the workplace. However, this explanation is not adequate in regards to jealousy. Feelings of jealousy are of ten more intense than feelings of envy (Boone, 2005). Since jealousy and envy were expected to both related to some of the same behaviors (i.e. social undermining and withdrawal
74 behaviors), feelings of jealousy would be expected to be a better predictor than fe elings of envy. It is not clear why jealousy did not predict any facets of CWB. Comparison of Employee and Supervisor Data Despite the employee data supporting the hypotheses, analysis of the supervisor reported CWB did not yield similar results. There were several significant differences between the employee and supervisor data when comparing the correlations bet ween emotions and CWB. Hypotheses 1 through 4 and 7 were only partially supported while hypotheses 5 and 6 received no support. In regards to the multiple regressions, negative emotions were unable to predict three of the CWB facets (i.e. production deviance, withdrawal behaviors, and horseplay). When negative emotions could be used to predict the CWB facets, anger was the most important emotion. Shame was also a signi ficant predictor of sabotage but the beta weight was negative so this is again evidence of suppression. A final difference between the employee and the supervisor results w as the moderated regressions. Shame and anger interacted to predict a few facets of C WB (i.e. abuse, production deviance, and social undermining) among the employee data, while boredom and anger interacted to predict sabotage, abuse, production deviance, and social undermining, when using the supervisor data. Boredom and anger did interact to predict theft when using the employee data, but these results were not duplicated in the analyses of the supervisor data. An explanation for these results is not apparent. There are definitely differences between the supervisor and employee reported CWB but i t is puzzling that the second research question was supported by the employee data while the first research question was supported by the supervisor data.
75 There are several potential explanations for the discrepancies between the employee and supervisor reported CWB. The first issue could be the sample size. The employee data had 241 cases while the supervisor data only had 103 cases. This could explain why fewer correlations were significant when using the supervisor data. However, the t-tests for dependent samples were conducted with equivalent sample s izes (N = 103). With equal sample sizes, the correlations derived from the employee dat a and from the supervisor data still yielded significantly different resul ts in 12 out of 49 cases. Therefore, it is likely that there is some systematic explanation for the di screpancies. Since the employee data were obtained from a self-report survey, common me thod variance could explain the higher correlations among the employee data. If common method variance was the culprit, higher correlations would be expected for all of the relationships between emotions and the facets of CWB. However, there are instanc es where the correlations derived from the supervisor data were significantly la rger than the correlations derived from the employee data. For instance, the correlation coeff icient between anger and sabotage was .38 while the employee correlations coeffici ent was .12 with a sample of 102. Thus, the role of common method variance cannot be determined in the current study but there is some evidence to suggest that it may not be responsi ble for all of the differences between the employee and supervisor reported data To best account for the differences between the employee and supervisor re ported data, it is useful to discuss the differences between the two sources in regards to CWB. An employee is at risk of being punished if their supervisor is aware that they c ommit CWBs. Thus, it is usually in the best interest of the employee to hide such behaviors from the supervisor. Some types of CWB are harder to hide than others. For instance, takin g an
76 extra long break is less likely to be noticed than acts of physical abuse. Out of a ll the hypothesized relationships that did not reach significance with the supervisor dat a (N = 10), six of the correlations were between the negative emotions and withdrawal behaviors. This may be due to the supervisorÂ’s inability to accurately monitor withdra wal behaviors. Supervisors, therefore, may not have an accurate impression of the freque ncy of CWB because they are unable to observe all of the CWBs committed by the employe e. Similarly, a supervisor is often responsible for more than one employee and it c ould become difficult to accurately remember the frequency of each subordinateÂ’s CWBs. In contrast, an employee may have a more accurate account of their own behaviors than other people within the organization (Fox, Spector, Goh, & Bruursema, 2007). The different correlations derived from employee and supervisor data may be due to inaccuracies in the supervisor reports of CWB. Comparing the Two Sets of Emotion Measures Two sets of scales were included in the current study to measure each negati ve emotion. The first set of scales was the full version that was comprised of seve ral items. The second set of scales was comprised of two items that referenced two adjec tives related to the negative emotion of interest. The differences in the correlations of the two versions with the CWB facets were not significantly different for sadness, anxiety, and jealousy. However, there were significant differences among the anger, bor edom, envy and shame scales. The full version of the scale yielded larger correlati ons in all instances where the correlations were significantly different. Researchers shoul d be careful about which versions of the scales they choose to use when investigating CWB. The shorter
77 adjective versions may be adequate when measuring sadness, anxiety, and jealous y. However, the full version scales should be used when measuring anger, boredom, envy, and shame. Limitations The current study has several limitations. First, the organizational tenure of the employees was rather low (Mean = 2.3 years). The frequency and type of CWB may change as the age and tenure of the employee increases. More experience d employees may experience less negative emotions because they are more satisf ied and committed to the organization. It is also possible that more experienced employees encounte r the same frequency of negative emotions but they are better able to handle the emotions. For instance, an experienced employee might choose alternative behaviors to CWB Similarly, an experienced employee could be better at avoiding detection when t hey commit CWB. The current study is unable to explore these possibilities so future re search should seek a more generalizable sample. A second limitation of the current study is that it was cross sectional. Since all of the study variables were measured at one time, it is not possible to determine t he causality of the relationships. Although negative emotions were found to predict ce rtain CWBs, committing CWB is likely to lead to negative feelings (i.e. guilt a nd shame). Therefore, future research should include experimental or longitudinal designs to investigate situations that might influence the causality of these relati onships. Some of the CWB facets had low reliabilities but this is not a limitation. If a measure is thought to be influenced by its associated construct, than it should have a hi gh
78 level of reliability because the items that comprise the measure are thou ght to reflect the same underlying construct. However, if the measure is believed to form or define t he associated construct, then the measure may have a low level of reliability be cause the individual items are no longer assumed to be influenced by the same underlying constru ct (Edwards & Bagozzi, 2000). Behavioral checklists, such as the CWB-C scale, are comprised of individual behaviors that are assumed to define the construct of interest but are not expected to be interchangeable. (Edwards & Bagozzi, 2000; Spector et al, 2006). For instance, physical assault and purposefully ignoring someone are both examples of abuse but they are not equivalent behaviors. Thus, the low reliabilities among the CWB-C facets are not a cause for concern. Conclusion The current study was one of the first to investigate the relationship between multiple negative emotions and several facets of CWB. In general, the result s provide some evidence to suggest that discrete emotions are legitimate predictors of organizational behaviors. Similarly, the results also support the stressor emot ion-model (Spector & Fox, 2002). Although I am unable to discuss causality, a wide range of negative emotions appear to be differentially related to CWBs. Similarly, ana lysis of the employee data revealed that some negative emotions are more important in predic ting facets of CWB than anger (i.e. envy, shame, boredom, sadness, and anger). This is a n interesting finding because anger has been traditionally considered the most important emotion in predicting CWB. The inconsistency in results between the employee and supervisor data is also important. The results of the current study may provide indi rect
79 evidence of a systematic discrepancy between sources in reporting CWB. Finally, this is one of the first studies to demonstrate that emotions can interact to predict wor kplace behaviors. Employees are able to experience several emotions at the same ti me and the results suggest that certain combinations are associated with incremental ly higher amounts of CWB. Therefore, organizations should be concerned about most types of negative emotions and they should strive to create policies and cultures that are orie nted towards attenuating such feelings.
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93 Appendix A: Extra Information
94 Appendix A Figure 1A. Illustration of how the CWB and related constructs overlap (Raver, 2005).
95 Appendix A (Continued) Figure 2A. Reproduced stressor-emotion model from Spector & Fox (2005).
96 Appendix A (Continued) Figure 3A. A reproduction of Perrew & ZellarÂ’s (1999) appraisal-attribution model.
97 Appendix A (Continued) # Hypothesis Analyses 1 Workplace anger will positively relate to withdrawal behaviors, theft, production deviance, abuse, sabotage, and social undermining. Correlation Multiple Regression 2 Shame will positively relate to withdrawal behaviors and aggressive behaviors (i.e. abuse, social undermining, and sabotage). Correlation 3 Envy will positively relate to theft, social undermining, and withdrawal behaviors. Correlation Multiple Regression 4 Workplace jealousy will positively relate to social undermining, abuse, and withdrawal behaviors. Correlation Multiple Regression 5 Anxiety will positively relate to withdrawal behavior Correlation Multiple Regression 6 Sadness will positively relate to withdrawal behaviors. Correlation Multiple Regression 7 Boredom will positively relate to withdrawal behaviors, theft, production deviance, abuse, sabotage, social undermining and horseplay. Correlation Multiple Regression R.Q. How do these emotions interact to predict CWB? Anger X Boredom Anger X Shame Moderated Regression Figure 4A. Summary of Hypotheses and Proposed Analyses
98 Appendix A (Continued) Abuse Theft Sabotage Production Deviance Withdrawal Social Undermining Horseplay Anger Shame Envy Jealousy Anxiety Sadness Boredom Figure 5A. Expected Relationships Among Study Variables
99 Appendix B: Survey Materials
100 Appendix B The questions that follow all deal with your feelings within the organization. P lease answer them while thinking about your current job. Instructions. Please use the following scale to indicate how often you experience each of the following statements in the past month How often have you experienced each of the statements below in the last month at your present job? In the past month I have experiences the following at work 0 times Once 2-3 times 4-5 times 6 or more 1. Became distressed by how slowly the day passes by. 1 2 3 4 5 2. Suffered from a lack of mental stimulation. 1 2 3 4 5 3. Became sluggish 1 2 3 4 5 4. Felt uninterested 1 2 3 4 5 Figure 1B. Workplace Boredom Scale
101 Appendix B (Continued) How often have you experienced each of the statements below in the last month at your present job ? 0 times Once 2-3 times 4-5 times 6 or more 1. Felt Calm. 1 2 3 4 5 2. Felt Furious. 1 2 3 4 5 3. Felt Strong. 1 2 3 4 5 4. Felt Tense. 1 2 3 4 5 5. Felt like banging on the table. 1 2 3 4 5 6. Felt at ease. 1 2 3 4 5 7. Felt angry. 1 2 3 4 5 9. Felt worried over possible misfortunes. 1 2 3 4 5 10. Felt like kicking somebody. 1 2 3 4 5 11. Felt nervous. 1 2 3 4 5 12. Felt like breaking things. 1 2 3 4 5 13. Felt jittery. 1 2 3 4 5 14. Felt mad. 1 2 3 4 5 15. Felt relaxed. 1 2 3 4 5 16. Felt irritated. 1 2 3 4 5 17. Felt worried. 1 2 3 4 5 18. Felt like hitting someone. 1 2 3 4 5 19. Felt steady. 1 2 3 4 5 20. Felt annoyed. 1 2 3 4 5 21. Felt frightened. 1 2 3 4 5 Figure 2B. STPI Anger & Anxiety
102 Appendix B (Continued) Figure 3B. State-Trait Depression Subscale (Speilberger, 1979) How often have you experienced each of the statements below in the last month at your present job ? 0 times Once 2-3 times 4-5 times 6 or more 1. Felt blue. 1 2 3 4 5 2. Felt miserable. 1 2 3 4 5 3. Felt downhearted. 1 2 3 4 5 4. Felt alive. 1 2 3 4 5 5. Felt sad. 1 2 3 4 5 6. Felt safe. 1 2 3 4 5 7. Felt gloomy. 1 2 3 4 5 8. Felt burned up. 1 2 3 4 5 9. Felt healthy. 1 2 3 4 5 10. Felt hopeful about the future. 1 2 3 4 5
103 Appendix B (Continued) Figure 4B. Experience of Shame Scale (Andrews, Qian, and Valentine, 2002) How often have you experienced each of the statements or displayed each of the behaviors below in the last month at your present job ? 0 times Once 2-3 times 4-5 times 6 or more Once or twice per week 1. Felt ashamed of any of your personal habits? 1 2 3 4 5 2. Tried to cover up or conceal your personal habits? 1 2 3 4 5 3. Felt ashamed of your manner with others? 1 2 3 4 5 4. Avoided people because of your manner? 1 2 3 4 5 5. Felt ashamed of the sort of person you are? 1 2 3 4 5 6. Tried to conceal from others the sort of person you are? 1 2 3 4 5 7. Felt ashamed of your ability to do things? 1 2 3 4 5 8. Avoided people because of your inability to do things? 1 2 3 4 5 9. Felt ashamed because you did something wrong? 1 2 3 4 5 10. Tried to cover up or conceal things you felt ashamed of having done? 1 2 3 4 5 11. Felt ashamed of your body or any part of it? 1 2 3 4 5 12. Avoided looking at yourself in the mirror? 1 2 3 4 5 13. Wanted to hide or conceal your body or any part of it? 1 2 3 4 5
104 Appendix B (Continued) Figure 5B. Envy and Jealousy Items How often have you experienced each of the statemen ts below in the last month at your present job ? 0 times Once 2-3 times 4-5 times 6 or more 1. Felt that you lacked what others tend to have 1 2 3 4 5 2. Felt bitter 1 2 3 4 5 3. Felt envious 1 2 3 4 5 4. Felt resentment or bitterness against others 1 2 3 4 5 5. Yearned over what others have 1 2 3 4 5 6. Felt others have things going better than you d o 1 2 3 4 5 7. Felt irritated or annoyed 1 2 3 4 5 8. Felt hatred towards others 1 2 3 4 5 9. Felt resentment or ill will toward others 1 2 3 4 5 10. Felt that a third party has threatened an impor tant relationship of mine. 1 2 3 4 5 11. Felt that a third party has troubled an importa nt relationship of mine. 1 2 3 4 5 12. Felt jealous of someone. 1 2 3 4 5 13. Felt concerned that someone is becoming too cl ose to someone who you think is important. 1 2 3 4 5 14. Felt that another person was going to replace y ou in an important relationship. 1 2 3 4 5 15. Felt jealous of someone elseÂ’s relationship. 1 2 3 4 5
105 Appendix B (Continued) Figure 6B Emotional Adjective List. How often have you experienced each of the following emotions at work in the past month ? 0 times Once 2-3 times 4-5 times 6 or more 1. Anxious 1 2 3 4 5 2. Angry 1 2 3 4 5 3. Envious of someone 1 2 3 4 5 4.Worried 1 2 3 4 5 5. Jealous of someone 1 2 3 4 5 6. Sad 1 2 3 4 5 7. Bored 1 2 3 4 5 8. Ashamed 1 2 3 4 5 9. Depressed 1 2 3 4 5 10. Irritated 1 2 3 4 5 11. Desirous of something someone has 1 2 3 4 5 12. Disinterested 1 2 3 4 5 13. Threatened that someone would take a relationship away 1 2 3 4 5 14. Disgraced 1 2 3 4 5
106 Appendix B (Continued) How often have you done each of the following things on your present job in the last month ? 0 times Once 2-3 times 4-5 times 6 or more nrnnn nn 1 2 3 4 5 nn nr 1 2 3 4 5 nr 1 2 3 4 5 !nnnn"rn r 1 2 3 4 5 # nrn 1 2 3 4 5 $ nrnrn 1 2 3 4 5 % &nnrrnn rnrnn 1 2 3 4 5 nnnnn(n n 1 2 3 4 5 ) nnnnnr 1 2 3 4 5 &nnnnn 1 2 3 4 5 &nn r 1 2 3 4 5 +nnn nn 1 2 3 4 5 nrnrrnnnn nn 1 2 3 4 5 ,nnnnrnn 1 2 3 4 5 # nnnn nn 1 2 3 4 5 $ -nnnrn rn 1 2 3 4 5 % !nnnrnnrn n 1 2 3 4 5 nnr 1 2 3 4 5
107 Figure 7B. Counterproductive Work Behavior Checklist (CWB-C) (45-item) ) .nr nnrnnrn 1 2 3 4 5 /nnnn"nn 1 2 3 4 5 0nnnnn 1 2 3 4 5 !nnr n 1 2 3 4 5 !nrn 1 2 3 4 5 nn rn 1 2 3 4 5 # !nnnr n 1 2 3 4 5 $ /nnnr 1 2 3 4 5 % ,nnnnnr 1 2 3 4 5 1nnnnnn r 1 2 3 4 5 ) nnnnrnnr n" 1 2 3 4 5 +n nnrnn 1 2 3 4 5 &nnrnnr 1 2 3 4 5 &nnnnnr 1 2 3 4 5 2nnnnr 1 2 3 4 5 0nnnnn3nn4 nnr 1 2 3 4 5 # !nnnnnrr5nn 1 2 3 4 5 $ !nnnnnr6 1 2 3 4 5 % &nnn nnrn nnn 1 2 3 4 5 7nnnr 1 2 3 4 5 ) nnnnr 1 2 3 4 5 nnnnn r 1 2 3 4 5 nnnnnn r 1 2 3 4 5 .nnnr5nn rn 1 2 3 4 5 7nnnr 1 2 3 4 5 /nnnnr 1 2 3 4 5 # 85nnnnn r 1 2 3 4 5
108 Appendix B (Continued) How often have you done each of the following things on your present job in the last month ? 0 times Once 2-3 times 4-5 times 6 or more Once or twice per week 1. Created or engaged in a non work-related game or activity to entertain myself and/or others during a meeting, seminar, or training session 1 2 3 4 5 2. Used the internet to browse, blog, email, or otherwise amuse myself for non work-related purposes 1 2 3 4 5 3. Engaged in amusing activities such as gossiping or joking with co-workers that distract me and others from work 1 2 3 4 5 4. Played practical jokes on co-workers or customers to entertain myself and/or co-workers during work time 1 2 3 4 5 5. Wasted company resources or supplies to create something for my own purposes or to amuse myself or others. 1 2 3 4 5 Figure 8B. Bruursema (2007) Horseplay items
109 Appendix B (Continued) How often has the target subordinate done each of the following things on your present job in the last month ? 0 times Once 2-3 times 4-5 times 6 or more Once or twice per week 1. Spread rumors about someone? 1 2 3 4 5 2. Delayed work to slow someone down or make someone look bad? 1 2 3 4 5 3. Talked bad about someone behind their back? 1 2 3 4 5 4. Criticized the way someone handle things on the job in a way that was not helpful? 1 2 3 4 5 5. Did not give as much help as they promised? 1 2 3 4 5 6. Competed with someone for status or recognition? 1 2 3 4 5 7. Let you know that he or she did not like someone? 1 2 3 4 5 8. Did not defend someone even though he or she knew others had spoken poorly of him/her? 1 2 3 4 5
110 Appendix B (Continued) Employee Copy How often has the target subordinate done each of the following things on your present job in the last month ? 0 times Once 2-3 times 4-5 times 6 or more Once or twice per week 1. Spread rumors about someone? 1 2 3 4 5 2. Delayed work to slow someone down or make someone look bad? 1 2 3 4 5 3. Talked bad about someone behind their back? 1 2 3 4 5 4. Criticized the way someone handle things on the job in a way that was not helpful? 1 2 3 4 5 5. Did not give as much help as you promised? 1 2 3 4 5 6. Competed with someone for status or recognition? 1 2 3 4 5 7. Let someone know that you did not like another person? 1 2 3 4 5 8. Did not defend someone even though you knew others had spoken poorly of him/her? 1 2 3 4 5 Figure 9B. Social Undermining 112(Duffy, 2002)
111 nr Employee Instructions (15 minutes to complete) 1. Go to the link below. This is the employee part of the survey www.surveymonkey.com/s/employeejeremythesis 2. Generate a code (instructions are provided on the s urvey). 3. Write down the code on the Â“supervisor instructions Â” page (right hand corner of attached sheet). 4. Complete the survey as truthfully as possible 5. Give your supervisor the attached supervisor sheet. Thank you for your participation. Please contact me if you have any questions. Jeremy A. Bauer, Doctoral Student Jbauer3@mail.usf.edu Department of Psychology University of South Florida Supervisor Instructions Secret Code ______________ (5-10 minutes to complete) One of your employees has agreed to participate in a study focused on workplace behaviors. We are aski ng the employee and his/her supervisor to complete a brief survey. Please follow the directions below to comp lete the survey. Additional information about the study will be pres ented once you access the survey. 1. Go to the link below. www.surveymonkey.com/s/supervisorjeremythesis 2. Enter the secret code (see top right of page). 3. Complete the survey in regards to the employee who handed you these instructions 4. Do not discuss your answers with the employee until after you have finished. Thank you for your participation. Please contact me if you have any questions. Jeremy A. Bauer, Doctoral Student Jbauer3@mail.usf.edu Department of Psychology University of South Florida Figure 10B. Instruction Booklet