I WON’T DO WHAT YOU TELL ME: AN EXPLORATION OF ORGANIZATIONAL EMOTIONAL DISPLAY RULE SOURCES By Nikhil Awasty A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Business Administration – Organizational Behavior – Human Resource Management Doctor of Philosophy 2022 ABSTRACT I WON’T DO WHAT YOU TELL ME: AN EXPLORATION OF ORGANIZATIONAL EMOTIONAL DISPLAY RULE SOURCES By Nikhil Awasty Emotional display rules, guidelines for which emotion is appropriate for a given situation, have largely stayed in the background of research on emotional labor with most of the prior work focusing instead on the emotion regulation strategies of surface and deep acting. This dissertation brings emotional display rules to the foreground by focusing on where these display rules come from. Specifically, research has assumed that emotion regulation and emotional labor are a response to organizationally prescribed emotional display rules (such as displaying positive emotions to customers). I challenge this assumption (as well as other problematic assumptions made by the extant literature on emotional labor) by integrating situations where employees create their own display rules in response to the specific context they are in (for instance they might decide to show frustration towards a customer). Further, this dissertation asserts that the aforementioned narrow conceptualization of emotional display rules has had the unintended consequence of focusing only on a small portion of employees (i.e., those that attempt to follow the display rules prescribed to them by their organization). Across 3 studies, I developed two new measures capturing the situation-person interaction of emotional display rule sources and conduct both variable- and person-centered analyses that allow me to integrate previously unidentified subpopulations of employees into the larger emotional labor literature. Copyright by NIKHIL AWASTY 2022 ACKNOWLEDGEMENTS I could not have picked a better place to get my PhD than the Management department at MSU. I was given an amazing combination of support and training throughout my time in the doctoral program, which has set me up for success in academia. I have many people to thank for helping me not only survive, but thrive, during my doctoral studies. First, I want to thank my advisor Brent Scott who has been a mentor, friend, and indispensable support system, especially through the pandemic years that constituted the final stretch of graduate school. I am sincerely grateful for all the time and energy Brent invested in my professional development and the one-on-one conversations that were filled with good humor and joy no matter the circumstances. I would also like to thank my committee members who have given me tremendous amounts of support and advice over the past six years: John Hollenbeck, Don Conlon, and Lance Ferris. I am grateful to John for taking me under his wing early in the program, teaching me the art of writing and framing arguments, and most importantly for making me feel at home in a new country and career. I’d like to thank Don for bringing me to MSU after we spent time together in India before my PhD. Don has always been in my corner, as a collaborator but also as department chair where he helped me develop into the instructor I have become today, for which I will be forever grateful. I would like to thank Lance for helping me become a better writer, something I struggled with most moving to academia. Most importantly, I am grateful to Lance for his incredible sense of humor which made even the most difficult days and tasks a rewarding experience. I am thankful to the senior students who became mentors to me early in the program, and my cohort, and Sue Polhamus, all of whom became my home away from home. I would like to thank my wife Radhika, and my parents and sisters, who push me to be a better version of iv myself every day. Finally, I’d like to thank my pre-Phd advisor Ruchi Sinha, without whom I would still be selling Coca-Cola in rural India. v TABLE OF CONTENTS LIST OF TABLES ......................................................................................................................... ix LIST OF FIGURES ....................................................................................................................... xi INTRODUCTION ...........................................................................................................................1 LITERATURE REVIEW: EMOTIONAL LABOR AND EMOTIONAL DISPLAY RULES ....12 Introduction to Emotional Labor ............................................................................................12 Emotional Display Rules ........................................................................................................12 Early Work on Emotional Display Rules in Related Fields ...................................................14 Early Work on Display Rules in Organizational Research ....................................................16 Emotional Dissonance and Emotional Deviance ....................................................................18 Source of Display Rules .........................................................................................................22 Early work on source of display rules................................................................................23 Prescribed display rules .....................................................................................................25 Contextual display rules .....................................................................................................26 CRITICAL (AND PROBLEMATIC) ASSUMPTIONS AND MIXED FINDINGS IN EMOTIONAL DISPLAY RULE RESEARCH.............................................................................28 Mixed findings in the emotional labor literature ....................................................................28 Skewed focus on PDRs ...........................................................................................................29 Assumption that PDR strength is static ..................................................................................30 Assumption that PDRs align with higher order performance goals (and all DDR being maladaptive) ...........................................................................................................................32 Redefining Contextual Display Rules ....................................................................................34 PERSON-CENTERED APPROACH............................................................................................37 Introduction to Person-Centered Approach ............................................................................37 Differences From and Advantages Over Variable-Centered Approaches ..............................39 PROPOSED DISPLAY RULE SOURCE BASED ACTOR PROFILES .....................................41 Display Rule Based Actor Profiles .........................................................................................41 Deviators ............................................................................................................................42 Proactives ...........................................................................................................................45 Rule-Followers ...................................................................................................................48 Passives ..............................................................................................................................49 Role of Emotional Regulation Strategies ...............................................................................51 THEORY DEVELOPMENT .........................................................................................................54 Theoretical Background..........................................................................................................54 Introduction to theory of emotional labor ..........................................................................54 Job Demands-Resources Theory of Burnout (JD-R) .........................................................55 Self-Determination Theory’s View on Self-Regulation ....................................................56 vi HYPOTHESES DEVELOPMENT ...............................................................................................59 Felt Inauthenticity ...................................................................................................................59 Felt inauthenticity & key outcomes ...................................................................................63 Ego Depletion .........................................................................................................................66 Ego Depletion & key outcomes .........................................................................................69 Autonomy ...............................................................................................................................71 Autonomy & key outcomes ...............................................................................................73 Social interaction quality ........................................................................................................75 Social interaction quality & key outcomes ........................................................................78 METHODS ....................................................................................................................................81 Summary .................................................................................................................................81 Study 1 ....................................................................................................................................81 Participants, procedure, and proposed analyses .................................................................81 Study 1 Measures ....................................................................................................................83 Study 1 Results .......................................................................................................................87 Phase 1: Item refinement ...................................................................................................87 Phase 2: Convergent and discriminant validity .................................................................91 Study 1 Discussion .................................................................................................................93 Study 2 ....................................................................................................................................94 Participants and procedure .................................................................................................94 Study 2 Measures ....................................................................................................................95 Study 2 Analyses ....................................................................................................................98 Study 2 Results .....................................................................................................................100 Test of Hypotheses ...........................................................................................................100 Latent Profile Analyses ....................................................................................................104 Study 2 Discussion ...............................................................................................................105 Study 3 ..................................................................................................................................107 Participants and procedure ...............................................................................................107 Analyses and measures ....................................................................................................107 Study 3 Results and Discussion ............................................................................................107 SUPPLEMENTARY ANALYSES .............................................................................................109 Supplementary Path Model Analyses ...................................................................................109 Control sub-facet of tendency to adopt CDRs and strength of PDRs for internal organizational members ...................................................................................................109 Control sub-facet of tendency to adopt CDRs and strength of PDRs for external organizational members ...................................................................................................110 Rule-breaking sub-facet of tendency to adopt CDRs and strength of PDRs for internal organizational members ...................................................................................................111 Rule-breaking sub-facet of tendency to adopt CDRs and strength of PDRs for external organizational members ...................................................................................................112 LPA Auxiliary Modeling ......................................................................................................112 GENERAL DISCUSSION ..........................................................................................................119 Summary and highlights of findings.....................................................................................119 vii Scale development ...........................................................................................................119 Variable-centered approach .............................................................................................120 Person-centered approach ................................................................................................120 Supplementary Analyses ......................................................................................................120 Theoretical Implications .......................................................................................................123 Practical Implications ...........................................................................................................128 Strengths, Limitations, and Future Research Directions ......................................................129 CONCLUSION ............................................................................................................................131 APPENDICES .............................................................................................................................132 APPENDIX A: Tables and figures .......................................................................................133 APPENDIX B: Measures .....................................................................................................164 REFERENCES ............................................................................................................................184 viii LIST OF TABLES Table 1 - Descriptive Statistics, Correlations, and Reliabilities for Sample 1 of Study 1. ..........134 Table 2 - Descriptive Statistics, Correlations, and Reliabilities for Sample 2 of Study 1. ..........135 Table 3 – Results of exploratory factor analysis for Strength of PDRs .......................................136 Table 4 – Results of exploratory factor analysis for Tendency to adopt CDRs ..........................137 Table 5 - Descriptive Statistics, Correlations, and Reliabilities For Study 2 ..............................139 Table 6 - Results of path analysis for Study 2 .............................................................................141 Table 7 - Indirect effects, conditional indirect effects, and moderated mediation results for Study 2....................................................................................................................................................142 Table 8 - Fit Statistics for Profile Structures in Study 2 and Study 3 ..........................................144 Table 9 – LPA Three-Step Results for Outcomes for Study 2 ....................................................145 Table 10 - Results of supplementary path analysis using the control sub-facet of tendency to adopt CDRs and the internal sub-facet of strength of PDRs .......................................................146 Table 11 - Indirect effects, conditional indirect effects, and moderated mediation results for supplementary analysis using the control sub-facet of tendency to adopt CDRs and the internal sub-facet of strength of PDRs. .....................................................................................................147 Table 12 - Results of supplementary path analysis using the control sub-facet of tendency to adopt CDRs and the external sub-facet of strength of PDRs .......................................................149 Table 13 - Indirect effects, conditional indirect effects, and moderated mediation results for supplementary analysis using the control sub-facet of tendency to adopt CDRs and the external sub-facet of strength of PDRs ......................................................................................................150 Table 14 - Results of supplementary path analysis using the rule-breaking sub-facet of tendency to adopt CDRs and the internal sub-facet of strength of PDRs ...................................................152 Table 15 - Indirect effects, conditional indirect effects, and moderated mediation results for supplementary analysis using the rule-breaking sub-facet of tendency to adopt CDRs and the internal sub-facet of strength of PDRs .........................................................................................153 Table 16 - Results of supplementary path analysis using the rule-breaking sub-facet of tendency to adopt CDRs and the external sub-facet of strength of PDRs ...................................................155 ix Table 17 - Indirect effects, conditional indirect effects, and moderated mediation results for supplementary analysis using the rule-breaking sub-facet of tendency to adopt CDRs and the external sub-facet of strength of PDRs ........................................................................................156 x LIST OF FIGURES Figure 1 - Hypothetical display rule profiles. ..............................................................................158 Figure 2 - Proposed model path diagram .....................................................................................159 Figure 3 - Interaction Between Tendency to adopt CDRs and PDR strength predicting felt Inauthenticity ...............................................................................................................................160 Figure 4 - Latent profiles for emotional display rule based actors in Study 2 .............................161 Figure 5 - Latent profiles for emotional display rule based in Study 3 .......................................162 Figure 6 - Interaction between rule-breaking sub-facet of tendency to adopt CDRs and internal PDR strength predicting felt inauthenticity .................................................................................163 xi INTRODUCTION Emotional labor, the process by which individuals attempt to regulate their emotional displays in order to meet various situational requirements (Hochschild Arlie, 1983), has received considerable attention from organizational scholars over the past three decades. Indeed, a search of the key words ‘emotional labor’ in PsycInfo yielded almost 3000 hits, 40% of which occurred in the span of the last six years (2015-2021). This increased interest in emotional labor research runs parallel to on-ground organizational realities wherein managing one’s emotions is more important than ever before with the majority of all work now being conducted in team contexts (Ilgen et al., 2005; Mathieu et al., 2017). Recognizing the significance of managing one’s emotions at work, there has been a significant amount of scholarly attention paid to the various antecedents and outcomes of emotional labor (Grandey & Gabriel, 2015). Perhaps the most important antecedent of emotional labor are workplace emotional display rules. Emotional display rules refer to the emotions that are appropriate to display to others (Diefendorff & Richard, 2003; Ekman, 1973b). The fundamental principle underlying emotional labor states that when an individual’s felt emotion is different from the emotion they are expected to display, they may expend effort to display the required emotion. These expected emotional displays or emotional display rules provide guidelines to employees as to the most appropriate emotional displays in any given interpersonal interaction (Ekman, 1973a) and constitute the end goal of, and thus the main motivation for, any emotional labor attempt (Ashforth & Humphrey, 1993; Cropanzano et al., 2003; Diefendorff & Gosserand, 2003; Grandey, 2000; Rafaeli & Sutton, 1987). Research on display rules has typically focused on the content of different display rules; that is whether display rules require individuals to display positive, negative, or neutral 1 emotional displays (Wharton & Erickson, 1993). However, the existing literature on emotional labor has largely ignored the source of these workplace emotional display rules barring a few exceptions (Diefendorff et al., 2010; Diefendorff & Greguras, 2009; Richard & Converse, 2016). Based on the limited theoretical and empirical work examining where such display rules originate, there are two distinct forms of emotional display rules depending on whether the source of the display rule is external (dictated by the organization) or internal (decided on by the individual). Specifically, emotional labor scholars have traditionally viewed display rules as being externally prescribed standards for emotional expression by the organization (e.g., Diefendorff & Richard, 2003; Schaubroeck & Jones, 2000) which are referred to as prescribed display rules (PDRs; Diefendorff & Richard, 2008). However, early conceptualizations of display rules were not rooted in workplaces but in more general interpersonal interactions. They were viewed as being individual perceptions of the appropriate emotional expressions for any given situation (Ekman, 1973) and are referred to as contextual display rules (CDRs; Diefendorff & Richard, 2008). Further, emotional labor scholars have also studied situations where employees choose to display an emotion that is different from expected display rules, thereby violating the expected rules of emotional expression, which is referred to as emotional deviance (Rafaeli & Sutton, 1987) or deviance from display rules (DDR). This dissertation aims to add to the small body of work that acknowledges the importance of CDRs and extends our understanding of emotional labor more generally by integrating what is very likely to be a ubiquitous phenomenon that has significant ramifications for critical individual outcomes of emotional regulation at work. It is the contention of this dissertation that the emotional labor literature has made certain critical assumptions concerning display rules and emotional deviance that are problematic, 2 leading to inconsistent and sometimes skewed findings regarding the effects of emotional labor on individual attitudes and well-being (Bono & Vey, 2005). First, existing emotional labor literature has focused almost solely on PDRs as the primary end goal of any emotion regulation process (Goldberg & Grandey, 2007; Grandey, 2000; Paul et al., 2015; Randolph & Dahling, 2013). Although a few research studies have acknowledged the possibility of employees having control over deciding the contextual appropriateness of the in-role expectations set by the organization and creating their own CDRs (e.g., Richard & Converse, 2016), we still lack any insight into what causes individuals to break from PDRs at work and create context specific display rules or what happens to individuals once they do decide to create and adopt CDRs. For example, a salesperson is expected (and often trained) to display positive emotions to customers but may decide to show disappointment (as opposed to enthusiasm) if they believe it will help them close a deal. This decision to break from organizationally prescribed display rules has yet to be meaningfully integrated into the emotional labor literature (with the exception of the concept of emotional deviance, discussed in more detail later). This myopic view of display rules as largely being prescribed by organizations is especially problematic as it effectively precludes individuals who assert agency in deciding the most appropriate emotional display for a particular situation. Indeed, the idea that emotional display rules can change across contexts and targets seems to be in disagreement with large swaths of the extant work on emotional labor which has assumed that employees are given a single set of display rules that apply across situations and contexts, whether they be explicitly or implicitly mandated by the organization (e.g., Diefendorff & Richard, 2003; Schaubroeck & Jones, 2000). Further, we know from the work done by Matsumoto and colleagues that display rules are often a function of an individual’s beliefs and values, and the target of the interpersonal 3 interaction (Matsumoto, 1990; Matsumoto et al., 2008; Matsumoto et al., 1998; Matsumoto et al., 2005). Therefore, this dissertation will attempt to challenge this rather pervasive assumption by attempting to integrate the individuals who adopt more CDRs at work into the theorizing around emotional labor and showcasing how the inclusion of these individuals can challenge the existing consensus on the effect of emotional labor on important individual outcomes typically studied by emotional labor scholars. Second, emotional labor scholars have tended to assume a static strength of PDRs in the workplaces they study (e.g., Judge et al., 2009; Totterdell & Holman, 2003; see Christoforou & Ashforth, 2015 for an exception). Notably, they have not accounted for the effect of varying levels of display rule flexibility at work wherein certain workplaces or roles can have weakly enforced PDRs, giving individuals the opportunity to exert a certain level of agency in deciding the most appropriate CDR for any specific situation. For instance, while a factory manager might have strict safety related rules to adhere to without any room for deviation, she would have ample room to decide what emotional displays would be most appropriate in her role depending on the target she is interacting with (a supervisor or coworker for instance) and the situation she is facing. On the other hand, some workplaces or roles can have stronger PDRs wherein individual employees are expected to not deviate at all from what is expected by the organization (Christoforou & Ashforth, 2015). For instance, a server at a restaurant is expected to display integrative emotional displays (amplify positive emotional displays and suppress negative displays) which is common in service or customer facing roles (Ashforth & Humphrey, 1993; Groth et al., 2009; Totterdell & Holman, 2003), in which case the server has relatively little (if any) wiggle room on deciding which emotion to display to customers. This dissertation will 4 attempt to formally theorize the situation-person interaction between strength of PDRs and adoption of CDRs to highlight a hitherto ignored critical individual difference. Third, nearly all the existing work on emotional deviance suggests that deviating from PDRs is a form of maladaptive or even deviant workplace behavior (see Dahling, 2017 for a review). This assertion assumes that PDRs are always aligned with higher order organizational or lower order individual goals. If that were the case, then violating organizationally PDRs would indeed be maladaptive. However, I posit that such findings in the literature are an artifact of an incomplete view of work contexts in which individual employees experience emotional labor, wherein the only assumed PDRs are those that are inherently related to individual and organizational performance goals. Further, this is also likely in part because of a skewed focus on customer facing work contexts which typically have strong PDRs as compared to work contexts where individuals have weaker display rules to follow, such as interactions with coworkers (Tschan et al., 2005). Indeed, emotional labor scholars have often explicitly stated that deviating from display rules is maladaptive based on the explicit assumption that such deviations always coincide with deviating from organizational or individual performance goals (see Zerbe, 2009). However, this assumption is especially problematic when PDRs do not align with individual and/or organizational goals. Consider the example of the server at a restaurant mentioned above. The server’s individual goal (for instance, getting a tip) and/or organizational goal (for instance, customer retention) may require the server to break from the strongly prescribed display rule of displaying positive emotions and suppressing negative emotions if the customer is unhappy with their order. In such a situation, the server could decide to show concern and frustration while throwing the kitchen staff under the bus (to save their own tip) and/or showing sympathy (to retain the customer). In such an example, one can clearly see how 5 the usually strong PDR can be misaligned with either the individual or organizational goal, requiring the sever to “think on their feet” to create and adopt a CDR of showing concern, frustration, or sympathy. Therefore, this dissertation will attempt to showcase that employees can decide to deviate from PDRs as an adaptive response to a specific situation or interpersonal interaction when organizational or individual goals are incompatible with existing PDRs. Taken together, the above-mentioned critical assumptions have led emotional labor scholars to focus on a small portion of the working population; that is, individuals who are in workplaces with strong PDR contexts (mainly customer facing jobs such as flight attendants; Hochschild Arlie, 1983). Additionally, even in such work contexts the existing literature has focused on situations where emotional deviance on part of individual employees is considered maladaptive, excluding situations where PDRs do not align with higher order performance goals (such as with the above example of the server in the restaurant) and therefore focusing only on those individuals who largely tend to not deviate from organizationally PDRs. This dissertation claims that this limited focus of the existing emotional labor literature has had the unintended consequence of precluding significant subpopulations of workers that work in weak PDR contexts (and therefore have more freedom to adopt their own CDRs) and those that consciously engage in functional forms of deviance from display rules at work. Traditionally, emotional labor research has examined the effect of emotion regulation by asking individual employees to self-report how they managed their emotions and then to examine the relationships between their emotional labor and outcomes of interest (e.g., Brotheridge & Lee, 2002; Grandey, 2003; Grandey, Fisk, & Steiner, 2005). This analytic approach adopts a variable-centered lens wherein unique and independent relationships between variables are examined (Craig & Smith, 2000). With the exception of a single study (Gabriel et 6 al., 2015) all the extant work on emotional labor is examined via a variable-centered approach. This dissertation challenges the above listed assumptions and aims to integrate precluded subpopulations into the existing emotional labor conversation by also adopting a person-centered theoretical and analytical lens, in addition to a more traditional variable-centered approach. As described by Zyphur (2009), both person- and variable-centered analytic approaches attempt to examines how focal variables relate to relevant outcomes (e.g., the relation between CDR adoption and wellbeing). However, these two strategies differ in how they treat various variables in a study. That is, “a person-centered approach examines how constructs combine within individuals, whereas a variable-centered approach examines how constructs operate separately between individuals” (Bennett et al., 2016, p. 1637; Wang & Hanges, 2011). Most importantly for the purposes of this dissertation, a person-centered approach accounts for unobserved heterogeneity that variable-centered analyses do not (Wang & Hanges, 2011). Specifically, a person-centered approach allows for the discovery of subpopulations that exist but have so far been unaccounted for by extant emotional labor theory. Therefore, a person-centered approach is uniquely positioned for examining the afore mentioned subpopulations of employees who differ on their motivation to deviate from PDRs (of varying strength) and create their own CDRs and have so far been largely ignored by emotion regulation scholars. Indeed, the central advantage of Latent Profile Analysis (LPA), the person- centered analysis tool I use for this dissertation, is its ability to generate profiles of individuals that are quantitatively and qualitatively unique (Marsh et al., 2009; Wang & Hanges, 2011). Specifically, the profiles vary quantitatively in the absolute level of the specified profile indicators (e.g., profiles could be high or low on strength of PDRs or CDR adoption tendency), and they vary qualitatively in terms of their unique combinations of the profile indicators (e.g., a 7 “Rule-Follower” profile is a combination of strong PDRs and low tendency to adopt CDRs; these profiles are discussed in detail in later sections). It is such qualitative variability that is lost when adopting a variable-centered approach and is one of the main motivations for also incorporating a person-centered approach for this dissertation. Put simply, person-centered analyses (such as LPA) are extremely useful theory building tools but have their limitations when testing the generated theory beyond the development of actor profiles. For a direct test of theory, a traditional variable-centered approach is more appropriate. Owing to the advantages of both approaches, I incorporate both person-centered (by developing and testing emotional display-based actor profiles) and variable-centered (by testing a traditional moderated-mediation model) into this dissertation. Taken together, this dissertation aims to make multiple contributions to the existing emotional labor literature. First, this dissertation extends research on emotional display rules by examining the source of the display rules themselves. I do this by relying on both variable- and person-centered approaches to test the effects of CDR adoption tendencies and PDR strength on key mechanisms and outcomes, and to develop theoretically grounded, distinct latent actor profiles that highlight subpopulations that have been ignored by the existing emotional labor research. Specifically, I add to the burgeoning literature that relies on person-centered analytical techniques to empirically identify different subpopulations of workers based on the combination of PDR strength and their tendency to adopt CDRs. In doing so, I will highlight how the existing emotional labor literature has largely focused their attention on one of potentially four theoretically derived subpopulations of workers, leaving considerable room to shift existing consensus regarding the effect of emotional labor on important individual outcomes. 8 Second, I integrate theories of self-regulation (i.e. the Job Demands-Resources model of Burnout and Self Determination Theory’s view on self-regulation) with what is generally referred to as “emotional labor theory” (Grandey, 2000; Grandey & Melloy, 2017) to test the relationships between tendencies to adopt CDRs, PDR strength and focal mechanisms (felt- inauthenticity, ego depletion, autonomy and social interaction quality) and outcomes typically studied by emotional regulation scholars (job satisfaction, emotional exhaustion and task performance; see Hülsheger & Schewe, 2011; Kammeyer‐Mueller et al., 2013 for meta-analytic reviews). I also draw on these theoretical frameworks to examine how the proposed display rule based actor profiles have differential effects on the focal mechanisms and outcomes. Specifically, I posit that mixed and contradictory findings on the detrimental (e.g., Hochschild Arlie, 1983) or beneficial (e.g., Ashforth & Humphrey, 1993; Coté, 2005) effects of emotional labor on individual well-being and performance are an artifact of not accounting for the sources of emotional display rules for individuals engaging in emotional regulation at work. Additionally, I extend the traditional theory of emotional labor by integrating not just intrapersonal mechanisms (i.e., authenticity, autonomy, and depletion) but also interpersonal mechanisms (social interaction quality) into the examination of emotional display rule sources. Therefore, this dissertation aims to add new insights into the conditions under which emotional display rules can dictate if emotional labor is more or less beneficial for individual well-being and performance. Third, I introduce and create two new measures assessing the source of emotional display rules – “strength of PDRs” and “tendency to adopt CDRs.” I aim to offer initial evidence of the reliability and validity of the two new measures. These measures will also be used to test a moderated-mediation model examining the interaction of the two new proposed constructs and 9 their effects on important mechanisms and outcomes outlined by the theory of emotional labor (Grandey, 2000; Grandey & Melloy, 2017; Hülsheger & Schewe, 2011) and also develop and generate the display rule based actor profiles proposed in this dissertation. Finally, this dissertation contributes to the scant research on the source of emotional display rules by clarifying and redefining CDRs and describing how they differ from PDRs. The limited theoretical and empirical work on the differences between the two sources of display rules is markedly ambiguous (Diefendorff & Richard, 2008; Richard & Converse, 2016). Traditionally, PDRs (e.g., Diefendorff & Gosserand, 2003; Schaubroeck & Jones, 2000) and CDRs (e.g., Ekman, 1973a) have largely existed in distinct and separate scholarly silos. The few studies that have studied them in conjunction have conceptualized PDRs and CDRs as “hierarchically arranged such that CDRs are lower-order goals that serve higher-order (more general) prescriptive display rules" (Richard & Converse, 2016, p. 413). This dissertation challenges this notion by showcasing subpopulations of employees for whom the two types of display rules can be orthogonal (i.e., workers who are in strong PDR work contexts but still chose to deviate and create their own CDRs). In the following sections, I will first review the history and general conclusions from the existing emotional labor literature with a particular focus on the origins and findings from the literature on emotional display rules. Then, I highlight some of the critical issues and problematic assumptions within the literature on emotional display rules and clarify the definitions of PDRs and CDRs. Next, I describe the person-centered approach I will also be adopting for this dissertation, emphasizing its advantages and appropriateness for addressing the issues highlighted in this dissertation. This is followed by a section wherein I introduce and propose the existence of four distinct latent display rule based actor profiles, providing detailed descriptions 10 and examples. Finally, I integrate the JD-R model of burnout (Demerouti et al., 2001) and self- determination theory’s perspective on self-regulation (Ryan & Deci, 2008) with the theory of emotional labor to develop the formal hypotheses for this dissertation. I then end by discussing my methods and results. 11 LITERATURE REVIEW: EMOTIONAL LABOR AND EMOTIONAL DISPLAY RULES Introduction to Emotional Labor Emotional labor, the process by which emotional expression is managed by individuals as part of their work role (Hochschild Arlie, 1983), was introduced by sociologists nearly four decades ago. Since then, research by management and organizational psychology on emotional labor (as well as its counterpart emotion regulation; Gross, 1998) has “seen unprecedented growth and impact” (Grandey & Gabriel, 2015, p. 324). A quick Google Scholar search lists over 60,000 research papers referring to emotional labor in some form, 20,000 of which have been published just in the last five years. The typical emotional labor process assumes that an individual’s genuine felt emotion is different from the emotion they wish to display and entails individuals attempting to display that desired emotion via different emotion regulation strategies (Grandey, 2000; Hochschild, 2012; Hochschild Arlie, 1983; Scott et al., 2020). The vast majority of the existing research on emotional labor has focused in one way or another on the two basic methods of emotion regulation adopted by individuals as part of the emotion labor process; surface acting wherein individuals fake the emotional expression they are expected to display and mask their felt emotion, and deep acting wherein individuals attempt to consciously cultivate the emotion they wish to display and then genuinely display it (Grandey, 2000; Hochschild Arlie, 1983). With the growth of emotional labor research, a certain set of relatively consistent trends have emerged regarding the effects of emotional labor on a slew of work-related outcomes. These results have been replicated by multiple stand-alone empirical studies and meta-analyses (see Bono & Vey, 2005; Hülsheger & Schewe, 2011; Kammeyer‐Mueller et al., 2013; Mesmer- Magnus et al., 2012). Generally speaking, the extant literature suggests a strong positive effect of 12 surface acting on individual illbeing including emotional exhaustion (Hülsheger & Schewe, 2011; Mesmer-Magnus et al., 2012), stress (Kammeyer‐Mueller et al., 2013), psychological strain (Hülsheger & Schewe, 2011), reduced personal accomplishment (Hülsheger & Schewe, 2011; Mesmer-Magnus et al., 2012) and psychosomatic complaints (Hülsheger & Schewe, 2011). Meta-analytic evidence suggests a weak positive or non-significant relationship between deep acting and individual ill-being factors (Hülsheger & Schewe, 2011; Kammeyer‐Mueller et al., 2013; Mesmer-Magnus et al., 2012). Similar trends can be found in the meta-analytic evidence for the effects of emotional labor strategies on individual job attitudes. Specifically, there is considerable consensus that surface acting harms individual job attitudes such as job satisfaction (Hülsheger & Schewe, 2011; Kammeyer‐Mueller et al., 2013; Mesmer-Magnus et al., 2012), and organizational commitment (Hülsheger & Schewe, 2011), and can increase work withdrawal and turnover intentions (Mesmer-Magnus et al., 2012). On the other hand, the effect of deep acting on job attitudes was rather mixed with some studies weak positive effects on job satisfaction (Kammeyer‐Mueller et al., 2013) while others finding no significant relationship (Hülsheger & Schewe, 2011; Mesmer-Magnus et al., 2012). The meta-analytic evidence also suggests that deep acting generally reduces turnover intentions and work withdrawal (Mesmer-Magnus et al., 2012). Clearly, emotional labor is now established as a ubiquitous and important determinant of employee wellbeing and job attitudes. Having acknowledged the importance of managing emotions at work, scholars went on to examine the various antecedents of emotional labor, the most central of which are emotional display rules. In the next section I go over the history and previous research done on emotional display rules in the management and related literatures. 13 Emotional Display Rules Organizational scholars have examined emotional display rules as one of the focal antecedents to emotional labor (Rafaeli & Sutton, 1987) right from its inception. However, the history of the study of emotional display rules originates in the field of cross-cultural research and the work of Ekman and colleagues (Ekman, 1973a; Ekman & Friesen, 1975; Ekman & Rosenberg, 1997). The next few sections will highlight the early work that examined emotional display rules outside the management and organizational psychology literatures, followed by how it has been conceptualized within an organizational context. Early Work on Emotional Display Rules in Related Fields The early groundwork for the study of emotional display rules was established in the 60’s and 70’s when research on facial expressions experienced a boom with a slew of scholarly work that systematically identified and examined how certain ‘facial poses’ (Tomkins & Affect, 1962; Tomkins & McCarter, 1964) could be consistently identified by observers. This work was carried forward by Ekman and colleagues (Ekman & Friesen, 1971; Ekman et al., 1969; Izard, 1971) who examined facial expressions across different cultures, finding consistent patterns of recognition across cross-culture populations. It was in their work examining cross-cultural differences in emotional displays that Ekman and Friesen (1969) coined the term ‘display rules’. They describe display rules as the reason “to manage the appearance of particular emotions in particular situation” (Ekman & Friesen, 1975, p. 137). Further, Ekman and Friesen (1975) suggest that while certain display rules are ingrained in us from a young age based on our cultural upbringing and context, often times operating based on muscle memory or “as habits, much like driving a car” (Ekman & Friesen, 1975, p. 138). They suggested that when faced with unfamiliar or stressful situations, 14 individuals will often pause to consider the most appropriate emotional display for that situation. They decide on the most appropriate emotional display by accounting for the situation, their role (or goal), and what is implicitly or explicitly expected of them. Indeed, Ekman and colleagues do acknowledge that individuals may need to “control” their facial expressions (follow display rules) because of their vocation (such as with actors needing to display emotions for a character they are playing or a diplomat showing a neutral facial expression) or “because it is to their advantage at a particular moment” (Ekman & Friesen, 1975, p. 20). Since the establishment of display rules, much research has also studied the role played by display rules in socialization which is an important precursor to how organizational scholars would eventually conceptualize display rules at work. Specifically, research on the development and management of emotional display rules in children highlighted the importance of the social context in deciding on the most appropriate emotional expression (Saarni, 1979, 1982, 1984) for a given social situation. This line of research posits that children gradually develop the ability to modify their emotional expressions to achieve a certain impression in the minds of others (Saarni, 1984), which forms the bedrock for adults to do the same. It is only fitting that the broad dichotomy of how display rules are perceived and used by adult individuals – as prescribed do’s and don’ts or as volitional decisions depending on the situation or context – has a basis in childhood development (e.g., Cole, 1985; Saarni, 1981). In sum, the earliest work on emotional display rules suggests that these display rules impact all emotional expression, whether these be culturally prescribed, or agentic decisions made in response to specific social situations. For the purposes of this dissertation, this early work lays the foundation for the two primary sources of workplace emotional display rules (prescribed and contextual). Put simply, emotional display rules are not just “the degree of 15 appropriateness of expressing emotions” (Matsumoto, 1990, p. 212) but also “an evaluation of a behavioral response relative to appropriateness” (Matsumoto, 1990, p. 212). Early Work on Display Rules in Organizational Research The primary precursor to the study of emotional labor in general and emotional display rules specifically can be traced to the work of social psychologist Arlie Hochschild (Hochschild, 1979; Hochschild Arlie, 1983). In her seminal work on emotional labor, Hochschild developed the concept of feeling rules a precursor to the current conceptualization of emotional display rules (Hochschild, 1979). She describes feeling rules as expectations for certain emotional displays given a specific situation. These feeling rules form the motivation for the verbal and non-verbal actions undertaken by individuals. Subsequent research drew a through line from Hochschild’s concept of feeling rules to Ekman’s (1972) concept of display rules with the former dealing with modifying felt emotions and the latter dealing with modifying expressed emotional displays (Saarni, 1982). Eventually, Rafaeli and Sutton (1987) decided to drop the term ‘feeling rules’ in favor of the term ‘display rules’ within the context of organizational research given the relative ease with which observable behaviors (i.e. emotional displays) can be measured in employee populations. Since then, emotional display rules have become the primary focus of emotional labor scholars (Ashforth & Humphrey, 1993; Diefendorff & Richard, 2003; Grandey, 2000; Rafaeli & Sutton, 1987), albeit with the relatively narrow conceptualization of display rules as prescribed expectations placed on employees by their organizations. The adoption of display rules over feeling rules was further emphasized by the theoretical work by Ashforth and Humphrey (1993) wherein they argued that focusing on the emotions that are publicly expressed over those that are felt is not just easier to observe and measure, but that individuals can 16 “conform with display rules without having to "manage" feelings” (Ashforth & Humphrey, 1993, p. 90). Display rules within an organizational context were therefore defined as the expected appropriate emotional displays that employees are expected to conform to in order to “gain control over others in ways that promote organizational goals” (Sutton, 1991, p. 245). These emotional display rules were typically influenced by cultural or societal norms and mores, norms of the specific role or occupation, and overarching organizational norms (Rafaeli & Sutton, 1989). Specifically, societal, or cultural norms are very similar to those discussed in the previous section on the early work on emotional displays and form the baseline for expected emotional code of conduct for employees. Occupational or role-specific norms are more localized and specific than cultural or societal norms, and are a function of the employee’s role. For instance, service occupations are likely to have explicit norms for emotional displays while dealing with customers, while occupations without a customer facing component likely would not. Organizational norms tend to dictate how employees should conduct themselves when interacting with customers and internal stakeholders alike (Ashforth & Humphrey, 1993; Rafaeli & Sutton, 1989). A fair amount of the early work on emotional labor focused on how organizations ensured that employees conformed to these normative emotional display expectations. The three primary practices to promote emotional display rule conformity highlighted by early emotional labor scholars were recruitment and selection, socialization, and rewards and punishment (Ashforth & Humphrey, 1993; Rafaeli & Sutton, 1987, 1989). Indeed, research has shown that for service roles, organizations purposefully select and hire employees with affective dispositions that are appropriate for the job (e.g., flight attendants in Hochschild, 1983; bill collectors in 17 Sutton, 1991). After being recruited, employees in customer facing roles are often formally coached and trained on the appropriate and organizationally expected emotional displays, whether they be to display positive emotions (e.g., store clerks in Rafaeli, 1989) or negative emotions (e.g., bill collectors in Sutton, 1991). Finally, employees are then rewarded for complying with the expected emotional display rules via raises, recognition or promotions or punished for violating expected emotional display norms via poor performance evaluations and other negative reinforcement techniques (e.g., Rafaeli, 1989; Sutton, 1991). The seemingly obvious reason for the emphasis paid by organizations on extracting compliance from employees on desired emotional displays is that such compliance leads to favorable outcomes for the organization and employee. Indeed, research on emotional labor has shown that within service role contexts, following expected emotional display norms can lead to higher customer satisfaction and store sales (Pugh, 2001; Sutton & Rafaeli, 1988), impact employee job satisfaction (Diefendorff & Richard, 2003), customer evaluations (Pugh, 2001), burnout, and sense of personal accomplishment (Brotheridge & Grandey, 2002). On the flip side, research has also emphasized the negative consequences of deviating from organizationally prescribed emotional display rules. The next section discusses the concept of emotional deviance and highlights the key findings regarding deviating from display rules. Emotional Dissonance and Emotional Deviance Within the emotional labor literature there are two other concepts that are especially germane when examining the effects of emotional display rules on individual well-being and performance, namely, emotional dissonance and emotional deviance. Emotional dissonance occurs when individuals express emotions that conform with organizationally PDRs, but are not aligned with their genuinely felt emotions (Rafaeli & Sutton, 1987). Emotional dissonance has 18 received almost as much attention from emotional labor scholars as any other aspect of the emotion regulation process. This is largely due to the heavy focus by researchers on the effects of emotion regulation strategies such as surface and deep acting, wherein the discrepancy between the emotion an individual is expected to display and the emotion they are feeling (i.e., emotional dissonance) forms the core rationale for the consensus around the harmful effects of emotional labor (Grandey, 2000; Hochschild Arlie, 1983; Rafaeli, 1989; Rafaeli & Sutton, 1987). Indeed, multiple studies have found a range of negative outcomes from emotional dissonance including but not limited to lower job satisfaction (Abraham, 1998a; Lawler III, 1973; Rutter & Fielding, 1988), higher emotional exhaustion and burnout (Abraham, 1998b; Morris & Feldman, 1996; Rafaeli & Sutton, 1987), increased stress (Abraham, 1998b), increased job-induced tension (Abraham, 1999a), hurt organizational commitment (Abraham, 1999b), and stimulated intention to turnover (Abraham, 1999b). While many more research studies have examined the antecedents and outcomes of emotional dissonance, relatively few studies have considered the concept of emotional deviance. Introduced by Rafaeli and Sutton (1989), emotional deviance broadly refers to the violation of organizationally PDRs by acting out emotions unsanctioned by the organization. Going forward, I will refer to emotional deviance as ‘deviance from display rules’ (DDR) as is the contemporary convention amongst emotions scholars (see Dahling, 2017; Tschan et al., 2005). Put simply, while emotional dissonance refers to the discrepancy between an individual’s felt and displayed emotions, DDR refers to the volitional discrepancy between an individual’s emotional display and organizationally PDRs (Barger, 2009; Rafaeli & Sutton, 1987; Richard & Converse, 2016; Tschan et al., 2005). 19 There is surprisingly little research examining the antecedents and outcomes of DDR, with the limited existing work focusing solely on DDR as a form of counterproductive workplace behavior (Dahling, 2017; Du et al., 2011). As is going to be a theme and central claim throughout this dissertation, this rather negatively skewed perspective on the effects of DDR on the individual and organization is largely an artifact of the service and client-facing context in which DDR has been studied (e.g., Barger, 2009; Du et al., 2011; Richard & Converse, 2016). So far, DDR has been conceptualized as situations wherein individuals choose to display their genuine felt emotions (usually a negative emotion in retaliation towards a customer, such a frustration or anger) in violation of organizationally prescribed “in-role” display rules. This conceptualization of DDR has shown to have a range of negative consequences such as customer dissatisfaction (Du et al., 2011), loss of customer business to competitors, poor word-of-mouth to other potential customers (Bougie et al., 2003), increased negative affect and lower individual wellbeing (Tschan et al., 2005). Further, because DDR has been studied in the context of it being a deviant workplace behavior, there is also some work suggesting that employees are likely to experience backlash from their managers and organizations for engaging in DDR (Berry et al., 2007; Coté, 2005; Dahling, 2017; Rotundo & Sackett, 2002). There has also been limited work examining the antecedents of DDR and when it is more or less likely to occur. For instance, drawing on theories of resource depletion (Baumeister et al., 2007) and control theories (Diefendorff & Gosserand, 2003), Richard and Diefendorff (2007) found that when individuals feel high levels of negative affect and when they experienced high levels of solidarity with customers, they were more likely to deviate from organizational display rules. These findings were replicated and extended by Richard and Converse (2016) who suggested that along with higher solidarity with the interaction target, relative power and affect 20 activation also positively predicted DDR. Barger (2009) subsequently built upon the work of Richard and Diefendorff (2007) with a cross-sectional study that drew from affective events theory (Weiss & Cropanzano, 1996) that hypothesized customer injustice as a predictor of DDR. She found support for this hypotheses and further suggested that the relationship between customer injustice and DDR would be mediated by anger (Barger, 2009). These findings were further supported by the findings of Richard et al. (2016) who replicated the relationship between customer injustice and DDR mediated by anger, and also found support for supervisor empathy as an important moderator buffering the effects of customer injustice on employee DDR. In the only study of DDR that examined coworker relationships along with customer interactions, Tschan et al. (2005) found that DDR was more likely with interactions with coworkers than with customers likely owing to the weaker display rule requirements when interacting with coworkers. They further found that DDR, whether with coworkers or customers, was consistently related to lower employee wellbeing and higher psychosomatic complaints (Tschan et al., 2005). The study by Tschan et al. (2005) is of particular import to this dissertation as it points to a higher prevalence of DDR within organizations than previously thought, wherein individuals are likely to deviate from expected emotional display norms not just in customer interactions but also in their interactions with their coworkers, supervisors and subordinates on a fairly consistent basis. However, while extant research has acknowledged the importance of display rules in general, and emotional dissonance and deviance more specifically for a variety of critical organizational and individual outcomes, I propose that the findings from the existing research likely skew more negative because it has largely focused on a single source of organizational 21 display rules (externally prescribed display rules). The next section focuses on the history and contemporary conceptualization of different sources of emotional display rules. Source of Display Rules As is evident by the previous sections outlining the history, development and evolution of the emotional display rule concept, there are two distinct conceptualizations of display rules that have been proposed and form the foundation for examining the source of organizational display rules. The first conceptualization of display rules is one originally introduced by Ekman and colleagues (e.g., Ekman, 1973a; Ekman & Friesen, 1975; Ekman & Rosenberg, 1997; Friesen & Ekman, 1978) which states that display rules refer to “the need to manage the appearance of particular emotions in particular situations” (Ekman & Friesen, 1975, p. 137), which are referred to as contextual display rules (Diefendorff & Richard, 2008). The second conceptualization is the one that has been adopted by the vast majority of emotional labor and management scholars wherein display rules refer to organizational expectations for emotional expression that are “externally prescribed by organizations, dictating what individuals should and should not express” (Diefendorff & Richard, 2008, p. 318) when interacting with others at work, usually customers and clients (e.g., Diefendorff & Richard, 2003; Grandey, 2000; Hochschild Arlie, 1983; Rafaeli & Sutton, 1987) which are referred to as prescribed display rules (Diefendorff & Richard, 2008). It is rather surprising that apart from a handful of studies (e.g., Diefendorff et al., 2010; Diefendorff & Greguras, 2009; Richard & Converse, 2016) contemporary scholarly work on emotional labor has not expanded to include both these conceptualizations of display rules. One of the central aims of this dissertation is to integrate the original conceptualization of display rules (that of CDRs) into the management literature and in turn attempt to clarify problematic assumptions and mixed findings that exist in the extant emotional labor literature. In 22 this section I will highlight early work on the source of emotional display rules followed by detailed descriptions of prescribed and contextual display rules. Early work on source of display rules. Some of the earliest work on display rules alluded to, albeit very briefly, where emotional display rules originate. For instance, the seminal work by Ekman and Friesen (1975) outlined four “reasons” for why individuals control their facial expressions, which can also be broadly conceptualized as four sources of emotional display rules most people follow. The first source is cultural (what they call cultural display rules) and are “conventions about facial expression that are followed by all (non-rebellious) members of a given social class, subculture, or culture” (Ekman & Friesen, 1975, p. 138). These include, for instance, display rules governing the intensity of grief that is appropriate to display at a funeral. The second source outlined by Ekman and Friesen (1975) is personal (what they refer to as personal display rules) wherein certain display rules are the byproduct of the idiosyncrasies of the individual and their familial upbringing. For instance, some individuals may have been brought up to never show anger to someone in a position of authority. The third source they outline is vocational (vocational display rules) and are the obvious precursors to the contemporary workplace emotional display rules that are the primary subject of this dissertation. They mention a variety of professions in which managing one’s emotions can be vital such as actors, diplomats, attorneys, salespeople etc. However, Ekman and colleagues only mention this type of display rule in passing, with cultural and personal display rules being the primary focus of their research. Finally, they mention that certain display rules are governed by what they term the “need of the moment” (Ekman & Friesen, 1975, p. 139). Display rules governed by the need of the moment may lead an individual to stray from their cultural, personal, and vocational display rules to display an emotion that is appropriate to the specific situation at hand. For 23 instance, a guilty person on trial will testify to his innocence by lying “with his face as well as his words, to save himself” (Ekman & Friesen, 1975, p. 139), deviating from his own cultural, personal and vocational display rules (unless he is a professional criminal, in which case he may also be relying on vocational display rules). In summary, the cross-cultural roots of emotional display rules, while acknowledging organizational display rules, had a broader conceptualization wherein situational or contextual appropriateness was of primary importance. On the other hand, all the research on emotional labor and emotion regulation that followed the initial work by Hochschild Arlie (1983) and Rafaeli and Sutton (1987) has conceptualized display rules as prescribed and often (though not always) formal expectations from managers and organizations (Ashforth & Humphrey, 1993; Diefendorff & Gosserand, 2003; Diefendorff & Richard, 2003; Grandey, 2000; Gross, 1998). Interestingly, even when scholars acknowledged that employees may need to adapt display rules to account for specific interaction targets and different situations, they did so within the confines of such adaptations to display rules being prescribed by the organization. For instance, in one of the few early studies that examined negative display rule contexts (i.e. wherein employees are expected to display negative emotions and suppress positive emotions when interacting with clients), Sutton (1991) notes that while bill collectors were generally expected to display a sense of urgency when talking with debtors, they were also trained to rely on “contingent norms” (p. 252) of emotional displays. Specifically, the base line display rules for bill collectors were to convey a sense of urgency augmented by displays of irritation or disapproval. However, bill collectors were also expected to diverge from the base line display rules contingent on the debtor’s demeanor. For instance, bill collectors were expected to display warmth to debtors who sounded anxious, display irritation or anger toward debtors who were indifferent, sad or friendly, and display 24 calmness to debtors who sounded angry (Sutton, 1991). These “contingent” emotional display norms were put in place to achieve the overarching organizational goal of collecting late payments from debtors, contingent on the demeanor of the debtor and the appropriate emotional display. In summary, when considering the source of emotional display rules two broad categories emerge (prescribed and contextual) which I will discuss in more detail below. Prescribed display rules. When organizational scholars started to study emotional labor, they conceptualized display rules as the appropriate emotion employees are expected to display as part of their work roles (Ashforth & Humphrey, 1993; Diefendorff & Richard, 2003; Rafaeli & Sutton, 1987). Specifically, display rules are standards of emotional expression that are externally prescribed by the organization as a guide to the emotional displays expected by managers and organizations. As described by Diefendorff and Richard (2008), PDRs are a form of “top-down organizational influence on employee emotional expressions” (p. 319). PDRs have been the focus of emotional labor research, as you will recall from the previous sections, because discrepancies between employee felt emotions and externally imposed display rules are the basis for emotional labor and its effects (Brotheridge & Grandey, 2002; Diefendorff & Gosserand, 2003; Diefendorff & Richard, 2003; Grandey, 2000). Due to the heavy focus on positive display rule contexts, PDRs have tended to be operationalized as demands to express positive emotions and suppress negative emotions (e.g., Diefendorff & Richard, 2003; Schaubroeck & Jones, 2000). This is evident from the items used in scales to measure display rules such as ‘To be effective in my job, I must act cheerful and sociable’ (Diefendorff & Richard, 2003; Schaubroeck & Jones, 2000) and ‘I am expected to suppress my bad moods or negative reactions to customers’ (Brotheridge & Grandey, 2002). 25 While most of the existing emotional labor literature has focused on customer facing, positive display rule contexts, display rules are likely to apply to workplace interactions outside of those with clients or customers. Indeed, there is limited prior research that extended the study of emotional labor to a wider range of workplace interactions wherein organizationally PDRs still apply. For instance, Pugliesi (1999) suggests that the conceptualization of emotional labor as solely relevant to customer interactions is too narrow and should be extended to include interactions with coworkers. Further, other early work on emotional labor suggests that organizations’ expectations of emotional displays do in fact extend to formal and informal interactions with coworkers, and that these coworker-focused PDRs are often most salient and often distressing to employees (Pierce, 1996; Pugliesi & Shook, 1997). This expanded conceptualization of PDRs was also highlighted by Diefendorff and Richard (2008) in their chapter delineating the differences between prescribed and contextual display rules. In summation, PDRs have been the primary focus of emotional labor scholars from its inception and these display rules have been studied and applied to variety of workplace interactions. Contextual display rules. The second type of display rules based on their source are CDRs. CDRs can be defined as “the rules that guide individuals’ emotional expressions at any given moment” (Diefendorff & Richard, 2008, p. 319). These display rules are closer to the original conception of emotional display rules as developed by Ekman (1973a) wherein emotional display rules are “standards of behavior that indicate which emotions are appropriate in a given situation” (Morris & Feldman, 1996, p. 988). There is surprisingly little research focusing on the role played by CDRs when examining the effects of emotional labor. To my knowledge, there are three empirical studies and one book chapter that have examined or at least acknowledged CDRs specifically (Diefendorff et al., 2010; 26 Diefendorff & Richard, 2008; Diefendorff & Greguras, 2009; Richard & Converse, 2016). Diefendorff and Richard (2008) coined the term CDRs to refer to emotional display rules that are not externally prescribed by the organization but are created by the individual employee in response to the specific situation they are in. Their definition of CDRs drew from the early works in cross cultural research wherein individuals decide on the appropriate emotional displays depending on the specific combination of situational factors such as the interaction target, the actor’s felt emotions, and the intended goal of the emotional expression (Diefendorff & Richard, 2008; Matsumoto et al., 2005). Put simply, PDRs are external expectations for emotional expression imposed by the organization and managers on employees, while CDRs are those adopted (and created) by employees depending on the needs of the specific situation at hand. Having covered the existing literatures on emotional labor, emotional display rules, emotional dissonance, deviation from display rules and two types of display rules depending on their source, in the next section I discuss the critical (but problematic) assumptions made by the extant work on emotional display rules and accompanying mixed findings. Clarifying these assumptions and mixed findings forms the crux of this dissertation’s contribution. 27 CRITICAL (AND PROBLEMATIC) ASSUMPTIONS AND MIXED FINDINGS IN EMOTIONAL DISPLAY RULE RESEARCH Mixed findings in the emotional labor literature From the inception of emotional labor as a field of study, research has found relatively consistent support for the harmful effects of emotional labor on individual wellbeing, attitudes, and performance. For instance, early work suggested that high levels of emotional labor led to increased incidences of alcohol and drug abuse, psychosomatic strain, absenteeism (Hochschild, 1983), lower job satisfaction (Wharton, 1993, 1996), and surface acting was found to be especially harmful for individual wellbeing (Hülsheger & Schewe, 2011; Kammeyer‐Mueller et al., 2013; Mesmer-Magnus et al., 2012). However, this general consensus on the negative effects of emotional labor on individual wellbeing is not without its inconsistencies and mixed findings (Bono & Vey, 2005; Coté, 2005). For instance, research has also suggested that individuals can use emotional labor to avoid ambiguity, avoid embarrassing situations at work, and disconnect emotionally from organizational demands leading to increased job satisfaction (Ashforth & Humphrey, 1993; Morris & Feldman, 1997). Tolich (1993) examined American supermarket clerks who had to follow explicit display rules to be friendly with customers and suggested that some clerks enjoyed following the organizationally PDRs that entailed joking and entertaining customers. Even the rather consistent relationship between emotional labor and strain was found to be inconsistent across different types of jobs (Coté, 2005). Indeed, other research has similarly found positive relationships between emotional labor and a sense of personal accomplishment (Brotheridge & Grandey, 2002), job satisfaction (Yang & Chang, 2008), and feelings of authenticity (Brotheridge & Lee, 2002). Early qualitative work examining the effects of 28 emotional labor has also found positive outcomes to emotional labor such as personal fulfillment and meaning, and increased job satisfaction (James, 1989; Tolich, 1993; Wharton, 1996). Further, the recent theoretical work by Scott et al. (2020) similarly brings into question the current consensus on the negative effects of emotional labor by suggesting that they likely paint an incomplete picture lacking nuance because of the skewed focus of the literature on service roles with largely positive display rule contexts. It is the contention of this dissertation that these inconsistent findings are possibly an artifact of the existing literature focusing on a narrow subsection of individuals who experience emotional labor at work, and accounting for the excluded subpopulations (based on source of display rules) of employees will provide a more detailed and nuanced understanding of the relationship between emotional labor and focal outcomes such as emotional exhaustion, job satisfaction and task performance while also clarifying some of the above mentioned mixed findings. Skewed focus on PDRs As mentioned in the previous section, except for three empirical studies (Diefendorff et al., 2010; Diefendorff & Greguras, 2009; Richard & Converse, 2016), the emotional labor research has focused solely on PDRs. Indeed, much of the early and seminal work on emotional labor and therefore emotional display rules focused solely on customer facing, service roles. This is evident by how early studies defined emotional labor, for instance, Morris and Feldman (1996) define emotional labor as “the act of expressing organizationally desired emotions during service transactions” (p. 987). This is also likely why emotional labor scholars have often conceptualized employee emotional displays as something to “be controlled, trained, and prescribed, in employee handbooks” (Miller et al., 2007, p. 233). This skewed focus on PDRs is especially 29 problematic as it implicitly excludes those subpopulations of employees that are more likely to rely on CDRs in their daily interactions at work. This exclusion of such subpopulations that regularly adopt CDRs in favor of organizationally PDRs is potentially responsible for the mixed findings outlined in the previous sub-section. For instance, the inconsistent findings about the relationship between emotional labor and stress or strain could potentially be due to the focus on employees that only follow PDRs and eschew CDR adoption. Assumption that PDR strength is static An implicit assumption across almost all emotional labor research is that there is a constant or static level of expectations from organizations in terms of emotional displays from employees. To my knowledge there is only a single study, conducted by Christoforou and Ashforth (2015), that examines the effect of explicitness of display rules on performance and customer satisfaction. They join a small group of studies (see also VanMaanen & Kunda, 1989) that have alluded to the varying strength of PDRs ranging from “ the absence of prescription to the intense communication of requirements” (Christoforou & Ashforth, 2015, p. 250). Further, the theoretical work done by Ashforth and Humphrey (1993) also acknowledges norm strength, or norm intensity, which they define as “the degree to which a norm is widely shared (consensus) and deeply internalized (potency) among a given aggregate of people” (p. 91). They suggest that norm strength is dependent on the nature of the interactions the individual typically engages in, which in turn is dependent on the type of role they occupy (Ashforth & Humphrey, 1993). However, apart from the few studies mentioned above, the concept of PDR strength is not one that has been integrated in any meaningful way into the emotional labor literature. This is likely due, once again, to the focus of the extant literature on service roles wherein it is assumed 30 (appropriately so) that strong PDRs are imposed on employees. While this is certainly true for customer facing roles, it is likely that much weaker display rules (explicit or implicit) exist in non-customer facing roles. Indeed, research supporting this notion has suggested that norm strength for emotional display rules was stronger for in-person interactions (where emotional expressions play a vital role to the task) as is common for customer facing or service roles (e.g., flight attendants) than for non-service roles (e.g., janitor) (Zerbe & Falkenberg, 1989). Furthermore, when accounting for daily interactions most employees have with coworkers, supervisors or subordinates, there is likely to be a range of PDR strengths depending on the specific situation or interaction partner. For instance, it is likely that subordinates have stronger PDRs when interacting with their supervisors (e.g., cannot show anger or frustration to their supervisor) than with coworkers. Indeed, even certain service organizations avoid prescribing strong display rules and encourage employees to “be themselves” and give employees more autonomy in deciding what emotional displays might be most appropriate (Fineman, 2006; Goldberg & Grandey, 2007; Martin et al., 1998). However, organizations also expect employees to be civil and courteous to customers and coworkers as per societal emotional display norms (Ekman & Friesen, 1971; Matsumoto et al., 2005), which are likely to be far weaker than the strong display rules in customer facing roles. The concept of display rule strength is especially important as roles, workplaces, or interactions with weak PDRs leave more room for individuals to adopt their own CDRs. This dissertation accounts for the different levels of PDR strength (and therefore varying rates of CDR adoption) by identifying situations and subpopulations of employees that engage in emotional regulation across varying levels of PDR strength. 31 Assumption that PDRs align with higher order performance goals (and all DDR being maladaptive) One of the primary assumptions made by the emotional labor literature is that organizationally PDRs help achieve higher-order individual and organizational goals. Most definitions of emotional display rules tend to speak of these rules as formal expectations of the appropriate emotional displays as part of a work role (Diefendorff & Richard, 2008). Indeed, this assumption is often explicitly stated, as exemplified by the review on emotional labor by Holman et al. (2008) wherein they define emotional display rules as “rules [that] specify the type of behavior needed to meet the higher-order goals of performance” (p. 302). Similarly, Diefendorff and Richard (2008) argue that the primary purpose of emotional display rules is in fact to “constrain employee emotional displays in a particular way so as to facilitate the attainment of organizational objectives” (p. 317). The assumption that PDRs always lead to attainment of organizational goals was codified by Cropanzano et al. (2003) who argued that imposing PDRs on employees can aid in achieving three types of organizational goals. First, imposing emotional display rules on employees (and the resulting emotional displays) improves customer satisfaction. There is some support for this assertion, wherein research found that displaying positive emotions to customers improved their satisfaction (e.g., Pugh, 2001; Tsai, 2001). Second, following PDRs can improve harmony among employees of an organization. Specifically, displaying positive emotions to coworkers can improve the quality of interactions amongst employees via the spread of positive emotions (Barsade, 2002; Bartel & Saavedra, 2000). Lastly, displaying positive emotions (as typically required by PDRs) can improve individual wellbeing (Cropanzano et al., 2003). For instance, Diefendorff and Richard (2003) found that when employees had strong PDRs for displaying 32 positive emotions imposed on them, they were more satisfied with their job. In summary, the extant emotional labor literature has assumed that imposing PDRs on employees helps achieve multiple organizational goals. Therefore, it isn’t surprising that, most of the research on display rules has conceptualized (and implicitly assumed) DDR as being maladaptive and such deviations as something to be controlled by the organization (Dahling, 2017; Tschan et al., 2005; Zerbe, 2009). Indeed, categorizing deviating from organizationally PDRs as a deviant behavior is undeniably linked to such behaviors being perceived as hindering goal progress. This line of thinking was best explained by Hollinger and Clark (1982) who suggest that “since deviant activity by organization members can interfere with the achievement of expressed goals and objectives, formal organizations have a vested interest in minimizing the prevalence of employee [emotional] deviance” (p. 334). This rather narrow conceptualization of DDR is likely due to how the construct was initially conceptualized and the context in which it was first developed. When emotional deviance was first introduced, it was defined as “the opposite of emotional dissonance because the organizational member expresses inner feelings and disregards feeling rules” (Rafaeli & Sutton, 1987, p. 33). It is no wonder that the examples typically touted by emotional labor scholars focus solely on individuals breaking from prescribed organizational display rules by instead displaying their felt emotions. For instance, flight attendants not smiling at passengers (Hochschild Arlie, 1983), Disney’s amusement park employees not behaving cheerfully (VanMaanen & Kunda, 1989), bill collectors failing to showcase urgency or anger to debtors (Sutton, 1991), or any other service employee failing to display positive emotions to clients (Rafaeli & Sutton, 1987, 1989). 33 Even when DDR has been examined outside of service role contexts, it is exclusively conceptualized as a form of deviance. For instance, Zerbe (2009) suggests that DDR directed towards customers is a form of production deviance (when an employee is not performing up to the expected standard; Robinson & Bennett, 1995) and DDR directed toward coworkers as a form of political deviance (when an employees behaves inappropriately; Robinson & Bennett, 1995). All the research that has examined the negative impact of DDR has failed to account for situations (and their accompanying subpopulations of employees) wherein PDRs do not align with organizational and/or individual goals, and DDR can be a form of positive rule breaking (Dahling et al., 2012; Morrison, 2006). An important first step in clarifying this assumption is to redefine CDRs and the role they play in achieving organizational and individual goals at work. Redefining Contextual Display Rules When discussing the two types of display rules (prescribed and contextual) based on their source, Diefendorff and Richard (2008) proposed that CDRs be conceptualized as lower order goals that help achieve the higher order goals of organizationally PDRs. Following the work of Diefendorff and Gosserand (2003), Diefendorff and Richard (2008) adopted a control theory lens (Lord & Levy, 1994) to hierarchically order prescribed and contextual display rules. Specifically, Diefendorff and Gosserand (2003) theorized that emotional labor requires individuals to constantly attempt to meet display rule requirements by managing their emotional displays. When employees perceive a discrepancy between their emotional displays and relevant display rules, they are motivated to reduce this discrepancy by either altering their emotional display or their felt emotion to more effectively meet the desired display rule. Diefendorff and Richard (2008) argue that the discrepancy between emotional displays and display rules can also be reduced by changing the display rule to match the emotional display instead of the other way 34 around. Indeed, their motivation to introduce CDRs to the emotional labor literature is in line with the motivation behind this dissertation. Specifically, they point to a problematic assumption made by emotional labor scholars that “the notion that display rules vary across situations seems to be at odds with much of the empirical research on emotional labor which implicitly assumes that employees have one set of display rules that apply to all situations” (Diefendorff & Richard, 2008, p. 321). While Diefendorff and Richard (2008) acknowledge that emotional labor is a dynamic process in which individuals may adopt CDRs as they “interact with their environment over time to produce the most effective emotional display for any given moment” (p. 321), and that “emotional displays and display rules can evolve and shift in response to the demands of situations” (p. 321), they conceptualize CDRs in a surprisingly narrow manner. Specifically, they suggest that CDRs constitute lower order goals that are evoked to achieve higher order goals (organizationally PDRs). Diefendorff and Richard (2008) further posit that changing the display rule to match the employee’s emotional display is likely to be “maladaptive because display rules exist so that individuals can attain some performance objective” (p. 320). Diefendorff and Richard (2008) use this line of thinking to argue for the hierarchical ordering of PDRs and CDRs. Specifically, the authors assume that “display rules represent subgoals in a performance goal hierarchy, and abandoning a display rule in favor of some other display standard (e.g., express one’s felt emotions) can negatively impact on job performance” (Diefendorff & Richard, 2008, p. 320). As mentioned in the previous section, I contend that this line of thinking is problematic as it assumes that all PDRs always align with higher order performance goals, which is not always the case. For instance, once again taking the example of a waiter at a restaurant, he/she potentially 35 has two higher order performance goals: customer retention and tips. In the case of an incorrect order, a waiter may decide to break from the PDRs of showing positive emotions to the customer and instead decide show anger or disappointment at the kitchen staff along with doing what they would have done anyway in terms of giving the customer a free meal or getting the food made again. In this example, the waiter could have potentially decided that the PDRs are not going to help them achieve their performance goals and they decide to adopt a more appropriate CDR instead. Therefore, I propose that CDRs and PDRs are better conceptualized as orthogonal constructs. Specifically, the primary claim of this dissertation is that imposition of PDRs by organizations and adoption of CDRs by individual employees can happen simultaneously in service of achieving a higher order organizational performance goal. This is not to say that CDR adoption cannot aid in achieving PDRs in certain conditions, but that that is one of many possibilities when examining interactions between PDRs and CDRs. This reconceptualized definition of CDRs forms the foundation of both the variable-centered approach and the display rule latent profiles proposed in this dissertation. Before discussing the various actor profiles, in the next section I introduce the person-centered approach that is also adopted in this dissertation and explain how it is uniquely positioned to challenge the problematic assumptions mentioned in the previous section, over and above traditional variable-centered approaches. 36 PERSON-CENTERED APPROACH Introduction to Person-Centered Approach Over the past decade, an increasing number of organizational scholars have argued for the importance of, and have adopted, a person-centered approach (Gabriel et al., 2018; Wang & Hanges, 2011). Organizational researchers are already familiar with using dimensional approaches (such as factor analysis) to examining various phenomena at work. These approaches typically use interrelatedness (such as covariances or a higher order latent factor) amongst the focal variables to infer insights on underlying process and causal mechanisms. More recently another form of capturing interrelatedness among constructs, one based on “unobserved heterogeneity of the population” (Wang & Hanges, 2011, p. 24), has started to become more popular in organizational research. Specifically, this “unobserved heterogeneity (also known as latent classes or latent mixture) often manifests specific configurations or patterns of observed individual and/or environmental variables (e.g., different types of person–environment fit), and a family of statistical methods, called latent class procedures, has been developed to estimate this unobserved heterogeneity” (Wang & Hanges, 2011, p. 25). These procedures to examine the unobserved heterogeneity forms the backbone of person-centered approaches to studying organizational phenomena. Person-centered approaches such as LPA primarily attempt to identify quantitatively and qualitatively distinct actor profiles from a given sample (Gabriel et al., 2018). Specifically, profiles can vary in their absolute level on each indicator (these would be quantitively distinct profiles) and in their shape or relative standing on each indicator (these would be qualitatively distinct profiles). The qualitative differences in actor profiles are a unique advantage of LPA over traditional cluster analyses which “forces” individuals into one profile or another, while 37 LPA accounts for the fact that individuals may not neatly fit into one profile but have shades of multiple levels on each indicator (Gabriel et al., 2018; Wang & Hanges, 2011). Once actor profiles have been identified, researchers can then examine what individual differences predict profile membership and how profile membership can lead to differences in outcomes of interest. In the recent past there has been a flurry of person-centered research in both organizational behavior and human resource management research. Leading the way in this relatively young approach are organizational commitment scholars who have adopted person- centered approaches with great enthusiasm and identified multiple subpopulations and actor profiles that vary in levels of the three primary forms of organizational commitment (i.e., affective, normative and continuance; Kabins et al., 2016; Meyer & Morin, 2016; Morin et al., 2011). Similarly, leadership scholars have also adopted person-centered approaches to identify unique leader profiles based on follower perceptions (Foti et al., 2012). Even emotional labor research has embraced person-centered approaches recently with Gabriel et al. (2015) using latent profile analysis to identify qualitatively and quantitatively unique actor profiles based on the different ways and levels at which individuals use surface and deep acting emotion regulation strategies. Research on recovery and psychological wellbeing have also adopted a person- centered lens to identify actor profiles (Bennett et al., 2016; Morin et al., 2017). Finally, drawing from self-determination theory (Deci & Ryan, 1980; Gagné & Deci, 2005), motivation researchers have built upon the foundation laid by previous variable-centered research and traditional cluster analyses to develop and identify actor profiles related to motivation based on need fulfilment (Graves et al., 2015; Howard et al., 2016). Human resource management research has also started relying on person-centered research with Woo and Allen (2014) once 38 again using LPA to examine intentions to turnover and identifying actor profiles of “stayers” and “leavers”. In summary, even though organizational person-centered research is in its nascency, it has started to gather significant steam behind a slew of research across varied fields of study, showcasing its utility and versatility in uncovering unique insights not possible with traditional variable-centered approaches. Next, I discuss these unique advantages over variable-centered research in more detail. Differences From and Advantages Over Variable-Centered Approaches As discussed above, over the past decade person-centered approaches to organizational research have been gaining traction with many scholars arguing for their importance (Gabriel et al., 2018; Wang & Hanges, 2011). When discussing the importance of person-centered approaches, it is equally important to showcase the advantages of such approaches when compared to more traditional variable focused approaches. Variable focused approaches (such as regression analyses, ANNOVA etc.) are great for examining relationships between predictors and outcomes, and identifying mediating mechanisms and boundary conditions for such relationships (Cohen et al., 2013). On the other hand, person-centered approaches aim to identify actor profiles that represent specific combinations of focal individual or situational characteristics and how various antecedents and outcomes vary across those profiles (Gabriel et al., 2018; Wang & Hanges, 2011). Put simply, while both person- and variable-centered analytic approaches attempt to examine how focal variables relate to outcomes of interest, person- centered approaches focus on how focal constructs combine within persons while variable centered approaches focus on how focal variables function discretely between persons (Wang & Hanges, 2011). Gabriel et al. (2015) argue for the advantage of person-centered approaches over 39 variable-centered approaches by stating that “theoretical frameworks applied to broad samples with little consideration of unobserved heterogeneity may miss nuances in the way constructs operate” (p. 865). Essentially, person-centered approaches account for individuals as a combination of traits as opposed to variable-centered approaches which tend to focus on traits in isolation (De Fruyt, 2002). Further, person-centered approaches such as LPA “identify constellations of constructs that exist within a sample by modeling the unobserved heterogeneity present within the data” (Gabriel et al., 2018, p. 881) while variable-centered approaches tend to implicitly “ignore the fact that participants may come from different subpopulations in which the observed relations between variables may differ” (Morin et al., 2011, p. 59). Therefore, the primary advantage of person-centered analytic approaches like LPA is that they help identify relevant subpopulations of employees (Morin et al., 2011) which can then be used to create theoretically meaningful actor profiles. 40 PROPOSED DISPLAY RULE SOURCE BASED ACTOR PROFILES Now that I have established the need for, and advantages of, a person-centered approach to examining the source of emotional display rules, this section focuses on the description of the four proposed actor profiles. It is important to note before proceeding that I am treating the proposed actor profiles as a relatively stable between-person individual difference, in line with previous research on latent profiles within the emotional labor literature (see Gabriel et al., 2015). Indeed, not only is this in line with previous emotional labor research, but some of the behaviors I am investigating have to do with proactivity and deviance which have been found to have almost a 50-50 split between variance within and between people (see Cangiano et al., 2019; Ferris et al., 2012; Judge et al., 2006). Although I expect these actor profiles to represent stable individual differences, it does not exclude the possibility of within-person variance across interactions, situations, days or targets, a point to which to return to in the discussion. However, as the first foray into the exploration of display rule based actor profiles, it is an important first step to identify the actor profiles that exist by treating them as a between person stable individual difference. Display Rule Based Actor Profiles I propose that there are four qualitatively and quantitatively distinct emotional display rule based actor profiles that employees can be slotted in to, which I label Deviators, Proactives, Rule-Followers and Passives (see Figure 1). These hypothesized actor profiles are based on a person-situation interaction; specifically, the interaction between the individual’s (stable) tendency to create and adopt CDRs and the strength of PDRs mandated by the individual’s work environment. The overarching assertion of this dissertation is that these four actor profiles exist 41 and have an important influence on key mechanisms and work outcomes typically examined in the emotional labor literature. I will now discuss these four profiles in more detail. Deviators. Deviators are characterized by their high propensity to adopt CDRs while working in an environment with strong organizationally PDRs. Work roles with strong PDRs form most of the extant emotional labor literature (see Grandey & Gabriel, 2015). Such strong display rule contexts typically entail organizations providing explicit guidance and even a “script” to employees to engage in emotion regulation (Diefendorff & Gosserand, 2003; Grandey, 2000; Kammeyer‐Mueller et al., 2013). Such work roles are typically customer facing or service- oriented roles wherein there is relatively little leeway given to employees in terms of variation in their emotional displays. Due to their strong tendencies to think independently, exert their agency in any given interaction, and need to achieve their assigned goals, Deviators are far more likely than other employees to deviate from PDRs and adopt CDRs they deem to be more appropriate for the specific situation they are in. I propose that there are likely two types of Deviators, based on different intentions, that none the less are likely to behave in a similar manner and reject existing display rules in lieu of their own CDRs. The first type of Deviators are those that deviate from organizationally PDRs in “bad faith” (Abraham, 1998a). Bad-faith Deviators are those that have been the focus of researchers examining DDR. For instance, these could include individuals who experience emotional dissonance because they do not believe faking emotions should be a mandated part of their role (Rafaeli & Sutton, 1987). Role theory scholars would suggest that such individuals experience a form of role conflict in which the individuals’ displayed emotion is in conflict with the displays expected by the organization (Abraham, 1998b; Kahn et al., 1964). Bad faith Deviators could also deviate from PDRs in retaliation to mistreatment from clients or coworkers, 42 or experienced injustice at work (Barger, 2009; Dahling, 2017; Tschan et al., 2005). While this may seem acceptable from the perspective of the individual employee, it would still be considered a “bad-faith” behavior from the perspective of the organization who expects a certain level of civility and compliance with emotional display expectations. As mentioned earlier, this subpopulation of employees have been studied by researchers interested in DDR and their act of adopting CDRs in lieu of PDRs is typically viewed as a counterproductive workplace behavior as deviating from strong PDRs typically has a slew of negative performance outcomes for both the individual and the organization (Bougie et al., 2003; Tschan et al., 2005; Wang et al., 2011). A real-world example of this is a customer service manager displaying anger to a rude customer instead of showing calmness or remorse in response. In such cases, the bad-faith Deviator is likely to experience significant backlash from the organization because of potential loss of business (the customer might never return after the rude altercation with the employee) and violation of organizational display rule expectations (Berry et al., 2007; Coté, 2005; Dahling, 2017; Rotundo & Sackett, 2002). The second type of Deviators are those who also deviate from the strong display rules prescribed by their organization by adopting their own CDRs but do so to achieve organizational and individual performance objectives. Specifically, as stated in the previous section on problematic assumptions in the emotional labor literature, in the cases where PDRs do not align with or help achieve higher order organizational goals it is in the interest of both the individual employee and the organization that CDRs be adopted in lieu of the misaligned PDR. An example of a good-faith Deviator would be the previously mentioned server in a restaurant who decides to display frustration at the kitchen staff for the mistake with an order, in order to empathize with and share in the customer’s anger and misfortune, in the hopes of appeasing the disgruntled 43 customer, retaining their future business (organizational goal of customer retention), and getting a good tip (individual goal). While this action may not be appreciated by the betrayed kitchen staff, from the perspective of goal attainment this would be considered (albeit an extreme case of) a good-faith deviation by both the individual and the organization. Therefore, the primary distinction between good- and bad-faith Deviators is the intention with which they decide to adopt a CDR. Specifically, bad-faith actors deviate from PDRs for self-focused reasons while good-faith Deviators do so for the purpose of achieving work goals. It must be noted that even though good-faith Deviators adopt CDRs with largely prosocial motivations, doing so when faced with strong PDRs is a high-risk decision because if they fail to achieve their performance objectives, like bad-faith Deviators, they could face backlash from the organization. This backlash could manifest in terms of poor customer feedback and angry reactions (e.g., Bougie et al., 2003) or lower performance ratings (e.g., Glomb & Hulin, 1997). More importantly, good- faith Deviators form a subpopulation of employees that emotional labor scholars have ignored, focusing instead on bad-faith Deviators (and Rule-Followers; more on them later). In summary, Deviators are highly motivated to exert some agency and create their own CDRs even when faced with the strong PDRs. They can either be motivated by purely self- focused reasons such as retaliation against mistreatment or prosocial reasons such as achieving work goals. In either case, they are likely to be proactive risk takers who believe in their abilities to choose and display the most appropriate emotional displays to achieve their goals. They (especially Deviators acting in bad-faith) are also more likely than other actor profiles to experience some form of backlash from the organization for their deviation as most organizations with strong PDRs are likely to view such deviations as counterproductive and 44 harmful to the organization. Put simply, Deviators have a high risk-high gain mentality towards using CDRs to achieve organizational and personal goals. Proactives. Proactives are characterized by a high propensity to adopt CDRs but unlike Deviators, they work in an environment that has relatively weak organizationally PDRs. Work environments with weakly held PDRs typically constitute roles that, understandably, are not customer facing as such roles usually have stricter emotional display requirements. However, that does not necessarily mean that such roles, where employees interact with other coworkers, supervisors and subordinates as opposed to customers, do not have PDRs. The only difference is that these PDRs are not explicitly laid out like they would be for customer interactions and likely implicitly require employees show socially accepted courtesy and civility to their coworkers (Ekman & Friesen, 1971; Matsumoto et al., 2005). Going back to the example of a customer service manager who likely has strong PDRs when interacting with customers, will have weaker PDRs when interacting with her team. In such a case, as a Proactive, she could meet the minimal display requirements for her interactions with her team, or she could proactively decide to show high levels of enthusiasm or disappointment if she believes it will help motivate them. Having the freedom to make this decision and then acting upon it is one of the key differences that sets Proactives apart from the other proposed actor profiles. In such a situation, wherein PDRs exist but are weakly held or enforced, individuals are likely to have more latitude to adopt CDRs that may deviate from expected display norms. This latitude usually manifests in the form of higher job autonomy wherein the individual employee has the freedom and discretion to decide on how to behave while performing tasks (Abraham, 1998a; Hackman & Oldham, 1975; Morris & Feldman, 1996). In autonomous work environments, individuals can decide to deviate from the weakly held PDRs with greater ease 45 than environments with stronger PDRs. Therefore, Proactives are likely able to adopt CDRs with greater ease, and with lower likelihood of backlash from the organization than Deviators. Specifically, this subpopulation of employees is characterized by their proactive, voluntary adoption of CDRs which could deviate or overrule the emotional display requirements prescribed by their organization. For example, a supervisor can decide to go above and beyond the typically expected emotional displays when interacting with subordinates by showing enthusiasm regarding their interests outside of work. Or, on the flip side, a supervisor may decide to display anger (an emotion organizations implicitly expect individuals to suppress in their workplace interactions; Diefendorff & Greguras, 2009) to show their disappointment in a subordinate’s performance in the hopes of motivating them to do better in the future. Indeed, research on workplace violence and aggression has shown that individuals tend to be more comfortable breaking from emotional display norms by displaying anger and aggression with coworkers than customers, especially if it helps them achieve an instrumental goal such as inducing motivation in others (Anderson & Bushman, 2002; Glomb, 2002; Leblanc & Barling, 2005). In both the above examples, the Proactive can decide to deviate from (show anger) or supersede (show enthusiasm) the weakly held PDRs but decide to do so with the intention to achieve an organizational goal. Unlike Deviators, Proactives are unlikely to face backlash from their organizations for their adoption of CDRs because their roles do not value conforming to the relatively weaker PDRs to the same extent as with Deviators. Research on the consequences of proactive behavior suggests that supervisors and coworkers tend to reinforce such behavior with rewards (behavior they deem to be beneficial for the organization) (Van Scotter et al., 2000) or punishment (for behavior that is detrimental to the organization) (Hollinger & Clark, 1982, 1983). Indeed, 46 Proactives could also receive a premium (in the form of awards, higher supervisor ratings, promotions) for going above and beyond the required display rule expectations in their attempt to achieve organizational objectives (Seibert et al., 1999; Seibert et al., 2001; Thompson, 2005; Van Scotter et al., 2000). However, under certain circumstances Proactives could also experience backlash for their adoption of CDRs (in the form of retaliation from coworkers, poor supervisor ratings) (Grant & Ashford, 2008; Greenberg, 1990, 2002; Hollinger & Clark, 1983; Holtfreter, 2005; Ivancevich et al., 2003). For instance, in the example above where a supervisor decides to display anger or aggression to motivate an employee, research has shown that displaying negative emotions to colleagues can lead to lower performance ratings (Glomb & Hulin, 1997; Lewis, 2000). As an aside, it is possible that some Proactives deviate from PDRs in bad-faith (in retaliation to mistreatment for instance) and provoke retaliation of some sort from coworkers, with the potential to start an incivility spiral (Andersson & Pearson, 1999; Penney & Spector, 2005). However, that backlash from the organization would be in response to general counterproductive behavior on the part of the Proactive, and not because of their deviation from display rules specifically, given that the organization values emotional display rules in a relatively limited capacity. In summary, Proactives are highly motivated to exert their agency and adopt CDRs much like Deviators. However, unlike Deviators, they are not “swimming upstream” as deviating from weakly held PDRs is likely to be more acceptable by such organizations and less likely to hinder progress on key organizational objectives. Therefore, they are also less likely as proactive or self-assured as Deviators and less likely to face punishment for deviating from expected display rules, making their deviation less risky, and possibly more likely to be rewarded. Proactives are 47 another subpopulation of employees that have been excluded from the emotional labor literature. This is likely due to a focus on stronger PDRs contexts such as service roles, and not accounting for certain prosocial behaviors as also having a affective component that relies on adopting CDRs. Including Proactives into the larger conversation on emotional labor will further help clarify critical assumptions in the literature and provide a nuanced understanding of emotional labor’s effects on important outcomes. Rule-Followers. Rule-Followers are characterized by a low tendency to adopt CDRs and high organizationally PDRs. Rule-Followers are the primary subgroup of individuals that emotional labor scholars have focused on. These are the employees who are in roles that have strong PDRs, which they attempt to follow without relying on creating their own CDRs. Specifically, Rule- Followers comprise employees who attempt to meet organizationally expected emotional display rules even if the PDRs differ from their felt emotions (i.e., emotional dissonance), do not align with organizational or personal goals, or if the employee believes another CDR is likely more appropriate for a given situation. Typical examples of Rule-Followers can be found across emotional labor studies wherein employees believe in the “service with a smile” philosophy and do not deviate from that expectation (Grandey, 2003; Pugh, 2001; Totterdell & Holman, 2003; Wharton, 1996). Rule- Followers are not limited to only positive display rule contexts (as is true for all four proposed actor profiles) and could include negative display rule contexts as well. For instance, these could be flight attendants (Hochschild, 1979) who display positive emotions to customers and suppress negative emotions or bill collectors (Sutton, 1991) who display urgency or anger while suppressing positive emotions. 48 In summary, Rule-Followers are those employees who face strong emotional display expectations from their organizations and managers, and try their best to meet those expectations even if doing so harms their wellbeing or is contrary to their belief that such displays will facilitate effective goal attainment. Therefore, they are also likely to be relatively less proactive and likely have weaker beliefs in their abilities to take control of their environments and prefer to passively adapt to daily work-related exigencies. Finally, I propose that much of the inconsistent findings and problematic assumptions that the emotional labor literature has made is due to their narrow focus on Rule-Followers (and bad-faith Deviators). Passives. Passives are characterized by a low propensity to adopt CDRs and weak organizationally PDRs. These individuals are typically in work roles that do not have strong emotional display expectations but decide to not proactively adopt any CDRs even though they have the freedom to do so. They are generally not highly motivated to go above and beyond the basic emotional display requirements of their job. They instead prefer to follow the weakly PDRs wherever required, or simply displaying their felt emotions when PDRs are very weak or non-existent. Most organizations have implicit emotional display requirements based on societal etiquette which usually include showing positive emotions to remain civil (Diefendorff & Greguras, 2009) which form the baseline for workplace interactions. Passives will tend to follow these implicit or weakly held emotional display norms but go no further even if adopting a more appropriate CDR would help them better achieve a work goal. For instance, a senior faculty member does not have strong emotional display requirements when dealing with graduate students beyond the basic societal behavioral etiquette to maintain civil workplace relationships. They have the freedom to show extreme negative (disappointment or even anger at tardy or poor-quality work) or positive (enthusiasm or joy at 49 well executed work or an ingenious idea) emotions to motivate their graduate students depending on the traits and needs of that student. A faculty member who is a Passive will decide to not proactively go above and beyond the basic integrative emotional displays even if they believe doing so will help their graduate student work harder or push them to achieve greater success. This would entail them meeting the minimal societal etiquette expectations their department has of them, but not going above and beyond those minimal expectations by using their emotional displays as a tool to achieve work goals. This could be for a variety of reasons ranging from poorer beliefs of self-efficacy and disengagement with certain aspects of their work, to lower work centrality at that stage of their career (importance that work has in one’s life; Paullay et al., 1994). Therefore, the primary characteristic of Passives is that they are not motivated to proactively use CDRs even when doing so could be beneficial to them or their organization (via helping them achieve a personal or organizational goal) and having the freedom (and low risk) to do so. Having described the four latent actor profiles, I propose that there will exist four qualitatively and quantitatively distinct profiles based on tendencies to adopt CDRs and strength of PDRs. Thus, one of the aims of this dissertation is to examine the potential existence of the four profiles described above (Deviators, Proactives, Rule-Followers & Passives), that emerge from jointly considering CDR adoption and PDR strength. Although the proposed actor profiles described above are hypothetical at this point (as mentioned, LPA is inherently an inductive method of analysis, wherein the emergent profiles can only be theoretically proposed a priori), they emerge as a result of the interaction between a tendency to adopt CDRs and PDR strength which have been traditionally tested with a variable- 50 centered approach. In the next section, I develop a model (Figure 2) whereby I examine the interactive effects of CDR adoption tendencies and PDR strength on key well-being and performance outcomes via both intrapersonal and interpersonal mediating mechanisms. Before moving on to the section on hypotheses development, it is important to briefly discuss the role played by emotion regulation strategies when discussing the impact of the different sources of emotional display rules. Role of Emotional Regulation Strategies So far, no mention has been made of the method used to achieve the desired emotional displays, whether prescribed or contextual. As has been referenced in previous sections, the emotional labor literature has distinguished three primary ways that individuals can achieve these emotional displays. Surface acting, in which individuals fake the emotion they need to display, deep acting, in which individual try to internally create the emotions they need to display, and the natural expression of genuine felt emotions (Grandey, 2000; Hochschild, 1983; Scott et al., 2020). While it is not the purpose of this dissertation to examine these three different means of achieving emotional displays, this dissertation contends that all three methods are very likely to be relevant to the adoption of CDRs by organizational members and all four proposed actor profiles. Specifically, I propose that employees (no matter their tendency to adopt CDRs) can achieve their prescribed or contextual display rules via any of the three emotion regulation methods. For example, a Deviator adopting a CDR of showing frustration to a customer (as was the case of the example of the server who threw her kitchen staff under the bus for the wrong order) could do so by faking the frustration (surface acting), really trying to feel the frustration they are attempting to display (deep acting), or by naturally showing the frustration they are 51 genuinely feeling (natural display). The same could be true for Proactives, Rule-Followers or Passives who all likely vary in their tendencies to adopt CDRs and the PDR strength they encounter at work. The notion that each actor profile has the flexibility to use any of the emotion regulation strategies is further supported by the recent theoretical work done by Scott et al. (2020). They reconceptualize the emotional labor process as a journey with an origin (felt emotion), destination (emotional display), and method of travel (emotion regulation strategy). They propose that individuals can use any emotion regulation strategy for a particular emotion labor journey, which is also what this dissertation claims with respect to how each actor profile achieves their prescribed or contextual emotional displays. Put simply, the traveler can choose any mode of travel irrespective which destination (prescribed or contextual) is being traveled to in an emotion regulation journey. However, it might also be the case that an employee may have a proclivity to use one regulation strategy more than another. For example, owing to the high level of autonomy afforded to Proactives by their environment and their tendency to utilize that autonomy to consciously adopt CDRs of their own making, they are likely to rely more heavily on deep acting and natural expressions than surface acting. As has been mentioned in the previous section, Proactives are motivated to go above and beyond the expectations their organization has of them to achieve their goals. Further, research has shown that individuals tend to rely on higher emotional intensity when consciously attempting to display an emotion (Frijda et al., 1992). Emotional intensity refers to the strength or magnitude of the displayed emotion (Morris & Feldman, 1996). Prior work examining emotional intensity in service contexts has suggested that the intensity of the displayed emotion is the primary driver in convincing or changing the minds 52 of customers (Frijda et al., 1992). Given that emotional intensity is hard to fake (Frijda et al., 1992), it is also likely that individuals are likely to rely more on deep acting or natural displays to display higher levels of emotional intensity (Morris & Feldman, 1996). Similarly, it is likely that the other actor profiles have a proclivity to use one regulation strategy over another, however for the purposes of this dissertation I assume that all four actor profiles can rely on any emotion regulation strategy to achieve their desired emotional displays. Further, while there are no formal hypotheses regarding the role of emotion regulation strategies, I acknowledge that it is important to measure them and control for them, which I explain in more detail in the methods section. 53 THEORY DEVELOPMENT Theoretical Background Introduction to theory of emotional labor. The groundwork for a unified theoretical framework for emotional labor was laid out by the seminal works of Hochschild Arlie (1983), Ashforth and Humphrey (1993) and Morris and Feldman (1997), which all proposed slightly differing definitions for, and underlying mechanisms of, the emotion labor process. Building off of this early work on emotional labor, Grandey (2000) proposed a reorganized and integrated theoretical framework for emotional labor at work. Specifically, the “theory of emotional labor” lays out the situational antecedents, process mechanisms, and individual and organizational outcomes of emotional labor. Emotional labor scholars have made extensions to the initial theoretical framework proposed by Grandey (2000) by defining emotional labor across multiple levels of analyses and expanding the targets, contexts and consequences of emotional labor in the workplace (Grandey & Melloy, 2017; Hülsheger & Schewe, 2011). However, the extant theoretical work has yet to incorporate the source of emotional display rules into the broader theory of emotional labor, instead focusing on the emotion regulation strategies of deep and surface acting as primary drivers of the effects of emotion regulation. This dissertation aims to extend this theoretical framework by delineating the ways in which different sources of emotional display rules influence these mechanisms and outcomes, above and beyond the emotion regulation strategies themselves. The following section examines the differential effects of the interaction between tendencies to adopt CDRs and PDR strength on three typical outcomes specified by extant emotional labor theory (Grandey, 2000; Grandey & Melloy, 2017; Hülsheger & Schewe, 2011). Specifically, I examine three categories of outcomes: personal well-being (emotional 54 exhaustion), job-related well-being (job satisfaction), and performance (task performance). I rely on two related theoretical frameworks i.e., self-determination theory’s perspective on self- regulation (Deci & Ryan, 1980, 1985; Ryan & Deci, 2008) and the job demands and resources model (Demerouti et al., 2001), to highlight the role played by the four key mechanisms (i.e., felt inauthenticity, ego depletion, autonomy and quality of social interactions) identified by previous research in explaining the interactive effects of CDR adoption and PDR strength on my outcomes of interest. I discuss them briefly below before moving onto the formal development of hypotheses. Job Demands-Resources Theory of Burnout (JD-R). The JD-R model suggests that workplaces include two categories of job characteristics: job demands and job resources (Demerouti et al., 2001). Job demands refer to “those physical, social or organizational aspects of the job that require sustained physical and/or psychological (i.e., cognitive or emotional) effort on the part of the employee and are therefore associated with certain physiological and/or psychological costs” (Bakker et al., 2003, p. 395). Examples of job demands include (but are not limited to) time pressure, physical work environments and emotional demands (such as those imposed by PDRs). Job resources on the other hand refer to “those physical, psychological, social, or organizational aspects of the job that may do any of the following: (a) be functional in achieving work goals; (b) reduce job demands and the associated physiological and psychological costs; (c) stimulate personal growth, learning and development” (Bakker et al., 2003, p. 395). Specific examples of job resources are social support, feelings of achievement, authenticity, job control, and autonomy. The JD-R model suggests that job demands tend to act as stressors at work and can harm employee wellbeing by experiencing negative health outcomes and emotional exhaustion, 55 whereas job resources can enhance employee wellbeing and reduce emotional exhaustion (Bakker et al., 2005; Schaufeli & Bakker, 2004). Further, job demands can also diminish individual resources (Hobfoll, 1989). Traditionally job demands and job resources have been theorized to relate to burnout (and emotional exhaustion specifically) through two different processes (Schaufeli & Bakker, 2004). Specifically, job demands and job resources effect emotional exhaustion via energetic and motivational processes (Schaufeli & Bakker, 2004; Van den Broeck et al., 2008). The energetic processes theorized by JD-R scholars suggest that job demands take a toll on an individual’s energy and limited resource pool, which in turn increases emotional exhaustion (Schaufeli & Bakker, 2004). Further, JD-R researchers suggest that motivational processes also underlie the relationship between job resources and emotional exhaustion. Specifically, they do so by helping employees stay engaged in their work and enhancing their resource pool indirectly through facilitating goal achievement and satisfying basic psychological needs (Schaufeli & Bakker, 2004; Van den Broeck et al., 2008). The basic premise of the JD-R model suggests that job demands and job resources are constantly depleting and replenishing an individual’s resources and energy (causing deficits and surpluses of resources), and strain and emotional exhaustion occurs when these resources become depleted faster than they can be replenished by the individual. Indeed, research suggests that managing to replenish resources faster than they can be depleted leads to improved individual wellbeing and reduced emotional exhaustion (Demerouti et al., 2001; Holman et al., 2008). Self-Determination Theory’s View on Self-Regulation. A closely related self-regulation theoretical framework proposed by Ryan and Deci (2008) draws on self-determination theory (SDT; Deci & Ryan, 2000; Ryan & Deci, 2000) to outline factors that facilitate maintenance, enhancement or depletion of energy and resources from individuals. The central premise of SDT 56 is that individuals range on a continuum from autonomous motivation to controlled motivation (Deci & Ryan, 2008). Autonomous motivation “comprises both intrinsic motivation and the types of extrinsic motivation in which people have identified with an activity’s value and ideally will have integrated it into their sense of self…. when people are autonomously motivated, they experience volition, or a self-endorsement of their actions” (Deci & Ryan, 2008, p. 182). Controlled motivation, on the other hand, consists of “external regulation, in which one’s behavior is a function of external contingencies of reward or punishment” (Deci & Ryan, 2008, p. 182). Further, SDT suggests that while both autonomous and controlled motivation direct behavior of individuals, they differ in their effects on individual resource depletion based on their ability to satisfy basic psychological needs as they pursue valued goals and outcomes (Deci & Ryan, 2000). Specifically, SDT posits that the basic psychological needs of autonomy, competence and relatedness are “nutrients that are essential for growth, integrity, and well- being” (Ryan & Deci, 2017, p. 10) and are fundamental to autonomously motivated behavior. The first basic psychological need specified by SDT is autonomy, which is the need “to self- regulate one’s experiences and actions” (Friedman, 2003; Ryan, 1993; Ryan & Deci, 2017). And to have one’s actions be consistent with one’s authentic self and values. The second basic need specified by SDT is competence, which is the need to feel effective and achieve mastery (Ryan & Deci, 2017). The final basic need specified by SDT is relatedness, which is the need to feel connected to others (Ryan, 1995; Ryan & Deci, 2017). The primary tenet of the SDT perspective on self-regulation (also referred to as the SDT model of vitality; Ryan & Deci, 2008) states that “whereas efforts to control oneself do indeed drain psychological energy and vitality, autonomous self-regulation does not” (Ryan & Deci, 2008, p. 702). Put simply, behaviors that stem from autonomous self-regulation aim to satisfy 57 SDT’s basic psychological needs which in turn provide nourishment to the self and enhancement of personal resources. More specifically, actions that satisfy needs of autonomy, competence or relatedness should enhance personal resources and energy while actions that thwart need satisfaction should deplete personal resources and energy (Nix et al., 1999; Ryan & Deci, 2008). Put another way, “when behavioral regulation is autonomous, it is both harmonious and efficient, requires the least inhibition, and entails the least conflict… in contrast, controlled motivation is often associated with pressure and tension and requires greater resources” (Ryan & Deci, 2008, p. 708). Taken together, applying the JD-R and SDT theoretical frameworks in tandem to the context of emotion regulation suggests that there are likely to be varying levels of emotional demands (in terms of PDR strength) and emotional resources (in terms of autonomous self- regulation by adopting CDRs) depending on the interaction of different sources of emotional display rules. Next, I draw on this theoretical lens to extend the theory of emotional labor and develop hypotheses to better incorporate display rule sources into the emotion regulation literature. 58 HYPOTHESES DEVELOPMENT In the following section I rely on the role played by four important theoretical mechanisms (i.e., felt inauthenticity, ego depletion, autonomy, and quality of social interactions) that mediate the interactive effects of CDR adoption and PDR strength to examine effects of my focal outcomes. Felt Inauthenticity Felt inauthenticity is one of the more commonly examined outcomes of emotional labor and plays an important role in explaining further downstream effects of the emotional regulation process (Erickson & Ritter, 2001; Gardner et al., 2009; Kammeyer‐Mueller et al., 2013; Mesmer- Magnus et al., 2012). Felt inauthenticity is defined as an individual’s self-perception of their authenticity when engaging in emotional regulation (Brotheridge & Lee, 2002; Erickson & Ritter, 2001). Authenticity refers to when an individual acts in accordance with their true self including their beliefs, values and identities (Harter, 2002; Metin et al., 2016). Further, authentic behavior reflects actions that are freely chosen by an individual with a sense of agency (Kernis & Goldman, 2006). Research has suggested that experiencing inauthenticity by disconnecting from one’s “true self” can increase strain and harm well-being (Erickson & Wharton, 1997; Sheldon et al., 1997; Wood et al., 2008). Since the advent of emotional labor research, felt inauthenticity has played a central role in explaining the detrimental effects of regulating emotions (Hochschild, 1983). Emotions form natural proxies for individuals to judge how close they are to their authentic self and therefore the emotions that are expressed when interacting with others are crucial to how individuals view themselves (Diefendorff et al., 2005). Accordingly, when individuals regulate their emotions they are constantly evaluating how consistent their behavior and emotional displays are aligned 59 with their inner values (or authentic self) (Carver & Scheier, 2001; English & John, 2013). This evaluation forms the basis for individuals that experience emotional dissonance while regulating their emotions. Put simply, the extant emotion labor literature assumes that individuals have a certain “meta-cognitive awareness of the discrepancy between felt and expressed emotions and are distressed about the discrepancy” (Pugh et al., 2011, p. 2). Recall from the section on emotional dissonance, the experience of emotional dissonance indicates to the individual that their behavior is inconsistent with their self-concept, causing felt inauthenticity (Festinger, 1957; John & Gross, 2004; Pugh et al., 2011). For the purposes of this dissertation, there is an important concept relevant to understanding the role played by felt inauthenticity when accounting for the source of emotional display rules, i.e., agency or control over decision making. Having agency and control is an essential antecedent to feeling authentic. This assertion is supported by emotional labor research that has focused on the effects of individual emotion regulation strategies such as surface and deep acting on felt inauthenticity. Further, the emotional dissonance experienced by individuals attempting to regulate their emotions, that increases feelings of inauthenticity, can likely be alleviated by allowing them the freedom to choose their displays (Abraham, 2000). When discussing the role played by emotional display rule sources, this idea of agency and control is especially relevant to the concept of CDRs. Drawing on the SDT perspective on self-regulation, when individuals rely on autonomous self-regulation (as is the case when individuals adopt CDRs), they are acting in a way that is consistent with their authentic self and values (Ryan & Deci, 2008). As described earlier, individuals with a high proclivity for adopting CDRs exert their agency and decide for themselves the appropriate emotional displays depending on the situation at hand. This type of autonomous self-regulation done via exertion of agency and 60 claiming control is likely to foment strong feelings of authenticity for such individuals (Erickson & Ritter, 2001). Specifically, regardless of whether emotion regulation strategies such as surface acting or deep acting – both of which are more “inauthentic” than displaying felt emotions - are used, the agency and volition experienced via autonomous self-regulation should make people feel more authentic (Erickson & Ritter, 2001; Ryan & Deci, 2008). Put differently, all else being equal (for two people who surface act for instance), the individual who chooses their emotional displays, as opposed to having it chosen for them, should feel more authentic. On the other hand, individuals characterized by a low propensity to create and adopt CDRs are not motivated to autonomously self-regulate and exert their agency to gain control of their emotional displays. Relatedly, the fundamental tenets of SDT suggest that when individuals think, feel and act in ways that are in line with their true selves and fulfill vital needs, they experience higher authenticity (Metin et al., 2016; Ryan et al., 2005). As I touch on in more detail in later sections, adoption of CDRs is likely to help fulfill SDT’s basic needs of autonomy, competence and belonging, which in turn is likely to increase their felt authenticity. In sum, I propose that there will be a negative relationship between the tendency to adopt CDRs and felt inauthenticity. As mentioned earlier, the primary purpose of this dissertation is to examine the situation- person interaction between the tendency to adopt CDRs and strength of PDRs on critical mechanisms underlying the emotional labor process such as felt inauthenticity. PDR strength is likely to vary across organizations ranging from weakly held PDRs where the organization does not give any direction to employees as to what emotional displays are deemed appropriate to strong PDRs wherein employees are told explicitly what the organization’s expectations are (Christoforou & Ashforth, 2015; VanMaanen & Kunda, 1989). In workplaces with strong PDRs, there is likely to be less room for individuals to adopt CDRs given the stronger and more 61 stringent emotional display expectations they are working with. As prior work on strong PDR contexts (such as service or customer facing contexts) has shown, organizations tend to have clear and specific expectations of emotional displays from employees in such contexts (e.g., Christoforou & Ashforth, 2015). On the other hand, weaker PDR contexts are likely to allow employees far more expressive latitude in deciding what emotions they can display (Christoforou & Ashforth, 2015; Diefendorff & Gosserand, 2003), allowing more room for individuals to adopt CDRs. Therefore, it is likely that the amount of felt inauthenticity experienced by employees adopting CDRs is contingent on the strength of PDRs in their work environment. Put another way, work environments with strong PDRs are likely to curtail satisfaction of autonomy and competence needs facilitated by CDR adoption. Indeed, viewing the strength of prevailing PDRs as a moderator of the relationship between CDR adoption and felt inauthenticity (as well as the other three mediators proposed in this dissertation) is in line with the situational strength hypothesis (Mischel, 1977), which proposes that person-based variables (such as traits, motives, affect etc.) have attenuated effects on behavior under situational constraints. Using language from the situational strength hypothesis, weak PDR strength represents a weak situation wherein individuals have more freedom to adopt CDRs, while strong PDRs represent a strong situation wherein individuals have less freedom to adopt CDRs. In sum, I propose that the negative relationship between CDR adoption and felt inauthenticity will be moderated by PDR strength, such that the relationship is stronger at lower levels of PDR strength and weaker at higher levels of PDR Strength. Hypothesis 1a: The negative relationship between tendency to adopt CDRs and felt inauthenticity will be moderated by PDR strength such that the relationship is stronger (weaker) at lower (higher) levels of PDR strength. 62 Felt inauthenticity & key outcomes. Next, I examine the interactive effects of CDR adoption and PDR strength on focal emotional labor outcomes of emotional exhaustion, job satisfaction and task performance, via felt inauthenticity. Emotional exhaustion is an indicator of the individual stress component of burnout (Maslach & Jackson, 1981) and can be defined as the “feelings of being overextended and depleted of one’s emotional and physical resources” (Maslach et al., 2001, p. 399). Emotional exhaustion is the most commonly examined outcome of emotional labor (Bono & Vey, 2005; Kammeyer‐Mueller et al., 2013; Mesmer-Magnus et al., 2012) and is typically associated with the energy exertion and mental resource depletion aspects of the emotional regulation process (Brotheridge & Lee, 2002). The relationship between feelings of authenticity and well-being has long been established, with research suggesting that authentic expression of the core self, increases a general sense of well-being (Deci & Ryan, 2000), reduces anxiety and distress (Sheldon et al., 1997). Adoption of CDRs, and the accompanying claiming of agency over one’s emotional displays, is an important means by which individuals express their core self. As per the JD-R model, authenticity experienced due to taking control of one’s emotional displays is likely to be an important job resource available to individuals to help counter exhaustion and burnout when faced with emotional demands at work (Bakker & Demerouti, 2017; Metin et al., 2016). Further, the additional emotional demands placed on an individual owing to the stronger PDRs in their work environment is likely to increase the amount of felt inauthenticity (Metin et al., 2016), and in turn further increase their experienced emotional exhaustion. Therefore, I propose that adoption of CDRs will have a negative indirect relationship with emotional exhaustion, via a reduction in felt inauthenticity. Further, this negative relationship is contingent on the strength of the PDRs expected of 63 employees, such that the relationship is stronger at lower levels of PDR strength and weaker at higher levels of PDR strength. Hypothesis 1b: The negative indirect effect of the tendency to adopt CDRs on emotional exhaustion via felt inauthenticity is stronger (weaker) at lower (higher) levels of PDR strength. Along with personal wellbeing indices such as emotional exhaustion, job satisfaction is the most frequently studied job-related well-being outcome of emotional labor (Bono & Vey, 2005; Brotheridge & Lee, 2002; Grandey, 2000; Kammeyer‐Mueller et al., 2013). Job satisfaction refers to an “evaluation or evaluative judgment made with regard to an attitudinal object” (Weiss, 2002, p. 175), in this case being one’s job. As previously discussed, there are some inconsistencies in the findings of research examining the relationship between emotional labor and job satisfaction (Bono & Vey, 2005; Grandey, 2000; Hülsheger & Schewe, 2011). Specifically, a large body of work contends that the relationship between emotional labor and job satisfaction is contingent on the type of regulation strategy used, with response focused strategies such as surface acting decreasing job satisfaction and antecedent-focused strategies like deep acting improving job satisfaction (Cote & Morgan, 2002; Grandey, 2000; Rutner et al., 2008). However, another line of research suggests that emotional labor can be beneficial for job satisfaction (Ashforth & Humphrey, 1993; Morris & Feldman, 1997) by improving their relationship quality with their interaction partners (Coté, 2005; Tolich, 1993), eliciting a sense of authenticity (Brotheridge & Lee, 2002) and sense of accomplishment (Brotheridge & Grandey, 2002). Additionally, recent theoretical work by Scott et al. (2020) suggests that the relationship between emotional regulation and job satisfaction may not be dependent on the chosen regulation strategy at all, further adding to equivocal nature of 64 the relationship between emotional labor and job satisfaction. I propose that one of the likely reasons for these inconsistencies is that prior research has failed to adequately account for differences in the sources of display rules adopted by individuals. One of the more important determinants of job satisfaction is felt inauthenticity. Indeed, prior research has suggested that individuals who stay in touch with and express their core selves are more satisfied with their jobs, with substantial support showing a positive relationship between authenticity and job satisfaction (Ménard & Brunet, 2011; Metin et al., 2016; Toor & Ofori, 2009; Van den Bosch & Taris, 2014). Additionally, as mentioned in the previous section, felt inauthenticity can be a sign of unfulfilled basic psychological needs on part of the individual, in turn harming the amount of job satisfaction they experience (Ménard & Brunet, 2011; Metin et al., 2016; Ryan et al., 2005). Therefore, I propose that adoption of CDRs will have a positive indirect relationship with job satisfaction, via a reduction in felt inauthenticity. Further, this negative relationship is contingent on the strength of the PDRs expected of employees, such that the relationship is stronger at lower levels of PDR strength and weaker at higher levels of PDR strength. The final category of outcomes outlined by the theory of emotional labor is performance, of which task performance is the most studied (Bono & Vey, 2005; Grandey & Gabriel, 2015; Hülsheger & Schewe, 2011). As has been mentioned, the findings regarding the effect of emotional labor on task performance is decidedly mixed (Grandey & Gabriel, 2015). For example, multiple meta-analyses have found weak negative, to no effects of emotional labor on task performance (Hülsheger & Schewe, 2011; Kammeyer‐Mueller et al., 2013; Mesmer- Magnus et al., 2012). Researchers have suggested that these equivocal findings could be due to the potential “performance trade-offs from engaging in emotional labor” (Grandey & Gabriel, 65 2015, p. 339). I propose that the mixed findings associated with the effects of emotional labor on performance are due to the narrow focus of the extant literature on strong PDR contexts and individuals who have a low tendency to adopt CDRs. Once again drawing on the JD-R model and the SDT perspective on self-regulation, individuals experience trade-offs in terms of the emotional job demands placed on them and the resources available to them (Demerouti et al., 2001) owing to basic need satisfaction and adoption of CDRs. Specifically, experiencing high levels of authenticity (from adoption of CDRs) can add to the resource pool of individuals, helping to offset the resource loss caused by the emotional demands placed on them (Grandey & Gabriel, 2015; Morris & Feldman, 1997), in turn improving individual task performance. Further, individuals who feel more authentic are also likely to be more intrinsically motivated and likely to perform better at tasks (Ryan et al., 2005). In sum, I propose the following hypothesis. Hypothesis 1c: The negative indirect effect of the tendency to adopt CDRs on (i) job satisfaction and (ii) task performance via felt inauthenticity is stronger (weaker) at lower (higher) levels of PDR strength. Ego Depletion Emotional labor scholars have long suggested that regulating one’s emotions requires self-control and can deplete self-regulatory resources (Diefendorff & Gosserand, 2003; Grandey & Gabriel, 2015; Grandey & Melloy, 2017; Hülsheger & Schewe, 2011). The concept of ego depletion was first conceived of by Baumeister and colleagues as a key tenet of the strength model of self-control (Baumeister et al., 1998; Baumeister & Heatherton, 1996; Baumeister et al., 2007; Muraven & Baumeister, 2000; Muraven et al., 1998). They suggest that purposefully engaging in acts of self-control and other self-regulatory processes is effortful and draws from a 66 limited pool of mental resources, which when depleted can hinder further self-control until the depleted resources are replenished. Put simply, “Ego depletion renders the self temporarily less able and less willing to function normally or optimally” (Baumeister & Vohs, 2007, p. 116). Within the context of emotional labor processes, ego depletion is one of the most common mechanisms put forth by scholars to explain the relationship between regulating emotions, and well-being and performance outcomes (Deng et al., 2017; Goodwin et al., 2011; Grandey et al., 2012; Grandey & Melloy, 2017; Hülsheger & Schewe, 2011; Mckibben, 2010). However, the clear focus of extant research on the depleting effects of emotional labor have focused on the differential effects of the two main emotion regulation strategies of surface and deep acting, wherein surface acting is generally considered to be more depleting than deep acting (Grandey & Gabriel, 2015). This dissertation is the first to examine the effects of the source of emotional display rules on ego depletion, and the differential depletion effects on downstream outcomes of interest. The acts of self-control when an employee is engaging in emotional labor, whether it be faking an emotion, resisting the impulse to emote naturally, focusing one’s attention, or any persistence towards the goal of a specific emotional display is depleting (Goldberg & Grandey, 2007; Zyphur et al., 2007). This is largely due to the continuous investment of attentional and motivational resources that such emotion regulation requires. However, as per the SDT perspective on self-regulation, not all acts of regulation are equally depleting (Ryan & Deci, 2008). Specifically, when individuals autonomously self-regulate by adopting CDRs, they are claiming agency over their emotional displays and deciding for themselves what emotions are most appropriate to show and how best to regulate their displays to achieve desired outcomes. While all acts of emotion regulation are a form of self-control, the difference between acts of 67 self-control done by choice and those done as a work-related responsibility is likely to be crucial to understanding the role played by CDRs in the emotion regulation process. Specifically, exerting agency over their emotional displays allows individuals who have a higher tendency to adopt CDRs to mentally reconstrue unwanted emotions before they fully activate via processes such as reappraisal (Gross, 1998). Further, being able to decide their own emotional displays depending on the context and situation they are facing, individuals who adopt CDRs have the opportunity to alter their experience of regulating their emotions (such as displaying a specific emotion) expend lesser effort (Deng et al., 2017; Fujita, 2011). Further, individuals who adopt CDRs are unlikely to need as many attentional resources (and therefore experience lower ego depletion) as compared to those that simply conform to the prevailing PDRs in their work environment. Indeed, prior research has suggested that when individuals have the autonomy to decide what emotion to display, it is less effortful (Ekman & Friesen, 1971; Matsumoto et al., 2005). Therefore, I propose that the tendency to adopt CDRs will be negatively related to ego depletion. The amount of depletion experienced by individuals adopting CDRs will however also depend on the strength of PDRs in their work environments. In strong PDR work contexts, the benefits of adoption of CDRs are likely to be dampened owing to the higher and more specific emotional display expectations the organization has of its employees. Indeed, expression of emotions under conditions of high PDR strength is expected to be especially depleting (Carver & Scheier, 1981; Christoforou & Ashforth, 2015) as such strong display rules engage higher amounts of mental resources to achieve (Diefendorff & Gosserand, 2003). Further, even though individuals that adopt CDRs are choosing the emotions they want to display, the act of deviating from strong PDRs can have negative consequences in the form of backlash, as has been shown 68 by scholars of emotional deviance (e.g., Dahling, 2017). This fear of retaliation is likely to cause those with a high tendency to adopt CDRs to experience stress which in turn is likely to lead them to experience higher depletion (Baumeister et al., 1999). In sum, I propose that the negative relationship between the tendency to adopt CDRs and ego depletion will be moderated by PDR strength such that the relationship will be stronger at lower levels of PDR strength. Hypothesis 2a: The negative relationship between the tendency to adopt CDRs and ego depletion will be moderated by PDR strength such that the relationship is stronger (weaker) at lower (higher) levels of PDR strength. Ego depletion & key outcomes. Drawing once again on the JD-R model of burnout and the SDT perspective on self-regulation, I first examine the mediating effect of ego depletion on emotional exhaustion. As a reminder, an excess of job demands is likely more depleting (Muraven et al., 1998) and causes higher exhaustion, on the other hand higher resources reduce depletion and in turn emotional exhaustion. Indeed, the positive relationship between ego depletion and exhaustion is well established (e.g., Lam et al., 2010; Muraven & Baumeister, 2000; Trougakos et al., 2015). Further, there is also ample evidence suggesting that more effortful forms of emotional regulation (such as surface acting) can lead to depletion of resources and in turn emotional exhaustion (Beal et al., 2013; Beal et al., 2006; Trougakos et al., 2015). I propose that adopting CDRs is likely to be less effortful than trying to display emotions that were instead mandated by the organization because of the benefits (such as increased autonomy and authenticity) accrued to employees who choose their own emotional displays and the satisfaction of basic needs of autonomy and competence. This in turn makes it more likely that individuals with a higher tendency to adopt CDRs are also likely to experience lower levels of depletion and in turn lower exhaustion. This relationship is further likely to be contingent on the strength of 69 PDRs imposed on individuals, wherein stronger PDRs are likely to dampen the benefits of CDR adoption because of the likelihood of the more stressful emotion regulation that will likely be required. Indeed, prior work has shown that chronic emotional regulation and suppression of emotions in particular, irrespective of the regulation strategy, depletes an individual’s resources (Grandey, 2003; Grandey & Melloy, 2017; Gross, 1998) and is therefore likely to be a debilitating job demand (and relevant boundary condition) faced by those facing stronger PDRs. Therefore, I propose the following hypothesis. Hypothesis 2b: The negative indirect effect of the tendency to adopt CDRs on emotional exhaustion via ego depletion is stronger (weaker) at lower (higher) levels of PDR strength. As previously mentioned, adoption of CDRs allows individuals the opportunity to satisfy needs of autonomy – by claiming agency over their emotional displays, and competence – by volitionally deciding which emotional display is most likely to help them achieve performance goals. As per the SDT perspective on self-regulation, satisfaction of these basic needs accrues individuals benefits in terms of enhanced energy and other personal resources (Ryan & Deci, 2008), in turn reducing amount of ego depletion. Further, satisfaction of these basic needs at work has shown to improve performance evaluations, commitment, and work engagement (Baard et al., 2004; Deci et al., 2001; Gagné, 2003), which in turn improve job satisfaction. However, in contexts of strong PDRs, the opportunities to satisfy needs of autonomy and competence are limited by the more stringent emotional display expectations the organization has of employees, likely increasing the amount of experienced ego depletion and in turn reducing job satisfaction. On the other hand, weaker PDR contexts are likely to amplify the benefits of CDR adoption, reduce depletion of personal resources and increase job satisfaction. Therefore, I propose that ego depletion mediates the positive interactive effects of tendency to adopt CDRs 70 and PDR strength on job satisfaction, such that the indirect effect will be stronger (weaker) at lower (higher) levels of PDR strength. According to ego depletion theory, any acts of self-regulation such as the regulation of emotions can deplete personal resources (Muraven & Baumeister, 2000), which in turn can hurt subsequent efforts of self-regulation such as task performance. However, as previously mentioned, not all acts of self-regulation are equally depleting, with autonomous self-regulation potentially enhancing an individual’s personal resources instead (Ryan & Deci, 2008). Extending that logic to the context of autonomously controlling one’s emotional displays, when individuals adopt CDRs and claim agency over their emotional displays, they are self-regulating in an autonomous manner and are likely to experience lowered ego depletion. Therefore, I posit that when individuals have a higher tendency to adopt CDRs, they are likely to experience lower ego depletion and have adequate personal resources to dedicate to task performance. This relationship will further be contingent on the strength of PDRs imposed on individuals, with the benefits from CDR adoption being weaker (stronger) at higher (lower) levels of PDR strength. In sum, I propose the following hypothesis. Hypothesis 2c: The positive indirect effect of the tendency to adopt CDRs (i) job satisfaction and (ii) task performance via ego depletion is stronger (weaker) at lower (higher) levels of PDR strength. Autonomy Autonomy generally refers to the freedom, independence and agency in decision making afforded to an employee at work (Hackman & Oldham, 1975; Morgeson & Humphrey, 2006). As was referenced in the section on emotional dissonance, the idea of having agency or autonomy over one’s actions is an important one when considering the effects of emotional 71 labor. Specifically, when an individual engages in behaviors such as faking or suppressing emotions, that run counter to their own identity and self-perceptions, the emotional dissonance they experience can be especially stressful (Ashforth & Humphrey, 1993; Festinger, 1957). Autonomy is one of the most studied antecedents, boundary conditions and mediating mechanisms when examining the effects of emotional labor on individual well-being and performance (Gopalan et al., 2013; Grandey, 2000; Grandey & Melloy, 2017; Johnson & Spector, 2007; Morris & Feldman, 1997). Indeed, emotional labor scholars learned fairly early that the negative effects of emotional labor were contingent on the level of perceived and experienced autonomy (Wharton, 1993). Within the context of examining the impact of emotional display rule sources, perceived autonomy and claiming agency over what emotion is most appropriate to display in any given situation is of particular consequence. Indeed, inherent to the adoption of CDRs is the literal act of claiming autonomy over one’s emotional displays. Simply put, when individuals adopt CDRs, they are ensuring they experience higher levels of autonomy, albeit limited to the sphere of emotional displays under their control. Therefore, I posit that individuals with a higher tendency to adopt CDRs are also likely to experience higher levels of autonomy. However, in line with the situational strength hypothesis, the amount of autonomy individuals who adopts CDRs experience will likely be contingent on the strength of PDRs they face, with strong PDRs curtailing the amount of autonomy such individuals would ideally like to experience given their natural tendencies for taking control of their emotional displays. Therefore, I propose that the amount of autonomy experienced by individuals who adopt CDRs is likely contingent on PDR strength with stronger (weaker) PDRs curtailing (enhancing) autonomy. 72 Hypothesis 3a: The positive relationship between tendency to adopt CDRs and autonomy will be moderated by PDR strength such that the relationship is weaker (stronger) at higher (lower) levels of PDR strength. Autonomy & key outcomes. Multiple previous studies have found evidence for the importance of employees perceiving having the choice to display a certain emotion as their own, buffering the negative effects of emotional labor (Grandey, Fisk, & Steiner, 2005; Johnson & Spector, 2007). Indeed, these previous studies suggest that even the most harmful emotion regulation strategies (such as surface acting within traditional positive display rule contexts) have a larger negative impact on individual well-being and performance when employees feel like they have no choice and are being forced by their organizations to meet PDR (Gopalan et al., 2013; Grandey, Fisk, & Steiner, 2005; Grandey & Melloy, 2017; Johnson & Spector, 2007). Further, according to the JD-R model and SDT’s view of self-regulation, autonomy provides individuals with vital personal resources to counteract the effects of emotion regulation on emotional exhaustion (Demerouti et al., 2001; Gopalan et al., 2013; Moller et al., 2006; Ryan, 1993). Therefore, I propose that claiming autonomy over one’s emotional displays by adopting CDRs is also likely to provide significant personal resources to counteract emotional exhaustion. Hypothesis 3b: The negative indirect effect of the tendency to adopt CDRs on emotional exhaustion via autonomy is stronger (weaker) at lower (higher) levels of PDR strength. As previously mentioned, autonomy is one of the three basic psychological needs specified by SDT (Deci & Ryan, 2000) and the satisfaction of the need for autonomy is one of the primary antecedents of job satisfaction. There is a slew of prior research from varied fields and areas of study such as job design (e.g., Armstrong, 1977; Blauner, 1964; Hackman & Oldham, 1975), education (e.g., Federici, 2013; Kreis & Brockopp, 1986), sales and marketing 73 (e.g., DeCarlo & Agarwal, 1999), and management (e.g., Fryxell & Gordon, 1989; Lee et al., 1990; Saragih, 2015; Shalley et al., 2000; Weaver, 1978) suggesting a positive relationship between autonomy and job satisfaction. Therefore, the increased autonomy experienced by individuals with a higher tendency to adopt CDRs is likely to in turn lead to higher levels of job satisfaction. Further, this positive relationship is likely contingent upon the strength of PDRs, with stronger (weaker) PDRs diminishing (enhancing) the job satisfaction benefits accrued due to increased autonomy. The relationship between autonomy and performance has been studied extensively for over half a century, with many finding positive direct (e.g., Fried & Ferris, 1987; Goldberg & Grandey, 2007; Johari et al., 2018; Liden et al., 2000), mediated (e.g., Joo et al., 2010; Morgeson et al., 2005; Muecke & Iseke, 2019), and interactive effects (Barrick & Mount, 1993; Cho et al., 2021; Fuller Jr et al., 2010; Moller et al., 2006) of autonomy on performance. Drawing once again from both JD-R and SDT models of self-regulation, I posit that the resources made available to individuals in the form of increased autonomy (via a higher tendency to adopt CDRs) is likely to further improve task performance by giving such individuals access to a larger personal resource pool. However, this increase in resources is likely to be curtailed by higher emotional demands in terms of stronger PDRs which are likely to inhibit the amount of agency and autonomy individuals adopting CDRs can claim. In sum, I propose the following hypothesis. Hypothesis 3c: The positive indirect effect of the tendency to adopt CDRs (i) job satisfaction and (ii) task performance via autonomy is stronger (weaker) at lower (higher) levels of PDR strength. 74 Social interaction quality The vast majority of emotional labor research has focused on intrapersonal processes, while interpersonal effects are also likely important to understanding how emotional labor affects individual well-being and performance. Coté (2005) proposed the social interaction model of emotional labor which takes both interaction partners’ emotional displays and reactions into account. While primarily focused on the employee-customer dyad, Cotḗ’s (2005) theoretical model expands “the role of receivers beyond customers and adding a link between receivers' behavior and senders' strain, the social interaction model extends existing models of emotion regulation in the workplace stating that senders' emotion regulation impacts receivers' behavior” (Coté, 2005, p. 516), which in turn affects the senders’ well-being, satisfaction and performance. The foundation of the social interaction model is based on the idea that emotional displays by organizational members are indicators of their goals, motives, and attitudes (Coté, 2005; Sutton, 1991; Van Kleef et al., 2004). Put another way, the “senders’ displays of emotion provide powerful signals to receivers during interpersonal interactions” (Coté, 2005, p. 514). Both sender and receiver are gleaning information from the emotional displays of their interaction partner and find themselves in a feedback loop that has three distinct stages. First, the sender (the person starting the feedback loop) regulates their emotions to arrive at a particular emotional display. Second, the sender’s emotional displays act as affective events (Weiss & Cropanzano, 1996) that receivers perceive, evaluate and finally react to. Third, the receiver’s reaction affects the sender’s well-being and performance. In sum, according to the social interaction model, the receiver’s responses, and reactions play an important role in understanding how the sender’s emotion regulation impacts their well- being and performance. Specifically, high quality of social interactions during emotion 75 regulation episodes improves key well-being and performance outcomes (Coté, 2005; Hülsheger & Schewe, 2011). Further, as was mentioned in the section on SDT, one of the basic psychological needs is that of relatedness (Deci & Ryan, 1985), or the need to feel meaningfully socially connected with others. Having higher quality social interactions, therefore, is also a source of personal resources via relatedness need satisfaction. Since the publishing of Coté’s social interaction theory, there has been some attention given to interpersonal effects of emotional labor and emotional displays in general (e.g., Cheshin et al., 2018; Martínez‐Íñigo et al., 2013; Niven, 2016; Niven et al., 2012; Troth et al., 2018; Van Kleef, 2016; Van Kleef et al., 2010). However, while Coté (2005) briefly refers to the idea of “personal control” over one’s emotional displays being important to understanding the effects of social interaction quality on individual well-being, no other investigation of interpersonal emotional regulation dynamics accounts for different sources of emotional display rules or choosing to control one’s emotional displays. I posit that the adoption of CDRs is especially relevant to understanding the role played by social interactions on interpersonal effects of emotional labor, over and above the choice of emotion regulation strategies of surface and deep acting. The prevailing consensus in line with the original propositions laid out by Coté (2005) is that the authenticity of emotional displays is pivotal to the enhancement of social interactions, and therefore surface acting (less authentic displays) impairs social interactions while deep acting (more authentic displays) enhances social interactions. However, I suggest that the exploration of such social interpersonal effects of emotional labor has omitted another source of authentic emotional displays i.e., adoption of CDRs. As per Coté’s (2005) model, receivers react more positively to authentic displays of emotion. Indeed, research has shown that people can differentiate between authentic and 76 inauthentic displays of emotion (e.g., Frank et al., 1993; Grandey, Fisk, Mattila, et al., 2005). Further, the primary rationale for prior work suggesting surface acting leads to more inauthentic displays of emotion than deep acting is due to the emotional dissonance experienced by senders when their displays do not match their felt emotions (Coté, 2005; Grandey et al., 2002; Grandey, 2003; Gross & John, 2003). As has been discussed in previous sections, individuals who adopt CDRs are likely to experience lower emotional dissonance and felt inauthenticity due to the autonomous self-regulation they engage in, which in turn is likely to lead to such individuals also having more authentic emotional displays. Additionally, receivers are likely to respond negatively to inauthentic displays of emotions regardless of the discrete emotion being displayed (Boles et al., 2000; Butler et al., 2003; Grandey et al., 2002; Hutson-Comeaux & Kelly, 2002; Rafaeli, 1989). Specifically, receivers may perceive inauthentic emotional displays are an attempt to control the outcomes of the interaction (Rafaeli, 1989), as a signal that the sender is disinterested in developing a positive relationship with the receiver (Grandey et al., 2002), signify a lack of personal attention (Grandey, 2003), or as a sign of dishonesty and mistrust (Collins & Miller, 1994; Parasuraman et al., 1985). Individuals that adopt CDRs are therefore likely to have higher quality social interactions than those that simply comply with prevailing PDRs, owing to their more authentic emotional displays. Therefore, I propose a positive relationship between the tendency to adopt CDRs and social interaction quality due to the higher likelihood of favorable reactions from receivers to authentic displays. Further, the extent to which individuals with a high tendency to adopt CDRs are actually able to display emotions more in line with their authentic selves is contingent on the strength of PDRs they face, with the more authentic displays being curtailed (enhanced) under strong (weak) PDR conditions. Therefore, I propose the following hypothesis. 77 Hypothesis 4a: The positive relationship between tendency to adopt CDRs and social interaction quality will be moderated by PDR strength such that the relationship is weaker (stronger) at higher (lower) levels of PDR strength. Social interaction quality & key outcomes. Once again drawing on the JD-R model and SDT’s view on self-regulation, high quality social interactions are likely to be an important resource for employees, that can act as a buffer against the emotional demands placed on them (Demerouti et al., 2001; Hobfoll, 1989; Hülsheger & Schewe, 2011). Additionally, high quality social interactions are also likely to satisfy needs for relatedness by providing CDR adopters the opportunity to build positive relationships at work (Ryan & Deci, 2008). Therefore, I propose that individuals with higher tendencies for CDR adoption are likely to have more authentic emotional displays and in turn higher quality social interactions which satisfy needs for relatedness and provide a resource surplus. This resource surplus is likely to diminish the amount of emotional exhaustion experienced by those with a high tendency to adopt CDRs (Demerouti et al., 2001; Ryan & Deci, 2008). However, this resource surplus could be curtailed by high PDRs, possibly leading to no net gain or loss, or worst case even a net loss of resources depending on the strength of prevailing PDRs. Therefore, I propose that the tendency to adopt CDRs will be negatively related to emotional exhaustion via improved social interaction quality. Additionally, this relationship is contingent upon the strength of PDRs with the relationship being stronger (weaker) at lower (higher) levels of PDRs. Hypothesis 4b: The negative indirect effect of the tendency to adopt CDRs on emotional exhaustion via social interaction quality is stronger (weaker) at lower (higher) levels of PDR strength. 78 Prior work on the interpersonal nature of emotions and emotional regulation suggests that enhancement of social interactions is positively related to job satisfaction (Fisk & Friesen, 2012; Grandey et al., 2013; Hülsheger & Schewe, 2011; Kafetsios et al., 2012). Indeed, these findings are supported by theoretical and empirical work that suggests that satisfying the basic psychological need for relatedness by having higher quality social connections also increases satisfaction at work (Coté, 2005; Hülsheger & Schewe, 2011; Ryan & Deci, 2008). Further, higher quality social interactions also give employees a sense of personal accomplishment and self-efficacy that further contribute to improved job satisfaction (Brotheridge & Lee, 2002). I propose that in combination with the resource surplus from enhanced social interactions and satisfaction of relatedness needs, individuals with a higher tendency to adopt CDRs are likely to experience higher job satisfaction. This effect is likely contingent on the strength of PDRs, with the positive effect of CDR adoption on job satisfaction via enhanced social interactions being stronger (weaker) at lower (higher) levels of PDR strength. According to the social interaction model (Coté, 2005) authentic displays of emotion are positively related to important performance outcomes such as emotional performance and customer satisfaction (Hülsheger & Schewe, 2011). Indeed, customers tend to react more favorably to authentic emotional displays and respond positively to the employee, leading to higher quality interactions which in turn improve customer satisfaction and evaluations (Brotheridge & Lee, 2002; Coté, 2005; Hennig-Thurau et al., 2006; Hülsheger & Schewe, 2011). Further, enhancement of social interaction quality results in a resource surplus that aids execution of job-related tasks and improves employee task performance (Goldberg & Grandey, 2007; Hülsheger & Schewe, 2011). Therefore, I propose that the enhancement of social interaction quality resulting from CDR adoption has a positive indirect relationship with task 79 performance. Additionally, this positive effect is contingent on PDR strength with the indirect effect being stronger (weaker) at lower (higher) levels of PDR strength. Hypothesis 4c: The positive indirect effect of the tendency to adopt CDRs (i) job satisfaction and (ii) task performance via social interaction quality is stronger (weaker) at lower (higher) levels of PDR strength. 80 METHODS Summary I conducted three studies for this dissertation. Study 1 consisted of two online cross- sectional samples and were used to develop and validate the two new proposed measures of emotional display rule sources (i.e., strength of PDRs and tendency to adopt CDRs). Study 2 was a field study conducted on a multinational sample comprised of employees from multiple organizations in the US and India, which was then augmented with a snowballed sample of full- time workers from 23 countries, with data being collected across three time points. The purpose of Study 2 was to test the moderated-mediation model examining the impact of emotional display rule sources on outcomes of interest via the proposed mechanisms. Study 2 was also used to generate the initial actor profile structure and test the relationship between profile membership and the proposed mechanisms and outcomes. I also controlled for possible confounds such as power, status, surface, and deep acting, to test the incremental explanatory power of the two newly developed measures and proposed actor profiles over and above the traditionally used emotion regulation strategies. Study 3 consisted of 428 full time working professionals recruited via Mturk. The purpose of Study 3 was to replicate the emotional display based actor profile structure generated in study 2. I explain these three studies in more detail below. Study 1 Participants, procedure, and proposed analyses. The primary purpose of Study 1 was to refine the items that have been generated, and assess the validity of the two new proposed constructs of PDR strength and tendency to adopt CDRs by illuminating their nomological network and examining their relationships with other similar constructs. The initial list of items for both scales were generated using two primary methods, consistent with recommendations by Hinkin 81 (1998). First, items were generated by adapting items from preexisting scales that did not assess display rule sources per se but were consistent with the definitions of both proposed constructs. For the Strength of Prescribed Display Rules scale, items from the Explicitness of Display Rules scale (Christoforou & Ashforth, 2015) were adapted to change the focus of the items from being solely customer focused. For the Tendency to Adopt Contextual Display Rules scale, items were adapted from the Prosocial Rule Breaking scale by Dahling et al. (2012), the Perceived Display Rule Conflict scale by Dieguez (2017), and the Deviating from Display Rules scale by Dahling (2017). Second, additional items were generated using a deductive approach wherein the items were based on the conceptual definitions of PDR strength and tendency to adopt CDRs presented in this dissertation. This process led to an initial pool of 12 items for the Strength of PDRs scale and 18 items for the Tendency to Adopt CDRs scale (see Appendix). Two online samples were collected for Study 1 using CloudResearch panels, an online platform that sources and organizes data collection from research subjects. Using online samples from platforms like CloudResearch, TurkPrime and Prolific have become more common (along with other online subject recruitment platforms such as MTurk) with researchers across different fields using it to recruit research participants (e.g., Callan et al., 2017; Marreiros et al., 2017; Simmonds et al., 2018). Data collected on online platforms such as CloudResearch have been found to yield high quality data comparable to data collected in person (Buhrmester et al., 2016; Landers & Behrend, 2015) as well as from commonly used samples such as student subject pools (Buhrmester et al., 2016; Goodman et al., 2013; Minton et al., 2013). In total, Sample 1 consisted of 259, and sample 2 consisted of 349, full-time working professionals, and was used to refine the list of items for both scales and assess the validity and reliability of both measures. For sample 1, 60% identified as female, 38% identified as male and 82 2% identified as transgender/non-binary with an average age of 37 years. For sample 2, 61% identified as female and 39% identified as male for an average age of 36.6 years. Participants in both samples received $2.00 for completing the online questionnaire that contained the two new measures as well relevant correlates from relevant nomological networks. The validation of the two new measures were conducted in two phases. First, as recommended by Hinkin (1998), I conducted exploratory (EFA) and confirmatory factor analyses (CFA) to evaluate the underlying factor structure of the items for both new scales and refine the final items. Second, I examined how the two new measures related to expected psychological correlates to establish discriminant and convergent validity (Campbell & Fiske, 1959; Hinkin, 1998). Study 1 Measures. Please refer to Tables 1 & 2 for reliabilities for all measures across both samples of Study 1. Unless otherwise indicated, items were measured on a 7-point scale ranging from 1 = strongly disagree to 7 = strongly agree. For the two new measures (i.e., Strength of PDRs and Tendency to adopt CDRs), two different question stems were used for both measures, one focusing on internal organizational members and the second on external organizational members. This was in keeping with prior work that has suggested that interactions between clients (most commonly examined external members) should be differentiated from those with internal members such as coworkers (e.g., Tschan et al., 2005). The following question stems were used to measure the two new measures across different interaction targets. “The questions below ask about the policies, norms, and procedures your organization may have with respect to the emotions you should show when interacting with “external people” at work. By “external people,” we mean anyone you interact with 83 as part of your work but who does NOT work for your organization, such as customers, vendors, clients, and parents/students (if you are a teacher). While some organizations may have strong explicit/overt or implicit/unwritten guidelines on the types of emotions their employees should show toward other external people, other organizations may not have any guidelines at all, with their employees free to choose the emotions they want to express. When interacting with “external people” as part of my work (i.e., customers, vendors, clients, etc.)…” “The questions below ask about the policies, norms, and procedures your organization may have with respect to the emotions you should show when interacting with “internal people” at work. By “internal people,” we mean anyone who you interact with as part of your work and who works for your organization, such as supervisors, coworkers, team members, and/or subordinates. While some organizations may have strong explicit/overt or implicit/unwritten guidelines on the types of emotions their employees should show toward other internal people, other organizations may not have any guidelines at all, with their employees free to choose the emotions they want to show to others. When interacting with “internal people” at work (i.e., coworkers, bosses, subordinates, and/or team members)…” Strength of Prescribed Display Rules. The initial list included 12 items for the new measure (see Appendix for full list of items). Sample items included (1) “My organization has clear policies regarding the expression of emotion when interacting with people at work”, (2) “The expectations of my organization with regard to expressing appropriate emotions when interacting with people at work were made clear to me”, and (3) “There is significant pressure from my organization to meet specific expectations in terms of the emotions I show at work.” 84 Tendency to Adopt Contextual Display Rules. The initial list included 18 items for the new measure (see Appendix for full list of items). Sample items included (1) “I feel comfortable deciding the most appropriate emotion to display at work, even if it differs from my organization’s expectations for what I should display”, (2) “When organizational rules regarding the appropriate emotions to display at work interfere with my work, I break those rules”, and (3) “I proactively decide on the most appropriate emotion to display in any situation I face at work, whether my organization wants me to or not.” Decision Authority. Decision authority is a sub-facet of job decision latitude and refers to the amount of latitude given to employees in their job (Karasek Jr, 1979). This is a broad measure of decision-making leeway given by an organization to its employees and should relate positively to the strength of PDRs. I used the 4-item measure developed by Karasek Jr (1979). The 4-items used were (1) “To what extent do you have the freedom to decide how to organize your work?”, (2) “To what extent do you have control over what happens on your job?”, (3) “To what extent does your job allow you to make a lot of your own decisions?”, and (4) “To what extent are you assisted in making your own decisions?” Responses will be measured on a 7-point Likert format, with the scale anchors 1 = To an extremely large extent; 7 = To an extremely small extent. Performance Pressure. Most organizations put pressure on employees to increase performance levels or face repercussions for the poor performance (DeZoort et al., 2006; Gutnick et al., 2012). Because PDRs are a form of organizational control for improving emotional performance, it is likely positively related to generalized performance pressure. I used the 4-item measure developed by Mitchell et al. (2018). The 4-items used were (1) “The pressure for performance in my workplace is high”, (2) “I feel tremendous pressure to produce results”, (3) “If I don’t 85 produce at high levels, my job will be at risk”, and (4) “I would characterize my workplace as a results-driven environment”. Role Ambiguity. While strong PDRs may curtail the autonomy of employees, they also likely make organizational expectations clearer. Therefore, it is likely that PDR strength would be negatively related to role ambiguity, which refers to the “perceived lack of job-related information” (Breaugh & Colihan, 1994, p. 191). I used the 16-item role ambiguity scale developed by House et al. (1983). Sample items included (see Appendix for full list of items) (1) “I don’t know what is expected of me [at work]”, (2) “My responsibilities are clearly defined”, and (3) “The planned goals and objectives are not clear”. Need for Achievement. A tendency to adopt CDRs represents the innate need of an individual to have agency over their emotional displays. It is likely that this tendency also correlates positively with a need for achievement (McClelland, 1975, 1987) which is defined as “the desire for competence, accomplishment, and superior performance” (Chun & Choi, 2014, p. 437). I used the 5-item scale developed by Steers and Braunstein (1976). The 5-items used were (1) “I do my best work when my job assignments are fairly difficult”, (2) “I try very hard to improve on my past performance at work”, (3) “I take moderate risks and stick my neck out to get ahead at work”, (4) “I try to avoid any added responsibilities on my job”, and (5) “I try to perform better than my co-workers”. Work Locus of Control. Locus of control is generally defined as “an expectancy that rewards, reinforcements or outcomes in life are controlled either by one’s own actions (internality) or by other forces (externality)” (Spector, 1988, p. 335). While having an internal locus of control is distinct from a tendency to adopt one’s own display rules, the two measures are likely to be positively related as both assess a certain sense of agentic control on one’s behaviors. I used the 86 16-item Work Locus of Control scale developed by Spector (1988) specifically for the work context. Sample items included (see Appendix for full list of items) (1) “A job is what you make of it”, (2) “Promotions are given to employees who perform well on the job”, and (3) “It takes a lot of luck to be an outstanding employee on most jobs.” Proactive Personality. The adoption of CDRs (by those I refer to as Deviators or Proactives) is predicated on employees claiming agency to choose their own emotional displays. Therefore, even though it is a broader construct (as compared to one that is specifically targeting emotional displays) it is very likely that an individual difference such as proactive personality, defined as people’s proclivity to change their environment and circumstances through direct action (Bateman & Crant, 1993), will be positively related to a tendency to adopt CDRs. I used the 10- item scale used by Seibert et al. (1999. 2001) which is the shortened version of the original proactive personality scale developed by Bateman and Crant (1993). Sample items included (see Appendix for full list of items) (1) “I am always looking for better ways to do things”, (2) “Nothing is more exciting that seeing my ideas turn into reality”, and (3) “If I see something I don’t like, I fix it”. Study 1 Results Phase 1: Item refinement. To stave off any idiosyncratic differences owing to differing contexts that may hamper the external validity of the new measures, the sample used to refine items should ideally include participants from a variety of contexts in with the measures will be used (Clark & Watson, 2016; Hinkin, 1998). Both samples collected via CloudResearch panels consisted of participants with wide range of job roles and industries. First, I ran separate EFAs for both internal-member and external-member versions of the new measures using sample 1. The reverse coded items across all four scales hung together on a 87 separate factor (items 8,10,11 for strength of PDRs; items 3,4,13 for tendency to adopt CDRs). This factor structure was replicated when running all the internal and external rated items together for both scales, wherein the reverse coded items formed their own factor and were dropped. Indeed, research has suggested that reverse coded items tend to fit poorly in factor models (Weijters & Baumgartner, 2012), potentially distort factor structures and incorrectly specify multiple factors based on the coded direction (e.g., Marsh, 1996), and often form a distinct method factor that isn’t meaningful (Woods, 2006). Subsequently, some experts recommend dropping reverse coded items despite their apparent advantages (see DeVellis & Thorpe, 2021). Next, I re-ran EFAs without reverse coded items for both internal-member and external- member versions of the new measures. Given that both new measures for internal- and external- members are likely to be interrelated, I used an oblique rotation while running the EFAs which allows any extracted factors to correlate (Sass & Schmitt, 2010). Starting with the measure for strength of PDRs, I extracted a two-factor solution which explained 95.46% of the total variance in the items (factor 1: eigenvalue = 9.66, factor 2 eigenvalue = 1.05, as compared to the factor 3 eigenvalue = 0.53). These initial results seem to suggest that strength of PDRs for internal- and external-members are two distinct but related constructs (see Table 3). Next, I ran an EFA for a tendency to adopt CDRs and extracted a two-factor solution which explained 91.03% of the total variance in the items (factor 1: eigenvalue = 14.18, factor 2 eigenvalue = 1.79, as compared to the factor 3 eigenvalue = 0.68). These initial results suggest that one’s tendency to adopt CDRs may have two distinct sub-facets that are consistent across internal and external organizational members (see Table 4). A closer examination of the items reveals the potential existence of two sub-facets of the tendency to adopt CDRs. Specifically, the items of factor 1 (items 1 & 7 from 88 the internal and external stems) describe a control dimension, while the items of factor 2 (items, 5,6,8,15,16 from the internal and external stems) describe a rule-breaking dimension of the tendency to adopt CDRs. These two sub-facets, as well as the internal and external sub-facets of PDRs, are discussed in more detail in the supplementary analyses section. Before comparing the potential single- and two-factor solutions for the two measures on model fit, I looked to drop items with low or crossed factor loadings, as well as drop items that had redundancies in terms of content. While there are no fixed rules as to the number of items a new measure should consist of, research has suggested that shorter measures are preferred to improve response rates and errors or biases owing to being distracted or exhausted (Kraut et al., 1975; Schmitt & Stuits, 1985). Further, having a large number of items may not always be the best representation of a construct as a large number of items may indicate adequate reliability (i.e., α > 0.70) in spite of relatively low inter-item correlations (Cortina, 1993; Loevinger, 1954). Therefore, extant recommendations suggest that when developing new scales, retaining four to eight items per scale should be sufficient to capture the construct domain and maintain homogeneity between items (DeVellis & Thorpe, 2021; Hinkin, 1998; Yu et al., 2019), though these suggestions need to be considered along with ensuring the primary construct domain is not being compromised. Subsequently, following this rule of thumb, based on the results from the initial EFAs, I dropped items from each of the four emergent scales (i.e., strength of PDRs for internal- and external-members, rule-breaking and control sub-facets of the tendency to adopt CDRs) with the lowest factor loadings. Ideally, one should attempt to retain all items with factor loadings that are considered “high” i.e., if they are greater than 0.7, however given the limitations of most social science research anything above a 0.4 is considered satisfactory (Costello & Osborne, 2005; Ford et al., 1986; Velicer & Fava, 1998). This resulted in a final set 89 of 5 items for strength of PDRs for internal members (α = .87), 7 items for strength of PDRs for external members (α = .91), 10 items for the rule-breaking sub-facet of tendency to adopt CDRs (α = .93), and 4 items for the control sub-facet of tendency to adopt CDRs (α = .81). Further, for the purposes of testing the hypotheses for this dissertation I also created unidimensional scales for strength of PDRs (12 items; α = .93) and tendency to adopt CDRs (14 items; α = .92) which were a simple combination of the retained items for both measures. Finally, I confirmed the factor structure of the final set of items for all the new measures using a CFA on Sample 2 (n=349). Prior research has laid guidelines that suggest that 1:10 item- sample ratio are needed to extract an accurate CFA solution (Fabrigar et al., 1999; Guadagnoli & Velicer, 1988). One of the key benefits of running CFAs is that they generate goodness of fit indices that can be used to judge the quality of the model, which in turn helps address issues with solely relying on EFAs (Fabrigar et al., 1999; Gerbing & Anderson, 1988). I compared the two- factor model of both new measures (i.e., with strength of PDRs for internal- and external- members, and the control and rule-breaking sub-facets of tendency to adopt CDRs, loading on separate factors respectively) with a single factor model (i.e., where all the items loaded on a single factor for both new measures respectively) for the retained items for all measures. For the strength of PDRs measure, while both models exhibited good model fit, the results suggested that the two-factor model (χ2 [df = 53, n = 336] = 177.85, CFI =.95, SRMR =.04) derived from the EFA fit the data better than the single-factor model (χ2 [df = 54, n = 336] = 284.32, CFI =.91, SRMR =.05). To further investigate, I conducted a chi-squared difference test (χ2diff [1] = 106.47, p < .05) on the two models, finding that the two-factor model did indeed yield better model fit than the single factor model. For the tendency to adopt CDRs measure, the results of the CFA suggested that the two-factor model (χ2 [df = 76, n = 349] = 153.37, CFI =.97, 90 SRMR =.04) derived from the EFA fit the data better than the single-factor model (χ2 [df = 77, n = 349] = 465.72, CFI =.87, SRMR =.08) as well. To further investigate, I conducted a chi- squared difference test (χ2diff [1] = 312.35, p < .05) on the two models, finding that the two-factor model did indeed yield better model fit than the single factor model. While both measures showed better fit for the two-factor models over a unidimensional factor model, for the purposes of this dissertation I plan to test the originally proposed hypotheses which relied on the unidimensional versions of the new constructs. Specifically, for the strength of PDRs measure, the single-factor model showed adequate fit (χ2 [df = 54, n = 336] = 284.32, CFI =.91, SRMR =.05), reliability (Sample 1: α = 0.93; Sample 2: α = 0.93), and the correlation between the internal and external versions of the measure was strong and significant (Sample 1: r=0.77, p<.05; Sample 2: r=0.68, p<.05), suggesting that the single factor model is reliable and valid. Similarly, while the single-factor model of the tendency to adopt CDRs exhibited poorer fit than the two-factor model, the unidimensional version of the measure was reliable (Sample 1: α = 0.92; Sample 2: α = 0.91), and the correlation between the control and rule-breaking sub-facets of the measure were moderately strong and significant (Sample 1: r=0.41, p<.05; Sample 2: r=0.57, p<.05). Given these results, while I plan to test the proposed moderated-mediation model with the unidimensional versions of the two new measures, I will also test the proposed model with the two-factor versions of both new measures in the supplementary analyses section. Phase 2: Convergent and discriminant validity. Phase 2 of the Study 1 analyses looked to establish the convergent and discriminant validity of the two new measures using both samples 1 & 2. Convergent validity refers to the extent to which the newly developed scale relates to other similar or closely related constructs; discriminant validity refers to the extent to which the new 91 scale has small or null correlations with constructs that are dissimilar to it (Campbell & Fiske, 1959; Hinkin, 1998). When considering the new proposed scales, it is important to consider related (but distinct) constructs that, in the case of the Strength of PDRs scale, assess job demands that affect the freedom to make decisions, and in the case of the Tendency to Adopt CDRs scale, assess individual differences that represent independent and proactive tendencies in individuals. The reliabilities of the new measures (as well as their two-factor sub-facets) along with their correlations with related measures from their nomological networks for both samples can be found in Tables 1 & 2. Starting with the unidimensional strength of PDRs measure, I found a significant positive relationship with decision authority for sample 1 (r = .17, p < .05) but a non- significant relationship for sample 2 (r = .04, p > .05), a significant positive relationship with performance pressure for both samples (Sample 1: r = .46, p < .05; Sample 2: r = .44, p < .05), and a significant negative relationship with role ambiguity for both samples (Sample 1: r = -.18, p < .05; Sample 2: r = -.15, p < .05), finding general support for the convergent and discriminant validity of the new unidimensional measure. As for the internal and external dimensions of the strength of PDRs, I found a similar pattern of relationships for both sub-scales (as for the unidimensional scale) with decision authority (Sample 1 internal: r = .11, p > .05, external: r = .18, p < .05; Sample 2 internal: r = .01, p > .05, external: r = .05, p > .05), performance pressure (Sample 1 internal: r = .47, p < .05, external: r = .41, p < .05; Sample 2 internal: r = .44, p < .05, external: r = .4, p < .05), and role ambiguity (Sample 1 internal: r = -.29, p < .05, external: r= - .07, p < .05; Sample 2 internal: r = -.17, p < .05, external: r = -.12, p < .05). The only difference between the unidimensional and two-factor version of this scale were with decision authority 92 which was significantly related only to the strength of PDRs for external members and not for internal members. For the tendency to adopt CDRs unidimensional measure, I found a significant positive relationship with a need for achievement for both samples (Sample 1: r = .55, p < .05; Sample 2: r = .52, p < .05), a significant positive relationship with having an internal locus of control for both samples (Sample 1: r = .51, p < .05; Sample 2: r = .57, p < .05), and a significant positive relationship with having a proactive personality for both samples (Sample 1: r = .29, p < .05; Sample 2: r = .24, p < .05), finding general support for the convergent and discriminant validity of the new unidimensional measure. As for the control and rule-breaking sub-facets of the tendency to adopt CDRs, I found similar patterns of relationships as for the unidimensional version of the new measure, albeit with different strengths for the two sub-facets. Specifically, I found a significant positive relationship for both sub-facets with a need for achievement (Sample 1 control: r = .55, p < .05, rule-breaking: r = .49, p < .05; Sample 2 control: r = .37, p < .05, rule- breaking: r = .48, p < .05), internal locus of control (Sample 1 control: r = .36, p < .05, rule- breaking: r = .51, p < .05; Sample 2 control: r = .37, p < .05, rule-breaking: r = .55, p < .05), and proactive personality (Sample 1 control: r = .51, p < .05, rule-breaking: r = .18, p < .05; Sample 2 control: r = .45, p < .05, rule-breaking: r = .13, p < .05). Study 1 Discussion In study 1, using two independent samples, I provide initial evidence that the two new proposed measures are psychometrically sound as evident by the internal consistency coefficients. Results from exploratory and confirmatory factor analyses found support for two- factor solutions for both measures. Finally, the significant relationships between strength of PDRs and decision authority, performance pressure and role ambiguity, and the significant 93 relationships between tendency to adopt CDRs and need for achievement, internal locus of control and proactive personality, suggest that both new measures (and their respective sub- facets) have good convergent and discriminant validity. While the unidimensional measures exhibited worse fit than their two-factor counterparts, they showed satisfactory validity and reliabilities to use them to test the proposed hypotheses for the purpose of this dissertation. However, as mentioned previously, I also test the proposed hypotheses using the two-factor versions of both measures in the supplementary analyses section. Study 2 Participants and procedure. The primary purpose of Study 2 was to test the proposed hypotheses and establish an initial actor profile structure based on the source of emotional display rules (and test how profile membership effects the proposed mediators and outcomes differentially). For Study 2, I collected data from 739 full-time working professionals across a variety of occupations (ranging from service roles to non-customer facing roles) across industries to get a broad and diverse cross section of the workforce. This data was collected via a mixture of snowball sampling and collaborations with multiple small organizations in India and the US. Of the final sample, 66% identified as female, 33% identified as male and 1% identified as non- binary or preferred not to say; the average age was 39.8 years. In terms of ethnicity, 42.3% were White, 3.5% were Black, 40.1% were South and South-East Asian, 1.2% were Hispanic/Latino(a), 0.5% were Middle Eastern, and 12.3% identified as having multiple ethnicities. While the majority of the sample came from the US (53%) and India (36%), there was representation from 23 countries across six continents, working in organizations across a wide range of industries and job roles. 94 Data collection took place across three time points, one week apart. Specifically, strength of PDRs, tendency to adopt CDRs and demographics were measured at Time 1, the four proposed mechanisms of felt inauthenticity, ego depletion, autonomy and social interaction quality were measured at Time 2, and the three outcomes of emotional exhaustion, job satisfaction and task performance were measured at Time 3. Potential confounds of surface and deep acting (Time 1), and power and status (Time 2) were also measured. Participants were given anonymized identifiers to match survey responses across time points. Participants were provided with individual feedback reports in exchange for their participation. There was attrition across time points with 739 completing the Time 1 survey, 598 completing the Time 2 survey and 554 completing the Time 3 survey. Study 2 Measures The two newly developed measures of Strength of PDRs and Tendency to Adopt CDRs were measured in addition to the below mentioned constructs. Unless otherwise indicated, items will be measured on a 7-point scale ranging from 1 = strongly disagree to 7 = strongly agree. Felt inauthenticity. 6-items from the scale developed by Erickson and Ritter (2001) were used to measure felt inauthenticity. The 6-items used were (1) “"To get through my work day, I feel like I have to become mechanical or robot-like", (2) "When I'm at work, I become unsure of what my 'real' feelings are", (3) "I worry that this job is hardening me emotionally", (4) "I don't feel I can be myself at work", (5) "I have to fake how I really feel when I'm at work", and (6) "I basically have to become a different person when I'm at work." Ego-Depletion. The 5-item depletion measure adapted from the original scale developed by Twenge et al. (2004) was used. The 5-items used were (1) “My mental energy is running low”, 95 (2) “My mind feels unfocused”, (3) “It takes a lot of effort for me to concentrate on something”, (4) “I feel drained”, and (5) “I feel like my willpower is gone”. Autonomy. The 3-item measure used by Morgeson et al. (2005) adapted from Oldham and Hackman (1981) was used to measure autonomy. The 3-items used were (1) “I have significant autonomy in determining how I do my job”, (2) “I can decide on my own how to go about doing my work”, and (3) “I have considerable opportunity for independence and freedom in how I do my job.” Social Interaction Quality. The 7-item scale was adapted from the Diary of Ambulatory Behavioral States (DABS) measure by Kamarck et al. (1998) (see appendix for full measure). The measure was measured on a 7-point scale ranging from 1 = Never to 7 = Always. Sample items included: (1) “How often do people at work show care and concern for you?”, (2) “How often do people give you constructive feedback at work?”, (3) “How often do people at work make you feel important?” Emotional Exhaustion. The 4-item scale adapted by Koopman et al. (2016) from the original scale developed by Maslach and Jackson (1981) was used to measure emotional exhaustion. The 4-items used were (1) “I am emotionally drained from my work”, (2) “I am burned out from my work”, (3) “I am frustrated by my job”, and (4) “I am working too hard on my job.” Job satisfaction. 5-items were used from the job satisfaction scale adapted by Judge et al. (2006) from the original measure developed by Brayfield and Rothe (1951). The 5-items used were (1) “Most days I am enthusiastic about my work”, (2) “I feel fairly satisfied with my present job”, (3) “I find real enjoyment in my work”, (4) “Each day of work seems like it will never end”, and (5) “I consider my job rather unpleasant.” 96 Task-Performance. The 7-item scale adapted by Koopman et al. (2016) from the scale developed by Williams and Anderson (1991) was used to assess task-performance. The 7-items used were (1) “I have adequately completed my assigned duties”, (2) “I have fulfilled responsibilities specified in my job description”, (3) “I have performed the tasks expected of me”, (4) “I have met the formal requirements of my job”, (5) “I have engaged in activities that directly affect my performance”, (6) “I have neglected aspects of the job that I am obligated to perform”, and (7) “I have failed to perform essential duties.” Surface and Deep Acting. The 5-item measure for surface acting and the 3-item measure for deep acting developed by Grandey (2003) was used. The 5-items for surface acting were (1) “I put on an act in order to deal with customers in an appropriate way”, (2) “I faked a good mood”, (3) “I put on a "show" or "performance", (4) “I just pretended to have the emotions I need to display for my job”, and (5) “I put on a "mask" in order to display the emotions I need to display for my job.” The 3-items for deep acting were (1) “I tried to actually experience the emotions I must show”, (2) “I made an effort to actually feel the emotions that I needed to display toward others”, and (3) “I worked hard to feel the emotions that I needed to show to others.” Power. The 7-item measure for power developed by (Yu et al., 2019) was used (see appendix for full measure). Sample items included: (1) “I formally manage many other people”, (2) “I have a great deal of power at work”, (3) “My job allows me to control access to other people with a great deal of power”. Status. The 8-item measure for power developed by (Yu et al., 2019) was used (see appendix for full measure).. Sample items included: (1) “Others often seek my opinion because they respect me”, (2) “I have a good reputation among those I work with”, (3) “People come to me for advice because I am good my job.” 97 Study 2 Analyses I conducted a moderated mediation analysis (Edwards & Lambert, 2007; Preacher et al., 2007) to test the indirect relationships between the two new constructs and the outcomes of interest. I centered the predictor variables at their means before conducting my analyses. This eliminated nonessential multicollinearity and allows for a more accurate interpretation of interaction plots (Cohen et al., 2013). Specifically, I tested the effect of tendency to adopt CDRs and strength of PDRs on emotional exhaustion, job satisfaction and task performance via felt inauthenticity, ego depletion, autonomy, and social interaction quality (see Figure 2). To test the proposed moderated mediation model, I followed the recommendations of Hayes (2017) and draw 5000 replacement samples to calculate bootstrapped confidence intervals for the conditional indirect effects. Further, to provide evidence for moderated-mediation, the index of moderated-mediation (Hayes, 2015) was also calculated. To find evidence of moderated- mediation the index of moderated-mediation must be significantly different from zero (Hayes, 2015). If the bootstrap confidence interval generated for the index does not include zero, this leads to the inference that moderated-mediation is present. Identifying which indirect effect at which particular level of the moderator is significant involves generating bootstrap confidence intervals for each indirect effect at each particular level of the moderator. Next, I ran a LPA on the Study 2 data. Following the recommendations made by Nylund et al. (2007), I started by specifying two latent profiles and kept increasing the number of latent profiles “until the increase in model fit no longer merited the reduction in parsimony achieved by specifying another latent class” (Gabriel et al., 2015, p. 866). This approach inductively generates qualitatively and quantitively different actor profiles and is the primary method used 98 by researchers using LPA (e.g., Foti et al., 2012; Gabriel et al., 2015; Graves et al., 2015; Woo & Allen, 2014). Consistent with recent research that has used LPA and standardized recommendations (see Dahling et al., 2017; Foti et al., 2012; Gabriel et al., 2015; Morin et al., 2011) I used seven statistics to assess model fit: entropy, , Bayesian information criterion (BIC; recommended by Nylund et al., 2007), sample-size-adjusted BIC (SSA–BIC; recommended by Tofighi & Enders, 2008), bootstrap likelihood ratio test (BLRT; recommended by Nylund et al., 2007), Lo- Mendell-Rubin likelihood ratio test (LMR; recommended by Tofighi & Enders, 2008), Akaike information criterion (AIC), and log likelihood (LL). Though there are no official threshold for these fit statistics to cross to be considered “best fitting” with respect to LPA, greater model fit can be judged by lower LL, AIC, BIC, and SSA–BIC values as compared to the other profile solutions; larger entropy values (ranging from 0.00 to 1.00) as compared to the other profile solutions; and LMR and BLRT should be significant (p < .05). Along with accounting for these fit statistics, I also eliminated profile solutions that are not theoretically grounded and meaningful (Foti et al., 2012) and selected a solution that also represents a fairly significant percentage of the sample to increase generalizability and replicability (Dahling et al., 2017). For the LPA, I used the automatic three-step approach recommended by Asparouhov and Muthén (2014). First, profile enumeration (i.e., determining the number of profiles that best fits the data) was conducted and a best fitting solution identified. In the second step, the most-likely class membership (i.e., the estimated probability that an individual could belong to each of the identified actor profiles, highlighting the profile to which the individual likely belongs; Morin et al., 2011) was obtained from the posterior distribution from the profile enumeration process from the previous step (Asparouhov & Muthén, 2014). Lastly, the auxiliary variables (i.e., the 99 hypothesized mechanisms and outcomes of the proposed actor profile membership) were modeled (Lanza et al., 2013) while accounting for the most-likely class membership from step two and the classification error rate (Asparouhov & Muthén, 2014; Gabriel et al., 2018). The last step i.e., the modeling of auxiliary variables, can be found in the supplementary analyses section. To model outcomes, I used the DCON command in Mplus (Asparouhov & Muthén, 2014; Lanza et al., 2013) which allows for comparisons between actor profiles on each of the modelled outcomes. Specifically, the DCON command assesses if there are significant differences between actor profiles for each outcome while accounting for possible errors in classification (one of the advantages of LPA over other latent class analyses). These analyses (i.e., DCON for modeling outcomes) are widely accepted and recommended when conducting LPA (e.g., Bennett et al., 2016; Dahling et al., 2017; Gabriel et al., 2015). Study 2 Results Test of Hypotheses. All analyses were conducted in Mplus Version 8.7 (Muthén & Muthén, 2017). Correlations, means and standard deviations can be found in Table 5. It should be noted that power (r = .11, p < .05) had a significant positive relationship with the tendency to adopt CDRs while status (r = .04, p > .05) did not. Subsequently, only power was used as a control (along with surface and deep acting) when testing the proposed model. I started by testing the proposed moderated-mediation model (see Tables 6 & 7). I allowed the errors between all the proposed mediators and outcomes to covary, and controlled for power, surface, and deep acting by including paths from the three controls to all the mediators as well as final outcomes. The model had good model fit (χ2 [df = 6, n = 573] = 9.65, CFI =.99, SRMR =.01). Hypotheses 1a predicted that the there is a negative relationship between the tendency to adopt CDRs and felt inauthenticity, and that this relationship will be moderated 100 by PDR strength. The path from tendency to adopt CDRs to felt inauthenticity not significant (B = .023, p > .05), however, the path model results indicated that PDR strength moderated the relationship between tendency to adopt CDRs and felt inauthenticity (B = .11, p < .05). Figure 3 presents the plot of this interaction, at conditional values of PDR strength and suggests that contrary to the proposed prediction, when accounting for PDR strength there is a positive relationship between the tendency to adopt CDRs and felt inauthenticity, and that this relationship is stronger (weaker) when PDR strength is higher (lower). Therefore, hypothesis 1a was not supported. Hypothesis 1b predicted that the negative indirect effect of the tendency to adopt CDRs on emotional exhaustion via felt inauthenticity is stronger (weaker) at lower (higher) levels of PDR strength. While the indirect effect of the tendency to adopt CDRs on emotional exhaustion via felt inauthenticity was not significant (B = -.006, p > .05), the index of moderated-mediation was significant (B = .031, p < .05). Further, the conditional indirect effects of the tendency to adopt CDRs on emotional exhaustion via felt inauthenticity at 1 SD below the mean (B = -.035, p < .05) for PDR strength was significant while at 1 SD above the mean (B = .022, p > .05) was not, providing partial support for Hypothesis 1b. Hypothesis 1c predicted that the positive indirect effect of the tendency to adopt CDRs on (i) job satisfaction and (ii) task performance via felt inauthenticity is stronger (weaker) at lower (higher) levels of PDR strength. The indirect effects of tendency to adopt CDRs on job satisfaction via felt inauthenticity was not significant (B = .005, p > .05), while the index of moderated-mediation was significant (B = - .023, p < .05). The conditional indirect effects of the tendency to adopt CDRs on job satisfaction via felt inauthenticity at 1 SD below the mean (B = .025, p < .05) for PDR strength was significant while at 1 SD above the mean (B = -.016, p > .05) was not, providing partial support for Hypothesis 1c(i). The indirect effects of tendency to adopt CDRs on task performance (B = 101 .001, p > .05) via felt inauthenticity as well as the index of moderated-mediation (B = -.004, p > .05) were not significant, rejecting Hypothesis 1c(ii). Hypothesis 2a predicted that the negative relationship between the tendency to adopt CDRs and ego depletion will be moderated by PDR strength such that the relationship is stronger (weaker) at lower (higher) levels of PDR strength. The path from tendency to adopt CDRs to ego depletion was not significant (B = .063, p > .05), and the results further indicate that PDR strength does not moderate this relationship (B = .022, p > .05), rejecting Hypothesis 2a. Hypothesis 2b predicted that the negative indirect effect of the tendency to adopt CDRs on emotional exhaustion via ego depletion is stronger (weaker) at lower (higher) levels of PDR strength. Hypothesis 2b was not supported with a non-significant indirect relationship between the tendency to adopt CDRs and emotional exhaustion via ego depletion (B = .025, p > .05) and a non-significant index of moderated-mediation (B = .009, p > .05). Hypothesis 2c predicted that the positive indirect effect of the tendency to adopt CDRs (i) job satisfaction and (ii) task performance via ego depletion is stronger (weaker) at lower (higher) levels of PDR strength. Hypothesis 2c(i) was not supported with a non-significant indirect relationship between the tendency to adopt CDRs and job satisfaction via ego depletion (B = -.009, p > .05) and a non- significant index of moderated-mediation (B = -.003, p > .05). Hypothesis 2c(ii) was also not supported with a non-significant indirect relationship between the tendency to adopt CDRs and task performance via ego depletion (B = -.003, p > .05) and a non-significant index of moderated-mediation (B = -.001, p > .05). Hypothesis 3a predicted that the positive relationship between the tendency to adopt CDRs and autonomy will be moderated by PDR strength such that the relationship is weaker (stronger) at higher (lower) levels of PDR strength. In partial support of Hypothesis 3a the path 102 model results indicate a significant positive direct relationship between the tendency to adopt CDRs and autonomy (B = .184, p < .05). However, the results suggest that PDR strength did not moderate this relationship (B = -.052, p > .05). Hypothesis 3b predicted that the negative indirect effect of the tendency to adopt CDRs on emotional exhaustion via autonomy is stronger (weaker) at lower (higher) levels of PDR strength. Hypothesis 3b was not supported with a non-significant indirect relationship between the tendency to adopt CDRs and emotional exhaustion via autonomy (B = 0.005, p > .05) and a non-significant index of moderated-mediation (B = .001, p > .05). Hypothesis 3c predicted that the positive indirect effect of the tendency to adopt CDRs (i) job satisfaction and (ii) task performance via autonomy is stronger (weaker) at lower (higher) levels of PDR strength. Hypothesis 3c(i) was not supported with a marginally significant indirect relationship between the tendency to adopt CDRs and job satisfaction via autonomy (B = .012, p > .05) and a non-significant index of moderated-mediation (B = -.003, p > .05). Hypothesis 3c(ii) was partially supported with a significant positive indirect relationship between the tendency to adopt CDRs and task performance via autonomy (B = .016, p < .05) and a non-significant index of moderated-mediation (B = -.005, p > .05). Hypothesis 4a predicted that the positive relationship between tendency to adopt CDRs and social interaction quality will be moderated by PDR strength such that the relationship is weaker (stronger) at higher (lower) levels of PDR strength. The path from tendency to adopt CDRs to social interaction quality was not significant (B = .055, p > .05), and the results further indicate that PDR strength does not moderate this relationship (B = -.069, p > .05), rejecting Hypothesis 4a. Hypothesis 4b predicted that the negative indirect effect of the tendency to adopt CDRs on emotional exhaustion via social interaction quality is stronger (weaker) at lower (higher) levels of PDR strength. Hypothesis 4b was not supported with a non-significant indirect 103 relationship between the tendency to adopt CDRs and emotional exhaustion via social interaction quality (B = -.005, p > .05) and a non-significant index of moderated-mediation (B = .006, p > .05). Hypothesis 4c predicted that the positive indirect effect of the tendency to adopt CDRs on (i) job satisfaction and (ii) task performance via social interaction quality is stronger (weaker) at lower (higher) levels of PDR strength. Hypothesis 4c(i) was not supported with a non-significant indirect relationship between the tendency to adopt CDRs and job satisfaction via social interaction quality (B = .013, p > .05) and a non-significant index of moderated-mediation (B = - .016, p > .05). Hypothesis 2c(ii) was not supported with a non-significant indirect relationship between the tendency to adopt CDRs and task performance via social interaction quality (B = .002, p > .05) and a non-significant index of moderated-mediation (B = -.003, p > .05). Latent Profile Analyses. Means, standard deviations and correlations for Study 2 are in Table 5. Tendency to adopt CDRs and PDR strength were weakly related (r = -.11, p <.05) suggesting that these are related but distinct constructs. Table 8 provides the fit statistics for the various possible latent profile solutions. As recommended by prior LPA research (Gabriel et al., 2018; Gabriel et al., 2015; Morin et al., 2017; Nylund et al., 2007) I chose the five-factor solution because it exhibited the lower LL, AIC, SSA-BIC and the second highest entropy, as well as significant LMR and BLRT values, in comparison to the two-, three-, four -, six – or seven- profile solutions. Although the two-profile solution had a lower BIC and the three-profile solution had a higher entropy, the five-profile solution exhibited the best overall fit. Therefore, I retained the five-profile structure (see Figure 4). I found general support for the proposed display rule actor profile structure, with some differences which I discuss next. First, I labeled those with the most common profile Reluctant Rule-Followers/Deviators (44.3%; M Tendency CDRs = 3.88; M PDR Strength = 3.98), given that these 104 individuals reported moderate levels of both, tendency to adopt CDRs, and PDR strength, they are likely to either reluctantly adhere to the moderate-high emotional display expectations in their environment or reluctantly deviate from those expectations. Those with the next most common profile match the proposed description of Proactives (21.3%; M Tendency CDRs = 4.70; M PDR Strength = 2.36) who have a high tendency to adopt CDRs and work in a weak PDR strength context. The next most common profile fit the proposed description of Passives (18.50%; M Tendency CDRs = 3.40; M PDR Strength = 2.63) who have a low tendency to adopt CDRs and work in a weak PDR strength context. The next most common profile fit the proposed description of Rule- Followers (10.40%; M Tendency CDRs = 3.14; M PDR Strength = 5.28) who have a low tendency to adopt CDRs and work in a strong PDR strength context. Finally, the least common profile fit the description of Deviators (5.50%; M Tendency CDRs = 4.98; M PDR Strength = 5.31) who have a high tendency to adopt CDRs and work in a strong PDR strength context. Taken together, the initial LPA results revealed two qualitatively different profiles (i.e., Rule-Followers and Proactives) and three quantitatively different profiles (i.e., Reluctant Rule-Followers/Deviators, Passives, and Deviators), partially conforming to the four proposed actor profiles. Further, these results suggest the existence of quantitatively and qualitatively different display rule based actor profiles. Before moving onto the modeling of auxiliary variables and examining how profile membership differentially affects the proposed mediators and outcomes (see supplementary analyses), I attempt to replicate this latent profile structure with another sample in Study 3. Study 2 Discussion In Study 2, I tested the proposed moderated-mediation model and generated the initial latent profile structure. The results of the path analyses suggest that the relationship between the 105 tendency to adopt CDRs and felt inauthenticity is moderated by PDR strength. However, the interaction pattern (Figure 3) was in the opposite direction from what was hypothesized with those high in their tendency to adopt CDRs experiencing higher felt inauthenticity, with this effect being stronger for weak PDRs. Further, while there were no significant indirect effects, I found evidence for a significant moderated-mediation wherein the tendency to adopt CDRs had a positive conditional indirect effect on job satisfaction, and a negative conditional indirect effect on emotional exhaustion, both at lower levels of PDR strength, partially supporting Hypothesis 1. These results suggest that while adoption of CDRs may inadvertently increase inauthenticity under conditions of strong PDRs, under conditions of weak PDRs individuals may still be able to reap the benefits of CDR adoption in the form of lowered emotional exhaustion and improved job satisfaction (as evidenced by significant conditional indirect effects). I also found a significant positive relationship between the tendency to adopt CDRs and autonomy, and a significant positive indirect relationship between the tendency to adopt CDRs and task performance via autonomy, providing partial support for Hypothesis 3. These results lend initial support for the importance of adopting CDRs in fomenting a sense of autonomy which can positively impact performance. All other proposed hypotheses were not supported. The results of the initial LPA found support for a five-profile solution that partially supported the proposed profile structure. The results confirmed the existence of Proactives, Passives, Rule-Followers and Deviators. Additionally, the LPA results suggested that the most common profile was one with individuals who exhibit moderate tendencies to adopt CDRs and experience moderate to strong PDRs. I labeled this profile the Reluctant Rule- Followers/Deviators given the relatively strong PDRs they experience in their work environments (similar to Rule-Followers and Deviators) and the moderate tendencies to adopt 106 CDRs would suggest that they likely are not especially motivated to either adhere to or deviate from the prevailing PDRs. Study 3 Participants & procedure. Study 3 builds off the results from Study 2 in that it attempts to replicate the actor profile structure that emerged from Study 2. Study 3 consisted of an online sample recruited from Mturk and consisted of 428 full time working professionals working across a wide range of industries and job roles. In this sample, 44.8% identified as female, 54.7% identified as male and 0.5% identified as non-binary or preferred not to say; the average age was 32.4 years. In terms of ethnicity, 68.7% were White, 11.4% were Black, 8.2% were South and South-East Asian, 3.7% were Hispanic/Latino(a), and 5.6% identified as having multiple ethnicities. Analyses and measures. The analytic procedures and measures used in Study 2 were used to replicate the proposed actor profile structure. Study 3 Results and Discussion Table 8 provides the fit statistics for the various possible latent profile structures for Study 3. As recommended by prior LPA research (Gabriel et al., 2018; Gabriel et al., 2015; Morin et al., 2017; Nylund et al., 2007). I chose the five-factor solution because it exhibited the lower AIC, SSA-BIC and the highest entropy, as well as significant LMR and BLRT values, in comparison to the two-, three-, four -, six – or seven-profile solutions. Although the two-profile solution had a lower BIC, the five-profile solution exhibited the best overall fit. Therefore, I retained the five- profile structure (see Figure 5). I found general support for, and replicated, the initial actor profile structure generated in Study 2, with key differences being in how common the profiles were. First, replicating the 107 findings from Study 2, the most common profile was that of Reluctant Rule-Followers/Deviators (41.14%; M Tendency CDRs = 3.84; M PDR Strength = 3.91). Those with the next most common profile were Passives (27.06%; M Tendency CDRs = 3.31; M PDR Strength = 2.29), followed by Rule-Followers (14.42%; M Tendency CDRs = 2.93; M PDR Strength = 5.39). The next most common profile were the Deviators (10.69%; M Tendency CDRs = 5.17; M PDR Strength = 5.51) and finally the least common profile were the Proactives (6.69%; M Tendency CDRs = 5.31; M PDR Strength = 1.68). In sum, the LPA results from Study 3 successfully replicated the actor profile structure generated in Study 2. Reluctant Rule-Followers/Deviators comprised the most common profile across both studies 1 & 2. Further, results from both studies suggest that Passives are the next most common actor profile, while Deviators are the least common actor profile. Most notably, results from both studies suggest that Rule-Followers represent a relatively small portion of the employee population (Study 1: 10.4%; Study 2: 14.42%), further highlighting the skewed focus on this subpopulation by extant emotional labor scholars. I discuss the specific advantages of a person-centered approach over a traditional variable-centered approach (in the context of examining emotional display rule sources) in the general discussion. 108 SUPPLEMENTARY ANALYSES Supplementary Path Model Analyses As had been mentioned when discussing the results of Study 1, the two factor solutions for both strength of PDRs and tendency to adopt CDRs scales showed better model fit and internal consistency than the unidimensional versions of the new measures. In this section, I test the proposed moderated-mediation model using the two-factor versions of the measures. Specifically, I test the model using the four combinations of the two new measures i.e., using the control and rule-breaking sub-facets of the tendency to adopt CDRs and the internal and external sub-facets of the strength of PDRs measures. Next, I discuss the path model results for each of these four moderated-mediation models. In order to not report redundant or null findings, I will only be reporting the significant relationships found in these analyses, the full path model results can be found in the appendices. Control sub-facet of tendency to adopt CDRs and strength of PDRs for internal organizational members. I first tested the full proposed moderated-mediation model using the control sub-facet of tendency to adopt CDRs and strength of PDRs for internal organizational members, while controlling for the rule-breaking sub-facet, a potential confound of perceived status (which was positively correlated with the control sub-facet measure; r = .16, p < .05), and the regulation strategies of surface and deep acting to establish the incremental validity of the control sub-facet measure over and above established emotion regulation strategies (see Tables 10 & 11). The model had satisfactory model fit (χ2 [df = 6, n = 569] = 11.16, CFI =.99, SRMR =.01). The results of the path analyses revealed a significant positive indirect effect of the control sub-facet on job satisfaction (B = .034, p < .05), a significant negative indirect effect of the control sub- facet on and emotional exhaustion (B = -.047, p < .05) via felt inauthenticity. Further, the 109 conditional indirect effects of the control sub-facet on emotional exhaustion via felt inauthenticity at 1 SD below the mean (B = -.047, p < .05) for PDR strength was significant while at 1 SD above the mean (B = .021, p > .05) was not. The conditional indirect effects of the control sub-facet on job satisfaction via felt inauthenticity at 1 SD below the mean (B = .031, p < .05) for PDR strength was significant while at 1 SD above the mean (B = .014, p > .05) was not. Importantly, the relationship between the control sub-facet and felt-inauthenticity was negative and significant, suggesting that the rule-breaking sub-facet (which forms the majority of the items for the full measure) is likely driving the counterintuitive results of Hypothesis 1a. Further, the conditional indirect effects also supported the hypothesized relationships in this dissertation, re-emphasizing that it was likely the rule-breaking sub-facet driving the counterintuitive and null findings. All other direct, indirect, and moderated mediated effects were non-significant. Control sub-facet of tendency to adopt CDRs and strength of PDRs for external organizational members. I next tested the full proposed moderated-mediation model using the control sub-facet of tendency to adopt CDRs and strength of PDRs for external organizational members, while controlling for the rule-breaking sub-facet, status, surface, and deep acting (Tables 12 & 13). The model had satisfactory model fit (χ2 [df = 6, n = 566] = 1.06, CFI =.99, SRMR =.004). The results of the path analyses revealed a significant positive indirect effects of the control sub-facet on job satisfaction (B = .027, p < .05) and a significant negative indirect effects of the control sub-facet on emotional exhaustion (B = -.042, p < .05) via felt inauthenticity. Further, the conditional indirect effects of the control sub-facet on emotional exhaustion via felt inauthenticity at 1 SD below the mean (B = -.057, p < .05) for PDR strength was significant while at 1 SD above the mean (B = .027, p > .05) was not. The conditional indirect effects of the control sub-facet on job satisfaction via felt inauthenticity at 1 SD below the mean (B = .037, p < 110 .05) for PDR strength was significant while at 1 SD above the mean (B = .017, p > .05) was not. These findings replicated the results from the previous model suggesting that accounting for both internal- and external-member PDR strength, the control sub-facet helps improve job satisfaction and reduce emotional exhaustion via increased felt inauthenticity, under conditions of weak PDRs. All other direct, indirect, and moderated mediated effects were non-significant. Rule-breaking sub-facet of tendency to adopt CDRs and strength of PDRs for internal organizational members. I next tested the full proposed moderated-mediation model using the rule-breaking sub-facet of tendency to adopt CDRs and strength of PDRs for internal organizational members, while controlling for the control sub-facet, perceived power (which was positively correlated with the rule-breaking sub-facet measure; r = .11, p < .05), and surface and deep acting (see Tables 14 & 15). The model had satisfactory model fit (χ2 [df = 6, n = 572] = 26.55, CFI =.98, SRMR =.021). The results of the path analyses revealed that internal member PDR strength moderates the relationship between the rule-breaking sub-facet and felt inauthenticity (B = .11, p < .05). Figure 6 presents the plot of this interaction, at conditional values of internal PDR strength and suggests that when accounting for internal PDR strength there is a positive relationship between the rule-breaking sub-facet of the tendency to adopt CDRs and felt inauthenticity, and that this relationship is stronger (weaker) when internal PDR strength is higher (lower). Additionally, the index of moderated-mediation effect of the rule- breaking sub-facet on emotional exhaustion via felt inauthenticity was significant (B = .029, p < .05). The conditional indirect effects at 1 SD above the mean (B = .046, p < .05) for internal PDR strength was significant while at 1 SD below the mean (B = -.017, p > .05) was not. The index of moderated-mediation effect of the rule-breaking sub-facet on job satisfaction via felt inauthenticity was also significant (B = -.026, p < .05). The conditional indirect effects at 1 SD 111 above the mean (B = -.040, p < .05) for internal PDR strength was significant while at 1 SD below the mean (B = .015, p > .05) was not. In sum, these results and interaction plots suggest that the (non-significant) positive relationship between CDR adoption and felt inauthenticity was indeed likely driven by the rule- breaking sub-facet. Further, we see from the conditional indirect effects that under conditions of strong PDRs this positive relationship can lead to higher emotional exhaustion and lower job satisfaction. Rule-breaking sub-facet of tendency to adopt CDRs and strength of PDRs for external organizational members. I next tested the full proposed moderated-mediation model using the rule-breaking sub-facet of tendency to adopt CDRs and strength of PDRs for external organizational members, while controlling for the control sub-facet, power, surface, and deep acting (see Tables 16 & 17). The model had satisfactory model fit (χ2 [df = 6, n = 569] = 7.15, CFI =.99, SRMR =.011). The results of the path analyses suggested that apart from two conditional indirect effects (see Table 17), all other direct, indirect, and moderated-mediated effects were non-significant. LPA Auxiliary Modeling I next modelled the proposed auxiliary variables i.e., the hypothesized mechanisms and outcomes of the proposed actor profile membership (Lanza et al., 2013) while accounting for the most-likely class membership and the classification error rate (Asparouhov & Muthén, 2014; Gabriel et al., 2018). As mentioned earlier, I conducted this analyses on the Study 2 field sample using the DCON command in Mplus (Asparouhov & Muthén, 2014; Lanza et al., 2013) which allows for comparisons between actor profiles on each of the modelled outcomes. Table 9 112 summarizes these results, highlighting the differences in the proposed outcomes across the five identified profiles. Starting with felt inauthenticity (n=589), Proactives experienced the least felt inauthenticity (M = 1.56, SE = .10), followed by Rule-Followers (M = 2.55, SE = .15), Passives (M = 2.69, SE = .08), and Reluctant Rule-Followers/Deviators (M = 2.82, SE = .07). All these profiles reported significantly less felt inauthenticity than Deviators (M = 3.45, SE = .29). There were no significant differences between the inauthenticity experienced by Passives, Rule- Followers, and Reluctant Rule-Followers/Deviators. This provides evidence for the negative relationship between tendencies to adopt CDRs and felt inauthenticity (supporting the results from the supplementary analyses regarding the control sub-facet). Additionally, these results suggest that those same tendencies to adopt CDRs in the context of weak PDRs (i.e., Proactives) result in the lowest felt inauthenticity (all profiles reported significantly more felt inauthenticity than Proactives) and having a high tendency to adopt CDRs in a strong PDR context (Deviators) can lead to the highest felt inauthenticity of all the proposed profiles. This seems to suggest that despite non-significant interactions in the proposed variable-centered path model, having a high tendency to adopt CDRs is likely dependent on PDR strength as is apparent by the significant differences in felt inauthenticity between Proactive and Deviators. This is likely due to the inability of Deviators to adequately claim agency over their emotional displays owing to the strong currents they face in the form of strong PDRs, that they experience a form of expectation violation (Pinquart et al., 2021) at not being able to adopt CDRs to the extent they would like that in turn makes them feel especially inauthentic. For ego depletion (n = 589), Reluctant Rule-Followers/Deviators (M = 3.41, SE = .09), Proactives (M = 3.29, SE = .12), and Deviators (M = 3.11, SE = .23) experienced similarly high 113 levels of ego depletion and were not significantly different from each other. Passives (M = 2.95, SE = .15) and Rule-Followers (M = 2.87, SE = .18) experienced lower ego depletion than the other three profiles and were not significantly different from each other. However, there was a significant difference between the ego depletion experienced by Passives and Reluctant Rule- Followers/Deviators (with Passives experiencing lower ego depletion), and there was a significant difference between the ego depletion experienced by Rule-Followers and Reluctant Rule-Followers/Deviators (with Rule-Followers experiencing lower ego depletion). These results suggest that having lower tendencies to adopt CDRs is less depleting (as is the case for Passives and Rule-Followers), irrespective of the strength of PDRs. For autonomy (n = 589), Proactives (M = 6.23, SE = .07) followed by Deviators (M = 5.63, SE = .16) experienced the highest autonomy, Passives (M = 5.10, SE = .09) and Reluctant Rule-Followers/Deviators (M = 5.15, SE = .07) experienced moderately high autonomy, while Rule-Followers (M = 4.65, SE = .20) experienced the lowest autonomy. There was no significant difference in the autonomy experienced by Passives and Reluctant Rule-Followers/Deviators. All other differences in autonomy across the five profiles were significant. These results suggest that high tendency to adopt CDRs is associated with feelings of higher autonomy (as is the case for Proactives and Deviators). However, having weaker PDRs imposed does lead to higher autonomy as is evident by Proactives experiencing higher autonomy than Deviators. Indeed, it is because of Proactives’ natural proclivity to claim agency in a work environment that already affords them significant freedom to decide what emotions to display, that likely causes them to experience the highest amount of autonomy. Not only do they not experience any coercion from their organization, they also maximize the autonomy they experience by consciously adopting CDRs at work. Further, having lower tendencies to adopt CDRs can lead to experiencing 114 moderately high autonomy as long as the prevailing PDRs are weak (as is the case for Passives). Passives, as mentioned above, prefer to not exercise their agency even with the freedom to do so. Therefore, Passives are likely to experience lower job autonomy as compared to Proactives and Deviators, both of whom proactively claim their autonomy whether their environments afford them that freedom or not. However, they will still experience higher levels of job autonomy than Reluctant Rule-Followers/Deviators and Rule-Followers who have a strong(er) preference to eschew adoption of CDRs. Indeed, Rule-Followers rigidly follow the strong PDRs they are required to, reducing the autonomy they experience. For social interaction quality (n = 586), Proactives (M = 5.48, SE = .17) reported the highest quality of social interactions, followed by Deviators (M = 5.01, SE = .15), Rule- Followers (M = 4.68, SE = .14), Reluctant Rule-Followers/Deviators (M = 4.36, SE = .06), and finally Passives (M = 4.13, SE = .07). All differences between profiles were significant except for between Rule-Followers and Deviators. These results suggest that a high tendency to adopt CDRs likely gives such individuals (Proactives and Deviators) more control over their social interactions thereby improving social interaction quality (which is line with the arguments laid out in the hypotheses development section). It is also not surprising to see Rule-Followers and Reluctant Rule-Followers/Deviators with moderately good quality of social interactions as research has suggested that when individuals follow PDRs it improves interpersonal indices such as customer interaction quality (Groth et al., 2009; Rafaeli, 1989). For emotional exhaustion (n = 547), there were largely no significant differences between profiles. Reluctant Rule-Followers/Deviators (M = 3.86, SE = .08) and Deviators (M = 3.83, SE = .25) experienced the highest emotional exhaustion, followed by Rule-Followers (M = 3.58, SE = .19), Passives (M = 3.43, SE = .14) and finally Proactives (M = 3.41, SE = .11). Passives and 115 Reluctant Rule-Followers/Deviators experienced significantly different levels of emotional exhaustion, and Rule-Followers and Reluctant Rule-Followers/Deviators experienced significantly different levels of emotional exhaustion. There were no significant differences between any other profiles. These results suggest that being a Reluctant Rule-Followers/Deviator or a Deviator (having moderate to high tendency to adopt CDRs while facing strong PDRs) is especially exhausting, and that they experience significantly more emotional exhaustion than individuals who face weak PDRs (Passives and Proactives). For job satisfaction (n = 542), Proactives (M = 6.86, SE = .08) experienced significantly higher job satisfaction than all the other actor profiles. Passives (M = 5.22, SE = .06), Rule- Followers (M = 5.25, SE = .13), and Deviators (M = 5.30, SE = .18) reported moderately high levels of job satisfaction and were not significantly different from each other. Reluctant Rule- Followers/Deviators (M = 4.99, SE = .06) reported the lowest job satisfaction, which was significantly different from the job satisfaction reported by Passives and Proactives. These results suggest that individuals with a high tendency to adopt CDRs who are given the freedom to do so are most satisfied (Proactives). Interestingly, Passives, Rule-Followers and Deviators all reported similar (moderately high) levels of job satisfaction, possibly pointing to differing reasons for feeling satisfied. For instance, Passives are likely satisfied with not being forced to take control of their emotional displays beyond the relatively weak requirements from their work; Rule-Followers are likely satisfied due to their attempts at achieving goals set for them at work (in terms of meeting emotional demands); Deviators are likely satisfied with attempting to claim agency over their emotional displays when faced with strong PDRs. Reluctant Rule- Followers/Deviators likely have the worst of all worlds with moderately high PDR strength and moderate tendencies to adopt CDRs, which likely do not give them the benefits accrued to either 116 Passives or Rule-Followers owing to the relatively lower need to claim agency over their displays (as compared to Deviators) and emotional demands that leave limited room open for them to do so (as compared to Rule-Followers). For task performance (n = 543), Proactives (M = 6.08, SE = .07) and Rule-Followers (M = 6.05, SE = .08) reported the highest levels of task performance, followed by Passives (M = 5.73, SE = .06) and Reluctant Rule-Followers/Deviators (M = 5.76, SE = .05), and finally Deviators (M = 4.98, SE = .26) with the lowest reported task performance. There were no significant differences between the task performance reported by Passives and Reluctant Rule- Followers/Deviators, and between Proactives and Rule-Followers. All other differences between profiles were significant. As has been mentioned, the findings regarding the effect of emotional labor on task performance is fairly mixed (Grandey & Gabriel, 2015). Researchers have suggested that these equivocal findings could be due to the potential “performance trade-offs from engaging in emotional labor” (Grandey & Gabriel, 2015, p. 339). The aforementioned trade-offs can be conceptualized in terms of the job demands placed on each actor profile and the resources available to them (Demerouti et al., 2001). These results further suggest that the mixed findings associated with the effects of emotional labor on performance are potentially due to the narrow focus of the extant literature on a single actor profile (i.e., Rule-Followers). The results of the auxiliary modeling suggest that Proactives reported the highest task performance likely due to the CDRs they adopt, with research showing that customers and coworkers are more satisfied when employees are more authentic with their emotional displays (Ashforth & Humphrey, 1993; Coté, 2005; Hennig-Thurau et al., 2006; Kammeyer‐Mueller et al., 2013). Therefore, even with the depletion of resources they experience due to their conscious emotional regulation, Proactives are likely to offset that resource depletion via resource gains 117 owing to better customer or coworker satisfaction, better performance evaluations owing to their proactivity, and the gains from increased autonomy and authenticity. Rule-Followers work in strong PDR contexts which implies that emotional displays are central to their roles or workplace interactions, and thus their task performance. Rule-Followers are likely to have higher customer satisfaction because they do not deviate from expected integrative display norms common to service interactions (Tan et al., 2004; Tsai, 2001). Similarly, they are also likely to receive higher performance ratings from supervisors for meeting organizationally mandated display requirements (Barger & Grandey, 2006; Tan et al., 2004). Therefore, even though they are likely to experience higher depletion of their resources (Goldberg & Grandey, 2007) owing to low autonomy and felt authenticity, they are likely to have better task performance than Deviators and Passives who either deviate from organizational norms, or do not put in the effort to go above and beyond what is expected of them. Even though Passives are not proactively adopting CDRs to best meet the requirements of their specific situation, they are meeting all the emotional display requirements of their job. They have ample attentional resources to dedicate to this rather minimal effort. They might be fairly dissatisfied with their job but do just enough to meet all the performance expectations the organization has of them. Deviators on the other hand constantly engage in a high-risk high-gain gambit with their adoption of contextual displays. While this strategy to adopt CDRs when faced with strong prescribed display rules has the potential to pay off with individual goal attainment, it is unlikely that the organization or management will take lightly to what they perceive as deviant behavior. Finally, the results suggest that Reluctant Rule- Followers/Deviators likely do not get the benefits accrued to Proactives and Rule-Followers in terms of better performance evaluations but neither do they risk the same level of backlash as Deviators. 118 GENERAL DISCUSSION This dissertation sought to highlight the underexamined impact of emotional display rule sources on important work and well-being related outcomes. Specifically, I theorized that individuals who adopt CDRs would experience lower felt inauthenticity and ego depletion and higher autonomy and social interaction quality, which in turn would reduce emotional exhaustion and improve job satisfaction and task performance. Additionally, I proposed that these relationships are contingent on the strength of PDRs with stronger PDRs dampening and weak PDRs strengthening these effects. Using two independent online samples, I developed and validated new measures capturing the two broad categories of display rule sources i.e., prescribed, and contextual emotional display rules. Next, using a large field sample, I adopted both variable-centered and person-centered approaches to examine the role played by display rule sources in the emotion regulation process. Specifically, I first tested a moderated-mediation path model to test my proposed relationships and then conducted a LPA wherein I generated qualitatively and quantitatively distinct actor profiles with the intention to highlight subpopulations that have so far been ignored by emotional labor scholars. Finally, I used another online sample of working professionals to replicate the actor profile structure. In this discussion section, I start with brief summary and highlights from my findings from both variable- and person-centered analyses, followed by a discussion of important insights gleaned from comparing the two sets of analyses, theoretical contributions, practical implications, limitations of this study, and finally future research directions. Summary and highlights of findings Scale development. The results of the scale validation supported a two-factor model for both new measures, i.e., PDR strength for internal and external organizational members and control 119 and rule-breaking sub-facets of the tendency to adopt CDRs. To test the hypothesized model in this dissertation I relied on the unidimensional version of the measures (which also had satisfactory validity and internal consistency). I also tested the proposed model using the bipartite versions of the measures as part of the supplementary analyses done for this dissertation (results discussed below). Variable-centered approach. The hypotheses from my proposed variable-centered model were largely unsupported. However, I did find initial (albeit limited) evidence pointing to the importance of accounting for adoption of CDRs. Specifically, results revealed that CDR adoption does give individuals a sense of autonomy which in turn can have benefits in the form of better task performance. Further, while the results contradicted the hypothesized relationship with felt inauthenticity, suggesting a positive relationship, they also suggested that under conditions of weak PDRs, individuals who adopt CDRs experienced lower emotional exhaustion and higher job satisfaction. The supplementary analyses conducted, discussed later, shed some additional light on this counterintuitive finding. Person-centered approach. The results of the LPA partially supported the proposed actor profile structure. The results across two studies revealed five profiles that varied in the level (quantitative differences—Deviators, Reluctant Rule-Followers/Deviators, and Passives) and shape (qualitative differences— Rule-Followers and Proactives) of the profile indicators. Supplementary Analyses. Despite the lack of support for my hypotheses, the results from the supplemental analyses on the control and rule-breaking subscales, LPA results, and especially the differences in the findings from the variable-centered and person-centered approaches do shed light on insights that might help explain some of the counterintuitive and null findings from the primary variable-centered model.. 120 First, I tested the proposed model using the bipartite versions of the newly developed measures. The results suggest that the control sub-facet of the tendency to adopt CDRs had significant positive indirect effect on job satisfaction and a significant negative indirect effect on emotional exhaustion, via felt inauthenticity. Further, the conditional indirect effects suggested that the benefits on taking control of one’s emotional displays were likely only be realized under conditions of weakly held PDRs. Interestingly, the control sub-facet had a negative significant relationship with felt inauthenticity while the rule-breaking sub facet had a positive non- significant with felt inauthenticity. These findings suggest that the counterintuitive results of testing Hypothesis 1a (regarding felt inauthenticity) could be being driven by the rule-breaking sub-facet which constituted the lion’s share of the items used for the composite measure. Indeed, the significant interaction between the rule-breaking sub-facet and internal member PDR strength is a near replication of the significant interaction between the two composite measures. Further, the control sub-facet had significant positive indirect effects on job satisfaction and task performance via autonomy. These results were generally in line with the proposed relationships for the tendency to adopt CDRs, suggesting that the rule-breaking sub-facet likely requires additional examination for contaminants and future researchers can look to explore more relationships using only the control sub-facet. Next, I modeled auxiliary variables as part of the extended LPA analyses to examine which mediating mechanisms and outcomes differed as a function of profile membership. These results were especially illuminating because even though I didn’t find general support for my hypotheses, the significant differences across outcomes based on profile membership may help gain insights into the unexpected and null findings from the path analyses. Before proceeding it is important to note that there were largely no significant differences in the ego depletion and 121 emotional exhaustion experienced by different actor profiles. The results suggested that Proactives experienced the least felt inauthenticity, highest quality of social interactions, autonomy, job satisfaction and task performance. This is very much in line with my proposed actor profile descriptions which suggested that Proactives would benefit from the freedom their environment gives them to enact their natural tendencies to adopt CDRs. The findings regarding Deviators on the other hand did not neatly align with my proposed actor profile description for them. Deviators experienced the highest felt inauthenticity and the lowest task performance, both of which were contrary to my proposed description. They did however experience the second highest autonomy and social interaction quality, which was in line with what I had expected. Passives, Rule-Followers and Deviators experienced similar levels of job satisfaction which was less than Proactives but more than Reluctant Rule-Followers/Deviators. Comparing the Proactives and Deviators reveals that strong PDRs likely hurt those characterized by a high tendency to adopt CDRs more than I had anticipated, both in terms of well-being and performance, likely due to the extreme person-environment mismatch experienced by Deviators. These results also give additional insight into the counterintuitive findings from the path analyses. Specifically, Deviators likely do not have much control afforded to them by their work environment and therefore are forced to break from prevailing strong PDRs, however that is unlikely to be a sustainable behavior given the environmental constraints, leading to even higher felt inauthenticity and worse wellbeing and performance outcomes. Rule-Followers experienced less inauthenticity than Reluctant Rule-Followers/Deviators and Deviators but more than Proactives (there was no difference between them and Passives). Rule-Followers also experience the lowest autonomy and the highest task performance. These findings are also in line with the proposed actor profile description for Rule-Followers, and are 122 also supported by the extant emotional labor literature that has focused on this subpopulation along with the Reluctant Rule-Followers/Deviators. The Reluctant Rule-Followers/Deviators consistently experience the worst outcomes of any profile. They had the second lowest social interaction quality, authenticity, and task performance and the lowest job satisfaction. This was the largest profile to emerge across both samples and is likely to experience the worst of all worlds. They do not get the autonomy advantages from being a very high CDR adopter nor the satisfaction and performance benefits of simply following PDRs. And it is also likely, given that they represented the majority of a fairly diverse, multinational sample, it is likely extant emotional labor scholars have been inadvertently oversampling this subpopulation which would potentially explain the harmful and/or mixed effects of emotion regulation. Finally, Passives had the third highest felt inauthenticity, autonomy, second lowest task performance and worst social interaction quality. They are also very satisfied with their work, second only to Proactives. They also experienced the lowest emotional exhaustion. These findings largely supported the proposed description of this profile. Passives do not feel the need to adopt CDRs and their environment does not ask them to, making them very satisfied with work. However, they do forego performance and social interaction benefits by choosing to not engage in much emotion regulation at all. Theoretical Implications By incorporating the interaction of the two different sources of emotional display rules (i.e., contextual, and prescribed display rules), this dissertation aimed to reconcile mixed findings in the emotion labor literature while simultaneously highlighting subpopulations of employees that have not been examined by emotion labor scholars (leading to a potentially skewed prevailing consensus on the effects of emotional labor). Despite the lack of support for my 123 proposed variable-centered model, this dissertation makes several important contributions to the emotional labor literature, especially when comparing the findings from the variable-centered and person-centered approaches. First, this dissertation establishes the importance of incorporating individuals who tend to rely on CDRs to guide their emotional displays at work, and clarifies and expands the definition of CDRs beyond that put forth by the limited research that has examined the source of emotional display rules (Diefendorff & Richard, 2008; Diefendorff & Greguras, 2009; Richard & Converse, 2016). The significant effect of the tendency to adopt CDRs on autonomy, marginally significant indirect effect on job satisfaction (via autonomy), and moderated mediation effects on emotional exhaustion and job satisfaction (via felt inauthenticity) indicate that adopting CDRs do indeed help explain variance in these outcomes over and above the ubiquitous emotion regulation strategies of surface and deep acting. Further, the development and validation of the measure for tendency to adopt CDRs revealed two sub-facets i.e., control and rule breaking. These sub-facets are in line with the proposed components of adopting CDRs which include claiming agency over their emotional displays (i.e., control) and deviating from prevailing PDRs (i.e., rule-breaking). Results suggested that the control sub-facet had a significant positive indirect effect on job satisfaction (via reduced felt inauthenticity and increased autonomy) and a significant negative indirect effect on emotional exhaustion (via reduced felt inauthenticity). The control sub-facet did not interact with PDR strength for either internal or external organizational members, possibly meaning that the control sub-facet is stable across interaction targets. The rule-breaking sub-facet on the other hand did interact with internal PDR strength to predict job satisfaction via felt inauthenticity, with the effect being significant under strong PDR conditions. PDR strength for external members also moderated the relationship between the rule-breaking 124 sub-facet and autonomy. Both these findings indicated that the tendency to deviate from PDRs (i.e., rule-breaking) had the counterintuitive effect of increasing felt inauthenticity, decreasing autonomy, and increasing emotional exhaustion. One possible explanation for these findings (and for the negative relationship between the unidimensional measure of adopting CDRs and felt inauthenticity) could be the expectation violation individuals with a high tendency to adopt CDRs experience when unable to (or experience resistance to) freely adopting CDRs (Pinquart et al., 2021). In sum, these findings from the proposed path model suggest that it is important to account for the tendency to adopt CDRs to gain a more nuanced understanding of the effect of emotion regulation on key outcomes, which so far have been solely attributed to the use of different emotion regulation strategies. Second, this dissertation added to the growing literature on the importance of accounting for differing PDR strength by developing a new (broader) measure and examining the moderating effect of differing PDR strength on the relationship between adopting CDRs and key outcomes. While the role of PDR strength became more apparent via the person-centered analyses, it was also a critical moderator of the relationship between CDR adoption and felt authenticity as evidenced by the findings of the path model. Additionally, the scale development process revealed that PDR strength for internal and external organizational members were related but distinct expectations held by organizations, further supporting research suggesting that there are differing emotional display expectations and reactions to varying targets at work (e.g., Diefendorff & Greguras, 2009). Third, this dissertation contributes to the young but growing body of work adopting person-centered approaches. Specifically, this is the second such examination of the emotion regulation process (other than Gabriel et al., 2015), and the first to account for emotional display 125 rule sources. The initial results of the LPA suggested the existence of five distinct actor profiles, four of which were proposed a priori (with the exception of reluctant Rule-Followers/Deviators, who formed the most common profile). Most notably, the results seem to suggest that Rule- Followers (the group of individuals most emotional labor scholars claim to study) and Reluctant Rule-Followers are likely driving some of the findings from extant emotional labor research, suppressing the differential experiences by some of the smaller sub-populations. Indeed, if researchers had spoken to a group of Proactives via a qualitative study, they might have developed theory about how emotional regulation is healthy and an asset for the individual and the organization, quite the departure from the prevailing consensus right now. It is likely that the group scholars have been studying is the reluctant Rule-Followers/Deviators who, were the most common profile (almost 45% of the population in both samples), and reported the highest emotional exhaustion, lowest job satisfaction but above average task performance, all of which is in line with existing findings (Grandey & Gabriel, 2015). On the other hand, scholars have not accounted for Proactives, Passives and Deviators, who comprise almost half the population, likely miscasting all these subpopulations as Rule-Followers or Reluctant Rule- Followers/Deviators. Therefore, this dissertation incorporates these smaller but not insignificant subpopulations into the emotional labor literature and highlights how profile membership differentially impacts key outcomes. Finally, this dissertation highlights the advantages of a person-centered approach over the traditional variable-centered approach by examining the differences in the findings of the two analyses. As already mentioned, a person-centered approach allows us to examine how profile membership differentially impacts key outcomes, and then compare those findings to those of the proposed path model. As is apparent from the largely unsupported hypotheses from the variable- 126 centered approach adopted in the first half of this dissertation, PDR strength did not moderate the relationship between CDR adoption and critical mechanisms and outcomes (with a few exceptions). Specifically, if I had relied solely on the variable-centered approach, I would have concluded that CDR adoption and PDR strength do not interact to affect outcomes of interest and at best, have mixed findings regarding direct effects. With a person-centered approach, this dissertation found evidence that suggested that there are distinct subpopulations of employees based on different constellations or combinations of CDR adoption and PDR strength, and these subpopulations significantly differ with regard to the outcomes of interest. For instance, while the path model indicated null findings regarding the effects of CDR adoption and PDR strength on social interaction quality, the LPA results suggest that Proactives and Deviators have significantly higher quality social interactions than the other three profiles. Without the person- centered approach I would have concluded that adopting CDRs has no effect on social interaction quality, in contrast, LPA results suggest that there are subpopulations (Proactives and Deviators) of employees who benefit greatly from adopting CDRs in the form of improved social interactions. Or looking at task performance, the path model suggests that adopting CDRs does not affect performance, however an examination of the LPA results suggests that this relationship is likely more complicated. The results suggest that Rule-Followers and Proactives reported the highest task performance while Deviators reported the lowest. This would point to the fact that individuals who do not deviate from organizational expectations (Rule-Followers) or have the freedom to adopt CDRs (Proactives) tend to perform better than those who do, especially when faced with strong PDRs (Deviators). Therefore, the CDR adoption and PDR strength interaction may not have found support via the variable-centered approach, but can still 127 provide useful information regarding smaller subpopulations that may not be adequately captured without a person-centered analyses. The LPA results can also help gain insight into the counterintuitive findings from the variable-centered analyses of this dissertation. For instance, the path model results suggest that a higher tendency to adopt CDRs tends to make such individuals experience higher felt inauthenticity. However, a closer examination of the differences in felt inauthenticity by profile membership indicates that that might not necessarily be the case as the subpopulation with the lowest felt inauthenticity (Proactives) also has a high tendency to adopt CDRs. It is then logical to assume that the primary reason for Deviators to report the highest and Proactives to report the lowest felt inauthenticity is that when faced with stronger PDRs Deviators are unable to adopt CDRs to the extent they would like to, causing an expectation violation and a form of dissonance that makes them feel especially inauthentic. Proactives on the other hand have the freedom to adopt the CDRs leading them to experience the least inauthenticity. Practical Implications Certain practical implications become apparent from the findings of this dissertation. In general, it may be beneficial for managers to intentionally and systematic manner think about how much leeway they are providing employees to express themselves emotionally at work. Specifically, my results suggest that many individuals prefer to choose their own emotional displays and that having very strict expectations of such individuals is likely to harm task performance, increase emotional exhaustion, and even increase feelings of inauthenticity. From a training and development perspective, depending on the different roles and their accompanying different PDR strengths, employees can be trained to either emphasize their CDR adoption tendencies for weak PDR contexts (Proactives exhibited the best outcomes of all the profiles) or 128 to learn to curtail those tendencies in strong PDR contexts. These sorts of emotional labor trainings are currently largely used to train individuals to follow prevailing PDRs (Hings et al., 2020; Mastracci et al., 2010; Shani et al., 2014), however I propose that such training programs can also be used to train individuals to discern contexts when they can and should not adopt CDRs. Lastly, if individuals belong to a subpopulation that experiences worse well-being (e.g., Deviators or Reluctant Rule-Followers/Deviators), managers may want to help cultivate a culture and environment that can help blunt some of the negative effects of belonging to certain problematic actor profiles on well-being indices. This could be done by either matching their tendencies to adopt CDRs with PDR contexts that would help them succeed and improve well- being (perhaps through a work rotation program to find the best “emotional fit”). For instance, if an individual with a high tendency to adopt CDRs is in a strong PDR context, they can be either given more control (by relaxing emotional display expectations) or be moved to a role where they can freely adopt the CDRs they deem fit. These factors could benefit employees who belong to a subpopulation that experiences a destructive combination of CDR adoption tendencies and PDR strength. Strengths, Limitations, and Future Research Directions This dissertation has several notable strengths such as contrasting traditional variable- centered analytical approaches to more novel person-centered approaches, collecting data across multiple samples including a large and diverse field sample collected across multiple time points, and using an additional online sample to replicate the actor profiles. That said, this dissertation also had a few limitations that in turn highlight fruitful directions for future research on emotional display rule sources. First, the data for Study 2’s field sample was collected from a single source and while “it is unlikely that profiles might be more or less likely to co-occur with 129 particular outcomes because of same source bias” (Gabriel et al., 2015, p. 877), future researchers should attempt to replicate these findings using other-reports (such as from managers, colleagues, clients, and team members). This is especially true for measures of task performance where self-ratings tend to be inflated (Kruger & Dunning, 1999). Second, it is possible to also model antecedents to profile membership as part of LPA which was beyond the scope of this dissertation. It would be interesting to assess individual differences such as self- monitoring, emotional intelligence or conscientiousness as antecedents given their relevance to following rules, understanding social context and relevance to the emotional regulation process. Third, while I controlled for both surface and deep acting in my path analyses, I did not include them as part of the LPA owing to sample size constraints. Future researchers could attempt to generate novel profiles that include all four indicators, potentially finding an overlap of the profiles generated in this dissertation and those generated by Gabriel et al. (2015). For instance, it is possible that Deviators who are also Deep Actors feel more authentic than Deviators who are Surface Actors. Lastly, this dissertation adopts a more static view of CDR adoption tendencies, while it is likely there is some within-person variation. Indeed, prior research has suggested that emotional labor is a dynamic process that can vary within person on a daily basis (e.g., Scott & Barnes, 2011). Future researchers could examine whether the actor profiles proposed in this dissertation demonstrate within-person variation over time, while exploring the situational and individual level factors that would affect such variation. 130 CONCLUSION The extant emotional labor literature has paid limited attention to emotional display rule sources. This dissertation attempted to use both variable-centered and person-centered analytical approaches to better understand how CDRs and PDRs interacted to affect key outcomes. I was able to demonstrate that (a) a tendency to adopt CDRs can be beneficial or harmful for wellbeing depending on the strength of prevailing PDRs, (b) five qualitatively and quantitatively distinct actor profiles exist, (c) latent profile membership differentiates across employee well-being and performance outcomes. Specifically, results showed that high tendency to adopt CDRs can be beneficial under conditions of weak PDRs (as for Proactives) whereas the same tendency can be harmful under conditions of strong PDRs (as for Deviators). Further, the subpopulation that emotional labor scholars have assumed to be studying may have been miscast as Rule-Followers when instead there are four other distinct subpopulations that have differing relationships with outcomes of interest. In sum, this dissertation adds to the growing body of scholarly work that demonstrates the benefits of adopting a person-centered approach to gain a more nuanced understanding of the emotion regulation process. 131 APPENDICES 132 APPENDIX A Tables and figures 133 Table 1 - Descriptive Statistics, Correlations, and Reliabilities for Sample 1 of Study 1. Variable Mean S.D. 1 2 3 4 5 6 7 8 9 10 11 12 1 TCDR 4.43 1.08 (.92) 2 TCDR-C 4.98 1.11 .63* (.81) 3 TCDR-R 4.21 1.22 .96* .41* (.93) 4 SPDR 4.29 1.28 .26* -.02 .30* (.93) 5 SPDR-I 4.23 1.39 .27* -.04 .33* .92* (.87) 6 SPDR-E 4.33 1.39 .22* .01 .25* .95* .77* (0.91) 7 Need for Ach. 3.25 1.02 .52* .37* .48* .36* .35* .33* (.71) 8 Internal LOC 4.68 .49 .57* .38* .55* .43* .41* .41* .61* (.85) 9 Pro. Per. 5.17 .99 .24* .45* .13* .22* .15* .25* .51* .46* (.89) 10 Dec. Auth. 5.09 1.19 .31* .37* .24* .03 .01 .05 .40* .29* .42* (.83) 11 Perf. Press. 4.58 1.24 .34* .13* .35* .44* .43* .40* .49* .40* .26* .08 (.82) 12 Role Ambiguity 4.68 .92 .02 .36* -.09 -.14* -.17* -.12* .19* .08 .48* .45* -.02 (.78) Notes. N = 259; reliabilities on diagonal; *p < .05. TCDR = Tendency to adopt CDRs; SPDR = Strength of PDRs; TCDR-C = Control sub-facet of TCDR; TCDR-R = Rule-breaking sub-facet of TCDR; SPDR-I = SPDR for internal members; SPDR-E = SPDR for external members; Ach. = Achievement; LOC = Locus of Control; Pro. Per. = Proactive Personality; Dec. Auth. = Decision Authority; Perf. Press. = Performance Pressure. 134 Table 2 - Descriptive Statistics, Correlations, and Reliabilities for Sample 2 of Study 1. Variable Mean S.D. 1 2 3 4 5 6 7 8 9 10 11 12 1 TCDR 4.43 1.15 (.91) 2 TCDR-C 5.21 1.15 .75* (.75) 3 TCDR-R 4.12 1.38 .97* .57* (.91) 4 SPDR 4.35 1.32 .43* .23* .45* (.93) 5 SPDR-I 4.26 1.42 .39* .14* .43* .88* (.88) 6 SPDR-E 4.44 1.39 .39* .26* .39* .94* .68* (.92) 7 Need for Ach. 3.22 .91 .55* .55* .49* .44* .35* .45* (.72) 8 Internal LOC 4.72 .41 .51* .36* .51* .42* .45* .34* .55* (.86) 9 Pro. Per. 5.17 .94 .29* .51* .18* .30* .20* .33* .56* .51* (.87) 10 Dec. Auth. 5.12 1.25 .32* .48* .22* .17* .11 .18* .44* .41* .60* (.82) 11 Perf. Press. 4.71 1.29 .38* .33* .35* .46* .46* .40* .50* .40* .41* .29* (.78) 12 Role Ambiguity 4.86 .88 -.26* .20* -.39* -.17* -.29* -.06 .05 -.20* .43* .33* -.07 (.86) Notes. N = 259; reliabilities on diagonal; *p < .05. TCDR = Tendency to adopt CDRs; SPDR = Strength of PDRs; TCDR-C = Control sub-facet of TCDR; TCDR-R = Rule-breaking sub-facet of TCDR; SPDR-I = SPDR for internal members; SPDR-E = SPDR for external members; Ach. = Achievement; LOC = Locus of Control; Pro. Per. = Proactive Personality; Dec. Auth. = Decision Authority; Perf. Press. = Performance Pressure. 135 Table 3 – Results of exploratory factor analysis for Strength of PDRs. Item External Internal 1. My organization has clear policies regarding the emotions I should and should not show. 0.82 2. I am clearly told what emotions are appropriate to show. 0.78 3. I am aware of my organization’s expectations regarding what emotions are appropriate to express. 0.39 4. My organization’s expectations about how to behave are formally stated in meetings or personnel briefings. 0.53 5. I was told which emotions are appropriate to show as part of the mentoring and coaching I get at work. 0.58 6. My supervisors have strong expectations of the types of emotions I show. 0.72 7. There is a lot of pressure from my organization to meet specific expectations in terms of the emotions I 0.71 show. 9. My organization has strict rules for which emotions to express. 0.71 12. I received guidance from others regarding how to behave and to express myself emotionally. 0.59 1. My organization has clear policies regarding the emotions I should and should not show. 0.72 2. I am clearly told what emotions are appropriate to show. 0.81 3. I am aware of my organization’s expectations regarding what emotions are appropriate to express. 0.78 4. My organization’s expectations about how to behave are formally stated in meetings or personnel briefings. 0.76 5. I was told which emotions are appropriate to show as part of the mentoring and coaching I get at work. 0.79 6. My supervisors have strong expectations of the types of emotions I show. 0.69 7. There is a lot of pressure from my organization to meet specific expectations in terms of the emotions I 0.75 show. 9. My organization has strict rules for which emotions to express. 0.65 12. I received guidance from others regarding how to behave and to express myself emotionally. 0.70 Note. N = 259. Retained items are in bold. 136 Table 4 – Results of exploratory factor analysis for Tendency to adopt CDRs. Rule- Item Control Breaking 1. I like to take control and decide for myself what is the most appropriate emotion to show. 0.74 2. I feel comfortable deciding the most appropriate emotion to show in any given situation. 0.48 5. If it helps me do my job more effectively, I will ignore my organization’s expectations regarding 0.81 what emotions I can show. 6. When organizational rules regarding the appropriate emotions to show interfere with my work, I 0.76 break those rules. 7. I like to be in charge of what emotions I show. 0.8 8. I feel comfortable disobeying my boss’s expectations of the appropriate emotions to. 0.81 9. I feel comfortable bending organizational rules regarding the appropriate emotions to so I can do 0.62 my work better. 10. I feel comfortable choosing the emotions to show even when my organization prefers that I not 0.45 show those emotions. 11. I take charge of what emotions to show if the emotions my organization wants me to show go 0.45 against my value system. 12. If it will help me achieve my work goals, I feel comfortable breaking from organizational norms 0.54 regarding the appropriate emotions to show. 14. I proactively take charge and choose the most appropriate emotion to show in any situation. 0.52 15. I ignore the expectations of my organization when they expect me to hide emotions that I believe 0.76 should be expressed to achieve my work goals 16. I choose what emotion to show, even if it hurts my performance at work. 0.78 17. I feel comfortable deciding what emotions to show, even if it may upset them. 0.44 18. I am comfortable showing anger if I believe they deserve it. 0.55 Note. N = 339. Retained items are in bold. 137 Table 4 (cont’d) Rule- Item Control Breaking 1. I like to take control and decide for myself what is the most appropriate emotion to show. 0.78 2. I feel comfortable deciding the most appropriate emotion to show in any given situation. 0.46 5. If it helps me do my job more effectively, I will ignore my organization’s expectations regarding 0.73 what emotions I can show. 6. When organizational rules regarding the appropriate emotions to show interfere with my work, I 0.81 break those rules. 7. I like to be in charge of what emotions I show. 0.78 8. I feel comfortable disobeying my boss’s expectations of the appropriate emotions to. 0.85 9. I feel comfortable bending organizational rules regarding the appropriate emotions to so I can do 0.61 my work better. 10. I feel comfortable choosing the emotions to show even when my organization prefers that I not 0.46 show those emotions. 11. I take charge of what emotions to show if the emotions my organization wants me to show go 0.47 against my value system. 12. If it will help me achieve my work goals, I feel comfortable breaking from organizational norms 0.61 regarding the appropriate emotions to show. 14. I proactively take charge and choose the most appropriate emotion to show in any situation. 0.5 15. I ignore the expectations of my organization when they expect me to hide emotions that I believe 0.73 should be expressed to achieve my work goals 16. I choose what emotion to show, even if it hurts my performance at work. 0.69 17. I feel comfortable deciding what emotions to show, even if it may upset them. 0.46 18. I am comfortable showing anger if I believe they deserve it. 0.58 Note. N = 339. Retained items are in bold. 138 Table 5 - Descriptive Statistics, Correlations, and Reliabilities For Study 2. Variable Mean S.D. 1 2 3 4 5 6 7 8 1 TCDR 3.95 0.90 (.88) 2 TCDR-C 5.39 1.01 .59* (.82) 3 TCDR-R 3.37 1.07 .95* .32* (.88) 4 SPDR 3.60 1.20 -.14* -.18* -.10* (.91) 5 SPDR-I 3.29 1.28 -.14* -.20* -.09* .87* (.81) 6 SPDR-E 3.85 1.35 -.15* -.15* -.12* .93* .64* (.89) 7 SA 2.89 1.34 .01 -.06 .02 .21* .21* .19* (.89) 8 DA 3.60 1.25 .07* .06 .06 .20* .17* .20* .26* (.73) 9 Power 3.85 1.40 .11* .06 .11* .15* .11* .16* -.02 .06 10 Status 5.36 0.88 .04 .16* -.01 .07 .04 .09* -.16* .05 11 FA 2.70 1.25 .02 -.16* .04 .10* .15* .05 .53* .06 12 ED 3.24 1.48 .03 -.08* .07 -.01 .02 -.05 .45* .03 13 Aut. 5.30 1.21 .19* .25* .13* -.16* -.19* -.12* -.22* -.03 14 SIQ 4.38 1.05 .06 .09* .03 .11* .01 .15* -.04 .14* 15 EE 3.67 1.36 -.01 -.07 .01 .09* .15* .03 .39* .05 16 JS 5.14 1.00 .05 .15* .01 -.05 -.08* -.01 -.40* -.02 17 TP 5.81 0.73 -.04 .18* -.12* -.03 -.07 .01 -.19* .01 Notes. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. TCDR-C = Control sub-facet of Tendency to adopt CDRs; TCDR-R = Rule-breaking sub-facet of Tendency to adopt CDRs; SPDR-I = Strength of PDRs for Internal members; SPDR-E = Strength of PDRs for External members; SA = Surface Acting; DA = Deep Acting; FA = Felt Inauthenticity; ED = Ego-Depletion; Aut. = Autonomy; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Reliabilities on diagonal; *p < .05 139 Table 5 (cont’d) Variable Mean S.D. 9 10 11 12 13 14 15 16 17 9 Power 3.85 1.40 (.91) 10 Status 5.36 0.88 .42* (.93) 11 FA 2.70 1.25 -.01 -.22* (.89) 12 ED 3.24 1.48 -.13* -.26* .57* (.92) 13 Aut. 5.30 1.21 .27* .29* -.32* -.31* (.89) 14 SIQ 4.38 1.05 .18* .39* -.35* -.27* .23* (.83) 15 EE 3.67 1.36 -.01 -.1* .58* .63* -.26* -.27* (.89) 16 JS 5.14 1.00 .14* .35* -.55* -.51* .33* .41* -.58* (.81) 17 TP 5.81 0.73 .06 .37* -.23* -.25* .21* .14* -.14* .34* (.81) Notes. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. FA = Felt Inauthenticity; ED = Ego-Depletion; Aut. = Autonomy; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Reliabilities on diagonal; *p < .05 140 Table 6 - Results of path analysis for Study 2. FA ED Aut. SIQ EE JS TP Predictors B (SE) B (SE) B (SE) B (SE) B (SE) B (SE) B (SE) Constant 1.44 2.45 4.81 3.75 1.63 4.91 5.44 TCDR -.02 (.05) .06 (.06) .18* (.05) .05 (.05) -.06 (.05) .03 (.03) -.07* (.03) SPDR -.01 (.04) -.12* (.05) -.13* (.04) .07 (.04) TCDR x SPDR .11* (.05) .02 (.05) -.05 (.04) -.07 (.04) FA .28* (.06) -.2* (.04) -.03 (.04) ED .39* (.04) -.14* (.03) -.05 (.03) Aut. -.03 (.04) .07 (.03) .08* (.03) SIQ -.09* (.04) .23* (.04) .04 (.03) SA .51* (.04) .54* (.04) -.16* (.04) -.06 (.03) .05 (.04) -.11* (.03) -.04 (.03) DA -.07* (.03) -.08 (.05) .01 (.04) .11* (.03) .01 (.03) .11 (.02) .02 (.02) Power .02 (.03) -.11* (.04) .23* (.03) .12* (.03) .09* (.03) .03 (.03) .00 (.02) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. Coefficients are unstandardized. SE = standard error. TCDR = Tendency to adopt CDRs; SPDR = Strength of PDRs; SA = Surface Acting; DA = Deep Acting; FA = Felt Inauthenticity; ED = Ego-Depletion; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. *p < .05. 141 Table 7 - Indirect effects, conditional indirect effects, and moderated mediation results for Study 2. Index of Moderated-Mediation Mediator DV Indirect Effect (95% CI; SE) Conditional Indirect Effect (95% CI; SE) (95% CI; SE) FA EE -.006 (-.038, .021; SE = .015) Low -.035* (-.071, -.003; SE = .017) .031* (.008, .056; SE = .012) High .022 (-.017, .060; SE = .020) FA JS .005 (-.016, .027; SE = .011) Low .025* (.002, .050; SE = .012) -.023* (-.041, -.006; SE = .009) High -.016 (-.045, .012; SE = .015) FA TP .001 (-.005, .007; SE = .003) Low .004 (-.006, .016; SE = .005) -.004 (-.015, .004; SE = .005) High -.003 (-.015, .004; SE = .005) ED EE .025 (-.029, .079; SE = .028) Low .017 (-.050, .083; SE = .034) .009 (-.036, .050; SE = .022) High .033 (-.035, .099; SE = .034) ED JS -.009 (-.030, .010; SE = .010) Low -.006 (-.032, .017; SE = .012) -.003 (-.018, .013; SE = .008) High -.011 (-.036, .012; SE = .012) ED TP -.003 (-.014, .004; SE = .005) Low -.002 (-.015, .007; SE = .005) -.001 (-.008, .006; SE = .003) High -.004 (-.018, .005; SE = .006) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. FA = Felt Inauthenticity; ED = Ego-Depletion; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Mediation and moderated-mediation is supported when the confidence interval excludes zero for 95% confidence intervals (CI). Unstandardized coefficients are reported with standard errors (SE). *p < .05. 142 Table 7 (cont’d) Index of Moderated-Mediation Mediator DV Indirect Effect (95% CI; SE) Conditional Indirect Effect (95% CI; SE) (95% CI; SE) Aut. EE -.005 (-.024, .011; SE = .009) Low -.006 (-.029, .014; SE = .011) .001 (-.004, .009; SE = .003) High -.004 (-.021, .009; SE = .007) Aut. JS .012 (.000, .029; SE = .008) Low .015 (-.001, .035; SE = .009) -.003 (-.012, .002; SE = .004) High .009 (-.001, .027; SE = .007) Aut. TP .016* (.004, .033; SE = .008) Low .020* (.006, .041; SE = .009) -.005 (-.015, .003; SE = .004) High .012 (.000, .030; SE = .008) SIQ EE -.005 (-.018, .005; SE = .006) Low -.011 (-.030, .002; SE = .008) .006 (-.002, .019; SE = .005) High .001 (-.013, .016; SE = .007) SIQ JS .013 (-.012, .037; SE = .012) Low .027 (-.002, .057; SE = .015) -.016 (-.036, .004; SE = .010) High -.002 (-.033, .030; SE = .016) SIQ TP .002 (-.003, .011; SE = .003) Low .005 (-.003, .018; SE = .005) -.003 (-.012, .002; SE = .003) High .000 (-.009, .007; SE = .004) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. Aut. = Autonomy; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Mediation and moderated-mediation is supported when the confidence interval excludes zero for 95% confidence intervals (CI). Unstandardized coefficients are reported with standard errors (SE). *p < .05. 143 Table 8 - Fit Statistics for Profile Structures in Study 2 and Study 3. No. of LMR BLTR Profiles LL FP AIC BIC SSA-BIC (p) (p) Entropy Study 1 2 -2142.489 7 4298.9780 4331.2150 4308.9880 0.0001 0.0000 0.507 3 -2138.708 10 4297.4150 4343.4680 4311.7150 0.0277 0.0800 0.649 4 -2133.661 13 4293.3220 4353.1910 4311.9110 0.0611 0.2500 0.554 5 -2121.821 16 4275.6410 4349.3260 4298.5210 0.0060 0.0000 0.623 6 -2120.388 19 4278.7750 4366.2760 4305.9440 0.5371 1.0000 0.579 7 -2119.623 22 4283.2460 4384.5620 4314.7040 0.5552 0.6667 0.613 Study 2 2 -1395.170 7 2804.3390 2832.7530 2810.5390 0.0002 0.0000 0.600 3 -1387.691 10 2795.3820 2835.9740 2804.2400 0.0018 0.0000 0.688 4 -1376.816 13 2779.6320 2832.4000 2791.1460 0.7349 0.0000 0.722 5 -1370.170 16 2772.3390 2837.2850 2786.5110 0.0394 0.0128 0.712 6 -1359.864 19 2757.7270 2834.8500 2774.5560 0.1122 0.0000 0.790 7 -1354.036 22 2752.0720 2841.3730 2771.5580 0.0538 0.0000 0.800 Note. LL = log-likelihood; FP = free parameters; AIC = Akaike information criteria; BIC = Bayesian information criteria; SSA–BIC = sample-size adjusted BIC; LMR = Lo, Mendell, and Rubin (2001) test; BLRT = bootstrapped log-likelihood ratio tests. 144 Table 9 – LPA Three-Step Results for Outcomes for Study 2. Outcome Pass (A) Rel (B) Rul (C) Pro (D) Dev (E) Chi square Mediators Felt Inauthenticity 2.69D,E 2.82D,E 2.55D,E 1.56A,B,C,E 3.45A,B,C,D 120.272*** Ego Depletion 2.95B 3.41A,C 2.87B 3.29 3.11 11.317* Autonomy 5.1C,D,E 5.15C,D,E 4.65A,B,D,E 6.23A,B,C,E 5.63A,B,C,D 155.725*** Social Interaction Quality 4.13B,C,D,E 4.36A,C,D,E 4.68A,B,D 5.48A,B,C,E 5.01A,B,C,D 74.233*** Outcomes Emotional Exhaustion 5.22B 4.99A,D 5.25 6.86B 5.3 359.161*** Job Satisfaction 5.73B,D 5.77A,D 6.05D 6.08A,B,C,E 4.99D 35.209*** Task Performance 3.43C,D,E 3.86C,D,E 3.58A,B,E 3.41A,B,E 3.83A,B,C,D 13.548** Note. All analyses were run utilizing the DCON procedure in Mplus. Values for each profile are means. Data were available for 589 participants for felt inauthenticity, 589 participants for ego depletion, 589 participants for autonomy, 586 participants for social interaction quality, 547 participants for emotional exhaustion, 542 participants for job satisfaction, and 543 participants for task performance. Subscripts indicate profiles that are significantly different at p < .05. Pass = Passives; Rel = Reluctant Rule-Followers/Deviators; Rule = Rule-Followers; Pro = Proactives; Dev = Deviators. ***p < .001; **p < .01; *p < .05 145 Table 10 - Results of supplementary path analysis using the control sub-facet of tendency to adopt CDRs and the internal sub-facet of strength of PDRs. FA ED Aut. SIQ EE JS TP Predictors B (SE) B (SE) B (SE) B (SE) B (SE) B (SE) B (SE) Constant 2.51 3.57 3.81 1.60 1.11 4.44 4.66 TCDR-C -.11* (.04) -.07 (.06) .23* (.05) .02 (.04) .02 (.04) .03 (.03) .07* (.03) SPDR-I .04 (.04) -.07 (.04) -.12* (.04) -.01 (.03) TCDR-C x SPDR-I .04 (.03) -.01 (.04) .02 (.04) -.05 (.03) FA .30* (.05) -.20* (.04) -.04 (.04) ED .39* (.05) -.13* (.03) -.04 (.03) Aut. -.05 (.04) .06 (.03) .03 (.03) SIQ -.13* (.05) .21* (.04) -.03 (.03) SA .47* (.04) .50* (.04) -.13* (.04) -.00 (.03) .06 (.04) -.09* (.03) -.02 (.03) DA -.07 (.04) -.08 (.05) .00 (.04) .10* (.03) .01 (.03) .01 (.03) .01 (.02) Status -.17* (.06) -.27* (.07) .34* (.06) .45* (.04) .20* (.06) .13* (.05) .27* (.05) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. Coefficients are unstandardized. SE = standard error. TCDR-C = Control sub-facet of TCDR; SPDR-I = SPDR for internal members; SA = Surface Acting; DA = Deep Acting; FA = Felt Inauthenticity; ED = Ego-Depletion; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. *p < .05. 146 Table 11 - Indirect effects, conditional indirect effects, and moderated mediation results for supplementary analysis using the control sub-facet of tendency to adopt CDRs and the internal sub-facet of strength of PDRs. Index of Moderated-Mediation Mediator DV Indirect Effect (95% CI; SE) Conditional Indirect Effect (95% CI; SE) (95% CI; SE) FA EE -.034* (-.067, -.006; SE = .016) Low -.047* (-.091, -.010; SE = .020) .013 (-.008, .034; SE = .010) High -.021 (-.058, .009; SE = .017) FA JS .022* (.004, .045; SE = .011) Low .031* (.007, .060; SE = .013) -.008 (-.022, .005; SE = .007) High .014 (-.006, .039; SE = .012) FA TP .005 (-.004, .015; SE = .004) Low .007 (-.005, .020; SE = .006) -.002 (-.007, .002; SE = .002) High .003 (-.003, .012; SE = .004) ED EE -.027 (-.076, .018; SE = .024) Low -.022 (-.087, .035; SE = .031) -.005 (-.039, .030; SE = .017) High -.032 (-.091, .020; SE = .028) ED JS .009 (-.006, .027; SE = .009) Low .008 (-.012, .030; SE = .011) .002 (-.010, .014; SE = .006) High .011 (-.007, .034; SE = .010) ED TP .003 (-.003, .013; SE = .004) Low .003 (-.005, .013; SE = .004) .001 (-.004, .006; SE = .002) High .004 (-.003, .015; SE = .005) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. FA = Felt Inauthenticity; ED = Ego-Depletion; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Mediation and moderated-mediation is supported when the confidence interval excludes zero for 95% confidence intervals (CI). Unstandardized coefficients are reported with standard errors (SE). *p < .05. 147 Table 11 (cont’d) Index of Moderated-Mediation Mediator DV Indirect Effect (95% CI; SE) Conditional Indirect Effect (95% CI; SE) (95% CI; SE) Aut. EE -.011 (-.031, .009; SE = .010) Low -.010 (-.031, .007; SE = .010) -.001 (-.007, .004; SE = .003) High -.012 (-.035, .009; SE = .011) Aut. JS .014 (-.001, .032; SE = .008) Low .012 (-.001, .030; SE = .008) .001 (-.004, .009; SE = .003) High .015 (-.001, .038; SE = .010) Aut. TP .006 (-.007, .020; SE = .007) Low .005 (-.006, .019; SE = .006) .001 (-.002, .005; SE = .002) High .007 (-.007, .023; SE = .008) SIQ EE -.002 (-.014, .009; SE = .006) Low -.009 (-.026, .005; SE = .008) .007 (-.002, .018; SE = .005) High .005 (-.009, .021; SE = .007) SIQ JS .003 (-.013, .020; SE = .008) Low .014 (-.007, .038; SE = .011) -.010 (-.025, .003; SE = .007) High -.007 (-.029, .013; SE = .011) SIQ TP .000 (-.005, .003; SE = .002) Low -.002 (-.010, .003; SE = .003) .001 (-.002, .007; SE = .002) High .005 (-.004, .007; SE = .007) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. Aut. = Autonomy; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Mediation and moderated-mediation is supported when the confidence interval excludes zero for 95% confidence intervals (CI). Unstandardized coefficients are reported with standard errors (SE). *p < .05. 148 Table 12 - Results of supplementary path analysis using the control sub-facet of tendency to adopt CDRs and the external sub-facet of strength of PDRs. FA ED Aut. SIQ EE JS TP Predictors B (SE) B (SE) B (SE) B (SE) B (SE) B (SE) B (SE) Constant 2.33 3.32 3.88 1.89 1.09 4.37 4.59 TCDR-C -.14* (.04) -.09 (.06) .25* (.05) .04 (.04) .02 (.05) .03 (.03) .08* (.03) SPDR-E -.05 (.03) -15* (.04) -.07* (.04) .09* (.03) TCDR-C x SPDR-E .05 (.03) .00 (.04) .03 (.03) -.05 (.03) FA .30* (.05) -.19* (.04) -.04 (.04) ED .39* (.05) -.13* (.03) -.04 (.03) Aut. -.05 (.04) .06 (.03) .03 (.03) SIQ -.13* (.05) .21* (.04) -.02 (.03) SA .48* (.04) .52* (.04) -.14* (.04) -.03 (.03) .06 (.04) -.09* (.03) -.02 (.03) DA -.05 (.03) -.06 (.04) -.01 (.04) .08* (.03) .01 (.04) .01 (.03) .01 (.02) Status -.16* (.06) -.25* (.07) .34* (.06) .43* (.05) .20* (.05) .13* (.05) .26* (.05) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. Coefficients are unstandardized. SE = standard error. TCDR-C = Control sub-facet of TCDR; SPDR-E = SPDR for external members; SA = Surface Acting; DA = Deep Acting; FA = Felt Inauthenticity; ED = Ego-Depletion; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. *p < .05. 149 Table 13 - Indirect effects, conditional indirect effects, and moderated mediation results for supplementary analysis using the control sub-facet of tendency to adopt CDRs and the external sub-facet of strength of PDRs. Index of Moderated-Mediation Mediator DV Indirect Effect (95% CI; SE) Conditional Indirect Effect (95% CI; SE) (95% CI; SE) FA EE -.042* (-.076, -.014; SE = .016) Low -.057* (-.102, -.019; SE = .021) .015 (-.004, .036; SE = .010) High -.027 (-.064, .003; SE = .017) FA JS .027* (.009, .049; SE = .011) Low .037* (.012, .067; SE = .014) -.010 (-.023, .003; SE = .007) High .017 (-.002, .041; SE = .011) FA TP .005 (-.005, .016; SE = .005) Low .007 (-.007, .021; SE = .007) -.002 (-.007, .002; SE = .002) High .003 (-.004, .013; SE = .004) ED EE -.036 (-.087, .010; SE = .024) Low -.037 (-.104, .023; SE = .032) .002 (-.033, .035; SE = .017) High -.034 (-.093, .019; SE = .028) ED JS .012 (-.003, .031; SE = .009) Low .013 (-.007, .037; SE = .011) -.001 (-.012, .012; SE = .006) High .012 (-.006, .033; SE = .010) ED TP .004 (-.002, .014; SE = .004) Low .004 (-.003, .016; SE = .005) .000 (-.005, .005; SE = .002) High .004 (-.003, .015; SE = .005) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. FA = Felt Inauthenticity; ED = Ego-Depletion; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Mediation and moderated-mediation is supported when the confidence interval excludes zero for 95% confidence intervals (CI). Unstandardized coefficients are reported with standard errors (SE). *p < .05. 150 Table 13 (cont’d) Index of Moderated-Mediation Mediator DV Indirect Effect (95% CI; SE) Conditional Indirect Effect (95% CI; SE) (95% CI; SE) Aut. EE -.012 (-.034, .010; SE = .011) Low -.010 (-.032, .009; SE = .010) -.002 (-.008, .003; SE = .003) High -.013 (-.039, .012; SE = .013) Aut. JS .016 (.000, .036; SE = .009) Low .014 (.000, .033; SE = .008) .002 (-.003, .009; SE = .003) High .018 (.000, .042; SE = .011) Aut. TP .007 (-.006, .023; SE = .007) Low .006 (-.006, .020; SE = .007) .001 (-.002, .005; SE = .002) High .008 (-.007, .026; SE = .008) SIQ EE -.006 (-.019, .005; SE = .006) Low -.012 (-.031, .001; SE = .008) .007 (-.001, .017; SE = .005) High .001 (-.013, .015; SE = .007) SIQ JS .009 (-.008, .028; SE = .009) Low .020 (-.001, .046; SE = .012) -.011 (-.025, .001; SE = .007) High -.001 (-.023, .020; SE = .011) SIQ TP -.001 (-.007, .003; SE = .002) Low -.002 (-.011, .005; SE = .004) .001 (-.003, .006; SE = .002) High .000 (-.004, .004; SE = .002) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. Aut. = Autonomy; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Mediation and moderated-mediation is supported when the confidence interval excludes zero for 95% confidence intervals (CI). Unstandardized coefficients are reported with standard errors (SE). *p < .05. 151 Table 14 - Results of supplementary path analysis using the rule-breaking sub-facet of tendency to adopt CDRs and the internal sub- facet of strength of PDRs. FA ED Aut. SIQ EE JS TP Predictors B (SE) B (SE) B (SE) B (SE) B (SE) B (SE) B (SE) Constant 1.58 2.63 4.76 3.57 1.61 4.89 5.38 TCDR-R .05 (.04) .12* (.05) .08 (.04) .00 (.04) -.07 (.04) .01 (.03) -.11* (.03) SPDR-I .06 (.03) -.04 (.04) -.16* (.04) -.02 (.03) TCDR-R x SPDR-I .11* (.03) .03 (.04) -.07* (.03) -.06 (.03) FA .28* (.05) -.20* (.04) -.03 (.04) ED .40* (.04) -.14* (.03) -.04 (.03) Aut. -.03 (.04) .07* (.03) .09* (.03) SIQ -.09* (.04) .23* (.04) .05 (.03) SA .48* (.04) .52* (.04) -.16* (.04) -.05 (.03) .05 (.04) -.11* (.03) -.05 (.03) DA -.08* (.03) -.10* (.04) .01 (.04) .12* (.03) .01 (.03) .01 (.03) .03 (.02) Power .01 (.03) -.13* (.04) .23* (.04) .13* (.03) .09* (.03) .03 (.03) .00 (.02) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. Coefficients are unstandardized. SE = standard error. TCDR-R = Rule-breaking sub-facet of TCDR; SPDR-I = SPDR for internal members; SA = Surface Acting; DA = Deep Acting; FA = Felt Inauthenticity; ED = Ego-Depletion; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. *p < .05. 152 Table 15 - Indirect effects, conditional indirect effects, and moderated mediation results for supplementary analysis using the rule- breaking sub-facet of tendency to adopt CDRs and the internal sub-facet of strength of PDRs. Index of Moderated-Mediation Mediator DV Indirect Effect (95% CI; SE) Conditional Indirect Effect (95% CI; SE) (95% CI; SE) FA EE .014 (-.010, .040; SE = .013) Low -.017 (-.045, .008; SE = .013) .029* (.011, .051; SE = .010) High .046* (.011, .086; SE = .019) FA JS -.010 (-.030, .007; SE = .009) Low .012 (-.006, .032; SE = .009) -.021* (-.036, -.007; SE = .007) High -.033* (-.063, -.007; SE = .014) FA TP -.002 (-.009, .003; SE = .003) Low .002 (-.003, .010; SE = .003) -.003 (-.013, .005; SE = .004) High -.005 (-.022, .007; SE = .007) ED EE .048* (.004, .097; SE = .024) Low .037 (-.017, .093; SE = .028) .011 (-.022, .042; SE = .016) High .060 (.001, .121; SE = .031) ED JS -.016 (-.035, -.001; SE = .009) Low -.013 (-.034, .006; SE = .010) -.004 (-.015, .008; SE = .006) High -.020 (-.044, .000; SE = .011) ED TP -.006 (-.017, .002; SE = .005) Low -.004 (-.016, .003; SE = .005) -.001 (-.007, .003; SE = .002) High -.007 (-.021, .002; SE = .006) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. FA = Felt Inauthenticity; ED = Ego-Depletion; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Mediation and moderated-mediation is supported when the confidence interval excludes zero for 95% confidence intervals (CI). Unstandardized coefficients are reported with standard errors (SE). *p < .05. 153 Table 15 (cont’d) Index of Moderated-Mediation Mediator DV Indirect Effect (95% CI; SE) Conditional Indirect Effect (95% CI; SE) (95% CI; SE) Aut. EE -.002 (-.012, .005; SE = .004) Low -.005 (-.021, .009; SE = .007) .002 (-.005, .011; SE = .004) High .000 (-.007, .008; SE = .003) Aut. JS .005 (-.001, .015; SE = .004) Low .011 (.000, .025; SE = .006) -.005 (-.014, .000; SE = .004) High .000 (-.011, .010; SE = .005) Aut. TP .007 (-.001, .017; SE = .005) Low .015* (.004, .030; SE = .007) -.007 (-.016, -.001; SE = .004) High .000 (-.014, .012; SE = .006) SIQ EE .000 (-.009, .010; SE = .004) Low -.005 (-.018, .005; SE = .006) .005 (-.001, .015; SE = .004) High .005 (-.005, .021; SE = .007) SIQ JS .000 (-.021, .019; SE = .010) Low .014 (-.011, .037; SE = .012) -.013 (-.029, .002; SE = .008) High -.013 (-.042, .012; SE = .014) SIQ TP .000 (-.006, .005; SE = .003) Low .003 (-.003, .012; SE = .004) -.003 (-.010, .001; SE = .003) High .000 (-.014, .003; SE = .004) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. Aut. = Autonomy; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Mediation and moderated-mediation is supported when the confidence interval excludes zero for 95% confidence intervals (CI). Unstandardized coefficients are reported with standard errors (SE). *p < .05. 154 Table 16 - Results of supplementary path analysis using the rule-breaking sub-facet of tendency to adopt CDRs and the external sub- facet of strength of PDRs. FA ED Aut. SIQ EE JS TP Predictors B (SE) B (SE) B (SE) B (SE) B (SE) B (SE) B (SE) Constant 1.41 2.42 4.81 3.81 1.62 4.82 5.32 TCDR-R .02 (.04) .09 (.05) .08 (.04) .02 (.04) -.07 (.04) .02 (.03) -.09* (.03) SPDR-E -.04 (.04) -.13* (.04) -.11* (.04) .09* (.03) TCDR-R x SPDR-E .06 (.03) .01 (.04) -.05 (.03) -.03 (.03) FA .28* (.05) -.19* (.04) -.02 (.04) ED .40* (.04) -.13* (.03) -.04 (.03) Aut. -.03 (.04) .07* (.03) .09* (.03) SIQ -.09* (.05) .24* (.04) .05 (.03) SA .51* (.04) .54* (.04) -.18* (.04) -.08* (.03) .05 (.04) -.11* .03 -.05 (.03) DA -.07* (.03) -.08 (.05) .01 (.04) .10* (.03) .01 (.03) .01 (.03) .03 (.02) Power .02 (.03) -.11* (.04) .24* (.03) .11* (.03) .09* (.03) .02 (.02) -.00 (.02) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. Coefficients are unstandardized. SE = standard error. TCDR-R = Rule-breaking sub-facet of TCDR; SPDR-E = SPDR for external members; SA = Surface Acting; DA = Deep Acting; FA = Felt Inauthenticity; ED = Ego-Depletion; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. *p < .05. 155 Table 17 - Indirect effects, conditional indirect effects, and moderated mediation results for supplementary analysis using the rule- breaking sub-facet of tendency to adopt CDRs and the external sub-facet of strength of PDRs. Index of Moderated-Mediation Mediator DV Indirect Effect (95% CI; SE) Conditional Indirect Effect (95% CI; SE) (95% CI; SE) FA EE .005 (-.021, .032; SE = .013) Low -.013 (-.043, .016; SE = .015) .017 (-.001, .036; SE = .009) High .024 (-.012, .061; SE = .018) FA JS -.004 (-.023, .014; SE = .009) Low .009 (-.011, .029; SE = .010) -.012 (-.026, .001; SE = .007) High -.017 (-.044, .008; SE = .013) FA TP .000 (-.006, .003; SE = .002) Low .001 (-.004, .008; SE = .003) -.001 (-.008, .003; SE = .003) High -.002 (-.013, .005; SE = .004) ED EE .036 (-.008, .083; SE = .023) Low .033 (-.023, .094; SE = .030) .003 (-.033, .034; SE = .017) High .039 (-.018, .096; SE = .029) ED JS -.012 (-.031, .003; SE = .008) Low -.011 (-.035, .007; SE = .011) -.001 (-.012, .012; SE = .006) High -.013 (-.035, .006; SE = .010) ED TP -.004 (-.014, .002; SE = .004) Low -.004 (-.016, .003; SE = .005) .000 (-.005, .005; SE = .002) High -.004 (-.017, .003; SE = .005) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. FA = Felt Inauthenticity; ED = Ego-Depletion; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Mediation and moderated-mediation is supported when the confidence interval excludes zero for 95% confidence intervals (CI). Unstandardized coefficients are reported with standard errors (SE). *p < .05. 156 Table 17 (cont’d) Index of Moderated-Mediation Mediator DV Indirect Effect (95% CI; SE) Conditional Indirect Effect (95% CI; SE) (95% CI; SE) Aut. EE -.002 (-.013, .005; SE = .004) Low -.004 (-.019, .007; SE = .006) .001 (-.003, .007; SE = .003) High -.001 (-.010, .005; SE = .004) Aut. JS .006 (-.001, .017; SE = .005) Low .010* (.000, .023; SE = .006) -.003 (-.010, .001; SE = .003) High .002 (-.007, .014; SE = .005) Aut. TP .008 (-.001, .019; SE = .005) Low .013* (.002, .026; SE = .006) -.004 (-.012, .001; SE = .003) High .003 (-.009, .016; SE = .006) SIQ EE -.002 (-.012, .007; SE = .005) Low -.005 (-.017, .006; SE = .006) .003 (-.004, .010; SE = .003) High .001 (-.011, .013; SE = .005) SIQ JS .005 (-.016, .026; SE = .011) Low .012 (-.014, .037; SE = .013) -.007 (-.021, .009; SE = .008) High -.002 (-.027, .024; SE = .013) SIQ TP .001 (-.004, .008; SE = .003) Low .003 (-.004, .012; SE = .004) -.002 (-.007, .002; SE = .002) High .000 (-.008, .007; SE = .003) Note. Time-1 N = 739; Time-2 N = 598; Time-3 N = 554. Aut. = Autonomy; SIQ = Social Interaction Quality; EE = Emotional Exhaustion; JS = Job Satisfaction; TP = Task Performance. Mediation and moderated-mediation is supported when the confidence interval excludes zero for 95% confidence intervals (CI). Unstandardized coefficients are reported with standard errors (SE). *p < .05. 157 Figure 1 - Hypothetical display rule profiles. 158 Figure 2 - Proposed model path diagram. 159 Figure 3 - Interaction Between Tendency to adopt CDRs and PDR strength predicting felt Inauthenticity. 160 Figure 4 - Latent profiles for emotional display rule based actors in Study 2. 6 5 4 3 2 1 0 Passives Reluctant Rule- Rule-Followers Proactives Deviators Followers /Deviators Tendency to adopt CDRs PDR Strength 161 Figure 5 - Latent profiles for emotional display rule based in Study 3. 6 5 4 3 2 1 0 Passives Reluctant Rule- Rule-Followers Proactives Deviators Followers /Deviators Tendency to adopt CDRs PDR Strength 162 Figure 6 - Interaction between rule-breaking sub-facet of tendency to adopt CDRs and internal PDR strength predicting felt inauthenticity. 5 4.5 4 Felt Inauthenticity 3.5 Weak Internal PDR Strength 3 2.5 Strong Internal PDR Strength 2 1.5 1 Low Rule-breaking sub-facet High Rule-breaking sub-facet of TCDRs of TCDRs 163 APPENDIX B Measures 164 Strength of Prescribed Display Rules Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions (internal): The questions below ask about the policies, norms, and procedures your organization may have with respect to the emotions you should show when interacting with “internal people” at work. By “internal people,” we mean anyone who you interact with as part of your work and who works for your organization, such as supervisors, coworkers, team members, and/or subordinates.” While some organizations may have strong explicit/overt or implicit/unwritten guidelines on the types of emotions their employees should show toward other internal people, other organizations may not have any guidelines at all, with their employees free to choose the emotions they want to show to others. When interacting with “internal people” at work (i.e., coworkers, bosses, subordinates, and/or team members)… 165 Strength of Prescribed Display Rules (cont’d) Instructions (external): The questions below ask about the policies, norms, and procedures your organization may have with respect to the emotions you should show when interacting with “external people” at work. By “external people,” we mean anyone you interact with as part of your work but who does NOT work for your organization, such as customers, vendors, clients, and parents/students (if you are a teacher). While some organizations may have strong explicit/overt or implicit/unwritten guidelines on the types of emotions their employees should show toward outsiders, other organizations may not have any guidelines at all, with their employees free to choose the emotions they want to express. When interacting with “external people” as part of my work (i.e., customers, vendors, clients, etc.)… 1. My organization has clear policies regarding the emotions I should and should not show. 2. I am clearly told what emotions are appropriate to show. 3. I am aware of my organization’s expectations regarding what emotions are appropriate to express. 4. My organization’s expectations about how to behave are formally stated in meetings or personnel briefings. 5. I was told which emotions are appropriate to show as part of my training at work. 6. My supervisors have strong expectations of the types of emotions I show . 7. There is a lot of pressure from my organization to meet specific expectations in terms of the emotions I show. 8. I am free to show any emotion I want. (R) 9. My organization has strict rules for which emotions to express. 10. My work environment is one in which people can freely chose which emotions to show. (R) 11. I get to decide what emotions to show. (R) 12. I received training regarding how to behave and to express myself emotionally. 166 Tendency to Adopt Contextual Display Rules Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions (internal): The questions below ask about the policies, norms, and procedures your organization may have with respect to the emotions you should show when interacting with “internal people” at work. By “internal people,” we mean anyone who you interact with as part of your work and who works for your organization, such as supervisors, coworkers, team members, and/or subordinates.” While some organizations may have strong explicit/overt or implicit/unwritten guidelines on the types of emotions their employees should show toward other internal people, other organizations may not have any guidelines at all, with their employees free to choose the emotions they want to show to others. When interacting with “internal people” at work (i.e., coworkers, bosses, subordinates, and/or team members)… Instructions (external): The questions below ask about the policies, norms, and procedures your organization may have with respect to the emotions you should show when interacting with “external people” at work. By “external people,” we mean anyone you interact with as part of your work but who does NOT work for your organization, such as customers, vendors, clients, and parents/students (if you are a teacher). While some organizations may have strong explicit/overt or implicit/unwritten guidelines on the types of emotions their employees should show toward outsiders, other organizations may not have any guidelines at all, with their employees free to choose the emotions they want to express. When interacting with “external people” as part of my work (i.e., customers, vendors, clients, etc.)… 167 Tendency to Adopt Contextual Display Rules (cont’d) 1. I like to take control and decide for myself what is the most appropriate emotion to show. 2. I feel comfortable deciding the most appropriate emotion to show in any given situation. 3. I prefer to let my organization decide which emotions I should show, even if they give me the freedom to decide for myself. (R) 4. I like to meet the expectations my organization has of me in terms of the appropriate emotions to show, even if I disagree with those expectations. (R) 5. If it helps me do my job more effectively, I will ignore my organization’s expectations regarding what emotions I can show,. 6. When organizational rules regarding the appropriate emotions to show interfere with my work, I break those rules. 7. I like to be in charge of what emotions I show. 8. I feel comfortable disobeying my boss’s expectations of the appropriate emotions to. 9. I feel comfortable bending organizational rules regarding the appropriate emotions to so I can do my work better. 10. I feel comfortable choosing the emotions to show even when my organization prefers that I not show those emotions. 11. I take charge of what emotions to show if the emotions my organization wants me to show go against my value system. 12. If it will help me achieve my work goals, I feel comfortable breaking from organizational norms regarding the appropriate emotions to show. 13. I would rather have my boss tell me which emotions are appropriate to show than decide for myself. (R) 14. I proactively take charge and choose the most appropriate emotion to show in any situation. 15. I ignore the expectations of my organization when they expect me to hide emotions that I believe should be expressed to achieve my work goals 16. I choose what emotion to show, even if it hurts my performance at work. 17. I feel comfortable deciding what emotions to show, even if it may upset them. 18. I am comfortable showing anger if I believe they deserve it. 168 Decision Authority All items were taken from the Decision Authority measure reported in Karasek Jr (1979) and use the instructions and scale anchors below: Source: Karasek Jr, R. A. (1979). Job demands, job decision latitude, and mental strain: Implications for job redesign. Administrative science quarterly, 285-308. Scale Anchors: 1 = to an extremely large extent, 2 = to a very large extent, 3 = to a large extent, 4 = to a moderate extent, 5 = to a small extent, 6 = to a very small extent, 7 = to an extremely small extent Instructions: Please indicate the extent that you agree with each of the following statements below. 1. To what extent do you have the freedom to decide how to organize your work. 2. To what extent do you have control over what happens on your job? 3. To what extent does your job allow you to make a lot of your own decisions? 4. To what extent are you assisted in making your own decisions? 169 Performance Pressure All items were taken from the Performance Pressure measure reported in Mitchell et al. (2018) and use the instructions and scale anchors below: Source: Mitchell, M. S., Baer, M. D., Ambrose, M. L., Folger, R., & Palmer, N. F. (2018). Cheating under pressure: A self-protection model of workplace cheating behavior. Journal of Applied Psychology, 103(1), 54. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. The pressure for performance in my workplace is high. 2. I feel tremendous pressure to produce results. 3. If I don’t produce at high levels, my job will be at risk. 4. I would characterize my workplace as a results-driven environment. 170 Role Ambiguity All items were taken from the Role Ambiguity measure reported in House et al. (1983) and use the instructions and scale anchors below: Source: House, R. J., Schuler, R. S., & Levanoni, E. (1983). Role conflict and ambiguity scales: Reality or artifacts? Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. My authority matches the responsibilities assigned to me. 2. I don't know what is expected of me. 3. My responsibilities are clearly denned. 4. I feel certain about how much authority I have. 5. I know what my responsibilities are. 6. I have clear planned goals and objectives for my job. 7. The planned goals and objectives are not clear. 8. I don't know how I will be evaluated for a raise or promotion. 9. I don't know how to develop my capabilities for future success in my job. 10. I often have unclear orders from my boss. 11. I know exactly what is expected of me. 12. I work under unclear policies and guidelines. 13. Explanations are clear of what has to be done. 14. I don't know what are the opportunities for advancement and promotion. 15. I don't know how to improve my performance on the job. 16. My boss makes it clear how he will evaluate my performance. 171 Need for Achievement All items were taken from the Need for Achievement measure reported in Steers and Braunstein (1976) and use the instructions and scale anchors below: Source: R. M., & Braunstein, D. N. (1976). A behaviorally-based measure of manifest needs in work settings. Journal of vocational behavior, 9(2), 251-266. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. I do my best work when my job assignments are fairly difficult. 2. I try very hard to improve on my past performance at work. 3. I take moderate risks and stick my neck out to get ahead at work. 4. I try to avoid any added responsibilities on my job. 5. I try to perform better than my co-workers. 172 Work Locus of Control All items were taken from the Work Locus of Control measure reported in Spector (1988) and use the instructions and scale anchors below: Source: Steers, R. M., & Braunstein, D. N. (1976). A behaviorally-based measure of manifest needs in work settings. Journal of vocational behavior, 9(2), 251-266. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. A job is what you make of it. 2. On most jobs, people can pretty much accomplish whatever they set out to accomplish. 3. If you know what you want out of a job, you can find a job that gives it to you. 4. If employees are unhappy with a decision made by their boss, they should do something about it. 5. Getting the job you want is mostly a matter of luck. 6. Making money is primarily a matter of good fortune. 7. Most people are capable of doing their jobs well if they make the effort. 8. In order to get a really good job you need to have family members or friends in high places. 9. Promotions are usually a matter of good fortune. 10. When it comes to landing a really good job, who you know is more important than what you know. 11. Promotions are given to employees who perform well on the job. 12. To make a lot of money you have to know the right people. 13. It takes a lot of luck to be an outstanding employee on most jobs. 14. People who perform their jobs well generally get rewarded for it. 15. Most employees have more influence on their supervisors than they think they do. 16. The main difference between people who make a lot of money and people who make a little money is luck. 173 Proactive Personality All items were taken from the shortened Proactive Personality measure reported in Seibert et al. (1999), based on the original measure by Bateman and Crant (1993) and use the instructions and scale anchors below: Source: Seibert, S. E., Crant, J. M., & Kraimer, M. L. (1999). Proactive personality and career success. Journal of Applied Psychology, 84(3), 416. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. I am constantly on the lookout for new ways to improve my life. 2. Wherever I have been, I have been a powerful force for constructive change. 3. Nothing is more exciting than seeing my ideas turn into reality. 4. If I see something I don’t like, I fix it. 5. No matter what the odds, if I believe in something I will make it happen. 6. I love being a champion for my ideas, even against others’ opposition. 7. I excel at identifying opportunities. 8. I am always looking for better ways to do things. 9. If I believe in an idea, no obstacle will prevent me from making it happen. 10. I can spot a good opportunity long before others can. 174 Felt inauthenticity All items were taken from the Felt inauthenticity measure reported in Erickson and Ritter (2001) and use the instructions and scale anchors below: Source: Erickson, R. J., & Ritter, C. (2001). Emotional labor, burnout, and inauthenticity: Does gender matter? Social psychology quarterly, 146-163. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. To get through my work day, I feel like I have to become mechanical or robot-like. 2. When I'm at work, I become unsure of what my 'real' feelings are. 3. I worry that this job is hardening me emotionally. 4. I don't feel I can be myself at work. 5. I have to fake how I really feel when I'm at work. 6. I basically have to become a different person when I'm at work. 175 Ego-Depletion All items were taken from the Ego-Depletion measure reported in Twenge et al. (2004) and use the instructions and scale anchors below: Source: Twenge, J., Muraven, M., & Tice, D. (2004). Measuring state self-control: Reliability, validity, and correlations with physical and psychological stress. Unpublished manuscript, San Diego State University. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. My mental energy is running low. 2. My mind feels unfocused. 3. It takes a lot of effort for me to concentrate on something. 4. I feel drained. 5. I feel like my willpower is gone. 176 Autonomy All items were taken from the Autonomy measure used by Morgeson et al. (2005) adapted from Oldham and Hackman (1981) and use the instructions and scale anchors below: Source: Morgeson, F. P., Delaney-Klinger, K., & Hemingway, M. A. (2005). The importance of job autonomy, cognitive ability, and job-related skill for predicting role breadth and job performance. Journal of Applied Psychology, 90(2), 399. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. I have significant autonomy in determining how I do my job. 2. I can decide on my own how to go about doing my work. 3. I have considerable opportunity for independence and freedom in how I do my job. 177 Social Interaction Quality Items were adapted from the Diary of Ambulatory Behavioral States (DABS) measure developed by Kamarck et al. (1998) and use the instructions and scale anchors below: Source: Kamarck, T. W., Shiffman, S. M., Smithline, L., Goodie, J. L., Thompson, H. S., Ituarte, P. H., ... & Perz, W. (1998). The Diary of Ambulatory Behavioral States: A new approach to the assessment of psychosocial influences on ambulatory cardiovascular activity. Technology and methods in behavioral medicine, 163, 93. Scale Anchors: 1 = never, 2 = rarely, 3 = sometimes, 4 = about half the time, 5 = often, 6 = most of the time, 7 = always. Instructions: Please indicate the extent that you agree with each of the following statements below. 1. How often do people do favors for you at work? 2. How often do people show confidence in your abilities at work? 3. How often do people at work show care and concern for you? 4. How often do people give you constructive feedback at work? 5. How often do people offer you help at work? 6. How often do people at work make you feel important? 7. How often do people at work treat you unfairly? 178 Emotional Exhaustion All items were taken from the Emotional Exhaustion measure adapted by Koopman et al. (2016) from the original scale developed by Maslach and Jackson (1981) and use the instructions and scale anchors below: Source: Koopman, J., Lanaj, K., & Scott, B. A. (2016). Integrating the bright and dark sides of OCB: A daily investigation of the benefits and costs of helping others. Academy of Management Journal, 59(2), 414-435. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. I am emotionally drained from my work. 2. I am burned out from my work. 3. I am frustrated by my job. 4. I am working too hard on my job. 179 Job satisfaction All items were taken from the job satisfaction measure adapted by Judge et al. (2006) from the original measure developed by Brayfield and Rothe (1951) and use the instructions and scale anchors below: Source: Judge, T. A., Scott, B. A., & Ilies, R. (2006). Hostility, job attitudes, and workplace deviance: test of a multilevel model. Journal of Applied Psychology, 91(1), 126. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. Most days I am enthusiastic about my work. 2. I feel fairly satisfied with my present job. 3. I find real enjoyment in my work. 4. Each day of work seems like it will never end. 5. I consider my job rather unpleasant. 180 Task-Performance - (7-items) All items were taken from the Task-Performance measure adapted by Koopman et al. (2016) from the scale developed by Williams and Anderson (1991) and use the instructions and scale anchors below: Source: Koopman, J., Lanaj, K., & Scott, B. A. (2016). Integrating the bright and dark sides of OCB: A daily investigation of the benefits and costs of helping others. Academy of Management Journal, 59(2), 414-435. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. 1. I have adequately completed my assigned duties. 2. I have fulfilled responsibilities specified in my job description. 3. I have performed the tasks expected of me. 4. I have met the formal requirements of my job. 5. I have engaged in activities that directly affect my performance. 6. I have neglected aspects of the job that I am obligated to perform. 7. I have failed to perform essential duties. 181 Surface and Deep Acting All items were taken from the Surface and Deep Acting measures reported in Grandey (2003) and use the instructions and scale anchors below: Source: Grandey, A. A. (2003). When “the show must go on”: Surface acting and deep acting as determinants of emotional exhaustion and peer-rated service delivery. Academy of Management Journal, 46(1), 86-96. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. Surface Acting: 1. I put on an act in order to deal with customers in an appropriate way. 2. I faked a good mood. 3. I put on a "show" or "performance". 4. I just pretended to have the emotions I need to display for my job. 5. I put on a "mask" in order to display the emotions I need to display for my job. Deep Acting: 1. I tried to actually experience the emotions I must show. 2. I made an effort to actually feel the emotions that I needed to display toward others. 3. I worked hard to feel the emotions that I needed to show to others. 182 Power and Status All items were taken from the Power and Status measures developed by Yu et al. (2019) and use the instructions and scale anchors below: Source: Yu, A., Hays, N. A., & Zhao, E. Y. (2019). Development of a bipartite measure of social hierarchy: The perceived power and perceived status scales. Organizational Behavior and Human Decision Processes, 152, 84-104. Scale Anchors: 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = neither agree nor disagree, 5 = slightly agree, 6 = agree, 7 = strongly agree Instructions: Please indicate the extent that you agree with each of the following statements below. Power: 1. I supervise a large number of subordinates. 2. I formally manage many other people. 3. 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