Emotional Labor in Customer Service Work

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EMOTIONAL LABOR IN CUSTOMER SERVICE WORK:

THE PERCEIVED DIFFICULTY AND DISPOSITIONAL ANTECEDENTS

A Dissertation

Presented to

The Graduate Faculty of The University of Akron

In Partial Fulfillment

of the Requirements for the Degree

Doctor of Philosophy

Diane M. Monaghan

August, 2006 EMOTIONAL LABOR IN CUSTOMER SERVICE WORK:

THE PERCEIVED DIFFICULTY AND DISPOSITIONAL ANTECEDENTS

Diane M. Monaghan

Dissertation

Approved: Accepted:

______Advisor Department Chair Dennis Doverspike Paul E. Levy

______Committee Member Dean of the College Harvey L. Sterns Ronald F. Levant

______Committee Member Dean of the Graduate School Janice D. Yoder George R. Newkome

______Committee Member Date Andrea F. Snell

______Committee Member Steven R. Ash

ABSTRACT

Emotional Labor in Customer Service Work:

The Perceived Difficulty and Dispositional Antecedents

Emotional labor is defined as the effort involved in performing emotional

regulation for the purpose of complying with the interpersonal demands required in order to perform a job in an organization. In previous research, emotional labor has been shown to be related to both personal and organizational outcomes. It has been established that of the two forms of emotional labor, surface acting and deep acting, surface acting has a greater negative impact on the individual performer, while deep acting has muted or reversed relationships with these negative personal outcome

variables. Previous definitions of emotional labor, however, have left out an important

component in the measurement of emotional labor, the perceived difficulty of performing

both deep and surface acting.

Replicating previous research, in this study of 198 employees in a customer

service organization the frequency of performing surface acting positively predicted

emotional exhaustion, but the frequency of deep acting was not significantly related to

the outcome variable of emotional exhaustion. The new variable of difficulty of

performing deep acting was found to be positively related to emotional exhaustion, a

previously unexplored relationship. The difficulty of surface acting, however, was not

found to be significantly related to emotional exhaustion.

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In addition to adding difficulty as a component of emotional labor, several dispositional variables were tested as antecedents of emotional labor. Many researchers have proposed dispositional antecedents of emotional labor in the literature, but only a handful have been tested. This study tested gender role identification, positive and negative affectivity, emotional intelligence, agreeableness, and action-state orientation as antecedents of both the frequency and difficulty components of emotional labor. Support was found for relationships between emotional labor and all the dispositional antecedents tested.

ACKNOWLEDGEMENTS

There are many people who gave me encouragement and support through the six

years that I was “working” on this project. I would like to thank all of you!

First, I would like to thank my parents; you were right. There, now it is in print forever, me admitting that you were right. Thank you for being right! Tara, thank you for bugging me just enough, and for laying off when I couldn’t handle it.

To Paully, KO, Darren, Kramen, Sully, and Danny B., thank you for making

Akron bearable, we still had more fun than any other class! To Paully, you have always

inspired me to finish this. You always believed in me and your confidence in me helped

me through the darkest times, even if you weren’t speaking to me. Whatever direction

your path and mine take, you will always have my respect and my friendship.

To Mel and Curtis, thank you for accepting me for who I am, no matter what.

You always knew I would finish, but you never made me feel like I had to.

To Holly, Rich, and Sarah, my BFF! Though you didn’t know the grad school me,

you have supported me in life more than anyone I can imagine. Where would I be today

without girl’s night? I love you all!

To the mountains, and the snow, and Uller, thank you for the distractions, without

you I may have finished earlier, but I wouldn’t have enjoyed the last six years nearly as

much.

Finally, a big thank you to all of the partners at Starbucks that helped me and supported me in my data collection. I could not have accomplished this without my daily dose of caffeine, and a lot of cooperation!

TABLE OF CONTENTS

Page

LIST OF TABLES……………………………………………………………………viii

LIST OF FIGURES……………………………………………………………….……x

CHAPTER

I INTRODUCTION…………………………………………………………..1

II LITERATURE REVIEW…………………………………………………..9

Emotional labor defined……………………………………………….9

A model of emotional labor………………………………..…………16

III METHODS…………………………………………….……..…………..48

IV RESULTS………………………………………….……………………..54

Hypotheses testing……………………………………………………56

V DISCUSSION……………………………………………………………..90

REFERENCES…………………………………………………………….……..….106

APPENDICES……………………………………………………………….………112

APPENDIX A. PARTICIPANT SURVEY…………………………….…....113

APPENDIX B. IRB APPROVAL…………………………………….……..128

APPENDIX C. INFORMED CONSENT……………………………………129

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LIST OF TABLES

Table Page

1 Summary of Hypotheses……………………………………..………………..46

2 Exploratory Factor Analysis with Varimax Rotation on Emotional Labor Items…………………………………………………….55

3 Bivariate Correlation Matrix………………………………………..…………57

4 Hierarchical Regression Predicting Emotional Exhaustion……………..…….59

5 Hierarchical Regression Predicting Emotional Labor from PAQ ……...……..62

6 Hierarchical Regression Predicting Emotional Labor from Negative Affectivity……………………………………………...……...64

7 Hierarchical Regression Predicting Emotional Labor from Positive Affectivity…………………………………………..………….67

8 Hierarchical Regression Predicting Emotional Labor from Self-monitoring …………………………………………….…..……….69

9 Hierarchical Regression Predicting Emotional Labor from Emotional Intelligence……………………………………..…….……..72

10 Hierarchical Regression Predicting Emotional Labor from Agreeableness ………………………………….…………….….……..74

11 Hierarchical Regression Predicting Emotional Labor from Action-State Orientation ………………………………….……………77

12 Summary of Significant Relationships between Antecedents and Emotional Labor………………………………….………………....……79

13 Hierarchical Regression Predicting Frequency of Deep Acting ……………..81

14 Hierarchical Regression Predicting Difficulty of Deep Acting ………...……82

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15 Hierarchical Regression Predicting Frequency of Surface Acting …….…….83

16 Hierarchical Regression Predicting Difficulty of Surface Acting ……..…….84

17 Hierarchical Regression Predicting Emotional Exhaustion Full Model…………………………………………………..…….…….……86

18 Means of Dichotomized Variables for Positive Affectivity………..……..….88

19 Means of Dichotomized Variables for Self-Monitoring……………..……….89

LIST OF FIGURES

Figure Page

1 Model of Emotional Labor……………………………………..……………..30

CHAPTER I

INTRODUCTION

Few would argue that one of the most noticeable trends in the workplace over the

last few decades has been the increased emphasis on service. Company jingles claim that employees love their jobs, advertising spews promises of satisfied customers, and company training procedures are filled with notions of service and promoting a comfortable, pleasant atmosphere for the customer.

Why this emphasis on service? One of the main reasons is inter-company

competition; as Hochschild (1983) aptly put it “when competition in price is out,

competition in service is in” (p. 92). In order to remain profitable in this highly competitive world, companies need to offer a pleasing customer service interaction in addition to a good product at a competitive price. As a result most jobs today have employees interacting with and monitoring their responses to customers, even in fields that were not originally intended to include a customer service component, such as engineering and auto repair. This management of emotional responses toward the customer has become a paid and evaluated part of the work role and has been given the label emotional labor (Hochschild, 1983).

The concept of emotional labor was originally introduced by Hochschild in 1983, and both the definition and the model of antecedents and outcomes have been continuously developed throughout the years (Ashforth & Humphrey, 1992; Bono &

Vey, 2005; Grandey, 1999; Morris & Feldman, 1996). The definition of emotional labor has evolved from a simple dichotomization of jobs into those requiring or not requiring emotional labor (Hochschild, 1983) into a construal of emotional labor as emotional regulation for the purposes of an organization (Grandey, 1999). This paper defines emotional labor as the effort involved in performing emotional regulation for the purpose of complying with the interpersonal demands required in order to perform a job in an organization and in order to produce an organizationally sanctioned emotional response.

Thus, emotional labor is occurring when an employee must purposefully alter his or her emotions in order to meet an organizational demand. This indicates that in order for emotional labor to be performed the employee must be experiencing, or about to experience, an emotional response that is not congruent with the organizational demand.

Most researchers view emotional regulation as requiring the use of one of two strategies, deep acting or surface acting. Deep acting refers to efforts directed toward changing the emotion felt, such as when an employee faced with an irate customer chooses to focus on a positive experience that occurred earlier in the day to maintain a positive emotion through the potentially negative experience. Surface acting, on the other hand, involves focusing on the external display of emotion, for example an employee who is angry at being short staffed and overworked, but fakes a smile to satisfy the customer service requirements of the job.

There is a third strategy that has been considered as a part of emotional labor,

namely genuine expression of emotion (Grandey, 1999). This takes place when the

employee’s actual emotions already mimic those expected from the job, thereby eliminating the effort involved in order to achieve the organizationally desired response.

As there is no effort involved in this strategy, an individual who was achieving the organizational goals by employing genuine expression would not actually be performing emotional labor; in fact according to the definition, he or she would not be performing emotional labor. As emotional events occur throughout the day, however, an individual may employ deep acting, surface acting, genuine expression of emotion, or a combination of the three. Thus, while the demand for a specific emotional display is mandated by the organization, the actual strategy employed will not be a function of the job, but rather a function of the context and the person. It is important to note that while the genuine emotion strategy of achieving an organizationally desired response strategy is theoretically viable, it would be almost impossible to separate its measurement from the measurement of deep acting. That is, if the individual is successful in his or her attempt to actually change the emotion felt, he or she should not be able to consciously decipher between genuine emotion and emotion created from deep acting strategies.

Both deep and surface strategies have been shown to relate to important personal and organizational variables such as emotional exhaustion and customer service performance. Interestingly, the direction of these relationships seems to depend on which type of emotional labor is used, with the deep acting strategy being far less detrimental to

the individual and the organization. Whereas surface acting leads to higher emotional

exhaustion and lower customer service, deep acting is unrelated to emotional exhaustion,

and can actually improve customer service experiences.

Most operational definitions have used the frequency of performing specific

behaviors to quantify emotional labor. This study proposes that another component of

emotional labor must be considered to fully understand the construct and to keep the

scale consistent across all individuals. That component is the perceived difficulty of

performing emotional labor. Consider and example using manual labor: if two

individuals, Tom and Harry, perform the same task, lifting 50 pound boxes, the same

number of times, but Tom is not as physically fit and finds it much more physically

taxing to lift the boxes than Harry, the two are arguably not exerting the same amount of

effort. The same can be said for performing emotional labor. If Tom and Harry are

performing a specific emotional regulatory behavior the same number of times, but Tom

finds that behavior much more difficult to perform than Harry does, to assert that Tom

and Harry experienced the same amount of emotional labor would not be accurate. By measuring the perceived difficulty of emotional labor behaviors in addition to their

frequency, we are able to evaluate the emotional labor of all individuals on the same

scale. One of the main purposes of this study was to introduce this perceived difficulty

component of emotional labor to its measurement, and to test the validity of the perceived

difficulty component on an established outcome of emotional labor, namely emotional

exhaustion.

Because emotional labor has been shown to be an important construct, it would be

useful to further understand its antecedents. Ideally these antecedents could help

employers identify how to structure jobs or train employees to reduce the negative impact

of emotional labor, and possibly determine which potential job candidates would be able

to handle the emotional labor requirements of each particular job, or which would benefit

most from training.

The second major purpose of this study was to investigate the relationships between emotional labor (both the frequency and difficulty) and its potential dispositional

antecedents. Numerous antecedents of emotional labor have been proposed in the

literature, from organizational level variables to dispositional variables (Grandey, 1999).

Most of the research on the antecedents of emotional labor has focused on the

organizational level variables (Brotheridge & Lee, 2002; Grandey, 1999, 2003; Morris &

Feldman, 1996, 1997; Pugleisi, 1997). While some of the dispositional antecedents have

been examined, not all have utilized the deep and surface acting operationalization of

emotional labor (see Morris & Feldman, 1996, 1997; Pugleisi, 1997), and no published

studies that I could identify have examined the relationships between these antecedents

and the perceived difficulty of emotional labor.

The dispositional antecedents of gender role identification, affectivity, self-

monitoring, emotional intelligence, agreeableness, and action-state orientation were

chosen based on a combination of propositions made in earlier research, results found in

the literature, and theoretical links. Each antecedent is briefly discussed below.

Gender has been proposed and tested by many as a predictor of emotional labor

due to the fact that those who conform to the feminine gender role stereotype will find

themselves in situations that require the nurturing of interpersonal relationships, thus will

need to regulate their emotions more often (Grandey, 2000; Hochschild, 1983; Jones,

1998; Schaubroeck & Jones, 2000; Strazdins, 2000; Wharton & Erickson, 1993). Gender

stereotype identification was chosen to be tested as a dispositional antecedent of

emotional labor instead of gender in order to discover more meaningful differences

beyond those based on physical sex characteristics (Yoder & Kahn, 2003).

Affectivity, self-monitoring, and emotional intelligence were originally proposed

as antecedents of emotional labor by Grandey (2000). Negative affectivity influences the

intensity of affective reactions to events that occur at work, thus persons who are high on

negative affectivity may be more reactive to negative events that may occur during the

work day which will result in a need for more frequent regulatory efforts to manage

negative emotions that result. Negative affectivity will also make deep acting harder to

perform, as a person who is continuously experiencing negative feelings will find it

extremely difficult to deep act and try to actually feel the positive emotions required by the organization. Positive affectivity, on the other hand, will act the opposite way, reducing the need for emotional regulation due to lessened responses to negative events.

Positive affectivity also makes engaging in deep acting easier to perform as a person high

on positive affectivity will be better suited to re-interpret a situation or conjure up

positive emotions due to heightened accessibility of positive thoughts.

Self-monitoring refers to the degree to which people pay attention to and control

the impression that they make on others (Snyder, 1974). Individuals high on self-

monitoring are very sensitive to emotional cues from others and will frequently adjust

their own outward emotional responses to suit the situation suggesting that high self-

monitors will perform emotional labor, both deep and surface, more frequently than low

self-monitors. Also, a person high on self-monitoring will likely find both strategies

easier because of the ease in identifying and producing the appropriate emotional

response.

Emotional intelligence has been defined as being comprised of three parts:

appraisal and expression of emotion, regulation of emotion, and utilization of emotion

(Mayer & Salovey, 1993). An emotionally intelligent individual, by definition incorporates the use of emotional regulation strategies more often, thus an emotionally intelligent individual would tend to use emotional regulation strategies, both deep and surface, for the purpose of an organization more often as well. Also, emotionally intelligent people are better at interpreting emotional cues, deciphering the appropriate response and regulating their responses, thus they will find both strategies of emotional regulation, deep and surface, easier, than less emotionally intelligent people.

Agreeableness and action-state orientation were chosen to be tested as antecedents of emotional labor based on the theoretical links between the variables. Agreeableness is a personality trait that involves consistently attempting to get along well with others. As such an individual high on agreeableness would be continuously altering his or her emotional responses to fit every situation, and this would be no different for the situation in which an organization was asking for particular emotional displays. But although agreeableness will make the frequency of deep acting higher, the case for surface acting is not the same. Agreeable persons may recognize that surface acting may not be seen as genuine and may backfire, motivating them to avoid that strategy of emotional regulation.

Action-state orientation describes a goal striving technique. Action oriented

individuals are better able to focus on the task at hand, whereas state oriented individuals

often are distracted with competing goals. This variable was chosen as a promising predictor of emotional labor since when the goal is to maintain an organizationally appropriate emotional response, a person’s goal striving technique will impact how often emotional regulation strategies need to be used and how difficult those behaviors are to perform. Action orientation refers to a person’s tendency to devote resources to the present task, thus an action oriented individual will be able to shift focus onto the goal of maintaining an organizationally sanctioned emotional response, making both deep and surface acting strategies easier. A state oriented person is going to be affected by negative events that may have occurred in the past present or are thought to occur in the future, since they will not be able to block them out. As a result, such individuals will have to continuously regulate emotional feelings and responses, as they fight emotions lingering from other goals, creating a situation where state oriented individuals will need to engage in emotional regulation strategies, both deep and surface, more often.

In summary, this study improved the definition of emotional labor by measuring both the frequency and the perceived difficulty of performing emotional labor and tested the predictive validity of this new measurement on the outcome variable of emotional

exhaustion. It also investigated the proposed dispositional antecedents of not only the

frequency of both strategies of emotional labor, but also the perceived difficulty of both

strategies, a previously unexplored area of research.

CHAPTER II

LITERATURE REVIEW

For many service and customer contact jobs, it is critical that the incumbent manage his or her emotions so as to present a “friendly face” to the customer. In the psychological literature, the term “emotional labor” is used to describe the efforts involved in effectively managing one’s emotions in the workplace. In this chapter, I will review the literature relevant to the concept of emotional labor. First, emotional labor will be defined based upon the work of Hochscild (1983) and Grandey (1999). Then a model of emotional labor will be described, including the outcomes of emotional labor, and its antecedents.

Emotional Labor Defined

While the concept of emotional labor was introduced by Hochschild, the actual definition of the construct has evolved through the years, and many versions have been proposed (Bono & Vey, 2005). Hochschild (1983) originally referred to emotional labor as the purposeful control of feelings in order to outwardly demonstrate an appropriate facial and body display. This control could be managed by using either surface acting, in which the outward expression was altered, or deep acting in which the actual emotion felt was altered through re-appraisal or directly conjuring the appropriate feeling. This type

of labor was said to have exchange value and thus should be included in the evaluation of

the worth of a job for purposes of compensating the employee. Support has been found

for the concept that higher emotional labor is compensated with a higher wage, but only

for jobs high in cognitive demands (Glomb, Kammeyer-Mueller & Rotundo, 2004).

Hochschild provided a list of occupations in which emotional labor was required,

implying a dichotomous operationalization of the construct.

Expanding upon this conceptualization, Ashforth and Humphrey (1993) focused

their definition of emotional labor on the actual behaviors performed during a service

interaction. They took more of an impression management approach to emotional labor, defining it as the contrived display of appropriate emotional responses in service encounters. They claimed that this type of labor could be performed via surface acting, deep acting, or a genuine experience of emotion. They based most of their propositions regarding the construct of emotional labor on social identity theory, asserting that the

degree to which a person identifies with their work role impacts how emotional labor performed in that role will relate to outcome variables such as psychological well being and emotional dissonance.

Morris and Feldman (1996) attempted to further specify the concept by delineating its dimensions. They explicitly defined emotional labor as the “effort, planning, and control needed to express organizationally desired emotion during interpersonal transactions to display appropriate emotions” (p. 987). Similar to Ashforth and Humphrey, their definition was centered on the expression of behavior, rather than the emotional feeling itself. This effort, planning, control and skill required to display

expected emotions was encompassed by four interrelated dimensions in their theory: frequency of interaction, required attentiveness to display rules (which was a function of

the duration and intensity of the emotional display), variety of expressed emotions, and

emotional dissonance.

Their concept of emotional dissonance merits some further discussion, as it has been used by other researchers as the sole indicator of emotional labor (i.e., Abraham,

1998; 1999). Emotional dissonance occurs when the expressed emotion is not congruent with the actual felt emotion, such as the cashier who is aggravated at a demanding customer, yet smiles and thanks the customer for his or her business. As in cognitive dissonance (Festinger, 1957), the resultant state is unpleasant, and has been linked to negative outcomes. Therefore, emotional dissonance is a direct outcome of behaving in a way that does not match the current emotional state. In other words, if an individual was to engage in surface acting, emotional dissonance would be the immediate result.

Further, since emotional dissonance is a state of being rather than an effortful process, it actually does not fit Morris and Feldman’s conceptualization of the construct (Grandey,

2000). This leads to the conclusion that emotional dissonance does not fall under the

definition of emotional labor, but rather could be considered an indicator that surface

acting had been performed.

Grandey (1999, 2000) noted the confusion inherent in these three separate

definitions of emotional labor, and attempted to integrate them into a comprehensive

definition of emotional labor that could be used to model and test its antecedents and

outcomes. She noted that the common thread in all three definitions was the idea that

emotional labor involved the regulation of emotion in order to benefit the employing

organization. By combining the different conceptualizations of emotional labor with theories on emotional regulation, Grandey created a definition of emotional labor that proposed that it was not simply the outward expression presented by an employee, as

Ashforth and Humphrey (1993) would have us believe, nor was it the combination of characteristics of the job, to which Morris and Feldman (1996) alluded. Instead, she argued that emotional labor involved the regulation of feeling and expression in order to meet organizational goals.

Gross (1998a, b) proposed that emotional regulation can occur in two ways. First, an antecedent-focused approach can be used in which emotions are controlled by altering factors such as the situation or the interpretation of the situation prior to the experience of emotion. Second, a response-focused approach could be taken in which the outward expressions are changed after the emotional reaction has begun. Grandey noted that these two types of emotion regulation corresponded to the deep acting and surface acting concepts used in Hochschild’s (1983) original conceptualization of emotional labor.

In the antecedent-focused approach, the target of emotional management is on changing the actual emotion felt. For example, in a situation with an angry customer trying to return a defective product, a person using the antecedent-focused approach might reappraise the situation by imagining his or herself in the customer’s shoes, or perhaps choose to focus on pleasant customer interactions that occurred earlier in the day.

Either tactic would help the individual to actually feel the positive emotions required in the display of emotion. This effort would be classified as deep acting.

In response-focused regulation, however, the target is on the management of facial and bodily expressions after the emotion has been felt. Using the same scenario above, an individual using a response-focused approach may experience negative emotions brought on by the confrontation, but would hide them and put on a fake smile while the customer ranted about his or her problem, creating the desired emotional response without changing the actual emotion felt. Hochschild referred to this as surface acting. When an individual recognizes the need an emotional regulation strategy, the person performing emotional labor has a choice as to which method is used, thus differentiating emotional labor from situational demand.

Grandey’s (2000) definition of emotional labor as the regulation of feeling and expression in order to meet organizational goals incorporates the important aspects of the three preceding definitions. The deep and surface acting concepts of Hochschild (1983) are clearly seen as the two approaches to regulation, and are consistent with Ashforth and

Humphrey’s (1993) ideas on how outward expressions can be created. Also, although the situational dimensions offered by Morris and Feldman (1996) are not part of the definition itself, the variables of frequency, attentiveness to display rules, and variety of expression are seen as antecedents to emotional labor. Further, emotional dissonance is

included in the model, but it is considered as a proximal outcome from surface acting,

rather than a facet of emotional labor.

Operational Definition of Emotional Labor

It is important to discuss the operationalization of Grandey’s definition of emotional labor. This definition of emotional labor as emotional regulation for the

purposes of an organization was used to develop a scale of emotional labor (Grandey,

1999). This scale included items asking how often employees performed specific emotional regulatory behaviors such as “putting on a show” or “actually trying to feel the emotion required.”

Although this is a very good start to measuring emotional labor, and extensive work has gone into developing and validating items for the scale, it appears to be missing an important aspect, that is, perceived difficulty. As it stands, this measure posits that if one person performs more emotional regulation behaviors than another, then that person is performing more emotional labor. However, this assumes that each behavior is at the same difficulty level for all people, and there is reason to doubt that this assumption is true. In order to use the same scale consistently across individuals we need to also take the perceived difficulty of each behavior into account. Emotional labor is not simply an objective job feature, but rather a perception of the job that differs for every individual, thus both the frequency and the perception of difficulty of performing specific emotional regulatory behaviors must be considered. For the purposes of this paper, emotional labor is defined as the effort involved in performing emotional regulation for the purpose of complying with the interpersonal demands required in order to perform a job in an organization. Emotional labor will be operationalized as the both the frequency and the difficulty of performing emotional regulatory behaviors.

Further, it is also important to note that while surface acting and deep acting are both facets of emotional labor, they are indeed separate ways of manifesting emotional labor. They are expected to be related to each other, since when emotional regulation is

required both strategies could be used, but they are distinct facets as the use of one does not necessarily require or inhibit the use of the other. Notably, when both deep acting and surface acting are measured in aggregate form, or as a collection of past behaviors, they will be more highly related than when measured on a single action basis. This is because over time an individual will employ both strategies to deal with the various situations requiring emotional regulation, whereas in a single situation only one strategy might be used. Since an aggregate measurement will be used in this study, a high correlation between deep acting and surface acting is expected.

Emotional labor is ubiquitous in the work world; however this research will focus on the customer service field. Other relevant fields for emotional labor research such as the nursing or health care have been studied (e.g. Sass, 1997; Shuler, 1997), but very different propositions and conclusions are expected, as the organizationally required emotional response is much different, involving compassion and a deeper sense of caring rather than customer connection and pleasantries. Also, although emotional labor can involve organizational demands to demonstrate positive, neutral, or negative emotions

(Grandey, 2000), the scope of this paper will be limited to positive emotions. Although all three types can be found in the work world, (e.g., debt collectors must be mean, lawyers must be neutral, salespeople must be nice), the majority of organizations are concerned with the customer service implications of emotional labor, and typically customer service is congruent with positive emotions. It makes sense to focus on positive emotional labor, as that is the type that the majority of organizations desire from their

employees. However, it has been shown that positive emotions can have different effects

than negative ones (Fredrickson, 1998) and findings with one may not generalize to the

other.

A Model of Emotional Labor

Combining past research and theory on both emotional labor and emotional

regulation, Grandey (2000) proposed a model that included proposed antecedents and outcomes of emotional labor. The antecedents included situational, individual and organizational factors, and the outcomes included individual and organizational well- being variables. In this section, the model of emotional labor will be clarified and discussed.

Outcomes of Emotional Labor

Most of the research that has been done on emotional labor in the last 10 years has been focused on outcomes. This is not that surprising, because much of the interest in the emotional labor construct has been based on its consequences (Mann, 1999). Emotional labor has been found to be related to stress (Adelmann, 1995; Pugliesi, 1999), emotional exhaustion (Abraham, 1998; 1999; Brotheridge & Grandey, 2002; Grandey, 2003), feelings of inauthenticity (Erickson & Ritter, 2001; Brotheridge & Lee, 2002), physical symptoms (Schaubroeck & Jones, 2000), job satisfaction (Abraham, 1999; Adelmann,

1995; Jones, 1998; Pugliesi, 1999; Wharton, 1993; 1996), job performance (Totterdell &

Holman, 2003), and organizational citizenship behaviors (OCBs) (Jones, 1998).

Several different operationalizations of emotional labor have been used in past research (Fisher & Ashkanasy, 2000). Despite the confusion inherent in combining

research using multiple definitions, it is clear that emotional labor is linked to important organizational and individual outcomes such as emotional exhaustion and job stress. In a quantitative review of the research in emotional labor, Bono and Vey (2005) investigated the relationships between emotional labor and the outcome variables tested in the literature. They concluded that emotional labor is related to poor psychological health, and weakly and inconsistently related to job attitudes such as job satisfaction (r = -.32) and role internalization (r = -.30), with these last two relationships being negative for surface acting, but small and not significant for deep acting. It is interesting to note that not all of the existing research agrees on the direction of the relationships between emotional labor and these important outcomes. Although some of this disagreement lies in the operationalization of emotional labor, clear distinctions are evident when the dimensions of deep and surface acting are examined separately.

Outcomes of Deep and Surface Acting

A great deal of the research on the outcomes of emotional labor has utilized a definition of emotional labor that is congruent with the concepts of deep and surface acting (Brotheridge & Grandey, 2002; Brotheridge & Lee, 2002; Erickson & Ritter,

2001; Grandey, 1999, 2003; Pugliesi, 1999; Totterdell & Holman, 2003). There is consensus in the literature that emotional labor has both positive and negative consequences for both the organization and the employee. In general these effects can be clarified by examining the two forms of emotional labor separately.

Personal Outcomes of Surface Acting

There is a great deal of evidence that surface acting has detrimental consequences

for the emotional laborer. In a survey study of university employees, Pugliesi (1999)

investigated the relationship between “self-focused” emotional labor, and several

outcome variables. “Self-focused” emotional labor was measured by three items that asked respondents to rate their agreement with statements related to being unable to express true feelings and having to behave in an artificially friendly manner; ideas that closely mimic surface acting. Pugliesi found that this measure of the surface acting method of emotional labor negatively related to global job satisfaction, and positively related to both job stress and psychological distress. Further, these relationships were significant even after controlling for job demands, job complexity and job control.

In a survey sample of university administrative assistants, Grandey (1999) also provided evidence that the surface acting method of emotional labor was negatively related to job satisfaction and positively related to turnover intentions even after controlling for the organizational demands of the job. The results also showed that performing surface acting was positively related to emotional estrangement, or a sensation of feeling alienated from one’s true emotions.

Erickson and Ritter (2001) replicated this positive relationship between the feelings of emotional inauthenticity and a measure of surface acting in a sample of employees from a broader array of occupations. Their measure of emotional labor looked specifically at how often “agitation emotions,” defined as anger, irritation or nervousness,

had to be hidden or covered up. This could be considered as a component of surface

acting.

Burnout has been the most commonly studied personal outcome variable in

relation to the surface acting method of emotional labor. The Maslach Burnout Inventory

(Maslach, Jackson, & Lieter, 1996) defines burnout in terms of three components. The first is emotional exhaustion, or “being emotionally overextended and exhausted by one’s work” (p.4). The second component of burnout is depersonalization, defined as “an unfeeling and impersonal response toward recipients of one’s service care, treatment, or instruction” (p.4). The final component of burnout is reduced personal accomplishment, defined as a reduction in the “feelings of competence and successful achievement in one’s work with people” (p.4).

Grandey (1999) investigated the relationship between emotional labor and all three components of burnout. She found support for the idea that surface acting has negative personal consequences; it was positively related to all three components of burnout in a sample of administrative assistants. Grandey’s (1999) findings for all three

components were replicated in a sample of Canadian employees from a wide variety of

jobs (Brotheridge & Grandey, 2002).

In a similar sample, Brotheridge and Lee (2002) found that surface acting was

positively related to all three components of burnout, but feelings of authenticity mediated the relationships between surface acting and personal accomplishment as well

as the relationship between surface acting and emotional exhaustion. Erickson and Ritter

(2001) only measured the emotional exhaustion component of burnout, and also found a

positive relationship between surface acting and emotional exhaustion in a broad range of

occupations. To further support this common finding, Grandey (2003) also corroborated the finding that the more often surface acting is performed, the greater the emotional exhaustion reported.

Personal Outcomes of Deep Acting

Surface acting has clearly been shown to have a wide variety of deleterious effects on the performer. Deep acting, on the other hand, has not shown to be as detrimental to the individual performing it, and in fact is related to many positive outcomes. Grandey (1999) found that unlike surface acting, deep acting was unrelated to the sense of personal accomplishment component of burnout. Further, although deep acting was positively related to the emotional exhaustion and depersonalization components of burnout, the coefficients were smaller than the relationships with surface acting. Interestingly, when those relationships were tested using hierarchical regression,

only the surface acting component of emotional labor remained a significant predictor of

burnout; deep acting was not a significant predictor of any of the components of burnout.

A similar pattern was found for the negative relationship between job satisfaction and

deep acting, as well as the positive relationships between deep acting and both turnover

intentions and emotional estrangement. Again, the correlations between these variables

were smaller for deep acting than they were for surface acting, and the relationships with

deep acting were not significant when surface acting was controlled for in hierarchical

regression.

Grandey in a 2003 study also found that unlike surface acting, deep acting did not

have a significant relationship with emotional exhaustion. Brotheridge and Grandey

(2002) not only found no significant relationships between deep acting and the negative

outcomes of emotional exhaustion or depersonalization, but also demonstrated that deep

acting was related positively to an increased sense of personal accomplishment.

Brotheridge and Lee (2002) also replicated the positive relationship between deep acting and increased sense of personal accomplishment. In addition they found that deep acting was positively related to a sense of authenticity and negatively related to depersonalization, opposite from the effects of surface acting.

Organizational Outcomes of Deep and Surface Acting

There is also a difference between the organizational outcomes of emotional

labor, depending on which type of emotional labor is used. Grandey (1999) showed that

even after controlling for organizational variables, surface acting was negatively related

to an co-worker rated customer service measure, whereas deep acting was positively

related to that measure.

Grandey (2003) replicated the finding that the more surface acting used by an

employee, the lower a peer rated the affective delivery of that employee, which was a

measure of the emotional display toward the customer. She also corroborated that higher frequency of deep acting was associated with higher ratings of affective delivery.

Grandey and others (Grandey, Fisk, Mattila, Jansen, & Sideman, 2005) further investigated the impact of surface acting, or faking emotions, on customer satisfaction in two studies: one lab controlled and one in a restaurant setting. They found that although

surface acting can result in a satisfactory encounter, the surface acting must be perceived as genuine in order to deliver positive results.

Apparently the result of emotional labor is more effective when deep acting is performed, and may actually backfire under surface acting. Self-reported job performance has also been shown to be positively related to deep acting but unrelated to surface acting in a diary study of call center employees (Totterdell & Holman, 2003), hinting that even employees themselves are aware that surface acting is less effective than deep acting.

The Relationship between Deep and Surface Acting

It is clear that although both deep and surface acting can be used to achieve the goal of emotional regulation for the purpose of achieving organizational outcomes, deep acting is less detrimental to the individual and possibly to the organization than surface acting. The two types of emotional labor are not entirely independent, however.

Brotheridge and Lee (2002) hypothesized that the relationship between surface and deep acting was a result of an attempt to conserve resources. They suggested that surface acting required more resources than deep acting, and as such people engaging in emotional regulation would actually try to use deep acting to “feel the emotion” in order to save resources. I believe this to be untrue, while faking a smile may be more emotionally taxing, as shown by the positive relationship between surface acting and emotional exhaustion, it does not necessarily require more resources to perform.

When the difficulty of emotional regulation behaviors is considered, this becomes clearer. The more difficult an individual finds one of the methods to be, the more

resources that particular method will likely require for that person to engage in that

method. When faced with the need for emotional regulation, if resources are not

available, the individual would likely avoid the strategy that is perceived as difficult and

chose the strategy that is easiest. Alternatively, if both strategies are perceived as difficult, then that individual may be unable to perform any emotional labor and would fail to alter the emotional display as mandated by the organization. Thus, when the difficulty of performing emotional labor is considered, a negative relationship between

the difficulty and the frequency of one type of emotional labor would be expected as well

as a positive relationship between the difficulty of one method, and the frequency of the

other.

When measured in aggregate form, the frequency of both types of emotional

labor, deep and surface, will be related due to the fact that when emotional regulation is

required, both strategies can be used. Over time an individual who requires emotional

regulation will likely use both strategies. Additionally, a positive relationship would be

expected even when measured in a single incident as when one type of regulation fails,

the other might then be employed to meet the organizational need. In fact, the frequency

of two types of emotional labor have been found to be related (r = .27, Brotheridge &

Grandey, 2002; r = .30, Brotheridge & Lee, 2002; r = .47, Grandey, 1999; r = .43,

Grandey, 2003; r = .54, Totterdell & Holman, 2003). However, although deep and

surface acting are positively related to each other, they are separate constructs and should

be investigated as such given the different relationships that have been found with

important outcome variables.

Hypotheses for the Outcomes of Emotional Labor

In summary, surface acting has been shown to be negatively related to job satisfaction and personal accomplishment. It has also been shown to be positively related to job stress, psychological distress, turnover intentions, emotional estrangement, sense of depersonalization, and emotional exhaustion. Deep acting, on the other hand, has been shown to have smaller or reversed relationships to depersonalization, job satisfaction, job performance and emotional exhaustion, and has been shown to positively relate to increased personal accomplishment and improved customer service. While all of these findings are interesting, clearly the most consistent outcome variable for emotional labor is emotional exhaustion.

This paper defines emotional labor as a combination of the frequency and difficulty of emotional regulation for the purpose of meeting organizational goals.

Because a measure of emotional labor that takes into account difficulty of emotional regulatory behaviors has not yet been used in the literature to date, an adapted version of

Grandey’s (1999) will be used. The first hypothesis in this study was set up to validate this new version of the measure. The goal was to show that the redefinition holds its predictive value of an outcome measure. As such one outcome variable will be measured. Emotional exhaustion was chosen because it has received the most attention and support from the literature as a potential outcome of emotional labor, with the most consistent results (Abraham, 1998, 1999; Brotheridge & Grandey, 2002 ; Brotheridge and

Lee, 2002; Grandey, 1999, 2003; Jones, 1998; Morris and Feldman, 1997; Totterdell &

Holman, 2003; Wharton, 1993, 1996).

In order to corroborate past findings on a fairly consistent outcome variable, and

investigate the predictive ability of the added component of perceived difficulty of

emotional labor, the following hypotheses about emotional labor and emotional

exhaustion were proposed:

H1a: The frequency of using the surface acting method of emotional labor will be

positively related to emotional exhaustion. The relationship between these variables will

be stronger for surface than deep acting.

H1b: The perceived difficulty of using the surface acting method of emotional

labor will be positively related to emotional exhaustion. The relationship between these

variables will be stronger for surface than deep acting.

Antecedents of Emotional Labor

Surprisingly, research on the antecedents of emotional labor has been sparse,

though many types of antecedents have been proposed including situational, job and

individual difference variables. The majority of research investigating antecedents of

emotional labor has focused on the situational and job features of the work environment.

Variables such as frequency of interaction, duration of interaction, variety of emotions

required, attentiveness to emotional display rules, job autonomy, task routines, role

power, and job satisfaction have been looked at as potential determinants of emotional labor (Brotheridge & Lee, 2002; Grandey, 1999, 2003; Morris & Feldman, 1996, 1997;

Pugleisi, 1997). Results have been found but have been inconsistent. This lack of consistency is likely related to both the differing operational definitions of emotional labor, and the diversity of occupations used throughout the literature.

Situational and Job Features as Antecedents of Deep and Surface Acting

There have been several studies that offer insight into the antecedents of emotional labor that have used the concepts of deep and surface acting in the measurement of emotional labor. The most common antecedents that have been proposed and tested under this framework are based around the features of the situations encountered while working. They include the frequency of interaction, the duration of interaction, the variety of emotions displayed, and attentiveness to emotional display rules. Display rules refer to the organizations expectation for emotional displays on the job. Grandey (1999) measured all of these as antecedents of emotional labor in a sample of administrative assistants. She only found support for display rules as an antecedent to the frequency of the deep acting method of emotional labor, none of the other potential antecedents predicted either deep or surface acting. Brotheridge and Lee (2002) also measured all of these variables, but combined the frequency of interaction, intensity of interaction and variety of emotional displays into one variable, which they labeled “role characteristics.” Their sample included a broader variety of occupations, and they found that both display rules and role characteristics were positively related to both the frequency of performing both the surface and deep methods of emotional labor.

Brotheridge and Grandey (2003) also measured these situational variables in a sample of employees holding many occupations, with the addition of two measures.

They asked about the perceived requirements to display positive emotions as well as requirements to hide negative emotions. They did not hypothesize any of the situational variables as antecedents of the frequency of surface and deep acting, but rather looked at

them as a separate form of “job-focused” emotional labor in the prediction of outcome

variables. As such they did not test them as antecedents, but the correlation matrix reveals relationships similar to the findings of Brotheridge and Lee (2002). All of the variables, with the exception of duration of interaction, were positively related to the frequency of both surface and deep acting. For duration of interaction, only the correlation between the frequency of deep acting was significant, surface acting was

unrelated. Grandey (2003), in another sample of administrative assistants, corroborated

the finding that display rules are an antecedent of the frequency of deep acting, but not of

surface acting.

In addition to the antecedents discussed above, Pugliesi (1997) measured some

job features including job complexity, job control, and job demands, or the perception that there is too much work to be completed in the time allotted. Although not tested as antecedents in this study, these variables have been proposed to be antecedents of emotional labor (Morris and Feldman, 1996). Pugliesi’s measure of emotional labor, which closely resembled surface acting, was negatively related to job complexity and job control, indicating that the less complex a job is, and the more control an individual feels they have in their job, the more often surface acting is performed. Further, surface acting was positively related to job demands; the more an employee felt that their job demanded too much of them, the more often surface acting was performed.

Potential outcomes of emotional labor, such as job satisfaction, have even been proposed as antecedents of emotional labor. Recently, Grandey (2003) proposed and found support for the idea that job satisfaction has an effect on which type of emotional

labor is performed. While both the frequency of deep and surface acting had a negative

correlation with job satisfaction, the relationship with surface acting was more pronounced. Satisfied employees had to “fake it” less often than unsatisfied ones.

In summary, several job characteristics have been proposed as antecedents of emotional labor. While some support has been found in the literature for situational features such as frequency of interaction, variety of emotions to be displayed, intensity of emotional responses, and job features such as job complexity, and job demands, replication of these results has not been consistent. There is one clear exception to this lack of replication, however. It is evident that required attentiveness to display rules is positively related to the frequency of using of the deep acting strategy of emotional labor.

This consistent finding is also supported by the results of a quantitative review of the emotional labor literature (Bono & Vey, 2005); the strongest association between predictors and emotional labor was found between display rules and the frequency of deep acting.

Because the sample for the current study included only one job, that of a retail customer service representative, the situational and job features such as display rules should be fairly consistent for all participants. Thus, no hypotheses regarding situational or job features as antecedents to emotional labor were proposed in this study.

Individual Difference Antecedents of Emotional Labor

Understanding situational and job determinants of emotional labor could be used to improve job design in order to attain the appropriate level and type of emotional labor required. Individual difference determinants, on the other hand would be useful in

determining who would be more suitable for a job, given the level of potential emotional labor that is inherent in its design. Just as for physical or mental work, companies try to select employees who are better suited for the job. It makes sense that, in relation to emotional work, a company may benefit from selecting individuals who are more suited to handle the requirements of that particular job (Adelmann, 1995; Briner, 1999).

Unfortunately, there has been little progress in determining individual difference variables that influence the amount of emotional labor that needs to be done on a job, despite the obvious need (Ashforth & Humphrey, 1993; Grandey, 1999, 2000).

Researchers have proposed lists of individual difference variables ranging from simple demographic variables such as gender to complex constructs such as emotional intelligence. One of the main focuses of this paper is to investigate several of these individual difference variables as antecedents of emotional labor (see Figure 1).

Gender

Gender has been proposed by many researchers to be related to the frequency of emotional labor performance. Hochschild (1983) predicted that women would engage in more emotional labor than men, based on the reasoning that women are called on to perform emotional work more, and they are more likely to be involved in situations that require such efforts. This has been supported in qualitative studies on emotional labor

(c.f. Steinberg & Figart, 1999), as well as in quantitative studies (Strazdins, 2000).

However, Jones (1998) failed to find a significant correlation between gender and emotional dissonance. As emotional dissonance is a direct outcome of surface acting, this indicates that gender was not related to surface acting. Recent researchers have

Demographic Variables: Age Gender Tenure Hours worked per week Job title

Frequency of surface acting

Frequency of deep acting Emotional Exhaustion Individual Differences: Gender Stereotype Identification Perceived difficulty Positive Affectivity of surface acting Negative Affectivity Self-monitoring Emotional Intelligence Agreeableness Perceived Action-State Orientation difficulty of deep acting

Figure 1

A Model of Emotional Labor

pointed out that it may not be the physical sex characteristics that create differences, but

rather contextual differences such as identification with gender based stereotypes that

explain differences found between women and men (Yoder & Kahn, 2003). Therefore,

this study will test hypotheses about identification with gender based stereotypes rather than simply biological sex. Still, the prediction of the frequency of performing both

surface and deep acting from identification with gender based stereotypes remains the same as the predictions made previously. Those who identify with the feminine gender based stereotype, more commonly called “expressiveness” (Spence & Helmreich, 1980), will tend to be more interpersonally oriented. Traits such as kindness, and awareness of the feelings of others are descriptive of those individuals who score high on the expressivity scale. These individuals will tend to self-select into situations where emotional regulation is more likely needed to maintain and nurture interpersonal relationships. Thus, individuals scoring high on identification with the feminine stereotype, or expressivity, would need to actively regulate emotions. This would lead them to use any available regulation strategy more often, including both deep and surface

acting strategies.

When considering the difficulty of performing emotional labor, however, the

prediction flips to the opposite direction. Those who identify strongly with the feminine

gender stereotype are supposed to be better at managing emotion (Hochschild, 1983) and

are doing it more often (Wharton & Erickson, 1993). As such, their self-regulatory skills

regarding emotion should be more efficient. This leads to a situation in which those who are identify strongly with the feminine gender stereotype will need to exert less effort in

order to regulate their emotional feelings or expressions, making deep or surface acting

easier.

H2a: Gender stereotype identification will be related to emotional labor such that

identification with the feminine stereotype will be positively related to frequency in

performing deep acting. Conversely, identification with the masculine stereotype will be negatively related to frequency in performing deep acting.

H2b: Gender stereotype identification will be related to emotional labor such that identification with the feminine stereotype will be negatively related to difficulty performing deep acting. Conversely, identification with the masculine stereotype will be positively related to difficulty in performing deep acting.

H2c: Gender stereotype identification will be related to emotional labor such that identification with the feminine stereotype will be positively related to frequency in performing surface acting. Conversely, identification with the masculine stereotype will be negatively related to frequency in performing surface acting.

H2d: Gender stereotype identification will be related to emotional labor such that identification with the feminine stereotype will be negatively related to difficulty in performing surface acting. Conversely, identification with the masculine stereotype will be positively related to difficulty in performing surface acting.

Affectivity

Affectivity is the tendency to experience a particular mood, and is split up into two distinct dimensions. Positive affectivity (PA) refers to having good feelings such as

joy, exhilaration and optimism, whereas negative affectivity (NA) refers to having bad feelings such as pessimism, anxiety, and disgust (Watson, Clark, & Tellegen, 1988).

Morris and Feldman (1996) predicted that when the emotional response desired was positive, as is the case in the present study, positive affectivity would reduce the amount of emotional dissonance present. Others have proposed that negative affectivity, on the other hand would increase the amount of emotional dissonance in that situation

(Abraham, 1998). Given that emotional dissonance is a direct result of surface acting, these predictions essentially assert that positive affectivity will reduce the need or frequency of surface acting, and negative affectivity will increase the frequency of surface acting.

Mixed support has been found for these propositions. For instance, Abraham

(1998, 1999) failed to find a significant antecedent relationship between negative affectivity and emotional dissonance, suggesting that negative affectivity did not impact the frequency of performing emotional labor. Jones (1998), however, found that positive affectivity reduced the amount of dissonance experienced when the display of positive emotions was required, indicating that positive affectivity was negatively related to the frequency of using surface acting; people who are naturally positive need to fake positive emotions less often.

Affective Events Theory (Weiss & Cropanzano, 1996) also lends insight into how affectivity will impact emotional labor. According to the theory, trait dispositions can influence the intensity of affective reactions to events that occur at work. As Grandey

(2000) noted, this means that persons who are high on negative affectivity may be more

reactive to negative events that may occur during the work day. In support of this,

Grandey, Tam and Brauburger (2002) found that in a diary study over two weeks, those who were high on negative affectivity reported having more negative events happen to them at work than those low on negative affectivity. Experiencing more negative events will result in a need for more frequent regulatory efforts to manage negative emotions that result. This means that negative affectivity should be positively related to both surface and deep acting.

For the difficulty of emotional labor, negative affectivity should make deep acting harder to perform, as a person who is continuously experiencing negative feelings will find it extremely difficult to try to actually feel the positive emotions required by the organization. There is no basis to expect a relationship between negative affectivity and the difficulty of performing surface acting; however the relationship will be explored.

H3a: Negative affectivity will be positively related to the frequency of using the deep acting method of emotional labor.

H3b: Negative affectivity will be positively related to the difficulty of using the deep acting method of emotional labor.

H3c: Negative affectivity will be positively related to the frequency of using the surface acting method of emotional labor.

A similar rationale can be applied to predictions for the relationship between positive affectivity and the different aspects emotional labor. Persons high on positive affectivity will not need to use regulatory strategies as often as those low on positive affectivity for several reasons. First, as they are naturally experiencing positive emotions

that are congruent with the organizational requirement, they will not need to do anything

to change that emotion; they are able to express genuine emotions and avoid emotional

regulation strategies. Secondly, persons high on positive affectivity will respond less

strongly to negative events in the workplace, again reducing the need to employ

emotional regulation strategies. Thus being high on positive affectivity should, in theory,

be negatively related to the frequency of both deep and surface acting. For deep acting,

however, as mentioned earlier, there may be no way for an individual to differentiate the

results of deep acting from the genuine expression of emotion. Thus, as a person high on

positive affectivity would tend to genuinely experience the positive emotions required by

the job, they would likely express that they were working toward actually feeling the

emotions required. Therefore, although in theory we would expect a negative relationship

between positive affectivity and the frequency of deep acting, since genuine emotion and deep acting are not practically separable in measurement, we instead would expect a positive relationship between the two variables.

In regards to the difficulty of performing deep acting, positive affectivity will make engaging in deep acting easier to perform as a person high on positive affectivity will be better suited to re-interpret a situation or conjure up positive emotions due to heightened accessibility of positive thoughts. Again, there is no basis to expect a relationship between positive affectivity and the difficulty of performing surface acting; however the relationship will be explored. This leads to the following hypotheses:

H4a: Positive affectivity will be positively related to the frequency of using the deep acting method of emotional labor.

H4b: Positive affectivity will be negatively related to the difficulty of using the

deep acting method of emotional labor.

H4c: Positive affectivity will be negatively related to the frequency of using the surface acting method of emotional labor.

Self-monitoring

Self-monitoring refers to the degree to which people pay attention to and control

the impression that they make on others (Snyder, 1974). Individuals high on self-

monitoring are very sensitive to emotional cues from others and will frequently adjust

their own outward emotional responses to suit the situation. On the other hand,

individuals low on self-monitoring are not as skilled at adapting their behavior to

changing situations and instead tend to express actual emotional responses regardless of

their appropriateness. This suggests that high self-monitors will perform emotional labor,

both deep and surface, more often than low self-monitors. As self-monitors are mostly

concerned with what others see, or the outward expression of emotion, it is evident that

surface acting would be the strategy of choice. However, as deep acting would also

achieve the goal of producing the correct emotional response, it is reasonable to expect

self-monitoring to also positively relate to the frequency of deep acting. Brotheridge and

Lee (2002) found support for a positive relationship between self-monitoring and the frequency of surface acting in a sample of service workers; however the frequency of deep acting was not related. Additionally in a recent study sampling university students employed in “people work” jobs, support was found for the positive relationship between self-monitoring and the frequency of surface acting, but not for a relationship between

self-monitoring and the frequency of deep acting (Diefendorff et al, 2005). Thus,

although self-monitoring is proposed to be related to the frequency of deep acting, this

relationship is expected to be smaller than the relationship between self-monitoring and

the frequency of surface acting.

For the difficulty of surface and deep acting, a person high on self-monitoring will likely find both strategies easier. First, he or she may be better able to identify the appropriate emotional response, and subsequently alter his or her response, reducing the resources required to perform the act of regulation. In addition, an individual who is low on self-monitoring will have a harder time suppressing their true emotions, which will make it more difficult to use either deep or surface strategies in order to express the appropriate emotion (Grandey, 2000). Thus, a negative relationship between self- monitoring and the difficulty of both surface and deep acting is expected. The strength of the relationship for deep and surface, however, may not be the same. High self- monitors tend to use external cues, such as the reactions of others, to guide their behavior modification, whereas low self-monitors tend to use more internal references, such as physiological reactions (Behncke, 2002). As deep acting requires more of an internal focus to effectively produce results, the advantage those high in self-monitoring have in recognizing the need for a change will not be as strong when the deep acting strategy is used. The above leads to the following predictions:

H5a: Self-monitoring will be positively related to the frequency of using the deep acting method of emotional labor.

H5b: Self-monitoring will be negatively related to the difficulty of using the deep

acting method of emotional labor.

H5c: Self-monitoring will be positively related to the frequency of using the surface acting method of emotional labor.

H5d: Self-monitoring will be negatively related to the difficulty of using the surface acting method of emotional labor.

H5e: For frequency, the relationship between self-monitoring and the surface acting method will be stronger than the relationship between self-monitoring and the deep acting method.

H5f: For difficulty, the relationship between self-monitoring and the surface acting method will be stronger than the relationship between self-monitoring and the deep acting method.

Emotional intelligence

Emotional intelligence has been defined as the “ability to monitor one’s own and others’ feelings and emotions, to discriminate among them, and to use this information to guide one’s thinking and actions” (Salovey & Mayer, 1990, p. 185). In other terms, emotional intelligence can be broken down into three parts: appraisal and expression of emotion, regulation of emotion, and utilization of emotion (Mayer & Salovey, 1993;

Schutte, Maulouff, Hall, Haggerty, Cooper, Golden, & Dornheim, 1998). Although it is a relatively new construct in the realm of intelligences, it has been differentiated from mental intelligence, and its use has been justified as a useful construct apart from other intelligences (Mayer & Salovey, 1993; Mayer, Salovey, & Caruso, 2000). Because

emotional regulation is a major component of this construct (Mayer & Salovey, 1995;

Salovey, Hsee, & Mayer, 1993) the lack of research in this area is especially surprising,

although it has been proposed as an antecedent (Grandey, 2000). It would be reasonable

to argue that if an individual was high on emotional intelligence, which incorporates the

use of emotional regulation strategies in its definition and measurement, then that

individual would tend to use emotional regulation strategies for the purpose of an

organization more often. A perspective from control theory helps clarify this expected

relationship. Dieffendorf and Gosserland (2003) suggested that the type of emotional

regulation strategy that will be employed may be based on weather the emotional event

that is occurring is anticipated or unexpected. Anticipated events, such as planning to

confront an unruly customer in the lobby, are more likely to generate a deep acting

strategy, because those events are known about in advance and can be prepared for prior

to the occurrence of an emotional reaction from the event. On the other hand, unexpected

emotional events, such as a customer approaching an employee with a complaint, would generate a surface acting strategy, as the emotional reaction may have already begun.

Since emotionally intelligent people are better able to anticipate emotional events, they will be able to use the deep acting strategy more often, and not have to use surface acting as often as a less emotionally intelligent individual. Thus it is expected that emotional intelligence will be positively related to the frequency of deep acting, but negatively related to the frequency of surface acting.

Only one study (Totterdell & Holman, 2003) has looked at emotional intelligence as an antecedent of emotional labor, and it found only a weak relationship between the

two. In their study, emotional intelligence predicted one aspect of the frequency of deep acting, an increase in use of positive refocus as a regulation strategy, but failed to show any relationship with the other indicators of the frequency of deep or surface acting.

As for the difficulty of both deep and surface acting, emotional intelligence should make both types easier to perform, as an emotionally intelligent person is interpreting emotional cues, deciphering the appropriate response and regulating his or her response, than will a less emotionally intelligent person. The better one is at these things, the easier emotional regulation, both deep and surface acting, for the purposes of an organization will be. As such the following hypotheses are proposed:

H6a: Emotional intelligence will be positively related to the frequency of using the deep acting method of emotional labor.

H6b: Emotional intelligence will be negatively related to the difficulty of using the deep acting method of emotional labor.

H6c: Emotional intelligence will be negatively related to the frequency of using the surface acting method of emotional labor.

H6d: Emotional intelligence will be negatively related to the difficulty of using the surface acting method of emotional labor.

Personality

Another surprising gap in the emotional labor literature is the lack of research involving relevant personality characteristics. Agreeableness is an obvious contender for an antecedent of emotional labor. Agreeableness is a personality trait that involves being compliant, cooperative and getting along with others (Carver & Scheier, 1996; Carlson,

1993). Agreeable persons tend to be described as kind, considerate, and empathetic.

(Tobin, Graziano, Vanman & Tssinary, 2000). It can be reasoned that a person who is consistently attempting to get along well with others and very concerned with keeping positive interpersonal relations would be frequently adapting emotional responses to fit the situation.

Tobin et al. (2000) showed support for the idea that persons high on agreeableness will use emotional regulatory strategies more often. In their study, undergraduate students read interpersonal scenarios that contained potentially emotional content, and then rated how much effort would be involved in controlling their emotions if they had to describe this event to another person. Their measure of effort asked if they would have to work at it controlling their emotions while describing the event, or in other words if they would have to perform some form of emotional regulation. Their measure of effort closely links to the frequency of performing emotional regulation. Participants who were high on agreeableness indicated that they would feel the need to regulate their emotions more often than those low on agreeableness. Diefendorff et al. (2005) suggested that persons high on agreeableness may recognize the negative impact of emotional displays that are not perceived as genuine, and thus would perhaps decide to avoid using the surface acting strategy of emotional labor. They found support for this negative relationship between the frequency of surface acting and agreeableness, and also found support for a positive relationship between the frequency of deep acting and agreeableness.

For the difficulty of emotional labor, there is reason to hypothesize that persons high on agreeableness would find both types of emotional labor less difficult to perform.

Agreeable people are constantly regulating their emotions in order to express emotions that are going to allow interpersonal interactions to go smoothly, thus they will have a great deal of practice under their belt, making it easier. Also, agreeable people may have a heightened ability to anticipate when the need for regulation may occur, so they can easily prepare for it. In Tobin et al.’s (2000) study, participants rated the degree to which they would anticipate an emotional reaction to the scenarios they read. Persons high on agreeableness indicated that they were more aware of potential emotional responses to the scenarios. This would lead to a prediction that agreeable persons are able to anticipate a need to alter their emotions, thus they would perceive the process as less difficult because it wouldn’t catch them off guard. This leads to the following hypotheses:

H7a: Agreeableness will be positively related to the frequency of using the deep acting method of emotional labor.

H7b: Agreeableness will be negatively related to the difficulty of using the deep acting method of emotional labor.

H7c: Agreeableness will be negatively related to the frequency of using the surface acting method of emotional labor.

H7d: Agreeableness will be negatively related to the difficulty of using the surface acting method of emotional labor.

Action-State Orientation

A final variable appears promising in the study of determinants of emotional

labor. Action-state orientation indicates a person’s goal striving technique, specifically the initiation and maintenance of goals (Kuhl, 1994). Action orientation refers to a person’s tendency to devote resources to the present task. This allocation of resources is

what allows an individual to attain a goal and move on to the next. An individual who is

action oriented is able to focus on the task at hand, and is not distracted by persisting

thoughts from other past or competing goals. A state oriented individual, on the other

hand, has trouble disconnecting from competing emotional or cognitive states, and often

has trouble blocking out thoughts and emotions which are non-task related (Diefendorff,

Hall, Lord, & Strean, 2000).

Although this variable was developed to explain motivational processes, it may

predict the amount of emotional labor in which an individual needs to engage. For an

action oriented individual, reinterpreting a situation, or volitionally changing one’s

emotional state will not be difficult; that individual will be able to shift focus onto the

goal of maintaining an organizationally sanctioned emotional response, regardless of

what has occurred previously, currently, or is anticipated to occur in the future. This will

result in action oriented individuals experiencing less difficulty in regulating emotional

feeling and expression for both deep and surface acting techniques than state oriented

individuals.

Action-state orientation will also impact how often regulation strategies need to

be employed. A state oriented person is going to be affected by negative events that may

have occurred in the past present or are thought to occur in the future, since they will not

be able to block them out. As a result, such individuals will have to continuously regulate emotional feelings and responses, as they will have to continually fight emotions lingering from other goals. Thus, state oriented individuals may need to use regulatory strategies, both deep and surface, more often to keep on track with the goal of displaying an organizationally appropriate response, than will action oriented individuals. This leads to the following hypotheses:

H8a: Action-state orientation will be related to emotional labor such that action oriented individuals will use emotional labor using the deep acting method less frequently than state-oriented individuals.

H8b: Action-state orientation will be related to emotional labor such that action oriented individuals will experience less difficulty using emotional labor using the deep acting method than state-oriented individuals.

H8c: Action-state orientation will be related to emotional labor such that action oriented individuals will use less emotional labor using the surface acting method less frequently than state-oriented individuals.

H8d: Action-state orientation will be related to emotional labor such that action oriented individuals will experience less difficulty using emotional labor using the surface acting method than state-oriented individuals.

In summary, expressivity, positive and negative affectivity, self-monitoring, emotional intelligence, agreeableness, and action-state orientation are expected to be related to the frequency and perceived difficulty of the deep and surface acting methods

of emotional labor. Deep and surface acting are then hypothesized to be related to emotional exhaustion.

This chapter has delineated the development of the theoretical and operational definitions of emotional labor, adding the component of perceived difficulty to the operational definition. It has also reviewed the literature regarding the outcomes of emotional labor, clarifying the difference between the outcomes of deep and surface acting components. Additionally, it has reviewed the situational and job feature antecedents of emotional labor. Finally, the dispositional antecedents of emotional labor were discussed, and hypotheses regarding each were made. A list of hypotheses can be found in Table 1.

Table 1

Summary of Hypotheses

Outcome Variables H1a: The frequency of using the surface acting method of emotional labor will be positively related to emotional exhaustion. The relationship between these variables will be stronger for surface than deep acting. H1b: The perceived difficulty of using the surface acting method of emotional labor will be positively related to emotional exhaustion. The relationship between these variables will be stronger for surface than deep acting. Dispositional Antecedents - Gender Stereotype Identification H2a: Gender stereotype identification will be related to emotional labor such that identification with the feminine stereotype will be positively related to frequency in performing deep acting. Conversely, identification with the masculine stereotype will be negatively related to frequency in performing deep acting. H2b: Gender stereotype identification will be related to emotional labor such that identification with the feminine stereotype will be negatively related to difficulty performing deep acting. Conversely, identification with the masculine stereotype will be positively related to difficulty in performing deep acting. H2c: Gender stereotype identification will be related to emotional labor such that identification with the feminine stereotype will be positively related to frequency in performing surface acting. Conversely, identification with the masculine stereotype will be negatively related to frequency in performing surface acting. H2d: Gender stereotype identification will be related to emotional labor such that identification with the feminine stereotype will be negatively related to difficulty in performing surface acting. Conversely, identification with the masculine stereotype will be positively related to difficulty in performing surface acting. Dispositional Antecedents - Negative Affectivity. H3a: Negative affectivity will be positively related to the frequency of using the deep acting method of emotional labor. H3b: Negative affectivity will be positively related to the difficulty of using the deep acting method of emotional labor. H3c: Negative affectivity will be positively related to the frequency of using the surface acting method of emotional labor. Dispositional Antecedents - Positive Affectivity. H4a: Positive affectivity will be negatively related to the frequency of using the deep acting method of emotional labor.

H4b: Positive affectivity will be negatively related to the difficulty of using the deep acting method of emotional labor. H4c: Positive affectivity will be negatively related to the frequency of using the surface acting method of emotional labor.

Table 1 Summary of Hypotheses Continued

Dispositional Antecedents - Self-monitoring. H5a: Self-monitoring will be positively related to the frequency of using the deep acting method of emotional labor. H5b: Self-monitoring will be negatively related to the difficulty of using the deep acting method of emotional labor. H5c: Self-monitoring will be positively related to the frequency of using the surface acting method of emotional labor. H5d: Self-monitoring will be negatively related to the difficulty of using the surface acting method of emotional labor. H5e: For frequency, the relationship between self-monitoring and the surface acting method will be stronger than the relationship between self-monitoring and the deep acting method. H5f: For difficulty, the relationship between self-monitoring and the surface acting method will be stronger than the relationship between self-monitoring and the deep acting method. Dispositional Antecedents - Emotional Intelligence H6a: Emotional intelligence will be positively related to the frequency of using the deep acting method of emotional labor. H6b: Emotional intelligence will be negatively related to the difficulty of using the deep acting method of emotional labor. H6c: Emotional intelligence will be negatively related to the frequency of using the surface acting method of emotional labor. H6d: Emotional intelligence will be negatively related to the difficulty of using the surface acting method of emotional labor. Dispositional Antecedents - Agreeableness. H7a: Agreeableness will be positively related to the frequency of using the deep acting method of emotional labor. H7b: Agreeableness will be negatively related to the difficulty of using the deep acting method of emotional labor. H7c: Agreeableness will be negatively related to the frequency of using the surface acting method of emotional labor. H7d: Agreeableness will be negatively related to the difficulty of using the surface acting method of emotional labor. Dispositional Antecedents - Action-State Orientation. H8a: Action-state orientation will be related to emotional labor such that action oriented individuals will use emotional labor using the deep acting method less frequently than state- oriented individuals. H8b: Action-state orientation will be related to emotional labor such that action oriented individuals will experience less difficulty using emotional labor using the deep acting method than state-oriented individuals. H8c: Action-state orientation will be related to emotional labor such that action oriented individuals will use less emotional labor using the surface acting method less frequently than state-oriented individuals. H8d: Action-state orientation will be related to emotional labor such that action oriented individuals will experience less difficulty using emotional labor using the surface acting method than state-oriented individuals

CHAPTER III

METHODS

Participants and Procedure

One hundred ninety eight participants were recruited from retail branches of a large coffee company. The area surveyed included Montana, Wyoming, Colorado, and

Utah. All participants received a packet of surveys to fill out. Each survey packet was accompanied by a cover letter explaining the purpose of the survey, the importance of the research, and instructions on how to complete the surveys. It also thanked the participant in advance for his or her cooperation.

Forty of these participants were obtained by distributing packets of surveys through district managers to stores. The surveys were accompanied by a note asking employees to take a survey home, fill it out, and mail it back in the enclosed self- addressed and stamped envelope. Four hundred surveys were initially given to district managers, with a 10% response rate. The other 158 surveys were obtained by going into retail locations and asking employees to fill out the surveys. These employees were paid for their time. One-hundred percent (100%) of the employees asked to fill out the survey in store agreed to do so.

Of the participants, the mean age was 25.99, with a range of 18-58. One hundred and twenty seven (127), or 64% of the participants were female, and three declined to answer the gender question. Fifty eight percent of the participants reported their job

position as entry level, 39% reported their position as shift supervisor, and 3% reported

their position as assistant store manager. As the number of assistant store managers was

small, shift supervisors and assistant managers were grouped together as management

employees. No store managers filled out surveys. For tenure, 27.3% of the sample had been an employee at their current job for less than six months, 17.2% had been in position six months to one year, 21.2% had been in position one to two years, 14.6% had

been in position two to three years, and 19.7 % had been in position over three years.

The average hours worked per week by the participants was 28.35, with a range of 8-45.

Measures

Demographic variables. Participants were asked to provide demographic information such as age, gender, tenure, average number of hours per week, and job title.

No other data was collected that could have allowed for the identification of individual respondents.

Emotional exhaustion was measured using the 7-point Likert scale (0 = never, 6 = everyday) extracted with permission from the Maslach Burnout Inventory (MBI)

(Maslach, et al., 1996). This scale consists of 9 items that ask participant to indicate how often they feel particular ways about work. Due to contractual obligations, sample items cannot be reproduced here, but can be found in the Maslach Burnout Inventory. The internal consistency of this scale in this sample was .90.

Self-report job performance was measured with one item asking participants to rate their overall performance at work using the same three point scale that the company used to conduct performance evaluations (1 = needs improvement, 2 = meets

expectations, and 3 = consistently exceeds expectations.) The mean response to this item was 2.33 (SD = .54).

Emotional labor was measured by a modified version of the scale developed and tested by Grandey (1999). This scale consists of six items asking participants to respond on a 5-point Likert scale (1= never, 5 = always) to items asking “in order to do your job

effectively on an average work day, how often do you …?” The first factor measures surface acting, and is made up of three items: “just pretend to have the emotions I need to

display for my job,” “put on a ‘show’ or ‘performance’” and “put on a ‘mask’ in order to

express the right emotions for the job.” The second factor measures deep acting, and

consists of three items: “make an effort to actually feel the emotions that I need to display

toward others,” “work hard to feel the emotions that I need to show to others,” and “try to

actually experience the emotions that I must show.” Grandey reported internal

reliabilities for these three factors to be .90 for surface and .80 for deep. This sample

resulted in slightly lower, but acceptable internal consistencies (alpha = .87 for surface,

alpha = .78 for deep).

Grandey’s scale asked respondents how often they perform various surface and

deep acting behaviors. As stated earlier it was believed that this measure was missing an

important component, perceived difficulty. In order to add perceived difficulty as a

measure of emotional labor an additional six items were added to the scale. The six items

asked respondents “At work, how difficult is it to….?” for each behavior on Grandey’s

original scale. Participants were asked to rate each item on a 5 point Likert Scale (1 = very difficult, 5 = very easy). The internal consistencies for these scales were .90 for

surface and .90 for deep. For analyses, all responses were reverse coded so that higher

scores indicated higher difficulty.

Gender role identification was measured by the Personal Attributes Questionnaire

(Spence & Helmreich, 1978), which asks participant to rate themselves using a 5- point scale on 16 pairs of contradictory characteristics. This scale measures identification with

the masculine and feminine gender roles in two separate subscales. The internal

consistencies for the two subscales were .71 for masculinity and .75 for femininity.

Positive and negative affectivity were measured using the Positive and Negative

Affectivity Schedule (PANAS) developed by Watson, Clark and Tellegen (1988). This measure considers positive affectivity and negative affectivity as two separate dimensions, however it has been noted that these two dimensions are more independent at the high ends of each pole (Weiss & Cropanzano, 1996). This measure asks respondents to rate the extent to which they have felt certain emotions in the past few weeks. Each of the 20 emotion words is rated on a 5- point scale (1= very slightly or not at all, 5 = extremely). The internal consistency of the positive affectivity (PA) scale was .86 in this sample, negative affectivity (NA) was .78.

Self-monitoring was measured using Snyder and Gangestad’s (1986) 18-item

scale. Each item asks respondents to indicate whether each item is true or false. The

internal consistency of this scale was alpha = .73.

Emotional intelligence. While there are many different measures of emotional intelligence that have been developed since the introduction of the construct, the measure by Schutte et al. was used for this study (Schutte, Malouff, Hall, Haggerty, Cooper,

Golden, & Dornheim, 1998). This measure is based on the original conceptualization of

emotional labor as developed by Salovey and Mayer (1990), and unlike competing

measures such as the Trait Meta Mood Scale, it covers all three components of the emotional intelligence definition. This measure consists of 33 items rated on a 5-point

Likert scale which asked participants to rate the extent to which each item described them

(1 = strongly disagree, 5 = strongly agree). Thirteen items represent the appraisal and

expression of emotion dimension, 10 items represent the emotional regulation dimension,

and 10 items represent the utilization dimension. This scale was validated by Schutte et

al. (1998), and demonstrated adequate discriminant and convergent validity. In this

sample, the 33-item scale had an internal consistency coefficient of .86.

Personality. Agreeableness was measured using the 10 item scale developed by

Goldberg (1999). This scale has been tested and validated intensively and is a

satisfactory equivalent of other scales such as the well known NEO-PI (Buchanan,

Goldberg, & Johnson, 1999; Goldberg, 1999). The internal consistency of these 10 items

in this sample was alpha = .80.

Action-state orientation was measured by the revised version of Kuhl’s (1994)

scale (Diefendorff, Hall, Lord, & Strean, 2000). This version is a three factor scale

consisting of a total of 22 dichotomous items. The first of the three factors is

preoccupation, referring to the tendency to continue to process information related to a

certain goal. Action oriented individuals are able to disengage from this information

processing in order to concentrate on the goal at hand. Eight items measure this factor,

with an alpha in this sample of .70. Hesitation is the second dimension; it refers to the

degree to which an individual will take initiative and start action on a goal, or hesitate to begin. Eight items measured this factor with an internal consistency of .77. The final factor is volatility and taps the degree of persistence toward a goal, action oriented individuals are able to focus efforts on the goal at hand without being distracted. Six items measured this factor with a rather low internal consistency of .59. The internal consistency for the volatility scale was actually higher than the internal consistency found in Diefendorff et al. (2000) which was .51. All scales were coded so that high scores indicate higher action orientation.

CHAPTER IV

RESULTS

First a factor analysis of the emotional labor scale was conducted in order to determine if perceived difficulty and frequency were indeed separate factors of the emotional labor. This analysis was carried out using principal axis factoring. Next the hypotheses were tested using both bivariate correlational analysis and regression analysis.

Factor analysis of emotional labor scale

An exploratory factor analysis was performed on the 16 emotional labor items using the principal axis factoring extraction method with Varimax rotation (see Table 2).

Four factors emerged with eigenvalues greater than one. The first explained 30% of the variance, and the five items intended to measure the difficulty of surface acting all loaded on this factor, loadings ranged from .65 to .85. The second factor explained 23% of the variance, and had the five items intended to measure the frequency of surface acting loading on it. Item loadings ranged from .59 to .80. The third factor explained 12% of the variance and had the three items intended to measure the difficulty of deep acting loading on it. Item loadings ranged from .75 to .88. The final factor had the three items intended to measure the frequency of deep acting loading on it, it explained 7% of the variance. The item loadings ranged from .67 to .92. Similar results were found in a factor analysis of these 16 items using Promax rotation, as well as when the number of factor were specified to be four.

Table 2

Exploratory Factor Analysis with Varimax Rotation on Emotional Labor Items

Variable Factor 1 Factor 2 Factor 3 Factor 4

Surface, Frequency

Act -.17 .77* .00 .00

Fake -.12 .80* .00 .00

Show -.29 .59* .10 .12

Pretend -.12 .77* .22 .00

Mask -.25 .68* .25 .00

Deep, Frequency

Experience -.12 .00 -.16 .67*

Effort .00 .00 -.15 .92*

Work hard .00 .11 .00 .63*

Surface, Difficulty

Act .65* -.17 .19 .00

Fake .77* -.21 .13 .00

Show .78* -.20 .11 .00

Pretend .82* -.16 .00 -.12

Mask .85* -.15 .00 -.12

Deep, Difficulty

Experience .00 .24 .80* -.16

Effort .17 .13 .88* -.19

Work hard .23 .17 .75* -.19

Note: N = 185, * Highest loading, see Appendix A for items

The factor analysis demonstrated that the variables of frequency and difficulty were

indeed separate components of emotional labor. The correlation between the frequency

of surface acting and the difficulty of surface acting summary scores was -.39 (p < .01),

and the correlation between the frequency of deep acting and the difficulty of deep acting summary scores was -.31 (p < .01). Although the frequency of performing each type of emotional labor was negatively related to the difficulty in performing it, they were distinct components of emotional labor.

Hypotheses testing

All hypotheses were tested first using bivariate correlation analysis, and secondly, as a more stringent test of those relationships, with hierarchical regression. All correlations, means and standard deviations are reported in Table 3.

Hypothesis 1: Emotional Labor and Emotional Exhaustion

H1a proposes a positive relationship between frequency of emotional labor and emotional exhaustion. There was significant positive bivariate correlation between frequency of surface acting and emotional exhaustion (r = .30, p < .01). The correlation between frequency of deep acting and emotional exhaustion was not significant (r = -.10, p = .16), and was negative. H1b proposes a positive relationship between difficulty of emotional labor and emotional exhaustion. Contrary to the hypothesis, the bivariate correlation between difficulty of surface acting and emotional exhaustion was not significant (r = .10, p = .18). The correlation between difficulty of deep acting and emotional exhaustion, however, was significant (r = .32, p < .01).

** .90 7

- -

.01, EL = Emotional Labor, EI = Emotional Intelligence, EE = Emotional Exhaustion Exhaustion Emotional EE = Intelligence, =Emotional EI Labor, = Emotional EL .01, # Variable Mean SD SD 1 Variable 2 Mean 3 4 5 6 7 8 9 21 20 19 17 18 16 15 14 13 12 11 10 ivariate Correlation Matrix of Study Variables Variables Study of Matrix Correlation ivariate 3. Tenure 2.82 1.48 .06 .08 - - .08 .06 - 1.48 8.29 2.82 25.99 Age - .30** Tenure -.08 .04 - .61** 8.00 28.35 .44** worked 1. .05 .08 title Gender 2. .50 Hours .42 3. Job -.09 -.08 4. -.04 .14 deep 2.64 .09 10.34 .09 .65 .78 5. Freq, .48 surface Freq, EL 6. EL .12 13.58 7. 3.17 3.98 .07 -.15* .06 .15* 23.23 -.18* .06 .71 surface .10 Diff, EL 8. .01 -.09.03 -.21** .17* .75 PAQ .14 -.03 .01 -.14 -.12 -.18* .20** .11 3.77 25.38 12.22 PAQ deep Diff, EL 9. Masculine -.04 4.64 Feminine 10. .14* 7.78 .12 NA 11. .18* -.13 .78 3.02 -.21** .06 .19** -.04 .15* -.08 12. -.04 .33** -.06 .03 .08 -.01PA .06 5.37 17.20 .03 .87 13. .12 .11 .14* .70 -.17* -.02 .24** 14. Self-monitoring 35.00 6.94 EI -.23** .13 .06 -.06 .00 36.95 .33** .03 -.06 -.11 -.01 15. .06 -.07 -.04 -.19** -.01 .00 -.08 .86 Agreeableness .25** 5.22 .18* 39.41 -.05 -.29** .35** -.17* .09 .05 -.23** -.02 .24** -.34** .02 .24** .80 4.10 .09 -.28** -.39** 2.15 -.07 .01 -.21** -.12 -.10 .19** .20** 11.44 .45** -.10 .03 12.72 Preoccupation 127.30 16. .06 -.15* -.09 -.27** .34** .14 .04 .09 -.25** .86 .12 .39** .34** -.10 -.11 .21** -.16* -.16* 17. Volatility .90 .27** .03 -.17* .06 1.35 .04 -.07 -.11 -.04 -.05 -.07 .06 .06 -.15* -.12 10.84 .02 .07 .08 .10 .06 -.08 .13 18. .09 -.31** .08 -.09 .59 .11 .18* -.06 .02 .15* .09 .12 -.05 .14 -.01 .06 -.01 Hesitation .22** - .18* .16* .54 2.33 .25** performance .07 19. 12.86 2.36 EE .13 -.15* -.01 .90 -.02 -.05 -.25** .05 Job 20. .25** .46** -.13 .07 -.01 -.34** .26** -.04 -.33** .14 .23** .45** .7 -.18* .34** 21. 10.49 18.39 .30** -.22** -.11 -.29 .07 .26** -.10 .23** .24** -.28** .17* -.34** -.16* .10 .23** .32** -.07 -.23** -.03 **p p<.05, * Note: -31** .08 -.11 .08 .15* .00 .70 Table 3 B 57

Regression analyses were then performed to test the relationships among these

variables (see Table 4). Because the level of responsibility associated with job level likely impacts the amount of emotional exhaustion experienced, job title was controlled for on step one and explained 6% of the variance in emotional exhaustion ()R2 = .064, F

= 12.99, p < .01). Frequency of surface acting and frequency of deep acting were entered

on step two, and they explained an additional 9% of the variance ()R2 = .086, F = 9.60, p

< .01; surface, $ = .27, p < .01; deep, $ = -.14, p = .04). These results support H1a.

Because it was desired to know how perceived difficulty of each component of emotional labor would predict emotional exhaustion above and beyond the frequency of emotional labor, the difficulty components of emotional labor were entered after controlling for the frequency components of emotional labor. Adding difficulty of surface acting and difficulty of deep acting on step three of the regression equation added

6% to the explanation of variance ()R2 = .056, F = 6.54, p < .01). In the final model,

however, only the frequency of surface acting and the difficulty of deep acting remained

significant (frequency surface $ = .28, p < .01, difficulty deep $ = .16, p = .04). Thus,

there was partial support for H1b.

The addition of the difficulty component to emotional labor adds predictive

ability above and beyond the frequency of emotional labor. It is also possible that there

could be an interaction effect on the outcome variable of emotional exhaustion. This was

tested separately for surface acting and deep acting using hierarchical regression;

however no interaction effects were found for frequency and difficulty of emotional labor

on the outcome variable of emotional exhaustion.

Table 4

Hierarchical Regression Predicting Emotional Exhaustion (N = 193)

Variable $i $f )R2 )F

Step 1: Job title .25** .19** .064 12.99**

Step 2: Frequency .086 9.60**

Surface .27** .28**

Deep -.14* .07

Step 3: Difficulty .056 6.54**

Surface .15

Deep .16*

Note: $i initial entry coefficient, $f final model coefficient, * p < .05, **p < .01

Antecedents of Emotional Labor

For each dispositional antecedent variable, both bi-variate correlational analyses

and hierarchical regression were used to test each hypothesis. For each regression

equation, the demographic control variables of age, gender, tenure, average hours worked

per week and job title were entered on step one. These demographic variables are

antecedents of emotional labor, and thus were controlled for (see Figure 1). For the

frequency of deep acting, the difficulty of deep acting, and the difficulty of surface acting

none of the control variables explained a significant amount of variance in the regression

equations. For the frequency of surface acting, however, the demographic control

variables explained 10% of the variance. Each antecedent variable was entered in a

separate equation on step two. The results are reported below.

Hypothesis 2: Gender stereotype identification and emotional labor. H2a looks at the relationship between gender stereotype identification and the frequency of performing deep acting. There was a significant bivariate correlation between identification with the feminine gender stereotype and frequency of deep acting (r = .17 p = .02). The correlation between identification with the masculine gender stereotype and frequency of deep acting was also significant (r = .15, p = .04), but in the opposite direction than predicted. Regression analyses were then performed to create a more stringent test of the relationship between these variables (see Table 5). Identification with the masculine gender stereotype and with the feminine gender stereotype were added together on step two. Together they added a significant 6% explanation of variance ()R2 = .057, F = 5.79,

p < .01). Both the feminine and masculine gender stereotype coefficient were significant,

however the masculine gender stereotype coefficient was in the opposite direction than

predicted (feminine $ = .19, p < .01, masculine $ = .16, p = .03). Hypothesis H2a was

partially supported.

H2b looks at the relationship between gender stereotype identification and the

difficulty of performing deep acting. The bivariate correlation between identification

with the feminine gender stereotype and difficulty of deep acting was not significant (r =

-.09, p = .23). The correlation between identification with the masculine gender

stereotype and difficulty of deep acting was significant (r = -.18, p = .02) but in the

opposite direction than predicted. Hypothesis H2b was not supported by correlational

analysis. Hierarchical regression did show some support for the hypothesis (see Table 5).

Masculine and feminine gender stereotype identification were entered on step two of the

regression, and 4% of the variance was explained above the controls ()R2 = .037, F =

3.61, p = .03); only the coefficient for masculine identification was significant and it was

in the opposite direction than predicted ($ = -.17, p = .02). Hypothesis 2b was not

supported.

H2c looks at the relationship between gender stereotype identification and the

frequency of performing surface acting. The bivariate correlation between identification

with the feminine gender stereotype and frequency of surface acting approached

significance (r = -.14, p = .052), but it was in the opposite direction than predicted. The correlation between identification with the masculine gender stereotype and frequency of surface acting was significant (r = -.21, p < .01), and in the correct direction. Regression analyses showed similar results (see Table 5). Adding masculine and feminine gender stereotype identification on step two, explained a significant 6% of variance ()R2 = .056,

F = 6.08, p < .01), but only the masculine gender stereotype coefficient was significant ($

= -.22, p < .01). Hypothesis H2c was partially supported.

H2d looks at the relationship between gender stereotype identification and the

difficulty of performing surface acting. The bivariate correlation between identification

with the feminine gender stereotype and difficulty of surface acting was not significant (r

= .01, p = .91). The correlation between identification with the masculine gender stereotype and difficulty of deep acting also was not significant (r = -.10, p = .45).

Regression analyses also failed to find a significant relationship between gender

F ) 2 R ) f $ i $ F ) 2 R ) f $ i $ .01 # F ) 2 * p<.05, **p *

R ) f $ i $ .034 1.30 .099 4.06** .024 .91 .024 4.06** .099 1.30 .034

F ) coefficient at final model, at final coefficient f $ 2 R ) .09 .07 .06 .05 .06 .05 .05 .06 .05 .06 .07 .09

f $ Frequency Deep Difficulty Deep Frequency Surface Difficulty Surface i $ .050 1.93 .050 Age -.03 -.06 Age -.05 -.07 -.17* -.20** .12 .12 Hours .13 .14 .00 .00 .20* .20* -.11 -.11 -.11 -.11 .20* .20* .00 .00 .14 .13 Hours coefficient at initial entry, entry, at initial coefficient Tenure -.16* Tenure -.13 i Gender -.07 -.08 .10 .10 .02 .00 .01 .02 .02 .01 .00 .02 .10 .10 -.08 -.07 Gender Job title .10 .06 title .11 .08 Job .04 .08 .02 .02

$ Table 5 Hierarchical Regression PredictingEmotional Labor from PAQ 190) (N = Variable Step 1 Demographics .03 2 -.22** -.03 Step -.17* -.11 .16* Masculine -.10 Feminine .19** .057 5.79** Note: .037 3.61* 6.08** .056 .001 .140

stereotype identification (see Table 5). Adding identification with the masculine and feminine gender stereotypes on step two did not add significant explanation of variance.

Hypothesis H2d was not supported.

To summarize, feminine gender stereotype identification was positively related to the frequency of deep acting, but unrelated to the other three components of emotional labor. Masculine gender stereotype identification was positively related to the frequency of deep acting, negatively related to the difficulty of deep acting and the frequency of surface acting, and unrelated to the difficulty of surface acting.

Hypothesis 3: Negative affectivity and emotional labor. H3a predicts a positive relationship between negative affectivity and the frequency of using deep acting. The bivariate correlation between these two variables was not significant (r = -.08, p = .25).

Regression analyses also failed to support H3a (see Table 6). The addition of negative affectivity to the model in step two did not add any significant explanation of variance.

H3a was not supported.

H3b predicts a positive relationship between negative affectivity and the difficulty of using deep acting. The bivariate correlation between these two variables was significant (r =.19, p < .01), supporting H3b. Regression analyses also provide support for H3b (see Table 6). The addition of negative affectivity to the model in step two added a significant 3% of explanation of variance of the difficulty of deep acting ()R2 =

.031, F = 6.03, p = .02), the coefficient for negative affectivity was significant ($ = .18, p

= .02). H3b was supported.

F ) 2 R ) f $ i $ F ) 2 R )

f $ i .01 $ # F ) * p<.05, **p * 2

R ) f $ i $ .18* .031 6.03* .29** .083 18.50** .00 .000 .003 .000 .00 1.30 .034 18.50** .083 4.06** .099 .29** 6.03* .914 .024 .031 .18*

F ) coefficient at final model, at final coefficient f $ 2 R ) .014 2.76

f $ Frequency Deep Difficulty Deep Frequency Surface Difficulty Surface i $ .05 1.93 .05 -.12 Age -.03 -.04 Age -.07 -.06 -.18** -.20** .12 .12 coefficient at initial entry, entry, at initial coefficient i Hours .13 .14 Hours .00 -.02 .20* .18* -.11 -.11 Tenure -.16* -.17* Tenure .09 .09 .06 .08 .06 .06 $ -.07 -.06 Gender .10 .10 .02 .01 .01 .01 Job title .10 .11 title .08 .07 Job .04 .02 .02 .02 Table 6 Table = 190) (N Affectivity Negative from Labor Emotional Predicting Regression Hierarchical Variable 1 Step Demographics 2 Step Negative affectivity Note:

H3c predicts a positive relationship between negative affectivity and the frequency of using surface acting. The bivariate correlation between these two variables was significant (r = .33, p < .01), supporting H3c. Regression analyses also support H3c

(see Table 6). The addition of negative affectivity to the model in step two added an additional 8% of explanation of variance ()R2 = .083, F = 18.50, p < .01). The coefficient for negative affectivity was significant ($ = .29, p < .01). Hypothesis H3c was supported.

In addition to the hypotheses regarding negative affectivity, the relationship between negative affectivity and the difficulty of using surface acting was explored. The bivariate correlation between these two variables was not significant (r = -.04, p = .59).

Regression analyses also failed to show support for a significant relationship between negative affectivity and the difficulty of surface acting (see Table 6). The addition of negative affectivity to the model on step two did not add any additional explanation of variance.

In summary, negative affectivity was positively related to the difficulty of deep acting and to the frequency of surface acting, but unrelated to the other two components of emotional labor

Hypothesis 4: Positive affectivity and emotional labor. H4a predicts a negative relationship between positive affectivity and the frequency of using deep acting. The bivariate correlation between these two variables was significant (r = .18, p = .01), but it was in the wrong direction. Regression analyses also showed a significant relationship between positive affectivity and the frequency of using deep acting, in the opposite

direction than predicted (see Table 7). The addition of positive affectivity to the model in

step two added an additional 4% of explanation of variance to the model above the control variables ()R2 = .041, F = 8.26, p < .01); the coefficient for positive affectivity

was significant, but in the opposite direction than predicted ($ = .20, p < .01). H4a was

not supported.

H4b predicts a negative relationship between positive affectivity and the difficulty

of performing deep acting. The bivariate correlation between these two variables was

significant (r = -.34, p < .01), supporting H4b. Regression analyses also provide support

for H4b (see Table 7). The addition of positive affectivity to the model in step two added

an additional 10% of explanation of variance above the control variables ()R2 = .103, F =

21.85, p < .01), the coefficient for positive affectivity was significant ($ = -.32, p < .01).

Hypothesis H4b was supported.

H4c predicts a negative relationship between positive affectivity and the frequency of using surface acting. The bivariate correlation between these two variables was significant (r = -.29, p < .01), supporting H4c. Regression analyses also support H4c

(see Table 7). The addition of positive affectivity to the model on step two added an additional 5% of explanation of variance above the control variables ()R2 = .049, F=

10.63, p < .01). The coefficient for positive affectivity was significant ($ = -.22, p < .01).

Hypothesis H4c was supported.

The relationship between positive affectivity and the difficulty of using surface

acting was also explored. The bivariate correlation between these two variables was not

significant (r = -.02, p = .80). Regression analyses also did not show a relationship

F ) 2 R ) f $ i $ F ) 2 R ) f $ i $ .01 # F ) * p<.05, **p p<.05, *

2 R ) f $ i $ .034 1.30 .099 4.06** .91 1.30 4.06** .024 .034 .099

F ) coefficient at final model, at final coefficient f $ 2 R ) f $ Frequency Deep Frequency Difficulty Deep Surface Frequency Surface Difficulty i $ .050 1.93 .050 .20** .041 8.26** -.32** .103 21.85** -.22** .049 10.63** -.08 .006 1.20 Age -.03 -.05 Age -.05 -.07 -.18** -.20** .12 .12 coefficient at initial entry, entry, at initial coefficient i

Hours .13 .15 Hours -.03 .00 .19* .20* -.11 -.11 7 Tenure -.16* -.16* Tenure .09 .08 .06 .06 .06 .05 $ Gender -.07 -.06 Gender .10 .10 .02 .01 .01 .01

Job title .10 .11 title .07 .08 Job .04 .04 .02 .02 Table Variable 1 Step Demographics 2: Step Positive Affectivity Note: Hierarchical Regression Predicting Emotional Labor from Hierarchical from Positive = Labor Emotional Predicting(N 191) Regression Affectivity

between positive affectivity and the difficulty of using surface acting (see Table 7).

Adding positive affectivity to the model on step two did not add any additional explanation of variance beyond the control variables.

In summary, positive affectivity was positively related to the frequency of deep acting, negatively related to the difficulty of deep acting and the frequency of surface

acting, and unrelated to the difficulty of surface acting

Hypothesis 5: Self-monitoring and emotional labor. H5a predicts a positive

relationship between self-monitoring and the frequency of using deep acting. The

bivariate correlation between these two variables was not significant (r = -.06, p = .44).

Regression analyses also failed to show a significant relationship between self-

monitoring and the frequency of using deep acting (see Table 8). The addition of self-

monitoring to the model on step two did not add a significant amount of explanation of

variance over the control variables. H5a was not supported.

H5b predicts a negative relationship between self-monitoring and the difficulty of

using deep acting. The bivariate correlation between these two variables was not

significant (r = .08, p = .29). Regression analyses also failed to provide support for H5b

(see Table 8). The addition of self-monitoring to the model on step two did not account

for a significant amount of variance above the control variables. Hypothesis H5b was not

supported.

H5c predicts a positive relationship between self-monitoring and the frequency of

using surface acting. The bivariate correlation between these two variables was

significant (r = .27, p < .01), supporting H5c. Regression analyses also support H5c (see

F ) 2 R ) f $ i $ F ) 2 R ) .06 .12

$ i .01 $ # F ) * p<.05, **p p<.05, *

2 R ) f $ i $ .034 1.32 .100 4.14** .93 1.32 4.14** .024 .034 .100 + F ) coefficient at final model, at final coefficient f $ 2 R ) .09 .08 .06 .05 .06 .07 .07 .06 .05 .08 .06 .09

f $ Frequency Deep Deep Frequency Deep Difficulty Surface Frequency Surface Difficulty i $ -.08 .005 1.03 .07 .005 .93 .22** .041 8.81** -.25** .054 10.86** 10.86** .054 1.92 -.25** .049 8.81** .041 .22** .93 .005 .07 1.03 .005 -.08 Age -.03 Age -.05 -.07 -.05 -.20** -.14* coefficient at initial entry, entry, at initial coefficient i Hours .13 .13 .01 .01 .19* .19* -.10 -.10 Tenure -.16* Tenure -.16 $ -.06 Gender -.08 .11 .13 .01 .05 .02 -.03 Job title title Job .10 .10 .06 .06 .06 .05 .02 .03 Table 8 Hierarchical from Self-monitoring 192)Labor = Emotional Predicting Regression (N Variable 1 Step Demographics 2: Step Self- monitoring Note:

Table 8). The addition of self-monitoring to the model on step two added an additional

4% of explanation of variance above the control variables ()R2 = .041, F = 8.81, p < .01).

The coefficient for self-monitoring was significant ($ = .22, p < .01). Hypothesis H5c

was supported.

H5d predicts a negative relationship between self-monitoring and the difficulty of

using surface acting. The bivariate correlation between these two variables was

significant (r = -.27, p < .01). Regression analyses also showed a relationship between

self-monitoring and the difficulty of using surface acting (see Table 8). The addition of

self-monitoring to the model on step two added an additional 5% explanation of variance

above the control variables ()R2 = .054, F = 10.86, p < .01). The coefficient for self-

monitoring was significant ($ = -.25, p < .01). Hypothesis H5d was supported.

H5e proposed that the relationship between the frequency of emotional labor and self-monitoring would be stronger for surface acting than for deep acting. This was supported; there was a significant relationship between the frequency of surface acting and self-monitoring but not for the frequency of deep acting.

H5f was supported a well. There was a significant relationship between the

difficulty of surface acting and self-monitoring, but not for the difficulty of deep acting and self-monitoring.

In summary, self-monitoring was unrelated to both the frequency and difficulty of deep acting. Self-monitoring was positively related to the frequency of surface acting, and negatively related to the difficulty of surface acting.

Hypothesis 6: Emotional intelligence and emotional labor. H6a predicts a

positive relationship between emotional intelligence and the frequency of using deep

acting. The bivariate correlation between these two variables was significant (r = .21, p <

.01). Regression analyses also supported significant positive relationship between

emotional intelligence and the frequency of using deep acting (see Table 9). The addition

of emotional intelligence to the model on step two added an additional 4% of explanation

of variance above the control variables ()R2 = .043, F = 8.56, p < .01); the coefficient for

emotional intelligence was significant ($ = .21, p < .01). H6a was supported.

H6b predicts a negative relationship between emotional intelligence and the

difficulty of using deep acting. The bivariate correlation between these two variables was

significant (r = -.16, p = .03). Regression analyses also found a negative relationship

between emotional intelligence and the difficulty of using deep acting (see Table 9). The

addition of emotional intelligence to the model on step two added an additional 3% of

explanation of variance above the control variables ()R2 = .032, F = 6.32, p = .01); the

coefficient for emotional intelligence was significant ($ = -.18, p = .01). Hypothesis H6b was supported.

H6c predicts a negative relationship between emotional intelligence and the frequency of using surface acting. The bivariate correlation between these two variables was not significant (r = -.11, p = .13), but it was in the right direction. Regression analyses did not provide any support for H6c (see Table 9). The addition of emotional intelligence to the model on step two did not add any significant explanation of variance.

Hypothesis H6c was not supported.

F ) 2 R ) f $ i $ -.11 .011 2.07 .011 -.11

F ) 2 R

) .013 2.74 f $ i .01 $ # F ) * p<.05, **p p<.05, *

2 R ) .02 .01 .03 .03 f

$ i $ F ) coefficient at final model, at final coefficient f $ 2 R ) f $ -.12 .06 -.12 .09 .03 .05 .04 .06 Frequency Deep Deep Frequency Deep Difficulty Surface Frequency Surface Difficulty

i $ .048 1.83 .035 1.31 .096 3.88** .025 .96 .025 3.88** .096 1.31 .035 1.83 .048 -.12 6.32* .032 -.18* 8.56** .043 .21** Age -.03 -.03 -.07 -.07 -.19** -.19** .11 -.07 .11 -.19** -.03 -.07 -.03 -.19** Age coefficient at initial entry, entry, at initial coefficient i Hours .13 .14 .01 .00 .19* .18* -.11 -.11 .00 -.11 .14 .18* .13 .01 -.11 .19* Hours Tenure -.16 Tenure $ -.06 Gender -.07 .12 .13 Job title .10 .05 .10 .05 .10 .06 .10 .07 title .05 .03 Job Table 9 189) from Emotional Hierarchical= Labor IntelligenceEmotional (N Predicting Regression Variable 1 Step Demographics 2: Step Emotional Intelligence Note:

H6d predicts a negative relationship between emotional intelligence and the

difficulty of using surface acting. The bivariate correlation between these two variables

was not significant (r = -.10, p = .18), but it was in the right direction. Adding emotional

intelligence to the regression analyses on step two did not add any additional explanation of variance (see Table 9). Hypothesis H6d was not supported.

In summary, emotional intelligence was positively related to the frequency of deep acting and negatively related to the difficulty of deep acting. It was unrelated to either component of surface acting.

Hypothesis 7: Agreeableness and emotional labor. H7a predicts a positive relationship between agreeableness and the frequency of using deep acting. The bivariate correlation between these two variables was significant (r = .19, p < .01). Regression analyses also supported significant positive relationship between agreeableness and frequency of using deep acting (see Table 10). The addition of agreeableness to the model on step two added an additional 4% of explanation of variance above the control variables ()R2 = .040, F = 8.20, p < .01); the coefficient for agreeableness was significant

($ = .21, p < .01). H7a was supported.

H7b predicts a negative relationship between agreeableness and the difficulty of using deep acting. The bivariate correlation between these two variables was significant

(r = -.21, p < .01), supporting H7b. Regression analyses also provided support for a negative relationship between agreeableness and the difficulty of using deep acting (see

Table 10). The addition of agreeableness to the model on step two added an additional

F ) 2 R )

$ i $ F ) 2 R ) f $

i .01 $ # F ) * p<.05, **p p<.05, *

2 R ) f $ i $ .034 1.32 .100 4.14** .93 1.32 4.14** .024 .034 .100

F ) coefficient at final model, at final coefficient f $ 2 R ) f $ Frequency Deep Deep Frequency Deep Difficulty Surface Frequency Surface Difficulty i $ .21** .040 8.20** -.23** .049 9.89** -.07 .004 .92 -.16* .023 4.39* .023 -.16* .92 1.92 .049 .004 -.07 9.89** .049 -.23** 8.20** .040 .21** Age -.03 Age -.05 -.07 -.05 -.20** -.19** .12 .13 coefficient at initial entry, entry, at initial coefficient i Hours .13 .10 .01 .04 .19* .20* -.10 -.08 .04 -.08 .10 .20* .13 .01 -.10 .19* Hours Tenure -.16* -.12 .04 -.12 .09 -.16* .05 .06 .03 .06 Tenure $ .18* -.12 .11 -.06 .03 .01 .06 .02 Gender Job title .10 .12 .04 .12 .10 .06 .05 .06 title .00 .02 Job Table 10 Hierarchical from 192) Agreeableness = Labor Emotional Predicting Regression (N Variable 1 Step Demographics 2: Step Agreeableness Note:

5% of explanation of variance above the control variables ()R2 = .049, F = 9.89, p < .01).

The coefficient for agreeableness was significant ($ = -.23, p < .01). Hypothesis H7b was supported.

H7c predicts a negative relationship between agreeableness and the frequency of using surface acting. The bivariate correlation between these two variables was not significant (r = -.10, p = .15), but it was in the right direction. Regression analyses did not provide any support for H7c (see Table 10). The addition of agreeableness to the model on step two did not add any additional explanation of variance above the control variables. Hypothesis H7c was not supported.

H7d predicts a negative relationship between agreeableness and the difficulty of using surface acting. The bivariate correlation between these two variables was not significant (r = -.12, p = .11), but it was in the right direction. Adding agreeableness to the regression analysis on step two added 2% to the explanation of variance ()R2 = .023,

F = 4.39, p = .04). The coefficient for agreeableness was significant ($ = -.16, p = .04)

(see Table 10). Hypothesis H7d was partially supported.

In summary, agreeableness was positively related to the frequency of deep acting,

negatively related to the difficulty of deep acting, negatively related to the difficultly of

surface acting, and unrelated to the frequency of surface acting.

Hypothesis 8: Action orientation and emotional labor. Although theoretically action-state orientation is treated as a univariate construct, it has been suggested that hypotheses be tested using the three sub-scales of the measure: preoccupation, volatility

and hesitation to further explain any relationships (Diefendorff et al., 2000). As such, all three sub-scales will be looked at to test these hypotheses.

H8a predicts a negative relationship between action orientation and the frequency of performing deep acting. None of the bivariate correlations were significant

(preoccupation r = .06, p = .38; volatility, r = .03, p = .69; hesitation, r = .05, p = .51), providing no support for H8a. Regression analyses also failed to show any relationship between any of the subscales of action orientation and the frequency of using deep acting

(see Table 11). Hypothesis H8a was not supported.

H8b predicts a negative relationship between action orientation and the difficulty of performing deep acting. The bivariate correlation between preoccupation and difficulty of deep acting was not significant (r = -.11, p = .14), nor was the correlation between volatility and difficulty of deep acting (r = -.11, p = .15), but the correlation between hesitation and difficulty of deep acting was significant (r = -.33, p < .01). All three were in the correct direction. Hierarchical regression was used to further test the relationship (see Table 11). Preoccupation, volatility, and hesitation were entered in step two following the control variables. The three components of action-state orientation added a significant 10% of explanation of variance on step two of the regression equation

()R2 = .096, F = 6.53, p < .01). The coefficient for hesitation was significant ($ = -.34, p

< .01), but neither the coefficient for volatility nor the preoccupation coefficient were significant. H8b was partially supported.

H8c predicts a negative relationship between action orientation and the frequency of performing surface acting. The bivariate correlation between preoccupation and

F ) 2 R )

f $ .14 i

$ F ) 2 R ) .10 .10 f

$ i $ .01 # F ) * p<.05, **p p<.05, * 2

R ) f $ .09 .02 -.01 .00 .00 .00 .09 -.01 .00 .02

i $ .044 1.63 .104 4.18** .024 .86 .024 4.18** .104 1.63 .044

F ) coefficient at final model, at final coefficient f $ 2 R ) f $ Frequency Deep Deep Frequency Deep Difficulty Surface Frequency Surface Difficulty i $ .007 .43 .096 6.53** .064 4.53** 2.05 .054 4.53** .064 6.53** .096 .43 .007 Age -.05 -.07 -.07 -.02 -.20** -.16* .13 -.16* -.02 -.20** -.07 -.07 -.05 Age Hours .11 .11 .04 .05 .18* .18* -.09 -.09 -.09 .18* -.09 .05 .18* .04 .11 .11 Hours Tenure -.18* -.18* .09 .10 .06 .06 .05 .06 .06 .10 .06 .06 .05 .09 -.18* -.18* Tenure Gender -.05 Gender .03 .13 Job title .14 .14 .07 .04 .09 .06 .00 .00 .00 .04 .06 .09 .00 .07 .14 .14 title Job coefficient at initial entry, entry, at initial coefficient i

Volatility .01 -.01 -.01 .01 -.12 Volatility Hesitation .05 -.34** -.22** -.09 -.09 -.34** -.22** .05 Hesitation $ Preoccupation .05 .08 .05 .01 .012 .74 .08 .05 .012 .05 Preoccupation .01 Table 11 Hierarchical Regression PredictingEmotional Labor from Action-State Orientation 185) = (N Variable 1 Step Demographics 2:Step Action- state orientation Note:

frequency of surface acting was not significant (r = -.07, p = .35), but the correlation between volatility and frequency of performing surface acting was significant (r = -.17, p

= .02), as was the correlation between hesitation and frequency of performing surface acting (r = -.25, p < .01). All three were in the correct direction. Hierarchical regression was used to further test the relationship (see Table 11). The addition of preoccupation, volatility, and hesitation in step two after the control variables added a significant 6% of explanation of variance, ()R2 = .064, F = 4.53, p < .01). Only the coefficient for hesitation was significant ($ = -.22, p < .01). Hypothesis H8c was partially supported.

H8d predicts a negative relationship between action orientation and the difficulty of performing surface acting. None of the bivariate correlations were significant

(preoccupation r = -.01, p = .84; volatility, r = .06, p = .39; hesitation, r = -.01, p = .64), providing no support for H8d. Regression analyses also failed to show any relationship between any of the subscales of action orientation and the difficulty of using surface acting (see Table 11). Hypothesis H8d was not supported.

In summary, the preoccupation and volatility components of action-state orientation were unrelated to emotional labor. The hesitation component, however, was negatively related to both the difficulty of deep acting and the frequency of surface acting. Hesitation was unrelated to the frequency of deep acting as well as the difficulty of surface acting.

Table 12 summarizes the significant results of all antecedent variables tested. For the frequency of deep acting, significant relationships were found for feminine gender role identification, masculine gender role identification, positive affectivity, emotional

intelligence, and agreeableness. The difficulty of deep acting was significantly related to

masculine gender role identification, negative affectivity, positive affectivity, emotional

intelligence, agreeableness and hesitation. The frequency of surface acting was significantly related to masculine gender role identification, negative affectivity, positive affectivity, self-monitoring, and hesitation. Finally, the difficulty of surface acting was significantly related to self-monitoring and agreeableness.

Table 12

Summary of Significant Relationships between Antecedents and Emotional Labor

Frequency Difficulty Frequency Difficulty Deep Deep Surface Surface Feminine X

Masculine X X

NA X X

PA X X X

Self-Monitoring X X

EI X X

Agreeableness X X X

Preoccupation

Volatility

Hesitation X X

Note: X significant relationship found, EI = Emotional Intelligence

Exploratory analyses

Model analyses. It would be of value to know which variables were the most

useful in the prediction of each form of emotional labor. Though no hypotheses were proposed regarding the entire model of emotional labor from antecedents to outcomes, six additional regression analyses were performed to further explore the model. The first four were designed to answer the question, when all antecedents are considered simultaneously, which ones emerge as the strongest predictors of each form of emotional labor? The last two analyses investigated if the emotional labor components mediated the relationship between the antecedent variables and the outcome of emotional

exhaustion.

The first four exploratory analyses were conducted by taking the antecedent variables that showed promise as predictors for each emotional labor component, and entering them on step two of the regression after the demographic variables.

For the frequency of deep acting, the antecedents of masculine gender role identification, feminine gender role identification, positive affectivity, emotional intelligence, and agreeableness were entered on step two (see Table 13). Although none of the antecedents had significant weight, together, they explained an additional 9% of the variance in emotional exhaustion ()R2 = .089, F = 3.64, p < .01).

Table 13

Hierarchical Regression Predicting Frequency of Deep Acting (N = 189)

Variable $i $f )R2 )F

Step 1: Demographics .048 1.83

Job title .10 .08

Gender -.06 -.11

Age -.03 -.06

Tenure -.16 -.10

Hours .13 .12

Step 2: Antecedents .089 3.64**

Masculine .09

Feminine .08

Positive Affectivity .09

Emotional Intelligence .09

Agreeableness .14

Note:$i initial entry coefficient, $f final model coefficient, * p < .05, **p < .01

For the difficulty of deep acting, the antecedents of masculine gender role

identification, negative affectivity, positive affectivity, emotional intelligence,

agreeableness, and the hesitation component of action-state orientation were entered on step two (see Table 14). They accounted for 18% of the variance in the difficulty of deep acting ()R2 = .179, F = 6.46, p < .01). The coefficients for positive affectivity ($ = -.25, p < .01) and hesitation ($ = -.25, p < .01) were the only significant predictors.

Table 14

Hierarchical Regression Predicting Difficulty of Deep Acting (N = 185)

Variable $i $f )R2 )F

Step 1: Demographics .044 1.59

Job title .08 .03

Gender .12 .10

Age -.07 .00

Tenure .09 .06

Hours .04 .03

Step 2: Antecedents .179 6.46**

Masculine .02

Negative Affectivity .05

Positive Affectivity -.25**

Emotional Intelligence .02

Agreeableness -.12

Hesitation -.25**

Note: $i initial entry coefficient, $f final model coefficient, * p < .05, **p < .01

For the frequency of surface acting, the antecedents of masculine gender role identification, negative affectivity, positive affectivity, self-monitoring, and hesitation were entered on step two (see table 15), explaining 19% of the variance ()R2 = .188, F =

9.12, p < .01). The coefficients for negative affectivity ($ = .23, p < .01), positive

affectivity ($ = -.16, p = .02), and self-monitoring ($ = .21, p < .01) were significant in the model.

Table 15

Hierarchical Regression Predicting Frequency of Surface Acting (N = 185)

Variable $i $f )R2 )F

Step 1: Demographics .103 4.08**

Job title .07 .07

Gender .03 .02

Age -.20** -.10

Tenure .06 .04

Hours .19* .15

Step 2: Antecedents .188 9.12**

Masculine -.14

Negative Affectivity .23**

Positive Affectivity -.16*

Self-monitoring .21**

Hesitation -.03

Note: $i initial entry coefficient, $f final model coefficient, * p < .05, **p < .01

For the difficulty of surface acting, self-monitoring and agreeableness were

entered on step two (see Table 16). They accounted for 9% of the variance in the

difficulty of surface acting ()R2 = .092, F = 9.60, p < .01). Both self-monitoring ($ = -

.29, p < .01) and agreeableness ($ = -.21, p < .01) were significant predictors.

Table 16

Hierarchical Regression Predicting Difficulty of Surface Acting (N = 192)

Variable $i $f )R2 )F

Step 1: Demographics .024 .93

Job title .02 .01

Gender .02 .02

Age .12 .06

Tenure .06 .03

Hours -.10 -.07

Step 2: Antecedents .092 9.60**

Self-monitoring -.29**

Agreeableness -.21**

Note: $i initial entry coefficient, $f final model coefficient, * p < .05, **p < .01

The final exploratory analyses regarding the model of emotional labor explored if

emotional labor mediated the relationship between the antecedents and the outcome

variable of emotional exhaustion (see Table 17). The first of these included all of the

variables in the model (see figure 1). As such, the demographic variables were entered on

step one explaining 15% of the variance in emotional exhaustion ()R2 = .146, F = 5.65, p

< .01). All eight proposed antecedents were entered on step two, explaining 18% of the

variance in emotional exhaustion ()R2 = .181, F = 5.60, p < .01). Positive affectivity ($

= -.26, p < .01), and hesitation ($ = -.17, p = .03) were the only antecedents that were significant. All four emotional labor components were entered on step three, explaining

3% of the variance in emotional exhaustion ()R2 = .032, F = 2.01, p = .10). After entering the emotional labor items, the coefficients for positive affectivity ($ = -.21, p <

.01), agreeableness ($ = -.12, p = .16), and hesitation ($ = -.14, p = .09) dropped, but

were not reduced to zero, indicating that emotional labor did not fully mediate the

relationship between these three antecedent variables and emotional exhaustion.

As positive affectivity, agreeableness and hesitation were the only three

dispositional antecedent variables that remained significant predictors of emotional

exhaustion when the whole model was considered, a final analysis was run of the entire

model eliminating the other dispositional antecedent variables (See Table 17). In this

model, the demographic variables explained 15% of the variance in emotional exhaustion

()R2 = .148, F = 6.15, p < .01). Positive affectivity, agreeableness, and hesitation were entered on step two, explaining 15% of the variance in emotional exhaustion ()R2 = .151,

F = 12.46, p < .01). Positive affectivity ($ = -.24, p < .01), agreeableness ($ = -.19, p =

.01), and hesitation ($ = -.15, p = .03) were all significant. All four emotional labor components were entered on step three, explaining 4% of the variance in emotional exhaustion ()R2 = .038, F = 2.45, p = .05). After entering the emotional labor items, the

coefficients for positive affectivity ($ = -.17, p = .01), agreeableness ($ = -.16, p = .03),

and hesitation ($ = -.09, p = .19) dropped, but were not reduced to zero, indicating that

emotional labor did not fully mediate the relationship between these three antecedent

variables and emotional exhaustion.

Table 17

Hierarchical Regression Predicting Emotional Exhaustion, Full Model (N = 180)

Variable $i $f )R2 )F $i $f )R2 )F

Step 1 Demographics: .146 5.97** .148 6.15**

Job title .09 .02 .10 .07

Gender .11 .11 .11 .11

Age -.23** -.15* -.22** -.16*

Tenure .20* .14 .20* .13

Hours .10 .08 .10 .08

Step 2 Antecedents: .181 5.60** .151 12.46**

Feminine -.06 -.05

Masculine .10 .11

NA .12 .08

PA -.26** -.21** -.24** -.17*

Self-Monitoring .05 .03

Emotional intelligence .04 .05

Agreeableness -.15 -.12 -.19** -.16*

Hesitation -.17* -.14 -.15* -.09

Step 3 Emotional Labor: .032 2.01 .038 2.45*

Frequency Surface .15 .15

Frequency Deep -.04 -.04

Difficulty Surface .10 .08

Difficulty Deep .09 .11

Note: $i initial entry coefficient, $f final model coefficient, * p < .05, **p < .01

Further Ad Hoc Analysis. As the difficulty of deep acting and the frequency of surface acting appeared to be the most relevant variables in predicting emotional 86

exhaustion, and seemed to continuously show significant relationships with several of the antecedent variables, a few more ad hoc analyses were performed. The goal was to identify if there were any individual difference variables that would be valuable in predicting who would tend to find deep acting difficult and also use surface acting more, and also who would find deep acting easy and use surface acting less. First, a variable was created identifying those who were high on both and those who were low on both by multiplying the difficulty of deep acting score by the frequency of surface acting score.

This term was then analyzed in seven different regression analyses as the dependent variable, with each dispositional antecedent as the independent variable. For all seven dispositional antecedent variables, the regression equation was significant suggesting that at least one antecedent was related to the newly created interaction variable.

This discovery led to a further investigation into why this effect was occurring.

Both the difficulty of deep acting and the frequency of surface acting were dichotomized into high and low groups. The means were then analyzed for each dispositional variable.

For only two variables, positive affectivity and self-monitoring, did the results indicate that there was a practically significant relationship between the antecedent variable and the interaction between difficulty of deep acting and frequency of surface acting. Those who scored high on positive affectivity tended to find deep acting easier to perform and did not engage in surface acting as often. Those who were low on positive affectivity either found deep acting easy to do, but chose not to perform surface acting as an alternative, or found deep acting hard to do with no impact on if they would perform surface acting or not (See table 18). Those who rated deep acting as less difficult and did

not perform surface acting had a mean score on positive affectivity of 38.60, whereas all

other combinations had lower mean scores on positive affectivity that were not very

different from each other. Those high on positive affectivity tend to use surface acting

less and find deep acting easy, whereas those lower on positive affectivity vary on how difficult they find deep acting and how frequently they use surface acting. Individuals who tend to experience positive affect would find it easy to actually feel positive emotions and deep act. Also, as these individuals are typically experiencing positive feelings, there would be less need to construct or falsely display an emotional response.

Table 18

Means of Dichotomized Variables for Positive Affectivity

Positive Affectivity Frequency of Surface

Low High

Difficulty of Deep Low 38.60 33.40

High 33.39 33.18

Self-monitoring did not have an impact on how frequently surface acting would be used when deep acting is seen as easy, but when deep acting was viewed as difficult, high self-monitors tend to use surface acting as an alternative more often than those who scored low on self-monitoring. This effect is illustrated by presenting the means in Table

19. High self-monitors found deep acting difficult and used surface acting often, whereas

low self-monitors found deep acting difficult, but did not use surface acting in its place.

This makes sense as self-monitoring is a trait that indicates how much a person cares

about the impression that they create on others. Individuals high on self-monitoring care

more about what others see than what they actually feel. These individuals are not skilled in actually changing their felt emotions, making deep acting difficult. Those low in self- monitoring would not care what others thought about them, so trying to change their actual emotions would not be easy, nor would they feel the need to fake their outward expression.

Table 19

Means of Dichotomized Variables for Self-Monitoring

Self-Monitoring Frequency of Surface

Low High

Difficulty of Deep Low 27.02 27.28

High 25.76 28.78

CHAPTER V

DISCUSSION

The goal of the present study was two-fold. First it set out to improve the measurement and utility of the construct of emotional labor by adding the component of perceived difficulty to the traditional operationization of emotional labor in terms of frequency of surface and deep acting. Secondly, it investigated some of the individual difference antecedents to emotional labor that have been proposed in the literature. This investigation was carried out using a real-world customer service sample.

In terms of the first goal, perceived difficulty of emotional labor significantly predicted emotional exhaustion above and beyond the frequency of emotional labor. This indicates that for the outcome variable of emotional exhaustion, both the frequency of surface acting and the difficulty of deep acting were the two components of emotional labor that were important.

For the second goal significant relationships were found between each antecedent variable tested and at least one component of emotional labor.

Predictive Ability of Emotional Labor on Outcome Variables

Many researchers have used the concepts of surface acting and deep acting in their conceptualizations of emotional labor, but have only considered the frequency of performing these emotional regulation behaviors (Brotheridge & Grandey, 2002;

Brotheridge & Lee, 2002; Grandey, 1999; 2003; 2005). This study added the component

of perceived difficulty in performing emotional labor, and showed that difficulty was a separate and important component in the study of emotional labor. As in previous research, this study found that the frequency of surface acting related positively to emotional exhaustion and the frequency of deep acting did not relate significantly to emotional exhaustion. This replicates findings in previous research (Brotheridge &

Grandey, 2002; Brotheridge & Lee, 2002; Grandey 1999), and re-iterates that the frequency of performing surface acting is more detrimental than the frequency of performing deep acting.

Notably, however, the difficulty of surface acting and the difficulty of deep acting also related positively to emotional exhaustion, above and beyond the frequency variables, demonstrating the predictive value of the difficulty of emotional labor. The high positive relationship between the perceived difficulty of deep acting and emotional exhaustion, however, was not originally expected. This is based on the lowered negative impact of deep acting on many other undesirable outcome variables as compared to surface acting. Upon further reflection, however, the finding makes sense. In this sample, positive emotions were the focus. People who find it harder to actually feel the positive emotions that they need to display experience emotional exhaustion more often because when negative events occur they find it harder to change their emotions to become positive. Thus, the effort involved to course correct is even more emotionally taxing than someone who finds deep acting easy to perform, leading to greater emotional exhaustion. In addition, since deep acting may not be successful, the individual may then engage in more surface acting to achieve the desired positive emotional response.

Notably, the difficulty of deep acting and the frequency of surface acting were the two components of emotional labor that predicted emotional exhaustion. These two were also positively and significantly related to each other. It can be argued the individuals who find deep acting difficult must resort to using surface acting more often in order to achieve the organizationally desired response. Thus, finding it hard to change one’s emotions to actually experience the positive feelings required by the organization is detrimental not only because of the frustration in finding deep acting difficult, but also because surface acting will often have to be employed in its place.

Researchers have suggested that organizations invest in training their employees on deep acting methods to avoid the negative consequences of surface acting (Totterdell

& Holman, 2003). The findings in this study suggest that training on such techniques should also reduce the difficulty of using deep acting, which has been shown to be detrimental to employees.

Antecedents

Eight individual difference variables were proposed as antecedents for each form of emotional labor. Every antecedent tested was related to at least one form of emotional labor as measured by the frequency and the difficulty of using both the deep and surface acting methods. Each individual difference variable is discussed below.

While this study examined the relationships between the proposed antecedent variables and all four components of emotional labor, it appears that the most relevant dimensions of emotional labor are the difficulty of deep acting and the frequency of surface acting. Also, it appeared that for the most part the individual differences

variables that predicted the difficulty of deep acting were also related to the frequency of

surface acting in the same direction. Those who were high on instrumentality, positive

affectivity, and action oriented found deep acting less difficult and used surface acting

less often. Also, those high on negative affectivity found deep acting difficult and used

surface acting more often. It is clear that when deep acting is easy, surface acting is less

likely to be needed, and thus is employed less often. Similarly, when deep acting is difficulty to perform, the individual is more likely to need to surface act.

If individuals were to be selected for their ability to perform emotional labor with the least amount of negative impact, instrumentality, positive affectivity, negative affectivity, and action orientation would be the variables to look at in that selection.

These variables could be used to choose which individuals to hire, or more importantly which employees would benefit the most from training on deep acting strategies.

The frequency of deep acting was negatively related to emotional exhaustion, indicating that it may be valuable to know which individuals tend to use this strategy more often. Persons high on instrumentality, or identification with the masculine gender stereotype, positive affectivity, emotional intelligence, and agreeableness reported using deep acting more often. Interestingly, these individuals also reported that deep acting was easier to perform. The difficulty of deep acting was negatively correlated with the frequency of using the deep strategy, however any direction of causality is not known and no conclusions are reached here about causality. It is possible that persons who have the attributes of instrumentality, positive affectivity, emotional intelligence and agreeableness find deep acting easy to do as their typical emotional experiences are

congruent with the positive emotions required by the organization. As they find it easy to

perform, they tend to utilize it more often when faced with a situation in which emotional

regulation is necessary.

Gender role identification. The hypotheses regarding gender were based on the idea that as a stereotype, women are called on to perform emotional labor more often than men. The practice that comes with that increased frequency of performing emotional labor should make it easier to perform. Looking at simple sex differences, there was no relationship between gender and emotional labor. Gender stereotype identification was

measured to explore this relationship beyond differences in physical sex characteristics,

and truly delve into the differences that stem from identifying with the stereotypes that

exist for feminine and masculine gender roles. The results did not entirely support the

hypotheses. The feminine gender stereotype did not relate to how often surface acting

was used, or how difficult it was to perform. It also did not relate to how difficult deep

acting was, contrary to expectations. As expected, those who identified with the feminine

gender stereotype did use the deep acting method more often than those who did not

identify with that gender stereotype.

The scale measuring identification with the feminine gender stereotype has more

commonly been considered as a measure of expressivity, tapping concepts such as

kindness and awareness of the feelings of others. These are the socially desirable

attributes associated with the feminine gender stereotype. Being high on expressivity

was associated with finding deep acting easier to accomplish, but was not related to any

other component of emotional labor.

Unexpectedly, a positive relationship between the frequency of deep acting and

identification with the masculine gender role was found. There has been debate on what

the PAQ masculine and feminine scales are actually measuring (Yoder, in press). The

feminine, or expressivity, scale asks questions related to relationships and feelings, which

coincides with the ideas on which the original hypotheses were based. Identification with

the masculine gender stereotype is not a measure of lacking identification with the

feminine gender stereotype, as the two scales are meant to be unrelated dimensions. This

explains the lack of relationship between identification with the masculine gender

stereotype and identification with the feminine gender stereotype. The masculine gender

stereotype scale measures concepts such as being independent, not giving up easily, and

being confident. In fact, this scale has been called a measure of instrumentality (Spence

& Helmreich, 1980), and also a measure of agency (Eagly, 1987). As such, the

predictions made about identification with the feminine gender stereotype do not apply in reverse to identification with the masculine gender stereotype.

The findings concerning the masculine gender stereotype, or instrumentality, are

interesting, however. When people who are independent, do not give up easily and are

confident are given a task to perform, they take those tasks on with fervor. When the task

at hand is to display an appropriate positive emotional response, they do not fake it, they

do it full force. This would lead to the prediction that they don’t use surface acting as

often, which would be the “easy way out,” but they do use deep acting more often and actually feel what they are supposed to display. This pattern was supported by the data.

Also, because individuals who are high on instrumentality don’t give up and are

confident, they do not report finding deep acting as challenging or difficult to perform as

someone who does not identify with these characteristics as strongly, explaining the negative relationship between identification with the masculine gender stereotype and the difficulty of performing deep acting.

Affectivity. Negative affectivity was the second individual difference variable tested as an antecedent. Negative affectivity is the tendency to experience negative

emotions. It was proposed that persons high on negative affectivity would be more

reactive to negative events in the workplace, and thus need to use emotional regulation

strategies more often when the goal was to display a positive emotional response.

Support was found for this with surface acting, but not for deep. People high on negative affectivity used surface acting more often than persons low on negative affectivity, but the frequency of deep acting was unrelated to negative affectivity. It was also proposed that those high on negative affectivity would find emotional labor more difficult to perform as they would have lowered access to positive thoughts which would be needed if they were to engage in deep acting. This was supported; being high on negative affectivity was related to greater difficulty in performing deep acting. Negative affectivity was unrelated to the difficulty of surface acting.

Contrary to negative affectivity, positive affectivity, or the tendency to experience

positive emotions, was proposed to require using surface acting, because people high on

positive affectivity are more likely to be experiencing emotions that are congruent with

the positive display required by the organization. In this sample, people high on positive

affectivity did report using surface acting less often, they did not need to fake their emotional response, since they were most likely feeling an appropriate emotion already.

Persons high on positive affectivity did report using deep acting strategies more

often than those low on positive affectivity. Even though they were already in a good

mood, they still reported trying to actually feel what they needed to display. Perhaps

because individuals high on positive affectivity are used to being in a positive mood, they

see it desirable to feel the positive emotions that they need to display when an event

occurs that makes them stray from their usual positive disposition. This would lead them

to use deep acting as their preferred strategy of regulation. It is also possible that the measurement of deep acting is consciously the same as genuinely experiencing the positive emotions that are required, thus persons high on positive affectivity would naturally report actually trying to change their emotions to be positive, or using deep acting strategies.

Viewing emotional labor from a control theory perspective supports this

(Diefendorff & Gosserand, 2003). From this perspective, the comparator is the display rules set forth by the organization to display positive emotions, and the output is emotional regulation. A person who tends to feel emotions that are congruent with the

display rules, i.e. someone high on positive affectivity, will have a higher expectancy for

displaying the correct emotion. This leads to a higher motivational force for following that display rule, and explains why those high on positive affectivity use deep acting more frequently. The actual effort involved when faced with such a situation will be low,

because as predicted, people high on positive affectivity found deep acting easier to perform. Positive affectivity was unrelated to the difficulty of surface acting.

Self-monitoring was also proposed as an individual difference antecedent to emotional labor. Self monitors are concerned about the outward appearance they project to others. As such when an organizationally appropriate emotional response is required, they find surface acting easy to do and do it more often than low self monitors, as expected. Also, as predicted, self-monitoring was not as strongly related to the use of deep acting, in fact it was not related to deep acting at all, in either difficulty of frequency. This can be explained because high self monitors are not necessarily concerned with what they actually are experiencing; only what others see. Using deep acting would not serve their goal, thus it would not be a technique of regulating emotion that they would use more or less often than a low self monitor. Additionally, the difficulty of actually feeling the emotions that they need to display wouldn’t be easier or harder as a function of self-monitoring. This finding is consistent with Brotheridge and

Lee (2002) who found a relationship between self-monitoring and surface acting, but not for deep acting.

Emotional intelligence was the sixth antecedent proposed. Emotionally intelligent people are better at figuring out the appropriate emotional response and regulating their emotions accordingly. The results showed that emotionally intelligent people do use deep acting strategies of emotional labor more often, and that they find it easier to perform. This was not the case for surface acting; emotional intelligence was not significantly related to the frequency or the difficulty of surface acting. This is consistent

with Totterdell and Holman (2003) who only found a significant relationship between emotional intelligence and the deep acting component of emotional labor; they failed to find a relationship with surface acting.

Agreeableness. It was predicted that agreeable people would use emotional regulation strategies more often because they would want to get along with others, and as such, if others wanted them to show an organizationally expected emotions, they would

do everything they could to do so. Further, because they would be doing this often, they would be practiced at the techniques and would find them relatively easy to perform. For deep acting, this was supported; people high on agreeableness reported using deep acting strategies more often and rated those behaviors as easier to perform. For surface acting, however, people high on agreeableness did not differ from those low on agreeableness on the frequency of performing surface acting. This finding failed to replicate findings from

Diefendorff et al.’s study of university students (2005) who found that agreeableness was negatively related to the frequency of surface acting. Persons high on agreeableness did find surface acting easier to perform than those low on agreeableness as predicted.

Action-state orientation. Finally, action-state orientation was predicted to be an antecedent of emotional labor. Action-state orientation is a goal striving technique.

Action oriented individuals tend to easily shift focus onto the goal at hand whereas state oriented individuals are less able to block out thought concerning competing goals.

Individuals who were more action oriented, as measured by the hesitation scale, the subscale of the action-state orientation scale measuring the tendency to take quick action when needed, used surface acting less often than those who were state oriented. Those

individuals also found deep acting easier to perform, as predicted. The frequency of deep acting and the difficulty of surface acting were unrelated to action-state orientation.

Model summary

surface acting in the same direction. Those who were high on instrumentality, positive

affectivity, and action oriented found deep acting less difficult and used surface acting

less often. Also, those high on negative affectivity found deep acting difficult and used

surface acting more often. It is clear that when deep acting is easy, surface acting is less

likely to be needed, and thus is employed less often. Similarly, when deep acting is difficulty to perform, the individual has no choice but to surface act.

If individuals were to be selected for their ability to perform emotional labor with

the least amount of negative impact, then instrumentality, negative and positive

affectivity, and action orientation would be the most relevant variables. These variables

could be used to choose which individuals to hire, or more importantly which employees

would benefit the most from training on deep acting strategies.

The frequency of deep acting was negatively related to emotional exhaustion,

indicating that it may be valuable to know which individuals tend to use this strategy

more often. Persons high on instrumentality, positive affectivity, emotional intelligence,

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and agreeableness reported using deep acting more often. Interestingly, the individuals high on these four variables also reported deep acting as easier to perform. In this study, the difficulty of deep acting was negatively correlated with the frequency of using the deep strategy, however causality is not known. It is possible that persons who have the attributes of instrumentality positive affectivity, emotional intelligence and agreeableness find deep acting easy to do as their typical emotional experiences are congruent with the positive emotions required by the organization. Because they find it easy to perform, they tend to utilize it more often when faced with a situation in which emotional regulation is necessary.

The difficulty of surface acting did not show to be an important component of emotional labor in this study. It did not significantly predict emotional exhaustion, and the only two individual difference variables that predicted it were self-monitoring, and agreeableness. This study only examined one potential outcome variable of emotional labor, thus it is possible that the difficulty of surface acting could be an important predictor of other outcomes of emotional labor, such as the job performance of an individual required to perform rote customer interactions, for example a toll booth collector.

Limitations

One of the major limitations of this study is that all data came from surveys.

Survey studies limit the inferences that can be made about causality. A lab study involving a task requiring emotional labor where individuals were selected based on

scores on the antecedent variables would strengthen our understanding of causality.

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Other methods of research should be applied to the research questions within this paper to strengthen the results. Totterdell and Holman (2003) used a diary method to research emotional labor, and found similar results to those found in this study. However, they did not measure difficulty of emotional labor, which has been shown in this study to be a valuable component of emotional labor.

Also, people tend to self-select into service occupations, which may limit the variance in the sample, a lab study would be able to correct for this by including participants that may not seek a service job. For example, persons high on negative affectivity, or the tendency to experience negative emotions, may choose not to apply for a job where presenting a friendly face to the customer is a requirement. In a lab study, a broader sample of the population would allow for a greater range in this variable as well as the others tested in this study.

Another limitation was in the use of existing scales to measure both the frequency and difficulty of the deep acting method of emotional labor. While using existing scales has advantages such as replication and validity evidence, it also has disadvantages in that the limitations of the existing scales are inherited. The existing scale for emotional labor has some flaws. The distinction between deep acting as measured and the expression of genuine emotion is not clear. Individuals who are genuinely experiencing the emotions they need to show may not differentiate their typical positive outlook from actually deep acting and putting forth effort to change their emotions when faced with an unpleasant situation. Perhaps the questions could be modified to include a context requiring the use of a regulation strategy, which would force participants to think of a situation in which

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emotional labor was required thereby eliminating the possibility of genuine emotions

being misconstrued as deep acting efforts. Asking participants to rate how they would

respond to an abrupt unhappy customer returning a product, for example.

This generalizability of this study is limited by the focus on situations in which the expression of a positive emotion is required by the organization. Though most customer service organizations expect positive emotional displays from their employees, there are situations in which other emotions are required such as sympathy, neutrality, and assertiveness. The findings in this study may not apply to those situations.

Future Research

Though the measurement should be improved, the perceived difficulty of performing emotional labor was established as an important component in the study of emotional labor. Future studies should include this component in research on emotional labor. Relationships that have been found in past research could be re-tested with the difficulty component added, and potential interactions between the components of frequency and difficulty could be investigated.

Future research could also look at how cultural influences may impact the

relationship between emotional labor and the outcomes. Bagozzi, Verbeke, and Gavino

(2003) found that culture moderated the relationship between the self-regulation of shame

and job performance. The present study was performed in a Western or independent

culture, it is possible that an Eastern or interdependent based culture may produce

different results.

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Additionally, this study focused on an organization that required positive displays of emotions. While this is the norm in most customer service situations, it is not clear if the findings would generalize to situations in which negative or neutral emotions were required (Fredrickson, 1998). Future research could investigate these relationships in situations where other types of emotions are the organizational appropriate response.

Finally, the literature has been clear that using deep acting more often is better for individual and organizational outcomes, indicating that it is preferable for employees to use deep acting strategies when performing emotional labor. In this study it was demonstrated that when an individual finds deep acting difficult to perform, it is detrimental to the individual, and they tend to use surface acting more often. Together, these findings suggest that developing a training program for employees to strengthen their use and ease of performing deep acting would be beneficial to both employees and organizations. No known program has been developed or evaluated. Such a program could teach deep acting strategies to participants, and help employees to recognize potential situations that require emotional regulation early enough to effectively employ those deep acting strategies. This could be a promising area for future research.

Conclusion

All customer service organizations require their employees to exhibit specific emotional responses during interpersonal interactions. While some employees may tend to genuinely experience these emotions, requiring no effort to satisfy this demand, all employees will at one point or another find themselves in a situation where a felt emotion does not match the one required to be displayed. In such situations emotional regulation

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must be employed to achieve the desired emotional response. The effort involved in such regulation is called emotional labor, and it has consequences for the individual performing it. These consequences have been shown to be different depending on which type of emotional labor is employed, and how difficult it is for an individual to perform.

Others have shown that the frequency of using surface acting is far more detrimental to an individual and an organization than deep acting. This study extended that by demonstrating that when an individual finds the deep acting strategy of emotional labor difficult to perform, and uses the surface acting strategy more often, emotional exhaustion is the result.

Additionally, this study identified several individual difference variables that predict the four components of emotional labor. Most notably, instrumentality, positive affectivity, emotional intelligence, agreeableness, and action orientation predicted who would find deep acting easier, use surface acting less, and use deep acting more. These variables could be very valuable in selecting individuals for jobs requiring more emotional displays, or for selecting individuals who would benefit most from training on deep acting methods which would make deep acting easier and heighten the use of that strategy. While such training may not improve job performance, as using either method would satisfy the job demand, the increased use and ease of deep acting would lower emotional exhaustion. Additionally, other valuable organizational outcomes, such as turnover and job satisfaction, would be impacted in a positive way.

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Zapf, D., Vogt, C., Seifert, C., Mertini, H., & Isic, A. (1999). Emotion work as a source of stress: The concept and development of an instrument. European Journal of Work and Organizational Psychology, 8 (3), 371-400.

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APPENDICES

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APPENDIX A

PARTICIPANT SURVEY Dear Fellow Employee:

I need your help! My name is Diane Monaghan and I’ve been working for this company since 1995. I have also been going to graduate school in that time and I am almost finished, but now I need your help. I am currently working on my dissertation and need to survey quite a few people in order to finish. That is where you come in. If you could take the time to fill out one of my surveys and send it back to me, I may actually be able to finally graduate with my Ph.D.! If you would like to volunteer to help me you will find instructions and a brief overview of the study inside. Thank you so much for helping me!!!!

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What is my study about? My study is centered around something called emotional labor, which is the idea that at work you are not just doing physical and mental duties; you are also controlling your emotions to accomplish your job. Think about it, you are not always in a good mood, but do you let your customers know that? Probably not. Somehow, time after time you are able to call out that decaf quad grande dry cappuccino with a smile and a thank you, regardless of how you really feel! Through this survey I am trying to find other things, such as personal characteristics, that may be related to perceptions of emotional labor in the workplace. By taking the time to fill this survey out, you are not only helping me, but also are helping increase our understanding of emotional labor which may someday be used to help employers recognize the importance of paying attention to emotions in the workplace!

Instructions: The contents of this booklet are for you to fill out. It should take approximately 30-45 min to complete. When you are finished, place the survey in the pre-addressed stamped envelope and mail it back to me. None of the responses will be traceable to any individual; therefore your responses will remain anonymous.

Thank you so very much for your help!

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Instructions: Please answer the following questions.

1. Date ______

2. Age ______

3. Gender (circle one) Male Female

4. How long have you been an employee at your current job? (circle one)

less than 6 months 6 months - 1 year 1 year - 2 years 2 years - 3 years more than 3 years.

5. On average, how many hours do you work per week? ______hours

6. What is your job title? (circle one) barista shift supervisor other

7. On average, and interaction I have with a customer takes approximately ______min.

8. Please rate your overall performance at work using the following scale: ______1 = needs improvement 2 = meets expectations 3 = consistently exceeds expectations

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Using the following scale, answer questions 9-13.

1 = never 2 = seldom often often never never always 3 = sometimes At work, how often are you seldom 4 = often expected to … sometimes 5 = always

9. Greet customers? ± ± ± ± ± 1 2 3 4 5 10. Interact with customers in order to determine their needs? ± ± ± ± ± 1 2 3 4 5 11. Talk with customers while they are waiting? ± ± ± ± ± 1 2 3 4 5 12. Display many different emotions when interacting with ± ± ± ± ± customers? 1 2 3 4 5

13. Use a wide variety of emotions in dealing with people? ± ± ± ± ± 1 2 3 4 5

For questions 14-19, please rate to what extent you agree or disagree with the statements using the following scale.

1 = strongly disagree 2 = disagree 3 = neither disagree nor agree 4 = agree agree neither 5 = strongly agree disagree Strongly agree agree Strongly Strongly disagree disagree Strongly 14. Part of my job is to make the customer feel good. ± ± ± ± ± 1 2 3 4 5 15. My workplace does not expect me to express positive ± ± ± ± ± * emotions to customers as part of my job. 1 2 3 4 5 16. This organization would say that part of the product to ± ± ± ± ± customers is friendly, cheerful service. 1 2 3 4 5 17. I am expected to suppress any negative emotions I may feel ± ± ± ± ± on the job. 1 2 3 4 5 18. At work, I can easily change my position so that I am not ± ± ± ± ± interacting with customers. 1 2 3 4 5 19. I am able to daydream at work. ± ± ± ± ± 1 2 3 4 5

Note: * item reverse coded

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Using the following scale answer questions 20-27. 1 = never 2 = seldom 3 = sometimes 4 = often In order to do your job effectively, often often never never always seldom seldom 5 = always how often do you… sometimes

20. Put on an act in order to deal with customers in an appropriate way. ± ± ± ± ± 1 2 3 4 5 21. Fake a good mood. ± ± ± ± ± 1 2 3 4 5 22. Put on a “show” or “performance.” ± ± ± ± ± 1 2 3 4 5 23. Just pretend to have the emotions I need to display for my job. ± ± ± ± ± 1 2 3 4 5 24. Put on a “mask” in order to display the emotions I need for the job. ± ± ± ± ± 1 2 3 4 5 25. Try to actually experience the emotions that I must show. ± ± ± ± ± 1 2 3 4 5 26. Make an effort to actually feel the emotions that I need to display ± ± ± ± ± toward others. 1 2 3 4 5 27. Work hard to feel the emotions that I need to show to others. ± ± ± ± ± 1 2 3 4 5

Using the following scale answer questions 28-35.* 1 = very difficult 2 = somewhat difficult 3 = moderate 4 = somewhat easy At work, how difficult is it to… moderate moderate 5 = very easy easy very very difficult somewhat easy somewhat difficult 28. Put on an act in order to deal with customers in an appropriate way. ± ± ± ± ± 1 2 3 4 5 29. Fake a good mood. ± ± ± ± ± 1 2 3 4 5 30. Put on a “show” or “performance.” ± ± ± ± ± 1 2 3 4 5 31. Just pretend to have the emotions I need to display for my job. ± ± ± ± ± 1 2 3 4 5 32. Put on a “mask” in order to display the emotions I need for the job. ± ± ± ± ± 1 2 3 4 5 33. Try to actually experience the emotions that I must show. ± ± ± ± ± 1 2 3 4 5 34. Make an effort to actually feel the emotions that I need to display ± ± ± ± ± toward others. 1 2 3 4 5 35. Work hard to feel the emotions that I need to show to others. ± ± ± ± ± 1 2 3 4 5 Note: * items 28-35 reverse coded

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Instructions: This next scale consists of a number of words that describe different feelings and emotions. Read each item and then mark the appropriate answer in the space next to that word. Indicate to what extent you have felt that way during the past few days. Use the following scale to record your answers.

1 = very slightly or not at all

2 = a little

3 = moderately

4 = quite a bit

5 = extremely

_____ interested PA _____irritable NA

_____ distressed NA _____alert PA

_____ excited PA _____ashamed NA

_____ upset NA _____inspired PA

_____ strong PA _____nervous NA

_____ guilty NA _____determined PA

_____ scared NA _____attentive PA

_____ hostile NA _____jittery NA

_____ enthusiastic PA _____active PA

_____ proud PA _____afraid NA

Note: PA items are part of the positive affectivity scale , NA items are part of the negative affectivity scale 118

Instructions: The items below inquire about what kind of person you are. Each item

consists of a pair of characteristics, with numbers from 0-4 in between. Each pair

describes contradictory characteristics--that is, you cannot be both at the same time.

Circle a number which describes where you fall on the scale.

not at all independent 0 1 2 3 4 very independent M not at all emotional 0 1 2 3 4 very emotional F F

very passive 0 1 2 3 4 very active M not at all able to devote self 0 1 2 3 4 able to devote self F

very rough 0 1 2 3 4 very gentle F not at all helpful to others 0 1 2 3 4 very helpful to others F

not at all competitive 0 1 2 3 4 very competitive M not at all kind 0 1 2 3 4 very kind F

not at all aware of the 0 1 2 3 4 very aware of the F feelings of others feelings of others has difficulty making decisions 0 1 2 3 4 can make decisions M easily

gives up very easily 0 1 2 3 4 never gives up easily M not at all self-confident 0 1 2 3 4 very confident M

feels very inferior 0 1 2 3 4 feels very superior M not at all understanding of others 0 1 2 3 4 very understanding F of others

very cold in relations 0 1 2 3 4 very warm in F with others relations with others goes to pieces under pressure 0 1 2 3 4 stand up well under M with others pressure with others

Note: F- Feminine scale, M- Masculine scale 119

Using the following scale, please rate the extent to which you believe that each of the following statements describes you.

1 = strongly disagree 2 = disagree 3 = neither disagree nor agree 4 = agree agree neither 5 = strongly agree disagree Strongly agree agree Strongly Strongly disagree disagree Strongly 1. I feel comfortable around people. ± ± ± ± ± 1 2 3 4 5 2. I have a good word for everyone. ± ± ± ± ± 1 2 3 4 5 3.* I have little to say. ± ± ± ± ± 1 2 3 4 5 4.* I have a sharp tongue. ± ± ± ± ± 1 2 3 4 5 5. I make friends easily. ± ± ± ± ± 1 2 3 4 5 6. I believe that others have good intentions. ± ± ± ± ± 1 2 3 4 5 7.* I keep in the background. ± ± ± ± ± 1 2 3 4 5 8.* I cut others to pieces. ± ± ± ± ± 1 2 3 4 5 9. I am skilled in handling social situations. ± ± ± ± ± 1 2 3 4 5 10. I respect others. ± ± ± ± ± 1 2 3 4 5 11.* I would describe my experiences as somewhat dull. ± ± ± ± ± 1 2 3 4 5 12.* I suspect hidden motives in others. ± ± ± ± ± 1 2 3 4 5 13. I am the life of the party. ± ± ± ± ± 1 2 3 4 5 14. I accept people as they are. ± ± ± ± ± 1 2 3 4 5 15.* I don’t like to draw attention to myself. ± ± ± ± ± 1 2 3 4 5 16.* I get back at others. ± ± ± ± ± 1 2 3 4 5 17. I know how to captivate people. ± ± ± ± ± 1 2 3 4 5 18. I make people feel at ease. ± ± ± ± ± 1 2 3 4 5 19.* I don’t talk a lot. ± ± ± ± ± 1 2 3 4 5 20.* I insult people. ± ± ± ± ± 1 2 3 4 5 Note: * reverse coded

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Using the following scale, mark each of the following 18 items as true or false. True False 1. I find it hard to imitate the behavior of other people. ± ± T F 2. At parties and social gatherings, I do not attempt to do or say things that ± ± T F others will like. 3. I can only argue for ideas which I already believe. ± ± T F 4.* I can make impromptu speeches even on topics about which I have almost ± ± T F no information. 5.* I guess I put on a show to impress or entertain people. ± ± T F 6.* I would probably make a good actor. ± ± T F 7. In a group of people I am rarely the center of attention. ± ± T F 8.* In different situations and with different people, I often act like very ± ± T F different persons. 9. I am not particularly good at making other people like me. ± ± T F 10.* I’m not always the person I appear to be. ± ± T F 11. I would not change my opinions (or the way I do things) in order to please ± ± T F someone else or win their favor. 12.* In have considered being an entertainer. ± ± T F 13. I have never been good at games like charades or improvisational acting. ± ± T F 14. I have trouble changing my behavior to suit different people and different ± ± T F situations. 15. At a party I let others keep the jokes and stories going. ± ± T F 16. I feel a bit awkward in company and do not show up quite as well as I ± ± T F should. 17.* I can look anyone in the eye and tell a lie with a straight face (if for a right ± ± T F end). 18.* I may deceive people by being friendly when I really dislike them. ± ± T F Note: * reverse coded

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For the next 33 questions, please rate to what extent you agree or disagree with the statements using the following scale.

1 = strongly disagree 2 = disagree 3 = neither disagree nor agree agree neither 4 = agree disagree Strongly agree agree Strongly

5 = strongly agree disagree Strongly 1. I know when to speak about my personal problems to others. ± ± ± ± ± 1 2 3 4 5 2. When I am faced with obstacles, I remember times I faced ± ± ± ± ± similar obstacles and overcame them. 1 2 3 4 5 3. I expect that I will do well on most things I try. ± ± ± ± ± 1 2 3 4 5 4. Other people find it easy to confide in me, ± ± ± ± ± 1 2 3 4 5 5.* I find it hard to understand the non-verbal messages of other ± ± ± ± ± people. 1 2 3 4 5 6. Some of the major events of my life have led me to re- ± ± ± ± ± evaluate what is important and not important. 1 2 3 4 5 7. When my mood changes, I see new possibilities. ± ± ± ± ± 1 2 3 4 5 8. Emotions are one of the things that make my life worth ± ± ± ± ± living. 1 2 3 4 5 9. I am aware of my emotions as I experience them. ± ± ± ± ± 1 2 3 4 5 10. I expect good things to happen. ± ± ± ± ± 1 2 3 4 5 11. I like to share my emotions with others. ± ± ± ± ± 1 2 3 4 5 12. When I experience a positive emotions, I know how to make ± ± ± ± ± it last. 1 2 3 4 5 13. I arrange events others enjoy. ± ± ± ± ± 1 2 3 4 5 14. I seek out activities that make me happy. ± ± ± ± ± 1 2 3 4 5 15. I am aware of the non-verbal messages I send to others. ± ± ± ± ± 1 2 3 4 5 16. I present myself in a way that makes a good impression on ± ± ± ± ± others. 1 2 3 4 5 17. When I experience a positive emotion, I know how to make it ± ± ± ± ± last. 1 2 3 4 5 18. By looking at their facial expressions, I recognize the ± ± ± ± ± emotions people are experiencing. 1 2 3 4 5 Note: * reverse coded 122

1 = strongly disagree 2 = disagree 3 = neither disagree nor agree 4 = agree agree neither 5 = strongly agree disagree Strongly agree agree Strongly disagree Strongly

19. I know why my emotions change. ± ± ± ± ± 1 2 3 4 5 20. When I am in a positive mood, I am able to come up with ± ± ± ± ± new ideas. 1 2 3 4 5 21. I have control over my emotions. ± ± ± ± ± 1 2 3 4 5 22. I easily recognize my emotions as I experience them. ± ± ± ± ± 1 2 3 4 5 23. I motivate myself by imagining a good outcome to tasks I ± ± ± ± ± take on. 1 2 3 4 5 24. I compliment others when they have done something well. ± ± ± ± ± 1 2 3 4 5 25. I am aware of the non-verbal messages other people send. ± ± ± ± ± 1 2 3 4 5 26. When another person tells me about an important event in ± ± ± ± ± his or her life, I almost feel as though I have experienced 1 2 3 4 5 this event myself. 27. When I feel a change in emotions, I tend to come up with ± ± ± ± ± new ideas. 1 2 3 4 5 28.* When I am face with a challenge, I give up because I ± ± ± ± ± believe I will fail. 1 2 3 4 5 29. I know what other people are feeling just by looking at ± ± ± ± ± them. 1 2 3 4 5 30. I help other people feel better when they are down. ± ± ± ± ± 1 2 3 4 5 31. I use good moods to help myself keep trying in the face of ± ± ± ± ± obstacles. 1 2 3 4 5 32. I can tell how people are feeling by listening to the tone of ± ± ± ± ± their voice. 1 2 3 4 5 33.* It is difficult for me to understand why people feel the way ± ± ± ± ± they do. 1 2 3 4 5 Note: * reverse coded

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Instructions: Please read each of the following nine statements carefully and decide if you ever feel this way about your job. If you have never had this feeling, fill in the “0” (zero) after the statement. If you have had this feeling, indicate how often you feel it by filling in the appropriate number (from 1 to 6) that best describes how frequently you feel that way.

0 = Never 1 = A few times a year or less 2 = Once a month or less 3 = A few times a month 4 = A few times a month Never

5 = A few times a week day Every Once a Week A few times a week A few times a month 6 = Every day less Once a or month

A few times a year or less

1. ± ± ± ± ± ± ± 0 1 2 3 4 5 6 2. ± ± ± ± ± ± ± 0 1 2 3 4 5 6 3. ± ± ± ± ± ± ± 0 1 2 3 4 5 6 4. ± ± ± ± ± ± ± 0 1 2 3 4 5 6 5. ± ± ± ± ± ± ± 0 1 2 3 4 5 6 6. ± ± ± ± ± ± ± 0 1 2 3 4 5 6 7. ± ± ± ± ± ± ± 0 1 2 3 4 5 6 8. ± ± ± ± ± ± ± 0 1 2 3 4 5 6 9. ± ± ± ± ± ± ± 0 1 2 3 4 5 6 Note: Items not printed due to license agreement. Modified and reproduced by special permission of the Publisher, CPP, Inc., Mountain View, CA 94043 from Maslach Burnout Inventory-GSB by Wilmar Schaufeli, Michael P. Leiter, Christina Maslach, and Susan E. Jackson. Copyright 1996 by CPP, Inc. All rights reserved. Further reproduction is prohibited without the Publisher’s written consent.

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Instructions: Please answer the following 24 questions by selecting the option that best fits your response.

H 1. When I know I must finish something soon: ± A. I have to push myself to get started ± B. I find it easy to get it done and over with

V 2. When I have learned a new and interesting game: ± A. I quickly get tired of it and do something else ± B. I can really get into it for a long time

P 3. If I’ve worked for weeks on one project and then everything goes completely wrong with the project: ± A. It takes me a long time to adjust myself to it ± B. It bothers me for a while, but then I don’t think about it anymore

H 4. When I don’t have anything in particular to do and I am getting bored: ± A. I have trouble getting up enough energy to do anything at all ± B. I quickly find something to do

H 5. When I am getting ready to tackle a difficult problem: ± A. It feels like I am facing a big mountain that I don’t think I can climb ± B. I look for a way that the problem can be approached in a suiTable manner

*P 6. If I had just bought a new piece of equipment (for example a tape deck) and it accidentally fell on the floor and was damaged beyond repair: ± A. I would manage to get over it quickly ± B. It would take me a long time to get over it

*H 7. When I have to solve a difficult problem: ± A. I usually don’t have a problem getting started on it ± B. I have trouble sorting things out in my head so that I can get down to working on the problem

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8. When I have been busy for a long time doing something interesting (for example reading a book or working on a project): ± A. I sometimes think about whether what I’m doing is really worthwhile ± B. I usually get so involved with what I am doing that I never think to ask whether it’s worthwhile

P 9. If I have to talk to someone about something important and, repeatedly, can’t find him or her at home: ± A. I can’t stop thinking about it, even when I’m doing something else ± B. I easily forget about it until I see that person

*V 10. When I read an article in the newspaper that interests me: ± A. I usually remain so interested in the article that I read the entire article ± B. I still often skip to another article before I’ve finished the first one

11. When I’m on vacation and having a good time: ± A. After a while I really feel like doing something completely different ± B. I don’t even think about doing anything else until the end of vacation

*P 12. When I am told that my work is completely unsatisfactory: ± A. I don’t let it bother me for too long ± B. I feel paralyzed

H 13. When I have a lot of important things to do and they must all be done soon: ± A. I often don’t know where to begin ± B. I find it easy to make a plan and stick with it

*V 14. When one of my co-workers brings up an interesting topic for discussion: ± A. It can easily develop into a long conversation ± B. I soon lose interest and want to go do something else

P 15. If I’m stuck in traffic and miss an important appointment: ± A. At first, it’s difficult for me to start do anything else ± B. I quickly forget about it and do something else

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V 16. When I am busy working on an interesting project: ± A. I need to take frequent breaks and work on other projects ± B. I can keep working on the same project for a long time *H 17. When I have to take care of something important which is also unpleasant: ± A. I do it and get it over with ± B. It can take a while before I can bring myself to do it

P 18. When something really gets me down: ± A. I have trouble doing anything at all ± B. I find it easy to distract myself by doing other things

H 19. When I am facing a big project that has to be done: ± A. I often spend too long thinking about where I should begin ± B. I don’t have any problems getting started

P 20. When several things go wrong on the same day: ± A. I usually don’t know how to deal with it ± B. I just keep on going as though nothing had happened

V 21. When I read something I find interesting: ± A. I sometimes still want to put the article down and do something else ± B. I will sit and read the article for a long time

*P 22. When I have put all my effort into doing a really good job on something and the whole thing doesn’t work out: ± A. I hadn’t have too much difficulty starting something else ± B. I have trouble doing anything else at all

*H 23. When I have an obligation to do something that is boring and uninteresting: ± A. I do it and get it over with ± B. It can take a while before I can bring myself to do it

*V 24. When I am trying to learn something new that I want to learn: ± A. I’ll keep at it for a long time ± B. I often feel like I need to take a break and go do something else for a while

Note: * reverse coded, H – hesitation scale, P-preoccupation scale, V- volatility scale This is the last Page. Thank you for completing this survey!

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APPENDIX B

IRB APPROVAL

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APPENDIX C

INFORMED CONSENT

Informed Consent: Participant

The study you are participating in is researching the individual difference variables that may be related to the use of emotional labor. Your participation will include filling out a survey and mailing that survey back to the researcher. It should take approximately 30 minutes to one hour to complete the survey. In addition we are asking that you give a short five minute survey to a co-worker to fill out about you and mail back to the researcher separate from your survey.

All answers will remain private and confidential. Participation in this study is completely voluntary and you may withdraw at anytime. Your return of this completed questionnaire implies your consent to participate in this research project. There are no foreseeable risks, discomforts, or benefits to be expected from participating in this survey. If you have any questions please feel free to contact me at via e-mail at [email protected] or you can

reach my advisor, Dr. Doverspike at 330-972-8372. This research project has been

reviewed and approved by The University of Akron Institutional Review Board for the

Protection of Human Subjects. Additional questions about your rights as a research

participant can be directed to Ms. Sharon McWhorter, Associate Director, Research

Services, at 1-330-972-7666 or 1-888-232-8790.

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