Affectivity, Emotional Labor, Emotional Exhaustion, and Emotional Intelligence in Coaching

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1 Journal of Applied Sport Psychology ISSN: (Print) (Online) Journal homepage: Affectivity, Emotional Labor, Emotional Exhaustion, and Emotional Intelligence in Coaching Ye Hoon Lee & Packianathan Chelladurai To cite this article: Ye Hoon Lee & Packianathan Chelladurai (2015): Affectivity, Emotional Labor, Emotional Exhaustion, and Emotional Intelligence in Coaching, Journal of Applied Sport Psychology, DOI: / To link to this article: Accepted author version posted online: 30 Sep Published online: 30 Sep Submit your article to this journal Article views: 82 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at Download by: [University of North Alabama] Date: 09 December 2015, At: 09:16

2 JOURNAL OF APPLIED SPORT PSYCHOLOGY, 00: 1 16, 2015 Copyright C Association for Applied Sport Psychology ISSN: print / online DOI: / Affectivity, Emotional Labor, Emotional Exhaustion, and Emotional Intelligence in Coaching YE HOON LEE Chung-Ang University PACKIANATHAN CHELLADURAI Troy University This study investigated the relationship among affectivity, emotional labor strategies, and emotional exhaustion, and the moderating effect of emotional intelligence in that relationship. There were 430 NCAA Division I coaches who completed questionnaires measuring affectivity, the forms of emotional labor, emotional exhaustion, and emotional intelligence, which were modified to fit the coaching context. The result indicated that positive affectivity predicted 3 forms of emotional labor. In addition, coaches surface acting and genuine expression significantly predicted their emotional exhaustion. Furthermore, emotional intelligence moderated the relationship between surface acting and emotional exhaustion. These results reveal the important role of emotional labor on coaches well-being. The term emotional labor, first introduced by Hochschild (1983), is defined as the regulation of both feelings and expression of emotions in order to be effective on the job (Grandey, 2000). Like physical and mental labor, employees and leaders purposefully produce and express job-appropriate emotions upon facing emotionally charged events in their interactions with customers and followers in exchange of one s wages. Failing to do so possibly provides one rationale for organizations to dismiss them (Ashforth & Humphrey, 1993). Emotional labor can be a crucial organizational psychology construct in sport, which has a potential to shed light on identifying an effective coping strategy that allows them to enhance individual outcomes (e.g., stress and health) and organizational outcomes (e.g., athlete and team performance). However, few studies have examined the role of emotional labor in coaching in particular and sport organizations in general. Received 8 March 2015; accepted 7 September Ye Hoon Lee is now at the Department of Health, Physical Education, and Recreation, University of North Alabama. Address correspondence to Ye Hoon Lee, Department of Health, Physical Education, and Recreation, University of North Alabama, Flowers Hall 403, Florence, AL ylee6@una.edu 1

3 2 Y. H. LEE AND P. CHELLADURAI GRANDEY AND GABRIEL S THREE-COMPONENT MODEL OF EMOTIONAL LABOR In the most recent review of the literature on the topic, Grandey and Gabriel (2015) presented a comprehensive model of emotional labor consisting of antecedents, outcomes, and moderators. They noted that emotional labor is an integrated function of emotion requirements of the situation, individual s internal emotion regulation process, and observable emotion performance. That is, these three components are intertwined to formulate the dynamic and reciprocal process of emotional labor. The regulatory strategies typically considered are surface acting and deep acting (Grandey, 2000). The antecedents in their model are person characteristics (personality traits, work motives, emotional abilities) and event characteristics (moods/emotions, customer treatment). The outcomes in their model are employee well-being (job satisfaction, burnout/health) and organizational well-being (interpersonal performance, task/overall performance). Finally, the moderators of the relationship between emotional labor and the outcomes are relational factors (including emotional traits/abilities, identification/values, and relational power/intimacy) and contextual factors (job status/autonomy, financial rewards, and social support). The focal emotion regulation strategies of surface acting and deep acting were presented based on Gross s (1998) emotion regulation model. In this model, emotion regulation includes two processes: antecedent-focused process and response-focused process. The responsefocused process is consistent with surface acting in that it involves the process of modifying only outward expressions without changing one s inner feelings. The labor in surface acting is essentially suppressing inappropriate feelings and faking the appropriate emotional display (Grandey, 2000). The antecedent-focused process relates to deep acting where individuals regulate the inner feelings before emotional expression (Gross, 1998). Whereas surface acting relates to observable expression, deep acting relates to changes in internal emotions to meet organizational expectations (Grandey, 2000). In both cases, the actor has learned to intervene either in creating the inner shape of a feeling or in shaping the outward appearance of one (Hochschild, 1983, p. 36). Recognizing the possibility that employees may be able to experience and display appropriate emotions spontaneously, Ashforth and Humphrey (1993) proposed the third category of emotional labor: genuine expression. Deep acting and genuine expression share similarity in that both involve the authentic expression of appropriate emotion (Diefendorff, Croyle, & Gosserand, 2005) and both are an antecedent-focused form of emotion regulation activated before an emotion has been fully elicited (Gross, 1998; Martinez-Inigo, Totterdell, Alcover, & Holman, 2007). However, genuine expression is different from deep acting in that it involves the spontaneous experience and expression of appropriate emotions and does not involve conscious acting (Martinez-Inigo et al., 2007). Thus, researchers have viewed deep acting as active and the latter as passive deep acting (Cropanzano, Weiss, & Elias, 2004). Although genuine expression does not involve conscious effort to change inner feelings, scholars of both emotions and emotional labor have suggested that it is a form of emotion regulation, because the term regulation in emotion literatures refers to changes to emotional response tendencies, which can be made either in a deliberate way or as an automatic process (Mauss, Cook, & Gross, 2007; Mikolajczak, Tran, Brotheridge, & Gross, 2009). Accordingly, we included genuine expression in our model.

4 EMOTIONAL LABOR DYNAMICS IN COACHING 3 AFFECTIVITY AND EMOTIONAL LABOR Affectivity, defined as the sum of individual mood states (Watson, Clark, & Tellegen, 1988), is considered a key individual difference variable that affects the levels and types of emotional labor displayed by service employees (Austin, Dore, & O Donovan, 2008) and sport performance (Martinent, Campo, & Ferrand, 2012). Schaubroeck and Jones (2000) noted that the extent to which individuals perceive that they are required to express or suppress certain types of emotional expression may depend as much on their emotional predispositions as it does on the objective characteristics of their organizational role (p. 182). Thus, an understanding of enduring affective dispositions should provide insights on how individuals select an emotional labor strategy. Positive Affectivity Positive affectivity, defined as the inherent tendency of individuals to experience positive and pleasurable moods (Watson & Tellegen, 1985), reflects a challenge-like, energetic engagement and optimism along with pleasurable interactions among athletes (Jackson, 1995). Based on these characteristics, individuals who are higher in positive affectivity have been found to put more effort in changing their inner feelings required by the display rule and thus engage less in surface acting and more in deep acting (Diefendorff et al., 2005). Accordingly, it is posited that coaches positive affectivity would be negatively related to surface acting but positively related to deep acting. In addition, a recent review by John and Gross (2007) on the role of extraversion and emotional regulation sheds light on the potential linkage between positive affectivity and genuine expression. It was found that extraverts, as compared to introverts, were more able to express both positive and negative emotions genuinely across social situations. As positive affectivity has been found to strongly predict extraversion (R 2 ranged.66.84; for a more detailed result, see Watson, 2000), it is posited that positive affectivity would be positively related to genuine expression. Negative Affectivity Negative affectivity refers to a stable tendency of a person to experience negative emotions across time and situational differences (Watson et al., 1988). Research has consistently shown that those high on negative affect are more likely to engage in surface acting, which involves faking or suppressing their emotions, than to modify their feelings (Brotheridge & Grandey, 2002; Brotheridge & Lee, 2002; Gosserand & Diefendorff, 2005). In contrast, Brotheridge and Lee (2002), Diefendorff et al. (2005), and Gosserand and Diefendorff (2005) reported a negative, albeit nonsignificant, relationship between negative affectivity and deep acting. Furthermore, Diefendorff et al. found no relationship between negative affectivity and genuine expression. Accordingly, we posit that negative affectivity will be positively related to surface acting and there will be no relationship between negative affectivity and deep acting, and genuine expression. EMOTIONAL LABOR AND EMOTIONAL EXHAUSTION A number of scholars have found that emotional labor required by organizational norms can negatively affect individual well-being (for a review, see Hülsheger & Schewe, 2011). More specifically, emotional labor may result in emotional exhaustion, defined as a lack of energy and a feeling that one s emotional resources are depleted (Maslach & Jackson, 1986). In their meta-analysis, Hülsheger and Schewe (2011) noted that when employees

5 4 Y. H. LEE AND P. CHELLADURAI engage in surface acting, they are more likely to experience emotional dissonance (i.e., a discrepancy between a felt emotion and the expressed emotion), resulting in a psychological strain that leads to emotional exhaustion. Furthermore, surface acting requires an individual to exert psychological effort to adhere to the organizational display rule and suppress his or her genuine emotion. This effort and strain along with emotional dissonance deplete one s emotional resource, and lead to depersonalized relationships which, in turn, lead to emotional exhaustion (Brotheridge & Grandey, 2002). Indeed, Dale and Weinberg (1990) suggested that the process of the excessive expenditure of mental and emotional energy contributes to job burnout among coaches. Thus, we hypothesized that coaches surface acting would be positively related to emotional exhaustion. Grandey (2000) noted that deep acting also requires psychological effort to change one s inner feelings. However, deep acting generates little emotional dissonance, because one s displayed emotions are congruent with expressed ones. Thus, we hypothesized that coaches deep acting would be negatively related to emotional exhaustion. Finally, individuals genuine expression barely requires effort or entails emotional dissonance, which in turn may not lead to emotional exhaustion. Empirical evidences of previous research in teaching domain have also supported this relationship (Martinez-Inigo et al., 2007; Taxer & Frenzel, 2015). Thus, we posit that coaches genuine expression would be negatively related to emotional exhaustion. It needs to be noted that emotional exhaustion is one of three dimensions of burnout (the other two being cynicism and inefficacy). We have chosen it as the only dependent variable because it has been considered the central quality of burnout and the most obvious manifestation of this complex syndrome (Maslach, Schaufeli, & Leiter, 2001, p. 402). In addition, we hypothesized the link between the two forms of affectivity and emotional exhaustion to be mediated by the three forms of emotional labor, as personality differences were known as important variables in understanding the differential impact of emotional labor on employees working (Judge, Woolf, & Hurst, 2009). Empirical research has found that positive affectivity or extraversion is negatively related to emotional exhaustion (Iverson, Olekalns, & Erwin, 1998; Judge et al., 2009), whereas negative affectivity or neuroticism is positively related on emotional exhaustion (Bakker, Van Der Zee, Lewig, & Dollard, 2006; Cano-Garcia, Padilla-Munoz, & Carrasco-Ortiz, 2005). Based on evidence related to the effects of emotional labor to emotional exhaustion noted earlier, we posit that the three forms of emotional labor would mediate the relationship between two forms of affectivity and emotional exhaustion. EMOTIONAL INTELLIGENCE AS A MODERATOR As noted, surface acting possibly contributes to negative health outcomes among coaches. However, this relationship could be moderated by one s emotional intelligence, defined as the ability to perceive, understand, regulate, and use emotion (Mayer & Salovey, 1997). Emotional intelligence has been found to have particular relevance in the study of emotional labor in psychology (Austin et al., 2008) and job burnout in teaching context (Chan, 2006). There has also been a growing interest in emotional intelligence as an important construct for coaches and athletes because practitioners believed that the construct is significantly related to sport coaching efficacy (Thelwell, Lane, Weston, & Greenlees, 2008), leadership effectiveness in organizational settings (Mayer & Salovey, 1997), and athlete performance (Meyer & Fletcher, 2006). Previous studies have also shown that emotional intelligence could help foster effective coping with current events and chronic stress (e.g., Folkman & Moskowitz, 2000). Mayer and Salovey (1997) proposed that emotional intelligence is composed of (a) perceiving emotions in the self and others, (b) understanding of emotions, (c) regulating emotion in

6 EMOTIONAL LABOR DYNAMICS IN COACHING 5 the self, and (d) utilization of emotion to facilitate thoughts. Each of these forms of emotional intelligence might render individuals less vulnerable to emotional exhaustion in that emotionally intelligent coaches are more likely to understand that they engage in surface acting only with the view to enhance the performance of their athletes and teams. That understanding is likely to mitigate the negative effects of surface acting including emotional exhaustion. In essence, then, coaches high on emotional intelligence are expected to be tactical emotional laborers who are more skilled in performing emotional labor, which in turn would make such labor less stressful and more satisfying. Accordingly, emotional intelligence should minimize the negative impact of surface acting and enhance the positive effects of deep acting and genuine expressions on emotional exhaustion. This perspective is consistent with Grandey and Gabriel s (2015) model, wherein emotional traits/abilities are seen as moderators of the relationship between emotional performance and employee well-being. THE CURRENT STUDY In summary, this study investigated the relationship among affectivity, emotional labor strategies, and emotional exhaustion in NCAA Division I coaches and the moderating effect of emotional intelligence on the emotional labor emotional exhaustion relationship. This focus on coaches emotional labor is critical because it has a potential to affect the wellbeing of the coaches themselves and the well-being of the organization in terms of improved performances of the athletes and teams. This research is, in fact, the verification of the Grandey and Gabriel (2015) conceptual model in the athletic context. More specifically, the purposes of this study were threefold: (a) to examine the relationship between two forms of affectivity (i.e., personality trait) and three forms of emotional labor, (b) to examine the relationship between the forms of emotional labor and emotional exhaustion (i.e., employee well-being), and (c) to examine the moderating role of emotional intelligence (i.e., emotional abilities) in the relationship between the three forms of emotional labor and emotional exhaustion. Furthermore, Wagstaff, Fletcher, and Hanton (2012) suggested incorporation of new constructs to nurture the field of sport psychology. Emotional labor is the recent organizational construct that has received the growing interests in such organizational sciences as organizational behavior and organizational psychology (Grandey & Gabriel, 2015). Although emotions and emotional regulation have been studied in organizational psychology in sport (e.g., Wagstaff, 2014; Wagstaff et al., 2012), relatively little attention has been given to emotional labor construct. We believe that our study fills this void by introducing the new and critical concept of emotional labor in coaching and organizational psychology in sport. METHOD Participants The census method was chosen after we obtained the list of all coaches in NCAA Division I program from a commercial website. Of the total 6,806 coaches so identified, 1,888 names were duplicated, leaving 4,918 coaches eligible to participate in the study. Of these, 464 coaches returned the completed questionnaires for a response rate of 9.4%. As 34 incomplete responses were excluded, the final tally of respondents was 430 head coaches (male = 278 [65.3%]; female = 152 [34.7%]; Caucasian = 375 [85%]), who coached men in 19 different sports and women in 21 different sports. Their ages ranged from 23 to 74 (M age = 42.6 years). The mean hours of contact with athletes was 4 hr per day (range = 1 14 hr), and the average coaching experience was years.

7 6 Y. H. LEE AND P. CHELLADURAI Measures Affectivity We used the shorter version of Positive Affectivity (four items) and Negative Affectivity (four items) Scales (Watson et al., 1988) to measure coach affectivity. The 5-point scale ranged from1(very slightly or not at all)to5(very strongly or extremely). The items included words reflecting each type of affectivity (e.g., interested and excited for positive affectivity; scared and upset for negative affectivity). Stebbing, Taylor, Spray, and Ntoumanis (2012) reported internal consistency estimate of.87 for positive affect and.82 for negative affect with the sample of athletic coaches. Surface acting and deep acting Both surface acting and deep acting were measured by Brotheridge and Lee s (2002) Emotional Labour Scale, which had been modified to fit the coaching context. The stem for the four items was On an average day at practice and competition, how often do you do each of the following when interacting with athletes? The response format was a 5-point scale ranging from 1 (never) to 5(always). The items were adapted to fit the coaching context. Sample items for surface acting are Hide my true feelings about a situation. For deep acting, a sample item is Make an effort to actually feel the emotions that I need to display to others. Brotheridge and Lee reported an alpha of.86 for surface acting and.89 for deep acting. Genuine expression In the absence of a scale for genuine expression specific to coaching, a three-item scale was developed for the purpose of this study based on the measures of expression of naturally felt emotions developed by Diefendorff et al. (2005). The respondents were required to indicate the extent to which they expressed their spontaneous and situational appropriate emotions on a 5-point scale from 1 (never)to5(always). The items were (a) I express genuine emotions to athletes, (b) I naturally experience appropriate emotions and express so, and (c) I express the emotions that I spontaneously experienced. Emotional exhaustion To keep the questionnaire brief, we employed a shorter (five of nine items) and modified version of the Emotional Exhaustion subscale of the Maslach Burnout Inventory (Maslach & Jackson, 1986) to measure coaches emotional exhaustion. The deleted items were (a) Working with athletes is really a strain on me, (b) I feel I am working too hard on coaching, (c) Working with athletes directly puts too much stress on me, and (d) I feel like I am at the end of my rope. The retained items were (a) I feel emotionally drained at coaching, (b) I feel used up at the end of the day, (c) I feel fatigued when I get up in the morning and have to face another day on the coaching, (d) I feel burnout out from coaching, and (e) I feel frustrated on coaching. Responses were rated on a 7-point format from 0 (never) to6(every day). A sample item is I feel emotionally drained at coaching. The word work was changed to coaching in all items. Donahue et al. (2012) reported a Cronbach s alpha of.91 with a sample of professional coaches. Emotional intelligence Emotional intelligence was measured using the 16-item Wong and Law Emotional Intelligence Scale (Wong & Law, 2002). The 6-point response format ranged from 1 (strongly disagree) to6(strongly agree). The scale consists of four dimensions that are consistent with Mayer and Salovey s (1997) definition of emotional intelligence. Sample items are I have a

8 EMOTIONAL LABOR DYNAMICS IN COACHING 7 good sense of why I have certain feelings most of the time for self-emotion appraisal and I have good understanding of the emotion of people around me for understanding of emotion, I am able to control my temper and handle difficulties rationally for regulation of emotion, and I always set goals for myself and then try my best to achieve them for utilization of emotion. Emotional intelligence construct is the second-order factor that consists of those four dimensions, and high scores in each construct correspond to high levels of each emotional intelligence dimension. The reported internal consistency estimates of.86 (Johnson & Spector, 2007). We chose this scale because (a) it used Mayer and Salovey s definition of emotional intelligence reflecting its conceptualization, (b) it is shorter, and (c) there is good evidence of its reliability and validity (e.g., Shi & Wang, 2007; Wong & Law, 2002). Procedure Before the main study, a pilot study was conducted with 43 randomly selected head coaches at NCAA Division II programs in order to establish the validity and the reliability of the survey questionnaire. Based on their comments and confirmatory factor analysis (CFA) results, the survey items were modified and reduced in order to improve the psychometric properties of the questionnaires. Next, the face and content validity of the items were reviewed again by three sport management professors who have an expertise in research on organizational behavior and leadership and two PhD students who had practical coaching experience. Based on the result from the pilot study and the comments and suggestions from the panels, the final instrument was refined. An online survey was utilized for this study after the approval from the human subjects institutional review board at the university in order to protect human subjects. The researcher sent a prenotification with information that contained the overall description of the study and the upcoming study schedule and encouraged the participation. An message containing the purpose, procedure of the research, and a survey link preceded the questionnaire. With a view to encouraging recipients of the message to participate in the study, the message included informed consent, assurance of confidentiality, and the voluntary nature of participation in the study. Data Analysis In the first step, descriptive statistics and the reliability of the variables of the study were computed using SPSS In the second step, we used a structural equation modeling technique that is available through LISREL 8.80 to test both the measurement and structural models. First, CFA was conducted on the latent variables to check convergent and discriminant validity of the variables. Second, the proposed structural relationship was tested by assessing structural coefficients of the relationship among the constructs in the research model. Furthermore, we employed moderated structural equation models technique to test the moderating effect of emotional intelligence on the relationship between emotional labor strategies and emotional exhaustion. We specifically employed latent variable interaction model technique (Schumacker & Lomax, 2010). This model first generated the latent product of surface acting and emotional intelligence, deep acting and emotional intelligence, and genuine expression and emotional intelligence and tested whether the independent latent variables as well as the generated latent products predicted emotional exhaustion. The moderating role of emotional intelligence was indicated when the generated latent product was found to be significantly related to emotional exhaustion.

9 8 Y. H. LEE AND P. CHELLADURAI Table 1 Descriptive Statistics and Correlations Among Study Variables Positive affectivity (.80) 2. Negative affectivity.17 (.78) 3. Surface acting (.71) 4. Deep acting (.71) 5. Genuine expression (.73) 6. Emotional exhaustion (.89) 7. Appraisal of emotion (.82) 8. Understanding of emotion (.78) 9. Regulation of emotion (.86) 10. Utilizing of emotion (.77) M SD AVE Note. N = 430. Bivariate correlations presented in the lower diagonal are based on subscale score. Cronbach s alpha coefficients on the diagonal. AVE = average variance of extracted. p <.05. p <.01. RESULTS Reliability and Validity Assessment As a first step and due to the low response rate, we conducted t tests between the means of early and late respondents on each factor and found no difference in any of the factors (p >.05), which led us to conclude that nonresponse error was not a problem with this study (L. Miller & Smith, 1983). Results of CFA showed a reasonably fitting model, χ 2 /df (354.46/174) = 2.04, p <.05; root mean square error of approximation (RMSEA) =.048, standardized root mean square residual (SRMR) =.055, Tucker Lewis index (TLI) =.96, comparative fit index (CFI) =.97. All the items defined the latent variables well, as their respective coefficients were above.40 and ranged from.45 to.91 (Stevens, 1996). Further evidence of the discriminant validity of constructs was indicated by the average variance extracted for the two constructs exceeding the square of the correlation between the constructs as suggested by Fornell and Larcker (1981). All constructs showed sufficient discriminant validity. We employed MacCallum, Browne, and Cai s (2006) population discrepancy function (i.e., the discrepancy between model-implied covariance matrix and observed covariance matrix) to derive the effect size. For the measurement model, it was.40 (N = 430, df = 174, noncentrality parameter = ). Unlike the traditional effect size indexes (e.g., Cohen s d), which provide a meaningful strength of the parameter, it is difficult to provide thresholds for fit function, because it is a model-dependent index (MacCallum et al., 2006). Descriptive statistics, alpha coefficient, and correlation coefficients for all study variables are presented in Table 1. Structural Equation Modeling and Moderation Analysis Finally, structural equation modeling was conducted to test all hypotheses in our theoretical model. The goodness-of-fit statistics indicated that the structural model showed a reasonable fit, χ 2 /df ( /129) = 2.49, p <.05; RMSEA =.059, SRMR =.077, TLI =.95, CFI =.96. Effect size for the overall model-data fit was.57 (N = 430, df = 129, noncentrality parameter

10 EMOTIONAL LABOR DYNAMICS IN COACHING 9 Figure 1. Structural equation model showing the relationship between among positive affectivity, negative affectivity, surface acting, deep acting, genuine expression, emotional intelligence, and emotional exhaustion and standardized path coefficients. Note. Solid lines represent significant relationships; dotted lines represent nonsignificant relationships. Values in parentheses are standardized path coefficients when the mediation analyses were employed. p <.05. p <.01. = ). As shown in Figure 1, positive affectivity had a significant and negative relationship with surface acting (β =.38, t = 6.22) and a significant and positive association with deep acting (β =.32, t = 4.45) and genuine expression (β =.45, t = 6.24). In addition, negative affectivity had a significant and positive relationship with only surface acting (β =.24, t = 4.78), and showed no significant relationship with deep acting (β =.08, t = 1.29) or genuine expression (β =.11, t = 1.87). Surface acting had a significant and positive relationship with emotional exhaustion (β =.52, t = 8.49), whereas genuine expression had a significant and negative relationship with emotional exhaustion (β =.17, t = 2.55). However, there was no relationship between deep acting and emotional exhaustion (β =.05, t =.91). Regarding the moderating effect, moderated structural equation analysis showed that the effect of the interaction of emotional intelligence and surface acting on emotional exhaustion was significant (β =.14, t = 2.01), which indicates that coaches high on surface acting experiencing sharp decrease in emotional exhaustion with increased emotional intelligence, whereas coaches low on surface acting reported slight decreases in emotional exhaustion (see Table 2). Also, the differences in the effects of the interaction of emotional intelligence and surface acting on emotional exhaustion widened in the case of low emotional intelligence compared to the case of high emotional intelligence. In contrast, the interaction effects of emotional intelligence and deep acting (β =.04, t =.33) and emotional intelligence and genuine expression (β =.04, t =.43) on emotional exhaustion were not significant. Mediation Analysis Regarding the mediating role of emotional labor, we followed Iacobucci, Saldanhan, and Deng s (2007) advice to fit one structural model (rather than fitting a series of models and employing model comparisons) that includes both direct and indirect paths simultaneously. The significance of mediating effects and all direct and indirect effects were then tested using a bootstrapping procedure (using 1,000 resamples) to determine the 95% bias-corrected

11 10 Y. H. LEE AND P. CHELLADURAI confidence interval around these effects. In this study, only surface acting mediates the relationship between two forms of affectivity and emotional exhaustion (β =.31 for positive affectivity, β =.23 for negative affectivity). More specifically, the direct path between two forms of affectivity and emotional exhaustion were significant. Furthermore, both paths from positive affectivity and emotional exhaustion were significant (β positive affectivity surface acting =.30, p <.01, β surface acting emotional exhaustion =.33, p <.01). The total standardized indirect effect was.10 (p <.05). In addition, the mediation path from negative affectivity to emotional exhaustion was also significant in that β negative affectivity surface acting =.37, p <.01, β surface acting emotional exhaustion =.60, p <.01. The total standardized indirect effect was.07, p >.01. Thus, we can conclude that surface acting partially mediates the relationship between positive affectivity and emotional exhaustion and negative affectivity and emotional exhaustion. DISCUSSION The purpose of this study was to test a part of Grandey and Gabriel s (2015) model of emotional labor by examining the relationships among two antecedents (positive and negative affectivity), three emotional labor strategies (surface acting, deep acting, and genuine expression), the individual outcome of emotional exhaustion, and the moderator of emotional intelligence among NCAA Division I coaches. The results mostly supported the model shown in Figure 1, making important theoretical contributions to the literature on the topic. Consistent with previous findings in organizational settings (e.g., Brotherige & Grandey, 2002; Brotheridge & Lee, 2002; Diefendorff et al., 2005), our results showed that positive affectivity was positively related to deep acting and genuine expression whereas it was negatively linked with surface acting. Those high on positive affectivity are characterized as active, enthusiastic, and attentive, and they tend to experience positive emotions more frequently (Watson et al., 1988). In addition, positive emotion leads individuals to approach rather than to avoid issues and strive to find better ways to solve the problems they face (S. Miller & Schnoll, 2000). With these features, positive affectivity might be negatively related to emotionally superficial surface acting as in faking their emotions or suppressing inappropriate emotions. That positive affectivity was positively associated with deep acting may be a function of the nearly identical characteristics shared by positive affectivity and deep acting. S. Miller and Schnoll (2000) suggested that one of the characteristics related to positive affect is effective coping with challenge and stress, which leads to active coping strategy, defined as behavioral or psychological responses designed to change the nature of the stressor itself or how one thinks Table 2 Results of Moderated Structural Equation Model Estimates β SE t SA Emotional exhaustion DA Emotional exhaustion GE Emotional exhaustion SA EI Emotional exhaustion DA EI Emotional exhaustion GE EI Emotional exhaustion Note. N = 430. SA = surface acting; DA = deep acting; GE = genuine expression; EI = emotional intelligence. p <.05. p <.01.

12 EMOTIONAL LABOR DYNAMICS IN COACHING 11 about it. Thus, individuals with positive affectivity usually attempt to change their perceptions of stressors or situations, a strategy equated with the process of deep acting. Moreover, high positive affectivity individuals are more likely to engage in genuine expression, as deep acting becomes automatic and requires little effort. In sum, it is reasonable to conclude that positive affectivity is positively related to the active emotional labor strategies of deep acting and genuine expression. As hypothesized, negative affectivity was significantly and positively related only to surface acting, and it had no significant relationship with deep acting or genuine expression. This result is consistent with earlier findings (e.g., Brotheridge & Grandey, 2002; Brotheridge & Lee, 2002; Diefendorff et al., 2005; Grandey, 2000). The results imply that coaches high on negative affectivity may hide or fake feelings more often in fulfilling minimum role requirement. Watson and Tellegen (1985) found that people with high negative affectivity tend to view themselves and the world around them in a more negative way, thus, may feel helpless and not attempt to change the situation actively. Thus, negative affectivity are more likely to associated with surface acting, which entails only the change of facial display, gestures, and voice tone (Ashforth & Humphrey, 1993) without modifying inner emotion (i.e., deep acting). In partial support of our hypotheses regarding the consequence, surface acting and genuine expression were significantly related to emotional exhaustion, whereas deep acting did not relate to emotional exhaustion. That is, coaches who tend to suppress their emotions are more likely to be emotionally exhausted. Indeed, Van Middendorp et al. (2005) found that expressive suppression strategy was a cognitive resources consuming process that negatively affects social and psychological functioning. Thus, coaches who engage in surface acting exhaust their resources and, thus, are emotionally exhausted. Furthermore, we also found significant and negative association between genuine expression and emotional exhaustion. That is, coaches who express the desired emotion in a spontaneous way were less likely to experience emotional exhaustion. Results of Mauss et al. s (2007) experimental study showed that automatic anger regulation process successfully decreased participant s anger experience. The authors explained that automatic emotion regulation (equated with genuine expression) is a cost-free process. In our context, we can say that coaches with genuine expression did not have to expend any psychological and cognitive resources, which in turn led to less emotional exhaustion. In fact, the strategy of genuine expression had the effect of reducing emotional exhaustion. Contrary to our expectation, deep acting did not predict emotional exhaustion. In Grandey s (2000) view, deep acting requires a great deal of mental energy in the form of motivation, engagement, and role internalization. Thus, deep acting should positively relate to emotional exhaustion because of the energy and cognitive efforts involved to modify inner feelings. On the flip side, however, there could be a negative relationship between them because deep acting is more authentic and, thus, reduces emotional dissonance (Brotheridge & Lee, 2002). Thus, the relationship between the two variables can be mixed. Future studies may examine the independent and joint effects of deep acting and emotional dissonance on emotional exhaustion. We also proposed a moderating role of emotional intelligence in the relationship between emotional labor strategies and emotional exhaustion. The results of moderated structural equation model analysis (see Table 2) showed that emotional intelligence significantly and negatively moderated the relationship of surface acting with emotional exhaustion, whereas it had no moderating effect on the relationship between genuine expression and emotional exhaustion. First, coaches who were low on emotional intelligence reported increased emotional exhaustion at the higher level of surface acting compared to coaches high on emotional intelligence. That is, high emotional intelligence coaches compared to low emotional intelligence

13 12 Y. H. LEE AND P. CHELLADURAI coaches are less likely to fall prey to emotional exhaustion as a consequence of engaging in surface acting. The finding that emotional exhaustion may be influenced by how coaches regulate their emotions holds important implications for athletic directors and coaches. Overall, the results indicate that athletic directors and coaches need to acknowledge the importance of the way coaches deal with their experienced emotions. The level of emotional intelligence and the type of emotional labor strategy that coaches engage in is likely to influence emotional exhaustion. Given that affectivity is a stable characteristic (Watson et al., 1988) that is hard to change, the strategy should be focused on learnable skills that would counter or buffer the negative effects of surface acting. Thus, athletic departments may need to implement an emotional labor training program designed to encourage coaches to engage in the use of deep acting, which would become over time the effortless form of genuine expression. That is, as emotional labor itself is a type of labor or skill, it can be developed through training (Hochschild, 1983). For example, a training program can present a series of pictures or video clips that generates aversive mood to coaches and subsequently help them regulate those negative emotions and express them in more adaptive ways. Indeed, Christou-Champi, Farrow, and Webb (2015) found that structured training improved the efficiency of emotional regulation as indicated by decreased time required to regulate emotions and increased heart rate variability. Furthermore, participants in reappraise condition (i.e., deep acting) were able to automatically regulate their negative emotions after 2 weeks of training and became more habitual in their use of deep acting (i.e., genuine expression). In addition, our results show that coaches with high emotional intelligence were less likely to experience emotional exhaustion as a function of surface acting. In so far as emotional intelligence can be enhanced through training (Mayer & Salovey, 1997), training programs can be instituted to increase the level of coaches emotional intelligence. In offering training programs relating to both emotional labor and emotional intelligence, athletic departments may indeed be contributing to coaches personal outcomes. Regular performance management processes, including communication, rewards, social support, and recognition procedures, should also be initiated to minimize the negative impact of surface acting on coach well-being. Limitations and Recommendations for Future Research This study was cross-sectional and correlational; thus, causality and directionality among the variables cannot be inferred. Furthermore, this study is based on self-report data, which may not be accurate. Self-report information may contain social desirability error, which can imply a relationship between variables when no true relationship exists (i.e., Type I error). Thus, future studies may try to reduce such biases by gathering and analyzing perceptions of different audiences such as athletes regarding the emotional labor exhibited by a coach. In addition, all instruments used in this study were modified from other domains. We have several recommendations for future research. First, as this was a cross-sectional study without any features of an experimental or quasi-experimental study, no inference can be made regarding cause effect relationships among the variables of the study. Future research may employ experimental designs or longitudinal studies to verify the cause effect relationships. Second, although CFA showed that the data from the modified scales defined the construct well, future studies may develop new scales that are more relevant to the coaching context. Furthermore, the relationship between emotional labor and additional individual outcomes such as job satisfaction, organizational commitment, and organizational citizenship behavior can be investigated to verify Grandey and Gabiel s conceptual model. Finally, given the deficiencies of self-reports wherein respondents might have given socially responsible

14 EMOTIONAL LABOR DYNAMICS IN COACHING 13 responses, future studies may try to reduce such bias by gathering and analyzing perceptions of different audiences such as assistant coaches and athletes regarding the emotional labor exhibited by a focal coach. Our findings that (a) positive affectivity was positively related to deep acting and negatively related to surface acting, (b) negative affectivity was positively related to surface acting, and (c) surface acting was positively related to emotional exhaustion cumulatively imply that coaches high on positive affectivity are likely to thrive longer in the job than coaches high on negative affectivity. This speculation needs to be verified in future research. Future studies may implement an experiment to investigate the depletion of mental or emotional resources by emotional labor strategies. For example, researchers can manipulate emotional labor by asking coaches to suppress their reactions to an upsetting video related to sports, try to feel the emotions that are appropriate for the situation, or act naturally. During the process, the coaches sympathetic activation of the cardiovascular system can be rated to identify their physical and cognition exertion (Gross, 1998). Given that performance and outcome are emphasized in athletics, it is also important to verify if the dynamics of emotional labor has any effect on such outcomes as team performance (e.g., win loss percentage), athlete s perceived organizational climate, athlete s satisfaction, and athlete s trust toward coaches. A line of research in interpersonal emotional regulation provided evidence that interpersonal emotional regulation predicted positive interpersonal and performance outcomes in athletic teams and sport organizations (see Tamminen & Crocker, 2013). In a similar vein, coaches interpersonal emotional regulation identified as emotional labor is expected to contribute to organizational outcomes in sport. In conclusion, this study is a significant contribution to the literature on sport coaching and organizational psychology in sport in that it has integrated for the first time the important psychological constructs into a model applicable to the athletic context. More specifically, we have examined the relationship among antecedents (i.e., positive affectivity and negative affectivity), types of emotional labor (i.e., surface acting, deep acting, and genuine expression), a consequence (i.e., emotional exhaustion), and a moderator (i.e., emotional intelligence). The model can be extended in future research to include additional critical variables as antecedents (e.g., other personality variables), consequences (e.g., job satisfaction, team performance), and/or moderators (e.g., perceived social support and gender). The coaching context involves several contingent factors that could impact the dynamics of emotional labor and its consequences. FUNDING This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2014S1A5B ). REFERENCES Ashforth, B., & Humphrey, R. (1993). Emotional labor in service roles: The influence of identity. Academy of Management Review, 18, Austin, E., Dore, T., & O Donovan, K. (2008). Associations of personality and emotional intelligence with display rule perceptions and emotional labour. Personality and Individual Differences, 44, Bakker, A., Van Der Zee, K., Lewig, K., & Dollard, M. (2006). The relationship between the big five personality factors and burnout: A study among volunteer counselor. The Journal of Social Psychology, 146,

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