Emotional intelligence as moderator of the surface acting-strain relationship.The authors examined the moderating role of emotional intelligence in the surface acting-strain relationship. Specifically, the authors hypothesized that higher levels of emotional intelligence were associated with a weaker relationship between surface acting and strain (i.e., depressed mood at work, somatic complaints). Results supported the hypothesized relationships, and the authors found that higher emotional intelligence attenuated the positive relationship between surface acting and depressed mood at work and somatic complaints. Implications of the results, limitations of the study, and directions for future research are discussed.

Keywords: emotional intelligence; surface acting; emotional labor

Introduction

Over the past century, the United States economy evolved from a production orientation to a service orientation. With this evolution came a marked increase in the percentage of jobs requiring direct, face-to-face interactions with customers, in which interpersonal warmth and friendliness are deemed essential (Grandey, 2003). Whereas the golden rule of service with a smile does seem to help generate positive customer reactions, employees do not seem likely to always feel the emotions they need to display, due to a variety of reasons such as fatigue or unpleasant customers (Hochschild, 1983). To observe the organizational policies and emotional norms, employees invest a certain amount of emotional effort in their jobs to try to display organizationally desirable emotions. Hochschild (1983) defined this effort as emotional labor, which is the physical and mental management of one's feelings in order to express organizationally required emotions.

Hochschild (1983) presented an appealing case for the performance of emotional labor. She distinguished two types of emotional labor strategies employed by service workers to satisfy organizational requirements for emotional expression: deep acting and surface acting. Whereas in deep acting service workers try to align their inner feelings with their expressions, in surface acting, the worker simply portrays the situationally appropriate emotion to fulfill job requirements of customer service and care. Using this form of emotional labor, the service worker focuses only on emotional expression by putting on positive emotional masks without trying to actually experience the displayed emotions.

Why one may or may not surface act is one of the topics currently discussed in the literature. For example, Liu, Prati, Perrewe, and Ferris (in press) discussed the choice of emotional labor activities as dependent upon one's personal resources, finding that those with more personal resources at their disposal will be less likely to surface act. The findings of Beal, Trougakos, Weiss, and Green (2006) imply that surface acting is not the choice of individuals who experience more positive emotions than negative and those having a positive self-evaluation of his or her job role. Regardless of the reason one might or might not engage in surface acting, research demonstrates that whereas both forms of acting could have detrimental effects on employee physical and psychological health, surface acting tends to be particularly harmful. This impact appears to be primarily attributed to the disconnect between the employees' true feelings and those they must display (e.g., Abraham, 1998; Brotheridge &

Grandey, 2002; Brotheridge & Lee, 2002, 2003; Erickson & Ritter, 2001; Grandey, 2003; Pugliesi, 1999; Totterdell & Holman, 2003; Zapf, Vogt, Seifert, Mertini, & Isic, 1999).

Given the detrimental effects of surface acting, it is important to examine factors that might help attenuate its negative impact. Whereas there are many situational factors, such as the service climate of the organization, that might be of relevance (cf. Liu & Yang, 2006), several researchers have proposed that individual differences also play a role (e.g., Abraham, 1998, 2000; Grandey, 2000; Lam & Kirby, 2002). For example, Abraham (1998) suggested that self-monitoring may reduce the impact of emotional dissonance resulting from surface acting. She suggested that as the ability to monitor the situational cues and to control expressive behavior based on those cues, self-monitoring might make it relatively easy for individuals to manipulate their emotional expressions in social settings. Abraham (2000) also proposed that emotional intelligence may alleviate strain resulting from emotional labor. In the present study, we focus on the moderating effect of emotional intelligence in the surface acting-strain relationships.

Emotional intelligence is one's understanding of and ability to use the symbolism of emotion through mental processing, the display of facial expressions, tone of voice, and other forms of emotional display and self-regulation in order to influence one's own emotions and the emotions of others (Bar-On, 2000; Goleman, 1995; Mayer & Salovey, 1997; Mayer, Salovey, & Caruso, 2000; Salovey & Mayer, 1990). Individuals with high emotional intelligence are able to perceive and interpret emotions of self and others accurately and to use such emotional knowledge to facilitate thoughts and actions (Mayer & Salovey, 1997). The possession of emotional intelligence is regarded as a potentially valuable asset for organizational members, particularly in terms of the performance of emotional labor (Foo, Elfenbein, Tan, & Aik, 2004; Giardini & Frese, 2006; Johnson & Spector, 2007).

The study makes two major contributions to the literature. First, it examines emotional intelligence as a moderator, a largely underresearched relational position for the construct, especially with regard to the relationship between emotional labor efforts and outcomes (Johnson & Spector, 2007). Specifically, this study is among the first to examine the moderating role of emotional intelligence in the relationship between emotional labor and strain, and it echoes the call by many for such an investigation (e.g., Douglas, Frink, & Ferris, 2004; Grandey, 2000; Humphrey, 2006; Lam & Kirby, 2002). Second, it contributes to stress coping research and practices by examining a factor that potentially helps employees decrease, or avoid increasing, their strain. Our research provides empirical evidence that facilitates future research trying to better understand the strain-alleviating role of emotional intelligence. It also provides helpful insights for managers regarding organizational intervention programs, such as training and counseling.

Hypothesis Development

Zapf, Seifert, Schmutte, Mertini, and Holz (2001) suggested that surface acting is the physical attempt to conceal the discrepancy between the emotions one presents and the emotions one actually feels. The literature suggests that this form of emotional labor is closely associated with emotional dissonance, an aversive psychological state in which one experiences a sense of discrepancy between the real self and socially presented self (Hochschild, 1983). To some extent, surface acting serves as an active work stressor for employees because in surface acting the ongoing reflection on the real versus acted self makes one recognize the discrepancy, which often results in an unfavorable moral judgment of the self (Hochschild,

1983). Perhaps this moral judgment is due in part to the veiled nature of the act. Because surface acting involves the manipulation of false impressions and the hiding or masking of true feelings, it can be considered a form of deception (cf. Leidner, 1993; O'Hair & Cody, 1994; Payne, 2008).

There are certainly positives attributed to the act of masking emotions. In most cases, the customer desires and expects a cheerful and amicable demeanor from customer service associates. Accordingly, managers promote and reward this type of representation (Constanti & Gibbs, 2005). When the employee does not genuinely feel such emotions, surface acting serves to maintain a certain level of affective service delivery and prevent possible service glitches (Spitzberg & Cupach, 1984). Regardless of possible benefits, surface acting is still a form of deception that can adversely impact the employees' psychological well-being and their relationship with the customer (if the act is perceived as insincere).

At the individual level, emotional dissonance resulting from such deceptive behaviors is considered problematic. Consistently, emotional dissonance is demonstrated as a precursor of experienced stress, burnout, and self-alienation (Abraham, 1998; Hochschild, 1983; Lewig & Dollard, 2003). Recent studies show that surface acting is associated with both psychological strain, such as depression, job tension, and emotional exhaustion, and physiological strain, such as high blood pressure, heart disease, and cancer progression (Grandey, 2000; Liu, Perrewe, Hochwarter, & Kacmar, 2004; Schaubroeck & Jones, 2000; Totterdell & Holman, 2003; Zapf et al., 1999).

We propose that emotional intelligence helps attenuate the deleterious impact of surface acting on strain. The reasons are multifold. First, emotionally intelligent service providers are better able to align their levels of emotional engagement with the emotional demands of the situation, which makes the act of surface acting less socially inappropriate and consequently, less psychologically stressful. Not all service situations require full emotional engagement of service providers. Customer expectations for service provider warmth and friendliness change depending on situations (e.g., store busyness; Sutton & Rafaeli, 1988), and service providers adjust their emotional labor behavior based on such situational cues (Rafaeli, 1989). Surface acting is more readily ignored, disregarded, or forgiven by customers in certain situations; for example, when the service provider is busy (cf. Grandey, Fisk, Mattila, Jansen, & Sideman, 2005), when the customer is rushed for the service, or when the customer is overly demanding.

Situations like these either require only a minimum level of emotional engagement on the part of the employee or allow the employees to justify their withdrawal or lack of emotional engagement in the interactions (e.g., "She's not being reasonable!"). As a result, individuals with high emotional intelligence who surface act in such situations are less likely to feel the moral uneasiness that may result from surface acting. In contrast, individuals who are low on emotional intelligence are likely less able to discern the differential emotional demands prescribed by the situation. As a result, they will unnecessarily call up their emotional energy to surface act when it is not demanded, which results in increased emotional drainage leading to strain.

Moreover, emotionally intelligent individuals also are likely to reduce strain related to surface acting because of their ability to separate work from their personal emotional life. A precursor of self-alienation resulting from emotional labor is the mingling of the work role with the self (Hochschild, 1983). Emotionally intelligent individuals, however, are able to understand the

causes and effects of their emotional experiences and develop tactics to reduce the impact of work stressors (Abraham, 2000; Mayer & Salovey, 1997). Johnson and Spector (2007) argued that such individuals are able to quickly adapt to the conflict between surface acting and felt emotion. As such, they are more likely to reflectively engage or detach from certain emotional experiences from work, thus making surface acting less likely to result in strain. Accordingly, when individuals with high emotional intelligence surface act, they are able to more or less maintain a healthy degree of psychological and physical well-being.

Another reason why those with emotional intelligence are better able to handle such strain involves the ability to view a certain issue from multiple perspectives (Abraham, 1999; Bar-On, 2000; Goleman, 1995; Mayer & Salovey, 1997). By viewing their emotional behaviors from both personal and organizational perspectives, and in some cases to rationalize their surface acting behaviors cognitively, individuals with high emotional intelligence redirect their attention to organizational gain rather than individual loss resulting from surface acting (cf. Abraham, 1999). In addition, Johnson and Spector (2007) reasoned that individuals with higher emotional intelligence are more in tune with the feelings of others and therefore are more likely to adapt their emotions toward the needs of others, such as customers or associates. The thought that one is contributing to the greater good is likely to help individuals to bounce back from aversive experiences quickly and reduce strain.

In sum, it is proposed that the skills of emotionally intelligent individuals allow them to surface act appropriately with the purpose of efficiently and effectively fulfilling organizational requirements of emotional display, and also it may provide them the capability to recover quickly from the aversive impact of surface acting (i.e., when it occurs), such that individuals of high emotional intelligence are less likely to experience strain. For the present study, two types of strain are examined: psychological strain in the form of depressed mood at work and physical strain in the form of somatic complaints. As previously mentioned, these two forms of strain have been shown to be outcomes of surface acting efforts.

Accordingly, we hypothesize the following:

Hypothesis 1: Emotional intelligence will moderate the relationship between surface acting and strain--i.e., (a) depressed at work and (b) somatic complaints--such that the positive relationship between surface acting and strain will be attenuated when emotional intelligence is high.

Method

Sample

A total of 550 employees and managers from 29 stores of a retail bookstore chain were surveyed, and a total of 220 employees provided complete and useable data (40% response rate). Stores in the chain were primarily located in the southeastern quadrant of the United States, and the 29 stores were located in both urban and rural areas. Each store returned respective responses in bulk within the requested time frame. The sample was primarily female (69.5%) and White (81.0%), with 7.1% African American, 1.0% Asian, 5.2% Hispanic, and 5.7% who regarded themselves as multicultural. The average age was 31 years with a range of ages between 18 and 72. The average tenure with the organization was 2 years with a range of tenure between 1 month and 30 years. The education level of associates was split, with 46.2% having high school degrees and 52.4% having at least some college-level

course work. According to information provided by the human resources director, the sample characteristics were determined as representative of the demographics of the organization, indicating a lack of response bias.

Managerial positions were held by 26.2% of the sample. Managerial staff responses were included in the data because of the common duties (e.g., customer service) they share with sales associates. All associates surveyed were responsible for front-line customer service. Various duties of associates included helping customers locate, order, and/or purchase books, magazines, and other printed media. Some employees were only responsible for duties related to the operation of the in-store coffee shop, which required a similar level of customer service.

Measures

Emotional intelligence. The Self-Report Emotional Intelligence Test (SREIT; Schutte et al., 1998) was used to measure emotional intelligence. The SREIT is a 33-item self-report measure of emotional intelligence developed based on Mayor and Salovey's (1997) conceptualization of the construct. It has good reliability and is distinctive from the Big Five personality factors (Abraham, 1999, 2000; Schutte et al., 1998; Schutte & Malouff, 1999), which is considered an improvement over many other self-report measures (Ciarrochi, Deane,& Anderson, 2002).

The measure generally is identified as having facets, namely, optimism, social skills, emotional regulation, and utilization of emotions (Petrides & Furnham, 2000). We used the composite scores to assess the overall level of emotional intelligence, which is consistent with past research that states the measure could be used as a unidimensional scale (C6t6, 2005a; Law, Wong, & Mobley, 1998; Schutte & Malouff, 1999; Wong & Law, 2002). A 5-point Likert-type scale was used, with item responses ranging from strongly disagree to strongly agree. Sample items of the scale are "I know why my emotions change," "I use good moods to help myself keep trying in the face of obstacles," and "I know what other people are feeling just by looking at them" The internal consistency reliability estimate for this measure was calculated at [alpha] = .90.

Surface acting. Surface acting was measured using Grandey's (2003) five-item scale. The respondents were asked to report job-related actions used to portray organizationally required emotions when dealing with customers. A 5-point Likert-type scale was used, with item responses ranging from never to always indicating the frequency of specific actions performed by the respondent. Items for the scale include questions such as "I fake a good mood" and "I just pretend to have the emotions I need to display for my job." The data yielded a reliability of [alpha] = .88 for this scale.

Depressed mood at work. The 10-item depressed mood at work scale created by Quinn and Shepard (1974) was used to measure psychological strain. A 5-point Likert-type scale was used, with item responses ranging from never to always indicating the frequency of symptoms experienced by the respondent. This scale contained items such as "I feel downhearted and blue" and "I am more irritable than usual." In this study, the depressed mood at work scale had a reliability of [alpha] = .82.

Somatic complaints. Respondents were asked questions from the five-item somatic anxiety scale (House & Rizzo, 1972). Four additional health questions were added to the survey.

Specifically, the additional items were: "I experience chest pains," "I experience headaches," "My blood pressure is abnormally high when checked," and "I experience colds and minor illnesses." A 5-point Likert-type scale was used, with item responses ranging from never to always indicating the frequency of symptoms experienced by the respondent. The reliability for this measure was [alpha] = .75.

Control Variables

The frequency of outward emotional expression (e.g., surface acting; Gross et al., 1997; Lawton, Kleban, Rajagopal, & Dean, 1992), the level of emotional intelligence (Goleman, 1995; Mayer, Caruso, & Salovey, 1999), and the tendency to experience stress (Antoniou, Polychroni, & Vlachakis, 2006; Birditt, Fingerman, & Almeida, 2005; Neupert, Miller, & Lachman, 2006) may differ depending on age, gender, and experience (e.g., tenure and job position). In addition, negative affectivity is associated with both surface acting (Brotheridge & Grandey, 2002; Schaubroeck & Jones, 2000) and psychological strain (Spector, Chen, & O'Connell, 2000). Therefore, these variables were included as control variables in the analyses.

Negative affectivity. Negative affectivity was measured with the 10-item Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). Respondents were asked to respond using a 5-point scale ranging from very slightly or not at all to extremely according to the extent they generally felt each item, which captured individual trait rather than state affectivity. The reliability of the scale was [alpha] = .83.

Data Analyses and Results

Before testing the hypothesis, a confirmatory factor analysis (CFA) was conducted for emotional intelligence, surface acting, depressed mood, and somatic tension to examine their construct validity, using all the items that were hypothesized to measure the four underlying constructs. Items for emotional intelligence were made to load on four predefined factors based on a prior exploratory factor analysis (detailed information is available from the first author upon request). The measurement model fit the data well. The fit indices of the model are as follows: chi-square ([chi square]) = 2923.64, degree of freedom (df) = 1518, p < .01, Non-Normed Fit Index (NNFI) = .90, Comparative Fit Index (CFI) = .90, standardized root mean square residual (SRMR) = .077, and root mean square of approximation (RMSEA) = .066. All the factor loadings and measurement errors were in acceptable ranges and were significant at .05. As such, it is concluded that there is adequate evidence for the convergent and discriminant validity of the constructs.

Because we used surveys to collect self-report data, we conducted Harman's (1967) one-factor test to assess the possible existence of common method bias. The exploratory factor analysis indicated that there was no one factor that accounted for the majority of the variance, which suggested that no substantial common method bias exists in the data. Furthermore, because the data were collected from multiple stores, it is possible that store membership has a significant impact on the dependent variables, in which case it would be necessary to control for store membership in the analysis.

To examine this possibility, a hierarchical linear modeling analysis was conducted using the one-way analysis of variance (ANOVA) with random effects model. The results indicated that the amount of variance in the dependent variables explained at the store level was limited.

Specifically, 7% of the variance in depressed mood and 3% of the variance in somatic tension was explained by store membership. It is thus concluded that multilevel analysis is not necessary for the data analysis, and we proceeded to analyze the data with hierarchical moderated regression. In the regression analysis, surface acting and emotional intelligence were mean-centered to reduce collinearity problems that can accompany the analysis of interactions. Descriptive statistics and correlations of all study variables are presented in Table 1. As expected, surface acting was positively related to both depressed mood at work and somatic complaints.

Results of the interaction of emotional intelligence and surface acting on depressed mood at work are shown in Table 2. As seen in Model 1, demographic variables were not significantly related to depressed mood at work. Negative affectivity was positively and significantly associated with depressed mood at work, consistent with prior findings. Model 2 indicated that emotional intelligence and surface acting both demonstrated significant main effects on depressed mood at work. As shown in Model 3, the interaction term was significantly related to depressed mood at work ([beta] = -. 11, p < .05). Model 3 explained a significant incremental portion of variance in depressed mood at work ([DELTA][R.sup.2] = .01, p < .05), and the interaction is graphed in Figure 1, using values one standard deviation above and below the mean.

[FIGURE 1 OMITTED]

The level of explained variance falls within the expected range for moderator effects in field studies (e.g., Champoux & Peters, 1987; Chaplin, 1991). As seen in the figure, individuals reported an increased level of depressed mood at work when the frequency of surface acting was high. Simple slope analysis (Aiken & West, 1991) indicated that the simple slopes for high emotional intelligence condition (.16, p < .05) and low emotional intelligence condition (.35, p < .01) both were significant. The pattern of the data indicated that when emotional intelligence was low, the line depicting the relationship between surface acting and depressed mood had a steeper slope than when emotional intelligence was high. Thus, Hypothesis la was supported.

Results of the interaction of emotional intelligence and surface acting on somatic complaints are shown in Table 3. As seen in Model 1, similar to the results for depressed mood, negative affectivity, but not demographic variables, was significantly related to somatic complaints. Model 2 indicated that emotional intelligence and surface acting both demonstrated significant main effects on somatic complaints. As shown in Model 3, the interaction term was significantly related to somatic complaints ([beta] = -.13, p < .05). Model 3 explained a significant incremental portion of variance in somatic complaints ([DELTA][R.sup.2] = .01, p < .05), and the interaction is graphed in Figure 2, using values one standard deviation above and below the mean.

As seen in the figure, individuals reported an increase in somatic complaints when the frequency of surface acting was high. Simple slope analysis (Aiken & West, 1991) indicated that the simple slopes for high emotional intelligence condition (.18, p < .05) and low emotional intelligence condition (.34, p < .01) both were significant. The pattern of the data however indicated that when emotional intelligence was low, the line depicting the relationship between surface acting and somatic complaints had a steeper slope than then emotional intelligence was high. Thus, Hypothesis lb was supported.

[FIGURE 2 OMITTED]

Discussion

Ever since Hochschild (1983) called attention to the negative outcomes of emotional labor in service environments, researchers have worked to understand the emotional labor process and how subsequent negative outcomes of such behavior may be quelled. The emotional labor literature indicates that surface acting represents a form of emotional effort exhibiting more detrimental effects on the individual and organization than other acting efforts. Surface acting is stressful to employees not only because of the physical effort involved, but also because of its psychologically taxing nature. Although not proposed as a formal hypothesis, it is found in the current study that surface acting is associated with both psychological and physical strain. The consistent finding in the literature regarding the negativity of surface acting adds to the importance of better understanding its antecedents, outcomes, and potential moderators. Accordingly, it behooves organizational leaders to understand what resources may be available to reduce or inhibit the detrimental outcomes of such stress-laden work behaviors.

Contributions of the Study

With rare exceptions (e.g., Mikolajczak, Menil, & Luminet, 2007; Wong & Law, 2002), emotional intelligence and emotional labor have not been simultaneously examined. This gap in the literature is surprising because both constructs are concerned about the management of emotional experiences and expressions. Because service employees may exercise various emotional labor strategies, whose performance both require different emotion regulatory skills and are associated with different outcomes, and because emotional intelligence is a skill set that helps individuals regulate emotions more effectively, it is likely that emotional intelligence and emotional labor jointly will influence individual outcomes.

Recently, many have called for an investigation of the moderating role of emotional intelligence, particularly in the areas of emotional labor processes and social effectiveness, (e.g., Douglas et al., 2004; Grandey, 2000; Lam & Kirby, 2002). This study echoes such a call by exploring the role of emotional intelligence in the emotional labor-strain relationship, and findings in this study provide evidence to represent emotional intelligence as a positive influence in alleviating strain resulting from surface acting. Whereas other individual difference variables such as trait affectivity (e.g., Schaubroeck & Jones, 2000) have been examined as moderators between emotional labor and strain, an examination of the moderating role of emotional intelligence represents a new avenue for investigation because it concerns particularly the manner in which individuals deal with emotions. By focusing on surface acting, the study also echoes the call for a more fine-grained examination of various emotion regulatory strategies and their impacts (Cote, 2005b).

Furthermore, recent works (e.g., Cote, 2005b; Hareli & Rafaeli, in press) indicate that human interaction is dynamic and inherently cyclical with regard to emotional influences. For instance, a certain representation by an individual (e.g., a customer service representative) in the interaction will prompt a response from the interactive partner (e.g., the customer) whose response will further solicit reaction from the first. Although this study does not provide insight into the influence of emotional intelligence at the depth of understanding needed to reveal information about these cyclical processes of an interaction, it does provide evidence that emotional intelligence may be a useful moderator in this dynamic exchange. Further investigations should attempt to uncover the influence of emotional intelligence on the cycles

of interaction within the emotional labor process.

Second, this study also contributes to stress coping research and practices. The idea that emotions play a role in the stress coping process is acknowledged. To date however, only a small number of researchers have explored the protective role of emotional intelligence regarding experienced strain (e.g., Jordan, Ashkanasy, & Hartel et al., 2002; Mikolajczak et al., 2007). Our research provides much-needed empirical evidence that should help guide future research in this regard. The success in this investigation of establishing support for emotional intelligence as a moderator of the relationship between emotional labor stressors (e.g., surface acting) and physical and psychological strain further supports the moderating function of emotional intelligence as well as its beneficial effect on strain. Also, it provides organizations seeking to develop intervention programs a different approach (e.g., providing emotional intelligence training; Goleman, 1998) that may be more likely to result in improved behavioral outcomes for employees faced with work-related stressors.

Limitations of the Study

The current study has several limitations. Worthy of mention are the cross-sectional design and the self-report measure of emotional intelligence. Unfortunately, the data collected were not sufficient to delve into the how regarding the moderating influence of emotional intelligence on experienced strain. At this point, it was only possible to establish that there is an influence. Future research should consider using more process-oriented, within-person research methods; for example, experience sampling technique, to capture exactly what emotionally intelligent individuals do to inhibit stress associated with surface acting (e.g., functional use of emotional labor, use of social support, broadened perspective taking).

Also, the measurement of emotional intelligence is a concern, as it is in most emotional intelligence studies. As stated previously, emotional intelligence is a set of skills providing individuals with the knowledge and understanding of emotional symbols to be used toward certain objectives. The most recent discussions of emotional intelligence measurement in research provide questions about whether it is appropriate to measure maximum ability (what one is capable of doing) or average ability (what one usually does; Chapman & Hayslip, 2005). In the case of measuring one's ability, the most theoretically sound method of measure would involve a performance measure, whereas the respondents' actual use of emotional intelligence skills may be measured more appropriately with self-report assessment.

The primary concern of using a self-report measure is that it is evaluating something other than the individuals' actual emotional intelligence (e.g., personality traits). As well, currently available performance-based measures also have certain limitations, such as the rating of performance and time demand on participants (Ciarrochi et al., 2002). We chose SREIT as our measure for emotional intelligence because of its relatively well-established psychometric validity and its brevity, though it is not without issues. Just as the measurement issue is a continuing concern in the field of emotional intelligence, the measure we used might not perfectly capture the entire domain of emotional intelligence. We suggest that the results of the study be interpreted in light of such limitations.

In addition, common method variance could be a concern if it affects the results as all the data were self-report. It should be noted however that there is a growing collection of resources in the literature showing that common method variance is not necessarily enough to reject results from single-source data (Breland, Treadway, Duke, & Adams, 2007). Several studies provide

evidence for the acceptance of this assertion (Breland et al., 2007; Crampton & Wagner, 1994; Doty & Glick, 1998; Spector, 2006). We acknowledge however that such self-report data in total may be considered a limitation to this study.

Finally, the results, though adequate in significant support of the hypotheses, should be interpreted with caution. The fact that the data supported our contentions certainly promotes the need for further study regarding these interactions. It could be that emotional intelligence is antecedent to certain coping mechanics, such as social support relationships at work (Cheung & Tang, 2007; Zapf, 2002), that have a more direct and resounding impact on the relationship between surface acting and strain.

Directions for Future Research

This study provides a number of directions for future research. We focused on emotional intelligence as a uniform construct, but also it is popularly considered to be a multidimensional construct. It would be interesting to examine whether particular subdimensions of emotional intelligence play more important roles in moderating the surface acting-strain relationship than other subdimensions. A better understanding of the moderating role of each of the subdimensions will give further insights as to what emotional intelligence does in the emotional labor process and provide useful practical guidance in employee training intended to increase emotional intelligence abilities. The factor structure of a scientifically acceptable emotional intelligence measure however must first be established. In addition, given the complicated issue of effectively measuring emotional intelligence, it is also beneficial to try to understand the construct step by step by examining its individual elements, such as emotional expression, emotion recognition (e.g., Elfenbein & Ambady, 2002, 2003), and emotion regulation (e.g., Gross, 1998; Gross & John, 2002).

Researchers also might consider examining other constructs similar conceptually to the dimensions of emotional intelligence. For instance, empathy (Decety & Jackson, 2006) may play a role in the specified relationship by providing the ability to understand the emotions of others and formulate responses accordingly. Perspective taking (Parker & Axtell, 2001) also may play a role in the understanding of the emotions of others and viewing these emotions as being influenced by events and not representative of the person expressing the emotion. Another closely related concept is self-monitoring (Gangestad & Snyder, 2000), which perhaps may motivate the performance of emotional labor in certain situations. These concepts, among others, could reveal important facets of the social interaction dynamics of the emotional labor process.

Another potential extension of the current research is to examine whether the impact of emotional intelligence differs for different forms of emotional labor. In the case of surface acting, investigations might analyze whether emotional intelligence is more beneficial for suppressing negative emotions or for facilitating positive emotions. Future research also can further our understanding by examining the moderating role of emotional intelligence in the surface acting-strain relationship by using other strain variables in the analysis, such as emotional exhaustion and burnout.

Furthermore, this research generates several questions with regard to deep acting. As the first-order correlation between emotional intelligence and surface acting indicates, surface acting does not appear to be the emotional labor method of choice for those with higher levels of emotional intelligence. Are these individuals more likely to deep act? Or, are they simply

more likely to express authentic positive emotions? Perhaps those with high emotional intelligence are better able to facilitate the emotions required so that acting is unnecessary. Perhaps they avoid the behavior because of the potential detrimental effects, personally and socially. This is certainly another important aspect of emotional labor that should be examined more thoroughly.

Implications for Practice

Practically speaking, the current research is important to illustrate the advantage emotional intelligence may afford employees who are faced with stressful job demands, especially where emotional labor is required. Strain resulting from such demands may be quite costly in the form of turnover (Wright & Cropanzano, 1998), decreased work performance (Wright & Bonett, 1997), and other outcomes detrimental to the employee and the organization. The results of this study provide evidence that emotional intelligence is a mitigating coping factor that may serve to alleviate stress-related outcomes. Also, because the emotional labor effort of focus was surface acting, managers of organizations that require this type of emotional labor may take heed that emotional intelligence may be useful to enable employees to withstand this particular stressor more effectively.

Indeed, it would behoove organizations to address the needs of employees involved in the emotional labor process because employees providing customer service are the most visible representatives of the organization. The implications of this investigation are particularly important to human resource professionals and business leaders who manage employees in the service and sales industries. Past research shows that emotional intelligence can be enhanced through training (e.g., Jordan et al., 2002). Thus, innovative human resource practices are needed to increase employees' ability to handle their own and others' emotions in the service encounters. Leadership may also play a role in increasing employee emotional competencies and reducing the negative impact of less effective emotion regulation strategies (e.g., surface acting). For example, it has been suggested that authentic leaders may facilitate an organizational environment where employees learn to respond to emotionally taxing circumstances more effectively (Liu, Zhu, & Perrewe, in press).

The finding that emotional intelligence can help reduce strain from surface acting however does not indicate that service workers with high emotional intelligence can simply surface act. In fact, our results indicated that surface acting induces strain regardless of the level of emotional intelligence, and as seen in the correlation table, emotional intelligence was negatively related to surface acting (r = -.18, p < .05). It is likely that individuals with high emotional intelligence have a larger repertoire of emotional labor strategies at hand and are able to choose those most appropriate according to the situational needs and use each of them skillfully. As such, it is important for professional trainers to make service employees aware of the negative impact of surface acting on their general well-being.

On the other hand, organizations also need to foster a service-oriented climate in which employees treat each other with respect, friendliness, and support. Whereas pressure from various aspects of work may result in the use of surface acting, sometimes unavoidably, a strong service climate will help increase employees' level of emotional energy, which may help them to deliver the affective service effectively (Liu & Yang, 2006).

Conclusion

In sum, although the potential benefits of emotional intelligence have been discussed and investigated, for the most part, there is much yet to be evaluated within the widespread realm of organizational research. There are many areas of organizational concern that may be beneficially influenced by this empowering attribute. We propose that emotional labor is one such area, and we hope the results of the present study stimulate further research interest in the important area.

10.1177/1548051808328518

Authors' Note: Please address correspondence to L. Melita Prati, Department of Management, College of Business, East Carolina University, Bate Building, Room 3112, Greenville, NC 27858; e-mail: pratil@ecu.edu.

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L. Melita Prati

East Carolina University, Greenville, North Carolina

Yongmei Liu

University of Texas at Arlington

Pamela L. Perrewe

Gerald R. Ferris

Florida State University, Tallahassee

L. Melita Prati is an assistant professor of management at East Carolina University. She received her PhD in business administration from the Florida State University in 2004. Her research interests include leadership, emotional intelligence, emotional labor, and stress. Her research has appeared in journals including International Journal of Organizational Analysis, Journal of Applied Social Psychology, and Journal of Management, Spirituality, and Religion.

Yongmei Liu is an assistant professor of management at the University of Texas at Arlington. She received her PhD degree in management from the Florida State University in 2006. Her current research interests include emotion in organizations, interpersonal relationships at work, and career development of young professionals. Her research has appeared in journals including Human Resource Management Review, Personnel Psychology, Journal of Occupational Health and Psychology, Journal of Vocational Behavior, and Human Performance.

Pamela L. Perrewe is the Haywood and Betty Taylor Eminent Scholar Chair of Business Administration at Florida State University. She received her PhD in Business Administration from the University of Nebraska. She has research interests in the areas of job stress, work-family interface, emotion, and personality. She is the author of numerous articles published in such journals as the Journal of Applied Psychology, Organizational Behavior and Human Decision Processes, Academy of Management Journal. and Journal of Occupational Health Psychology. She serves as lead editor of the annual series, Research in Occupational Stress and Well Being. She is a fellow of the Southern Management Association, the Society of Industrial and Organizational Psychology, and the American Psychological Association.

Gerald R. Ferris is the Francis Eppes Professor of Management and Professor of Psychology at Florida State University. He received a PhD in Business Administration from the University of Illinois at Urbana-Champaign. He has research interests in the areas of social influence processes in human resources systems, and the role of reputation in organizations. He is the author of numerous articles published in such journals as the Journal of Applied Psychology, Organizational Behavior and Human Decision Processes, Personnel Psychology, Academy of Management Journal, and Academy of Management Review. He served as editor of the annual series, Research in Personnel and Human Resources Management, from 1981-2003. He has been the recipient of a number of distinctions and honors, and in 2001 was the recipient of the Heneman Career Achievement Award from the Human Resources Division of the Academy of Management.

Table 1Means, Standard Deviations, and Intercorrelations of Variables

Variables M SD 1 2 3

1. Age 31.18 13.36 2. Gender 1.70 .46 -.01 3. Education 1.50 .52 .20 ** -.10 4. Tenure 1.95 3.19 .52 ** -.01 .03 5. Job 1.27 .48 .00 .10 .09 6. Negative 1.57 .48 -.33 ** -.04 .09 affectivity 7. Emotional 3.86 .40 -.03 .17 * -.04 intelligence 8. Surface acting 2.16 .77 -.28 ** .00 .04 9. Somatic 1.83 .57 -.24 ** .02 .03 complaints10. Depressed mood 2.15 .56 -.24 ** -.05 .01

Variables 4 5 6 7

1. Age 2. Gender 3. Education 4. Tenure 5. Job .08 6. Negative -.22 ** -.09 affectivity 7. Emotional .00 .12 -.37 ** intelligence 8. Surface acting -.21 ** .00 .37 ** -.18 ** 9. Somatic -.20 ** -.09 .41 ** -.28 ** complaints10. Depressed mood -.21 ** -.14 * .50 ** -.43 **

Variables 8 9

1. Age 2. Gender 3. Education 4. Tenure 5. Job 6. Negative affectivity 7. Emotional intelligence 8. Surface acting 9. Somatic .35 ** complaints10. Depressed mood .38 ** .63 **

Note: N = 220. Coding for gender in the model was 0 = male,1 = female; tenure was measured by years; coding for job 1sales, 2 = management.

* p < .05. ** p < .01.

Table 2Regression Results for Depressed Mood

Model 1 Mode1 2 Model 3

Age -0.05 -0.07 -0.06Gender -0.03 0.02 0.02Tenure -0.08 -0.06 -0.07Education -0.01 -0.01 -0.01Job -0.09 -0.08 -0.08Negative 0.45 ** 0.27 ** 0.27 ** affectivitySurface acting 0.20 ** 0.20 **Emotional -0.29 ** -0.28 ** intelligenceEmotional -0.11Intelligence x Surface ActingModel F 12.93 ** 15.64 ** 14.57 **Adjusted [R.sup.2] 0.25 0.35 0.36Adjusted [DELTA][R.sup.2] 0.10 ** 0.01 *

Note: N = 220. Standardized beta values are used forreporting. Coding for gender in the model was 0 = male, 1 =female; tenure was measured by years; coding for job was 1 =sales, 2 = management.

* p < .05. ** p < .01 (one-tailed test for independent andmoderating variables).

Table 3Regression Results for Somatic Complaints

Model 1 Mode1 2 Model 3

Age -0.09 -0.09 -0.08Gender 0.04 0.06 0.07Tenure -0.08 -0.06 -0.07Education 0.03 0.03 0.03Job -0.05 -0.05 -0.05Negative 0.35 ** 0.22 ** 0.22 **Surface acting 0.20 ** 0.20 *Emotional -0.17 * -0.16 * intelligenceEmotional -0.13 * Intelligence x Surface ActingModel F 8.19 ** 8.60 ** 8.32 **[R.sup.2] 0.17 0.22 0.23[DELTA][R.sup.2 ] 0.05 ** 0.01 *

Note: N = 220. Standardized beta values are used forreporting. Coding for gender in the model was 0 = male, 1 =female; tenure was measured by years; coding for job was 1 =sales, 2 = management.

* p < .05. ** p < .01 (one-tailed test for independent andmoderating variables).