Development and validation of the hospitality emotional labor scale

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Tourism Management 27 (2006) 1181–1191 www.elsevier.com/locate/tourman

Research Article

Development and validation of the hospitality emotional labor scale Kay Hei-Lin Chua,, Suzanne K. Murrmannb a

Department of Hospitality Management, Tunghai University, P.O. Box 891, Tunghai University, Taichung, Taiwan, ROC b Department of Hospitality and Tourism Management, Virginia Tech., 356 Wallace Hall, Blacksburg, VA 24060, USA Received 11 October 2005; accepted 13 December 2005

Abstract This paper describes the development and validation of a 19-item instrument (hospitality emotional labor scale, HELS) for assessing employees’ perception of emotional labor in hospitality organizations. Three studies were conducted to purify the scale items, examine the scale’s dimensionality, and to evaluate the scale’s reliability, factor structure, and validity. The internal consistency coefficients from the three studies, ranging from .69 to .88, evidence the reliability of the HELS. The paper concludes with a discussion of potential applications of the scale. r 2006 Elsevier Ltd. All rights reserved. Keywords: Emotional labor; Service acting; Hospitality employee; Scale development; Emotive dissonance; Emotive effort; Hospitality emotional labor scale

1. Introduction As the economy in most of the developed countries has shifted from manufacturing to the service industry, the nature of job role requirements has changed. Where workers in factories are hired for their ‘‘hands’’ or ‘‘brains,’’ in service firms, employees are hired for their sincerity and concern for the guest. In most service jobs, employees need to perform not only intellectual and physical labor but also emotional labor, which Hochschild (1983) defined as ‘‘the management of feeling to create a publicly observable facial and bodily display; emotional labor is sold for a wage and therefore has exchange value’’ (Hochschild, 1983, p.7). In the service industry in general, and the hospitality industry in particular, being friendly or nice to people is a value-added part of the product that employees provide (Schneider & Bowen, 1985). Most managers believe that the friendliness and good cheer of employees are strongly related to customer satisfaction and increase customer commitment, and loyalty, and therefore, affect bottom Corresponding author. Tel.: +886 4 2310 9268; fax: +886 4 2350 6053.

E-mail addresses: [email protected] (K.H. Chu), [email protected] (S.K. Murrmann). 0261-5177/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.tourman.2005.12.011

lines (Albrecht & Zemke, 1985; Bowen, Siehl, & Schneider, 1989). To secure employees’ emotional expression, some organizations have clear display rules to regulate employees’ behavior. ‘‘Show an upbeat attitude at every table’’ or ‘‘Put energy and enthusiasm into every guest interaction’’ are common instructions in employee handbooks. Since Hochschild’s (1983) research, interest in emotional labor has accelerated rapidly over the past decades. The theoretical development of emotional labor originated in case studies on flight attendants (Hochschild, 1983), fastfood employees (Leidner, 1993), wait staff (Adelman, 1989; Paules, 1991; Rose, 2001), amusement park employees (Van Maanen & Kunda, 1989), and supermarket cashiers (Rafaeli & Sutton, 1987). In recent years, researchers (Brotheridge & Lee, 2003; Grandey, 2000; Kruml & Geddes, 2000; Morris & Feldman, 1996; Schaubroeck & Jones, 2000) have used a more systematic, quantitative approach to measure the dimensions and nature of emotional labor presented by nurses, bank tellers, and university administrators. In respect to the theory of the development process of emotional labor, we found that researchers examined the behavior of hospitality employees, such as waitresses or fast food employees, to accumulate knowledge and construct a theory of emotional labor, yet very few empirical studies have collected

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Step 1: Item Generation Create Items Step 2: Content Adequacy Assessment Test for conceptual consistency of items Step 3: Questionnaire Administration Determine the scale for items Determine an adequate sample size Administer questions with other established measures Step 4: Factor Analysis Exploratory to reduce the set of items Confirmatory to test the significance of the scale Step 5: Internal Consistency Assessment Determine the reliability of the scale Step 6: Construct Validity Determine the convergent and criterion-related validity Step 7: Replication Repeat the scale-testing process with a new data set Fig. 1. Guidelines for scale development and analysis. Source: Hinkin, Tracey, and Enz (1997).

quantitative evidence from hospitality employees to support the rich texture data of theoretical research. To address the need for an emotional labor scale that is tailored to measure hospitality employees’ emotional labor presentation, we developed an instrument called the hospitality emotional labor scale (HELS). The purpose of this article is to describe the development of the HELS, and to present the scale’s properties and potential applications. The steps employed in constructing the scale closely parallel the scale development guidelines provided by DeVellis (1991) and Hinkin, Tracey, and Enz (1997). Fig. 1 provides an overview of the steps. 2. Theoretical framework and item generation The first step in the development of any scale is to construct a sound conceptual specification of the construct being scaled (Churchill, 1979). The conceptual framework for the HELS was derived from the work of researchers who have examined the meaning of emotional labor (Brotheridge & Grandey, 2002; Brotheridge & Lee, 2003; Grandey, 2000; Kruml & Geddes, 2000) and from

comprehensive qualitative research studies that defined emotional labor and illuminated its dimensions along with describing how emotional labor is formulated and performed (Ashforth & Humphrey, 1993; Hochschild, 1983; Rafaeli & Sutton, 1987). Hochschild (1983) conceptualized emotional labor based on a service acting paradigm, which suggests service is a ‘‘show’’ where the service employee is the ‘‘actor,’’ the customer is the ‘‘audience,’’ and the work setting is the stage. The work place, such as a restaurant, provides the setting and context that allows actors, i.e., wait staff, to perform for audiences, the diners. The interaction between actors and audiences is based on their mutually understood definition of the setting, specified as occupational or organizational norms or display rules. There are three level of acting involved: surface acting, deep acting, and genuine acting (Ashforth & Humphrey, 1993; Hochschild, 1983). In surface acting, employees simulate emotions that are not actually felt, by changing their outward appearance (i.e., facial expression, gestures, or voice tone) when showing required emotions. Deep acting occurs when employees change not only their physical expressions, but also their inner feelings by using imagination or recalling past cheerful experiences to generate appropriate positive emotions. Finally, employees are engaged in genuine acting when their felt emotions are congruent with expressed emotion and display rules. For example, a bartender may show genuine caring when trying to comfort a depressed customer. In recent empirical studies, emotional labor has been conceptualized from either a job-focused approach (Morris & Feldman, 1996) or employee-focused approach (Brotheridge & Grandey, 2002). The former emphasizes the job characteristics (frequency, duration, variety, and intensity of employee–customer interaction) inherent in any emotional labor jobs, whereas the latter focuses on the emotion management process, which affects the way employees act out emotional labor. The employee-focused approach has received increasing research attention because this approach closely follows Hochschild’s acting paradigm of the emotion management process (Brotheridge & Lee, 2003). Approaching emotional labor from the acting perspective can help in understanding the internal process of emotional labor and the impact of such labor on organizations’ effectiveness as well as employee well-being. Based on service acting, researchers have developed different instruments to measure emotional labor (Brotheridge & Lee, 2003; Kruml & Geddes, 2000). Kruml and Geddes (2000) developed an instrument to measure emotional labor according to surface acting, deep acting, and genuine acting. They identified two dimensions: emotive dissonance and emotive effort (a ¼ :68; a ¼ :66, respectively). In the dimension of emotive dissonance, surface acting and genuine acting are at opposite ends of a continuum. It reflects the degree to which an employee’s expressed emotions aligns with his or her true feelings. Emotive effort represents the concept of deep acting as

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employees need to exert effort to achieve the right emotion for work. For the emotional labor scale (ELS), Brotheridge and Lee (2003) developed three items to measure surface and deep acting, respectively (a ¼ :79 for surface acting, a ¼ :83 for deep acting). The intent of the abovementioned scales is to measure emotional labor from an employee perspective using three acting techniques. However, to assess hospitality employees’ emotional labor presentation, these scales need to be modified to fit the context of the hospitality industry as well as to be improved for better reliability. To develop a HELS, we followed the employee-focused approach to conceptualize emotional labor. Emotional labor is operationally defined as ‘‘the degree of manipulation of one’s inner feelings or outward behavior to display the appropriate emotion in response to display rules or occupational norms.’’ This working definition emphasizes the different degrees of effort employees exert for the purposes of manipulating or changing their emotional state and behavior. The construction of the HELS was embedded in this operational definition and the three service acting levels of emotional labor.

2.1. Generation of scale items The next step in scale development is to generate an item pool. DeVellis (1991) suggests that the ideal size of the item pool should be four times larger than the final scale, or as small as 50% larger than the final scale. To generate a large item pool, two sources were used to generate scale items: the existing literature, and focus groups. The researchers compiled instruments in the literature that related to emotional labor in general, the three acting mechanisms in particular, and then formulated an item pool. Specifically, these items were drawn from the studies of Brotheridge and Lee (1998), Kruml and Geddes (2000), Grandey (1999), and DeLay (1999). The items were then reworded to fit the context of the hospitality industry. A total of 31 items were drawn from the literature. Additional items were then generated from interviews with one focus group of hospitality students and two focus groups of hotel employees in southwestern Virginia in the United States. Nine students with at least 6 months’ hotel/restaurant work experience at customer-contact positions were selected for the student focus group. Thirteen local hotel employees who worked at front desks (n ¼ 4), restaurants (n ¼ 2), banquets (n ¼ 3), in sales (n ¼ 3), and in the housekeeping department (n ¼ 1) were selected for the two hotel employee groups. Fifty-one items were generated in the focus groups. Although the items generated were somewhat redundant, DeVellis (1991) indicated that having multiple and redundant items is important since items’ irrelevant idiosyncrasies will cancel out during the scale purification process. Therefore, considerable redundancy in the item pool is desired when developing a new scale. The initial 82-item pool tapped the entire spectrum of

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surface acting, deep acting, genuine acting, and emotive dissonance. The 82-item instrument was subjected to three stages of data collection and refinement. The first study focused on condensing the instrument by retaining only those items capable of discriminating well across respondents. The second study was conducted to explore the underlying factor structure. Lastly, the third study, confirmatory in nature, was conducted to re-evaluate the factor structure by analyzing fresh data from different samples. 3. Study 1: scale purification The initial items were incorporated into a questionnaire for a pilot study. The purpose of this process was to ‘‘confirm expectations regarding the psychometric properties of the new measure’’ (Hinkin et al., 1997, p. 105). A seven-point scale ranging from ‘‘strongly disagree’’ (1) to ‘‘strongly agree’’ (7), with no verbal labels for scale points 2–6, accompanied each item. This questionnaire was administered to hospitality students who were enrolled in senior level classes at three American universities. One hundred and twenty-two hospitality students with working experience participated in the pilot study. After excluding cases with missing values, a total of 117 responses were retained for analysis. Although we used a student sample in this initial scale purification process, the results of descriptive analysis of data revealed that the students who participated in this study had had sufficient hospitality work experience which justified the use of a student sample. The majority of the respondents had hospitality industry experience (91.5%), and most of them had 1–3 years of work experience (68.3%), with an average length of 2.3 years. The data were subjected to exploratory factor analysis (EFA) using a Varimax rotation to reduce the number of items. Churchill (1979) suggested that the purification of a measurement instrument should begin with the computation of the coefficient a. The value of the coefficient a ranged from .62 to .77 for the three acting dimensions and this implied that it was necessary to remove some items from each dimension to improve the a value. Items with corrected item-to-total correlation lower than .30 were discarded (Churchill, 1979). As individual items were removed, a values were recomputed for the remaining items and the new corrected correlations were evaluated for further deletion of items. Nineteen items were removed from the analysis. A total of 63 items, with a values ranging from .69 to .81, were retained for further unidimensionality examination. EFA was performed to identify and confirm the underlying structure of the items and to further reduce their number. Unlike other statistical techniques such as multiple regression in which multicolinearity among the data matrix is a violation of its underlying assumptions, some degree of multicolinearity is desirable in the case of factor analysis since its objective is to identify interrelated sets of

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variables (Hair, Anderson, Tatham, & Black, 1998). The Kaiser–Meyer–Olkin (KMO) measure and Bartlett’s test of sphericity were used to ensure that the data had inherent sufficient correlations to perform EFA. The KMO index was .80, and Bartlett’s test of sphericity was significant at a level of .00, which justified the use of EFA. The data matrix was then examined for underlying factors using EFA with a Varimax rotation. The first factor analysis resulted in a 13-factor solution, which explained 70% of variance. To achieve a more meaningful solution, items were deleted if they loaded equally heavily onto more than one factor, and their loadings were smaller than .55, in consideration of the small sample size (Hair et al., 1998). Each time items were removed from the analysis, the factor analysis was re-run and coefficient a was re-computed until a satisfactory result was achieved. After a series of deletions reduced the number of items to 20, a clear two-factor structure emerged. The process of scale purification in this initial stage reduced the number of items from 82 to 20. Among these 20 items, the factor analysis extracted two factors which explained 57% of variance with item loadings exceeding 0.55. This result is similar to Brotheridge and Lee’s (2003) results, which generated four factors explaining 60.5% of the total variance. As can be seen in Table 1, factor one was comprised of 15 items with factor loadings greater than .55, which explained 39% of variance. Among these 15 items, eight items measured surface acting, five items measured genuine

acting, and two items measured emotive dissonance. Kruml and Geddes (2000) indicated that surface acting and genuine acting present the two opposite ends of a continuum (emotive dissonance). Employees feel high emotive dissonance when they use more surface acting than genuine acting when performing emotional labor, or vice versa. As a result, this factor was labeled ‘‘emotive dissonance.’’ Five deep acting items were loaded onto the second factor with loadings exceeding .55, which explained 18% of variance. This factor was labeled ‘‘emotive effort’’. The two-factor structure corresponded to that of Kruml and Geddes’s study (2000). 3.1. Scale reliability and validity Reliability is one of the major criteria for evaluating research instruments. Reliability coefficients of the HELS were calculated to examine the internal consistency of the factors (Table 1). The results of the reliability analysis indicated that the HELS exhibits good internal consistency (a ¼ :80 for the emotive dissonance factor, a ¼ :69 for the emotive effort factor). Validity is the extent to which the items accurately measure what they are supposed to measure (Hair et al., 1998). Having high reliability is a necessary but not sufficient condition for a valid scale. The scale also needs to satisfy other conceptual and empirical criteria to be considered a valid scale. The most basic type of validity is face or content validity (Zikmund, 1997), i.e., agreement

Table 1 Initial stage scale purification factor analysis (n ¼ 117) Attribute

Factor 1

My smile is often not sincere (S). I fake the emotions I show when dealing with customers (S). I feel as if I have a split personality when interacting with customers because I act not like myself at all (S). I put on an act in order to deal with customers in an appropriate way (S). I put on a mask in order to express the right emotions for my job (S). I display emotions that I am not actually feeling (S). I behave in a way that differs from how I really feel (Di). I fake a good mood when interacting with customers (S). I believe that I display very genuine hospitality when dealing with customers (G). I look forward to chance interactions with customers at work (G). I actually feel the emotions that I need to show to do my job well (G). I display sincere hospitality when interacting with customers (G). My interactions with customers are very robotic (S). I am usually a happy worker (G). I have to cover up my true feelings when dealing with customers (Di). When helping customers, if I pretend I am happy, I can actually start to feel it (D). When getting ready for work I tell myself that I am going to have a good day (D). I think of pleasant images when I am getting ready for work (D). I try to actually experience the emotions that I must show when interacting with customers (D). I have to concentrate more on my behavior when I display an emotion that I don’t actually feel (D).

.775 .765 .750 .739 .690 .686
.682 .674 .669 .634 .625 .623 .611 .596
.574

Cronbach’s a Variance explained (%) Kaiser–Meyer–Olkin measure of sampling adequacy Bartlett’s test of sphericity (significance level)

.80 38.9 .89 .000

Note: S ¼ surface acting; G ¼ genuine acting; D ¼ deep acting; Di ¼ emotive dissonance.

Factor 2

.721 .692 .653 .614 .561 .69 17.89

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among professionals that a scale is measuring what it is supposed to measure. Researchers and experts in the area of hospitality management were asked to review the items and their matched dimensions. It was suggested that four emotive dissonance items be removed because they did not exhibit strong face validity with regard to the emotive dissonance construct. The number of items was reduced from 20 to 16 after reviewing face validity. Some items were reworded to achieve greater clarity. The remaining 16 items all exhibited satisfactory face/content validity for the HELS. The factor structure that emerged from this study conformed to Kruml and Geddes’s (2000) two-factor structure of emotional labor. However, a close examination of the remaining items revealed that the six items derived from Kruml and Geddes’ emotional labor scale were dropped from the earlier stage of the analysis due to small factor loadings. In consideration of theoretical validity, Kruml and Geddes’ emotional labor items were retained in the questionnaire of the second stage analysis. Therefore, the HELS was comprised of 22 items with fourteen emotive dissonance items and eight emotive effort items. This 22-item HELS was then examined for its unidimensionality on a different set of data. 4. Study 2: scale property examination The second stage of scale development is to evaluate its robustness. To accomplish this, the 22-item scale was used to measure emotional labor of hotel employees. A convenience sample of 97 employees was selected from three hotels located in southwestern Virginia. Data were analyzed to obtain a values and a factor-loading matrix with a Varimax rotation. The majority of the respondents were female (57.4%), Caucasian (56.0%), and between 21 and 29 years old (48.2%). Most respondents worked in a food service area (24.7%) or at the front desk (16.9%). The average tenure at all customer-contact positions was almost 10 years (M ¼ 9:7), with the longest tenure being 37 years, and the shortest being 6 months. A majority of the employees had either one to less than 4 years’ tenure (26.4%) or 4 to less than 8 years’ tenure (21.8%). Similar to that of the first study, the principal component factor analysis extracted two factors. However, the initial results of the factor analysis differed somewhat from the first-stage findings. Six emotional labor items developed by Kruml and Geddes (2000) showed good item-to-total correlations, and loaded onto their designated dimensions with sufficient factor loadings. These results demonstrated that including the Kruml and Geddes’s items in the scale was a correct judgment call to secure the scale’s theoretical validity. However, the emotive dissonance dimension had a lower a than that obtained from the first data set. After reviewing the correlation matrix, we found that three emotive dissonance items had low corrected item-to-total correlations. Consequently, we deleted the three low itemto-total emotive dissonance items.

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Table 2 shows the results of the factor analysis on the remaining 19 items. The two-factor solution accounted for 62% of the total variance with the emotive dissonance dimension accounting for 39% of the variance and the emotive effort dimension accounting for 23% of the variance. As expected, all items had loadings greater than .50 and loaded well onto their corresponding dimensions. The emotive dissonance dimension was comprised of eleven items with a value of .89, which demonstrated a very good internal consistency among the items. The emotive effort dimension was comprised of eight items with alpha value of .77, which indicated an acceptable level of internal consistency among items. Thus, a HELS was satisfactorily developed. 5. Study 3: confirmatory factor structure The last stage of scale development was to reevaluate the factor structure of the HELS using confirmatory factor analysis (CFA). The scale’s convergent and discriminant validities were also examined. Using the 19-item HELS, data were collected from respondents employed in different hotels located on the east coast of America. Three hundred seventeen full-time employees from twenty hotels (3 fourstar, 8 three-star, and 9 two-star) were asked to fill out the questionnaires. A total of 305 useful questionnaires were analyzed. The profile of the respondents included that they were, in the majority, female (n ¼ 186, 61%), Caucasian (n ¼ 158, 52%), under 40 years old (n ¼ 207, 68%), with 1–4 years’ tenure at current positions (n ¼ 198, 65%). They were full time entry-level employees who worked in food service (n ¼ 110, 36%) and the front desk area (n ¼ 106, 35%). Some of them held managerial positions (n ¼ 43, 14%) in various areas. Most of the respondents had worked in customer-contact positions in various fields for either 1–4 years (n ¼ 109, 34%), or 4–8 years (n ¼ 70, 23%). About 9% of the respondents had worked in customer-contact positions for more than 20 years. Overall, the sample was representative of the hotel employee population with respect to gender, race, and age. CFA with maximum likelihood estimation in LISREL 8.3 was utilized to examine the factor structure of the HELS. We postulated an a priori measurement model linking observed variables with latent factors, and then tested that model for its ability to fit the data using CFA. The fit of the measurement model for the data was based on the w2 statistic, standardized root mean square residual (SRMR), comparative fit index (CFI), goodness-of-fit index (GFI), and critical N (CN). In the event that poorly fitting models emerged from the initial series of analyses, further model re-specification would be needed to improve the model fit based on standardized residuals and modification indices. Large standardized residuals and modification indices identified pairs of indicators in which the covariance was either overpredicted or underpredicted by the model. One of the two items was removed based on redundant content, salience, or content that was

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Table 2 Second stage scale purification factor analysis (n ¼ 97) Attributes

Emotive dissonance

I fake a good mood when interacting with customers.a I fake the emotions I show when dealing with customers.a I put on a mask in order to express the right emotions for my job.a The emotions I show to customers match what I truly feel. I behave in a way that differs from how I really feel.a I put on an act in order to deal with customers in an appropriate way.a My interactions with customers are very robotic.a I display emotions that I am not actually feeling.a I have to cover up my true feelings when dealing with customers.a I actually feel the emotions that I need to show to do my job well. I show the same feelings to customers that I feel inside. I try to change my actual feelings to match those that I must express to customers. When working with customers, I attempt to create certain emotions in myself that present the image my company desires. I think of pleasant things when I am getting ready for work. I try to talk myself out of feeling what I really feel when helping customers. When getting ready for work, I tell myself that I am going to have a good day. I try to actually experience the emotions that I must show when interacting with customers. I work at calling up the feelings I need to show to customers. I have to concentrate more on my behavior when I display an emotion that I don’t actually feel. Cronbach’s a Variance explained (%) Eigenvalue Kaiser–Meyer–Olkin measure of sampling adequacy Bartlett’s test of sphericity (significance level)

Emotive effort

.775 .744 .731 .725 .716 .686 .638 .616 .567 .563 .531 .746 .729 .707 .698 .592 .587 .573 .563 .89 39 4.28 .859 .000

.77 23 2.57

Note: aReverse coded.

ambiguous for determining its placement within the model. The CFA was then rerun to determine whether the modification resulted in an improved fit. This process was continued until a reasonable model was generated. The initial estimation of the 19 item of two-factor structure emotional labor model did not generate a satisfactory result (w2 ¼ 891:37, df ¼ 170, CFI ¼ :69). This indicated a poor fit between the sample data and the model. The data were subsequently subjected to a specification search, as previously described. This search resulted in a final model consisting of 15 items, with 10 items loaded onto the emotive dissonance factor, and five items loaded onto the emotive effort factor. The final model provided an improved and reasonable fit for the data (w2 ¼ 206:49, df ¼ 86, p ¼ :00, SRMR ¼ :048, CFI ¼ :93, GFI ¼ :92, CN ¼ 175:73). Table 3 lists the construct and indicator factor loadings and reliability scores. Both emotive dissonance and emotive effort indicators with loadings ranging from .37 to .81 demonstrated that the HELS indicators were moderately strong measures of emotive dissonance and emotive effort aspects of emotional labor, respectively. In addition, the composite reliability (i.e., variance captured by items versus variance associated with measurement error) for the emotive dissonance and emotive effort factors were .88 and .71, respectively, which exceeded the recommended .70 (Hair et al., 1998), and

therefore, evidenced the good internal consistency of the HELS. 5.1. Construct validity Construct validity focuses on the extent to which data exhibit support of discriminant validity and convergent validity. Discriminant validity deals with the concept that dissimilar constructs should be different (Burns & Bush, 1995). If two constructs are distinct in nature, the instruments used to measure these two constructs should share a minimal correlation. Unlike discriminant validity, convergent validity is the overlap between alternative measures that are intended to tap the same construct but that have different sources of irrelevant, undesired variation (Judd, Smith, & Kidder, 1991). It means that indicators designed to tap the same construct should overlap with each other or share a good deal of variance. To establish discriminant validity, we examined the correlations between the two subscales and other existing scales which measure related constructs, such as emotional exhaustion (seven items, from the Maslach Burnout Inventory, Maslach & Jackson, 1979), and job satisfaction (five items, from the Job Diagnostic Survey, Hackman & Oldham, 1975). Discriminant validity was secured by examining the constructs in sets of two (Anderson & Gerbing, 1988). Constructs were paired to be tested against

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Table 3 CFA results of HELS (n ¼ 305Þ Construct and indicators

Emotive dissonance I put on a mask in order to express the right emotions for my job. The emotions I show to customers match what I truly feel. I have to cover up my true feelings when dealing with customers. I display emotions that I am not actually feeling. I fake the emotions I show when dealing with customers. I show the same feelings to customers that I feel inside. My interactions with customers are very robotic. I put on an act in order to deal with customers in an appropriate way. I behave in a way that differs from how I really feel. I fake a good mood when interacting with customers. Emotive effort I work at calling up the feelings I need to show to customers. I have to concentrate more on my behavior when I display an emotion that I don’t actually feel. I try to talk myself out of feeling what I really feel when helping customers. I try to change my actual feelings to match those that I must express to customers. When working with customers, I attempt to create certain emotions that present the image my company desires.

Completely standardized loadings

Construct/ indicator reliability

Error variance

.63 .53 .62 .59 .75 .37 .49 .44 .79 .81

.88 .39 .29 .38 .35 .56 .13 .24 .60 .63 .66

.12 .61 .71 .62 .65 .44 .87 .76 .40 .37 .34

.62 .47

.71 .38 .22

.29 .62 .78

.64 .73 .37

.41 .54 .14

.59 .46 .86

Fit statistics w2 ¼ 206:49 (df ¼ 86, p ¼ :00) CFI ¼ .93 GFI ¼ .92 Standardized RMR ¼ .048 CN ¼ 175.73

each other. For example, the ‘‘emotive dissonance’’ construct was tested against the ‘‘job satisfaction’’ construct to ensure that these two constructs were not measuring the same concept. Then, the emotive dissonance was tested against another construct, and so forth, until every possible pair of constructs was tested. When testing each pair of constructs, two models were utilized: a constrained model and an unconstrained model. In the constrained model, the correlation between two constructs was set at 1.00 (the fixed model). In the unconstrained model (the free model), the correlation parameter was freely calculated (Anderson & Gerbing, 1988). A w2 difference test was performed for these two models. Discriminant validity was achieved if the w2 values were significantly different for these two models (Anderson & Gerbing, 1988; Gursoy, 2001). Table 4 lists the results of the w2 difference tests for all possible pairs of constructs. In Table 4, the w2 values were generated for both constrained and unconstrained models with respective degrees of freedom. As all w2 differences were significant at po.00, it was concluded that all constructs possessed discriminant validity. Anderson and Gerbing (1988) suggested that evidence of convergent validity for a measurement model is present if all observable indicators load significantly onto their respective latent factors. In this study, all observable

indicators loaded significantly onto their latent variables (Table 3) at the .05 significance level. Therefore, the results of CFA provided evidence of convergent validity for the constructs. 5.2. Model comparison The last part of the analysis was to compare the final model, which was derived from CFA, with the alternative models. The development of the HELS was based on three acting techniques. The results of the second and third studies revealed a two-factor structure of emotional labor with 15 items. To further evidence that the confirmed twofactor structure is superior to other models, we compared the fit of three models including: (1) a two-factor model identified in this study; (2) a three-factor model; and (3) a null model. We used the 15 items retained from the third study in order to build a series nested model to secure the same number of indicators. In the two-factor model, the items measuring surface acting (nine) and genuine acting (two) were allowed to load onto one latent factor (emotive dissonance), and items measuring deep acting were loaded onto one latent factor (emotive effort). In the three-factor model, the surface acting, genuine acting, and deep acting items were only allowed to load onto their respective factors. In both the

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Table 4 Results of discriminant validity tests (N ¼ 305) Corr.

1–2 1–3 1–4 2–3 2–4

Fixed model

.86
.55 .42
.37 .30

Free model

w2

d.f.

w2

df

172.38 129.64 93.57 126.08 70.42

54 27 27 14 14

140.21 45.18 42.90 36.72 31.57

53 26 26 13 13

Dw2

Dd.f.

Sig.

32.17 84.46 50.67 89.36 38.85

1 1 1 1 1

0.00 0.00 0.00 0.00 0.00

Note: 1 ¼ emotive dissonance; 2 ¼ emotive effort; 3 ¼ emotional exhaustion; 4 ¼ job satisfaction.

Table 5 Summary of model comparisons Model

w2

df

SMRM

CFI

GFI

ECVI

Dw2

Ddf

Sig.

Null model Two-factor model Three-factor model

268.50 244.87 199.14

88 87 85

.057 .054 .045

.90 .91 .93

.89 .90 .92

1.10 1.03 .89

— 23.63 14.79

— 1 1

— .00 .00

Note: two-factor model: emotive dissonance (surface acting, genuine acting) & emotive effort (deep acting). Three-factor model: surface acting, genuine acting, and deep acting.

two- and three-factor models, all latent variables were allowed to covary with each other. Finally, in the null model, all paths were constrained to equal zero. This model was used as a based model to determine the improvement of fit achieved by the two- and three-factor model. Table 5 presents the comparison results. The results of model comparison (Table 5) showed that both the two- and three-factor models had a significant improvement in fit over the null model. Further, the threefactor model had a slightly better fit than the two-factor model (w2 difference ¼ 45.73, po.05). Other fit indices also indicated that the three-factor model had a better fit between the model and the data (CFI ¼ .93; GFI ¼ .92, SRMR ¼ .045). Although the three-factor model was superior in fit to the two-factor model, the two-factor model also performed equally well and provided a more parsimonious model for emotional labor (CFI ¼ .91, GFI ¼ .90, SRMR ¼ .054).

property, we conducted a second study with data collected from 97 hotel employees. EFA was employed to examine the dimensionality of the HELS. The results led to a deletion of three items, and the unidimensionality of each subscale was confirmed for the remaining nineteen items. Finally, we conducted a third study to confirm the hypothesized factor structure using CFA on data collected from 305 hotel employees. Four items were removed to ensure a better fit between the data and the model. The number of the HELS items was reduced to 15, with ten items measuring emotive dissonance and five items measuring emotive effort. These items were then loaded onto their designated latent variables. In these three studies, the internal consistency coefficients for the two subscales, ranging from .69 to .88, demonstrated acceptable scale reliabilities. Scale validity was secured through the examination of face validity, convergent validity, and discriminant validity.

6. Discussion

6.2. Research application

6.1. Summary

In keeping with the tremendous expansion of the service economy, researchers have begun to devote increasing effort to the examination of the construct of emotional labor, a unique job characteristic of service employees. The HELS was designed to measure the emotional labor that hospitality employees present for their customers. Although the scale has been tested on multiple samples and achieved good reliability and validity, it requires further replication in different contexts to ensure consistency. When applying the HELS, special consideration has to be paid to the number of items. We recommend that future researchers use the 19-item rather than the 15-item

The overall purpose of this study was to examine the psychometric properties of a newly developed scale, the HELS, designed to assess the emotional labor that hospitality employees perform for their customers. The development and validity process of the HELS was presented in detail. Three studies were conducted to establish and confirm scale unidimensionality, reliability, and validity. The first study was conducted with the purpose of item purification. The results of the first study derived a 22-item scale. To further examine the scale

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instrument. In the scale development process, we first used EFA to identify the underlying factor structure on one sample, and then followed with CFA to confirm such factor structure on another sample. The results of these two analyses were somewhat different in terms of the item numbers, whereas the factor structure remained the same. One of the explanations for this item number difference was the theoretical and mechanical bases underlying the analytic methods for evaluating the factor structure. EFA is a data-driven approach for identifying (rather than confirming) a model that explains the covariances among items, whereas CFA is a theoretically driven approach for testing how well a model explains the covariances among items. The fundamental mechanical difference between analytic methods may contribute to the item number differences. To achieve a better fit, four items were removed from the third study as the result of CFA procedure. However, this result should be interpreted with caution since the HELS is a newly developed scale and still needs to be tested to ensure the scales’ stability over times and across individuals (Byrne, 1998). It is recommended that future researchers use the 19-item rather than the 15-item scale when applying the HELS. Based on the three acting techniques, the employeefocused approach of emotional labor model was confirmed in the three studies. The three studies revealed a two-factor structure confirming Kruml and Geddes’s findings (2000). However, the results of model comparison showed that the three-factor model had a better fit than the two-factor model. The difference between the two models is the loading of surface acting and genuine acting. Items measuring both surface acting and genuine acting loaded onto the same latent factor (emotive dissonance) in the two-factor model. In the three-factor model, surface acting items and genuine acting items loaded onto their designated latent factors in the three-factor model. Although the fit indices of these two models achieved acceptable levels, the three-factor model had a better model fit than the twofactor model. More studies need to be conducted to further examine the replication and the stability of the factor structure of the HESL. Future research should examine how training affects employees’ emotional labor presentation. In the third study, 305 hotel employees from various star-rated hotels participated in this study. As hotels’ star-ratings vary, the organizational demands for emotional labor as well as training implementation also differ. A five-star hotel may strongly emphasize employees’ emotional labor presentation, and therefore implement various training modules or display rules. Conversely, a one-star hotel may be less concerned about the emotional labor that its employees perform. Examining how training changes the way an employee performs emotional labor using different acting techniques may shed some light on how emotional labor affects organization performance as well as employee’s well-being.

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The development of the HELS was based on the three acting techniques to capture the emotion management process of performing emotional labor. This study found that service acting contributes to the emotion management process of emotional labor. The availability of this scale can help hospitality researchers further explore the skills, effort, and responsibilities associated with such labor and how it affects employees’ well-being. The impact of culture on behavior was postulated by Hofstede in 1998. An important implication of the social nature of customer–employee interaction is that culture plays a predominant role in influencing how emotional labor is presented by employees to their customers. The concept of appropriate emotional labor in one culture is not always transferable to another. For example, some service acting techniques, such as surface acting, may not exist in certain cultures, such as some service-oriented Asian cultures. Since the HELS was developed and tested in the United States, it is important to examine whether respondents conceptualize the construct in identical ways when applying this instrument to measure emotional labor in different countries with distinctly different cultural backgrounds. It is recommended that future researchers employ a back-translation approach to secure the language equivalent when applying HELS to a non-western culture (Becker & Murrmann, 1999). In addition, future researchers need to examine the factor invariance to ensure that the relationships between the items and the construct remain the same across cultures. 6.3. Management applications of the HELS In a highly emotion-charged environment, employees’ emotional expression is significant in determining customers’ perception of service quality. Therefore, it is important for employers or managers to monitor the emotional labor performed by their employees. The hospitality emotional labor scale presented here is a concise multiple-item scale, exhibiting good reliability and validity, that hospitality firms can use to better understand the emotional effort that their employees perform and their customers perceive. The HELS is most valuable when it is used periodically to track employees’ emotional labor performance, and when it is used in conjunction with an organization’s performance assessment practices. A hotel, for example, could learn a great deal about its employees’ performance by measuring how they enact emotional labor and then determining what needs to be done to improve it. In addition, hospitality practitioners can use the HELS as a selection tool to identify the ‘‘right’’ employees with strong potential to perform excellent emotional labor. The ability to identify a job candidate’s tendency to use a particular type of acting skill to perform emotional labor can help the company to select employees who are genuinely welling to engage in emotive effort. From a customer’s perspective, the HELS can provide additional information when it is used in conjunction with

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other customer satisfaction measures. This scale can assess how customers perceive the quality of interaction they have with servers, as well as the emotional presentation that the servers perform. Soliciting such information can help the hospitality organization to better identify the link between emotional labor and customer satisfaction in order to pinpoint the importance of employees’ emotional labor performance. 6.4. Conclusion To a greater or lesser extent, every job requires a certain degree of emotional labor. In fact, it would be difficult to identify any job that does not require the exercise of emotional labor. And, for hospitality firms, the display of genuine feelings of concern for the customer is viewed as an essential ingredient in service quality. The HELS has a variety of potential applications. It can be used by a wide range of hospitality organizations in assessing employees’ emotional labor level as well as customers’ perceptions of the desired or expected emotional effort. It can also help in pinpointing areas requiring more managerial attention and action to improve the emotional labor hospitality employees perform. Lastly, it is our hope that the availability of this instrument will stimulate much needed empirical hospitality emotional labor research. Appendix A. The HELS questions A.1. Section I: emotive dissonance 1. I fake a good mood when interacting with customers. 2. I fake the emotions I show when dealing with customers. 3. I put on a mask in order to express the right emotions for my job. 4. The emotions I show to customers match what I truly feel. 5. I behave in a way that differs from how I really feel. 6. I put on an act in order to deal with customers in an appropriate way. 7. My interactions with customers are very robotic. 8. I display emotions that I am not actually feeling. 9. I have to cover up my true feelings when dealing with customers. 10. I actually feel the emotions that I need to show to do my job well. 11. I show the same feelings to customers that I feel inside. A.2. Section II: emotive effort 1. I try to change my actual feelings to match those that I must express to customers. 2. When working with customers, I attempt to create certain emotions in myself that present the image my company desires.

3. I think of pleasant things when I am getting ready for work. 4. I try to talk myself out of feeling what I really feel when helping customers. 5. When getting ready for work, I tell myself that I am going to have a good day. 6. I try to actually experience the emotions that I must show when interacting with customers. 7. I work at calling up the feelings I need to show to customers. 8. I have to concentrate more on my behavior when I display an emotion that I don’t actually feel.

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