Keywords

Emotional labor, Emotional Exhaustion, Surface Acting, Deep Acting, Pride in Work, Anxiety.

Introduction

Service sector has witnessed outstanding performance in last 5 years since 2013-14 in the growth of GDB of Pakistan. It has shown consistent growth to the GDB of Pakistani economy i.e. “4.37% in 2014–15, 4.95% in 2015–16, 6.46% in 2016–17 and 6.43% in 2017–18”. The total
share of service sector is witnessed to 60.2% in Pakistani economy (Nadeem et al., 2019). During the year 2016-17,

“Hospitality industry contains more than 10,000 hotels comprising 50,000 rooms in Pakistan” (Nadeem et al., 2019).

The current contribution in GDP is 3% by the hotel industry but it is expected to increase as law and order situation in the country has improved. The occupancy rate has been reached to 75% with the beginning of China Pak Economic Corridor (CPEC) project (Nadeem et al., 2019). Despite facing multiple challenges, hotel industry has displayed positive signals and share in the growth of economy of Pakistan.

Hospitality industry helps to earn foreign direct investments. As per United Nations World Tourism Organization (UNWTO) report 2018, there is an average one million tourists in a year in Pakistan whereas the top ten tourist’s countries average is at 50 million tourists in a year. Pakistan falls in the lowest 10% of the worldwide hospitality sector. It was affected badly especially after 9/11 war on terror by US (Ahmed et al., 2014). With such situation, Pakistan clearly shows lower levels of tourism attraction and makes it significant to study the hospitality sector on various dimensions and flourish it. It is necessary to have committed and trained employees in hotels. MNCs are unique and complex because of their interactions and uncertainty, group dynamics, cultural diversity and work related stress which leads to conflict and inefficiency of the organization (Farndale et al., 2015; Trefry, 2006). Same is with the multinational hotel chains like four star and five star international hotels. In such a diverse working environment, communication becomes more time taking and complex along with emotional labor. It becomes difficult to reach on a common understanding and different expectations may lead to clash and negative assessment of employees (Trefry, 2001). It leads towards emotional exhaustion (Alola et al., 2019). Emotional exhaustion is usually found in highly stress circumstances and significantly affects the work quality (Zopiatis & Constanti, 2010). It has strong inclination towards stressing the individual’s emotional resources and finally the physical resources as well (Maslach et al., 2001). Emotional labor is an essential element of employees working for hospitality industry (Hameed, 2016). In Pakistan, emotional labor research among frontline employees of hospitality sector is rare (Hameed & Bashir, 2017). So the current study will address on theoretical and empirical examination of emotional labor on emotional exhaustion.

The Conservation of Resources theory (COR) entails emotional labor as emotional resource affecting on emotional exhaustion as a psychological job strain (Hobfoll, 2001).

Hobfoll’s (1989) Conservation of Resources theory (COR) posits that

“People have a basic motivation to acquire, retain, protect and enhance their psychological resources. Individuals experience stress when they are threatened with resource loss, actually lose resources, or fail to gain resources after resource investment. Individuals confronted with stress attempt to minimize the net loss of their resources by investing in other resources”.

From the perspective of the Conservation of resources theory (Hobfoll, 1989),

“Employees engage in emotional labor according to their job requirements, meaning that they must continuously expend mental energy in order to perform the job”.

Therefore, employees may view emotional labor as a source of job stress (Chen et al., 2019). Pride in work or sense of pride is the feeling of deep pleasure or satisfaction which comes from one’s achievements. Taking pride in one’s work is a massively important role for any professional (Jin & Guy, 2009). It is the positive resource of the employees. Furthermore, both variables have been found to exert the impact on motivational outcomes such as commitment (Aktaş, 2014; Chaudhry & Shah, 2011; Huey & Zaman, 2009).

Asif (2012) in his study proved that work-related requirements increases stress, anxiety and emotional exhaustion among employees. He further argued that unpleasant interaction with client cause frustration, anger and distress among employees (Asif, 2012). Prevailing economic environment in Pakistan is characterized by uncertain economic future, high unemployment rate, and mobility of industrial infrastructure to other countries. It is necessary to focus on employee retention. Front line employees of service-oriented organizations especially the hospitality sector is considered as the contact point between clients and organizations (Chen et al., 2019). They are further considered as source of competitive advantage for business (Chen et al., 2019). The hospitality industry is an important and dynamic sector of service industry throughout the world. Since, the client retention is the source of profitability, hotel managers deeply focus on client satisfaction and creating and retaining a pool of potential and loyal customers (Karatepe, 2011), Likewise, they also ensure that attitude and behavior of frontline employees are also consistent with organizations; expectations while dealing the clients (Hartline & Ferrell, 1996). Definitely, the front line employees are the most important link in the service process (Karatepe, 2011). Since the frontline employees are usually given task to completely satisfy the clients while directly communicating with them. Therefore, their job is more likely to cause emotional labor in order to conform the certain explicit display rules (Li et al., 2017).

The emotional labor presence in hospitality industry in Pakistan is still unacknowledged and unnoticed as it is embedded in work (Asif, 2012). Organizations must address this phenomenon and formulate multipronged strategies to effectively deal its management. As a result, the current study investigates the emotional labor more specifically in hotel sector. Goussinsky (2015) and Karatepe & Nkendong (2014) and Kensbock et al. (2016) state that the specific dimensions of surface acting and deep acting are therefore underexplored, require empirical testing as this is new concept and require special attention of the researchers. Another important effort of the researcher’s will be to explore the dimension of pride in work and its significance in hospitality industry. This study will also help the employees to deal with deep acting strategy and get its advantages which are for both the customers and organizations. So, the current study is intended to fill this gap by investigating emotional labor among employees of four star and five star hotels in Pakistan.

Research Objectives and Significance

The study has following objectives.

1. To investigate the relationship between emotional labor strategies and emotional exhaustion.
2. To investigate the mediating role of anxiety between emotional labor strategies and emotional exhaustion.
3. To investigate the moderating role of pride in work between emotional labor strategies and emotional exhaustion.

The study will have a vital practical support. The study will provide practical implications for appropriate emotional labor acting strategies. It will facilitate the hotel managers to investigate and see the impact how their frontline employees conform to organizational display rules. The way of acting engages employees directly into emotional exhaustion. The study will suggest mangers which acting strategy must be encouraged and which strategy must be discouraged for employees. It is evident from last 5 year economic indicator examination that servicer sector has become the vital contributor of Pakistani economy with tremendous growth (Nadeem et al., 2019). It will be significant to study the role of emotional labor in reducing the emotional exhaustion among service related employees. This study will contribute to the present literature on organizational psychology.

Literature Review

Emotions are transmissible (Huang & Dai, 2010). Hence, employees only try to carry those emotions which can be transmissible to their customers. The employees need to deal clients with a smile even in a worst situation so that the customers feel better and may come out of the situation (Walsh, 2019). For this, employees use either surface acting or deep acting. The characteristic of emotional labor states that emotions are always followed by certain rules which are being expressed under any situation (Gruber et al., 2011; Tamer, 2015). As per study of Ekman (1973) we always follow some rules when we interact with others which are called as display rules. Display rules are those certain emotions which are considered suitable on specific occasions. Kamp & Dybbroe (2016) state that employees also need to align their emotions with those display rules in performing their duties which results in emotional labor. It is likewise in organizations that every culture has certain written and unwritten display rules. Organizations also have some written and unwritten display rules (Horo, 2014). The written display rules are self-explanatory and simple to follow. In contrast, there are certain unwritten display rules imbedded in culture strongly which are not only compulsory to follow but they must be learned by everyone in the organizations. Employees usually indulge in emotional labor while performing and following both types of display rules.

Hülsheger et al. (2013) and Morris & Feldman (1997) and Simillidou (2016) state that the employees feel emotional exhaustion while dealing with negative situations and engaging in emotional labor in service organizations. Emotional exhaustion is identified as consequence of increase stress level but some researchers have considered emotional dissonance, its main attribute. Emotional exhaustion can be defined as

“The psychological discomfort that is being felt by a person when they take part in activities or get involved in situations that actually attribute this feeling (Dijk & Brown, 2006)”.

Emotional labor refers to managing emotions in order to display the set rules (Hochschild, 1983). The emotional labor leads to burnout in service industry which is a syndrome of emotional exhaustion (Brotheridge & Grandey, 2002; Grandey, 2003; Maslach et al., 2001). Surface acting is defined as

“Changing expression without changing the inner emotional state” (Cheung et al., 2011).

Emotional exhaustion produces when emotions and feelings become exhausted in result of fear of work or lack of interest. There is not a significant uniform finding in relationship between emotional exhaustion and emotional labor strategy. Emotional exhaustion is caused by surface acting approach (Totterdell & Holman, 2003). Therefore, emotional exhaustion and emotional labor are believed to be positively correlated. As per Abraham (1999) study of frontline employees, the employees who adopt surface acting method yield low service quality.

Deep acting and surface acting help the employees to display the set emotions but both have different spirit in nature. Deep acting can be defined as a

“Strategy of emotional labor refers to changing inner emotions according to the desired emotions” (Miller et al., 2007).

The employees experiencing surface acting may have high level of inner stress as compared to the employees who adopt deep acting method. Such employees change their inner feelings as well so they don’t have such tension. So deep acting may not be as such related to burnout and emotional exhaustion though it may relate to personal accomplishment or depersonalization (Brotheridge & Grandey, 2002; Hochschild, 1983).

Conservation of Resource Theory (COR) stresses that emotional labor is an exerted activity which results in emotional exhaustion. When employees frequently remain busy in managing their emotions and engage themselves to consume their personal resources at large like physical and mental resources, they definitely undergo with resources loss (Hameed & Bashir, 2017). Simply, when job demands compel the employees to regulate their inner emotions and feelings while hiding their true emotions, they are emotionally drained (Brotheridge & Grandey, 2002). Within premises of COR theory, surface acting and deep acting have different outcomes regarding emotional exhaustion (Grandey, 2003).

Hwa (2012) argues that it is not only the emotional labor which results in emotional exhaustion. Rather it depends upon the ways in which emotional labor is performed either by deep acting or surface acting method. The emotional exhaustion and surface acting have relationship in difficult situations. It is stated that when employees deal in negative situation they automatically face the emotional exhaustion (Grandey, 2003). It is proved through researches on emotional labor in hospitality sector that employees will feel more emotional exhaustion if they will be more engaged in surface acting (Karatepe, 2011). Therefore surface acting is positively related to emotional exhaustion and deep acting is negatively associated with emotional exhaustion (Hwa, 2012; Lee & Chelladurai, 2016). Goussinsky (2011) and Hwa (2012) and Wang & Groth (2014) stated that engaging in surface acting method brings major disadvantage on the employees’ well-being. The researchers proposed that if these employees start using deep acting method, it would be favorable for them to avoid emotional exhaustion and other undesirable penalties of surface acting. Though, it is not empirically verified yet and it does not guide employees how to engage in deep acting (Lee & Chelladurai, 2016). The current study will fill this gap. Therefore, we propose that both facets of emotional labor have relationship with emotional exhaustion. Hence we built hypotheses as:

H1: Surface acting is positively correlated with emotional exhaustion. H2: Deep acting is negatively correlated with emotional exhaustion.

Literature identifies that anxiety and depression are mostly studied in the US organizations (Elovainio et al., 2001; Spell & Arnold, 2007; Suls & Bunde, 2005). As Pakistan is a developing country and unstable economy, it will be a worthy to study the employee mental health via anxiety in hospitality industry where employees have long working hours than normal. Recent economic slowdown in developing countries has resulted in increased anxiety, stress, less sleep and helplessness among employees to achieve organizational goals (Rai, 2015). Mostly organizations have studied anxiety and depression with job insecurity (Rai, 2015). The current study will explore the anxiety as a mediating variable to find the relationship between Emotional labor and emotional exhaustion in context of Pakistan and hospitality industry. This dimension will expand the scope of the research globally. The current study will only take anxiety as in indicator of employee mental health because of its common representation for employee mental health (Spell & Arnold, 2007). In the perspective of COR theory, one has a limited number of resources and the loss of such resources affects the job tasks and its sub-tasks (Hobfoll, 2001). If these are the valid assumptions, then surface acting will consume more energy and resources in order to modify the true feelings than deep acting which expresses the true emotions and will require fewer resources (Hobfoll, 2001). Empirical evidence supports this theoretical proposition (Brotheridge & Grandey, 2002; Kim & Han, 2009).

“Employees experience stress when they face threats that may come from a risk of resource loss, actual resource loss, or the insufficient return of supplementary resources on investments of resources” (Hobfoll, 2001).

The current study will propose that emotional labor affects the employees’ anxiety level which will impact the emotional exhaustion. Employees who are facing emotional labor may feel an impact from mental health like anxiety (Rai, 2015). Therefore, it leads towards such hypotheses that any relationship between emotional labor and emotional exhaustion may be mediated by anxiety.

H3: Anxiety mediates the relationship between surface acting and emotional exhaustion. H4: Anxiety mediates the relationship between deep acting and emotional exhaustion.

Pride is an important element in social behavior context (Tracy & Robins, 2007). Previous researches discussed two types of pride in organizational context; one is personal pride and other is collective pride. According to Lea and Webley (1997), personal pride is an intrinsic motivation related to self-accomplishments. Collective pride is desire to connect organizational group (Bouckaert, 2001). Collective pride is an organizational context (Arnett et al., 2002).

Pride is a positive emotion which expresses the personal satisfaction in relevance to a certain event, either justified or not. It plays a vital role in job satisfaction (Tracy & Robins, 2007). Authentic pride is to get pride on one’s own activities and attainments (Tracy & Robins, 2007). Hubristic pride is pride; one has other than personal accomplishment and efforts (Williams & DeSteno, 2008). Literature recommends that one’s sense of pride in work increases job commitment.

Many researchers mentioned pride in their studies while discussing the findings of their researches on paradigms like narcissism, self-esteem, shame and guilt (Else-Quest et al., 2012), but only a few have examined pride individually and a very few have worked on pride at workplace. There is still an extensive work to be done in this area to fully understand pride’s emotional experience and potential benefits in organizations. The lack of attention to the pride with respect to an individual’s own achievements gives the researcher a motivation to study.

Currently, the lack of attention to pride is specifically making it, as an exciting concept. It has been described as an individual’s emotional experience and it has been mentioned in a lot of researches (Roethlisberger & Dickson, 2003). The first presence of pride was in Hawthorne studies, where a large numbers of employees show their participation, when an employee described that morale goes to peak when the operator shows pride in their work. The employee reported that

“Peak in morale was apparent through other operators showing pride in their work, trying to outperform their previous best records, and helping each other to create higher standards” (Roethlisberger & Dickson, 2003).

Pride in work or sense of pride is the feeling of deep pleasure or satisfaction which comes from one’s achievements. Taking pride in one’s work is a massively important role for any professional (Jin & Guy, 2009). It is the positive resource of the employees. Emotional labor refers to managing emotions in order to display the set rules (Hochschild, 1983). COR theory suggests that individuals’ resources act as motivational vectors which are hierarchically ordered in values but universal (Halbesleben et al., 2014; Morelli & Cunningham, 2012).

In the perspective of COR, resources gain are noticeable in context of resources loss (Hobfoll, 1989, 2001). Similarly, Jin & Guy (2009) also hold same opinion that high level of pride in work can develop positive attitude like commitment, devotion, creativity, collaboration, hard work etc. Under COR premises, all these qualities/characteristics are positive resources which are essential for employees to happily stay somewhere (Halbesleben et al., 2014). On the basis of above arguments, it seems that pride in work supports adoption of deep acting strategy instead of surface acting strategy with true emotions (Kensbock et al., 2016). If employees will have high level of pride in work, they can moderate the relationship between emotional labor and emotional exhaustion.

Frontline service employees need to self-monitor them vigilantly while handling challenging and difficult customers. All those workers who score high on pride in work try their best to deliver what is demanded from them and in doing so they experience deep acting which helps them perform better on their jobs at the same time reduces emotional exhaustion associated with performing emotional labor (Grandey et al., 2018). So, it may hypothesize that:

H5: Pride in work may moderate positive relationship between surface acting and emotional exhaustion such that this relationship may weaken when pride in work is high and strengthened when pride in work is low.

H6: Pride in work may moderate negative relationship between deep acting and emotional exhaustion such that this relationship may further weakened when pride in work is high and strengthened when pride in work is low.

Based on literature review, we proposed following model in Figure 1.

Methodology

The nature of the study was deductive and explanatory in nature. Research was structured and based on quantitative approach. It was non- contrived and time lag study. Researcher distributed self-administered questionnaire on two different times. The 3 weeks gap was followed. Lam & Chen (2012) also used time lag study in order to measure turnover intentions in hotel employees in 3 points. Hameed & Bashir (2017) also used time lag to study emotional labor. The present study tries to examine the causal relationship between emotional labor strategies, affective commitment and anxiety. One survey was regarding demographics and emotional labor. The second survey addressed the affective commitment and anxiety. One round was completed in first two weeks of July 2019. Second round was completed in first two weeks of September 2019. Employee code was used as recognition. Primary source were employees of hotels. The unit of analysis was the individual. Data collection tool was an already developed questionnaire which was close ended and has 5 point Likert scale. 520 employees from hotels were chosen as sample. Multistage sampling allowed the researcher to choose a suitable sample from a large population. The actual sample size was selected from only 32 hotels which were listed as four star and five star hotels on www.pha.org.pk. Ten responses for one item (10:1) are appropriate as per Tanaka’s (1987) item response theory. A total of 520 questionnaires were distributed to the hotels as per item response theory. However the researcher received 464 responses. The latest version of SPSS 23and AMOS 23 was used to statistically analyze the gathered data. Descriptive statistics was used to analyze the demographics.

Measures

The already developed questionnaire was used on 5 point likert scale from 1 to 5. Emotional labor was measured by emotional labor scale devised by (Grandey, 2003; Kruml & Geddes, 2003; Diefendorff et al., 2005). The instrument has 12 items. The scale has reliability index of 0.81. Emotional Exhaustion was measured by scale adopted from The Maslach Burnout Inventory by Maslach & Jackson (1981). The instrument has 9 items and reliability index of 0.87. Anxiety was measured by scale devised by adopted (Caplan et al., 1980). The instrument has 4 items and reliability index of 0.81. Pride in work was measured by scale devised by (Guy et al., 2008). The instrument has 7 and reliability index of 0.87.

Data Analysis and Discussion

Table 1 show that male respondents are more than female respondents by 56.4% that is a significant difference. The reason is obvious that hotel sector is more male oriented and females are working less in number so response is appropriate according to their population. Age group of respondents shows that there are between twenty to thirty years are 59.9%. 30.2 percent respondents fall in age category from thirty one years to forty years. 9.9 % are those respondents who are above forty in age group. Therefore, it can say that young employees are there and insignificant numbers of employees who are above forty in age. Data shows that number of married respondents is more than unmarried by 43.1%. Therefore, there is significant difference between the no. of unmarried and married hotel employees in Pakistan. If we discuss about the education level, majority of respondents belong to the third category that is graduation class that represents the forty four percent (44%, n = 204 of total share).

Table 1: Demographics
Demographic characteristics	Frequency	Percent	Cumulative percent
Gender
Female	101	21.8	21.8
Male	363	78.2	100.0
Age
20?30	278	59.9	59.9
31?40	140	30.2	90.1
>41	46	9.9	100.0
Marital status
Married	264	56.9	56.9
Single	200	43.1	100.0
Education Level
Matric	63	13.6	13.6
Intermediate	98	21.1	34.7
Graduate	204	44.0	78.7
Master	96	20.7	99.4
M.Phill	3	0.60	100.0

Descriptive Statistics

The descriptive statistics are shown in Table 2. The dependent variables, emotional exhaustion (EE) possesses the lowest and highest values 1.07 and 5.07 respectively and for the same variable, the average value and its standard deviation i.e., dispersion from mean is 3.03 and 0.822 respectively. An independent variable, surface acting (SA) possesses the lowest and highest values 0.88 and 4.57 respectively and for the same variable, the average value and its standard deviation i.e., dispersion from mean is 2.91 and 0.779 respectively. Second independent variable, deep acting (DA) possesses the lowest and highest values 0.93 and 4.19 respectively and for the same variable, the average value and its standard deviation i.e., dispersion from mean is 2.86 and .643 respectively. A mediating variable, anxiety (ANX) possesses the lowest and highest values 0.98 and 4.96 respectively and for the same variable, the average value and its standard deviation i.e., dispersion from mean is 2.78 and 1.000 respectively. A moderating variable, pride in work (PIW) possesses the lowest and highest values 0.87 and 4.32 respectively and for the same variable, the average value and its standard deviation i.e., dispersion from mean is 3.13 and 0.733 respectively.

Table 2: Mean and Standard Deviation of Variables (N = 464)
Constructs	Minimum	Maximum	Mean	Std. Deviation
Surface Acting (SA)	0.88	4.57	2.91	0.779
Deep Acting (DA)	0.93	4.19	2.86	0.643
Emotional Exhaustion (EE)	1.07	5.07	3.03	0.822
Anxiety (ANX)	0.98	4.96	2.78	1.000
Pride in Work (PIW)	0.87	4.32	3.13	0.733

KMO and Bartlett’s test of Sphericity

Factor analysis has been applied on the collected data to examine the either data is appropriate for further necessary statistical analysis (Malhotra, 2010). Before going ahead of factor analysis, it has recommended to conduct the KMO and Bartlett’s measure of Sampling Adequacy and Sphericity. These tests explain the suitability of data either it will support for factor analysis. If all statistical values of both tests fall in the recommended range then data is ready for factor analysis (Malhotra, 2010).

Statistically, the thresholds or recommended values belong to the range 0.50-1.0 (˃ 0.90
= excellent; 0.80=admirable; 0.70=moderate; 0.50=not good and < 0.50=undesirable) (Dziuban & Shirkey, 1974). For the current study, Table 3 reflects the values for KMO and Bartlett’s tests are in acceptable range that KMO value is 0.914 and significance level of Bartlett’s test that require < 0.05 and in this case, its p value (p<0.001) that also satisfied the condition and of course data can proceed for further analysis.

Table 3: Kmo and Bartlett's Test
Test Name Statistical Value
Kaiser-Meyer-Olkin Measure of Sampling Adequacy		0.914
Bartlett's Test of	Approx. Chi-Square	14819.424
Sphericity	df	1326
	Sig.	0.000

Correlation Analysis

Correlation analysis was done to investigate the relationships between variables and the nature. Table 4 depicts the correlation analysis

Table 4: Magnitude and Direction of Correlation among Study Variables (N=464)
	1	2	3	4	5
SA	1
DA	0.865**	1
EE	0.466**	-0.473**	1
ANX	0.202**	0.185**	0.644**	1
PIW	0.356**	0.568**	0.192*	0.033	1

Surface acting, anxiety and pride in work have significant positive relationship with the dependent variables which is emotional exhaustion, and the values of correlation coefficient are r =0.466, 0.644, & 0.192, p<0.01. Deep acting has weak negative relationship with emotional exhaustion and the values of correlation coefficient is r=-0.473, p<0.01. Surface acting has positive weak relationship with emotional exhaustion and the value of correlation coefficient is r = 0.466, p<0.01. Hence it proved the first two hypotheses (H1 and H2).

AMOS 23 was used to apply structural equation modeling (SEM). SEM provides the choice of bootstrapping. Mediation has tested bootstrapping technique. Testa (2001) has indicated that SE modeling is a multivariate statistical procedural approach to test the hypothesized models.

Confirmatory Factor Analysis

Confirmatory factor analysis (CFA) can be described as a specific case of structural equation modeling that explains covariance in structure (McDonald, 1978) or describes the linearity of relationships in a model (Carmines & Zeller, 1979). Confirmatory factor analysis reports about the collected data either it is fit the theoretical measurement model that is grounded from the past researches (Kline, 2015).

Discussion Related Goodness of Fit Indexes

Some explicit measures exist that researchers have used to calculate for the assessment of goodness of fit hat are called fit indices. It has recommended in literature some model fit indices are relatively permanent whereas others are flexible. Usually, under consideration model is said to be adequate if value of X2/d.f. (chi-square) is less than three (<3) (Kline, 1998; Ullman, 2001) and sometimes this measure is permissible at less than 5 (<5) (Hair et al., 2010). Another index is “Root Mean Square Error of Approximation” (RMSEA) and its value is acceptable that is less than 0.08 (<0.08) (Browne & Cudeck, 1993; Hu & Bentler, 1998), the value of this measure is considered good if less than 0.05 (<0.05) (Steiger, 1990) and sometimes researchers recommend its value less than 0.10 (<0.10) (Hair et al., 2010) i.e., <0.05 considered as good, 0.05-0.10 considered as moderate and ˃0.10 considered as bad. The value of two indices: NFI-Normed Fit Index and GFI-Goodness of Fit Index should greater than 0.09 (>0.9) (Byrne, 1994). Similarly, the value of NNFI-Non-Normed Fit Index also be greater than 0.09 (>0.9). Hair et al. (2010) recommend the acceptable value of CFI-Comparative Fit Index are greater than 0.95 (>0.95) great; greater than 0.90 (>0.90) traditional; greater than 0.80 (>0.80) sometimes permissible. In literature, consensus is there on CFI value, its value is acceptable 0.70 and 0.85 if model already generated and in progress respectively (Bollen, 1989). There is no need to compute the value of CFI if RMSEA have value less than 0.158 of null model or in other case, there will be very small value of CFI (Kenny, 2015). Hair et al. (2010) suggest the values of SMRM-Standardized Root Mean Residual, PCLOSE and AGFI-Adjusted Goodness of Fit Index are <0.09, >0.05 and >0.80 respectively.

Measurement Model

This model provides the facility to the researcher to measure the association among the latent constructs and latent constructs further measure through the observed variables. Graphically, the study measurement model is presenting in Figure 2. Table 5 is showing all the goodness of fit values for measurement model. It is obvious in Table 5 that all the required scores are within the range of recommended values. Henceforth, all values are in range so the model is good fit. Table 6 represents the standardized regression weights which show all values in significant position.

Table 5: Model Fit Summary for Measurement Model
Fit Indices	Recommended Value	Result
X2/d.f.	< 3	2.441
GFI (goodness of fit index)	> 0.9	0.827
AGFI (adjusted goodness of fit index)	> 0.80	0.795
RMSEA (root mean square error of approximation)	< 0.08	0.056
RMR (root mean square residual)	< 0.08	0.085
NFI (normed fit index)	> 0.90	0.831
CFI (comparative fit index)	> 0.80	0.892
PCLOSE> 0.050.278	> 0.05	0.001

Table 6: Standardized Regression Weights for Constructs
Variables	Estimate	p-value
SA5 <--- SA	0.727	***
SA4 <--- SA	0.773	***
SA3 <--- SA	0.822	***
SA2<---SA	0.735	***
SA1 <--- SA	0.62	***
DA7 <--- DA	0.603	***
DA6 <--- DA	0.539	***
DA5 <--- DA	0.728	***
DA4 <--- DA	0.757	***
DA3 <--- DA	0.76	***
DA2 <--- DA	0.66	***
DA1 <--- DA	0.73	***
EE9 <--- EE	0.717	***
EE8 <--- EE	0.775	***
EE7 <--- EE	0.574	***
EE6 <--- EE	0.77	***
EE5 <--- EE	0.725	***
EE4 <--- EE	0.664	***
EE3 <--- EE	0.639	***
EE2 <--- EE	0.707	***
EE1 <--- EE	0.687	***
PIW7 <--- PIW	0.722	***
PIW6 <--- PIW	0.727	***
PIW5 <--- PIW	0.742	***
PIW4 <--- PIW	0.762	***
PIW3 <--- PIW	0.829	***
PIW2 <--- PIW	0.844	***
ANX4 <--- ANX	0.861	***
ANX2 <--- ANX	0.752	***
ANX1 <?. ANX	0.699	***
PIW1 <--- PIW	0.784	***

Structural Model (SM)

Another model was developed after testing the measurement model that was structural equation model. Structural equation model has sketched by using AMOS v23. SEM is a multivariate statistical technique that uses for the evaluation of structural relationships. Usually SEM consists of measurement model (i.e., MM) and structural regression model (i.e., SRM). In the present study, SEM presents the structural relationships among surface acting, deep acting, affective commitment and anxiety. Graphically, the study structural equation model is presented in Figure 3. Table 7 is showing all the goodness of fit values for SE model. It is obvious in Table 7 that all the required scores are within the range of recommended values. Therefore all values are significant and model is good fit. Table 8 shows all the standardized regression weights of structural equation model which are significant.

Table 7: Model Fit Summary for Structural Equation Model
Fit indices	Recommended Value	Result
X2/d.f.	< 5	3.399
GFI (Goodness of Fit Index)	> 0.9	0.998
AGFI (adjusted Goodness of Fit Index)	> 0.80	0.957
RMSEA (Root Mean Square Error of Approximation)	< 0.08	0.062
RMR (Root Mean Square Residual)	< 0.08	0.001
NFI (Normed Fit Index)	> 0.90	0.998
CFI (Comparative Fit Index)	> 0.95	0.999
PCLOSE	> 0.05	0.278

Table 8: Standardized Regression Weights for Structural Equation Model
Path of Variables	Estimate	S.E.	C.R.	p-value
ANX<--- SA	0.202	0.058	4.441	***
EE <--- ANX	0.573	0.027	17.656	***
EE <--- SA	0.350	0.034	10.788	***
ANX <--- DA	0.185	0.071	4.048	***
EE <--- DA	-0.366	0.041	11.464	***
EE <--- ANX	0.576	0.026	18.043	***

Mediation Analysis

Mediation analysis was applied in structural equation modeling via bootstrapping. Bootstrapping is vibrant method for mediation analysis as it provides the confirmation for mediation effect in a true sense (Byrne, 2016; Cheung & Lau, 2008). Mediation in SEM through bootstrapping allowed researchers to obtain the direct (Direct Beta without Mediation, Direct Beta with Mediation), indirect (Indirect Beta) and total effects of proposed model that helped to decide the mediation type either it is full, partial or no mediation. Practically, it can be done through Bollen & Stine Bootstraps, N=2000 with 95% bias-corrected confidence intervals (MacKinnon, 2008; Byrne, 2016).

Table 9 shows the results related to hypothesis 3, and hypothesis 4. Table 9 has recorded three effects about each mediation: 1) direct effect (i.e., direct β and p-value) between independent and dependent variables in the absence of mediator, 2) direct effect (i.e., direct β and p-value) between independent and dependent variables in the presence of mediator, and 3) indirect effect (i.e., direct β and p-value) in the presence of mediator and eventually record the final decision about the type of mediation observed.

Table 9: Inference for Mediation
Hypothesis	Direct Beta w/o Med	Direct Beta w/Med	Indirect Beta	Mediation Type Observed
1SA_ANX_EE	� = 0.492,	� = 0.370,	� = 0.116,	Partial
	p = 0.000	p = 0.000	p = 0.001	Mediation
2DA_ANX_EE	� = 0.477,	� = 0.366,	� = 0.107,	Partial
	p = 0.000	p = 0.001	p = 0.001	Mediation

Mediation 1: ANX mediates between SA and EE

In mediation 1, surface acting is an independent variable, anxiety is a mediating variable and emotional exhaustion is a dependent variable. Table 9 reveals the results about hypothesis 3. The value of direct beta between independent and dependent variable is recorded in the absence of mediator that is β=0.492 and calculated its level of significance through p-value that is p=0.000. After that direct effect is calculated in the presence of mediator and its beta value is recorded that is β=0.370 and evaluated its level of significance that is p=0.000. In a same trend, indirect effect has also analyzed and its beta & p-value are β=0.116 & p=0.001. It shows that the direct effect of SA towards EE is significant without mediator and with mediator and even it is significant through indirect path. Therefore ANX partially mediates the relationship between SA and EE.

Mediation 2: ANX mediates between DA and EE

In mediation 2, deep acting is an independent variable; anxiety is a mediating variable and emotional exhaustion is a dependent variable. Table 9 reveals the results about hypothesis 4. The value of direct beta between independent and dependent variable is recorded in the absence of mediator that is β=0.477 and calculated its level of significance through p-value that is p=0.000. After that direct effect is calculated in the presence of mediator and its beta value is recorded that is β=0.366 and evaluated its level of significance that is p=0.001. In a same trend, indirect effect has also analyzed and its beta & p-value are β=0.107 & p=0.001. It shows that the direct effect of DA towards EE is significant without mediator and with mediator and even it is significant through indirect path. Therefore ANX partially mediates the relationship between DA and EE.

The results of H3 and H4 shows there is partial mediation. It concludes that both hypotheses show partial mediation. Therefore, anxiety is an important predictor in emotional exhaustion of hotel employees.

Moderation Analysis

Moderation analysis was run to test the hypothesis 5, and hypothesis 6. To investigate the nature of relationship of two-way interaction, a simple effect analysis has executed. For this, Gaskin (2016) recommended “Stats Tools Package” is used in which unstandardized regression coefficients of independent variable, moderator (pride in work herein study), and interactional variable are required to plot the graph and later check its statistical significance through the obtained simple slops. Independent variable (IV) is that whose relationship with dependent variable (DV) is required to moderate. Further, moderator has considered as another variable independent variable that will play the role of moderation. Interactional variable has obtained through the product of independent variable and moderator. The intercept/constant box required value 3 and is important to put in relevant box that makes the most sense. To get the unstandardized regression coefficients, linear regression analysis has executed.

Moderation 1: PIW moderates between SA and EE

The presented graph in Figure 4 has drawn to test the effect of moderation 1 and it portrays by getting the unstandardized regression coefficients (i.e., B) of independent variable that is surface acting, moderator that is pride in work, and interaction that is product of IV and moderator. The outputs of linear regression analyses have delivered the B₁=0.492 (p<0.001), B₂=0.216 (p<0.001), and B₃=0.089 (p<0.001) of surface acting, pride in work, and interaction respectively. Results in Figure 4 have revealed that pride in work strengthens the relationship between “surface acting” and “emotional exhaustion”. Hence, relationship between surface acting and emotional exhaustion is positive and significant at high and low pride in work as is depicted by positive slops. It proves the hypothesis 5.

Moderation 2: PIW moderates between DA and EE

The presented graph in Figure-5 has drawn to test the effect of moderation 2 and it has portrayed by getting the unstandardized regression coefficients (i.e., B) of independent variable that is deep acting, moderator that is pride in work, and interaction that is product of IV and moderator. The outputs of linear regression analyses have delivered the B₁ = 0.605 (p < .001), B₂= 0.216 (p < .001), and B₃ = 0.083 (p < .001) of deep acting, pride in work, and interaction respectively. Results in Figure -5 have revealed that pride in work strengthens the relationship between „deep acting‟ and „emotional exhaustion‟. Hence, relationship between deep acting and emotional exhaustion is positive and significant at high and low pride in work as is depicted by positive slops. It proves the hypothesis 6.

Discussion and Conclusion

H1 shows the relationship between surface acting and emotional exhaustion. The value of correlation coefficient is (r=0.466**, p<0.01) that has explained a weak positive relationship between surface acting and emotional exhaustion. Standardized regression weights were calculated by the structural equation modeling which shows a positive connection of surface acting with emotional exhaustion which is reflected through the statistical value of (β=0.350, p< 0.001). Thus, the interpretation of results indicated that the surface acting influences on emotional exhaustion of hotel sector positively significant.

H2 shows the relationship between deep acting and emotional exhaustion. The value of correlation coefficient is (r=-0.473, p<0.01) that has explained a weak negative relationship between deep acting and emotional exhaustion. Standardized regression weights were calculated by the structural equation modeling which indicated a negatively significant relationship between deep acting and emotional exhaustion which is reflected through the statistical value of (β=- 0.366, p<0.001). Thus, the interpretation of results indicated that the deep acting influences on emotional exhaustion of hotel sector negatively significant.

The previous studies also support that attention must be given to these kinds of jobs and the employees where frequent personal interaction is required with clients and there are more chances to suffer from emotional exhaustion in result of surface acting (Ashforth & Humphery, 1993). The literature support that surface acting has positive association with emotional exhaustion and deep acting has negative association with emotional exhaustion.

Deep actors are stick to organizational display rules so they don’t express their fake emotions and surpass them so they hardly act on surface (Diefendorff et al., 2005). The findings are consistent with the literature as it shows negative relationship with emotional exhaustion. Austin et al., (2008) also supported the same findings. The current study supports that fake emotional feelings can be cause of negative resources accumulation in employees personality as it constraints the personal growth and success of employees so they don’t like to act on surface. The positive relationship of surface acting with emotional exhaustion confirms that cultural intelligence can be a positive resource among employees and it can enable employees to handle the display rules with true feelings to fulfill the organizational display rules. The employees with high cultural intelligence quotient have more capabilities to solve the problems and handle the critical situations to sustain interpersonal relationships and organizational objectives.

The findings are consistent with previous literature that deep actors are more intelligent and hardworking and have high level of conscientiousness (Barrick & Mount, 1991, 2005) so they express the display rules more truly and avoid the state of emotional exhaustion in every kind of profession. Previous study supports that conscientious people do their responsibilities and roles with lot of care; they do their best efforts to adjust their inner emotions for a perfect display of emotions (Grandey, 2000). They are more prepared and understand their job descriptions and display the organizational display rules more effectively (Grandey, 2000). The cultural intelligence becomes more of a positive resource for deep actors and it enhances relationship.

The results depicted that anxiety mediated the relationship between emotional labor strategies and emotional exhaustion. The results indicated that frontline employees of hotel sector of Pakistan require an extra emotional effort to display rules while performing their job duties so they remain in anxiety and are emotionally drained. So, the management of hotel sector of Pakistan should take respective measures to help employees to display their real emotions. The managers need to intervene in appropriate policy making to secure frontline employees from negative consequences like anxiety. The anxiety also plays its role so low emotional exhaustion between emotional labor strategies and emotional exhaustion may be due to existence of anxiety. The mediating role of anxiety depicted that either go for surface acting or deep acting, individuals have to confront the anxiety as when they change their inner feeling and display certain roles they experience certain level of anxiety. Therefore, anxiety is an important predictor in emotional exhaustion of hotel employees as it partially mediates the relationships between emotional labor strategies and emotional exhaustion. The findings are consistent with previous researches as individual’s regular engagement and efforts involved in surface acting leads to high anxiety level which results in high level of emotional exhaustion (Morris & Feldman, 1997). Whereas deep acting did not lead towards anxiety so there is no danger for high emotional exhaustion level. The surface actors experience more anxiety as they have to unauthentically regulate their emotions for certain display rules as compare to deep actors who will have low anxiety as they will show authentic emotions (Hameed & Bashir, 2017).

Results of both hypotheses indicate that pride in work moderates the relationships between emotional labor strategies and emotional exhaustion. Based on the above discussion it is concluded that pride in work is an important driver that played a crucial role in the emotional exhaustion. The results of the study depicted that pride in work is also moderated the relationship between surface acting-emotional exhaustion. The results also validated that pride in work moderated the relationship between deep acting-emotional exhaustion. On the basis of above arguments, it seems that pride in work supports adoption of deep acting strategy instead of surface acting strategy with true emotions (Kensbock et al., 2016). If employees will have high level of pride in work, they can moderate the relationship between emotional labor and emotional exhaustion and affective commitment. Frontline service employees need to self- monitor them vigilantly while handling challenging and difficult customers. All those workers who score high on pride in work try their best to deliver what is demanded from them and in doing so they experience deep acting which helps them perform better on their jobs at the same time reduces emotional exhaustion associated with performing emotional labor (Grandey et al., 2018).

Conclusion

The study proves the relationship between deep acting, surface acting and emotional exhaustion. The study proved that there is partial mediation of anxiety between both emotional labor strategies and emotional exhaustion. The proposed mediating relationship of anxiety between surface acting and emotional exhaustion was supported. Results show that proposed mediating role of anxiety between deep acting and emotional exhaustion is also supported.

Pride in work is a significant moderator of surface acting and emotional exhaustion as well as deep acting and emotional exhaustion relationship. The employees who have high level of pride in work will be emotionally involved to regulate their emotions more heart fully instead of individuals who don’t feel pride for their work and they will not do their job with heart so will indulged more in regulating their emotions hence will be more emotionally exhausted. Thus pride in work will moderate the relationship between emotional labor strategies and emotional exhaustion.

Managerial Implications

The currents study suggests the hotel managers to keep in mind the model of occupational choices while recruiting the employees. Those candidates can be selected while hiring who have such personalities who can cope with emotional labor stress and anxiety while playing their difficult roles. Managers need to hire only those candidates who are strong enough to cope emotional labor positively can be hired.

Moreover, managers need to realize the importance of emotional labor and its negative consequences at workplace affecting employee’s job burnout and they try to reduce its harmful effects. Supervisors need to provide full support and training to front line hotel employees. Duke et al. (2009) also recommended that negative outcomes of emotional labor associated with surface acting can be reduced by perceived organizational support. Thus pride in work can moderate the negative effects of emotional labor on job burnout.

The next finding is that training plays an important role to reduce the detrimental effects of emotional labor. Managers can enhance the emotional resources of employees with suitable training and can indulge the sense among frontline employees that emotional labor and demand of clients is a challenge for them instead of threat (Schneider, 2004). Moreover, Grandey et al., (2005) stated that emotional labor is a kind of phenomenon which can learn and developed by training and repetition also.

Limitation and Future Research

The data was collected from frontline employees of four star and five star hotels of Pakistan only. In future, other sectors like aviation and tourism can be considered to capture emotional labor in whole hospitality industry. In order to represent the better validity more hotels should be obtained. 3 star hotels can also be included. The study is conducted in Pakistani hotel sector where there is scarcity of knowledge about emotional labor so limited dimensions were included but in future other variables can be included with emotional labor.

References

1. Abraham, R. (1999). Emotional intelligence in organizations: A conceptualization. Genetic, social, and general psychology monographs, 125(2), 209-210.
2. Ahmed, R., Ahmad, N., Saifullah, A., & Jatoi, I. (2014). Ravaged Lands: An Investigation of Factors Affecting Pakistan's Tourism Industry. Information and Knowledge Management, ISSN.
3. Aktaş, M. (2014). Moderating effect of idiocentrism and allocentrism on person-organization person-job fit and work attitudes relationship. Cross Cultural Management, 21(3), 290-305.
4. Alola, U.V., Olugbade, O.A., Avci, T., & Öztüren, A. (2019). Customer incivility and employees' outcomes in the hotel: Testing the mediating role of emotional exhaustion. Tourism Management Perspectives, 29, 9-17.
5. Anderson, J.C., & Gerbing, D.W. (1982). Some methods for respecifying measurement models to obtain unidimensional construct measurement. Journal of Marketing Research, 19(4), 453-460.
6. Arnett, D.B., Laverie, D.A., & McLane, C. (2002). Using job satisfaction and pride as internal-marketing tools. Cornell hotel and restaurant administration quarterly, 43(2), 87-96.
7. Ashforth, B.E., & Humphrey, R.H. (1993). Emotional labor in service roles: The influence of identity. Academy of Management Review, 18(1), 88-115.
8. Asif, K.M. (2012). Impact of emotional labor on emotional exhaustion, and moderating role of social support: an empirical study on hospitality industry in Pakistan. Актуальні проблеми економіки, 5, 321-329.
9. Austin, E.J., Dore, T.C., & O’Donovan, K.M. (2008). Associations of personality and emotional intelligence with display rule perceptions and emotional labour. Personality and Individual Differences, 44(3), 679-688.
10. Barrick, M.R. & Mount, M.K. (2005). Yes, personality matters: Moving on to more important matters. Human Performance, 18(4), 359-372.
11. Barrick, M.R., & Mount, M.K. (1991). The big five personality dimensions and job performance: a meta‐analysis. Personnel Psychology, 44(1), 1-26.
12. Bollen, K.A. (1989). Structural Equations with Latent Variables John Wiley New York.
13. Bouckaert, G. (2001). Pride and performance in public service: Some patterns of analysis. International Review of Administrative Sciences, 67(1), 15-27.
14. Brotheridge, C., & Lee, R.T. (2003). Development and validation of the Emotional Labor Scale. Journal of Occupational and Organizational Psychology, 76, 365-379.
15. Brotheridge, C.M., & Grandey, A.A. (2002). Emotional labor and burnout: Comparing two perspectives of people work. Journal of Vocational Behavior, 60, 17-39.
16. Browne, M.W., & Cudeck, R. (1993). Alternative ways of assessing model fit. Sage focus editions, 154, 136-136.
17. Byrne, B.M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). New York: Routledge.
18. Carmines, E.G., & Zeller, R.A. (1979). Reliability and validity assessment, 17. Sage publications.
19. Chaudhry, M.A., & Shah, N. (2011). Impact of supportive leadership and organizational learning culture as a moderator on the relationship of psychological empowerment and organizational commitment. Journal of Business Strategies, 5(1), 39.
20. Chen, A.S.Y. (2015). CQ at work and the impact of intercultural training: An empirical test among foreign laborers. International Journal of Intercultural Relations, 47, 101-112.
21. Chen, K.Y., Chang, C.W., & Wang, C.H. (2019). Frontline employees’ passion and emotional exhaustion: The mediating role of emotional labor strategies. International Journal of Hospitality Management, 76, 163- 172.
22. Cheung, F.Y.L., & Tang, C.S.K. (2009). The influence of emotional intelligence and affectivity on emotional labor strategies at work. Journal of Individual Differences, 30(2), 75-86.
23. Cheung, F., Tang, C.S.K., & Tang, S. (2011). Psychological capital as a moderator between emotional labor, burnout, and job satisfaction among school teachers in China. International Journal of Stress Management, 18(4), 348.
24. Cheung, G.W., & Lau, R.S. (2008). Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models. Organizational Research Methods, 11(2), 296-325.
25. Chi, N. W., & Grandey, A. A. (2019). Emotional labor predicts service performance depending on1 activation and inhibition regulatory fit. Journal of Management, 45(2), 673-700.
26. Diefendorff, J.M., Croyle, M.H., & Gosserand, R.H. (2005). The dimensionality and antecedents of emotional labor strategies. Journal of Vocational Behavior, 66(2), 339-357.
27. Duke, A.B., Goodman, J.M., Treadway, D.C., & Breland, J.W. (2009). Perceived organizational support as a moderator of emotional labor/outcomes relationships. Journal of Applied Social Psychology, 39(5), 1013- 1034.
28. Dziuban, C.D., & Shirkey, E.C. (1974). When is a correlation matrix appropriate for factor analysis? Some decision rules. Psychological Bulletin, 81(6), 358.
29. Ekman, P. (1973). Cross-cultural studies of facial expression. Darwin and facial expression: A century of research in review, 169222(1).
30. Elovainio, M., Kivimaki, M. & Helkama, K. (2001). Organization justice evaluations, job control, and occupational strain. Journal of Applied Psychology, 86, 418-424.
31. Else-Quest, N.M., Higgins, A., Allison, C., & Morton, L.C. (2012). Gender differences in self-conscious emotional experience: A meta-analysis. Psychological Bulletin, 138(5), 947.
32. Farndale, E., Biron, M., Briscoe, D.R., & Raghuram, S. (2015). A global perspective on diversity and inclusion in work organisations. The International Journal of Human Resource Management, 26(6), 677-687.
33. Gaskin, J. (2016). Excel StatTools. Stats tools package.
34. Goussinsky, R. (2011). Customer aggression, emotional dissonance and employees' well-being. International Journal of Quality and Service Sciences, 3(3), 248-266.
35. Goussinsky, R. (2015). Customer aggression, felt anger and emotional deviance: The moderating role of job autonomy. International Journal of Quality and Service Sciences, 7(1), 50-71.
36. Grandey, A.A. (2000). Emotion regulation in the workplace: A new way to conceptualize emotional labor. Journal of Occupational Health Psychology, 5(1), 95-110.
37. Grandey, A.A., & Sayre, G.M. (2019). Emotional Labor: Regulating Emotions for a Wage. Current Directions in Psychological Science, 0963721418812771.
38. Grandey, A.A., Ferris, D.L., & Melloy, R.C. (2018). A dual signal model of pride displays in organizations. Research in Organizational Behavior.
39. Grandey, A.A., Fisk, G.M., & Steiner, D.D. (2005). Must service with a smile be stressful? The moderating role of personal control for American and French employees. Journal of Applied Psychology, 90(5), 893.
40. Grandey, A.A. (2003). When the show must go on: Surface and deep acting as determinants of emotional exhaustion and peer-rated service delivery. Academy of Management Journal, 46, 86-96.
41. Hair Jr, J.F., Black, W.C., Babin, B.J., Anderson, R.E., & Tatham, R.L. (2010). SEM: An introduction. Multivariate data analysis: A global perspective, 629-686.
42. Halbesleben, J.R. (2006). Sources of social support and burnout: a meta-analytic test of the conservation of resources model. Journal of applied Psychology, 91(5), 1134.
43. Halbesleben, J.R. (2010). The role of exhaustion and workarounds in predicting occupational injuries: A cross- lagged panel study of health care professionals. Journal of Occupational Health Psychology, 15(1), 1.
44. Halbesleben, J.R.B., & Bowler, W.M. (2007). Emotional exhaustion and job performance: The mediating role of motivation. Journal of Applied Psychology, 92, 93-106.
45. Halbesleben, J.R., & Buckley, M.R. (2004). Burnout in organizational life. Journal of Management, 30(6), 859-879.
46. Halbesleben, J.R., & Wheeler, A.R. (2011). I owe you one: Coworker reciprocity as a moderator of the day‐level exhaustion–performance relationship. Journal of Organizational Behavior, 32(4), 608-626.
47. Halbesleben, J.R., & Wheeler, A.R. (2015). To invest or not? The role of coworker support and trust in daily reciprocal gain spirals of helping behavior. Journal of Management, 41(6), 1628-1650.
48. Halbesleben, J.R., Harvey, J., & Bolino, M.C. (2009). Too engaged? A conservation of resources view of the relationship between work engagement and work interference with family. Journal of Applied Psychology, 94(6), 1452.
49. Halbesleben, J.R., Neveu, J.P., Paustian-Underdahl, S.C., & Westman, M. (2014). Getting to the COR understanding the role of resources in conservation of resources theory. Journal of Management, 40(5), 1334-1364.
50. Halbesleben, J., Wheeler, A.R., & Paustian-Underdahl, S.C. (2013). The impact of furloughs on emotional exhaustion, self-rated performance, and recovery experiences. Journal of Applied Psychology, 98(3), 492.
51. Hameed, F., & Bashir, S. (2017) Front Line Female Hospitality Worker’s Emotional Labor and Adaptive Performance: Does Islamic Work Ethics Moderate Relationship?. Journal of Managerial Sciences 71 (11), 49-72
52. Hobfoll, S.E. (1989). Conservation of resources: A new attempt at conceptualizing stress. American Psychologist, 44(3), 513-524.
53. Hobfoll, S.E. (2001). The influence of culture, community, and the nested‐self in the stress process: advancing conservation of resources theory. Applied Psychology, 50(3), 337-421.
54. Hobfoll, S.E. (2002). Social and psychological resources and adaptation. Review of general Psychology, 6(4), 307- 324.
55. Hobfoll, S.E. (2011). Conservation of resource caravans and engaged settings. Journal of Occupational and Organizational Psychology, 84(1), 116-122.
56. Hobfoll, S. E. (2011). Conservation of resources theory: Its implication for stress, health, and resilience. The Oxford handbook of stress, health, and coping, 127-147.
57. Hobfoll, S.E. (2012). Conservation of resources and disaster in cultural context: The caravans and passageways for resources. Psychiatry: Interpersonal & Biological Processes, 75(3), 227-232.
58. Hobfoll, S.E., Freedy, J., Schaufeli, W.B., Maslach, C., & Marek, T. (1993). Professional burnout: Recent developments in theory and research.
59. Hobfoll, S.E., Halbesleben, J., Neveu, J.P., & Westman, M. (2018). Conservation of resources in the organizational context: The reality of resources and their consequences. Annual Review of Organizational Psychology and Organizational Behavior, 5, 103-128.
60. Hobfoll, S.E., Stevens, N.R., & Zalta, A.K. (2015). Expanding the science of resilience: Conserving resources in the aid of adaptation. Psychological Inquiry, 26(2), 174-180.
61. Hochschild Arlie, R. (1983). The managed heart: Commercialization of human feeling.
62. Hochschild, A.R. (1979). Emotion work, feeling rules, and social structure. American Journal of Sociology, 85(3), 551-575.
63. Horo, P.R. (2014). Impact of emotional labour on employee well-being: A conceptual framework. Review of HRM, 3, 21.
64. Hülsheger, U.R., Alberts, H.J., Feinholdt, A., & Lang, J.W. (2013). Benefits of mindfulness at work: the role of mindfulness in emotion regulation, emotional exhaustion, and job satisfaction. Journal of Applied Psychology, 98(2), 310.
65. Hwa, M. A. C. (2012). Emotional labor and emotional exhaustion: does co-worker support matter?. Journal of Management Research, 12(3), 115.
66. Jin, M.H., & Guy, M.E. (2009). How emotional labor influences worker pride, job satisfaction, and burnout: An examination of consumer complaint workers. Public Performance & Management Review, 33(1), 88-105.
67. Kamp, A., & Dybbroe, B. (2016). Struggles of professionalism and emotional labour in standardized mental health care. Nordic Journal of Working Life Studies, 6, 67-86.
68. Karatepe, O.M. (2011). Do job resources moderate the effect of emotional dissonance on burnout? A study in the city of Ankara, Turkey, International Journal of Contemporary Hospitality Management, 23(1), 44-65.
69. Kenny, D.A. (2014). Measuring model fit (http://davidakenny.net/cm/fit.htm). Accessed January.
70. Kensbock, S., Jennings, G., Bailey, J., & Patiar, A. (2016). Performing: Hotel room attendants employment experiences. Annals of Tourism Research, 56, 112-127.
71. Kline, R. (1998). Principles and practice of structural equation modeling: A very readable introduction to the subject, with good coverage of assumptions and SEM's relation to underlying regression, factor, and other techniques: NY: Guilford Press
72. Kline, R.B. (2005). Methodology in the social sciences.
73. Kline, R.B. (2015). Principles and practice of structural equation modeling. Guilford publications.
74. Lam, W., & Chen, Z. (2012). When I put on my service mask: Determinants and outcomes of emotional labor among hotel service providers according to affective event theory. International Journal of Hospitality Management, 31(1), 3-11.
75. Lea, S.E., & Webley, P. (1997). Pride in economic psychology. Journal of Economic Psychology, 18(2-3), 323-340. Lee, R.T. & Ashforth, B.E. (1993). A further examination of managerial burnout: Toward an integrated model. Journal of Organizational Behavior, 14, 3-20.
76. Lee, Y.H., & Chelladurai, P. (2016). Affectivity, emotional labor, emotional exhaustion, and emotional intelligence in coaching. Journal of Applied Sport Psychology, 28(2), 170-184.
77. Li, J.J., Wong, I.A., & Kim, W.G. (2017). Does mindfulness reduce emotional exhaustion? A multilevel analysis of emotional labor among casino employees. International Journal of Hospitality Management, 64, 21-30.
78. MacKinnon, D.P. (2008). Multilevel mediation models. Introduction to Statistical Mediation Analysis. New York, NY: Lawrence Erlbaum Associates, 237-274.
79. Malhotra, N.K. (2010). Marketing research: An applied orientation, 834.
80. Maslach, C., & Jackson, S.E. (1981). The measurement of experienced burnout. Journal of Organizational Behavior, 2(2), 99-113.
81. Maslach, C., & Leiter, M.P. (1997). The truth about burnout: How organizations cause personal stress and what to do about it. San Francisco: Jossey-Bass.
82. Maslach, C., & Leiter, M.P. (2008). Early predictors of job burnout and engagement. Journal of Applied Psychology, 93(3), 498.
83. Maslach, C., Jackson, S.E., & Leiter, M.P. (1996). Maslach burnout inventory manual, 4. Palo Alto, CA: Consulting psychologists press.
84. Maslach, C., Schaufeli, W.B., & Leiter, M.P. (2001). Job burnout. Annual Review of Psychology, 52(1), 397-422. McDonald, R.P. (1978). A simple comprehensive model for the analysis of covariance structures. British Journal of Mathematical and Statistical Psychology, 31(1), 59-72.
85. Miller, K.I., Considine, J., & Garner, J. (2007). Let me tell you about my job: Exploring the terrain of emotion in the workplace. Management Communication Quarterly, 20(3), 231-260.
86. Morelli, N.A., & Cunningham, C.J. (2012). Not all resources are created equal: COR theory, values, and stress. The Journal of Psychology, 146(4), 393-415.
87. Morris, J.A., & Feldman, D.C. (1997). Managing emotions in the workplace. Journal of Managerial Issues, 9(3), 257.
88. Morris, M.W., Leung, K., Ames, D., & Lickel, B. (1999). Views from inside and outside: Integrating emic and etic insights about culture and justice judgment. Academy of Management Review, 24(4), 781-796.
89. Nadeem, K., Riaz, A., & Danish, R.Q. (2019). Influence of high-performance work system on employee service performance and OCB: the mediating role of resilience. Journal of Global Entrepreneurship Research, 9(1), 13.
90. Rai, S. (2015). Organizational justice and employee mental health’s moderating roles in organizational identification. South Asian Journal of Global Business Research, 4(1), 68-84.
91. Roethlisberger, F.J., & Dickson, W.J. (2003). Management and the Worker, 5. Psychology press.
92. Schneider, T.R. (2004). The role of neuroticism on psychological and physiological stress responses. Journal of Experimental Social Psychology, 40(6), 795-804.
93. Simillidou, A. (2016). Managing emotional labour consequences during aggressive customers’ interactions: A study of the Cyprus hospitality industry (Doctoral dissertation, University of Gloucestershire).
94. Spell, C.S., & Arnold, T.J. (2007). A multi-level analysis of organizational justice climate, structure, and employee mental health. Journal of Management, 33(5), 724-751.
95. Steiger, J.H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research, 25(2), 173-180.
96. Stewart, D.W. (1981). The application and misapplication of factor analysis in marketing research. Journal of Marketing Research, 18(1), 51-62.
97. Suls, J., & Bunde, J. (2005). Anger, anxiety, and depression as risk factors for cardiovascular disease: the problems and implications of overlapping affective dispositions. Psychological Bulletin, 131(2), 260.
98. Tamer, I. (2015). The effect of positive psychological capital on emotional labor. International Journal of Research in Business and Social Science, 4(2), 20.
99. Tanaka, J.S. (1987). How big is big enough?: Sample size and goodness of fit in structural equation models with latent variables. Child Development, 134-146.
100. Testa, M.R. (2001). Organizational commitment, job satisfaction, and effort in the service environment. The Journal of Psychology, 135(2), 226-236.
101. Totterdell, P., & Holman, D. (2003). Emotion regulation in customer service roles: Testing a model of emotional labor. Journal of Occupational Health Psychology, 8(1), 55.
102. Tracy, J.L., & Robins, R.W. (2007). Emerging insights into the nature and function of pride. Current Directions in Psychological Science, 16(3), 147-150.
103. Tracy, J.L., & Robins, R.W. (2014). Conceptual and empirical strengths of the authentic/hubristic model of pride. Emotion, 14(1), 33-37.
104. Trefry, M. (2001). Multicultural teams: Insight from experiences in Luxembourg. In Proceedings of the European International Business Association Annual Conference. Paris, France.
105. Trefry, M.G. (2006). A double-edged sword: organizational culture in multicultural organizations. International Journal of Management, 23 (3), 563-575.
106. Van Dijk, P.A., & Brown, A.K. (2006). Emotional labour and negative job outcomes: An evaluation of the mediating role of emotional dissonance. Journal of Management & Organization, 12(2), 101-115.
107. Walsh, G. (2019). Service employees’ naturally felt emotions: Do they matter?. European Management Journal, 37(1), 78-85.
108. Wang, K.L., & Groth, M. (2014). Buffering the negative effects of employee surface acting: The moderating role of employee–customer relationship strength and personalized services. Journal of Applied Psychology, 99(2), 341.
109. Williams, A.A., Bryant, Z., & Carvell, C. (2019). Uncompensated emotional labor, racial battle fatigue, and (in) civility in digital spaces. Sociology Compass, e12658.
110. Williams, L.A., & DeSteno, D. (2008). Pride and perseverance: the motivational role of pride. Journal of Personality and Social Psychology, 94(6), 1007.
111. Wonnacott, R. (1990). Introductory Statistics for Business and Economics. New York: Wiley.
112. Zopiatis, A., & Constanti, P. (2010). Leadership styles and burnout: is there an association?. International Journal of Contemporary Hospitality Management, 22(3), 300-320.