Emotional labor in hospitality: Positive affective displays in service encounters

Abstract

The study used web-based simulated hospitality scenarios to examine cultural differences in emotional cognition of facial expressions among Chinese and American subjects in an exploratory study. Results indicate that the two cultural groups interpreted smiling and direct eye-gaze similarly. Although a smiling face elicited positive emotional affective responses from both cultural groups, smiling alone was not sufficient to stimulate more positive subject reactions: Smiling needs to be accompanied by direct eye-gaze to fully elicit positive reactions from subjects. Study results suggest that global hospitality standards should reflect findings of psychological research on emotional labor and also that business normative guidelines should encourage the display of smiling faces along with direct eye-gaze to motivate a positive customer experience. No support was found for tailoring facial expressions related training to customers’ cultural backgrounds.

Keywords

Culture emotional labor affective facial displays emotional cognition customer service

Introduction

Service quality in the hospitality sector has been linked to business competitiveness and to ultimate success (Giannakos et al., 2014; Yildiz and Kara, 2012). Attention to service quality contributes to high customer satisfaction because it exhibits responsiveness to customers and fosters emotional bonding between customers and service providers (Davidson, 2003; Gustafsson et al., 2005; Hanif et al., 2010). The interaction between frontline service providers and guests is considered a critical determinant of service satisfaction and of brand loyalty because it affects customers’ perceptions of service quality (Barger and Grandey, 2006; Hui and Toffoli, 2002; Kandampully et al., 2001; Stauss and Mang, 1999; Tsai and Huang, 2002; Zeithaml et al., 2006).

Given the significance of the provider–customer interaction, the concept of emotional labor has emerged to describe organizational expectations that employees display positive emotions to prompt customers’ positive disposition toward the service provided (Groth et al., 2009; Hochschild, 1983; Wharton, 2009). Since service is produced and consumed simultaneously, customers’ perceptions of emotional displays impact critical business outcomes in terms of customer purchasing behavior (e.g. intention and amount of purchase) and willingness to commit to future purchases (Chang, 2000; Hochschild, 1983; Tsai and Huang, 2002). Emotional labor has become an important job requirement in the hospitality industry, especially for those positions entailing a direct relationship with the guests, because it builds provider–customer bonding (Chu and Murrmann, 2006). Such bonding, in turn, enhances the competitive advantages of organizations and lead to their long-term survival (Lam and Chen, 2012; Lucus and Deery, 2004).

Due to high expectations for service quality in the hospitality industry, emotional labor has become a critical variable in service performance (Shani et al., 2014). Nevertheless, hospitality scholarship is scant as regards quantitative measurement of emotional displays and their impacts on customers (Chu et al., 2012). Additionally, the literature verifies that the study of emotions is also important as a cross-cultural issue (Shani et al., 2014) given that the hotel sector has been largely influenced by globalization and international franchising trends (Go and Pine, 1995; Guerrier and Deery, 1998). However, there are few studies exploring the role of culture in the performance of or response to emotional displays. Since cultural manifestations (e.g. beliefs, values, traditions) shape people’s thoughts and behavior (Furrer et al., 2000; Leu et al., 2011), it is expected that culture also impacts emotional displays and customers’ perceptions of providers’ emotions (Johanson and Woods, 2008).

This exploratory study responds to the need to better understand emotional labor performance during a provider–customer interaction in the hospitality industry (Chu et al., 2012; Johanson and Woods, 2008; Kim, 2008; Medler-Liraz, 2014; Shani et al., 2014). A better phenomenological understanding of emotional displays is important to identify positive cues that can foster customer satisfaction and expectations, thus clientele retention (Chu et al., 2012; Hochschild, 1983; Kim, 2008). It is especially critical to understand the role of culture since emotional display and perceptions of emotions have been found to be culturally determined (Bello et al., 2010; Ekman et al., 1987; Mesquita, 2003). Thus, this study pursues two objectives: examine subjects’ stated emotional perceptions of service providers’ facial expressions (i.e. smile and eye gaze) and explore the cultural effect (Chinese versus American) on customers’ perceptions of common emotional displays in the hospitality industry.

By addressing the aforementioned objectives, this study moves forward the phenomenological understanding of emotional labor by recognizing the role of cultural influences upon specific nonverbal markers (i.e. customers’ perception of presence/absence of smile and direct/indirect eye gaze). In doing so, study results carry important managerial applications, specifically to inform hospitality service global standards and internal organizational normative guidelines that foster positive emotional displays, and thus, improve provider–customer interaction and organizational performance. Although emotional cues are hard to prescribe, fostering employees to display positive emotions (e.g. authentic smile) during service interaction is both possible (Baum and Devine, 2005) and important as they impact service quality (Chu and Murrmann, 2006; Hochschild, 1983; Pizam, 2004).

Literature review

Emotion is the psychophysiological process of experiencing or displaying affect and often involves biological and mental reactions to signals exteriorized through facial expressions, verbal statements, and physical behaviors of others (Tsai et al., 2006). The communication of emotions, referred as emotional display, is a fundamental aspect of the provider–customer interaction because customers’ perceptions of providers’ emotions determine customer satisfaction (Barger and Grandey, 2006; Chi et al., 2011; Chu et al., 2012; Jack et al., 2014; Tsai and Huang, 2002). This is especially important in service industries, such as in the restaurant and lodging sectors, because the product (e.g. food served in a restaurant) and service (e.g. serving the food to patrons) provided are inseparable (Parasuraman et al., 1985, 1993).

Displaying positive emotions through simulated affection on the part of employees (e.g. respectful expressions, empathy) is associated with organizational objectives such as customer satisfaction, intention to return, and positive word of mouth (Chi et al., 2011; Johanson and Woods, 2008; Söderlund and Rosengren, 2008; Tsai, 2001). Conversely, negative affective displays (e.g. impolite wording, unfriendly attitude) have a negative effect on service satisfaction (Brotheridge and Grandey, 2002; Brotheridge and Lee, 2003; Gross and John, 2003). Thus, certain emotional displays are encouraged by hospitality organizations to maximize the positive outcomes of provider–customer interaction.

Smile and eye gaze are two common nonverbal expressions/features in customer service interactions (Ford, 1998). Smiling employees manifest core service indicators of courtesy, respect, compassion, and hospitality (Barger and Grandey, 2006; Gross and John, 2003; Matsumoto and Hwang, 2012) and thus have become the golden rule for American businesses and have been encouraged since the early 1900s (Barger and Grandey, 2006; Chi et al., 2001; Chu et al., 2012; Hunter, 2011; Johnson and Spector, 2007; Söderlund and Rosengren, 2008). Likewise, the directness of eye gaze is positively associated with comfort, which can foster a sympathetic provider–customer relationship (Exline, 1974).

Emotional labor and positive affective displays

Organizations have developed internal normative standards to encourage their frontline employees to simulate certain emotions through facial (e.g. smile, eye gaze) or verbal (e.g. greetings, farewell) expressions (Shani et al., 2014) to optimize the provider–customer interaction and elicit desirable feelings from customers. Employees who are expected to display positive emotions through observable facial and body expressions (e.g. smile) are assigned “emotional labor,” a term originally coined by Hochschild (1983). Thus, emotional labor has been recognized as a key dimension of service quality (Parasuraman et al., 1985) and a key contributor to organizational goals (Grandey and Brauburger, 2002).

The deployment of emotional labor in hospitality organizations is meant to elicit a positive affect from customers (Johanson and Woods, 2008; Kim, 2008; Kim and Han, 2009; Larsen and Ketelaar, 1991; Watson and Slack, 1993). Positive affect is the tendency of an individual to experience positive emotions (e.g. happiness, relaxation) and to be influenced by their positive perceptions of the world (George, 1992; Larsen and Ketelaar, 1991; Watson et al., 1988). Emotional displays facilitate a corresponding (contagion) emotional state in others (Hatfield et al., 1994). This explains, for example, why service providers in the hospitality sector displaying positive affective emotions receive higher tips and positive customer appreciation (Medler-Liraz, 2014). From an exchange value perspective, emotion is an important transactional element in customer relationships.

Smile as a positive emotional display at work

Encouraging service professionals to enact a variety of positive affective displays is a strategy to manage customers’ emotional states during provider–customer interaction (Mattila and Enz, 2002). This is especially important in the hospitality industry given the large number (1.86 million) of hotel workers with varied backgrounds and personalities that have to directly interact with customers (American Hotel and Lodging Association, 2014) and the emergent demand for highly skilled service providers (Baum, 2002; Baum and Devine, 2007). Among all emotional displays, smile is especially recommended among all frontline service providers (Cook and Macaulay, 1997; Muir, 2008) because of its strong impact on customers’ dispositions (Burns, 1997; Line and Runyan, 2012; Warhurst and Nickson, 2007).

Although service workers are encouraged to display positive and friendly attitudes through certain types of smile features (e.g. authentic, natural, genuine) that customers tend to favor (Ariffin and Maghzi, 2012; Chu and Murrmann, 2006; Ekman, 1992; Grandey et al., 2005), formal training toward such a goal is challenging and controversial. At a minimum, the quest for standardized positive emotional displays requires service providers to modify their nonverbal and verbal displays to meet job requirements. Such training and concomitant performance expectations may often conflict with employees’ authentic feelings (Johnson and Spector, 2007; Johanson and Woods, 2008; Kim, 2008; Kim and Han, 2009; Lam and Chen, 2012; Zapf and Holz, 2006). Employee cultural practices may also be a factor in an employee’s ability or willingness to display positive affect to customers.

Cultural impact on emotional display and perception

Culture, defined as an intricate system of social concepts and beliefs, norms each individual’s emotional display of and expectations for social interaction (Engelmann and Pogosyan, 2013; Leu et al., 2011). Since variations in the display and the perception of emotions are culturally bonded (Bello et al., 2010; Ekman et al., 1987; Mesquita, 2003), interactions between emotional labor and customers are ultimately a cultural issue. Individuals from western individualistic cultures tend to convey their emotions in a more direct way than do people who are engrained in collectivistic cultures; the latter are encouraged to control their emotional expressions to maintain group harmony (Heine et al., 1999; Markus and Kitayama, 1991; Matsumoto et al., 2008). Chinese, as compared to Americans for example, use different linguistic forms and semantic content to express their complaints because of their sensitivity to social power associated with their group-oriented culture (Chen et al., 2011). Similarly, Japanese were found to restrain expressions of power (e.g. anger, contempt, and disgust) more than did Canadians (Safdar et al., 2009). Americans tend to convey their appreciation directly using both verbal and nonverbal expressions, while Chinese favor nonverbal over verbal expressions (Bello et al., 2010).

Research also indicates that cultural background is associated with emotional perception of facial signals (Nagashima and Schellenberg, 1997). For example, Americans tend to rate facial expressions of happiness, sadness, and surprise more intensely than Japanese and Russians do (Engelmann and Pogosyan, 2013), although Japanese infer stronger emotions to neutral facial expressions than do Americans (Matsumoto et al., 2002). Culture also appears to influence individuals’ responses to eye gaze. For example, Adams et al. (2010) concluded that Japanese tend to avert direct eye gaze to a greater extent than Americans, most likely because a direct eye gaze represents a threatening social cue among Japanese.

In brief, the literature suggests that emotional labor influences the provider–customer interaction and that culture affects both the display and perception of emotions. However, evidence to date is scant and previous studies tend to neglect assessment of customer perception of emotions. Although the levels of customer satisfaction based on service agents’ hospitable attitudes (e.g. welcoming, courtesy, friendliness) have been explored (e.g. Li et al., 2016; Shani et al., 2014), few studies have investigated customers’ perceptions of facial expressions and whether those perceptions are influenced by cultural background. To address this gap in the literature, this study focuses on the following two hypotheses:

Hypothesis 1: Customer’s stated emotional perceptions are associated with the type of service provider’s emotional display (i.e. smile with direct eye, smile with indirect eye, no smile with direct eye).

Hypothesis 2: American respondents exhibit more intense emotional responses (either positive or negative) to stimulus faces than Chinese respondents.

Methodology

Research design

Following Yücesan et al. (2001), a web-based simulated experimental design of facial expressions was developed to address the study objectives. Although using a web-based simulated scenario within a laboratory environment may not capture the subtle nuanced nature of real social exchanges, this method was deemed suitable for this study to reduce biases associated with research designs involving real-life scenarios (e.g. moods’ swings affecting the uniformity of facial displays in field observations), to tailor desired face displays in a consistent manner, and to reduce biases from memory lapses and rationalization processes (Levin and Zickar, 2002; Levy et al., 2004; Smith et al., 1999).

A web-based platform (Qualtrics) was used to describe the simulated scenario (exposure to a stimulus face of a hotel front desk employee) and to prompt two facial expression attributes: presence/absence of smile and direct/indirect eye gaze. Although other attributes (e.g. customers’ moods) can influence emotional display and perceptions in “real” provider–customer encounters (Grandey et al., 2004), smiling and eye gaze as static displays were chosen because of their relevance in service industries (Barger and Grandey, 2006; Ford, 1998; Gross and John, 2003; Matsumoto and Hwang, 2012) and being the core exteriorization of the provider–customer relationship (Exline, 1974). Three experimental treatments were designed to garner participants’ emotion perception using three images of the same service provider displaying different facial expressions: smile with direct eye gaze, smile with indirect eye gaze, and no smile with direct eye gaze (Figure 1). The high-quality images used were identical in size, 4.8 in. wide (12.3 cm) by 3.2 in. height (8.2 cm), and in resolution (72 pixels/in.; 28.4 pixels/cm).

Figure 1.

Study images representing smile/nonsmile faces with direct/indirect eye gaze.

Sampling and survey development

The sample of this study was composed of female students enrolled in a U.S. higher education institution representing two cultural groups: American and Chinese. Although the study sample is not drawn directly from sampling frames of American and Chinese hospitality customers, using student samples is a common practice in exploratory experimental designs (e.g. Barsade, 2002; Surprenant and Solomon, 1987), especially to evaluate consumers’ preferences and perceptions across various kinds of services (Furrer et al., 2000). Two different sampling procedures were followed: American participants were recruited by emailing the 230 students enrolled in the Department of Community and Therapeutic Recreation in a U.S. university; Chinese students were recruited using a snowball sampling technique, initiated with acquaintances of one of the authors (Flick, 2014). Following linguistic design protocols, only female students were sampled to maximize group homogeneity and minimize cross-gender observation bias (Furumo and Pearson, 2007; Mast and Hall, 2004; Mulac et al., 2001).

Participants were asked to imagine approaching a hotel front-desk receptionist. They were presented with one (of three) of the aforementioned images and asked to rate a suite of emotions such an image portrayed. Then, participants accessed another page where a second image was presented and asked to rate the same set of emotions, after which they accessed another page to rate the third image. The order of the images was randomly presented to participants to reduce bias associated with researchers’ hypothesized causal relationships and to increase research design validity (Abraham and Wasserbauer, 2006). Informed by the literature (George, 1992; Larsen and Ketelaar, 1991), emotional perceptions were measured through eight indicators: comfort, relaxation, goodness, happiness, courteous, politeness, friendliness, and appropriateness using five-point Likert type scales (1 indicating the lowest score and 5 the highest). Specific scales were built for each emotion; for example Comfort was measured from Extremely Uncomfortable (1) to Extremely Comfortable (5).

The scenarios and questions were stated in English. The use of English was not considered a barrier among Chinese participants because of their certified language competency as college students in an American institution; furthermore, evidence suggests that Chinese English learners and native English speakers have similar abilities to comprehend the emotion concepts being measured in this study (Yu-Cheng, 2011). The survey was launched in December 2013 and data collection spanned to January 2014; two reminders were sent to increase participation. The survey was closed after recruiting 23 female students from Mainland China (n = 23; 52.3%) and 21 from the United States (n = 21; 47.7%), after securing sample sizes well above the minimum of 10–15 per treatment recommended for experimental studies (Riddick and Russell, 2008).

Statistical analysis

Descriptive and inferential analyses were used to analyze data collected. Descriptive analysis was conducted to examine participants’ demographic characteristics and their perceptions of the service provider’s facial expressions. Cronbach alphas were computed to test the internal reliability of the eight emotion scales. Repeated Measures Analysis of Variance (RM-ANOVA) was performed to compare emotional perception across the three images (smile direct eye, smile indirect eye, and nonsmile direct eye); assumption of sphericity was examined using Mauchly’s test (Howell,2013). Given that likewise method was used to handle missing values when comparing emotional perceptions across the three images, initial mean scores within each image may slightly differ from those resulting from the RM-ANOVAs. Post hoc paired t-tests were then employed to compare all pairs of levels of the independent variable in each significant RM-ANOVA results. The Bonferroni correction (p = 0.05/3 = 0.017) was used to reduce type II statistical error. Independent samples t-tests were conducted to compare the cultural variation on participants’ emotional perception of facial expression displayed in the three images.

Results

Demographic profile of respondents

The dominant respondents’ age group was between 21 and 25 years (n = 25; 56.8%); those between 26 and 30 years old (n = 12; 27.3%) and between 18 and 20 years old (n = 7; 15.9%) were less represented. Slightly over half (n = 25; 56.8%) were currently enrolled in a graduate program and 43.2% were undergraduate students (n = 19). Education level was significantly different across the two cultural groups (χ²= 9.031; p = .003); more Chinese students were enrolled in a graduate program (n = 18; 78.3%) than were U.S. respondents (n = 7; 33.3%). Half (n = 22; 50.0%) of participants had some prior experience working in a position entailing some customer interaction, with an average of five years of experience. The American and Chinese samples were homogeneous in terms of age (t = 2.10; p = .77) and education level (t = 3.29; p = 1.00). Although customer interaction experience was significantly more prevalent (χ²= 11.023; p = .001) among the American participants (n = 16; 76.2%) as compared to their Chinese counterparts (n = 6; 26.1%), such difference was not significantly different (t = 3.75; p = .73).

Participants’ perception to facial expressions

Reliability tests showed high internal consistency among the eight emotion indicators within the three images, smile direct eye gaze (α = .946), smile indirect eye gaze (α = .975), and no smile direct eye gaze (α = .949). Overall, looking at Hypothesis 1, results suggest that smiling faces elicit high positive affect although to a greater extent when accompanied with direct eye gaze (M = 4.4, SD = 0.6) than with indirect eye gaze (M = 3.2, SD = 1.1); the nonsmile direct eye gaze (M = 1.9, SD = 0.8) evoked negative affect (Table 1). Smile direct eye gaze evoked positive affect in all eight indicators examined (M ≥ 4.2) being especially strong in conveying friendliness (M = 4.5). The smile indirect eye gaze image elicited overall neutral affect, although it was somewhat positive to evoke friendliness (M = 3.4) and happiness (M = 3.4). On the contrary, the no smile direct eye gaze image evoked negative emotions across participants, being especially negative in terms of portraying friendliness (M = 1.6).

Table 1.

Frequency distribution, mean, and standard deviation of facial expression cognition.

	Levels of cognition (%)^a
Emotion indicators	1	2	3	4	5	Mean	SD
Smile direct eye gaze (α = .946)
Friendliness	0.0	0.0	7.0	32.6	60.5	4.5	0.6
Politeness	0.0	0.0	11.4	34.1	54.5	4.4	0.7
Comfort	0.0	0.0	15.9	27.3	56.8	4.4	0.8
Goodness	0.0	2.3	11.4	29.5	56.8	4.4	0.8
Happiness	0.0	0.0	9.1	40.9	50.0	4.4	0.7
Courtesy	0.0	0.0	11.4	40.9	47.7	4.4	0.7
Relaxation	0.0	2.3	13.6	31.8	52.3	4.3	0.8
Appropriateness	0.0	2.3	20.5	34.1	43.2	4.2	0.8
Overall SDEG						4.4	0.6
Smile indirect eye gaze (α = .975)
Friendliness	9.1	25.0	15.9	38.6	15.9	3.4	1.2
Politeness	11.4	27.3	27.3	22.7	13.6	3.0	1.2
Comfort	9.1	20.5	25.0	29.5	15.9	3.2	1.2
Goodness	6.8	11.4	36.4	27.3	15.9	3.3	1.2
Happiness	11.4	18.2	25.0	27.3	22.7	3.4	1.2
Courtesy	9.1	20.5	22.7	29.5	15.9	3.2	1.3
Relaxation	4.5	15.9	29.5	29.5	13.6	3.2	1.2
Appropriateness	13.6	25.0	20.5	27.3	13.6	3.0	1.3
Overall SIEG						3.2	1.1
No smile direct eye gaze (α = .949)
Friendliness	54.5	27.3	18.2	0.0	0.0	1.6	0.8
Politeness	52.3	27.3	15.9	4.5	0.0	1.7	0.9
Comfort	45.5	29.5	22.7	2.3	0.0	1.8	0.9
Goodness	36.4	22.7	38.6	2.3	0.0	2.1	0.9
Happiness	47.7	20.5	31.8	0.0	0.0	1.8	0.9
Courtesy	50.0	27.3	13.6	9.1	0.0	1.8	1.0
Relaxation	34.1	36.4	25.0	4.5	0.0	2.0	0.9
Appropriateness	50.0	22.7	15.9	9.1	2.3	1.9	1.1
Overall NSDEG						1.9	0.8

Measured on a five-point scale with “1” indicating the lowest score and “5” the highest score. SDEG = Smile direct eye gaze score; SIEG = Smile indirect eye gaze score; NSDEG = No smile direct eye gaze score.

The result of Mauchy’s test of sphericity was not significant, thus no corrective measures were applied. In a further test of Hypothesis 1, RM-ANOVA showed significant differences in the overall emotional perception across the three facial images and the eight individual affection indicators examined (p ≤ .001; Table 2). Post hoc paired t-tests resulted in significant differences in participants’ emotional perception across the three images. Smiling with a direct eye gaze evoked the most positive subject response while nonsmiling direct eye gaze induced the most negative affect in all eight emotions and overall emotion perception score. Smile indirect eye gaze scored significantly higher than no smile direct eye gaze, but statistically lower than smile direct eye gaze. Altogether, these results showed that smiling was conducive to positive affect. However, results suggested that smile alone was not sufficient enough to evoke positive affect as participants reported relatively neutral emotion perceptions toward smiling with indirect gaze, finding that is surprisingly taking into consideration the preponderant role that smile alone is given to elicit positive emotions.

Table 2.

A comparison of emotional cognition elicited across three facial images.

Emotion indicators	Smile direct eye gaze^a	Smile indirect eye gaze^a	No smile direct eye gaze^a	F statistic	p-value
Friendliness	4.5	3.4	1.7	137.133	< .001^b
Politeness	4.4	3.1	1.7	106.403	< .001^b
Comfort	4.4	3.2	1.8	92.799	< .001^b
Goodness	4.4	3.3	2.1	77.803	< .001^b
Happiness	4.4	3.4	1.8	91.640	< .001^b
Courtesy	4.4	3.2	1.8	95.125	< .001^b
Relaxation	4.3	3.2	2.0	81.717	< .001^b
Appropriateness	4.2	3.0	1.9	60.823	< .001^b
Overall mean	4.4	3.2	1.9	7.835	= .001^b

Measured on a five-point scale with “1” indicating the lowest score and “5” the highest score.

Post hoc Bonferroni adjusted paired t tests showed significant differences across the three images.

Cultural variations on emotion perception of facial expressions

In an examination of Hypothesis 2, independent t-tests did not yield significant differences between Chinese (M = 4.3) and American (M = 4.5) participants in their overall emotion perception of smile direct gaze expressions, nor on their specific indicators (Table 3). The high mean scores reported with this image confirmed that smiling accompanied by direct eye gaze evoked positive affect in both cultural groups without significant differences in intensity. Although American participants (M = 3.5) reported an overall higher positive perception of the smile indirect eye gaze than their Chinese counterparts (M = 3.0), such difference was not significant.

Table 3.

A comparison of emotional cognition of facial expressions between Chinese (CH) and American (US) participants.

Emotion indicators	Smile direct eye gaze^a			Smile indirect eye gaze^a				No smile direct eye gaze^a
Emotion indicators	CH	US	t	CH	US	t		CH	US	t
Friendliness	4.5	4.6	−.627	3.0	3.7	−1.974	*	1.9	1.3	2.670	**
Politeness	4.3	4.5	−.835	2.8	3.3	−1.545		2.0	1.4	2.199	**
Comfort	4.3	4.5	−.960	2.9	3.6	-1.841	*	1.9	1.8	.406
Goodness	4.3	4.6	−1.319	3.0	3.7	−2.122	**	2.1	2.0	.139
Happiness	4.3	4.5	−1.107	3.2	3.8	−1.344		1.9	1.8	.222
Courtesy	4.3	4.5	−1.043	2.9	3.5	−1.499		2.0	1.6	1.601
Relaxation	4.3	4.4	−.686	3.1	3.3	−.542		2.0	2.0	.000
Appropriateness	4.0	4.4	−1.520	2.9	3.2	−.824		2.0	1.8	.828
Overall score	4.3	4.5	−1.211	3.0	3.5	−1.566		2.0	1.7	1.105

Mean score, where “1” indicating the lowest mean score and “5” the highest mean score.

p < .05; *p < .10.

However, smiling with an indirect eye gaze did provoke more significant positive emotions on Americans than Chinese in terms of friendliness (M_US = 3.7; M_CH = 3.0; p = .055), comfort (M_US = 3.6; M_CH = 2.9; p = .073), and goodness (M_US = 3.7; M_CH = 3.0; p = .040). In addition, Chinese participants (M_CH = 2.0) appeared to be overall slightly less negative than their counterparts (M_US = 1.7) on emotional indicators associated with a nonsmiling face with direct eye gaze, although differences were only statistically significant related to friendliness (M_US = 1.3; M_CH = 1.9; p = .011) and politeness (M_US = 1.4; M_CH = 2.0; p = .033). Thus, Hypothesis 2 was not fully supported in this study.

Discussion and implications

Study results confirmed the importance of smiling as important emotional labor requirement for both Chinese and American (Li et al., 2016; Line and Runyan, 2012; Mattila and Enz, 2002; Muir, 2008); moreover, participants from both countries expressed positive emotional affect in response to a smile with direct eye contact. Study findings verify both the importance of emotional labor as a strategy to maintain and enhance service quality and the idea that enhancing the skills and knowledge of hospitality staff’ emotional displays is critical for branding, as well as for repeat business and increased profitability. These findings bring important theoretical and practical implications as detailed below.

Theoretical implications

Study findings are consistent with earlier studies (e.g. Chu et al., 2012; Johnson and Spector, 2007; Söderlund and Rosengren, 2008) that indicate that smiling elicits positive customer emotional responses to emotional labor and thus influences perceptions of service quality. Nevertheless, study findings show that for both cultural groups, smiling required also a direct gaze to evoke customers’ most positive emotions; this finding challenges the extant literature suggesting that East-Asian cultural groups (e.g. Chinese) are low-contact cultures, which tend to perceive “direct gaze” as rude (Mehrabian, 1971; Scheflen and Scheflen, 1973). Thus, study findings confirm that multiple facial features interact (e.g. smiling along with direct eye gaze) in influencing customers in interpersonal encounters (e.g. Brotheridge and Lee, 2003; Johnson and Spector, 2007; Zapf and Holz, 2006).

Results also validating prior work demonstrated that cultural groups interpret facial expressions in different ways (e.g. Engelmann and Pogosyan, 2013;Matsumoto et al., 2002, 2005). However, resulting differences between Chinese and American respondents were insufficient to establish culture as a significant driver of emotional responses to facial stimuli. Rather, results suggest that certain facial expressions (i.e. smiling in combination with direct eye gaze) meet universal psychological needs for interpersonal connection described in the literature (e.g. Ariffin and Maghzi, 2012; Chu et al., 2012; Grandey et al., 2005).

Practical implications

The present study suggests that hospitality companies can make good use of research on facial expressions in service settings to inform organizational service strategies for emotional labor. It is desirable for hospitality organizations to develop internal normative guidelines to encourage the display of smiling with direct eye contact as a universally applicable standard for hospitality emotional labor. This is especially important to implement among front-desk positions in the hospitality industry. Since our study found that the lack of a smile, particularly when accompanied by direct eye gaze, was perceived negatively by study subjects, organizations should foster emotional labor to refrain from exhibiting such facial expressions that might diminish the customer–provider connection.

Considering the role of culture in customer responses to facial expressions, the present study results support the International Labor Organization (1979)’s recommendation that universal skills requirements for the hospitality industry be drawn from the job itself without referencing the cultural setting specifically. Thus, hospitality organizations should deemphasize the importance of cultural differences in displaying facial expressions in customer service, and adopt instead an approach that encourages universal smiling features (Hochschild, 1983). An organization-wide normative standard should be established regardless of the cultural context where service interaction happens and a rewards system devised to recognize employee adherence to these emotional display rules.

Stated recommendations presume that employees will physically engage in direct contact with customers and that employees are expected to attempt to influence customer satisfaction through visible mannerisms in a face-to-face context. Thus, the source of information about employee performance must derive from the customer as well; this requires systems (e.g. using incentives) to be in place to collect customer data involving service encounters. Much customer data have been focused on satisfaction with employee behaviors in general; the present study indicates that feedback that is narrowly focused on customers’ emotional responses to specific nonverbal and verbal communication acts may be useful as well.

Generally, when encouraging employees to display certain emotions, other evaluative stakeholders including the employees themselves are not considered. Beyond incorporating emotional display into the organizational reward system, managers will want to assess existing barriers to the transfer of service standards to the actual workplace. Work on emotional labor and burnout research has shown that employees may suffer exceptional stress during customer service encounters due to loss of perceived control over interpersonal behaviors. Organizations may also want to combine the inducement of positive emotional displays (e.g. smile with direct eye gaze) with the suppression of negative emotional displays (e.g. no smile; indirect eye gaze) to foster increased professionalization and manage emotional exhaustion of service staff.

Limitations and future research

Results of this study should be interpreted with caution given three main limitations. First, although the research scenario simulated a customer symbolic interaction (a method used in similar types of linguistics experiments), the study participants’ cognitive immersion in the described situation was dependent on their individual abilities to imagine the hypothesized scenario. A second limitation refers to the adoption of a laboratory method simulating face-to-face contact between employees and customers using pictures. Although this method is suitable to control for biases presented in real life, it cannot capture the nuances and complexities occurring in actual phenomenological studies observing provider–consumer interactions. Lastly, China and the U.S. are diverse culturally within their respective geographies, thus study participants do not necessarily represent unified cultural identities from each of these regions.

Accounting for these limitations, this exploratory study has identified significant rationales for the use of facial displays in hospitality service encounters that need to be further explored. It is suggested that future studies consider replicating this study at a larger scale (sample size) and wider scope (more cultural groups) to allow greater generalizations. Future analyses might also incorporate additional information about demographic qualities of service providers and psychological profiles (e.g. customers’ mood) of respondents to assess effects on emotional perceptions. Researchers may want to explore the use of additional technologies to break down smiling and eye contact into meaningful observable units that may be manipulated further. Future studies may also consider the use of other research methodologies (e.g. immersive virtual environments, real-life scenarios) with actual service agents and customers so as to overcome bias associated with the recreation of simulated scenarios using web-based surveys and static images of stimulus faces.

Conclusion

In this study, emotional labor was studied in the form of facial expression—the display of smile and direct eye gaze—through a hypothetical hospitality scenario at a hotel front desk. This study examined perception of emotions among Chinese and American individuals through the display of different stimulus faces (smile with direct eye contact, smile with indirect eye contact, and no smile with direct eye contact) and cultural variation in assessing these faces. In doing so, study results identified scholarly and practical contributions useful to increase the performance of service encounters in the hospitality sector.

Footnotes

Acknowledgement

The authors would like to gratefully acknowledge the editor and the anonymous reviewers for their comments and suggestions on the article.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Jing Li is a doctoral candidate in the Department of Parks, Recreation and Tourism Management at North Carolina State University. Her dissertation research evaluates the performance of associations serving the tourism and hospitality sectors. Jing adopts psychosocial approaches in her studies, which integrates psychological and marketing concepts into social network analysis.

Bonnie F Canziani holds a PhD from Cornell University in Hotel Administration. Dr Canziani has worked with the hospitality and tourism industry for 30 plus years, including her current position at the University of North Carolina at Greensboro. Her teaching and research spans services management and marketing, entrepreneurship, cultural issues and global management, and wine industry strategy and marketing.

Carla Barbieri is an associate professor in Equitable and Sustainable Tourism at North Carolina State University. Her research focuses on specialized forms of tourism associated with natural and cultural resources and their impact on societal well-being. She also investigates agritourism and farm entrepreneurial diversification. Barbieri uses sustainability, sociological, and tourism approaches to frame her studies.

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