1. Introduction
To promote the well-being of teachers, it is essential to explore the factors affecting their emotional exhaustion, which is a core dimension of teacher burnout and an important indicator of well-being [1,2]. Emotional exhaustion refers to feelings of mental and emotional fatigue arising from being overloaded with work [1]. It is important for both researchers and policymakers to understand teachers’ emotions as both individual and sociocultural experiences [3]. Therefore, it is necessary to explore how personal psychological factors and sociocultural factors affect teachers’ well-being. Scholars have found that job burnout was influenced by job factors (e.g., social support, work-family conflict) and personal factors (e.g., emotional labor, self-esteem) [4,5,6,7]. The cultural context (e.g., cultural values) might also impact the straining process [8].
Because teachers are required to conduct a lot of emotional labor during their work, emotional labor strategies are one of the most significant personal influencing factors of teachers’ emotional exhaustion [2,9,10]. Emotional labor was defined as “the management of feeling to create a publicly observable facial and bodily display” by Hochschild [11]. Some studies have confirmed that there are three emotional labor strategies used while working: deep acting (DA), surface acting (SA), and the expression of naturally felt emotions (ENFE) [10,11]. SA occurs when employees’ fake unfelt emotional states, or hide felt feelings without any change in inner feelings. DA involves modifying internal emotions to actually experience the required emotion. In ENFE, individuals display expected emotions as they feel them [12]. In other words, SA is the regulation of expression, involving noninternalized behaviors, and DA is the regulation of feelings with a higher internalization level [9,13]. ENFE is the expression of genuine emotion with the highest internalization level, viewed as “automatic emotion regulation” [14,15].
Previous studies showed that Chinese teachers also used these three emotional labor strategies (i.e., SA, DA, and ENFE) [2,16,17,18]. Considering the influence of Chinese culture on the emotion regulation of teachers, Yin summarized the emotional labor strategies of Chinese teachers through qualitative analysis; he found that Chinese teachers also used three categories of emotional labor strategies, namely, surface acting, deep acting, and genuinely expressing, which could be divided into seven strategies [19]. In this research, it was found that due to the high-power distance between teachers and students, Chinese teachers have more space to use their negative emotions. For example, they can use SA or genuinely express their negative emotions to maintain a professional and authoritative image, and improve teaching efficiency. According to the results of the questionnaire survey on Chinese teachers, it was found that ENFE was used more than DA and SA, with students as the main interaction partner, or a lack of a classification of partners [17]. In addition, in the Chinese sample, research has also demonstrated the influence of different emotional labor strategies on teachers’ emotional exhaustion, which has also been proved to be the core component of Chinese teacher burnout [17,18,20]. Although previous studies have explored teachers’ emotional labor, and its relationship with emotional exhaustion in the context of Chinese culture [15,16], it remains ambiguous as to how Chinese culture affects Chinese teachers’ emotional labor and emotional exhaustion, due to the complexity of culture.
Using emotion regulation theory as a guide, in 2000 Grandey proposed an integrated framework to understand the mechanism of emotional labor [21]. Grandey’s (2000) model of emotional labor can reveal the long-term consequences of emotional labor (i.e., its effects on the well-being of individuals and organizations), as well as the antecedents of emotional labor (i.e., SA and DA), including situational cues (i.e., interaction expectations and emotional events); individual factors (e.g., gender and emotional intelligence); and organizational factors (e.g., job autonomy and supervisor support) [21]. This 2000 model does not, however, consider the effect of cultural factors. Grandey and Melloy revised the model in 2017, with the major model revisions included the following [22]: First, the revised model expands emotional labor strategies, not only focusing on SA and DA. Second, it takes into account felt emotions and dynamic temporal variations of emotion regulation. Third, the 2017 model shows that a good–bad dichotomy should not be used for SA and DA. Fourth, the 2017 model supplements the recent findings regarding situational cues, consequences, individual factors, and organizational factors. For instance, interaction expectations and work context are represented as work context level factors that influence the emotional labor and outcomes, and relational characteristics are added to interaction expectations.
It should be noted that in the 2017 model, Grandey and Melloy considered the influence of cultural values. For example, the association between emotional labor and job burnout in the Chinese context (i.e., a collectivist culture) was found to be different from that in the US context (i.e., individualist culture) [23]. These cross-cultural studies compared groups from different cultures or countries to explore the effects of culture (i.e., national paradigm); Grandey’s model, meanwhile, pays more attention to the moderating role of culture between emotional labor and outcomes, and between emotional events and emotional labor [24]. The model remains unclear regarding the antecedent influences of culture on emotional labor, and their role in promoting well-being. Given the heterogeneity that exists among the members of a nation, a cultural paradigm that uses “cultural values” as the independent variable can help us to better understand cultural effects [25,26]. Therefore, although the measurement of cultural values is at the individual level [22], the influence of cultural values can still reflect the role of culture [25,26,27]. The antecedents of emotional labor and well-being among teachers mainly focus on individual differences (e.g., personality) and contextual work factors (e.g., school climate); yet, there are few empirical studies that examine the influence of cultural values as antecedent factors [27,28]. Moreover, previous studies mostly compared individualist/collectivist or western/eastern cultures when exploring cultural effects on emotional labor, but rarely included other dimensions of cultural values, such as power distance [23,24].
Earlier studies have suggested that emotional labor is associated with power relations [29] because power relations “influence what can, cannot or must be said (and done) about one’s self and body” [3]. Against the background of Confucian culture, which emphasizes social order, interpersonal emotions in workplaces are greatly influenced by power distance (PD), which is generally recognized as a typical characteristic of Chinese culture [30]. PD is a cultural value that reflects whether the less powerful members of institutions can accept the unequal distribution of power [31]. The present study examined the cultural effect in Grandey’s model by exploring the effect of PD on emotional labor and exhaustion.
Moreover, the power relations between teachers and various interactive partners (e.g., students, parents, and colleagues/leaders) are different. Thus, teachers’ emotional labor might be influenced by the type of interactive partner [17]. However, few quantitative studies have explored teachers’ emotional labor strategies with different interactive partners, and even fewer have considered the effects of national culture on emotional labor and exhaustion. This study addressed this gap by examining how PD and emotional labor affected exhaustion among Chinese teachers, with special attention paid to the mediating role of emotional labor with different interactive partners.
According to Grandey’s model, power is an important relational characteristic as a situational factor affecting the emotion-regulation process. Examining the emotional labor of different interaction partners may help us to understand the influence of power relations on emotional labor. Meanwhile, exploring the influence of cultural values related to power (such as PD) on emotional labor and emotional exhaustion, will also be valuable for better understanding teachers’ emotions from the perspective of power, and exploring the antecedent influence of culture in Grandey’s model.
In short, an investigation of the influence of interactive partners on emotional labor and the relationships between PD, emotional labor, and exhaustion is helpful to understand the characteristics of Chinese teachers’ emotional work under the culture of great respect for teachers. The results can help us to develop an intervention program for Chinese teachers’ well-being, under the Chinese cultural background.
The current study aimed to answer three questions: firstly, does the type of interactive partner influence the use of teachers’ emotional labor strategies? Secondly, does power distance influence Chinese teachers’ emotional labor and well-being (i.e., emotional exhaustion)? Lastly, does the emotional labor mediate the relationship between power distance and emotional exhaustion?
2. Literature Review
2.1. Emotional Labor and Emotional Exhaustion
Many researchers have confirmed the significant correlation between teachers’ emotional labor and emotional exhaustion. Grandey’s (2000, 2017) model shows that different emotional labor strategies (e.g., SA and DA) have different effects on job burnout as consequences [21,22].
In SA, individuals suppress inner emotions and express fake emotions, which requires a lot of physiological effort, thus resulting in higher stress than other strategies [21,32]. Evidence has shown that SA is robustly and positively related to emotional exhaustion [17,33,34,35]. By contrast, ENFE, which is effortless, has been found to be negatively related to exhaustion [9,34,36]. However, the findings regarding the relationship between DA and teachers’ emotional exhaustion are more complex than for SA. DA also expends energy compared to no regulation, but it can also lead to positive outcomes to gain resources, such as authenticity, and rewarding feedback [37,38,39]. Thus, as Grandey concluded in the 2017 model, DA had a weaker relationship (both negative and positive) with emotional exhaustion than SA [10,22,38]. Owing to DA’s acquisition and consumption of resources at the same time, the relationship between DA and emotional exhaustion is unstable and weak [22,38]. DA has even been found to not be significantly correlated with teachers’ emotional exhaustion [18,40]. According to Grandey’s model (2017), the beneficial or harmful relationship between emotional labor (i.e., SA and DA) and consequences, may be different in various interpersonal and professional work contexts. A meta-analysis suggested that cultural background might influence the relationship between DA and teachers’ well-being: in the samples of eastern subjects, DA showed a positive relationship with well-being, while in the samples of western subjects, DA showed a negative relationship with well-being [28]. Different indicators of well-being may also have different findings. For example, DA may be positively correlated with both emotional exhaustion and job satisfaction [22]; therefore, the discussion on the relationship between Chinese teachers’ emotional labor and emotional exhaustion may enrich the evidence in this field. Based on the abovementioned findings, we hypothesized that:
SA is strongly positively correlated with emotional exhaustion.
ENFE is negatively correlated with emotional exhaustion.
There is a weaker positive correlation between DA and emotional exhaustion than SA.
2.2. Effect of Power Distance
Some studies have supported the premise that teachers’ emotions have both an individual and sociocultural basis [3,29]. Accordingly, emotional labor strategies and display rules are influenced by cultural contexts, according to the theoretical model of Grandey [22]. Yin (2016) examined the influence of Chinese culture on teachers’ emotional regulation, especially the role of social order in traditional Confucian culture [19]. There is a long tradition in China in which people place considerable emphasis on education and respect for teachers. This is evident in well-known sayings such as: “He who teaches me for one day is my father for life” (Taigongjiajiao); “If a state is to flourish, its teachers must be honored” (Xunzi); and “All enlightened rulers honor teachers and respect rules” (The History of the Later Han Dynasty). Therefore, teachers in China tend to have a high social status and authority, in relation to students and even parents. This allows them to genuinely express their emotions or use SA to maintain a mysterious or even threatening image before students, as well as a “hierarchical but friendly” teacher–student relationship [19].
The influence of the wider social context, especially power relations, is central to emotional labor [29]. Lower-level employees are required to follow emotional rules formulated by management, reflecting a power imbalance with regard to emotions [11,29]. Due to the emphasis of Confucian culture on obedience to social hierarchy, Chinese culture is considered to be characterized by a relatively high PD [30,41]. As a part of national cultural value, PD is “the degree to which the less powerful members of a society accept and expect that power is distributed unequally” [42]. Teachers with a high-power distance expect an unequal distribution of power at schools, as well as accepting and maintaining hierarchies [43]. Chinese teachers with a high-power distance and high social status, tend to maintain an authoritative image in front of students, and maintain a high-power status of teachers [19,44]. They usually do not allow students to violate the rules made by teachers [45]. When faced with individuals with a higher power, such as school administrators, they may usually follow the instructions of the administrators instead of expressing their differing opinions. Some researchers have suggested that the features of Chinese emotional responses, such as their lower frequency, intensity, and duration, can be interpreted using the construct of PD [46]. Expressions of emotion by Chinese teachers tend to be restrained, and carefully regulated, to maintain interpersonal harmony and status hierarchies [44,47,48]. However, how PD affects Chinese teachers’ emotional labor has not been fully explored. One comparative study found that cultures that emphasize maintaining social order tended to have higher scores for suppression (i.e., SA), and PD tended to be positively related to suppression and non-significantly correlated with reappraisal (i.e., DA) [49]. In cultures that emphasize social order, the suppression of emotion may be necessary. However, the aforementioned study used country-level data, ignoring the differences that might exist in a highly diverse culture. The only study to directly explore the relationship between PD and emotional labor at the individual level found that in meetings in the western context, PD was positively related to the SA and DA of meeting attendees [50]. Additionally, the relationship between PD and ENFE is not well-studied.
In settings with considerable PD, people tend to consider the manner of emotional response that will best preserve social order [50]. Therefore, they tend to engage in more SA and DA, with less ENFE, since expressing inner emotions is not conducive to maintaining social order in the workplace. They will be more cautious with regard to expressing genuine emotions. Thus, we propose the following:
Chinese teachers with greater power distance use more SA and DA strategies and less ENFE.
PD’s influence on emotions in the workplace is reflected in its influence not only on emotional labor, but also on job burnout. Farzianpour and colleagues found a positive and significant correlation between PD and burnout, and they also found that the PD variable was more important than other cultural variables (i.e., masculinity/femininity, individualism/pluralism, the avoidance of ambiguity) for anticipating change in job burnout [51]. A qualitative study of manufacturing and banking employees in Nigeria found that a high-power distance culture exacerbated stress by discouraging employees from challenging employers on issues relating to stressors at work, such as unconducive work environments [52]. According to the relationship between emotional labor, emotional exhaustion, and PD in previous findings, the PD of Chinese teachers may affect emotional exhaustion through emotional labor. In Grandey’s model, more attention is paid to the relationship between emotional labor and employee strain, as well as the influence of individual and context variables, such as cultural values on this relationship; however, less attention is paid to the relationship between cultural values and employee strain, and the mediating role of emotional labor [22]. Although previous studies have attempted to explore the mediating role of emotional labor between factors and emotional exhaustion [33,53,54], there are still a few studies on cultural factors as an antecedent [55], especially the mediating role of emotional labor between PD and emotional exhaustion. Considering the relationships between emotional labor, PD, and emotional exhaustion, we hypothesize that:
Power distance is positively correlated with emotional exhaustion.
Emotional labor (SA, DA, and ENFE) mediates the relationship between power distance and emotional exhaustion.
2.3. Emotional Labor with Different Interactive Partners
Grandey’s revised model notes the influence of relational characteristics on emotional labor as a type of situational cue [22]. Power is an important relational characteristic. Different interactive partners will reflect different power relations, and changes in power relations produce changes in emotional expressions and ideas [56]. However, little is known about the influence of interactive partners on teachers’ emotional labor strategies, especially in the culture of China.
Schools are “complex emotional arenas” in which teachers must deal with the emotional demands of different interactive partners [44]. Chinese teachers perform emotional labor with three main types of partners: students, parents, as well as colleagues and leaders [17,20]. Under the influence of traditional Confucian culture, Chinese teachers traditionally enjoy a relatively high social status. Thus, Chinese teachers are in a powerful position in relation to students, and parents also traditionally treat teachers with respect. Meanwhile, with the influence of marketization, some teachers are starting to view parents as “customers” to be served. Compared with students, the teachers’ power advantage relative to parents tends to be less obvious [57]. Thus, for Chinese teachers, their power and authority decrease when interacting with parents, and further when interacting with colleagues/leaders, compared to when they are interacting with students.
Past research has suggested that power is related to a reduced tendency to comprehend how other people see, think, and feel [58]. That is, having high-power leads to insufficient adjustment to others’ perspectives, while having low-power can lead to adopting another person’s perspective. Overbeck et al. found that powerful negotiators responded to their own emotional states and not to those of counterparts, while low-power negotiators did not respond to their own emotions, but were influenced by those of high-power counterparts [59]. In short, high-power individuals will act based on their own will, reflecting an intrapersonal process, whereas low-power individuals are more reactive, reflecting an interpersonal process [60]. Consequently, with increases in the power of interactive partners, teachers will use less ENFE with a high internalization level and more SA, which is alienating to one’s sense of self. When facing students, because teachers are in a more powerful position, they may take less account of students’ feelings, while acting according to their own will, so as to often express genuine emotion. However, if teachers are faced with parents and leaders with higher power, they may need to consider the feelings of partners to a greater extent, thus reducing genuine expression and making them more likely to engage in emotional regulation, such as SA and DA. We therefore propose the following hypotheses:
When interacting with three type of interactive partners, Chinese teachers used SA and DA the most with colleagues and leaders and the least with students.
When interacting with three type of interactive partners, Chinese teachers used ENFE the most with students and the least with colleagues and leaders.
Using Grandey’s model to explore the effects of cultural and social factors, we aimed to examine the effect of interactive partners on the emotional labor of Chinese teachers, and identify the influence of emotional labor and PD on exhaustion by focusing on the mediating role of emotional labor strategies.
3. Materials and Methods
3.1. Participants
The participants consisted of 3312 Chinese teachers working in elementary and secondary schools in Beijing, China. The age groups of these teachers are as follows: under 25 (6.6%), 26–30 (12%), 31–40 (30.8%), 41–50 (40%), and 51–60 (10.6%). Overall, 81.9% of these teachers were female. Moreover, 54.4% of the teachers taught in primary schools, 30.2% in middle schools, and 15.5% in high schools. The years of teaching experience ranged from 0 (new teachers) to 39 years (M = 17.29, SD = 10.04), and there are 63 (1.9%) instances of missing data.
When teachers participated in the teacher training programs of the local education authorities, we distributed online questionnaires to them by sending a Survey Star link in November 2020. It took approximately 5–10 min to complete the questionnaire. In the guidance part of the questionnaire, we explained the purpose of the research and assured participants that the data would only be available to the research team and would be for research use only. The data were collected anonymously. All of the participants volunteered and could cease participation at any time.
3.2. Measures
3.2.1. Emotional Labor Strategies
We assessed three emotional labor strategies using the Questionnaire on Emotional Labor (QEL) developed by Diefendorff, Croyle, and Gosserand in 2005 [61]: (1) SA (seven items), (2) DA (four items), and (3) ENFE (three items). Participants answered each item via a five-point Likert scale (1 = strongly disagree, 5 = strongly agree). To measure emotional labor strategies with different interactive partners, “customers” in the original questionnaire was replaced with teachers’ interactive partners (i.e., students, parents, as well as colleagues and leaders). Cronbach’s alpha coefficients were found to be 0.86–0.94 for SA of three interactive partners, 0.80–0.83 for DA, and 0.91–0.94 for ENFE.
3.2.2. Emotional Exhaustion
We assessed teachers’ emotional exhaustion using the subscale from a Chinese version of the Maslach Burnout Inventory for Educators [62]. This scale consists of eight five-point Likert-type items. Cronbach’s alpha coefficient was 0.96.
3.2.3. Power Distance
The PD subscale of the CVSCALE scale was developed by Yoo, Donthu, and Lenartowicz [31]. It measures Hofstede’s cultural values at the individual level. This subscale consists of five five-point Likert-type items. Cronbach’s alpha coefficient was 0.91.
3.2.4. Data Analysis
Data analysis included two procedures. First, the results of the reliability test, descriptive statistics, ANOVA, and correlation analysis were obtained using SPSS 18.0 (IBM, Chicago, IL, USA). Second, structural equation modeling with latent variables was used to analyze the mediation effects using Mplus 8.0 (Muthén & Muthén, Los Angeles, CA, USA). Listwise deletion was used to handle the missing data. Bootstrapping was used to examine the direct and indirect effects [63]. Following previous studies [64,65], a series of indicators were used to evaluate model fit: RMSEA < 0.08, SRMR < 0.10, CFI > 0.90, and TLI > 0.90.
4. Results
4.1. Common Method Bias Testing
Because all variables in this study were measured by a self-reported questionnaire, Harman’s single-factor test was used to avoid common method bias [66]. We put all the items for each variable into a factor analysis. The result showed that the first factor explained 25.13% of the variance, below 40%, demonstrating that there was no serious common method bias problem in this research.
4.2. Descriptive Statistics
Table 1 presents the means, standard deviation, and correlations between variables. These results were prepared for mediation analysis. As expected, PD was positively related to emotional exhaustion (EE) and SA for the three interactive partners, and negatively correlated with ENFE for the three interactive partners. Meanwhile, there was no significant correlation between PD and DA. Additionally, EE was positively related to DA and SA and negatively associated with ENFE. These results preliminarily supported H1, H2, and H3.
Gender was found to be positively related to PD and negatively related to EE. Additionally, years of teaching experience were positively associated with ENFE and EE, and negatively associated with SA. Since gender and years of teaching experience were significantly correlated with some core variables, they were included in the mediated model as control variables for subsequent analysis [22,67].
4.3. Effect of Interactive Partners and Power Distance
We used the PD scores to group teachers. The 30th and 70th percentile were selected for subgrouping teachers with small and large PD. A total of 1002 teachers met the large PD criteria, with scores above the 70th percentile; 1074 met the small PD criteria, with scores below the 30th percentile.
We conducted a 3 (interactive partners: students, parents, and colleagues and leaders) × 3 (emotional labor strategies: SA, DA, and ENFE) × 2 (PD: large, small) repeated-measures ANOVA on scores of the emotional labor strategies. The categories of interactive partners and emotional labor strategies were the within-subject variables, and the PD group was the between-subjects variable. There were significant main effects for interactive partners (F (2, 2073) = 87.551, p < 0.01, ƞ2 = 0.078) and emotional labor strategies (F (2, 2073) = 1072.022, p < 0.01, ƞ2 = 0.508), a significant three-way interaction of all factors (F (4, 2071) = 11.839, p < 0.01, ƞ2 = 0.022), and significant two-way interactions between emotional labor strategies and PD (F (2, 2073) = 22.234, p < 0.01, ƞ2 = 0.177), and interactive partners and PD (F (2, 2073) = 3.347, p < 0.05, ƞ2 = 0.003), as well as interactive partners and emotional labor strategies (F (4, 2071) = 86.729, p < 0.01, ƞ2 = 0.143). The main effect of PD was not significant (F (1, 2074) = 3.435, p = 0.064, ƞ2 = 0.002).
For the interaction of interactive partners and emotional labor strategies, the simple effect analysis revealed significant interactive partner effects for all of the emotional labor strategies (see Figure 1; SA: F (2, 2073) = 97.121, p < 0.01, ƞ2 = 0.086; DA: F (2, 2073) = 106.608, p < 0.01, ƞ2 = 0.093; ENFE: F (1, 76) = 88.050, p < 0.01, ƞ2 = 0.078). Specifically, the mean SA scores showed the following relations: students < colleagues and leaders < parents (students: M = 2.683, SD = 0.019; parents: M = 2.878, SD = 0.020; colleagues and leaders: M = 2.746, SD = 0.021; all pairwise comparisons were significant, p < 0.01). The mean ENFE scores showed the following relations: colleagues and leaders < parents < students (students: M = 3.988, SD = 0.018; parents: M = 3.827, SD = 0.018; colleagues and leaders: M = 3.780, SD = 0.018; all pairwise comparisons were significant, p < 0.01). The mean DA scores for both students and parents were significantly higher than for colleagues/leaders (p < 0.01), while there was no significant difference between students and parents (students: M = 3.677, SD = 0.018; parents: M = 3.660, SD = 0.017; colleagues and leaders: M = 3.458, SD = 0.018). Most of the results supported H5.
The simple effect analysis also revealed significant effects of emotional labor strategies for all of the interactive partners (see Figure 1; SA: F (2, 2073) = 1255.12, p < 0.01, ƞ2 = 0.55; DA: F (2, 2073) = 70.94, p < 0.01, ƞ2 = 0.40; ENFE: F (1, 76) = 646.21, p < 0.01, ƞ2 = 0.38). For all of the interactive partners, SA scores were significantly lower than DA and ENFE, and DA was significantly lower than ENFE (p < 0.01).
For the triple interaction effect, further simple effect analyses demonstrated that PD effects were significant for all of the emotional labor strategies. The mean SA scores of the small PD group were lower than for the large PD group for all of the interactive partners. The mean DA and ENFE scores of the small PD group were higher than for the large PD group for all of the interactive partners (see Table 2). The simple effect analyses also revealed that the SA scores of parents were significantly higher than for students and colleagues and leaders in the small PD group (p < 0.01), while colleagues and leaders’ scores increased greatly in the large PD group; thus, there was no significant difference between parents and colleagues and leaders. Meanwhile, ENFE for colleagues and leaders decreased faster than for students and parents in the large PD group (Figure 2 and Table 2).
4.4. Measurement Model
The measurement model included five latent factors (PD, SA, DA, ENFE, EE) and 27 observed variables. Considering that we investigated emotional labor for three interactive partners, we used three measurement models. The fit indices showed a good model fit (see Table 3). The factor loadings of the 27 indicators on the latent variables were significant (p < 0.01), revealing that all of the latent variables were well represented by their respective indicators. We also compared one-factor, two-factor, three-factor, and four-factor models to test the discriminant validity of our core variables (see Table 3). These results show that the five-factor model (PD, SA, DA, ENFE, EE) fit the data better.
4.5. Hypothesis Testing
The three structural models were tested for different interactive partners. In the hypothesized models, emotional labor strategies (i.e., SA, DA, ENFE) mediated the relationship between PD and EE after controlling for gender and years of teaching experience (Figure 1). Based on the results of correlation analysis, we only controlled the effect of gender on PD and EE, as well as the effect of years of teaching experience on SA, ENFE, and EE (p < 0.01).
The fit indices were satisfactory (students: χ2 = 5180.23, df = 363, RMSEA = 0.064, TLI = 0.92, SRMR = 0.06, CFI = 0.93; parents: χ2 = 5769.26, df = 363, RMSEA = 0.068, TLI = 0.92, SRMR = 0.06, CFI = 0.93; colleagues and leaders: χ2 = 5962.01, df = 363, RMSEA = 0.069, TLI = 0.92, SRMR = 0.06, CFI = 0.93). For students and parents, the standardized path coefficients from PD to DA, and from ENFE to EE, were nonsignificant. Additionally, the path coefficient from DA to EE in the parents’ model was marginally significant (p = 0.058). All of the other path coefficients in the students and parents’ models were significant (Figure 3). PD negatively predicted ENFE (students: β = −0.14, p < 0.001; parents: β = −0.11, p < 0.001), while it positively predicted SA (students: β = 0.35, p < 0.001; parents: β = 0.34, p < 0.001) and EE (students: β = 0.05, p < 0.05; parents: β = 0.04, p < 0.05). SA and DA positively predicted EE (SA-students: β = 0.25, p < 0.001; SA-parents: β = 0.26, p < 0.001; DA-students: β = 0.05, p < 0.05; DA-parents: β = 0.05, p = 0.058). For colleagues and leaders, PD negatively predicted ENFE (β = −0.13, p < 0.001), while it positively predicted SA (β = 0.42, p < 0.001). Only SA had significant positive effects on EE (β = 0.26, p < 0.001). Most of the results support H1a, H2, and H3, except for the results for the relationships between DA and PD.
Bootstrapping was used to examine the mediation effects [63]; 5000 bootstrapping samples were generated. The indirect effects of PD on EE via SA were significant and positive in all three models (see Table 4), supporting H4. The indirect effect in the model of colleagues and leaders was greater than that in the other models. According to the different patterns of mediation proposed by Zhao et al. [68], there was a complementary mediation of SA between PD and EE in the models for students and parents, and there was an indirect-only mediation in the models for colleagues and leaders.
5. Discussion
Most of the research on teachers’ emotional labor has focused on individual and organizational factors, while largely ignoring power relations and the role of culture. We expanded Grandey’s model to include PD as a cultural factor and explored the influence of interactive partners on emotional labor strategies, which reflect relational characteristics (i.e., power). We tried to obtain better insights into the possible relationships between PD, emotional labor strategies, and EE, focusing especially on the mediating role of emotional labor among Chinese teachers. The findings largely support the hypotheses, except with regard to emotional labor strategies with parents, as well as the relationships between DA and PD, and between ENFE and EE. Our findings are valuable for understanding teachers’ emotions from the perspective of power, and for exploring the antecedent roles of culture in Grandey’s model.
5.1. Emotional Labor with Different Interactive Partners
The results of this study demonstrated that SA had a strong positive effect on emotional exhaustion regardless of the interaction partner, while ENFE did not have a significant effect. Moreover, DA only had a significant and small positive effect on EE when interacting with students, but had no significant effect on EE when interacting with parents and colleagues and leaders, showing a weak and unstable relationship between DA and EE. The research results of SA and DA are mostly consistent with previous findings in various cultural contexts [17,20,33,34]. Surprisingly, an insignificant effect of ENFE on EE was found in the model that controlled for other variables. The reason for this may be that the ENFE of Chinese teachers contains not only the release of positive emotions, but also the outpouring of negative emotions [19]. Previous studies have found that genuinely expressing negative emotions might hurt well-being [28]. Therefore, if ENFE is a variable mixed with positive and negative emotions, its relationship with EE is likely to be not significant [28].
We found that regardless of who the interactive partner was, ENFE was the most-used strategy by Chinese teachers, followed by DA and finally SA. The findings are consistent with earlier research, reflecting the high social status and power of Chinese teachers, who are characterized by more authentic expression and less emotional masking [2,19]. The results also support the hypothesis that the emotional labor strategies of Chinese teachers are influenced by the type of interactive partner. We found that Chinese teachers used SA the most with parents and the least with students; they used ENFE the most with students and the least with colleagues and leaders. The findings are mostly in accordance with previous studies, which found that the greater the power, the more genuine the emotion [59,60]. Compared with other interactive partners, students have the least power relative to teachers, and were therefore associated with the least SA and the most ENFE. It was also not surprising that there was less ENFE in relation to more powerful colleagues and leaders.
We found, however, that the results for parents did not align with expectation and involved more SA than with colleagues/leaders. This suggests that the power relationship with parents might be uncertain, as Hargreaves noted [69]. Although Chinese teachers traditionally have a higher power status relative to parents, parents’ opinions and complaints are receiving more attention in the context of modernization, especially in large cities, such that many teachers might believe they occupy an inferior position during interactions with parents [57]. Given this situation, it is possible that Chinese parents already have more power than we might think. At the same time, previous studies have found that when power is involved, interactions with parents often cause negative emotions, such that teachers sometimes try to avoid, reduce, or manage these interactions by inducing or suppressing feelings (i.e., emotional labor) [70]. Using Hargreaves’s theory of emotional geographies, qualitative research on teachers in Taiwan found that teachers frequently used emotional masking to smooth tensions with parents and enlarge the teacher–parent political distance, which reflects a power relationship [70]. Given the complex relationship between parents and teachers, the finding that teachers used more SA with parents warrants further attention, especially from the perspective of power.
We also found that Chinese teachers used more DA when working with students and parents. This could be related to professional and ethical norms among Chinese teachers. Influenced by traditional Confucian culture, Chinese teachers put a great deal of emphasis on regulating emotions according to established norms [47,57]. Clear ethical norms exist with regard to emotional interaction with both students and parents, thus compelling teachers to conduct more DA with them.
The findings also show that teachers with larger PD had more SA, and less DA and ENFE, no matter the kind of interaction partners they faced. Meanwhile, ENFE for colleagues and leaders decreased faster than for students and parents, and SA for colleagues and leaders increased greatly in the large PD group. This result implies that these differences between interactive partners may be related to power, which also reveals the cultural effects of PD. Of course, we should also note that power may not be the only factor explaining these differences in interactive objects, such as the influence of ethics. Yin found that Chinese teachers internalized the ethics of teaching, such as caring for students, so they spontaneously conducted the emotional labor of care [19]. This may also be an explanation for having more ENFE for the students. However, power is undoubtedly a very important perspective, which is also proved by the effect of PD.
5.2. Effect of Power Distance
Studies have found that cultural values have a moderating effect on employees’ well-being and emotion regulation [22,71]. However, most studies used a national paradigm, ignoring the complexity of cultures. By exploring the influence of PD on emotional labor and exhaustion, this study’s findings provide evidence in support of the cultural effect in Grandey’s theoretical model.
Our findings indicated that PD positively predicted SA and negatively predicted ENFE, in line with previous research [48,49,50,51]. In the context of Chinese culture, which emphasizes social order, teachers with large PD might be more cautious about ENFE for fear of disrupting the social hierarchy. At the same time, more SA is used to display the emotions that preserve social order. In other words, the greater the PD, the more fake the emotions. Further, when interacting with colleagues and leaders, PD had a greater positive effect on SA. This supported H2, except for the uncorrelated relationship between PD and DA. This is not surprising, however, since DA involves both genuine emotions and changes in inner emotional states [61]. Given the complexity of DA, the results for DA in previous studies have also been mixed [28]. Our findings imply that although Chinese teachers will perform more emotional labor under the influence of high PD, they will not change their inner emotions, but just hide or fake them.
Moreover, the results of the multiple mediation models reveal a complementary mediation of SA between PD and exhaustion, in the models for students and parents. Further, there was an indirect-only mediation in the models for colleagues and leaders. Such mediation might help to explain the underlying sociocultural-psychological mechanism of the development of job burnout. We found that PD had positive effects on EE, either through direct or indirect effects. Although previous studies have reported the positive role of PD in relation to burnout, there is no clear explanation for this result [51]. The present study explained the role of culture through emotion pathways, indicating that Chinese teachers with large PD used more SA, which expends a lot of energy, eventually leading to more EE. We elucidated the mechanisms underlying the effect of culture on emotional labor and exhaustion by introducing PD into Grandey’s model, and provided evidence that schools should pay more attention to teachers’ emotional labor strategies and cultural values, to reduce their exhaustion.
It is worth noting that the verification of cultural effects in Grandey’s model in this study suggests that it is important for us to pay attention to emotional labor and its influence on well-being under different cultures. Hobfoll et al. pointed out that “the major rules governing how we respond to stress are embedded within shared cultural beliefs” [72]. We did find cross-cultural consistency in some results, such as the relationships between SA, DA, PD and EE, and the relationship between PD and SA. These results are coincident with those in previous studies of different cultures [17,20,33,34,50]. Although the rules of the stress–strain process may be similar in different cultures—for example, the type of interactive partners, emotional labor strategies and cultural values will all have impacts on teachers’ well-being—the factors affecting the process and their importance may be different [8,72]. For instance, there was no significant correlation between ENFE and EE in this study, which might be related to the fact that ENFE of Chinese teachers involved both positive and negative emotions.
At the same time, under the influence of traditional Confucian culture, Chinese teachers traditionally enjoy a relatively high social status and are granted a high degree of authority. Some studies also found that Chinese teachers, influenced by the culture of great respect for teachers, had different characteristics of emotional labor from other cultures [19,44]. Furthermore, in the context of Chinese culture, the power relations between teachers and various interactive partners may be different from those in other countries [57]. This may lead to the difference between Chinese teachers’ emotional labor strategies and those of other cultures, when facing different interacting partners. Therefore, investigating the emotional labor strategies used by Chinese teachers with different interaction partners may be helpful in explaining emotional labor in Chinese culture.
In conclusion, on the one hand, this study supports Grandey’s model in the context of Chinese culture; meanwhile, it also shows the influence of culture on emotional labor and its consequences, which further enriches Grandey’s model in the context of Chinese culture, and provides some results that may have cultural significance. This may indicate that the emotional labor framework reflected by Grandey’s model has cross-cultural consistency, but the influence of cultural background still needs to be considered for some specific variable relations, and more abundant cultural samples are needed.
5.3. Limitations and Future Research
First, the conclusions provided in the present study are based on correlational relationships. In future research, a longitudinal design can establish more solid evidence for causal relationships. A second limitation is that we did not actually assess the power levels of different interactive partners. Furthermore, this study did not distinguish between colleagues and leaders, because some studies have suggested that teachers shorten political distances by creating communities where they work together as equals [73]. Accordingly, it is necessary to exercise caution when explaining the effects of interactive partners with regard to power. Future research can use empirical methods to verify the effect of power on emotional labor.
6. Conclusions
The results reveal that the relationship between PD and teachers’ EE is mediated by emotional labor. The findings also indicate that the cultural factor can be an antecedent for Chinese teachers’ emotional labor, which is also influenced by the type of interactive partner. Specifically, Chinese teachers used SA the most with parents and the least with students; they used ENFE the most with students and the least with colleagues and leaders. These differences were more salient in teachers with large PD, indicating that these differences may be related to power. The greater the relative power of teachers, the more ENFE they used. In addition, PD negatively influenced ENFE and positively influenced EE and SA. Only SA mediated the relationship between PD and exhaustion. That is to say, the greater the PD, the more fake the teachers’ emotions.
The results provide an interesting take on our understanding of the sociocultural effects of emotional labor, further supporting and enriching Grandey’s model in the Chinese context. The results also suggest that we should consider the roles of personal psychological factors (i.e., emotional labor), social factors (i.e., interactive partners), and national culture (i.e., PD) in promoting teachers’ well-being. This study has the following practical implications for enhancing teachers’ well-being: First, training and interventions for teachers should focus on understanding emotional labor strategies and how to manage emotions wisely, using less SA. Second, school principals should try to reduce PD by fostering a sense of equality among teachers. Third, policymakers and schools should pay attention to teachers’ emotional labor when faced with different interaction partners, especially when interacting with parents and colleagues.
Conceptualization, X.Z. and G.T.; methodology, G.T., X.Z., and Z.L.; formal analysis, X.Z. and G.T.; investigation, X.Z., G.T. and Z.L.; data curation, X.Z. and G.T.; writing—original draft preparation, X.Z., G.T. and Z.L.; writing—review and editing, G.T.; funding acquisition, X.Z. and G.T. All authors have read and agreed to the published version of the manuscript.
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Research Ethics Committee of the School of Education of Capital Normal University in 15 September 2020.
Informed consent was obtained from all subjects involved in the study.
The data presented in this study are available on request from corresponding author. The data are not publicly available due to confidentiality and research ethics.
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Enlarge this image.Figure 2. Interaction of interactive objects, PD, and emotional labor strategies.
Enlarge this image.Figure 3. Relationships between power distance, emotional labor, and emotional exhaustion (solid lines indicate significant paths; dotted lines indicate the insignificant paths). Note: * p < 0.05; *** p < 0.001; Years: years of teaching experience.
Means (M), standard deviations (SD) and correlations.
| PD | EE | SA-S | DA-S | ENFE-S | SA-P | DA-P | ENFE-P | SA-C | DA-C | ENFE-C | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| PD | 1 | 0.12 *** | 0.3 *** | 0.01 | −0.12 *** | 0.3 *** | −0.02 | −0.1 *** | 0.37 *** | 0.02 | −0.13 *** |
| EE | 0.12 *** | 1 | 0.24 *** | 0.11 *** | −0.04 * | 0.25 *** | 0.12 *** | −0.06 *** | 0.25 *** | 0.09 *** | −0.05 ** |
| Gender | 0.16 ** | −0.06 ** | 0.03 | −0.01 | −0.02 | 0.01 | −0.01 | −0.003 | 0.03 | −0.003 | −0.02 |
| Years | 0.02 | 0.14 ** | −0.101 ** | 0.016 | 0.061 ** | −0.150 ** | 0.032 | 0.109 ** | −0.100 ** | −0.003 | 0.084 ** |
| M | 2.18 | 3.59 | 2.68 | 3.66 | 3.98 | 2.90 | 3.66 | 3.80 | 2.73 | 3.46 | 3.78 |
| SD | 0.96 | 0.97 | 0.87 | 0.78 | 0.78 | 0.93 | 0.76 | 0.82 | 0.96 | 0.79 | 0.82 |
Note: S: students; P: parents; C: colleagues and leaders; Gender: 1 = male; 0 = female. Years: years of teaching experience, * p < 0.05; ** p < 0.01; *** p < 0.001.
Means (standard deviations) for three emotional labor strategies and the simple effect analyses for the triple interaction effect.
| SA | DA | ENFE | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Small PD | Large PD | F | ƞ2 | Small PD | Large PD | F | ƞ2 | Small PD | Large PD | F | ƞ2 | |
| Students | 2.41 (0.03) | 2.95 (0.03) | 196.44 *** | 0.09 | 3.73 (0.03) | 3.62 (0.03) | 10.33 ** | 0.01 | 4.16 (0.03) | 3.82 (0.02) | 92.88 *** | 0.04 |
| Parents | 2.59 (0.03) | 3.17 (0.03) | 204.45 *** | 0.09 | 3.75 (0.03) | 3.57 (0.02) | 25.21*** | 0.01 | 4.00 (0.03) | 3.66 (0.03) | 86.63 *** | 0.04 |
| Colleagues and leaders | 2.37 (0.03) | 3.12 (0.03) | 330.35 *** | 0.14 | 3.51 (0.03) | 3.41 (0.03) | 8.75 ** | 0.004 | 4.00 (0.03) | 3.57 (0.03) | 136.52 *** | 0.06 |
| Significant pairwise comparisons of different interactive partners | S < P, |
S < P, |
S > C, |
S > C, |
S > P, |
C < P < S | ||||||
Note: S: students; P: parents; C: colleagues and leaders. ** p < 0.01; *** p < 0.001.
Fit indices for the measurement models of three interactive partners.
| χ2 | df | RMSEA | TLI | SRMR | CFI | Standardized Factor Loadings | |
|---|---|---|---|---|---|---|---|
| 5-factor Model-S | 4972.47 | 314 | 0.067 | 0.92 | 0.063 | 0.93 | 0.39–0.94 |
| 5-factor Model-P | 5599.92 | 314 | 0.071 | 0.92 | 0.065 | 0.93 | 0.58–0.94 |
| 5-factor Model-C | 5808.42 | 314 | 0.073 | 0.93 | 0.067 | 0.93 | 0.59–0.95 |
| 4-factor Model-S | 9501.32 | 318 | 0.093 | 0.85 | 0.094 | 0.86 | 0.002–0.94 |
| 4-factor Model-P | 11,422.24 | 318 | 0.103 | 0.84 | 0.104 | 0.85 | 0.04–0.93 |
| 4-factor Model-C | 11,502.28 | 318 | 0.103 | 0.85 | 0.102 | 0.86 | −0.002–0.95 |
| 3-factor Model-S | 16,198.14 | 321 | 0.122 | 0.74 | 0.112 | 0.77 | −0.04–0.92 |
| 3-factor Model-P | 19,044.82 | 321 | 0.133 | 0.73 | 0.122 | 0.75 | 0.006–0.92 |
| 3-factor Model-C | 20,150.51 | 321 | 0.137 | 0.73 | 0.122 | 0.76 | −0.018–0.927 |
| 2-factor Model-S | 26,852.31 | 323 | 0.157 | 0.57 | 0.172 | 0.61 | 0.02–0.92 |
| 2-factor Model-P | 34,732.61 | 323 | 0.179 | 0.51 | 0.197 | 0.55 | 0.04–0.92 |
| 2-factor Model-C | 47,292.47 | 323 | 0.210 | 0.38 | 0.218 | 0.43 | −0.01–0.92 |
| 1-factor Model-S | 38,084.76 | 324 | 0.188 | 0.40 | 0.200 | 0.44 | 0.02–0.92 |
| 1-factor Model-P | 45,956.48 | 324 | 0.206 | 0.35 | 0.222 | 0.40 | 0.04–0.92 |
| 1-factor Model-C | 56,945.29 | 324 | 0.230 | 0.25 | 0.31 | 0.23 | −0.023–0.91 |
Note: 5-factor: PD, SA, DA, ENFE, EE; 4-factor: PD, SA + DA, ENFE, EE; 3-factor: PD, SA + DA + ENFE, EE; 2-factor: PD, SA + DA + ENFE + EE; 1-factor: PD + SA + DA + ENFE + EE.
The results of the indirect effects.
| Model Pathways | Estimated Standardized Effect | BC 95% CI | p |
|---|---|---|---|
| Total effect | |||
| PD→EE | |||
| Students | 0.130 | [0.092, 0.168] | 0.000 |
| Parents | 0.130 | [0.092, 0.167] | 0.000 |
| Colleagues and leaders | 0.130 | [0.092, 0.167] | 0.000 |
| Direct effects | |||
| PD→EE | |||
| Students | 0.047 | [0.007, 0.084] | 0.023 |
| Parents | 0.042 | [0.002, 0.081] | 0.045 |
| Colleagues and leaders | 0.021 | [−0.021, 0.056] | 0.336 |
| Indirect effects | |||
| PD→SA→EE | |||
| Students | 0.085 | [0.063, 0.104] | 0.000 |
| Parents | 0.088 | [0.068, 0.110] | 0.000 |
| Colleagues and leaders | 0.110 | [0.088, 0.135] | 0.000 |
| PD→DA→EE | |||
| Students | −0.001 | [−0.005, 0.001] | 0.560 |
| Parents | −0.002 | [−0.007, 0.000] | 0.237 |
| Colleagues and leaders | 0.000 | [−0.001, 0.003] | 0.860 |
| PD→ENFE→EE | |||
| Students | −0.001 | [−0.008, 0.006] | 0.771 |
| Parents | 0.002 | [−0.003, 0.009] | 0.400 |
| Colleagues and leaders | 0.000 | [−0.007, 0.005] | 0.916 |
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