The office of the Financial Stability and Development Commission of the State Council of China issued 11 measures to open up the financial industry to the outside world in July, 2019 (China Economic Net, 2019). The “catfish effect” induced by foreign capital forces the regulation and transformation of domestic wealth management enterprises. Wealth management enterprises are typical service organization (Lu et al., 2006) for its intensive interaction with customers. Service organizations are vulnerable to customer switching because of the high level of competition (Lam et al., 2004). A loyal customer is like an asset to an organization (Arora & Narula, 2018). It can lead to customers’ future repurchase and positive word of mouth. Customer loyalty promotes profitability (Hayes, 2008). Increased loyalty stimulates additional purchases, and loyal customers are less likely to switch brand preferences if competitors offer lower prices (Bowen & Shoemaker, 1998). They can help to keep a dominant position in competition and gain more profit (Geng & Jia, 2014). The cost of acquiring new customers is 4 - 5 times of retaining current ones (Desatnick & Detzel, 1988). How to preserve customer and enhance customer loyalty has been an issue for the practitioners. Consumers value the frontline employees’ service because of the interaction and trustworthiness that they offer (Riquelme et al., 2016; Larivière et al., 2017; Lee, 2017). Frontline employees appear to be the essential element capable of assuring a firm’s success (Cadwallader et al., 2010).
Frontline employees’ competences are especially important in creating a pleasurable and convenient service encounter (Lucia-Palacios et al., 2020). Nguyen confirmed that the competence of Canadian financial service employees is the antecedent of customer loyalty (Nguyen, 2016). Wealth management is still in its infancy in China, and the study on the influence factors of customer loyalty is rare. Whether Nguyen’s study result is applicable in China needs to be tested.
Nguyen suggested that employees’ competence directly affect customer loyalty, whereas Suhail et al. suggested that customer trust has a positive influence on customer loyalty in an Indian retail banking sector (Bhat et al., 2018). This indicates that both competence and trust are antecedents of customer loyalty. However, in the context of wealth management, the correlation among employee competence, trust, and customer loyalty has yet to be examined. In the current study, we argue that there is a process before customers become loyal to an enterprise, and employees’ competence needs a mediation mechanism (i.e. trust) to influence customer loyalty instead of directly. Mayer (2008) and Guiso et al. (2004, 2008) show that Financial transactions are very trust-intensive and that trust in financial markets is an important factor for financial development. As the main business is to manage customers’ money, it is important to achieve customers’ trust for wealth management organization. Without customers’ trust, only high competence is not enough to achieve customer loyalty.
Creating loyalty for corporate brands has become more challenging due to minimal differentiation among their competitive offerings and similar corporate and organizational values among competitors (Anisimova, 2007; Dawes, Meyer-Waarden, & Driesener, 2015). In this sense, building and maintaining effective relationships with consumers is crucial for gaining customer loyalty (Gbadamosi, 2015). This relationship refers to the emotional component between consumer and firm. Employees’ emotion regulation during service interactions affects customer loyalty, all of which are critical for service success (Seger-Guttmann & Medler-Liraz, 2016). Employees are required to regulate emotion expression strategically when interacting with customers, that is, to show positive emotion and suppress negative emotion through facial expression or cognition regulation. This indicates employees have exposed to emotional labor. According to emotional contagion theory, employees’ positive emotion will be experienced by customers. At the same time, customers will have more trust with employees if they show more professional competence. Otherwise, customers will doubt employees’ competence if they experience their faked emotion display. Previous study has investigated emotional labor’s moderation effect on the relationship between customer participation and buying (Seger-Guttmann & Medler-Liraz, 2016). However, there is a very limited understanding about the moderation effect of emotional labor in the wealth management context. The current study aims to investigate the mechanism of customer loyalty in the wealth management organization from the perspective of emotional labor.
2. Literature Review and Hypothesis
2.1. Customer Loyalty
Customer loyalty is an important factor in enhancing the sustainability of a company through maintaining existing customers and strengthening relationships (Hallowell, 1996). Customer loyalty includes two dimensions: attitudinal and behavioral (Chandrashekaran et al., 2007). From the attitudinal perspective, customer loyalty can be interpreted as a degree of positive attitude or preference towards a product or service (Jacoby & Chesnut, 1978). It can be described as the intention to recommend and repurchase (Kumar et al., 2013). Attitudinal loyalty expresses a consumer’s desire to establish a relationship with an enterprise. The problem is to verify if this intention will transfer to an action (Nguyen, 2016). From the behavioral perspective, customer loyalty is described as the repeat purchasing or use of a given service or product over time (Leenheer et al., 2007). Behavioral loyalty includes retention, repurchase, duration of the relationship (Kumar et al., 2013). Whether perceived as an attitude or type of behavior, loyalty is one of many elements that influence consumers’ buying decisions (Nguyen, 2016).
The competence of service employees is a body of knowledge gained from training and experience. It constitutes their capacity to provide transactions requested by the customer and to perform in a way to meet his or her expectations (Barclay & Smith, 1997). This competence usually relies on the ability of service employees to acquire and apply this knowledge in accomplishing their job. It is to ensure the success of transactions during the service encounter and help to increase customer’s trust towards the firm (Xie & Peng, 2009) and customer retention (Delcourt et al., 2013).
Competence has two components: technical expertise and problem-solving skills (Sirdeshmukh et al., 2002). Technical expertise is considered as a cognitive component of competence. It is the degree of knowledge directly related to the firm’s activity. This expertise is requested as a necessary qualification in the recruitment process. It is possessed individually through the employee’s professional training. Technical expertise can be accumulated on the job and enhanced by continuing education. Due to its significant impact on the outcome of transactions, technical expertise can help service employees to meet the consumer’s expectations and to gain his or her trust towards the firm. The problem-solving skill is the behavioral component of competence. It represents the ability of service employees to tackle conflictual issues, i.e., service failure. In service recovery, employees have to take into consideration the motivations of both parties while attempting to satisfy the customer’s needs and protecting the firm’s interests. The problem-solving skill of service employees is the result of their individual personality traits and their perceptions of the social interaction with customers during the service encounter (Hartline et al., 2003; Solomon et al., 1985). The two components of competence are the same important components in attracting customers.
Previous research has examined the influences of employee competence on various aspects of the firm, including corporate image (Nguyen & Leclerc, 2011), service quality, customer satisfaction (Arora & Narula, 2018) and customer loyalty (Nguyen, 2016). In the context of wealth management service, the competence of employees is specifically geared towards the success of the transaction that meets the customer’s requirements and in turn the loyalty to the firm. Hence the first hypothesis can be stated as follows:
H1: Wealth management service employees’ competence is positively related to customer loyalty.
Trust is the expectation held by a consumer that the service provider is dependable and can be relied high on to deliver on its promises and to put the client’s interest first. It is an essential ingredient for stable relationships (Kimes, 2010). Trust removes the vulnerability to exploitation (Hansen, 2012). Consumers’ perceived trust in a relationship partner has been found to influence overall satisfaction and generate behaviors that increase cooperation, loyalty (Tran & Strutton, 2020) and performance (Kinnel, 2010). The development of trust between the consumer and the financial service provider may promote relational exchanges that prove to add value for both partners (Winchester & Huston, 2017). As trust decisions involve both thinking (cognitive) and feeling (affective) process (Srivastava et al., 2015), the current study examines the concept of trust through its cognitive and affective components. Cognitive trust is driven by knowledge and a rational thought process (Wang et al., 2016), whereas affective trust is driven by feelings and emotional exchanges (Albert & Merunka, 2013; Dowell et al., 2015).
Cognitive trust is an instrumental inference made from information about another’s behavior under specific circumstances (Zhang, 2015). The level of cognitive trust may reflect integrity factors including honesty and fairness of the referent (Dirks & Ferrin, 2002). Affective trust relates to the extent to which one feels secure and comfortable about the trustee (Komiak & Benbasat, 2006; Zhang, 2015).
2.4. Stimulus-Organism-Response Theory
Stimulus-Organism-Response (SOR) theory was developed by environmental psychologists. The theory posits the environment functions as a stimulus. Organisms’ external environments influence their internal reactions. These reactions, in turn, promote external behavioral responses among organisms (Mehrabian & Russell, 1974). These internal organism responses include affective (emotional) and cognitive elements. These emotional and cognitive beliefs mediate approach or avoidance responses toward the environment (Tran & Strutton, 2020). According to SOR theory, employees’ competence might function as an environmental stimulus; trust (i.e., customers’ internal reaction) as an organism; and customer loyalty functioned as behavioral responses. Hence, we hypothesize as follows:
H2: Trust mediates the relationship between employees’ competence and customer loyalty.
2.5. Emotional Labor
In the workplace, employees should not only pay mental and physical labor, but also emotional labor. In 1983, American sociologist Hochschild proposed the concept of emotional labor on the basis of absorbing Goffman’s Parody theory through the analysis of Delta Air flight attendants (Hochschild, 1983). He defined it as “to get paid, front-line employees manage their own emotions, and perform to customers according to the organization’s requirements through facial expression or body language”. Later studies found that emotional labor in the workplace also exists in other situations, such as doctor-patient relationship, colleague relationship (Geddes & Lindebaum, 2020), collective decision making, negotiation and subordinate relationship of leadership (Van Kleef et al., 2012). This paper focuses on the customer service situation. The core of emotional labor is an effort to regulate emotions. This regulation process includes two strategies: deep acting and surface acting. Deep acting is a kind of antecedent-focused emotion regulation strategy (Gross, 1998). It needs to reappraise the situation to regulate the inner feelings, and then express the positive emotions required by the organization (through facial expression, tone, gesture and body posture). Surface acting is reaction-focused, which only needs to regulate the expression of emotions, that is, to suppress negative emotions and show positive ones, although the real feelings of the heart remain the same (Grandey, 2000). Emotions have internal effects, that is, employees engaged in emotional labor will have an impact on themselves, such as loss of self (Hochschild, 1983), emotional exhaustion (Grandey & Melloy, 2017), burnout, health problems (Zapf, 2002), and low job satisfaction. Emotions also have interpersonal effects, that is, employees engaged in emotional labor will have an impact on customers’ emotion, attitude, cognition and behavior (Van Kleef, 2016).
Grandey and Melloy’s research suggested that employees’ deep acting strategy is related to customer positive outcomes, while surface acting is the opposite (Grandey & Melloy, 2017). Taeshik et al. found that the two strategies of hotel employees’ emotional labor affect customer loyalty through customers’ positive emotions and perceived service quality. These researches mainly focus on hotel and other service industries. Grandey suggested that emotional labor research needs to be combined with certain social and cultural situations (Grandey & Melloy, 2017). The situation of wealth management has its unique characteristics. It makes financial planning for customers by taking customers as the center. According to the theory of emotional contagion, customers will perceive employees’ emotions and be infected. Therefore, the positive emotional display of employees is conducive to the good emotional experience of customers. On the contrary, customers will doubt the service ability of employees if they perceive the fake emotional display of employees. This study supposes that emotional labor moderates the positive effect of employee competence on customer trust. That is to say, the stronger the employees’ professional knowledge and problem-solving ability, the more trust the customers will have, and the sincere service (deep acting) of the employees will strengthen this relationship; on the contrary, the false display (surface acting) will weaken this relationship.
Customer perceived and employee perceived emotional labor are two different concepts (Gong et al., 2020). In the process of establishing the boundary of host and guest emotional communication, customers play a leading role (Christou et al., 2019). Therefore, the current study chooses the employees’ emotional labor perceived by customers to study its moderating effect on the positive relationship between employee competence and customer trust. As customers perceive emotional labor in two ways at the same time, deep acting and surface acting are regarded as two independent constructs to explain emotional labor. Accordingly, we hypothesize as follows:
H3a: Employees’ deep acting strategy positively moderates the relationship between employees’ competence and customer trust;
H3b: Employees’ surface acting strategy negatively moderates the relationship between employees’ competence and customer trust.
To sum up, the conceptual model is shown in Figure 1.
Figure 1. The conceptual model.
3.1. Data Collection
Data was gathered using an online survey. To test the tool, a pilot test was first carried out from January 14 to 23, 2020 through WeChat. This initial study sought to improve the questions and remove unclear and/or ambiguous items in order to refine the survey content and structure. Preliminary evidence presented reliable and valid scales. Following the pre-test, the formal research data was collected on Mar. 2020 through social media platforms. After removing 21 incomplete and invalid (income below 4000) questionnaires, we finally get 183 (>150) (Rigdon, 2005) valid responses. Table 1 lists the basic information of the sample. More than 50% of respondents were men; more than 60% of them were older than 36 years of age, and more than 90% of the income were above 5000.
We used Harman’s single-factor test to assess common method bias. The first factor explains 35.3% of the covariance amongst all constructs. This is less than 50%, which means that common method bias does not affect our data (Podsakoff et al., 2003, 2012). This study entails all the common shortcomings involved in using an open access sampling methodology (e.g., self-selection bias, lack of information about non-respondents, and unknown response rate) (Kuss et al., 2014).
3.2. Scale Design
The questionnaire items were based on those reported in the literature and adapted for this context. Five items were used for the measurement of competence according to Nguyen’s study (Nguyen, 2016). Two items were for the technical expertise component and three other items are for the problem-solving skills component. Trust included ten items according to Sena et al.’s work (Ozdemir et al., 2020), is drawn from studies by Johnson & Grayson (2005), McAllister (1995), Massey & Dawes (2007), Massey & Kyriazis (2007) and Wang & Qiu et al. (2016). Six items were used to measure customer loyalty according to Nguyen’s study which was based on the work of Zeithaml et al. (1996). We measured surface acting using Groth’s et al. (2009) three-item scale and deep acting using Brotheridge & Lee’s (2003) three-item scale. All items for each question were measured with Likert’s 5-point range scale, from “strongly disagree” (1) to “strongly agree” (5) (see Appendix).
Table 1. Respondents’ socio-demographic characteristics.
Our control variables included gender and income. Mittal et al. (2019) investigated that female are more satisfied and loyal to their bank compared to male. Including income as a control variable enabled us to control the effect of investing power on consumer loyalty.
4. Data Analyses and Results
4.1. Indicator Reliability and Validity
The linkage between constructs was tested and analyzed using SPSS 21.0 and AMOS software. Structural equation modelling (SEM), namely partial least squares (PLS) path modelling was employed. All of the constructs were measured by reflective constructs. As shown in Table 2, the Cronbach’s alphas for competence,
Table 2. Indicators’ reliability and validity.
Note: SA—surface acting; DA—deep acting; EL—emotional labor; TR—trust; CO—competence; CL—customer loyalty.
trust, customer loyalty, surface acting and deep acting were 0.801, 0.829, 0.919, 0.648 and 0.76 respectively, greater than 0.6. In order to test convergent validity, we analyzed factor loading and average variance extracted (AVE). All of the factor loadings were greater than 0.5. Fornell & Larcker (1981) suggested that the AVE should present a value not lower than 0.5, which reflects adequate convergent validity (Götz et al., 2010). Consequently, and according to the results shown in Table 2, all constructs indicate AVE greater than 0.5.
To investigate the discriminant validity of the variables, we conducted confirmatory factor analysis (CFA) using AMOS and examined the fit indices of the hypothesized 3-factor model (i.e., competence, trust and customer loyalty). The CFA results (Table 3) show that the hypothesized 3-factor model fit the data well (χ2/df = 1.10, NFI = 0.92, RFI = 0.94, TLI = 1.00, IFI = 1.00, RMSEA = 0.003). As shown in Table 4, most values of the correlation coefficients between the independent variables were below the cut-off value of 0.7 (Field, 2009; Pallant, 2007). The composite reliability (CR) of each construct ranged from 0.81 to 0.98; the square root of AVE of each construct was greater than its correlations with other constructs (Table 4) which indicates good discriminant validity of the scales.
4.2. Structural Model and Hypotheses Testing
Through Pearson’s correlation analysis, we evaluated the correlation of the constructs, as shown in Table 4. We can conclude from Table 4 that employee competence was positively related with costomer trust and loyalty (β = 0.424, 0.503, p < 0.01); surface acting was negatively related with customer trust (β = -0.338, p < 0.05); deep acting was positively related with customer trust (β = 0.609, p < 0.01). The amounts of the sample were greater than 100, we used maximum likelihood estimation method (MLE) to evaluate the structure model (Hou et al., 2004). The results of the path analysis is shown in Figure 2 (χ2 =
Table 3. Confirmatory factor analysis.
Table 4. Correlations among variables.
Note: *p < 0.05; **p < 0.01 (two-tailed). Boldface letter is the square root of AVE. DA—deep acting; SA—surface acting; CO—competence; TR—trust; CL—customer loyalty.
11.87, df = 18, χ2/df = 0.659, CFI = 1.000, PNFI = 0.476, RMSEA = 0.000). Competence is positively related to customer loyalty, supported H1.
4.3. Mediation and the Moderated Mediation Effect
To test the mediation and moderated mediation hypotheses, we used the PROCESS macro for SPSS (version 3.0) (Hayes, 2018). In Table 5 and Table 6, we provided estimates of the mediation and moderated mediation effects, along with 95% bias-corrected bootstrapped confidence intervals of our path estimates. As suggested in H2, customer trust mediates the positive relationship between employees’ competence and customer loyalty (95% CI [0.15, 0.26]). H2 was supported.
H3a states that the mediating effect of customer trust on the relationship between employees’ competence and customer loyalty is positively moderated by employees’ deep acting. The index of moderated mediation indicated that CI did not include zero (95% CI [0.11, 0.29]). So H3a was supported. A 95% bootstrap confidence interval includes zero only when customer trust is relatively low (−1SD) (95% CI [−0.01, 0.33]). H3b states that the mediating effect of customer
Figure 2. Results of the structure model testing.
Table 5. Mediation effect of trust.
CO—competence; TR—trust; CL—customer loyalty.
Table 6. Moderated mediation effects model predicting customer loyalty.
DA—deep acting; SA—surface acting; CO—competence; TR—trust; CL—customer loyalty.
trust on the relationship between employees’ competence and customer loyalty is positively moderated by employees’ surface acting. The index of moderated mediation indicated that CI did not include zero (95% CI [−0.12, −0.02]). A 95% bootstrap confidence interval includes zero only when customer trust is relatively low (−1 SD) (95% CI [−0.05, 0.19]). So H3b was supported.
The frontline employees play a vital role in wealth management organization. According to the emotional contagion theory and SOR theory, the conceptual framework of the relationship among employees’ competence, customer trust and loyalty was supposed and tested. Several results have reached.
Firstly, employees’ competence (including professional knowledge and problem-solving ability) positively influences customer loyalty. This indicates that wealth management service organization should primarily strengthen employees’ competence through training and other education. Specific hiring strategy should be employed to select suitable employees.
Secondly, trust plays mediation role in the positive relationship between employees’ competence and customer loyalty. Besides competence, wealth management service organization should seek for other practical trust building techniques.
Thirdly, employees’ deep acting display strategy positively moderate the positive relationship between employees’ competence and customer loyalty, while surface acting plays a negative role. In experience economy era, customers’ experiences could be affected by the nature of service employees’ emotional labor, which can act as a potentially damaging outside source (Groth et al., 2009). Wealth management service organization should encourage employees to display genuine emotions (deep acting). Unique HRM policy should be employed, such as recruitment, selection, performance evaluation, etc.
5.1. Theoretical and Managerial Implications
From a theoretical perspective, the current study has contributed to understanding the mediation and moderation factors impacting customer loyalty. Allied to this, emotional contagion theory and SOR theory have played a critical role in this study. Its major innovation and theoretical contribution is in introducing emotional labor’s moderation effect into wealth management context. To the best of our knowledge, this is one of the rare empirical research that investigates emotional labor’s moderation effect on customer loyalty in wealth management service organization. The result shows that employees’ emotional labor as well as are simultaneously important to generate customer loyalty.
From a practical perspective, there are important implications for wealth management practitioners and universities. University is the place that fosters future practitoners. The courses offered should take emotional labor education into consideration. Nowadays, emotional labor is highlighted in most service organizations especially financial corporates. These corporates pay to train employees necessary emotion expression. For the cost reduction purpose, we advise universities to add emotional labor course in the wealth management-related majors. Through this, the overall cost our society will decrease. This will increase university’s popularity in society and the employment rate will be raised.
Practitioners sought to raise customer loyalty because it is less costly and more beneficial. This study suggests employees’ competence is the primary element to influence customer loyalty. In practice, we should ensure employees’ professional knowledge and problem-solving ability firstly. This could be realized by entrance training and timely evaluation. The mediation effect of turst indicates that obtaining customers’ trust is also important in fostering loyal customers. Wealth management service organization should put more efforts in earning trust. Sharpe et al. (2007) investigated communication strategies which lead to trust. He found that being comfortable (or calm) with client expressions of strong emotions; actively seeking to understand clients’ personalities, family history, and values; and involving the consumer in a systematic process for identifying their values and goals are all practical techniques for building consumer trust.
5.2. Limitations and Future Research
This research has some limitations unavoidably. First, the study is subject to all of the shortcomings that exist regarding open access sampling (e.g., self-selection bias, lack of information about non-respondents, unknown response rate) (Kuss et al., 2014). However, the full range of scores on all variables was represented in the data, which normally strengthens the validity of estimated relationships between constructs. Second, the sample size is 183, its representativeness may be not enough. Future research can broaden the sample size to enhance the representativeness. Thirdly, we only tested one antecedent (competence), one mediation factor (trust) and one moderation factor (emotional labor) of customer loyalty, other antecedents, mediation and moderation factors should be included in order to obtain a comprehensive understanding of customer loyalty in future.
Supported by Wealth Management Project of Shandong Technology and Business University (No: 2019ZBKY042).
R: reversed score.
 Anisimova, T. A. (2007). The Effects of Corporate Brand Attributes on Attitudinal and Behavioural Consumer Loyalty. Journal of Consumer Marketing, 24, 395-405.
 Arora, P., & Narula, S. (2018). Linkages between Service Quality, Customer Satisfaction and Customer Loyalty: A Literature Review. The IUP Journal of Marketing Management, 17, 30-54.
 Barclay, D. W., & Smith, J. B. (1997). The Effects of Organizational Differences and Trust on the Effectiveness of Selling Partner Relationships. Journal of Marketing, 61, 3-21.
 Brotheridge, C. M., & Lee, R. T. (2003). Development and Validation of the Emotional Labor Scale. Journal of Occupational and Organizational Psychology, 76, 365-379.
 Cadwallader, S., Jarvis, C. B., Bitner, M. J., & Ostrom, A. L. (2010). Frontline Employee Motivation to Participate in Service Innovation Implementation. Journal of the Academy of Marketing Science, 38, 219-239.
 China Economic Net (2019). Financial Commission of the State Council Issued 11 Measures to Open Up the Financial Industry to the outside World.
 Christou, P., Avloniti, A., & Farmaki, A. (2019). Guests’ Perceptions of Emotionally Expressive and Non-Expressive Service Providers within the Hospitality Context. International Journal of Hospitality Management, 76, 152-162.
 Dawes, J., Meyer-Waarden, L., & Driesener, C. (2015). Has Brand Loyalty Declined? A Longitudinal Analysis of Repeat Purchase Behavior in the UK and US. Journal of Business Research, 68, 425-432.
 Delcourt, C., Gremler, D. D., van Riel, A. C. R., & van Birgelen, M. (2013). Effects of Perceived Employee Emotional Competence on Customer Satisfaction and Loyalty. The Mediating Role of Rapport. Journal of Service Management, 24, 5-24.
 Dirks, K. T., & Ferrin, D. L. (2002). Trust in Leadership: Meta-Analytic Findings and Implications for Research and Practice. Journal of Applied Psychology, 87, 611-628.
 Dowell, D., Morrison, M., & Heffernan, T. (2015). The Changing Importance of Affective Trust and Cognitive Trust across the Relationship Lifecycle: A Study of Business-to-Business Relationships. Industrial Marketing Management, 44, 119-130.
 Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18, 39-50.
 Gbadamosi, A. (2015). Brand Personification and Symbolic Consumption among Ethnic Minority Teenage Consumers: An Empirical Study. Journal of Brand Management, 22, 737-754.
 Gong, T., Park, J. K., & Hyun, H. (2020). Customer Response toward Employees’ Emotional Labor in Service Industry Settings. Journal of Retailing and Consumer Services, 52, Article ID: 101899.
 Götz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of Structural Equation Models Using the Partial Least Squares (PLS) Approach. In Handbook of Partial Least Squares (pp. 691-711). Berlin: Springer.
 Grandey, A. A. (2000). Emotion Regulation in the Workplace: A New Way to Conceptualize Emotional Labor. Journal of Occupational Health Psychology, 5, 95-110.
 Grandey, A. A., & Melloy, R. C. (2017). The State of the Heart: Emotional Labor as Emotion Regulation Reviewed and Revised. Journal of Occupational Health Psychology, 22, 407-422.
 Groth, M., Hennig-Thurau, T., & Walsh, G. (2009). Customer Reactions to Emotional Labor: The Roles of Employee Acting Strategies and Customer Detection Accuracy. Academy of Management Journal, 52, 958-974.
 Hallowell, R. (1996). The Relationship of Customer Satisfaction, Customer Loyalty and Profitability: An Empirical Study. International Journal of Service Industry Management, 7, 27-42.
 Hansen, T. (2012). Understanding Trust in Financial Services: The Influence of Financial Healthiness, Knowledge, and Satisfaction. Journal of Service Research, 15, 280-295.
 Hartline, M. D., Woolridge, B. R., & Jones, K. C. (2003). Guest Perceptions of Hotel Quality: Determining Which Employee Groups Count Most. The Cornell Hotel and Restaurant Administration Quarterly, 44, 43-52.
 Komiak, S. Y. X., & Benbasat, I. (2006). The Effects of Personalization and Familiarity on Trust and Adoption of Recommendation Agents. MIS Quarterly, 30, 941-960.
 Kumar, V., Pozza, I. D., & Ganesh, J. (2013). Revisiting the Satisfaction-Loyalty Relationship: Empirical Generalizations and Directions for Future Research. Journal of Retailing, 89, 246-262.
 Kuss, D. J., Griffiths, M. D., Karila, L., & Billieux, J. (2014). Internet Addiction: A Systematic Review of Epidemiological Research for the Last Decade. Current Pharmaceutical Design, 20, 4026-4052.
 Lam, S. Y., Shankar, V., Erramilli, M. K., & Murthy, B. (2004). Customer Value, Satisfaction, Loyalty, and Switching Costs: An Illustration from a Business-to-Business Service Context. Journal of the Academy of Marketing Science, 32, 293-311.
 Larivière, B., Bowen, D., Andreassen, T. W. et al. (2017). “Service Encounter 2.0”: An Investigation into the Roles of Technology, Employees and Customers. Journal of Business Research, 79, 238-246.
 Lee, H. (2017). Personality Determinants of Need for Interaction with a Retail Employee and Its Impact on Self-Service Technology (SST) Usage Intentions. Journal of Research in Interactive Marketing, 11, 214-231.
 Leenheer et al. (2007). Do Loyalty Programs Really Enhance Behavioral Loyalty? An Empirical Analysis Accounting for Self-Selecting Members. International Journal of Research in Marketing, 24, 31-47.
 Lucia-Palacios, L., Pérez-López, R., & Polo-Redondo, Y. (2020). How Situational Circumstances Modify the Effects of Frontline Employees’ Competences on Customer Satisfaction with the Store. Journal of Retailing and Consumer Services, 52, Article ID: 101905.
 Massey, G. R., & Dawes, P. L. (2007). Personal Characteristics, Trust, Conflict, and Effectiveness in Marketing/Sales Working Relationships. European Journal of Marketing, 41, 1117-1145.
 Massey, G. R., & Kyriazis, E. (2007). Interpersonal Trust between Marketing and R&D during New Product Development Projects. European Journal of Marketing, 41, 1146-1172.
 McAllister, D. J. (1995). Affect- and Cognition-Based Trust as Foundations for Interpersonal Cooperation in Organizations. Academy of Management Journal, 38, 24-59.
 Nguyen, N. (2016). Reinforcing Customer Loyalty through Service Employees’ Competence and Benevolence. The Service Industries Journal, 36, 13-14+721-738.
 Nguyen, N., & Leclerc, A. (2011). The Effect of Service Employees’ Competence on Financial Institutions’ Image: Benevolence as a Moderator Variable. Journal of Services Marketing, 25, 349-360.
 Ozdemir, S., Zhang, S. J., Gupta, S., & Bebek, G. (2020). The Effects of Trust and Peer Influence on Corporate Brand—Consumer Relationships and Consumer Loyalty. Journal of Business Research. (In Press)
 Podsakoff, P. M., Mackenzie, S. B., & Podsakoff, N. P. (2012). Sources of Method Bias in Social Science Research and Recommendations on How to Control It. Annual Review of Psychology, 63, 539-569.
 Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. Journal of Applied Psychology, 88, 879-903.
 Riquelme, I. P., Román, S., & Iacobucci, D. (2016). Consumers’ Perceptions of Online and Offline Retailer Deception: A Moderated Mediation Analysis. Journal of Interactive Marketing, 35, 16-26.
 Seger-Guttmann, T., & Medler-Liraz, H. (2016). Does Emotional Labor Moderate Customer Participation and Buying? The Service Industries Journal, 36, 7-8+356-373.
 Solomon, M. R., Surprenant, C., Czepiel, J. A., & Gutman, E. G. (1985). A Role Theory Perspective on Dyadic Interactions: The Service Encounter. Journal of Marketing, 49, 99-111.
 Srivastava, N., Dash, S. B., & Mookerjee, A. (2015). Antecedents and Moderators of Brand Trust in the Context of Baby Care Toiletries. Journal of Consumer Marketing, 32, 328-340.
 Tran, G. A., & Strutton, D. (2020). Comparing Email and SNS Users: Investigating E-Servicescape, Customer Reviews, Trust, Loyalty and E-WOM. Journal of Retailing and Consumer Services, 53, 1-17.
 Van Kleef, G. A. (2016). The Interpersonal Dynamics of Emotion: Toward an Integrative Theory of Emotions as Social Information. Cambridge: Cambridge University Press.
 Wang, W., Qiu, L., Kim, D., & Benbasat, I. (2016). Effects of Rational and Social Appeals of Online Recommendation Agents on Cognition- and Affect-Based Trust. Decision Support Systems, 86, 48-60.
 Xie, Y., & Peng, S. (2009). How to Repair Customer Trust after Negative Publicity: The Roles of Competence, Integrity, Benevolence and Forgiveness. Psychology and Marketing, 26, 572-589.
 Zapf, D. (2002). Emotion Work and Psychological Well-Being: A Review of the Literature and Some Conceptual Considerations. Human Resource Management Review, 12, 237-268.
 Zhang, S. (2015). An Empirical Assessment of the Impact of Brand Trust Violations in the Chinese Dairy Industry on Consumers’ Repurchasing Intentions: A Brand/Consumer Relationship Perspective. Journal of Entrepreneurship in Emerging Economies, 7.