Pandemic-oriented customer mistreatment, service sabotage and service performance: a self-presentation perspective

Abstract

Purpose

In this study, the authors develop a path model and investigate the effect of pandemic-oriented customer mistreatment on service sabotage through the lens of self-presentation theory. Moreover, the authors question the role of service climate as a moderator of the relationship between service sabotage and service performance.

Design/methodology/approach

Data were collected via a survey of 165 F&B frontline employees in restaurants in Iran. The hypotheses are examined using confirmatory factor analysis, structural equation modeling and ordinary least squares regression.

Findings

The findings reveal that POCM has a substantial and positive effect on service sabotage, and service climate mitigates the effect of service sabotage on service performance.

Practical implications

The study introduces and conceptually defines the term POCM. Furthermore, the authors apply the self-presentation theory as the overarching theory to explain underlying conditions in customer mistreatment and service sabotage. Moreover, although prior literature has described the saboteur–customer relationship as a one-line interaction, this study contributes to employee sabotage as a multi-linear transaction.

Originality/value

In this study, the authors identify new perspectives on the dark side of hospitality services in crises, such as the COVID-19 pandemic. The authors argue that pandemic-induced changes are essential not simply because they change customers’ moods and lower their patience threshold, but they further provoke ostentatious behaviors in saboteur–customer relations. These findings shed new light on the literature and provide managerial implications for enhancing hospitality performance.

Citation

Khademi-Gerashi, M., Akhgari, F., Damberg, S. and Moradi, F. (2023), "Pandemic-oriented customer mistreatment, service sabotage and service performance: a self-presentation perspective", International Hospitality Review, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IHR-10-2022-0044

Introduction

Understanding the moral values of employees in service environments is a critical component in creating effective communication (Liu et al., 2022b; Sergeant & Frenkel, 2000). It has been widely acknowledged that the behavior of frontline employees is the most prominent factor influencing customer perceptions of service and, ultimately, the organization’s performance (Singh, 2000). The main merits of superior performance are secure relationships, employees’ self-confidence, social relationships, and thus increasing customer commitment to a long-term relationship. Nevertheless, some unexpected events, such as economic shocks or health crises, can affect the behavior of staff and customers. During the worldwide COVID-19 pandemic, the emergence of successive variants of the coronavirus associated with declines in mental well-being and social relationships changed the analytical sphere in customer service and raised new debates (Kim, Kim, & Wang, 2021).

When customers mistreat frontline employees, many employees adopt coping strategies, such as service revenge, which is evident in 64% of cases (Peng et al., 2021a, b; Reynolds & Harris, 2006). Through sabotage and a sense of self-worth, one can defend, revive and rebuild oneself if wrongdoers can achieve what they deserve (Ma et al., 2021; Harris & Ogbona, 2006). Customers in manufacturing sections may need help understanding, or be familiar, with the meaning of service sabotage by employees. Still, they are the first target to be affected in service settings, while the company’s performance subsequently suffers from what happened (see Harris & Ogbona, 2009). Service sabotage is a deliberate behavior intended to downgrade a company’s services (Harris & Ogbona, 2002). Service climate in workplaces may affect employee performance at any hierarchical level. Evidence supports the moderating role of service climate as employees’ shared perceptions of methods, practices and behaviors that are rewarded and kept in a particular context (Harris & Ogbonna, 2006). Since multiple climates simultaneously exist in a single organization, service climate can be considered a specific reference structure such as support, innovation, and safety (Ma et al., 2021).

The global COVID-19 pandemic has brought unpredictable changes in service businesses and re-defined the relationship between employees and customers. Some of the risky conditions created by the corona outbreak have complicated the analysis of service challenges (Wong & Yang, 2020). These changes have diminished the performance of services and provoked new debates on service “moments of truth.” The present study was designed to make two theoretical and methodological contributions.

First, we study the impact of customer mistreatment on service sabotage in crises which has yet to be addressed in the literature. A long-term quarantine reduces people’s tolerance threshold and increases the likelihood of injustice when faced with strict regulations (Wong & Yang, 2020). Therefore, we introduced and operationally defined pandemic-oriented customer mistreatment (POCM).

Second, we applied the self-presentation theory as our overarching theory to explain underlying conditions for customer mistreatment and service sabotage with motives to attract the attention of others. Due to the increasing isolation of social relations in pandemic conditions, the tendency to express oneself is strengthened (Rajkumar, 2020).

Literature review

Pandemic-oriented customer mistreatment (POCM)

The high level of human intervention (service provider and customer) in the production and delivery of services means that service quality depends heavily on the attitude and behavior of frontline employees and the expectation and behavior of customers (Liu et al., 2022a, b). The customer’s interest in service quality assumes that a positive perception of an organization’s service quality is likely to keep a customer (Nikbin et al., 2016). Schneider and co-authors showed that the customer’s overall understanding of service quality leads to a strong interaction (Schneider, White, & Paul, 1998). Their study found that how employees perceive their organization’s service climate is related to the quality of services understood by their customers (Wang, Liao, Zhan, & Shi, 2011). In a customer-oriented organization with a strong quality program, mistakes during service delivery are still ongoing (Patterson, Cowley, & Prasongsukarn, 2006). The person providing the service is the critical factor in determining the quality of appropriate services.

In this study, we analyze customer mistreatment from three perspectives. First, we investigate the effects of the COVID-19 pandemic on customers’ moral well-being. This variable consists of three sub-constructs extracted from interviews and analysis of the comments of restaurant employees. First, general mistreatment (GM) under normal circumstances (i.e., not just in a global crisis situation, such as the COVID-19 pandemic), including customers’ arrogant behaviors and unrealistic expectations when receiving service in a restaurant. Second, pandemic restriction diversion (PRD), which refers to customers’ disobedience to the general rules of the hospitality sector in a city or state; and third, pandemic rules aggression (PRA), which refers to customers’ behavior toward a restaurant’s specific rules in an epidemic (such as ridicule and neglect). Moreover, building on self-presentation theory, we introduce a newer perspective by analyzing possible negative angles of customer behavior in crises.

Service sabotage

The behavior of frontline service personnel is widely recognized as the most prominent factor influencing customer perceptions of service performance and, ultimately, organizational survival (Sergeant & Frenkel, 2000). Workplace sabotage is a behavior that tends to damage, disrupt or overturn a company’s operations to meet personal goals by creating unwanted advertising, embarrassing, delaying production, damaging property and destroying business relationships (Peng et al., 2021a, b).

Although sabotage can have multiple purposes (Cortina & Magley, 2003), some researchers focus on customer-directed sabotage. The literature shows that abuse victims seek sabotage from the aggressor (Liu et al., 2022a, b). Moreover, Scarmicki and co-authors have shown that the interpersonal mistreatment of customers positively correlates with customer sabotage. Service sabotage (e.g., delaying a customer) immediately impacts the “injured” customer. As a result, the customer may contact management to file a complaint to correct service quality damage (Harris & Ogbonna, 2006; Hwang, Yoo, & Kim, 2021). The varying degrees of employee response are essential for researchers to understand the factors that predict this kind of reaction. Harris and Ogbonna (2002) define customer-oriented service sabotage as any deviant behavior by service employees to negatively affect the customer experience (Nyamekye, Adam, Boateng, & Kosiba, 2021). Other studies show that customer mistreatment in many service organizations is institutional. In addition, recent studies using experimental simulation and cross-sectional field data (Dormann & Zapf, 2004) have shown that employees who receive customer abuse have experienced higher levels of negative emotions (Harris & Reynolds, 2003). Despite the widespread acceptance of the essential role of service personnel, commentators have recently observed that the actions and behaviors of frontline service personnel are poorly understood and insufficiently studied. Although Harris and Ogbonna (2002) have shown that sabotage is likely more pervasive in customer service relationships and has a more profound impact, quantitative evidence of service is limited and seems to focus more on case studies and oral evidence.

Service climate

Companies benefit from having a stable service climate (Schneider et al., 1998; Dietz et al., 2004). In the service literature, the climate is defined as employees’ shared perceptions of how methods and behaviors are rewarded and supported in a particular context (Ma et al., 2021). Climate may apply in most situations, such as services, support systems, innovation management and safety systems (Schneider, Gunnarson, & Niles-Jolly, 1994). It also consists of procedures and behaviors expected to be rewarded and supported in the organization based on the quality of service (Schneider et al., 1998).

Service climate is a collective and common phenomenon created in the light of organizational measures focusing on customer service. Service climate has specific, descriptive and collective content. Organizational climate studies introduced the social cognitive structure of care and service climate through which employees learn consistent internal patterns (Zohar, 2000). A company has a positive service climate if employees engage in distinctive practices and encourage behaviors that lead to excellent service delivery. The climate for growth services is shared understanding through interpreting and interacting with social guidance in the workplace. Care and service climate are essential aspects of an organization’s culture to counteract negative behaviors (Ma et al., 2021).

Furthermore, employee service climate enhances employees’ shared understanding of services (Schneider, Ehrhart, Mayer, Saltz, & Niles-Jolly, 2005). When employees collectively understand the service climate, they will realize that management will reward and support these excellent services if their organization provides high-quality services (Schneider & Bowen, 1993). They describe employee perceptions as a measure of service. This perception determines whether a company has a solid or weak service climate (Dietz et al., 2004). Service development is the end-to-end process of developing and launching a new customer service (Bowen & Schneider, 2014). Understanding how employees react emotionally is vital to understanding how atmospheres are created and shared in a particular organizational section. In a general context, the service climate depends not only on organizational structure, but also on the mental characteristics, employees’ feelings, and, eventually, their motivation at work. This study evaluates both managerial and cultural aspects of service climate.

Furthermore, Schneider et al. (2005) argue that service climate positively affects financial criteria and market performance. In the past, service climate has been understood as perceived independence, five personality traits (extroversion, conscientiousness, emotional stability, adaptability and empiricism), and control of service personnel in literature (Morgan, Rapp, Glenn Richey, & Ellinger, 2014). Schneider, English, Tabana, Padayachee, and Orgill (2014) showed that team members are flexible in supporting service development. Researchers also noted that interaction in work, strength and self-sacrifice positively affect service climate (Morgan et al., 2014).

Service performance

Performance is generally formed from two structural dimensions: Objective performance, which includes financial and market-driven factors, like profitability, market share and return on investment; and judgmental performance, which embraces aspects of customers and employees, including service perceived quality, customer satisfaction and employee satisfaction. Some studies of employee service performance have ignored a particular type of service interaction; however, service performance requires addressing customers’ long-term needs. Employees are committed to paying more attention to long-term customer goals and interests as a critical element of service performance (Liao & Chuang, 2007). The performance of top services leads to benefits such as trust, confidence, social interaction and customer recognition, thus increasing customer commitment to a long-term relationship. Therefore, employees with better service performance are more successful in building customer relationships and gaining more customers in the long run (Liao & Chuang, 2004, 2007). The service-oriented organization needs care and a service climate to manage the individual and culture at the organizational level to improve service performance.

Self-presentation theory

Self-presentation is premised on Goffman's (1978) as the intentional and tangible component of identity. Erving Goffman popularized the concept of perception management in his book, The Presentation of Self in Everyday Life, where he argues that impression management not only influences how one is treated by other people, but is an essential part of social interaction. Self-presentation is behavior that endeavors to communicate information about oneself, or some image of oneself, to others. It designates a type of motivation in human behavior (Thogersen-Ntoumani and Ntoumanis, 2007). Self-presentation is structured by the primary peer group and the more expansive, partially internalized reference group. Individuals vary in their orientation toward the peer group or the reference group (Thogersen-Ntoumani and Ntoumanis, 2007). Self-presentational motivations are built by the existence of others who convey to the audience. Therefore, group settings boost self-presentational motivations. These motivations are partly good dispositions of individuals, but they rely on situational factors to provoke them (Sedgewick, Flath, & Elias, 2017; Peng et al., 2021a, b).

Hypotheses development

Harris and Ogbonna (2006) conceptualize and test service sabotage, and they suggest that frontline personnel related to customer service are involved. Their results show various individual characteristics, management control efforts and labor market climate associated with service sabotage. In addition, their analysis reveals that the destructive behaviors of services were related to individual and group rewards effects on customers and other managerial measures. Customer mistreatment causes employees to suffer psychologically. Many studies have described how employees respond to customer mistreatment (Meng & Choi., 2021). The primary purpose of sabotage is to create or increase employee self-esteem, and employees often perceive these behaviors as natural and logical (Harris & Ogbonna, 2002). Organizational members can resist individual abuse using a variety of strategies. Prior research has shown that sabotage is likely more pervasive and has a more profound impact on employees in direct contact with customers when there is limited evidence of service. The primary purpose of sabotage is to create or increase a sense of self-worth. Harris and Ogbonna (2006) reported increased self-esteem resulting from service sabotage. Wong and Yang (2020) argue that daily customer abuse significantly predicted customer-directed sabotage. From the point of view of emotional support, employees’ negative feelings intensify the effect of customer mistreatment on sabotage. Prior studies (Harris & Ogbonna, 2009, 2002, Specter et al., 2006; Kao, Cheng, Kuo, & Huang, 2014; Wang et al., 2011; Shao & Skarlicki, 2014) show that if employees encounter rude customers, they might choose a strategy to deal with them, and that is service sabotage. We, therefore, argue that crises, such as the COVID-19 pandemic, can aggravate the condition of customer abuse and employee retaliation (Hwang et al., 2021; Kim et al., 2021). Based on the above, our first hypothesis is as follows:

H1.

POCM positively affects service sabotage.

The source of sabotage is often a hidden phenomenon. Customer mistreatment affects service sabotage, which can affect the performance of services and, ultimately, the growth and profitability of the organization. Recent research argues that sabotage is a rational behavior that stems from a person's reaction to the surrounding environment (Cheng, Guo, Tian, & Shaalan, 2020). In services, it is widely acknowledged that the behavior of frontline employees is the most prominent factor influencing customer perceptions of service performance (Sergeant & Frenkel, 2000) and, ultimately, the organization’s survival (Singh, 2000). A sense of personal mastery, attitude or ability to do work is associated with increased self-efficacy as an important motivating factor (Liao and Chuang, 2007). Employees must show appropriate social feelings during service delivery, essential to maintaining long-term relationships with clients. Employees who are more satisfied with their work are more optimistic, show their feelings at work, interact with customers, and deliver better service performance. Based on these arguments, the following hypothesis is proposed:

H2.

Service sabotage negatively affects service performance.

Service climate is an intangible investment in the workplace that supports service quality (Schneider et al., 1998). Therefore, the service climate should weaken the relationship between social stressors and negative service behaviors. Poor service culture and incivility cannot inspire service enthusiasm (Cheng et al., 2020; Wang and Groth, 2014), and service climate positively affects service personnel’s behavior (Bowen & Schneider, 2014). These cultural-control interventions reduce service sabotage (Harris & Ogbonna, 2002, 2006). A robust organizational climate is associated with managers and subordinates (Morgan et al., 2014). Service climate permeates the workforce and reflects how employees perceive the company as the provider of their expectations (Morgan et al., 2014; Schneider et al., 1998). The high frequency of customer relationships moderated the effects of service climate on customer satisfaction. The authors showed that more contact between employees and customers leads to a stronger relationship between service climate and customer attitudes. In addition, support for resource perspectives, work experience and service commitment regulations have weakened customer abuse (Liao & Chuang, 2004). Reynolds and co-authors argue how the variables of service climate affect overall job satisfaction. Their findings show that job satisfaction, emotional commitment, and organizational citizenship behaviors are generally created when jobs and working climates are inherently motivating, supportive and fair (Reynolds & Harris, 2006, Harris and Ogbonna, 2006).

In addition, some research shows that when retail stores have a poor employee engagement climate, stores can benefit from having employees with a conscience, emotional stability and consistency. Based on the literature on service climate (Schneider et al., 1998), good facilities provide the services of a sub-unit, excellent services and better customer reactions. Studies have repeatedly discovered the relationship between customer service climate and customer service outcomes. Research has shown a relationship between service and performance climate using employee self-reporting, regardless of the views of those who received the service (Salanova, Agut, & Peiró, 2005). Moreover, a favorable service environment positively affects customer loyalty (Ma et al., 2021). The results of a study noted that employees who have experienced a positive service climate are more likely to provide positive service experiences (Liao & Chuang, 2007).

Along with the research on service climate, prior studies have discovered the relationship between service climate and customer outcomes (Schneider et al., 1998). Liao and Chuang (2004) examined the relationship between customer perception of service quality and employee perception of service climate. The results also show that services in a work unit may affect employee performance in a department, from top to bottom (Liao and Chuang, 2004). Services are positively related to employee performance (Liao and Chuang, 2004). Therefore, service climate may affect customer loyalty by undirecting employee performance appraisal. Zoghbi-Manrique-de-Lara, Aguiar-Quintana, & Suárez-Acosta (2013) shows that reducing customer loyalty is a reaction to perceived injustice and engaging in infidelity and inefficient behavior. Service climate penetrates all company levels, including front-office employees and customer relationships. By adopting market orientation, the company sends a message about its evolving culture to the frontline employees and determines the climate it expects them to offer customers (Morgan et al., 2014). Theories of service and research climate emphasize that it is the staff's experience that reports customer service quality (Hwang et al., 2021), customer satisfaction (Dean, 2004; Ma et al., 2021) and customer loyalty (Liao and Chuang, 2004). As one of the organizational characteristics, Dean (2004) states that service climate can play an essential role concerning organizational and customer variables. Some researchers argue that intermediation in service climate led to organizational resources and job interaction predicting service climate, indicating employee performance and customer loyalty (Kao et al., 2014). Based on the above, we hypothesize the following:

H3.

Service climate affects service performance positively.

H4.

Service climate moderates the relationship between POCM and service sabotage.

Figure 1. graphically illustrates the conceptual framework proposed in this study.

Method and analysis

The data used in this study were obtained from F&B frontline employees working in restaurants in Tehran, Iran. We applied systematic random sampling. According to Hair, Babin and Anderson (2010), the estimated sample size for models with five or fewer constructs relates to at least 100 restaurants for our model. Before selecting the restaurants to be included in the sample, some considerations had to be made, such as restaurant class, customer diversity, number of customers, and high communication between employees and customers. First, Tehran restaurants were classified into seven regions based on their location. Then, in each region, restaurants were selected based on their class and service level. To determine the class of restaurants, we had two references: Firstly, the official classification, which is the basis of the menu pricing by the city authorities, and secondly, the reliable rating websites in determining the class and level of luxury of the restaurants. We ensured that the selected restaurants had set rules and frameworks in the pandemic situation. Moreover, the restaurant manager or the owner informed about the study’s purpose and the levels of access to information beforehand.

Some managers were concerned that discussing the questionnaire questions among employees might lead to conflict, so we tried to address their concerns beforehand. Due to the nature of our research subject, some restaurants resisted cooperating with us or were initially prejudiced or denied the issue of mistreatment and retaliation in their restaurant. We talked to the managers about maintaining confidentiality and sending them final information in the form of a report after completing the analysis. Then the interviewees were selected. In the selection of responses, we aimed to select managers and executive supervisors, who deal with customers to some extent, and on the other hand, are relatively familiar with the management plans and rules of the restaurant or have participated in setting them up. Questionnaires were distributed at times when the employees had the necessary concentration. After the data collection, it was found that some of the respondents left certain questions unanswered, especially the questions related to employee retaliation, so these questionnaires were deleted. Finally, after two pretest rounds, the questionnaires were sufficient, and the analyses were conducted accordingly. According to the estimated sample size, 260 questionnaires were distributed among respondents. More than 5% missing data were removed, and 165 final questionnaires were analyzed, indicating a response rate of 0.63. Descriptive statistics were obtained using the SPSS software (see Table 1) and structural equation modeling (SEM) was used to test the hypotheses developed in the study (see Table 6). SEM is the primary analytical method used to develop and test structural path models. Statistical significance for all path coefficients was tested based on the critical ratios, i.e., parameter values divided by corresponding standard errors. Descriptive statistics, including frequency distribution, central tendency and variability of a dataset, was done using SPSS. Ordinary least squares (OLS) were employed for the inner and outer models using the AMOS 26 software. To further evaluate the measurement items used in the study, factor analysis (FA) was performed. Generally, the variable of interest was determined among the coherent subsets relatively independently, i.e. confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) using two-factor analysis techniques. EFA aims to find out and give the current information and data about the possible factors best representing the researcher’s data (Hair, Black, Babin, & Anderson, 2012).

Furthermore, the CFA is used to verify the measurement factors within the set of variables in the theoretical model, and SEM is used to perform the CFA. We aimed to investigate the validity of the survey instrument up to this study stage; therefore, the latent variables’ theory is verified using CFA‏.

Convergent validity means the degree of agreement of several items to measure the same concept. Hair et al. (2010) suggests that the composite reliability, factor loadings and average variance extracted (AVE) are assessed for convergence validity. The AVE of all values is >0.5, and composite reliability (CR) values are of >0.7. More precisely, values of CR range from 0.728 (cultural aspects) to 0.791 (general mistreatment), and values of AVE range from 0.526 (general mistreatment) to 0.689 (cultural aspects).

After removing the items with too low factor loadings (P7, Ss6, Ss3), the fit indices improved and reached an acceptable level. Tables 2 and 3 indicate the different measures applied in this study and their results. Convergent validity was confirmed, so discriminant validity was also assessed. Discriminant validity means the differentiation of constructs in the items or measurement of the different concepts. The AVE is compared with the squared correlations, or the square root of the AVE is compared with correlations to assess this. Table 4 shows that the AVE's square root is compared with the second method's correlations. According to the criteria, the larger square root of the AVE, as shown in the diagonals, compared to the values in the columns and rows of the particular construct shows the measures' discriminant validity. Table 4 shows larger values in the diagonals than the values of their related row and column. Thus, the results of Table 4 show sufficient discriminant and convergent validity.

The model’s overall fit was the last remaining criterion to analyze the covariance-based structural equation model (SEM) created using the structural model analysis applying AMOS. The incremental fit index (IFI) is used to test if the model improved on a baseline model, which is usually a model of uncorrelated variables or independence; RFI: the Relative Fit Index, also known as RHO1, is not guaranteed to vary from 0 to 1. However, RFI close to 1 indicates a good fit. RFI variations are not explicitly designed to give penalties for less parsimonious models such as non-normed fit index (NNFI or TLI or Tucker–Lewis index), the normed fit index (NFI) and no centrality-based indices to calculate no centrality parameter by subtracting the model’s degrees of freedom from the chi-square (χ²/df) such as root-mean-square error of approximation index (RMSEA) and the comparative fit index(CFI). NFI/NNFI/TLI: The (Non) Normed Fit Index. An NFI of 0.95 indicates the model of interest improves the fit by 95\ NNFI (also called the Tucker Lewis index; TLI) is preferable for smaller samples. They should be >0.90 (Byrne, 1994) or >0.95 There was a statistically significant overall Chi-square for the four variables in the model, and the ratio of the chi-square to degrees of freedom(X²/df) (x2=2015.52,df=695; x2df=2.900), CFI, RMSEA, NFI, GFI, AGFI and TLI has also examined. GFI/AGFI: The (Adjusted) Goodness of Fit is the proportion of variance accounted for by the estimated population covariance. Analogous to R2. The GFI and the AGFI should be >0.95 and >0.90, respectively. All fit indexes indicate a good fit of the measurement model. Table 5 shows an “acceptable fit” to the data based on the fit indices (see Table 6).

The estimation of the path‏ coefficient s(β), coefficient of determination R-square for the endogenous variable, t-value and effect size (f-square) were the primary criteria used to assess the structural model in this study (Tenenhaus, Vinzi, Chatelin, & Lauro, 2005). Based on the results, customer mistreatment (β = 0.44; P < 0.01) positively affects service sabotage, and service climate (β = −0.269; P < 0.01) negatively affects service sabotage. Therefore, hypotheses H1 and H2 are confirmed. Service sabotage (β = 0.05; P > 0.05) does not affect service performance, but the service climate (β = 1.026; P < 0.01) has a positive effect on the service performance. Therefore, H3 is not confirmed, whereas H4 is confirmed. Overall, 34% of the variance in service performance was explained by the model (R² = 0.48). The moderator variable is divided into upper and lower groups. The difference value of these coefficients has a z-factor equal to −2.915, measured at an error level of <1%. As a result, service conditions significantly impact the relationship between customer abuse and service sabotage. Given the amount of beta in conditions where service conditions are poor, the effect of customer abuse on service sabotage is more substantial than in conditions where service conditions are vital.

Discussion

This study aimed to investigate the effect of pandemic-induced customer mistreatment on employee sabotage and service performance with the moderating role of the service climate. One of our examined variables is POCM, which has a positive relationship with service sabotage. Harris and Ogbonna (2006) showed that employees might sabotage services when customers are rude to employees. When customers mistreat frontline employees, many frontline employees, instead of being passive recipients, adopt a strategy to combat service sabotage (Spector et al., 2006). Pandemic conditions lead to reduced interactions and an even quieter atmosphere inside service spheres, in which some customers are more inclined to self-expression.

The correlation between customer mistreatment, service sabotage, and service climate was confirmed. When employees face low-quality behavior from customers, they deal with customers according to the degree of their type of treatment. Meanwhile if employees understand the organization’s practices in such a way that if they provide quality services to customers, they will be supported by top-level managers (Schneider et al., 1998; Salanova et al., 2005). According to Kao et al. (2014), who examined the factors of social stressors and service sabotage, the vital component of service climate is service upgrades. If the company provides good service, high-quality service behaviors can be displayed even when employees encounter rude customers. Service disruption usually leads to decreased customer satisfaction, perceived service quality and value. With low satisfaction, consumers spend less, and their loyalty decreases. A crisis, such as the global COVID-19 pandemic, can affect customer expectations in cases such as speed in service delivery and the level of health observed, which may ultimately lead to a decrease in customers’ level of satisfaction (Ding & Jiang, 2021). Ultimately, it would affect the output and performance of service companies (Harris and Ogbonna, 2002; 2006). Service-oriented organizations therefore need good care and a reasonable service climate at the organizational level to improve service performance (Kao et al., 2014). Research has shown that the existence of service climate is positively related to the performance of service personnel (Liao and Chuang, 2004). This study shows that customers perceive their overall evaluation of a service provider and do not generalize an unpleasant personal experiment.

Surprisingly, we did not see enough evidence of the effect of employee sabotage on performance because of no significant path between the constructs, which can be interpreted in several ways. First, in many service sections like restaurants, employee sabotage may occur gradually, so the restaurant’s image may not be affected. Furthermore, when customers become attached to a service provider’s brand, such as a restaurant, they often overlook the missteps and defects of employees. According to our results, service climate has a positive effect on performance, and creating a positive service climate in the organization is associated with better performance of employees generally and in a crisis, such as the COVID-19 pandemic.

Theoretical contributions

One of the novel contributions of our study stems from the modeling and operationalization of a framework of service sabotage dynamics (in pandemic situations). As our results show, employees ask customers to change their “normal” behaviors due to pandemic circumstances, thus providing the ground for mistreatment or defiance of customers, which can eventually lead to sabotage behaviors. Accordingly, we developed a model to theorize this discussion that could shed light on some new aspects of the client’s behavior in a crisis situation, such as the COVID-19 pandemic. Moreover, the research results show that service climate is considered an influential factor between customer mistreatment and service sabotage, which contributes to the literature in the field, such as the demand support model, theory of resource conservation and the barrier challenge framework that have to our knowledge so far only explained the relationships between stressors and behaviors. In this study, the self-presentation theory was used to provide a novel analysis perspective to show the demonstrative behaviors of customers to attract the attention of others in a service space, which has not been considered in the literature.

Furthermore, our results contribute to self-presentation theory. This theory is used in the positive aspects of behavior, which this study showed that pretentious actions could occur based on misbehavior. In addition, this study showed that restrictive conditions could stimulate the emergence of self-presentational behaviors.

Practical implications

This study finds that restaurant rules in a crisis situation can affect customer behavior, in that customers’ views and expectations should be considered in the provisions of these rules. The way they are presented should not provoke destructive behaviors. It is especially applicable for service providers whose mission is to provide quality to customers. Furthermore, managers should consider that a well-managed service atmosphere can mitigate the effects of inappropriate behaviors in the service environment when formulating their operational strategies. One of the strategies that a service company could use to prevent customer mistreatment is to provide emotion management advice for employees suffering from customer mistreatment.

Given that empirical evidence suggests that employees’ perceived social support in the workplace can be affected by customer mistreatment (Wang et al., 2011), managers may provide more support (e.g., organizational support). The service delivery often depends on the attitude and behavior of frontline staff on the one hand and customer expectations on the other hand. Managers should therefore consider the source of the problem before investigating service sabotage. It requires a precise strategy of exploiting existing customer and employee surveys or collecting other relevant data. Our findings additionally have practical implications for hiring and promoting employees with specific personalities who can provoke a positive service climate. We highly recommend training, job enrichment, improving a positive service culture and developing a better monitoring system to prevent service sabotage. The possibility that employees from different countries and cultures react differently to customer mistreatment is essential for multinational service companies with a diverse workforce. Furthermore, state and local authorities are advised to consider regional culture when making regulations related to the pandemic. Also, regulations should not only be punitive, and incentives can also influence the motivation of restaurant owners.

Limitations and avenues for future research

Some limitations should be noted regarding our findings. One limitation is the self-reported nature of the study, which can affect the results, especially in measuring sabotage. Future research can tackle this problem by using a combination of qualitative or laboratory research on top of quantitative surveys. Nevertheless, we controlled for the influence of social desirability bias, and it is unlikely that the relationships analyzed in the current study were affected by common method bias. Future studies may derive outcomes and objective measures based on alternative data sources like restaurant customers’ online comments. In this study, restaurant hours were reduced due to corona conditions. We did not measure the effect of working hours during the day, which can be due to increased workload and employee fatigue on the results, especially on behaviors such as sabotage. Given that we studied the views of frontline employees, some of them may have responded conservatively. Upcoming research could examine twofold perspectives (customer and employee) and either consider employees or use qualitative research to overcome this limitation.

Notwithstanding the limitations, our study develops theoretical discussions on this issue. An implication arises from finding significant links between antecedent variables and service sabotage. A longitudinal study could enrich the findings and generate a deeper understanding of the dynamics of service dysfunction considering other organizational variables (e.g., human resource management programs). Given that any perception of positive and negative customer behavior has perceptual roots, future studies may focus on the deeper aspects of employees’ perceptions of service functions.

In conclusion, in this study, we analyzed customer mistreatment through the self-reported approach. Future research can further use and further extend our model to explain and conceptualize customer-oriented employee sabotage in the service environment. Furthermore, prior literature has focused on the one-to-one interaction between the abuser and the saboteur. In this paper, we found evidence of the “spillover effect.” An employee may pass his displeasure with a customer's behavior to other innocent customers. This phenomenon can be analyzed as an independent construct in future studies and fills an essential gap in the literature. Furthermore, it is widely accepted that even with the end of the COVID-19 pandemic, the behavior of people and customers will not fully return to what it was before (Kim et al., 2021). We believe that some of the existing misbehaviors will continue after the end of the pandemic. Particularly in the case of reactions affected by demonstrative behaviors, it can be argued that our results and analyses will also be valid in future periods of crises. We therefore suggest that future research could further explore the breadth and range of our findings in the post-COVID-19 era to validate the findings of the proposed conceptual model.

Figures

Figure 1

Conceptual framework

Table 1

Descriptive statistics

Variable	Type	Frequency
Gender	Male	135
	Female	30
Age	18–25	22
	26–35	79
	36–45	45
	+45	19
Employee Work Experience	Less than one year	16
	1–10	86
	11–20	43
	21–30	11
	31–40	9
Restaurant age	Less than one year	9
	1–10	98
	11–20	23
	21–30	11
	31–40	15
	+40	9
Class level	High	25
	average	118
	Less than average	22

Table 2

Reliability, Convergent and discriminant validity

Index	Critical value
Reliability	• CR > 0.7
Convergent validity	• Loading factors are significant at p < 0.05 • Loading factor > 0.5 • CR > AVE • AVE > 0.5
Discriminant Validity	• AVE > MSV

Note(s): AVE=Average Variance Extracted, CR=Composite Reliability, CA=Cronbach Alpha, MSV= Maximum square variance

Table 3

Measurements

Item description	Item	Factor loading	Sub-variable	Variable
Some customers had excessive demands	GM1	0.46	GM	Customer mistreatment
Some customers thought they were more important than others	GM2	0.37
Wrong mood customers have emptied themselves on my head	GM3	0.61
We usually encounter inappropriate customer behavior if we make a small mistake while serving	GM4	0.51
Customers insisted on a request irrelevant to my service only to attract attention	GM5	0.62
Some customers used arrogant words to deal with us	GM6	0.55
Customers wanted the restaurant staff to do their desired work under the pretext of pandemic conditions	PRD1	0.39	PRD
When we reminded them of social distancing, they spoke violently to attract the attention of others	PRD2	0.65
Customers are angry at us, even in requests to comply with trivial principles of pandemic behavior	PRD3	0.66
Customers refused to listen about obedience to health issues	PRD4	0.53
Customers doubted our information about Corona in front of others	PRD5	0.54
Customers did not care about restaurant rules	PRA1	0.46	PRA
Customers have complained about the restaurant's corona rules for no reason	PRA2	0.49
Customers were shouting at me when I notified them of the pandemic rules	PRA3	0.59
While talking about the rules during the pandemic, they cut us off	PRA4	0.63
Customers made requests that we could not provide	PRA5	0.55
Customers’ patience decreased during the pandemic	PRA6	0.39
Some of the customer abuse is to express and attract attention	PRA7	0.57
Employees sabotage rude customers	Ss1	0.46		Service Sabotage
Employees are forced to rush customers when they want to (e.g., rushing them to eat)	Ss2	0.38
In this restaurant, I think an employee’s sabotage is somehow due to previous complexities of other violent customers	Ss3	0.26
Sometimes, staff transfers the grief from one customer to other innocent customers	Ss4	0.52
Sometimes, employees shake hands with customers to make others laugh	Ss5	0.52
Employees never show off in front of customers	Ss6	0.25
When employees are upset about a particular customer's behavior, they usually think about it for a long time and think of retaliation	Ss7	0.44
Employees sometimes slow down service on purpose	Ss8	0.26
In a pandemic situation, you never intentionally mistreat customers	Ss9	0.50
If the restaurant’s atmosphere is good, the customers will ignore an inappropriate experience	C1	0.58		Service Climate
I think the effort to measure and track the restaurant’s atmosphere to make it tranquil is quite enough	C2	0.75	C
I love and respect the hospitality culture in this restaurant	C3	0.71
I admire the efforts made at my workplace to create the proper relationship between employees and customers during a pandemic	C4	0.70
Employees receive praise and reward for service in pandemic situations	M1	0.45	M
Managers support to make adequate efforts in the quality of services	M2	0.66
There are enough tools and equipment provided for employees to offer excellent quality service	M3	0.67
Your overview of the restaurant’s performance in gaining customer satisfaction	p1	0.72		Performance
Customers praise the quality of our services to others	p2	0.89
The volume of our customers has increased compared to previous periods	p3	0.57
Financially, our profitability and input have been upward compared to previous years	p4	0.60
Customers love the atmosphere of the restaurant	p5	0.44
We provide different/customized service options to customers	p6	0.37
Our customers are loyal and have a unique sense of closeness	p7	0.30

Note(s): GM: General Mistreatment PRD: Pandemic Restriction Diversion PRA: Pandemic Rules Aggression

SS: Service Sabotage M: Managerial Aspects C: Cultural Aspects

Table 4

Square root AVE and correlations of latent variables (discriminant validity)

Latent variable	CR	AVE	MSV	GM	SS	SP	PRA	C	M	D
General mistreatment	0.791	0.526	0.399	0.725
Service sabotage	0.757	0.535	0.179	0.436	0.731
Service performance	0.737	0.591	0.156	−0.051	−0.191	0.769
Pandemic rules aggression	0.769	0.539	0.434	1.026	0.564	−0.082	0.734
Cultural aspects	0.728	0.689	0.238	−0.001	−0.241	0.702	−0.186	0.831
Managerial aspects	0.729	0.641	0.248	−0.043	−0.488	0.614	−0.229	0.893	0.804
Pandemic restriction diversion	0.778	0.542	0.433	1.072	0.481	−0.152	1.067	−0.214	−0.135	0.736

Note(s): AVE=Average Variance Extracted, CR=Composite Reliability, MSV= Maximum Shared Variance

Table 5

Model fit summary

Model	Chi-square	DF	Chi-square/DF	NFI	IF	TLI	CFI	RMS	GFI	AGFA
Value	108.68	52	2.07	0.914	0953	0.93	0.949	0.07	0.846	0.824
Critical value	–	–	<3	>0.9	>0.9	>0.9	>0.9	>0.9	>0.8	>0.8

Table 6

Hypothesis testing

Hypothesis	Beta	t-value	P	R2	Result	Sign
Customer mistreatment - > Service sabotage	0.44	3.301	0.001	0.34	Supported	+
Services climate - > Service sabotage	−0.27	−2.917	0.004		Supported	–
Service sabotage - > Service performance	0.05	0.547	0.584	0.48	NS
Services climate - > Service performance	0.93	6.195	0.001		Supported	+

	Low		High		z-score	Result
	Beta	P	Beta	P
Customer mistreatment - > Service sabotage	0.428	0	0.254	0	−2.915	Supported

Note(s): Standardized coefficient beta (β)