Customer Ethnic Bias in Service Encounters

Abstract

As ethnic diversity continues to rise, customer bias in interethnic service encounters becomes an increasingly problematic issue for the parties involved, the service firms, and society at large. Against this background, the aim of our research is to examine ethnically biased customer responses, their key psychological mechanisms, and the effectiveness of enacted service scripts to shape interethnic service encounters. Building on the aversive racism framework and homophily theory, we propose a baseline effect of majority customers’ ethnic bias toward minority employees in the form of less positive behaviors in interethnic service encounters. In an initial laboratory study, we use experimental video simulations of frontline service encounters and confirm the robustness of this effect across two replications. In a subsequent field experiment, we test an extended framework of customer responses to interethnic service encounters, finding that customers’ experience of rapport and identification with the firm represent two serial mediators that facilitate the effects of interethnic service encounters on customer loyalty intentions. Together, these contributions enrich our understanding of how psychological mechanisms facilitate the incidence of ethnically biased customer behavior and also provide insights into viable ways to improve such encounters.

Keywords

ethnic bias service encounters rapport customer-company identification homophily stereotyping frontline marketing

Rising ethnic and racial¹ diversity is a prominent sociodemographic trend, especially in developed economies (Organization for Economic Cooperation and Development 2017). The United States appears to be progressing toward plurality, such that minority populations are anticipated to more than double in size by 2060 (Colby and Ortman 2015). In terms of workforce integration, ethnic minorities constitute a disproportionally larger share of people holding service jobs in the United States and Europe (Urso and Schuster 2013; U.S. Census Bureau 2019). In turn, the number of interethnic service encounters is bound to continue to increase, and to the extent that these encounters involve distinct psychological or behavioral dispositions, such as ethnic biases, they will pose a growing challenge to the management of contemporary service encounters.

Prior research highlights the effects of customers’ demonstrated behaviors on employees’ well-being (Gong, Yi, and Choi 2014), showing that negative customer behaviors lead to job stress and burnout (Grandey, Dickter, and Sin 2004), absenteeism, and turnover (Singh, Goolsby, and Rhoads 1994). Customers’ ethnic bias in particular can exert a destructive impact on the individual employee and the service organization (e.g., Grandey, Dickter, and Sin 2004; Kern and Grandey 2009). Empirical findings show that customer ethnic bias manifests in decreased levels of satisfaction with employee performance (Etgar and Fuchs 2011; Lynn and Sturman 2011), less favorable tipping behaviors (Lynn et al. 2008), and negative customer evaluations of the service facility and the organization overall (Hekman et al. 2010). Ethnically biased customer behavior also can create stress for minority service employees (Kern and Grandey 2009), which may partially account for their higher rates of health-related absenteeism (James 1997) and increased risk of stress-related cardiovascular diseases (Pascoe and Smart Richman 2009), both of which have been associated with job burnout (Melamed et al. 2006). Workplace stress also tends to affect job performance and service outcomes (Crosno et al. 2009) and may exacerbate the already high turnover rates in service industries (Ziobro and Morath 2015).

Despite the destructive consequences of customer ethnic bias for individual consumers and service firms, few studies have investigated the key psychological mechanisms through which interethnic service encounters affect customers or the effectiveness of various service design elements that might be deployed constructively in these settings. Examining such effects could advance both scholarly service research and management practice, through an enhanced theoretical understanding of the psychological processes underlying ethnically biased customer behavior, as well as a clear specification of effective strategies service firms can use to shape interethnic service encounters positively and respond constructively to a changing society.

Accordingly, the aim of this research is to examine ethnically biased customer responses, their key psychological mechanisms, and the effectiveness of enacted service scripts (i.e., elevating employee exit friendliness) to shape interethnic service encounters. Building on the aversive racism framework (Dovidio and Gaertner 2004) and homophily theory (McPherson, Smith-Lovin, and Cook 2001), we propose a baseline effect of majority customers’ ethnic bias toward minority employees in the form of less positive behaviors in interethnic service encounters. In an initial laboratory study, we use experimental video simulations of frontline service encounters (e.g., Pham, Hung, and Gorn 2011) and confirm the robustness of this effect across two replications (Wagner, Lutz, and Weitz 2009), referring to employee order taking and complaint handling scenarios. In a subsequent field experiment, we test an extended framework of customer responses to interethnic service encounters, which exhibits a serial mediation structure (e.g., Hayes 2018).

The framework includes three independent variables, namely, customer and employee ethnicity (i.e., belonging to the country’s ethnic majority or not) and a service script that emphasizes employees’ exit friendliness, that is, the employee’s friendliness after the service interaction has ended (Albrecht et al. 2017). Loyalty intentions provide the ultimate downstream variable, and we include customers’ experience of rapport and identification with the firm as two serial mediators in that sequential order. The field experiment reveals a two-way interaction, such that majority customers experience superior levels of rapport with majority than with minority employees, but no corresponding effect emerges for minority customers (i.e., no increased levels of rapport with minority employees). Demonstrated exit friendliness increases experienced rapport, in an effect that is generally more pronounced for minority employees, as reflected in another two-way interaction. That is, exit friendliness has a greater positive impact on minority employees, independent of the customers’ own ethnic background. Finally, customer rapport increases identification, which in turn predicts loyalty intentions, facilitating the indirect effects of the two interactions on the final outcome variable.

With these findings, the present research offers four contributions to existing literature. First, we demonstrate that customers’ actual behavior during personal encounters with service employees is subject to ethnic bias. Previous services marketing research has established that this bias affects impersonal postinteraction outcomes such as covert evaluations of the employee and the organization (e.g., Bharadwaj and Roggeveen 2008; Hekman et al. 2010; Ouellet 2007). Our laboratory simulations confirm how ethnic bias manifests directly during personal encounters. Second, to the best of our knowledge, this work is the first to examine customer ethnic bias in service encounters with a field experiment using both actual customers and frontline employees in a real-life service environment. Existing studies tend to survey customers exclusively (e.g., Klinner and Walsh 2013). With the evidence from the field experiment, we can draw causal inferences about the proposed relationships and also affirm the external validity of this important effect. Third, this study provides initial insights into the central psychological mechanisms that facilitate customers’ information processing in interethnic service encounters. Moving beyond direct outcomes of customer ethnic bias in services, we shed light on the mediating, indirect effects that explain customer reactions, in terms of their loyalty intentions. Specifically, we introduce customers’ experience of rapport and subsequent identification with the firm as effective mediators. Fourth, the findings provide guidance for organizational efforts geared toward improving the effectiveness of interethnic service encounters by highlighting the positive impact of elevated exit friendliness for minority frontline employees. Together, these contributions enrich understanding of how psychological mechanisms facilitate the incidence of ethnically biased customer behavior and also provide insights into viable ways to improve such encounters.

In the next section, we review research pertaining to the cognitive and motivational foundations of ethnic customer bias. We then detail our research hypotheses and present our conceptual framework. Next, we test the baseline effect proposed in the first hypothesis with a video-based laboratory simulation and examine the subsequent hypotheses with a field experiment. We conclude with reflections on the implications and limitations of this research for both literature and service management practice.

Theoretical Background

Aversive Racism

Overt expressions of ethnic prejudice generally have been decreasing in Western societies (Greenwald and Pettigrew 2014), but social psychology research demonstrates that these societies are by no means “color blind,” and ethnicity and race still represent major social categories that critically and often automatically affect intergroup relations (Boshoff 2012; Dovidio and Gaertner 1993). The resulting effects include less positively toned behaviors of ethnic majority members toward minority interaction partners (Vorauer and Turpie 2004). As a consequence, interethnic interactions often elicit feelings of self-consciousness and discomfort (Crocker, Major, and Steele 1998) or negative emotional responses, such as anxiety and anger (Brown and Kirmani 1999), among the parties subjected to this kind of discrimination.

Noting the overall decline of overt prejudice, researchers explain these findings as manifestations of unintentional, subtle forms of bias and propose terms such as “modern racism” (McConahay 1986), “symbolic racism” (Sears 1988), or “aversive racism” (Dovidio and Gaertner 2004), which can operate even among well-intentioned members of ethnic majorities. Dovidio, Gaertner, and Pearson (2016, p. 96) define aversive racism as “a form of individual-level prejudice characterizing the thoughts, feelings, and behaviors of the majority of well-intentioned” people, and they further reason that members of ethnic majorities who engage in aversive racism “believe that they are not prejudiced, but […] unconscious negative feelings and beliefs get expressed in subtle, indirect, and often rationalizable ways” (Dovidio, Gaertner, and Pearson 2017, p. 270).

Although qualitatively different from more overt forms of prejudice, this contemporary form of bias significantly affects the course and quality of interethnic interactions in a wide range of social realms (Kleinpenning and Hagendoorn 1993). The aversive racism framework posits that contemporary ethnic bias gets expressed in indirect ways that do not threaten the dominant group member’s (i.e., aversive racist’s) self-image as unprejudiced (Dovidio, Gaertner, and Pearson 2017). In this view, members of ethnic majorities show bias against members of ethnic minorities in “a context in which there is a plausible, nonprejudiced explanation available for what might be considered prejudiced behavior” (McConahay 1986, p. 100). For example, in simulated personnel decision tasks, members of the ethnic majority tend to choose a lower ratio of members of minorities when applicants’ qualifications are moderate, whereas when the qualifications are unambiguously weak or strong, bias does not affect the selection process (Dovidio and Gaertner 2000). The central premise of the aversive racism framework thus is that many members of ethnic majorities unconsciously and unintentionally maintain negative intergroup attitudes, even if they endorse norms of egalitarianism and reject explicit out-group negativity (Dovidio, Gartner, and Pearson 2016).

Customer Bias in Interethnic Service Encounters

Similarly, customers’ ethnic bias may influence service encounters with minority members of the work force, in that these intergroup situations evoke cognitive and motivational processes that likely result in behaviors favoring a social in-group. Ethnicity and race function as primary social groups that shape people’s similarity judgments, and people commonly categorize their interaction partners into ethnic in- or out-groups in a virtually automatic way (Dovidio and Gaertner 1993; Johnson, Meyers, and Williams 2013). This subconscious classification drives bias, according to the aversive racism framework, and prompts homophily effects (Page-Gould and Mendoza-Denton 2011). Homophily is the degree to which associated people tend to be similar in social attributes (e.g., age, attitudes, values, ethnicity), and it shapes social interactions in general (McPherson, Smith-Lovin, and Cook 2001) and customer service perceptions in particular (e.g., Dellande, Gilly, and Graham 2004; Mai and Hoffmann 2011; Rosenbaum and Walsh 2012). A preference for interactions with similar others or members of an in-group influences emotional, cognitive, and behavioral elements of intergroup contacts. That is, people automatically favor members of their in-group and experience more positive affect toward them than toward members of another ethnic group (Otten and Moskowitz 2000). Moreover, identified members—or people who express a feeling of “oneness with or belonging to a group” (Ashforth and Mael 1989, p. 34)—find interactions with other members of this group more rewarding because they obtain validation of their perceptions and views (Byrne 1961).

In terms of cognitive outcomes, people process information about members of their in-group with greater elaboration (Park and Rothbart 1982), whereas they encode and store less positive information about members of other groups, which augments their readiness to develop and maintain negative stereotypes and prejudices (Howard and Rothbart 1980). In terms of behavioral outcomes, people prefer members of their own group (vs. other groups) in reward allocations and demonstrate more helping behaviors (Dovidio et al. 1997), greater effort allocations (Worchel et al. 1998), less greed, and more trustworthy behaviors in such interactions (Insko et al. 2001). Therefore, own-group favoritism exerts a dual effect, insofar as it tones emotional, cognitive, and behavioral outcomes toward own-group members positively while also promoting more negative and biased intergroup behavior including ethnic discrimination (Allport 1954; Dovidio et al. 2010). We thus hypothesize the following hypothesis:

Hypothesis 1: Majority customers demonstrate more positive behaviors toward majority than toward minority employees in service encounters.

Psychological Processing of Interethnic Service Encounters

Beyond the baseline effect predicted in Hypothesis 1, whereby ethnic majority customers display less positively toned behavior toward minority employees, we investigate to what extent interethnic service encounters shape socially oriented service process elements such as rapport. As suggested by aversive racism literature, interethnic bias is an unintentional phenomenon that shapes the quality of service encounters (Dovidio et al. 2002). For example, this bias could increase the speed of the speech of the dominant group member as well as the duration and perceived warmth of interactions (Dovidio, Gaertner, and Pearson 2017). Because service encounters with members of another (vs. own) group may be laden with bias, they also may shape important customer outcomes such as rapport, identification with the service firm, and loyalty intentions.

Based on the notion that customers prefer interactions with homophilous others, we predict that customers prefer friendly relationships with others who are like them in terms of key traits such as ethnicity (McPherson and Smith-Lovin 1987). Line, Hanks, and Kim (2018) point out that a perceived sense of similarity translates into increased interaction levels and identification with the service organization, and Dellande, Gilly, and Graham (2004) maintain that homophily fosters relationships based on liking. This similarity-based sense of liking and emotional attachment in turn leads to customer rapport perceptions (e.g., Bernieri et al. 1996). According to Gremler and Gwinner (2000, p. 92), rapport represents “a customer’s perception of having an enjoyable interaction with a service provider employee, characterized by a personal connection between the two interactants.” Majority customers may have less favorable rapport experiences when interacting with ethnic service employees because they evaluate the service encounter on the basis of their previously formed stereotypes (Mai and Hoffmann 2011). In line with the premise that customers prefer and are more comfortable with interactions with demographically homophilous service employees, we predict that customers and employees are less likely to “click” in interethnic encounters. By the same rationale, ethnic minority customers should find interactions with minority employees more rewarding, resulting in more positively toned behavior toward this type of employee and more positive customer outcomes.

Hypothesis 2: The interaction of customer and employee ethnicity affects customers’ experience of rapport in service encounters, such that (a) majority customers experience greater levels of rapport with majority than with minority employees and (b) minority customers experience greater levels of rapport with minority than with majority employees.

Customers’ experience of rapport represents a potent mechanism for establishing healthy customer-firm relationships, by creating favorable associations with frontline employees (Yim, Tse, and Chan 2008). Rapport occurs when customers experience a personal interaction with a service employee as enjoyable, accompanied by feelings of personal connection (Gremler and Gwinner 2000). Rapport is not necessarily the outcome of a series of personal interactions but even can emerge during a single, emotionally affective service encounter (Hennig-Thurau et al. 2006). According to extant research, rapport exerts a positive impact on customers’ various perceptions and evaluations of service delivery (e.g., DeWitt and Brady 2003), yet its impact on customer–firm identification generally has not been tested, despite evidence that customers’ interactions with well-liked service employees increase their identification with the firm (e.g., Marín and de Maya 2013). This effect occurs because positively valenced encounters help customers evoke favorable, self-relevant information from memory (Ahearne, Bhattacharya, and Gruen 2005). Translating this rationale to our study context and acknowledging that rapport is an emotional psychological response (Tickle-Degnen and Rosenthal 1990), we propose the following hypothesis:

Hypothesis 3: Customers’ experience of rapport increases their identification with the firm.

From a consumer perspective, identification with the firm entails “perceived oneness with or belongingness to an organization” (Bhattacharya, Rao, and Glynn 1995, p. 46). In an attempt to determine the consequences of such identification, Bhattacharya and Sen (2003) show that it motivates consumers to engage in favorable and potentially unfavorable company-related behaviors. Otherwise, research regarding identification with the firm and its economically relevant downstream consequences is limited, so we turn to related research settings. For example, Ahearne, Bhattacharya, and Gruen (2005) show that identification with the firm increases consultancy product utilization, and Bhattacharya, Rao, and Glynn (1995) detect a positive effect on repurchase frequency among art museum members. We also note evidence of the effects of customer–brand identification on word-of-mouth intentions (Kuenzel and Halliday 2008; Tuškej, Golob, and Podnar 2013), consumer commitment (Tuškej, Golob, and Podnar 2013), and brand loyalty (He, Li, and Harris 2012; Homburg, Wieseke, and Hoyer 2009; Kuenzel and Halliday 2010). From this basis, we propose the following hypothesis:

Hypothesis 4: The joint effect of customer and employee ethnicity on loyalty intentions is serially mediated by customers’ rapport and identification with the firm.

Scripting Friendliness in Interethnic Service Encounters

Customers generally expect a display of positive affect, in the form of friendliness, during interactions with service employees (Albrecht et al. 2017; Ashforth and Humphrey 1993). Employee friendliness also prompts important customer outcomes such as behavioral intentions (e.g., Tsai and Huang 2002), such that customers generally respond favorably to employee displays of friendliness.

Beyond these general influences though, Mullen’s (1991) meta-analysis indicates that members of both minority and majority populations tend to maintain stereotypes about a given minority, whereas members of the majority are less likely to make stereotypical assumptions about their own (majority) population. This asymmetric effect likely stems from the smaller group size of the minority population, such that their group membership is more salient and reinforces the typicality of this minority group. That is, “the smaller proportionate size of the minority makes it stand out, and thereby leads to an overestimation of the prevalence of the minority (both by the minority and by the majority)” (Mullen 1991, p. 303). A similar effect arises between low- and high-status groups of a society, such that the low-status group tends to be subject to higher levels of stereotyping by members of both the low-status and the high-status groups (Cadinu, Latrofa, and Carnaghi 2013). This similarity is understandable, in that minority populations tend to be associated with lower social status (Brown and Smith 1989), and status generalization theory suggests that lower status corresponds with lower performance expectations (Milanovich et al. 1998). Translating these rationales to our study context, we anticipate that customers might generally exhibit lower performance expectations of minority employees, including for their demonstrated friendliness during the interaction. If minority employees demonstrate exit friendliness toward the end of the service encounter, it accordingly might exert a particularly pronounced effect, such that

Hypothesis 5: Frontline employees’ demonstrated exit friendliness increases customers’ experience of rapport, especially for minority (cf. majority) employees.

Status generalization also influences identification with others, of both lower and higher social status. Consumers’ rapport with a service employee should result in identification with the firm, which may represent the underlying psychological variable that leads to favorable behavior toward that firm (Donavan, Janda, and Suh 2006; see also Hypothesis 4). We propose the following hypothesis:

Hypothesis 6: The joint effect of exit friendliness and employee ethnicity on loyalty intentions is serially mediated by customers’ rapport and identification with the firm.

To test our hypotheses, we conducted a laboratory experiment and a comprehensive field experiment in a retail setting. Our conceptual framework summarizes the proposed effects and connects them to the two empirical investigations (see Figure 1).

Figure 1.

Conceptual framework. Boxes denote manipulated factors; ovals represent measured variables.

Study 1. Testing the Behaviors of Majority Customers With a Laboratory Experiment

To test our first hypothesis, we use a video-based experimental simulation to assess customer behavior in intra- versus intergroup service delivery scenarios, differentiating two replications that pertain to either employee order taking or handling a customer complaint. The video methodology provides a realistic emulation of interpersonal service interactions while still maintaining a controlled investigative setting (Bateson and Hui 1992).

Procedure and Sample

We used a 2 (ethnicity of employee: majority vs. minority) × 2 (type of service interaction: order vs. complaint) between-subjects experimental design to test our hypothesis. Participants were 118 ethnic majority students from a large university in Germany: 45% were men, and the average age was 22.6 years, ranging from 19 to 32 years. We selected telecommunications services as the study context, and all participants were prescreened to ensure that they were customers of a mobile phone company.

Material and Pretests

In the video-simulated behavioral experiment (e.g., Pham, Hung, and Gorn 2011), we manipulated the ethnicity of the service employee conducting a simulated video chat, as either German or Turkish. In Germany, Turkish people represent the largest group of foreigners and are among the least accepted ethnic out-groups (Rosenbaum and Walsh 2012). Participants interacted with the service employee in a simulated video chat based on prerecorded video material. We adapted the study design from Vorauer and Turpie (2004) who examine behavior during interethnic versus same-ethnic interactions. The videos for the Turkish and German employees were shot in the same setting and were identical in terms of the employees’ verbal expressions, behavior, and clothing. We pretested the material extensively to establish the effectiveness of the manipulations. Akin to Degner et al. (2007), 40 participants were exposed to pictures of either the Turkish or German employee and rated how typical his or her physiognomy was with respect to either ethnic group on a semantic differential scale ranging from 1 (German) to 5 (Turkish). Next, with a randomized approach, we asked participants to listen to an audio file of one employee’s video, without any visual cues, to ensure that the employee’s voices did not differ in friendliness levels or accent; participants responded on 5-point Likert-type scales (1 = totally disagree, 5 = totally agree). The pretest results confirm that these participants perceived both employees’ physiognomy as prototypical for their ethnic group, German employee: M = 1.2, SD = 0.52; Turkish employee: M = 4.4, SD = 0.71; t(38) = 15.68, p < .001. In addition, the employees’ voices did not differ in friendliness, German employee: M = 3.7, SD = 1.3; Turkish employee: M = 3.6, SD = 1.00; t(38) = 0.18, ns, or accent, German employee: M = 2.3, SD = 1.7; Turkish employee: M = 2.3, SD = 1.3; t(38) = 0.03, ns.

Procedure

Participants (n = 118) arrived individually at the laboratory to complete a study investigating “video chat-based interactions with customer service agents.” Ethnic majority experimenters, blind to the hypothesis, provided a brief standardized overview of the study and then left the room. Participants received self-explanatory instructions on printed material and were assigned to a personal computer equipped with a webcam and speakers. To ensure fluency, the study relied on the experimental software package MLAB version 1.30, which incorporates control software for a webcam that records participants’ behavior, which we used to assess the dependent variable.

Participants first recorded a trial video to familiarize themselves with operating the webcam. Next, they opened an envelope with further instructions, explaining that during the course of the study, they would engage in a video chat with an employee of a phone company, introduced as a partner in the research project. The instructions explained that the video chat would be conducted through recorded videos because technical processes were the alleged focus of the study. The envelope also contained material that differed depending on the replication condition of the service request (customer order vs. complaint). In the order condition, it offered descriptions of three phone contracts with different conditions, and participants had to study these contracts and select the one that best suited their mobile phone habits. In a subsequent video chat, participants ordered the contract they picked. In the complaint condition, the envelope contained a phone contract and a phone bill with higher costs than listed in the contract. The participants were instructed to study the invoice, note its inconsistencies, and then address the inconsistencies in a subsequent video chat with an employee of the phone company. After studying the material, participants began the video chat, revealing a 10-second long video of a male service employee who, depending on the condition, was either German (majority service employee) or Turkish (minority service employee). The employee introduced himself by giving his Turkish/German name and then asked what he could do for the customer (i.e., participant).

The viewing window was framed with company logos, corresponding to the printed material, to strengthen the coherence of the manipulation. Subsequently, the instructions asked participants to use the computer’s webcam to record their service request. While waiting for the employee’s answer, participants filled out a questionnaire containing a manipulation check for the order versus complaint manipulation. Finally, the experimenter entered the room and debriefed them, handed them €5 in compensation (approximately US$6), and thanked them.

Measures

Participants’ observed behavior in the recorded video served as the dependent variable. In line with previous research (e.g., McConnell and Leibold 2001; Vorauer and Turpie 2004), the present operationalization of valenced behavior is defined in terms of participants’ friendliness, openness, demonstrated likability during the interaction, and how often the participant smiled while addressing the service employee. Such behavioral cues are commonly used to measure the valence of behavior during interactions by social psychological research because they “convey emotions and attitudes” (McConnell and Leibold 2001, p. 438). Two trained independent judges (one woman and one man), blind to the experimental conditions, viewed the videos of the service requests. On a scale from 1 (not at all) to 7 (very much), they rated the subjects on the given behavioral properties. To assess interrater reliability, we computed intraclass correlation coefficients (ICCs) using a two-way mixed effects model (McGraw and Wong 1996). The ICCs were .63 for friendliness, .54 for likability, .57 for openness, and .73 for smiling. All ratings were acceptable (Vorauer and Turpie 2004), suggesting adequate levels of agreement and reliability and thereby justifying the aggregation of the ratings across coders. Accordingly, we combined the four measures into an overall dependent variable, “valence of customers’ behavior toward employee” (α = .87), such that higher ratings indicate more positively toned behaviors.

Results and Discussion

We tested our first hypothesis with an analysis of variance. The overall model is significant, F(3, 117) = 6.49, p < .001, explaining 14.6% of the variance in the dependent variable. Furthermore, the main effect of the ethnicity of the service employee is significant, F(1, 117) = 18.47, p < .001, such that customers’ behavior is more positively toned toward majority service employees (M = 3.79, SD = 0.14) than minority service employees (M = 2.96, SD = 0.13), in support of Hypothesis 1. Neither the main effect of the manipulation of the service request, F(1, 117) = 0.29, ns, nor the interaction effect, F(1, 117) = 0.88, ns, is significant. That is, consumers’ ethnically biased behavior toward service employees does not differ between complaint and order service requests (Figure 2). These results underline the robustness of our results, by showing that minority service employees are treated less favorably by majority participants, regardless of the content of the interaction, in agreement with Hypothesis 1.

Figure 2.

Effect of employee ethnicity.

Study 2. Testing Customer Responses in Real-Life Interethnic Service Encounters

Building on the findings presented above, we extend our approach to a field study to probe real customer–service employee interactions and identify key downstream variables. The field study also accounts for joint effects of the interactions of customer and service employee ethnicity as well as of customer ethnicity and (employee) exit friendliness on rapport.

Study 2a. Procedure and Sample

We selected a Swiss grocery retailer that operates about 600 stores nationwide as an appropriate research context to test Hypotheses 2 to 6. We conducted the field experiment in one of the retailer’s stores on 8 different days over a 2-week period. Switzerland has a rich history of immigration, especially from other European countries, leading to a particularly high presence (around one quarter of the population) of foreigners (Nguyen 2017). By 1997, the Eurobarometer survey already had identified Switzerland as “a good example of a multicultural society and the peaceful co-existence of different groups and languages” (Freitag and Rapp 2013, p. 425). As a result, it also features a relatively high number of workers with migration backgrounds² in service sectors.

We identified the deli counter of this grocery retailer as an ideal setup for our field design. First, it demands a direct customer–frontline employee interaction (Shostack 1985). This conventional service encounter tends to be short, with limited prior contact or mutual knowledge between parties, so both the customer and the employee rely almost exclusively on observable cues and related stereotypes to form expectations about the encounter and evaluate its success or failure (Barker and Härtel 2004). Second, we were allowed to design the deli counter staffing plan, together with the store manager (Carroll and Samek 2018), so we could control for the deployment of employees with and without migration backgrounds during our field study.

To obtain unbiased measures of minority/majority customers, we combined observational and survey methods. We instructed two Swiss research assistants to observe the migration backgrounds of customers entering a store. The training for this effort took place in a 120-minute session, in which one author showed pictures and videos of customers with different migration backgrounds, common in Swiss society. The two coders indicated whether they perceived a migration background (“This customer has a migration background”) and an accent in spoken language (“This customer has a foreign accent”; Hill and Tombs 2011) on 7-point scales anchored by strongly disagree (1) and strongly agree (7). For the main study, we instructed the research assistants to focus on predefined employees with/without migration background and the customers served by each employee. From these observations, they coded each customer’s degree of migration background, degree of spoken accent, gender, and estimated age. By specifying their focus on a selected employee and her or his interactions with multiple customers, we obtained more observations while reducing task complexity which bears potential for confusion that may arise if coders chose which customer-employee interactions to observe by themselves. After the observation, the research assistants approached the observed customers and asked them to fill out a short questionnaire (Albrecht et al. 2017), which included questions about their perceptions of the service encounter, general attitudes, and demographics.

The coders observed 724 customer-employee interactions, and 286 customers (39.5%) agreed to complete the questionnaire. Among this final sample, 182 participants were women (64.3%), 85 had a migration background (29.7%), and their ages ranged from 17 to 88 years (M = 50.16, SD = 17.97). The interactions involved 12 different employees, resulting in a customer to employee ratio of about 24:1. Each employee was observed on multiple occasions during a single day.

To control for the customers’ self-identified migration background, we mapped their responses onto the coders’ observations, using an independent samples t test. The results suggest the reliability of the measures; on average, participants who did not report a migration background received significantly lower scores from our coders on the migration background question (M = 1.39, SD = 0.82) than participants who identified their own migration background, M = 3.07, SD = 2.07; t(279) = −9.80, p < .001. The coders also rated the degree of spoken foreign accent significantly lower for participants without self-reported migration backgrounds (M = 1.20, SD = 0.69) than for those with them, M = 3.30; SD = 2.30); t(273) = −11.53, p < .001.

Study 2a. Measurements

After interacting with the employee, participants indicated their rapport with the frontline employee and identification with the company on a paper questionnaire. Finally, participants responded to a loyalty intentions scale and provided basic sociodemographic information. To ensure scale reliability, we used established items from prior literature.³

Study 2a. Results

Manipulation check

One question in the survey requested the customer’s perception of the employee’s migration background (“I assume this employee has a migration background”). We anticipated that interacting with an employee with a migration background would lead to significantly higher migration evaluations. The independent t test affirms that customers’ evaluations of migration backgrounds were significantly lower for employees without such backgrounds (M = 2.26, SD = 1.72) than for employees with them, M = 4.20, SD = 2.28; t(283) = −8.05, p < .001. The manipulation achieved through the staffing plan, in cooperation with the store manager, thus was effective.

Rapport

A 2 (employee ethnicity: majority vs. minority) × 2 (customer ethnicity: majority vs. minority) analysis of covariance (ANCOVA) of rapport with the service employee, controlling for stereotyping, intercultural competence, and gender⁴ confirmed the interaction we predict in Hypothesis 2a, F(1, 279) = 10.10, p < .01 (see Figure 3). The main effects of both employee ethnic background, F(1, 279) = .84, ns, and customer ethnic background, F(1, 279) = .06, ns, do not reach significance.

Figure 3.

Interaction effect of customer and employee ethnicity.

Consistent with Hypothesis 2a, the planned comparisons reveal that majority customers express significantly higher levels of rapport, F(1, 196) = 13.44, p < .001, toward majority employees (M = 5.46, SD = 1.18) than toward minority employees (M = 4.82, SD = 1.30). In contrast, the difference in minority customers’ rapport with minority (M = 5.35, SD = 1.30) versus majority (M = 4.95, SD = 1.28) employees is not significant, F(1, 80) = 1.62, ns, though it offers directional support. Still, we are unable to formally support Hypothesis 2b because minority customers do not experience greater levels of rapport with minority than with majority employees.

Serial mediation analysis

To test our predicted serial mediation pathway (Hypotheses 3 and 4), we ran PROCESS Model 6 (Hayes 2018; Preacher, Rucker, and Hayes 2007) with a 5,000-bootstrap resampling method. The independent variable, interethnicity of the service encounter, predicted rapport, which predicted identification with the firm, which ultimately predicted loyalty intentions. Interethnicity of the service encounter occurs when a minority employee and a majority customer or majority employee and minority customer interact. As illustrated in Figure 4, the interethnicity of the service encounter significantly predicts rapport. Rapport predicts identification with the firm, which then predicts loyalty intentions. Moreover, the indirect effect of the overall model is statistically significant. In contrast, when we test single mediator models, with either rapport or identification with the firm as the sole mediator, the indirect effects are not significant. Nor is the main effect of the interethnicity of the service encounter on loyalty intentions significant. In summary, we find support for both Hypotheses 3 and 4.

Figure 4.

Serial mediation of customer and employee ethnicity interaction. Unstandardized coefficients (B) and standard errors (SEs) are reported. Bootstrapping procedures are based on 5,000 resamples. Dashed arrows designate nonsignificant path coefficients. Bias-correlated and accelerated estimates of 95% confidence intervals (CI) for the indirect effects, coefficients, and SEs: CE × EE → Rapport → Loyal Intensions: CI [−.02, .04], B = .01, boot SE = .02; CE × EE → Rapport → Identification → Loyal Intensions: CI [.01, .09], B = .04*, boot SE = .02; CE × EE → Identification → Loyal Intensions: CI [−.07, .19], B = .06, boot SE = .07; *p < .05. **p < .01.

Thus, the interethnicity of service encounters predicts customer rapport; majority customers experience higher levels of rapport when interacting with majority as opposed to minority employees. Rapport drives customer identification with the service firm, and the joint effect of employee and customer ethnicity on customer loyalty is serially mediated by customer rapport and identification.

Study 2b. Procedure and Sample

Customers can detect degrees of service script usage, in both standardized and customized encounters (Victorino et al. 2012), and when they detect variations in service delivery, it influences important outcomes such as perceptions of service quality and loyalty intentions (Groth, Hennig-Thurau, and Walsh 2009; Schau, Dellande, and Gilly 2007). The retail firm that partnered with us for this study does not use any scripting techniques, so encounters at its deli counter are highly customized. We accordingly did not want to risk implementing a high-level script (i.e., scripting the whole service encounter), which would be totally unfamiliar to employees. Instead, in close cooperation with the store manager and qualified deli personnel (Carroll and Samek 2018), we proposed a statement to signal exit friendliness that also achieved brevity and supported dialect-pronounced phrasing: “Thank you for your purchase at our store, and have a nice day.” After a week of data acquisition, we briefed deli employees on this specific exit friendliness statement. Together with the store manager and the research assistants, we provided two further briefings on the rationale and purpose of this low-level script. In addition, we placed a copy of the statement behind the deli counter and in employee locker rooms to remind them to use it during their encounters. We collected the data for this experimental condition on 2 consecutive days (Tuesday and Wednesday) to account for possible day-of-the-week effects.

From the experimental group featuring exit friendliness, the coders observed 267 customer-employee interactions, and 162 (60.1%) customers agreed to complete the questionnaire. Of this final sample, 97 participants were women (59.9%), 36 had a migration background (22.2%), and the ages ranged from 16 to 85 years (M = 51.34, SD = 16.60). Using the same pool of employees as in Study 2a, the interactions involved 11 employees, for a customer to employee ratio of about 15:1. Each employee was observed on multiple occasions during the day. As a control group, we used the participants of Study 2a, who were not exposed to the exit friendliness script (Liu and Aaker 2008; Marchand et al. 2017). The multi-item measures were the same as in Study 2a (Appendix).

Study 2b. Results and Discussion

Manipulation checks

As a first manipulation check, we used the same question to solicit customers’ perception of the employee’s migration background (“I assume this employee has a migration background”). The independent t test reveals that customers assessed the migration backgrounds of employees without migration backgrounds as significantly lower (M = 2.33, SD = 1.92) than those of employees with migration backgrounds, M = 3.90, SD = 2.46; t(157) = −4.45, p < .001, in support of the effectiveness of the manipulation. The mean values are comparable to those in Study 2a. As an additional manipulation check, we checked perceived exit friendliness of employees; this measure also had appeared in the customer survey for Study 2a (“This employee has sent me off really friendly”). An independent t test comparing the two conditions reveals that customers’ perception of employees’ exit friendliness is significantly lower in the control group (M = 4.71, SD = 1.71) than in the exit friendliness condition, M = 6.50, SD = .77; t(445) = −12.54, p < .001. Consequently, this manipulation also is effective.

Rapport

A 2 (employee ethnicity: majority vs. minority) × 2 (exit friendliness: scripted vs. nonscripted) ANCOVA on rapport with the service employee, controlling for stereotyping, intercultural competence, and gender,⁵ confirms the predicted interaction and Hypothesis 5, F(1, 437) = 6.32, p < .05 (see Figure 5). The main effect of the ethnic background of employees, F(1, 437) = 0.12, ns, is not significant. However, the main effect for exit friendliness reaches significance, F(1, 437) = 14.57, p < .001: When frontline employees demonstrate exit friendliness, it increases customers’ experience of rapport.

Figure 5.

Interaction effect of employee ethnicity and exit friendliness.

We use planned comparisons to determine whether employees’ exit friendliness increases customers’ perceived rapport even more when they are members of the minority rather than majority. In support of Hypothesis 5, exit friendliness has no significant effect on customers’ perception of rapport with majority employees, F(1, 206) = 1.36, ns; control without exit friendliness, M = 5.28, SD = 1.23; scripted exit friendliness, M = 5.47, SD = 1.12, but the difference in customers’ perceived levels of rapport with minority employees is significant, F(1, 228) = 20.64, p < .001; control without exit friendliness, M = 4.95, SD = 1.32; scripted exit friendliness, M = 5.73, SD = 1.07.

Serial mediation analysis

To examine the serial mediation pathway we predicted in Hypothesis 6, we ran PROCESS Model 6 to test whether the independent variable (interaction of ethnicity of the service employee and exit friendliness) predicts rapport, which shapes identification with the firm and in turn determines loyalty intentions. We find that the interaction significantly predicts rapport; minority employees displaying exit friendliness can favorably influence majority customers’ behavior. Rapport predicts identification with the firm, and identification with the firm predicts loyalty intentions. The indirect effect of the overall model also is statistically significant. When we examine single mediator models, using rapport or identification with the firm as sole mediators, the indirect effects are not significant. Finally, the main effect of the independent interaction term on loyalty intentions is not significant (Figure 6). These findings support Hypothesis 6.

Figure 6.

Serial mediation of employee ethnicity and exit friendliness interaction. Unstandardized coefficients (B) and standard errors (SEs) are reported. Bootstrapping procedures are based on 5,000 resamples. Dashed arrows designate nonsignificant path coefficients. Bias-correlated and accelerated estimates of 95% confidence intervals (CI) for the indirect effects, coefficients, and SEs: EE × EF → Rapport → Loyal Intensions: CI [−.01, .02], B = .003, boot SE = .01; EE × EF → Rapport → Identification → Loyal Intensions: CI [.01, .07], B = .03*, boot SE = .01; EE × EF → Identification → Loyal Intensions: CI [−.07, .14], B = .04, boot SE = .05; *p < .05. **p < .01.

Thus, Study 2b confirms that the exit friendliness displayed by service employees positively affects customers’ rapport experience, especially when majority customers interact with minority employees. Moreover, we find that the joint effect of employee exit friendliness and ethnicity on customer loyalty is serially mediated by customer rapport and identification.

General Discussion

The notion that employees are a service company’s best resource is widely accepted (e.g., Maglio and Spohrer 2008; Vargo and Lusch 2008). With increasing and sustained immigration into developed countries, interethnic service encounters eventually may become the rule rather than the exception. Interethnic service encounters can engender bias, which may produce negative employee and customer outcomes. Therefore, interethnic service encounters are of great practical relevance to both service scholars and managers, and to enhance insights into them, we adopt an aversive racism perspective. Accordingly, we clarify how employees’ ethnicity might influence customers’ behavior in contemporary service encounters (Hypothesis 1), how majority and minority customers perceive their rapport with majority and minority employees (Hypothesis 2), how customers’ experience of rapport drives their identification with the firm (Hypothesis 3), how the joint effects of customer and employee ethnicity (Hypothesis 4) and of exit friendliness and employee ethnicity (Hypothesis 6) on loyalty intentions are serially mediated by customer rapport and identification with the firm, and how employee exit friendliness affects customer rapport with employees who are members of the minority or majority group (Hypothesis 5).

Overall, the present research effectively underlines the existence of a customer ethnic bias in service encounters under the aspect of both internal validity and external validity. The initial laboratory study demonstrates that interethnic service encounters evoke less positively toned (majority) customer behavior toward service employees across varying service contexts such as order taking versus complaint handling (Study 1). The laboratory setting and design of this study support the reliability of the causal inferences derived from the empirical findings, demonstrating internal validity. Distinguishing between two separate replication contexts in the design supports the robustness of the observed effect. Addressing also the issue of external validity with a subsequent exhaustive field experiment (Study 2), we find that interethnic (vs. intraethnic) service encounters result in lower levels of customer rapport, and rapport positively predicts customer identification with the service firm. This finding is consistent with the aversive racism framework, which maintains that majority members’ bias is an indirect phenomenon. The results also show that customer and employee ethnicity jointly affect loyalty intentions through customer rapport and identification with the firm, providing a novel perspective into the psychological mechanisms in the cognitive processing of individuals’ perceptions of interethnic service encounters. The findings also demonstrate that exit friendliness can effectively increase customers’ experience of rapport, especially in relation to minority employees. Finally, exit friendliness and employee ethnicity jointly affect loyalty intentions through customer rapport and identification with the firm, again, underlining the key role of these two psychological mechanisms.

Theoretical Implications

This research makes several contributions to literature on interethnic service encounters. First, in Study 1, we establish that majority customers show less positively toned behavior toward minority (vs. majority) service employees, consistent with the aversive racism framework (Dovidio and Gaertner 2000), which posits that overt expressions of prejudice are unlikely in situations in which normatively appropriate behavior is clear. Moreover, in Study 2, we consider the interactive effect of customer and employee ethnicity on rapport as an important outcome, revealing that majority-majority dyads can evoke high levels of rapport.

Second, we investigate the psychological mechanism by which interethnic service encounters link to important employee outcomes such as rapport. Rapport positively predicts customer identification with the service firm, which predicts customer loyalty intentions. Thus, we extend prior research on the effect of customers’ biases by showing that, in addition to their evaluations or satisfaction ratings (Etgar and Fuchs 2011; Hekman et al. 2010; Lynn and Sturman 2011), customers’ explicit behavior toward service employees may reflect ethnic biases. Customer satisfaction ratings tend to be anonymous, so biased majority customers can be frank about their views without fear of social repercussions, but our results go even further and show that customer behaviors are susceptible to bias during actual service encounters. Furthermore, biased satisfaction ratings can affect important outcomes, such as promotion decisions, but customers’ biased behavior directly affects frontline employees’ well-being and can create significant stressors for minority employees (Kern and Grandey 2009).

Third, we theorize and test for the moderating role of a scripted (positive) expression of exit friendliness, which helps reveal the contingencies that underlie ethnic customer bias and thus indicates some options for combating their negative consequences. In line with the tenets of status theory, which suggests that biases caused by own-group favoritism are associated with lower performance expectations of minority employees, we predicted that if customers interact with a minority employee of a service company who exhibits exit friendliness, they experience rapport. That is, if minority employees show exit friendliness, majority customers experience a positive disconfirmation of their service expectations, which results in greater rapport. Our results support this prediction, in the sense that behaviors toward minority employees do not differ significantly (or even may be more positively toned) from behaviors toward employees with a shared majority background when employees all express exit friendliness.

Managerial Implications

Ethnically biased behaviors by coworkers and supervisors are important stressors that affect minority employees’ promotions, health, turnover rates, and absenteeism (Raver and Nishii 2010; Sanchez and Brock 1996). Scant research has examined customers’ biased behaviors during interethnic service encounters though. Customer biases exert negative effects on employee well-being and performance, such that they pose a growing challenge to service management. Our research yields some managerially relevant insights into the mechanism that links interethnic encounters to customer outcomes and how service managers can influence and reduce the impact of biased behaviors, by fostering (minority) employee-customer rapport through easy-to-implement, minimally scripted expressions. Managers might measure customers’ level of rapport systematically to establish a baseline against which they could then monitor the success of actions geared toward generating employee-customer rapport. Regular monitoring of this metric could reveal any fluctuations in rapport, and we advise such monitoring tactics because our results suggest that companies that require scripted expressions toward majority customers can reduce the risk of exposing their minority service employees to the negative effects of their customers’ biased behavior.

Although rapport is an important goal in its own right, it can help foster customer identification with and loyalty to the service firm too. Service managers should actively stimulate customer-firm identification, whether through increased rapport or in other ways. For example, they could encourage employees’ identification with the firm, which can spill over to customers (Homburg, Wieseke, and Hoyer 2009). Such a strategy could establish a more strongly identified customer base in the long run, which in turn may reduce customers’ biased behavior during interethnic service encounters. Managers also could strengthen the firm’s identity. Service companies with strong organizational identities display related values and characteristics, which can be an attractive source of identification for customers who perceive congruence between aspects of the company’s identity and their own self-concept (Ashforth and Mael 1989; Brown et al. 2006). In addition, managers could adopt tactics to increase customers’ recognition of the service company as a distinct social group. For example, they could stress favorable comparisons between their organization and competitors and thereby sharpen the profile of the company as an attractive in-group (Dutton, Dukerich, and Harquail 1994).

Limitations and Further Research

The present research uses the concept of ethnicity as an umbrella term, acknowledging that different groups may also be further differentiated in terms of ethnic, racial, or cultural properties or any combination of these characteristics (Page-Gould, Mendoza-Denton, and Tropp 2008). Future research may examine whether unique effects can be detected for these facets of ethnicity in a service context. The experimental setting of Study 1 enabled us to test our hypothesis regarding customers’ biased behavior in a controlled environment and attain some causal inferences. However, it also has distinct limitations such as limited levels of external validity. The Study 1 test focused on the onset of the service encounter, and though the first seconds of contacts generally are critical for interaction outcomes, especially in terms of evoking group membership perceptions (Pearson et al. 2008), investigating entire service episodes would be more realistic. Noting these limitations, we conducted a field investigation in a contemporary service setting (Study 2) that includes additional contextual factors. Despite these strengths, Study 2 also has limitations. For example, we could not control for different variables as well as we did in our lab experiment, such as crowdedness or background music, which may influence customer and employee moods and behaviors (Walsh et al. 2011). We also acknowledge that our field study results may be less replicable than our Study 1 (lab) findings. Finally, our research focuses on ethnic bias, as one type of bias, but other types exist and are worthy of investigation. For example, studies might determine how employee ethnicity interacts with visible characteristics such as obesity (Cowart and Brady 2014) to shape customer perceptions and behaviors toward employees.

Footnotes

Appendix

Table A1.

Measures for Study 2.

Construct	Item	Cronbach’s α: Study 2a (N = 286)	Cronbach’s α: Study 2b (N = 162)^a	Sources
Rapport	I enjoyed interacting with this employee.	.91	.86	Gremler and Gwinner (2000); Yim, Tse, and Chan (2008)
	I felt I had a harmonious relationship with this person.
	You can have a nice conversation with this employee.
	I feel like there is a “bond” between this employee and myself.
	I look forward to seeing this person when I visit (name of company).
	This person has taken a personal interest in me.
Identification with the firm	I strongly identify with this firm.	.90	.91	Homburg, Wieseke, and Hoyer (2009); Mael and Ashforth (1992)
	When someone criticizes (name of company), it feels like a personal insult.
	This company’s successes are my successes.
	When someone praises the company, it feels like a personal compliment.
	If a story in the media criticized (name of company), I would feel embarrassed.
Loyalty intentions	I would do most of my business with this company.	.91	.92	Sirdeshmukh, Singh, and Sabol (2002); Zeithaml, Berry, and Parasuraman (1996)
	I would recommend this company to my friends, neighbors, and relatives.
	I would consider this company my first choice to do business.

Note. Item responses were on 7-point scales, anchored by 1 (strongly disagree) and 7 (strongly agree).

^a This analysis refers to the exit friendliness treatment group.

Acknowledgments

The authors thank Severin Bischof and Tim Lersch for their excellent assistance on this project and the managers of the anonymous retail company for their support. The authors are also grateful to the editorial reviewer team for constructive comments and suggestions.

Declaration of Conflicting Interests

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

Funding

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

ORCID iD

Gianfranco Walsh

Notes

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