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Article

Managing Multiple Customer Interactions: Exploring Customer Reactions and Gender Differences in Response to Employee-to-Other Customer Interaction Quality in the Social Servicescape

by
Youngsun Sean Kim
1,*,†,
Bosul Yoo
1,†,
Danni Wang
2,†,
Se Jin Kim
3,† and
Chanho Song
4,†
1
College of International Management, Ritsumeikan Asia Pacific University, Beppu 874-0011, Japan
2
Hospitality Management, University of Lincoln, Lincoln LN6 7TS, UK
3
College of Business, Western New England University, Springfield, MA 01119, USA
4
Department of Marketing, California State University, San Bernardino, CA 92407, USA
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Tour. Hosp. 2026, 7(5), 131; https://doi.org/10.3390/tourhosp7050131
Submission received: 25 March 2026 / Revised: 16 April 2026 / Accepted: 24 April 2026 / Published: 6 May 2026
(This article belongs to the Special Issue Customer Behavior in Tourism and Hospitality)
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Abstract

Cultivating high-quality interactions between customers and employees has become a central concern for both researchers and practitioners. However, most studies have primarily centered on examining and enhancing the quality and effectiveness of direct interactions between employees and customers. Building upon social influence theory, this study diverges by investigating how interactions among employees and other customers, along with their quality, impact the service perceptions of observing customers within the social servicescape. Using a 2 × 2 × 2 between-subjects experimental design with 384 participants, this study provides the first empirical evidence that the interaction quality among other social actors in a shared service environment significantly influences the perceived customer orientation and service quality for observing customers. Hypotheses were tested using multivariate analysis of variance (MANOVA). Importantly, this effect persists even when the observing customers themselves are not directly involved in the interactions with either the service provider or the other customer. Additionally, the study uncovers a noteworthy gender difference in how individuals respond to the quality of interactions between employees and other customers. Furthermore, the findings suggest that an observing customer’s prior emotional attachment to the service provider does not significantly interact with the effects of employee-to-other customer interaction quality, indicating that the underlying expectation for interaction quality in the social servicescape remains consistent regardless of the customer’s preexisting relationship with the service provider.

1. Introduction

In the past, many businesses held the belief that achieving the highest product quality was the key to success. However, latest trends indicate a shift towards prioritizing the development of a distinctive and memorable “customer experience” (Tao et al., 2024; Becker & Jaakkola, 2020; Keiningham et al., 2020; Zwilling, 2014). The concept of customer experience is generally shaped by the interactions between an organization and its customers over the course of their relationship (Lemon & Verhoef, 2016). This shift is particularly evident in the hospitality and travel service industry, where customer-contact staff not only deliver products but also play a crucial role in establishing rapport. Positive outcomes for customers, such as increased loyalty and a higher likelihood of making a purchase, can be attributed to the staff’s effective rapport-building behaviors (K. Kim & Baker, 2019).
As a result, developing high-quality interactions between customers and employees has become a central concern for both researchers and practitioners (H. Kim & Qu, 2020). However, most studies have predominantly concentrated on investigating and improving the quality and impact of direct interactions between employees and customers (H. S. Kim & Choi, 2016). Limited knowledge exists regarding the potential effects of indirect interactions through observation between employees and other customers, particularly concerning their quality. This becomes particularly evident when considering that various indirect interactions and observations commonly take place in public customer-contact service settings, such as restaurants, airport check-in counters, and amusement parks (Y. S. Kim & Baker, 2020; Wu et al., 2017).
The social influence theory (Kelman, 1958) suggests that individuals are profoundly affected by the thoughts and behaviors of others. People inevitably face pressures to conform from peers within their social groups. The actions of fellow group members, even though non-direct interactions such as observation of others’ behavior and communication, significantly influence an individual’s judgments (Sridhar & Srinivasan, 2012). Despite the presence of various social actors and their important influences though observations in the public servicescape, much of the earlier literature solely focuses on the one interaction quality type of direct customer-to-employee interaction (Y. S. Kim & Baker, 2020; Wu et al., 2017). However, prior research has largely overlooked that observational interactions in service environments do not merely act as external cues, but can become an integral part of customers’ own service experience formation, thereby shaping how service quality is perceived.
To address this gap, this study empirically examines the effect of employee-to-other-customer interaction quality on observing customers’ perceptions of customer orientation and service quality in a restaurant context. Building on this perspective, this study argues that interaction quality should not be viewed merely as an external stimulus observed by customers, but as an integral component of customers’ own service experience formation. Accordingly, this shifts attention to the service delivery process itself, where customer-contact employees must manage not only direct interactions but also multiple simultaneous interactions that shape the overall experience of observing customers (H. S. Kim & Choi, 2016). Therefore, further research is needed to examine how customer-contact employees manage multiple concurrent customer interactions while maintaining consistent interaction quality across service encounters. Based on this logic, this study aims to extend the existing literature by highlighting the role of managing multi-customer interactions as a key mechanism in shaping customer experience in shared service environments.
Furthermore, our research investigates the potential moderating roles of observing customers’ emotional brand attachment and gender (Ashley & Leonard, 2009). Assessing service experience does not stem solely from any single attribute but rather from the interplay of various individual and prior relational factors, which may collectively shape customer perceptions (Y. S. Kim & Baker, 2020). Specifically, utilizing a hypothetical experiment, this study adopts a between-subject design featuring the following factors: interaction quality (high vs. low), emotional brand attachment (strong vs. weak), and gender (male vs. female), resulting in a 2 × 2 × 2 design.
In summary, this research distinguishes itself from previous studies by examining the influence of not only core interaction quality but also employee-to-other customer interaction quality on observing customers. This represents an important avenue for future managerial observation and research. Our findings offer valuable insights for managers to reconsider how service encounters with the presence of multiple customers and their interaction quality should be effectively “managed.” Even without direct interactions, customers and employees retain the ability to influence other customers simply through observation in shared service settings. This underscores the imperative for service organizations to acknowledge the significance of customer observations and devise effective strategies to manage and elevate the overall customer experience quality for all customers involved.

2. Literature Review and Hypothesis Development

2.1. Social Influence Theories in Service Context

The intangibility of service encourages customers to heavily rely on a physical environment cue to mitigate any cognitive dissonance (Bitner, 1992). Tombs and McColl-Kennedy (2003) incorporate the social elements of the service environment such as the presence of employees and other customers into the framework and thus introduce the integrated model of “social servicescape.” The premise of social servicescape is that the contextual, social components of the purchase occasion (e.g., expressed emotions and behaviors of others) can influence a customer’s cognitive and emotional state. Although this framework is valuable in terms of its effort to include social actors such as employees and customers as a social stimulus in the servicescape, very little is still known about how interactions among such social actors would affect one’s observing responses in service encounters (Y. S. Kim & Baker, 2020). Therefore, a new direction for advancing our understanding of the influence of others in the service encounter is to study those customers whose experiences are affected by observing others’ behaviors and service interactions.
The social influence theory, pioneered by Herbert Kelman in 1958, offers a framework for understanding how individuals affect each other in social settings. This study adopts social influence theory as the overarching theoretical framework to explain how observational interactions among social actors in service environments shape customers’ perceptions and evaluations. Specifically, the theory helps explain how employee-to-other-customer interaction quality, even when not directly involving the focal customer, can influence perceptions of customer orientation and service quality through observational learning and social comparison processes. The premise is that people are naturally influenced by the presence of another individual or group of people. Latané (1981) suggests that the presence of others is a multi-dimensional phenomenon, and the social impact of others will be more significant when the source of influence has high status, stronger intimacy, short distance, and multiple sources of influence. Since individuals frequently face conformity pressures from others within a social group, the actions of fellow members exert a significant impact on the judgments of a particular individual (Sridhar & Srinivasan, 2012).
In addition, the direct observation of group members’ behaviors is not always essential for such social influence to take hold, yet simply conveying a norm through written communication, such as describing how others including people they do not know behave in a specific situation, can induce conformity (Sridhar & Srinivasan, 2012). X. Zhang et al. (2014) demonstrates that stimulus of other people in a retail shop on a target customer’s behavior increases as the number of other shoppers and the intensity of social interactions (e.g., conversations) in a shop rises. Along with the social impact theory, script theory (Tomkins, 1978) further explains that individuals have a mental schema of the predetermined set of activities called scripts, and they use such scripts, which usually contains the roles of others, when evaluating others. In most public service settings, for example, consumers often use mental scripts to judge others’ behavior and react based on such evaluation (Miao, 2014). By extending the logic of these social influence studies, this research seeks to shed light on how observing how behaviors of employees and other customers in a social service context impacts customer perceptions towards service employees and organizations.

2.2. Interaction Quality

Interaction quality within service contexts pertains to customers’ perceptions of their engagements with the human element of a service organization (Grönroos, 1982). The key components of interaction quality, such as courtesy, pleasantness, and warmth displayed by a service employee during the interactions with customers, play a crucial role in shaping the perceived level of service encounter quality (Choi & Kim, 2013). Not surprisingly, the way frontline service employees smile at a customer determines perceived interaction quality and consumer satisfaction (Choi & Kim, 2013; Pugh, 2001). In other words, the expressed emotions of employees during the service delivery process are critical because customers “catch” the influence of employees through emotional contagion (Pugh, 2001). Therefore, the significance of managing interaction quality for the service encounter and customer satisfaction has been extensively acknowledged (M. Zhang et al., 2021; Ekinci & Dawes, 2009). Nonetheless, there exists limited understanding regarding the impacts of the presence and interaction behavior of both employees and other customers. This gap in research underscores the necessity for studies that delve into the outcomes of various service interactions, encompassing both interactions between employees and other customers within the social servicescape. Thus, the primary focus of the present research is to examine how the quality of interactions between employees and other customers impacts the service perceptions of observing customers.

2.3. Perceived Customer Orientation

Customer orientation perception refers to the extent to which service employees’ behavior fulfills customer needs during their interactions (Hennig-Thurau, 2004). Prior studies emphasize the significance of customer-contact employees’ capability and willingness to fulfill customer needs in shaping perceptions of customer orientation (Groth et al., 2009). Certainly, customer service perceptions are influenced by the caliber of external expressions demonstrated by individuals during social interactions (Y. S. Kim & Baker, 2019). This aligns with the perspective of emotional contagion theory, which posits that sustained exposure to others expressing positive or negative emotions can induce a similar emotional state change in observers (Liu et al., 2019; Pugh, 2001). Drawing from these findings, this study suggests that witnessing a service employee engage in high-quality interaction behavior towards other customers is likely to improve an observer’s perception of the employee’s customer orientation. Put differently, the observation of a high-quality interaction indicates the employee’s readiness to fulfill customers’ needs and satisfy them (Groth et al., 2009). Conversely, witnessing a low-quality interaction between an employee and another customer is anticipated to adversely affect perceived customer orientation. Based on these premises, we hypothesize that
Hypothesis 1.
Employee-to-other customer interaction quality is positively related to observing customer’s perceived employee customer orientation.

2.4. Perceived Service Quality

Furthermore, studies on consumer behavior indicate that customers actively seek information about the overall performance of the firm during interactions with employees (Kattara et al., 2008). This information-seeking behavior is essential in the evaluation of service quality. As an example, Groth et al. (2009) demonstrate that when customers perceive employees as highly reliable and responsive, it boosts their confidence in the service provider, simultaneously resulting in enhanced perceived service quality. While customer orientation perception refers to the extent to which a specific service employee’s behavior fulfills customer needs during their interactions, service quality perception pertains to a customer’s overall evaluation of the excellence of the service organization (Bitner, 1992; Groth et al., 2009). Research on service quality highlights that positively perceived service quality enhances a firm’s profitability and strategic effectiveness (Powell, 1995). Consequently, many service organizations strive to improve customer service quality perceptions by enhancing operational processes such as responsiveness and reliability (Zeithaml et al., 1990). Additionally, the psychology and organizational literature indicates that individuals naturally pay attention not only to their own treatment but also to how others are served (Colquitt, 2004; Spencer & Rupp, 2009). Service encounters often take place in the presence of other customers, and previous research has investigated different facets of how other customers can influence the service experiences of focal customers. For example, Shin et al. (2018) illustrates a experimental study where customers may encounter feelings of injustice and negative emotions when they observe other customers being mistreated. Based on this premise, this study contends that witnessing a positive interaction quality between employees and other customers positively influences a customer’s overall service impression. Conversely, observing a low-quality interaction may cause observing customers to question the overall quality of their service provider and their own service experiences, consequently reducing perceived service quality. Thus, we hypothesize that
Hypothesis 2.
Employee-to-other customer interaction quality is positively related to observing customer’s perceived service quality.

2.5. Moderating Roles of Gender and Emotional Brand Attachment

This research examines not only the main impact of interaction quality of others on perceptions of the observing customer but also examines how individual and relational factors influences customers’ perceptions in the context of employee-to-other customer interactions. Previous research has highlighted the significance of gender as an important differentiator among customers in the service industry (Spathis et al., 2004). Specifically, men and women tend to prioritize different aspects of service delivery, with women having higher expectations of service quality and displaying greater purchasing behavior compared to men (W. B. Lin, 2010). Studies on gender’s influence on service recovery also suggest that women are generally more interested in efforts to rectify service failures than men (Mattila, 2010; McColl-Kennedy & Sparks, 2003). While existing research has shown that gender characteristics have a significant impact on customer reactions when assessing service performance, this aspect has not been thoroughly examined in the context of diverse customer interactions in public service settings. Therefore, this study contributes to the literature by proposing that customers’ observed reactions to the quality of employee-to-other customer interactions may depend on the gender of the observing customer. Based on this, we hypothesize the following:
Hypothesis 3.
Gender moderates the impact of employee-to-other customer interaction quality on (a) perceived employee customer orientation and (b) perceived service quality.
Additionally, this study investigates the influence of the emotional strength of the customer–brand relationship as a potential relational factor on customers’ perceptions of the employee-to-other customer service interaction in public settings. While customers engage with various products and brands throughout their lives, they tend to develop a strong emotional connection with only a select few (Ashley & Leonard, 2009). Some research suggests that customers may exhibit negative behaviors towards a brand and forgive transgressions when their favored brands disappoint them (Japutra et al., 2018). Conversely, other studies indicate that a strong brand attachment can lead to feelings of violation towards the company in cases of inappropriate practices (Ashley & Leonard, 2009; Grégoire & Fisher, 2008). However, the impact of emotional brand attachment on other customer service experiences has not been thoroughly examined. Hence, this study contributes to the existing literature by investigating the role of emotional brand attachment in the context of employee-to-other customer service interactions. As a result, it suggests that the level of emotional attachment to the brand will moderate the influence of observing the quality of employee-to-other customer interactions on customers’ perceptions of the service. In summary, we hypothesize the following:
Hypothesis 4.
Emotional brand attachment moderates the impact of employee-to-other customer interaction quality on (a) perceived employee customer orientation and (b) perceived service quality.

3. Methodology

3.1. Research Design and Data Collection

The objective of the study is to investigate how the quality of interactions between employees and other customers within a social servicescape affects employee customer orientation and overall service quality as perceived by observing customers. Furthermore, the study explores the potential moderating effects of emotional attachment to the brand and the gender of the observing customer. To test the hypotheses, a between-subjects experimental design was employed, involving a 2 (high vs. low interaction quality) × 2 (strong vs. weak emotional brand attachment) × 2 (male vs. female) design. Data were collected through a web-based survey using the MTurk platform. The study focused on U.S. participants, given the strong restaurant service culture and high population diversity, which make the context particularly suitable for examining customer perceptions in shared service environments. To ensure data quality, attention-check items were embedded throughout the survey. After excluding responses that failed the attention checks or contained incomplete information, the final sample consisted of 384 participants. The research setting chosen for this study was a full-service restaurant, as observing others’ service interactions frequently occur in such contexts (Her & Seo, 2018).
Survey participants were instructed to imagine dining out at a restaurant and were presented with a scenario to read. They were then asked to complete a survey questionnaire, referring only to the scenario they had read. The scenario-based approach is widely employed in service interaction research and is found to be effective in experimental design studies due to its capability to regulate extraneous variables (Y. S. Kim & Baker, 2019; Miao & Mattila, 2013). The scenario described the participants witnessing a service interaction between the restaurant server and other customers seated at a neighboring table. The level of employee-to-other customer interaction quality was manipulated based on previous research that identified key components of interaction quality behavior, such as politeness, friendliness, and sensitivity (Choi & Kim, 2013; N. P. Lin et al., 2001). More specifically, participants in the high interaction quality condition were informed that they observed the restaurant server returning to the other customers multiple times with a smiling face and providing courteous and friendly service. In contrast, participants in the low interaction quality condition were informed that the server only returned to the other customers a few times with a neutral or unexpressive face, and the service provided to the other customers lacked politeness and friendliness. Emotional brand attachment was manipulated at two levels: strong and weak, based on prior research on brand commitment (Ashley & Leonard, 2009). More specifically, in the strong emotional brand attachment condition, participants were asked to feel a strong attachment to the restaurant brand, while in the weak condition, there was no strong attachment or close connection to the brand. Emotional brand attachment was experimentally manipulated as a categorical condition (high vs. low), rather than measured as a continuous construct. The gender variable was measured directly by asking participants to indicate their gender identity.

3.2. Measures

To measure the constructs in this study, validated scales with seven-point Likert and multiple items were utilized. Customer orientation was assessed using a five-item scale from previous studies (Brown et al., 2002; Nguyen et al., 2014). Service quality was measured with a two-item scale developed by Brady and Cronin (2001). Inter-item reliability was assessed, and Cronbach’s α values were found to be 0.96 and 0.97, respectively, indicating acceptable internal consistency for all dependent constructs. Furthermore, the items demonstrated significant loadings on their designated latent variables, ranging from 0.90 to 0.98, thus supporting the construct validity. The composite reliability (CR) values exceeded 0.7, and the average variance extracted (AVE) values exceeded 0.5, as shown in Table 1, indicating satisfactory ranges (Fornell & Larcker, 1981).
The effectiveness of the manipulation of interaction quality was evaluated using three items adapted from previous research by Choi and Kim (2013) (e.g., “I think that the quality of the restaurant employee’s interaction with other customers is excellent”). Additionally, to assess the manipulation effectiveness of emotional attachment to the brand, two items from the scale developed by Ashley and Leonard (2009) were employed (e.g., “I feel connected to this brand”). The complete list of measurement items can be found in Table 1. In addition, the conceptual model of the current study can be found in Figure 1.

3.3. Results

3.3.1. Sample and Manipulation Check

A total of 384 subjects participated in this study, all of whom were adults over the age of 18 residing in the United States. The sample had a mean age of 41.7 years, with 49% identifying as male and 51% as female. In terms of racial demographics, 66% of the subjects were Caucasian, while approximately 56% of the participants reported earning an annual income of between $35,000 and $100,000.
To verify the effectiveness of the manipulation, a manipulation check was conducted. The results of independent t-tests indicated significant differences between the two conditions of observed employee-to-other customer interaction quality (M high = 6.16 vs. M low = 2.67, t = 25.957, p < 0.001), confirming that the manipulation was successful. Furthermore, emotional brand attachment also exhibited significant differences (M strong attachment = 5.76 vs. M week attachment = 2.77, t = 17.326, p < 0.001). The ecological validity of the scenarios was assessed using realism measures. Participants evaluated the extent to which the scenario could occur in real life and how realistic it appeared. The results indicate that participants perceived the scenarios as generally realistic (M = 5.12, SD = 1.17), and although a partial difference across conditions was observed, the overall level of realism remained high across all scenarios. Taken together, the results reveal validate manipulations.

3.3.2. Hypothesis Testing

The results revealed a statistically significant main effect of employee-to-other customer interaction quality on perceived employee customer orientation, F (1, 376) = 440.338, p < 0.001, as well as on service quality, F (1, 376) = 478.494, p < 0.001. As hypothesized, observing a higher level of employee-to-other customer interaction quality had a more positive impact on the observing customer’s perceptions of employee customer orientation and overall service quality of the restaurant. Hence, both hypothesis H1 and H2 were supported.
Furthermore, the univariate results demonstrated a significant interaction effect between the gender of the observing customer and employee-to-other customer interaction quality on employee customer orientation, F (1, 376) = 22.690, p < 0.001, η2 = 0.057, as well as on service quality, F (1, 376) = 18.121, p < 0.001, η2 = 0.046 (see Table 2). Notably, observing a lower level of employee-to-other customer interaction quality had a negative impact on the service perceptions of the observing customer, with this negative impact being even stronger for female customers compared to male customers (see Figure 2). These findings support hypotheses H3a and H3b. However, no significant interaction effects were found for emotional brand attachment and employee-to-other customer interaction quality on employee customer orientation, F (1, 376) = 0.976, p = 0.324, η2 = 0.003, and service quality, F (1, 376) = 0.332, p = 0.565, η2 = 0.001. Therefore, hypotheses H4a and H4b were not supported.
Overall, the results indicate that the quality of employee-to-other customer interactions significantly influences customers’ perceptions of employee customer orientation and service quality. The gender of the observing customer also plays a moderating role in these effects. However, emotional brand attachment did not have a significant moderating effect on these relationships.

4. Conclusions and Implications

This study addresses gaps in previous research on observation service experiences, human interactions in service encounters, and the quality of interactions, thus offering valuable theoretical and practical implications. Firstly, it contributes to the limited literature on how customers influence each other in a service encounter without direct interactions, which has been an overlooked research area (Y. S. Kim & Baker, 2019; Voorhees et al., 2017). Consumers do not evaluate their experiences in isolation but often refer to other customers with similar consumption patterns to assess their own experiences (Albrecht et al., 2016). By examining the customers’ observation experience, this research sheds light on the significant impact of observed interactional quality among social actors on customer service perceptions. This effect can be explained through moral equity (Adams, 1965; Oliver & Swan, 1989) and emotional contagion (Hatfield et al., 1993; Barsade, 2002), which jointly shape cognitive fairness evaluations and affective responses. Importantly, this situational effect is strong enough to influence not only new or weak brand-attaching customers, but also those with existing brand relationships. In such contexts, situational cues within the service environment may temporarily override prior brand attachment, reducing its expected buffering role. Notably, the hypothesized moderating effect of emotional brand attachment was not supported, suggesting that situational cues in shared service environments may outweigh the buffering role of prior relational bonds.
Secondly, while customer-contact employees play a crucial role in shaping the quality of service interactions (Baker & Magnini, 2016), there is a lack of research exploring their role in managing multiple customers in shared service environments. This study offers empirical support for the positive impact of employee interaction behaviors, including politeness, friendliness, sensitivity, and positive displays, on service performance judgments. Importantly, these findings demonstrate that these behaviors influence not only the perceptions of direct customers but also those of observing customers.
Third, gender is a significant factor in distinguishing customer segments, particularly in the context of service interactions. Understanding gender characteristics and their influence on perceptions of service quality delivered to others is crucial. This research contributes to the existing literature by examining the effects of gender when observing employee-to-other customer interactions in shared service environments. The findings provide compelling evidence of gender effects on these perceptions. More specifically, while there are no significant differences in the perception of customer orientation and service quality when observing high-quality employee-to-other customer interactions, female customers are more susceptible to the influence of low-quality employee-to-other customer interactions, leading to significantly decreased service perceptions. These findings align with previous evidence suggesting that men and women react differently to low service quality, with women generally being more sensitive to service delivery and quality (McColl-Kennedy & Sparks, 2003). The stronger response observed among female customers can be explained through dispositional empathy and social role theory. Individuals with higher empathic sensitivity are more likely to experience vicarious involvement in others’ service experiences, leading to stronger emotional and cognitive reactions to indirectly observed service encounters (Davis, 1983; Eisenberg & Miller, 1987). In addition, social role theory suggests that women are more likely to be socialized toward relational orientation and interpersonal sensitivity, which may further amplify their responses to low-quality indirect interactions (Eagly et al., 2000). The findings of the study highlight the importance of considering gender differences in the context of managing multiple customers in shared service environments.
Fourth, a notable finding of this study is the lack of a significant interaction effect between emotional brand attachment and employee-to-other customer interaction quality, despite emotional brand attachment being significantly related to service provider quality perceptions (Saavedra Torres et al., 2020; Moussa & Touzani, 2017). This result may seem to diminish the importance of the customer–brand relationship, which has been widely recognized in relationship marketing research (Khamitov et al., 2019). However, this finding can be explained from a perspective of social servicescape management. While customers with strong brand attachments may still maintain a positive attitude towards the service firm (Keller, 2001), their underlying expectations for the quality of interactions between employees and other customers may not significantly differ compared to those with weak brand attachments. This suggests that the actions and behaviors of customer-contact employees play a significant role in shaping customer judgments during a service encounter, regardless of the strength of the customer’s brand attachment. Therefore, the study highlights the crucial role of customer-contact employees in influencing customer perceptions in service encounters, even in the presence of strong emotional brand attachments.
Fifth, our findings shed light on a practical aspect that has received limited attention in the literature: the techniques and policies employed by customer-contact employees to handle multiple customers and maintain interaction quality for all customers involved. While services are typically delivered in the presence of multiple customers, research examining how customer-contact employees manage this aspect in conjunction with maintaining interaction quality is scarce (H. S. Kim & Choi, 2016). The results of this research emphasize the significance of effectively managing multiple customers as a crucial service management strategy. It is evident that even in the absence of direct interactions, customers still have the power to influence one another through the mere act of observation in shared service environments, which is supported by the view of social influence theory research. This highlights the need for organizations to recognize the impact of customer observations and consider effective strategies to manage and enhance the overall service experience for all customers involved.
Lastly, it is crucial for service firms and managers to consider effective motivation strategies for enabling their customer-contact employees to serve multiple customers with the appropriate level of care. From the perspective of employees, adjusting their behavior to meet the interpersonal demands of each customer can be a challenging task and may lead to increased employee turnover (Cho et al., 2016). Therefore, this research holds significant importance as its findings provide empirical evidence that emphasizes the need for organizations to create work environments that effectively address the challenges faced by customer-contact employees who serve multiple customers with different needs at the same time. In other words, managers should prioritize providing tailored training and coaching that focus on the skills needed to appropriately respond to the demands of multiple customers in the social service environment. By doing so, managers can simultaneously promote employee well-being and enhance customer outcomes.

5. Limitations

In addition to recognizing the theoretical and managerial significance of this study, it is important to acknowledge its limitations. Although the researchers aimed to ensure the generalizability of the findings by conducting a hypothetical experiment in one service category, future studies should expand their investigations to include other service categories, such as retail and healthcare services. Moreover, conducting studies in field study settings would further enhance the generalizability of the results. This is especially important because of a potential limitation of this study that relates to the use of a scenario-based experimental design. The relatively large effect sizes observed in the analysis may indicate the presence of demand characteristics, as participants may have inferred the purpose of the study and responded accordingly. While such designs allow for greater control over experimental conditions, they may also lead to more idealized or consistent responses. Furthermore, future research in this area should explore potential differences based on various types of interaction effects. This could include examining the effects of verbal versus nonverbal interactions, interactions between employees, and distinguishing between functional and relational interactions. By considering these factors, a more comprehensive understanding of the dynamics of customer interactions and their impact on service quality can be achieved. In addition, future research should further investigate the mechanisms underlying the non-significant moderating effect of emotional brand attachment, particularly how situational dominance in social servicescape contexts interacts with pre-existing brand relationships.

Author Contributions

Conceptualization, Y.S.K., S.J.K. and D.W.; methodology, B.Y. and Y.S.K.; software, C.S. and Y.S.K.; validation, S.J.K.; formal analysis, B.Y. and Y.S.K.; investigation, C.S. and Y.S.K.; resources, Y.S.K.; data curation, S.J.K.; writing—original draft preparation, Y.S.K.; writing—review and editing, S.J.K. and D.W.; visualization, Y.S.K.; supervision, Y.S.K.; project administration, Y.S.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study due to obtaining an exemption from the California State University.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to privacy restrictions.

Conflicts of Interest

The authors declare no conflicts of interest.

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Tourismhosp 07 00131 g001
Figure 1. Conceptual Model.
Figure 1. Conceptual Model.
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Tourismhosp 07 00131 g002
Figure 2. Interaction Effects of Gender on Employee Customer Orientation and Service Quality.
Figure 2. Interaction Effects of Gender on Employee Customer Orientation and Service Quality.
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Table 1. Measurement Items.
Table 1. Measurement Items.
ConstructItemsCronbach α Factor LoadingCRAVE
Employee Customer OrientationThe restaurant employee tries to help customers achieve their goals. 0.95
The restaurant employee achieves his/her own goals by satisfying customers.0.960.920.960.86
The restaurant employee gets customers to talk about their service needs with him/her. 0.94
The restaurant employee takes a problem-solving approach with their customers. 0.90
The restaurant employee keeps the best interests of the customer in mind. 0.91
Service QualityI would say that the restaurant provides superior service. 0.970.970.970.95
I believe the restaurant offers excellent service. 0.98
Table 2. MANOVA and Univariate Follow-Up Results.
Table 2. MANOVA and Univariate Follow-Up Results.
SourceMultivariate Univariate
Pillai’s TraceFp ValueDVFdfp Value η2
IQ0.584263.6280.000ECO440.3381, 3760.0000.539
SQ478.4941, 3760.0000.560
EBA0.0193.6890.026ECO0.6451, 3760.4220.002
SQ5.4631, 3760.0200.014
Gender0.0234.3430.014ECO8.6901, 3760.0030.023
SQ5.1881, 3760.0230.014
IQ × EBA0.0030.5140.599ECO0.9761, 3760.3240.003
SQ0.3321, 3760.5650.001
IQ × Gender0.06011.8920.000ECO22.6901, 3760.0000.057
SQ18.1211, 3760.0000.046
IQ × EBA × Gender0.0030.640.528ECO1.0321, 3760.3100.003
SQ1.1881, 3760.2770.003
Note. DV = dependent variable, IQ = interaction quality, EBA = emotional brand attachment, ECO = employee customer orientation, SQ = service quality.
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MDPI and ACS Style

Kim, Y.S.; Yoo, B.; Wang, D.; Kim, S.J.; Song, C. Managing Multiple Customer Interactions: Exploring Customer Reactions and Gender Differences in Response to Employee-to-Other Customer Interaction Quality in the Social Servicescape. Tour. Hosp. 2026, 7, 131. https://doi.org/10.3390/tourhosp7050131

AMA Style

Kim YS, Yoo B, Wang D, Kim SJ, Song C. Managing Multiple Customer Interactions: Exploring Customer Reactions and Gender Differences in Response to Employee-to-Other Customer Interaction Quality in the Social Servicescape. Tourism and Hospitality. 2026; 7(5):131. https://doi.org/10.3390/tourhosp7050131

Chicago/Turabian Style

Kim, Youngsun Sean, Bosul Yoo, Danni Wang, Se Jin Kim, and Chanho Song. 2026. "Managing Multiple Customer Interactions: Exploring Customer Reactions and Gender Differences in Response to Employee-to-Other Customer Interaction Quality in the Social Servicescape" Tourism and Hospitality 7, no. 5: 131. https://doi.org/10.3390/tourhosp7050131

APA Style

Kim, Y. S., Yoo, B., Wang, D., Kim, S. J., & Song, C. (2026). Managing Multiple Customer Interactions: Exploring Customer Reactions and Gender Differences in Response to Employee-to-Other Customer Interaction Quality in the Social Servicescape. Tourism and Hospitality, 7(5), 131. https://doi.org/10.3390/tourhosp7050131

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