Guest–Server Exchange Model and Performance: The Connection Between Service Climate and Unit-Level Sales in Multiunit Restaurants

Abstract

Using a sample of 51 full-service restaurants from three competing full-service restaurant companies, we extended the research on service process management by connecting the reactions of service-based employees to guests’ satisfaction with their service experience and firm-level performance. We replicated and confirmed previous tests of the existing guest–server exchange model connecting frontline-level employees’ attitudes toward their work as service providers to guests’ satisfaction in the restaurants. Most notably, we extended the guest–server exchange model by including the relationship between guests’ reports of satisfaction with service and firm performance, bringing together three unique sources of data. The findings from the test of our structural equation model revealed that 26% of the variance in firm performance was accounted for by guest satisfaction, showing that organizational policies and support for employees, are connected to a positive service climate, guest satisfaction, and firm performance, measured as sales per available seat in each restaurant.

Keywords

restaurant food & beverage service climate human resources financial performance financial management

As service organizations continue to grow in prevalence across our economy, the need to further develop our understanding of how hospitality organizations deliver service excellence has never been greater. Hospitality organizations—and in this specific case restaurants—are complex because they mainly deal with combinations of tangible and intangible elements that are offered, bought/sold, and consumed in a very short time frame (i.e., normally within a single service episode; Susskind, 2005). Through these service episodes, restaurant workers and their guests cocreate and interpret their service experiences as part of a shared service climate (W. Kim & Ok, 2010; Mayer, Ehrhart, & Schneider, 2009; Susskind, Kacmar, & Borchgrevink, 2003). Guests and service providers, in turn, evaluate the outcomes that emerge from the guest–server exchange (GSX) based on expectations that are formed through their experiences (Susskind, 2005). These shared experiences and expectations ultimately influence the outcomes of the service environment and how well a service organization performs in both the short and long term (Huang & Miao, 2013).

Related to service-based organizations, existing research has explored several factors that influence the GSX and how line-level employees and guests interact in service-based businesses to produce and consume products and services (Mayer et al., 2009; Schneider, Ehrhart, Mayer, Saltz, & Niles-Jolly, 2005; Susskind et al., 2003). What is noticeably missing from this prior work is the connection between employee-level variables, customer-level variables, and a direct measure of the firms’ financial performance. The primary goal of this study is to expand the understanding of the relationships between line-level service-based employees, guests, and financial performance at the unit level. We do this specifically to offer restaurateurs (and operators of service-based businesses more generally) additional insight into how their staff, customers, and performance are connected through a climate for service. This is important for chain restaurants as each unit is staffed and managed by different people, yet the company’s culture must be pervasive across all the units in the chain.

Very little empirical work has connected these three important elements through the direct measurement of all three components. Research in the services marketing domain has only begun to define the direct connection between guest satisfaction and firm performance as the majority of published studies to date have limited their analyses to secondary data analyses or use proxies for firm performance, such as return intentions, loyalty, service quality, switching costs, market share data, stock price or firm value, such as Tobin’s Q, return on equity, and return on investment (cf. Keiningham, Morgeson, Aksoy, & Williams, 2014; Kumar, Umashankar, Kim, & Bhagwat, 2014; Rego, Morgan, & Fornell, 2013; Schneider, Macey, Lee, & Young, 2009). Hong, Liao, Hu, and Jiang (2013) conducted a meta-analysis of the service profit chain broadly examining the relationships among employees, customers, and firm outcomes. Of the 58 studies they included in their analyses, 17 of the studies had a firm performance measure, with only 11 studies directly accessing financial performance without the use of proxies. Furthermore, only 4 of the 58 studies examined consumers, employees, and firm performance concurrently; and only 2 of those studies included an objective measure of financial performance (see Schneider et al., 2005; Yavas, Babakus, & Ashill, 2010). Based on these findings, we conclude that given the large amount of research conducted on this topic, relatively few studies exist that have tested the GSX or related models using an objective measure of firm performance along with employee and customer variables.

The same measurement gap exists in the hospitality literature. For example, Chi and Gursoy (2009) studied the connection between customer satisfaction, employee satisfaction, and firm performance; their financial performance metric was created by asking managers to rate their company’s financial performance relative to their three major competitors during the past 12 months using a 5-point scale (Chi & Gursoy, 2009), making their measure only a proxy of financial performance. Likewise, Gupta, McLaughlin, and Gomez (2007)—using a large database of guest experience metrics, point-of-sales data, marketing data, and restaurant characteristics—studied the connection between guests’ reactions to their service experience, return intentions, and financial performance; their study did not, however, include service employee-related metrics in their models. Sun and Kim (2013) examined the relationship between customer satisfaction and firm performance using the American Customer Satisfaction Index and were unable to capture unit-level sales directly, a noted limitation in marketing strategy and market-based research which requires researchers to create proxies to measure financial performance (see Rego et al., 2013). Last, G. Kim (2014) tested the service profit chain among a set of chain restaurants in Korea, but only used data from employees and customers.

While these studies offer a better understanding of the components of the GSX, they, fall short of examining the direct relationship between line-level service-based employees, guests, and true unit-level financial performance. As a result, the relationship between the influence of organizational elements such as employees’ views of, and reactions to, their work environment and work-related behavior have not been sufficiently studied in concert with both guests’ reactions to service experiences and true firm financial performance. Our goal in the current study is to fill this gap by modeling the reactions of frontline-level employees and guests on a direct, objective measure of firm performance.

We present Figure 1 as a replication and extension of the research presented by Susskind et al. (2003), Schneider et al. (2005), Yavas et al. (2010), and the meta-analysis conducted by Hong et al. (2013) by adding direct firm performance measurement to the model, a third, unique source of data rarely examined in this type of research.

Figure 1

Hypothesized GSX Model

Guest Service Management

Similar to the GSX, the service profit chain (Heskett, Jones, Loveman, Sasser, & Schlesinger, 1994) describes how organizations create standards and policies designed to elevate employee performance, employee loyalty, and employee satisfaction. Satisfied and loyal employees help create value for the firm, which influences guest satisfaction and guest loyalty. Firm profit and growth emerge from building and maintaining a base of loyal guests. Regardless of the model that managers use to frame their approach to service delivery, it remains important to define and understand the elements that influence employee performance, guests’ reactions to the products and services, and linkages between employees, guests, and unit-level performance (Schulte, Ostroff, Shmulyian, & Kinicki, 2009).

Existing research shows that both the GSX and the service profit chain offer a logical way to examine the relationship between organizational behavior and attitudes and performance outcomes in service-based organizations as a series of mediated steps (Hong et al., 2013). To build on this area of inquiry, we present and examine an extended version of the GSX model which includes a measure of firm performance as an additional outcome variable through a series of six hypotheses.

Theoretical Framework

Role Theory

In service-based organizations, each constituent has a role to play in either delivering or receiving service. When considering high-contact services, such as full-service restaurants, where the guests and service providers cocreate the service experience with notable customer participation in the process (Heidenreich & Handrich, 2015), defined roles and scripts are naturally formed for employees and their customers. That is, each constituent in the service exchange has a role to play in executing the exchange, which is consistent with role theory (Giebelhausen, Robinson, Sirianni, & Brady, 2014; Solomon, Surprenant, Czepiel, & Gutman, 1985). The roles that customers and service providers play in the service exchange are based on expected and learned behaviors that should result in desirable (i.e., planned) outcomes for both parties (Solomon et al., 1985). Furthermore, we argue that the execution of roles in the GSX is dependent on and facilitated by a climate for service (Schneider et al., 2009; Schulte et al., 2009).

Service Climate

A climate for service is defined as a shared set of employees’ perceptions of an organization’s expectations for service-oriented behaviors, which are highlighted, supported, and/or rewarded by the organization. Therefore, a climate for service emerges from a collection of organizational members’ interpretations of organizationally prescribed behaviors (such as organizational standards and practices) and discretionary behaviors (such as organizational citizenship, organizational support, and/or organizational commitment). A climate for service is said to exist when organizational constituents (employees, customers, and managers) share the same or similar beliefs regarding the service exchange.

A climate for service has been shown to influence customers’ reactions to service experiences and firm performance (Schneider et al., 2005; Schneider et al., 2009), and has been shown to embody an organization’s human resources practices, such as shared beliefs encompassing a strategic and/or supportive focus (Schulte et al., 2009). Typically, climates are composed of individual elements that influence or produce both desirable and undesirable outcomes for a firm and its constituents, making climates and the contexts in which they operate thought-provoking theoretically and practically.

The idea of contextual climates is also well established with known applications to contexts such as service and safety (Schulte et al., 2009). Schulte et al. (2009) identified climate configurations as a bundle of factors shown to influence or connect to organizational outcomes. Climate configurations are composed of three components: (a) the extent to which the climate feature is viewed positively (elevation), (b) the extent to which the elements of the climate are agreed on widely by constituents of the climate (variability), and (c) how much the climate varies relative to the measured outcomes (Schulte et al., 2009).

Schulte et al.’s (2009) work showed that it is possible for multiple configurations of climates to exist concurrently in an organization. In this study, we are interested in examining elements that affect employees, elements that affect customers, and how those two elements affect the organization. In essence, we are examining a bundle of climate characteristics that explain performance outcomes. To do so, we look at the interrelationship of service climate variables affecting employees (standards for service and support from coworkers and supervisors), a climate variable affecting both employees and guests (guest orientation), and two related outcome variables (guest satisfaction for the guests and unit-level sales for the firm). While our model recognizes that both servers and guests have a role to play in the GSX, the service climate will influence servers’ behaviors in the GSX. Service climate, therefore, is operationalized in our study as recognized standards for service, supervisor and coworker support, and a generalized guest orientation.

GSX Model

The extended GSX model outlined in Figure 1 identifies three main, interconnected elements: (a) frontline-level employees’ attitudes and behaviors toward their work (i.e., perceptions of service climate), (b) guests’ satisfaction with their service experience, and (c) firm performance measured as unit-level sales. Each element is discussed below.

Frontline-Level Employees

The employee portion of the GSX model begins by considering employees’ perceptions of organizational standards for service delivery present in their restaurants; that is, the extent to which employees believe that the organization has a high level of standards for service.

Standards

Standards are the processes and procedures in place that are used to guide and direct product and service delivery. Standards, or standard operating procedures, outline what is to be done and who should do it and help managers evaluate whether it was done properly. As part of a service climate, standards are positively related to employee attitudes and service performance (Hong et al., 2013), including elements like citizenship behavior (Schneider et al., 2005) and service-related managerial support (Chiaburu & Harrison, 2008; W. Kim & Ok, 2010; Teng, Lee, Chu, Chang, & Liu, 2012). Since frontline-level employees in hospitality organizations tend to be the primary point of contact for guests, the presence of explicit standards are important in shaping service delivery and behavior of frontline-level employees and management (Susskind et al., 2003; Teng et al., 2012). We next introduce support functions and discuss their relationship with standards for service as part of a climate for service.

Support Functions

Perceived organizational support, a second element of climate, is defined as an employee’s belief that he or she receives meaningful work-related support to perform his or her duties (Eisenberger, Huntington, Hutchinson, & Sowa, 1986) and perceived support functions reported by employees are associated with a heightened ability to interpret guests’ needs in a service-based environment (Susskind et al., 2003). The GSX model takes the definition further by framing support functions in organizations in two ways: coworker support and supervisory support (Susskind et al., 2003). The relationships have been further delineated by Chiaburu and Harrison (2008) and Teng et al. (2012) who also found that coworker support operates separately from managerial support.

Coworker support is defined as the extent to which employees believe their coworkers are willing to provide work-related assistance to aid in the execution of their service-based duties (Susskind et al., 2003). In service-based organizations, coworker support is needed for work-related tasks (Chiaburu & Harrison, 2008), but is also connected to other behaviors and affect, such as employee attitudes and organizational citizenship (Hong et al., 2013). Coworker support emerges from frontline-level subordinates and should correspond with other types of formal support from supervisors and managers (Teng et al., 2012). Support from coworkers also has been shown to mitigate negative influences from the service environment and is recognized as a coping tool for frontline-level employees, making coworker support a meaningful service climate element (Huang & Miao, 2013). In a restaurant setting, coworker support at the line level can manifest itself in many ways—such as helping with table maintenance, running food to tables, refilling beverages, and assisting with guests’ requests and needs.

Similarly, in the GSX model, supervisory support is defined as individuals’ beliefs that their supervisors offer them important work-related assistance to help them perform their jobs (Susskind et al., 2003). While supervisors in some instances may help with line-level activities, supervisory support is a mechanism through which communication, training, coaching, scheduling, and the like are used to maintain service quality (Chiaburu & Harrison, 2008). Furthermore, supervisory support has been shown to have a distinct influence in the GSX, highlighting the separate role that supervisors and frontline-level employees play in service-based organizations (Susskind et al., 2003; Teng et al., 2012).

A supportive climate for service has been shown to be connected to service-related behaviors (Hong et al., 2013) and has been shown to improve employee loyalty and employee satisfaction in the service profit chain (Heskett et al., 1994). Standards for service delivery set the stage for required and expected levels of performance (Susskind et al., 2003). The standards are used by the individuals involved in the service process as a behavioral guide, while support helps ensure that the appropriate service-related behaviors are executed and delivered to the guests. Based on the known relationships between standards and support functions described above, we propose the following hypotheses:

Hypothesis 1₀: As part of a climate for service, standards for service are not significantly related to coworker support.

Hypothesis 1_A: As part of a climate for service, standards for service are positively and significantly related to coworker support.

Hypothesis 2₀: As part of a climate for service, standards for service are not significantly related to supervisory support.

Hypothesis 2_A: As part of a climate for service, standards for service are positively and significantly related to supervisory support.

Guest Orientation

In the last step of the frontline-level employee portion of the GSX model, employees’ perceived coworker and supervisory support are presented as antecedents of frontline employees’ guest orientation. In this case, guest orientation is defined as employees’ level of commitment to their guests and the importance they place on guest service as part of a climate for service. Guest orientation has been identified as a set of beliefs that emerge for employees through the service process (Rafaeli, Ziklik, & Doucet, 2008) and defines service providers’ commitment to their guests (Kelley, 1992; G. Kim, 2014; Lam & Mayer, 2014; Susskind et al., 2003). In theory and practice, guest orientation has been referred to as organizational citizenship behavior (Schneider et al., 2005); however, service-oriented behaviors in organizations can be discretionary or formalized as part of the service delivery process (Rafaeli et al., 2008). For example, a discretionary behavior for a service employee may involve offering a guest an opinion or recommendation, while a formal behavior may be the requirement to introduce yourself by name to your guests.

According to Donavan, Brown, and Mowen (2004), guest orientation emerges from a blend of employees’ intrapersonal attributes and the service climate in which they are embedded. This combination of personal and organizational attributes suggests that employees who understand and buy into an organization’s goals and objectives will better fit with the organization (Caplan, 1987; G. Kim, 2014; Tsaur, Luoh, & Syue, 2015), give and receive support from/to their coworkers, and more readily execute their roles in the GSX (Giebelhausen et al., 2014; Solomon et al., 1985).

As noted by Chiaburu and Harrison (2008), Susskind et al. (2003), and Lam and Mayer (2014), when service providers work in a supportive environment a stronger commitment to the service process (and hence guests) is likely to emerge. We present the following hypotheses to test the relationship between employees’ perceptions of support functions and guest orientation in a climate for service:

Hypothesis 3₀: As part of a climate for service, coworker support is not significantly related to guest orientation.

Hypothesis 3_A: As part of a climate for service, coworker support is positively and significantly related to guest orientation.

Hypothesis 4₀: As part of a climate for service, supervisory support is not significantly related to guest orientation.

Hypothesis 4_A: As part of a climate for service, supervisory support is positively and significantly related to guest orientation.

Guests

In the guest portion of the GSX model, guest orientation is presented as an antecedent of guests’ reported satisfaction with service. Guest satisfaction is subsequently presented as an antecedent to unit-level performance.

Guest Satisfaction

Guests do not become satisfied with a restaurant experience by themselves; it is the exposure to and interaction with all of the elements of a service experience that will set guests on a path toward satisfaction (Swanson & Hsu, 2011). Servers with a well-developed guest orientation will be able to read and respond to guest expectations and better satisfy their guests.

As noted above, a service-focused frontline staff wrapped in a climate for service is one key part to making guests happy. A connection between the delivery of quality service and guest satisfaction has been found (Lai, 2015), such that guests who viewed their service staff to be more guest oriented reported higher levels of satisfaction with their experience in restaurants (W. Kim & Ok, 2010). This noted relationship connects elements of a service climate to desired organizational outcomes referred to as the “shape” of the relationship by Schulte et al. (2009), where, in this case, a high presence of guest orientation (opposed to a low presence) affects the outcome (satisfaction).

Schneider et al. (2005) reported that line-level employees’ positive perceptions of service processes and their work was positively related to guests’ service experiences, showing that a high level of positive employee affect among service providers was related to a high level of guest satisfaction with service among their guests (Hong et al., 2013; Lai, 2015; Susskind et al., 2003). Hence, guest orientation is a service climate element that is shared with guests. Based on the relationships noted above between employees’ reactions to their work as service providers and guests’ reactions to service experiences, we present the following hypotheses:

Hypothesis 5₀: Guest orientation, as part of a service climate, is not significantly related to guest satisfaction.

Hypothesis 5_A: Guest orientation, as part of a service climate, is positively and significantly related to guest satisfaction.

Organizational Performance

The last part of the GSX model connects guests’ satisfaction with their service experience to organizational performance. Research in retail/production has shown that customer satisfaction is related to organizational measures of performance including cash flow, return on investment, return on assets, market share, and/or shareholder value (Rego et al., 2013). In these studies, customer satisfaction and perceived service quality are presented as antecedents to guest loyalty, repeat business, and the benefits of reduced switching costs, which are then associated with a higher value of the firm in the marketplace, as indicated by financial metrics. In the existing research among service-based businesses, guest satisfaction has been shown to fully mediate the relationship between employees’ organizational citizenship behaviors and various metrics of firm performance (Hong et al., 2013; Schneider et al., 2005), highlighting the connection between guests’ positive reactions to service experiences and organizational performance.

Surprisingly, as noted above, very few studies examining service-based firms—including hotels and restaurants—have formally examined the connection between guest affect and objective measures of financial performance and even fewer studies have examined the connection between frontline-level employees’ attitudes and perceptions, customer satisfaction, and firm performance concurrently. From the limited research that has been conducted, a positive relationship has been reported between guest satisfaction with the service delivery, attributes of a restaurant experience (e.g., food, service, complaint management), and value in relation to guest counts, repeat purchase intentions, or proxies for financial performance (Chi & Gursoy, 2009; Gupta et al., 2007). Given the anticipated connection between guest satisfaction, service process outcomes, and firm performance, we propose the following hypothesis:

Hypothesis 6₀: Guest satisfaction is not significantly related to firm performance measured as sales per seat.

Hypothesis 6_A: Guest satisfaction is positively and significantly related to firm performance measured as sales per seat.

Method

Participants and Procedure

Six hundred and thirty-nine service workers (servers and bartenders) from 51 casual dining restaurants employed in three full-service chain restaurant firms based in the Midwestern and the Southeastern United States were sampled for this investigation. We approached these three companies to conduct this study because all three chains (a) are consistently ranked by Nation’s Restaurant News as a leading Top 100 chain; (b) they are each mature, well-established brands having operated in United States for over 35 years; and (3) each are known in the industry to have well-established operating procedures and standards in place. These three chains provided us with a chance to test our model.

To gather the data from the guests and the employees, we visited each restaurant on three occasions over a 3-month period. During the three visits to each restaurant, we distributed a total of 30 attitude surveys to be completed by the frontline-level employees at their convenience (servers and bartenders). The paper-and-pencil surveys were collected via a secured drop box left in the managers’ office. The response rate across the employee sample was 41.7%, yielding an average of 12.52 surveys from each restaurant. To collect the guest satisfaction data during our three visits to each restaurant, we asked 30 guests to complete the six question survey as they were exiting the restaurant. We collected 561 responses from guests yielding a 37.7% response rate and an average of 11.32 guests sampled per restaurant.

The restaurants we sampled ranged from 160 to 210 available seats in size (M = 195.64, SD = 10.98), with monthly sales available per seat (based on a 3-month average during data collection) ranging from $732.00 to $1577.20 (M = $971.02, SD = $177.25). The sales data for each unit sampled was provided by the corporate office of each of the three companies after we collected the employee and guest data (see Table 1 and Table 2 in the online supplement for additional information on the three brands studied: available at http://jht.sagepub.com/content/by/supplemental-data).

A total of 57% of the service workers were female, were between the ages of 17 and 53 years (M = 23.90, SD = 6.32), and had worked for their organization an average of 2 years.

Measurement and Analyses

Frontline-Level Employees

Using the survey measures developed and validated by Susskind et al. (2003), we evaluated the frontline-level employees’ perceptions of standards for service delivery with four items (α = .82), coworker support with three items (α = .94), supervisory support with four items (α = .95), and guest orientation with five items (α = .88). The participants were asked to report their agreement with each question on a 5-choice scale ranging from strongly agree = 5 to strongly disagree = 1. To ensure that the sociodemographic characteristics of the frontline-level employees were not connected to any of the variables in the model, we examined sex, education level, age, and tenure with the company. None of the sociodemographic variables were significantly related to the variables in the model; thus, we opted to not include them as controls in our analyses. The survey items and additional information on the sociodemographics of the respondents are included in the online supplement.

Construct Validity

To determine the construct validity of our measures, we conducted confirmatory factor analyses. The results from the confirmatory factor analyses from our LISREL 8.12a (Jöreskog & Sörbom, 1993) analyses yielded a root mean square error of approximation = .08 and a comparative fit index = .96, supporting the factor structure of the survey items, χ²(98) = 552.72, p = .00. To ensure that common method variance was not a concern among each of our line-level employee constructs, we also conducted a Harman’s one-factor test. As expected four a priori factors emerged from the analysis accounting for 75.56% of the total variance. The first factor (supervisor support) accounted for 21.66% of the variance, the second factor (standards) accounted for 18.75% of the variance, the third factor (guest orientation) accounted for 18.45% of the variance, and the fourth factor (coworker support) accounted for 16.70% of the variance. These results showed that no general factor emerged. Combined with the results of the confirmatory factor analysis, we concluded that common method variance is not a great concern among these data.

Guests

We measured guest satisfaction using a six-item single-factor scale adopted from Susskind et al. (2003) applying the same 5-choice scale described above. We aggregated the guest satisfaction data to the organizational level producing an organizational mean ranging from 1.30 (SD = 0.27) to 4.63 (SD = 0.41). This measure also proved to be reliable (α = .95).

Data Aggregation

To ensure that our data were suited to aggregation at the unit level, we calculated and examined the intraclass correlations (ICC[1] and ICC[2]) of each variable in the model which is reported in the online supplement. The descriptive statistics and correlations of the variables aggregated to the unit level are reported in Table 3 and the ICCs are described and reported in the data supplement.

Table 3

Descriptive Statistics and Correlations From the Scales at the Organizational Level

	M	SD	(1)	(2)	(3)	(4)	(5)	(6)
(1) Standards for service delivery	3.63	0.39	—
(2) Coworker support	3.77	0.45	.59**	—
(3) Supervisor support	3.56	0.45	.45**	.26	—
(4) Guest orientation	4.27	0.39	.55**	.70**	.31*	—
(5) Guest satisfaction	3.55	0.93	.40**	.59**	.38**	.66**	—
(6) Sales per seat	971.02	170.76	.28*	.34*	.07	.42**	.51**	—

Note: N = 51 restaurants.

p < .05. **p < .01.

Structural Equation Modeling

Following the confirmatory factor analyses reported above, we tested Figure 1 with LISREL 8.12a (Jöreskog & Sörbom, 1993). We used a maximum likelihood approach and a covariance matrix as input. Based on the recommendations of Hayduk (1987), we allowed the error terms and only the relationships specified in the path diagram to correlate in the structural analyses. To correct for measurement error, we set the paths from the latent variables to the indicators to the square root of the scale reliability at the unit level. Additionally, we set the error variance to equal the variance of the scale multiplied by one minus the reliability in order to fix the proportion of error variance assigned to each factor based on the scale reliabilities and the relevant variance from each factor (Hayduk, 1987).

Results

Test of the GSX Model

The hypothesized model estimation presented as Figure 2 showed that the fully mediated model fit the data well, χ²(9) = 6.75, p = .66; comparative fit index = 1.00, normed fit index = .95, root mean square error of approximation = .00. All of the paths in the model were positive and significant at the p < .01 level except for the path between supervisory support and guest orientation. To test the overall effect of the mediated chain hypothesized in Figure 1 and tested in Figure 2, we examined the indirect effect of standards for service delivery on sales per seat through coworker support, customer orientation, and customer satisfaction. This relationship was significant (.30, p < .01). The indirect effect between standards for service delivery and unit-level performance through supervisor support, guest orientation, and guest satisfaction was not significant due to the insignificant path between supervisor support and guest orientation, indicating that coworker support plays a more significant role in the mediated GSX model than supervisory support.

Figure 2

Estimated GSX Model

The test of Figure 2 revealed that employees who reported high levels of standards for service delivery also reported a high level of coworker support (β = .77, p < .01) and supervisor support (β = .60, p < .01), rejecting the null hypothesis for Hypothesis 1 and Hypothesis 2, respectively. We found a strong and statistically significant association between coworker support and guest orientation (β = .89, p < .01) rejecting the null hypothesis for Hypothesis 3. The null hypothesis was not rejected for Hypothesis 4, as we found no significant relationship between supervisory support and guest orientation. Regarding Hypothesis 5, frontline-level employees’ reports of guest orientation were positively and significantly associated with guest satisfaction (β = .79, p < .01), rejecting the null hypothesis. Last, guest satisfaction was significantly associated with unit-level sales per seat (β = .55, p < .01), rejecting the null hypothesis for Hypothesis 6. The R² for each endogenous variable in the path model is reported in Figure 2 to show the effect size of the relationships.

We ran a set of alternative nested and moderated models to ensure that our model best represented the data. The analyses confirmed that the hypothesized model represented the best fit to the model, and demonstrated that supervisory support was not a significant contributor to the model’s fit.¹

Discussion

Our findings support and build on the work of Schneider et al. (2005; Schneider et al., 2009) and Susskind et al. (2003) highlighting the interrelationship between employees’ reactions to a service climate bundle, guests’ satisfaction, and unit-level performance in service-based organizations. Specifically, this study extended the previous tests of the GSX model to include a measure of actual firm performance using three unique sources of data, showing that in this case, the connection between policies and procedures, when properly translated for and executed by employees as part of climate for service, are indeed connected to better firm performance—measured as sales per seat.

The test of the enhanced GSX model revealed three notable findings, two of which confirmed the GSX model and one of which extended it. First, frontline-level employees’ perceptions of standards were shown to be strongly related to support functions. Second, as the service profit chain also suggests, service orientation among frontline-level employees is connected to happy guests; showing that frontline employees’ perceptions of coworker support were significantly related to their commitment to guest service (measured as guest orientation). Similarly, reported support from frontline-level employees’ supervisors was not significantly connected to their levels of guest orientation, highlighting the different roles that support plays in service-based organizations. While the latter finding was counterintuitive, by design management would be less involved in the service delivery and implementation on the floor of the restaurant, where support from coworkers takes place. Furthermore, supervisors are one hierarchical level removed from the guests and might be less involved in shaping server guest orientation as measured. This suggests that a service climate dimension or climate bundle surrounding supervisory or managerial support may exist. Last, and most important, higher levels of guest satisfaction were connected to higher unit-level performance (sales per available seat), extending the GSX model to include a direct measure of operational performance.

Implications for Theory

Our study makes three contributions to the theory behind service-based organizations. First, we have shown that a specific service climate bundle exists and is connected to organizational outcomes similar to what Schulte et al. (2009) reported in their study of banks and food distribution stores. The climate bundle we formed in the GSX consists of employees’ reactions to high levels of organizational standards, support functions, and guest orientation. There are likely other climate configurations that exist in service-based organizations that can have both a positive and negative effect on organizational outcomes. Future research should attempt to define these unmeasured dimensions. Next, the statistically significant connection from standards to supervisory support followed by the nonsignificant connection between supervisory support and guest orientation suggests that supervisory support is likely a part of an additional service climate bundle, which could be captured through the measurement of managers. It also is possible that the service climate configuration or bundle for employees overlaps with the bundle for managers. A service climate bundle for management would likely be more broad and related to hiring, training, coaching, and monitoring to ensure each line-level employee has the tools needed to succeed, while coworker support would be more connected to the direct interaction and involvement with the service process and guests during the shifts (as measured here). The importance of coworker support in our model provides evidence for Bowen’s (2016) recognition that service exchanges, such as those captured by our model, can no longer be viewed as simple dyadic exchanges, but are dependent on more complex service systems. One of the service roles that Bowen (2016) identifies, enabler, is enacted by coworkers. Another role Bowen (2016) specifies, coordinator, is captured by our measure of supervisor support. This set of relationships needs additional testing to better define the boundaries of service climate elements in service-based organizations.

Last, based on the positive connection between guest orientation and guest satisfaction, we have confirmed that when servers positively fulfill their role by reading guest expectations and providing the correct level of guest service, guests will react positively in their role in the GSX, supporting the conception of role theory in service-based organizations (Bowen, 2016; Giebelhausen et al., 2014; Solomon et al., 1985; Tax et al., 2013).

Practical Implications

In sum, our findings emphasize the importance of articulating standard operating procedures. Given the strong connection that service standards have to employee affect and ultimately firm performance, it is imperative that standard operating procedures are established and clearly articulated for each type of employee in the organization (i.e., for different frontline-level positions, supervisory positions, and managerial positions). Very simply, standards, and how they are articulated, shape the way individuals view and execute their service-related duties. This is particularly important for chain restaurants that aim to have service experiences for their guests executed consistently both within each unit and across all units in the chain. Whether formally codified in standard operating procedure manuals or informally disseminated through day-to-day interaction among staff (i.e., coworker support), standards are the mechanism that allow operators to set the stage for the guest experience. All companies have some form of standards in place; what separates good from great companies is how well the standards are articulated and executed by their frontline-level staff on a daily basis, and whether employees are held accountable for adhering to and meeting said standards. Ultimately, management sets the tone and helps build the climate and culture of the organization, as they hire and retain the people who directly interact with guests to deliver the service experience.

As noted above, consistent with role theory (Chiaburu & Harrison, 2008; Solomon et al., 1985), standards help lay the foundation for supportive behaviors from both coworkers and superiors, but employees and managers play a distinct role in service-based organizations that result in different actions and outcomes. Support functions therefore help build a climate for service. Operators should be mindful that building a strong service climate is important and can pay dividends in several ways, with outcomes such as better morale, a more satisfying work environment, and lower voluntary turnover (Hong et al., 2013).

Happy Employees = Happy Guests

Our findings from the test of the extended GSX model show that guest-oriented employees are better able to fulfill their role as service providers and offer their guests the required level of service (Chiaburu & Harrison, 2008; Solomon et al., 1985; Surprenant & Solomon, 1987). While this may seem elementary, the process of creating and fostering an environment that creates guest orientation is far from simple. It begins with hiring employees with the requisite skill set, the appropriate cultural fit, and desired traits so line-level employees can be successful and happy. Cropanzano and Wright (2001) suggest that happiness is a relatively stable personal characteristic which could be used in selection. Additionally, their research suggests that productive employees are indeed happy employees, further emphasizing the importance of the selection process.

Happy Guests Lead to Better Unit-Level Sales Performance

Last, in our study, guest satisfaction was shown to be strongly related to unit-level performance. This relationship is an important one, but needs to be interpreted carefully. In the GSX model, guest satisfaction accounted for 26% of the variance in unit-level sales (which is quite high for a single variable), leaving nearly three quarters of the variance in sales performance unaccounted for in the model. So yes, guest satisfaction is significantly related to higher sales levels at the unit level, but there is more to it. What our data show is that other factors not measured here also are connected to unit-level performance. Some of these unmeasured factors might be repeat patronage intentions, the ambiance, more macro factors such as weather, competition, or the broad based factors in the economy (e.g., gas prices, unemployment rate, and the cost of consumer goods). Guest satisfaction is an important part of any business’ success, but success emerges from a confluence of many factors (Parsa, Self, Njite, & King, 2005).

Limitations and Conclusion

It is important to note a few limitations of our study and offer some directions for future research. First, we used a relatively small sample of a single type of service organization (i.e., restaurants). While the sample composition is similar to studies of this type (see W. Kim & Ok, 2010; Mayer et al., 2009; Schneider et al., 2005; Teng et al., 2012), future studies would benefit from the statistical power afforded by larger samples and the potential for capturing additional variance through different types of service organizations. Second, we tested the model at the organizational level. Consistent with the findings of Hong et al. (2013), the aggregation statistics showed that unit-level analyses were appropriate with this sample; it would, however, be valuable to match employees and customers at the unit level (see Stock & Bednarek, 2013) to offer a dyadic or triadic analysis which includes a direct connection between guests and/or their specific service providers, and unit performance indicators when possible. Additionally, a matched sample of employees, guests, and revenues would open the door for the use of multilevel modeling to simultaneously account for effects at both the individual and unit level concurrently.

In conclusion, the mechanics behind service operations are complex and dynamic. Studies such as this help highlight the important parts of the service process and offer operators a look into how service processes unfold for employees, guests, and management. The expanded GSX presented here, provides operators a road map to build and execute procedures and processes to benefit restaurant employees, guests, and operators alike in a service climate built around excellence.

Supplemental Material

Supplemental_Materials – Supplemental material for Guest–Server Exchange Model and Performance: The Connection Between Service Climate and Unit-Level Sales in Multiunit Restaurants

Supplemental material, Supplemental_Materials for Guest–Server Exchange Model and Performance: The Connection Between Service Climate and Unit-Level Sales in Multiunit Restaurants by Alex M. Susskind, K. Michele Kacmar and Carl P. Borchgrevink in Journal of Hospitality & Tourism Research

Footnotes

Notes

Alex M. Susskind is an Associate Professor of Food and Beverage Management in the School of Hotel Administration at Cornell University. K. Michele (Micki) Kacmar is a professor in the Department of Management at Texas State University. Carl P. Borchgrevink is an Associate Professor at The School of Hospitality Business at Michigan State University.

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