Is Seeing Eye to Eye Always Beneficial? How and When (Dis)agreement on Service Climate Influences Store Turnover and Sales Performance

Abstract

This study examines the effect of (dis)agreement between the employees and their store manager regarding service climate on store-level turnover and subsequently sales performance. In addition, we test the moderating effect of perceived employee fit with customers on these relationships. Using polynomial regression and response surface methodology with data from 753 frontline employees and 125 managers nested in 125 stores, we found that collective turnover is lower when the store manager and the employees both perceive (vertical agreement) that customer service is prioritized at moderate levels. However, turnover is higher when managers and employees do not agree on the level of the service climate (vertical disagreement). The results indicate that the beneficial effect of vertical service climate agreement on turnover was higher when perceived employee-customer fit was high. The detrimental effect of vertical service climate disagreement on turnover was reduced when the strength of employees’ service climate was strong (high horizontal agreement). Furthermore, our examination found that the level of turnover in stores was negatively related to sales performance and that the effect of vertical service climate agreement on sales performance was conditional on the degree of perceived employee-customer fit.

Keywords

service climate (dis)agreement customer fit store turnover sales performance

Research has demonstrated that frontline employees are more motivated to deliver high-quality service and to remain with their organization longer when they share the belief that the organization values customer service (Gracia, Cifre, and Grau 2010). These shared values, referred to as a service climate, have obvious implications for customer experiences and organizational performance (Hausknecht and Trevor 2011; Hong, Liao, and Jiang 2013; K. Jiang et al. 2016; Kacmar et al. 2006; Schneider et al. 2005). Yet, researchers have mainly examined service climate through team members’ or customers’ aggregated perceptions (Dean 2004), which implicitly assumes that managers do not hold distinct evaluations of service climate (Matta et al. 2015). This is troubling, in that there is considerable evidence to suggest that employees and managers do frequently disagree in their work-related assessments (Bashshur, Hernández, and González-Romá 2011; Gibson, Cooper, and Conger 2009; McKay, Avery, and Morris 2009) and that a lack of mutual understanding regarding customer service policies can undermine their successful implementation (Gibson, Cooper, and Conger 2009). To address this gap in the customer service literature, this article explores how employee-manager (dis)agreement regarding the level of service climate may affect store-level turnover and sales performance.

Furthermore, although scholars have identified specific conditions under which investments in customer service return benefits (see the review by Bowen and Schneider [2014]), they have not explored moderators of the influence of service climate (dis)agreement. Inspired by prior research on the importance of perceived similarities between salespeople and customers in terms of customer outcomes (L. Jiang et al. 2009; Netemeyer, Heilman, and Maxham 2012), the present study examines whether the extent to which store team members’ perceptions of their fit with customers moderates the relationship between employee-manager (dis)agreement on service climate and store performance.

The current study has the potential to advance theory and practice in several ways. By focusing on perceptual (dis)agreement regarding service climate, our study offers a theoretical contribution to the person-environment (P-E) fit literature and a finer understanding of the attraction-selection-attrition (ASA) model (Schneider 1987). As Vogel, Rodell, and Lynch (2016) recently pointed out, the ASA theory supposes that divergences on organizational goals and processes may lead to employee attrition and subsequently to negative sales outcomes. Our study challenges this view by proposing that disagreement on the level of service climate does not always prompt negative reactions or outcomes. More specifically, we tested how team members’ perceived fit with customers influences the impact of their level of (dis)agreement with their manager regarding service climate on store-level outcomes. As such, our research also contributes to the employee-customer fit literature by examining how this understudied type of fit may intensify the effects of agreement on service climate and weaken the effects of disagreement on store outcomes. In terms of practical importance, by clarifying the conditions under which (dis)agreement between employees and their managers with respect to service climate affects collective turnover and sales efficiency, our results can help guide managers in their attempts to manage these important performance indicators. Figure 1 displays the study’s overall theoretical framework.

Figure 1.

Conceptual model.

Conceptual Background

Perceptual Agreement/Disagreement in Service Research

The ASA model (Schneider 1987) helps to explain how fit assessments emerge in the workplace and how they influence employee behavior by elaborating the role of organizational goals and processes in determining the types of people who are attracted to, selected by, and retained by a particular organization. In service settings, for instance, an organization that promotes high service excellence is likely to attract and select people who endorse this value. In turn, people whose values fit the environment are more likely to remain longer in the organization, whereas those who do not are more likely to leave. Socialization processes, initiated either by the immediate supervisor and/or existing team members, provide job incumbents with social cues that shape their personal values and perceptions such that these become more closely aligned with those held by current members of the organization or its representatives (Cable and Parsons 2001). Over time, these processes lead the organization to become more homogeneous (Schneider 1987).

However, certain factors may lead individuals, teams, and supervisors to maintain different perceptions when faced with the same stimuli or events (Gibson, Cooper, and Conger 2009). Disagreements regarding the organization’s goals and values may result, for instance, from recruitment, selection, and placement errors (Schneider 1987), inadequate communication from the store manager, or differences in position and power between the manager and his or her team (Bashshur, Hernández, and González-Romá 2011). Indeed, although managers and team members are two potentially important sources of information for a given employee, their influence is not always symmetrical. On the one hand, formal leaders are frequently considered as primary shapers of members’ affect, beliefs, and behaviors owing to their freedom to express their beliefs and opinions (Keely and Barsade 2001; Seong and Choi 2014). On the other hand, service climate perceptions of work group members may have a greater influence on group outcomes because they are a more proximal determinant of group behaviors (Carter and Mossholder 2015; Matta et al. 2015).

Service Climate Agreement and Store-Level Turnover

A collective climate generally signals what types of behaviors are encouraged, expected, and rewarded (Schneider, Macey, and Young 2006). Prior research has provided evidence that unit-level service climate positively relates to various unit-level outcomes (Borucki and Burke 1999; Chuang and Liao 2010; Hong, Liao, and Jiang 2013; Salanova, Agut, and Peiró 2005). However, this body of research has not explicitly examined how differences in service climate perceptions between store employees and their manager may affect turnover and subsequently sales performance.

Service climate refers to the extent to which people who work for an organization share the perception that the policies, procedures, standards, technology, and expected employee behaviors emphasize and facilitate service excellence (Schneider, White, and Paul 1998). Service teams and leaders who agree on process standards and work routines can complete service tasks more efficiently, given the mutual understanding and shared mental models of the behavioral scripts that guide a team’s activities (Mathieu et al. 2000). Clearly aligned and agreed-upon work routines serve as guidelines that enable team members to reduce task uncertainty and standardize task execution (Cordery et al. 2010). This mutual understanding regarding the level of customer service climate facilitates the emergence of a shared plan of the processes needed for accomplishing tasks (Hu and Liden 2011). Agreement between employees and their manager may occur at high and low levels. We may surmise that collective turnover is lower when both employees and the manager perceive a high level of service climate compared to when both perceive the level of service climate is low.

There is pervasive evidence that agreement at a high level of favorable perceptions of the work context between leaders and team members is associated with various positive outcomes (e.g., Bashshur, Hernández, and González-Romá 2011; Ostroff, Shin, and Kinicki 2005). A recent study of service climate by Benlian (2014), for instance, revealed that team performance was greater when team- and leader-rated service systems were both high, rather than when both were low. When store employees and their managers agree that customer service is a high priority, employees are more reassured that they will receive the necessary support and rewards to accomplish their role. These positive expectations and experiences have a positive impact on their desire to remain in their jobs (Sowinski, Fortmann, and Lezotte 2008).

By contrast, in situations in which employees and the manager agree that customer service is a low priority, two opposite effects may occur. On the one hand, ASA theory suggests that agreement, even at a low level, will tend to discourage turnover because these stores are more likely to attract managers and employees who share a weak interest in the customer. On the other hand, shared beliefs in a low level of service climate will tend to indicate for most employees that it was a mistake to accept a position within the organization (Schneider 1987), and provide low inducements or job embeddedness, which would increase the probability of turnover. Thus, we propose the following hypothesis:

Hypothesis 1: Store turnover will be lower when the store manager’s perception and employees’ shared perception regarding the level of service climate are in agreement and high, rather than in agreement and low.

Disagreement on Service Climate Perceptions and Store-Level Turnover

Disagreement may occur when the leader and the team have access to different information, hold divergent interpretations of the same information, or have different points of reference for the team (Gibson, Cooper, and Conger 2009). The existing literature has revealed the detrimental effects of such divergences between managers and employees. For example, Bashshur, Hernández, and González-Romá (2011) found that when team managers and team members disagreed with respect to the level of perceived organizational support (POS), team performance decreased. Their study revealed, moreover, that the negative effects of disagreement were stronger when managers perceived that the team received higher levels of support than the team itself did, in other words, when the manager overestimated the level of POS relative to employees’ estimations.

We argue that the resulting dynamic is more detrimental for store outcomes when it is the store manager who “overestimates” the service climate, that is, when he or she perceives the service climate in a more positive manner compared to his or her employees. In such situations, important task and goal conflicts may arise with the superior. This may lead to a lack of clarity about working standards, procedures, and expectations or else may entail feelings of loss, disorientation, and frustration. Employees may find such situations highly stressful and demotivating since they may be experienced as a gap between the perceived job demands (high service selling expectations and goals set by the superior and role conflicts) and job resources (low training, weak incentives). There is considerable evidence that working in a demanding context with few resources is associated with higher turnover (Schaufeli and Bakker 2004). For instance, Sowinski, Fortmann, and Lezotte (2008) found a marginal relationship between the strength of customer service perceptions and unit turnover and suggested that a lack of employee-manager agreement on the capability of human resources to deliver superior quality service and on training and rewards adequacy to deliver high customer service may elicit higher role stress, frustration, and conflicts with managers and subsequently higher voluntary turnover (Schneider 1980; Sowinski, Fortmann, and Lezotte 2008).

On the contrary, when it is the employees who overestimate the service climate relative to the manager’s perception, they perceive that their unit places more value on customer service excellence. While this lack of agreement may still influence store outcomes, due to a lack of mutual understanding between employees and the manager, it can be argued that it will not be as severe as when the manager overestimates the service climate. Research on self-fulfilling prophecies (Eden 1984), for instance, suggests that simply believing that the organization offers sufficient resources and rewards to provide excellent customer service may motivate store employees to exhibit the expected behaviors. According to Kristof-Brown, Li, and Schneider (2014), these beliefs may lead teams to fully understand and appreciate the customer service actions taken by the organization. Therefore, we propose the following hypothesis:

Hypothesis 2: Store turnover is higher when the store manager’s perception of the service climate is higher than the employees’ shared perception, rather than when the employees’ shared perception is higher than the store manager’s perception.

Employee-Customer Fit as an Enhancer of Agreement and as a Buffer of Disagreement

The notion of P-E fit refers to the similarity between the person and the environment (Edwards and Cable 2009). P-E fit has been conceptualized as an overarching construct that includes several types of fit, such as person-vocation (P-V) fit, person-job (P-J) fit, person-superior (P-S) fit, person-group (P-G) fit, and person-organization (P-O) fit (Kristof-Brown, Zimmerman, and Johnson 2005). There is pervasive evidence that employees who experience a poor fit with their environment are more likely to leave the organization (Boon and Biron 2016). Of these various types of fit, the P-O and P-J fits are the most widely studied.

Marketing scholars have recently begun to examine a new type of fit, namely, person-customer (P-C) fit (Jaewon 2016). At the individual level, P-C fit captures the degree to which employees perceive an interpersonal compatibility with the customers they serve. Although the bulk of P-E fit research has principally focused on the “person” as the referent for comparison, a growing number of scholars have begun to study the fit construct at the group level (Kristof-Brown et al. 2014; Seong et al. 2015; Shin 2008). The present study examines the notion of employees-customer (E-C) fit climate, which refers to the shared perception that the personalities and values of the employees are similar to those of the customers.

We draw on the perceived self-other similarity theory and on P-E fit theory to explain why employees’ perceived fit with customers may moderate the impact of agreement/disagreement on service climate perceptions. The perceived self-other similarity theory (Byrne 1971) suggests that individuals who perceive similarities with others on attitudes, values, and traits are attracted to these people, motivated to develop and maintain affiliation with groups composed of these people, and work to support this environment (Kristof-Brown, Li, and Schneider 2018). When individuals perceive self-similarity with others, they are more likely to take the perspective of these individuals and to enter into social exchanges with them. This perceived self-similarity with customers elicits close interpersonal bonds and fewer conflicts with customers, reducing the turnover of frontline employees.

We propose that collective turnover will be lower when the manager’s and employees’ perceptions regarding the level of service climate in the store are in agreement and high, and the perceived fit with customers is high. According to Tett and Burnett (2003), when traits or characteristics are thematically connected with the cues of the environment, employee or team behaviors are more positive. Employees who feel a high degree of fit with customers and perceive that service excellence is encouraged, supported, and rewarded are more likely to exhibit lower turnover because the environment is compatible with their characteristics. Conversely, we expect a higher level of turnover in stores in which employees and the manager agree that the service climate is low and the perceived customer fit is also low. Although there is compatibility between the situation and workforce characteristics, the motivation to remain is low because this environment is neither stimulating nor rewarding. Therefore, we propose the following hypothesis:

Hypothesis 3: Agreement on service climate elicits a lower store turnover when employees’ perceived fit with customers is high, rather than when it is low.

With respect to disagreement on service climate perceptions, we posit that a higher E-C fit may mitigate its deleterious effect on turnover, whereas a low customer fit amplifies this relationship. In weak situations, such as when disagreement on service priorities is high, team members’ behaviors are more likely to be idiosyncratic or self-prompted, guided by their unique characteristics (Mischel 1976; Tett and Burnett 2003). Under these conditions, a high degree of perceived customer similarity should stimulate more compassion-related responses and higher customer-directed citizenship behaviors because the self-other similarity increases perspective-taking and feelings of attachment and responsibility (Oveis, Horberg, and Keltner 2010). In addition, research suggests that perceiving shared values with others, such as customers, increases one’s willingness to act at a cost to oneself (Krebs 1975). These altruistic actions are more likely to be noted and reciprocated by customers through more respectful and rewarding affective relationships with frontline employees, providing them the motivation to remain, despite a conflicting perception with their manager with regard to customer service priorities.

On the other hand, we expect that store turnover is higher when disagreement on service climate perceptions is high and E-C fit is low. Research suggests that perceiving a lack of fit at work seriously undermines employees’ intentions to remain in the organization (Schneider et al. 2005). First, disagreements on service priorities, resources, and rewards are likely to elicit task and emotional conflicts with the manager and the perception among employees that the organization does not provide them with adequate support. Second, a perceived lack of fit with customers can lead team members to experience opinion disagreements with customers, further exacerbating the level of conflict at work, eroding their job embeddedness and motivating actual turnover decisions (K. Jiang et al. 2012). Therefore, we propose the following hypothesis:

Hypothesis 4: Disagreement regarding service climate elicits a higher store turnover when employees’ perceived fit with customers is high, rather than when it is low.

Turnover as a Mediator of the Relationship Between Service Climate (Dis)agreement and Sales Performance

The relationship between employees’ shared service climate and operational and financial unit outcomes is well-documented in the literature (e.g., Borucki and Burke 1999; Hong, Liao, and Jiang 2013). However, except for the study by McKay, Avery, and Morris (2009) on climate diversity, we are not aware of any research that has examined the influence of (dis)agreement regarding perceptions of service climate on unit sales performance. We propose that the effects of (dis)agreement on unit sales are mediated through workforce stability or retention.

A recent body of research has linked turnover to customer service outcomes and subsequently to firm efficiency and profitability (Holtom and Burch 2016). A recent meta-analysis (Park and Shaw 2013) indicates that a turnover rate of between 12% and 22% decreases sales growth from .22 to .13, which is a reduction of 40%. Several theoretical justifications have been proposed to explain this relationship. Hausknecht, Trevor, and Howard (2009) argued that voluntary turnover hampers customers’ perceptions of service quality because turnover creates operational disruptions within the work unit by depleting firm-specific knowledge and experience from the unit, as leavers are replaced with individuals who lack knowledge of the current work processes. Thus, customers receive service from less knowledgeable and less experienced staff. In addition, turnover burdens remaining employees with activities that divert attention away from quality service provision (Shaw et al. 2005).

All in all, we posit a partial mediation effect of turnover because there may be other mechanisms through which these (dis)agreements regarding customer service perceptions can influence sales performance. For example, the customer service literature review by Bowen and Schneider (2014) indicates that customer-focused organizational citizenship behaviors and customer satisfaction are two important mechanisms through which (dis)agreement regarding service climate perceptions can influence sales performance. Therefore, we posit the following hypothesis:

Hypothesis 5: Store-level turnover partially mediates the relationship between employee-manager (dis)agreement regarding the service climate and unit sales performance.

Given the proposed moderating effect of E-C fit on turnover, we argue that the indirect relationship between (dis)agreement regarding service climate perceptions and sales performance depends on the degree of customer fit. Recent research suggests that P-C fit may lead, directly or indirectly, to less stressful emotional customer interactions, more authentic behaviors toward customers (Jaewon 2016), and higher customer relationship satisfaction and loyalty toward employees (Jamal and Adelowore 2008). It has been proposed that the similarity between a salesperson and a customer has the potential to increase the persuasiveness of the sales pitch, thus influencing purchasing intentions (L. Jiang et al. 2009) and actual customer spending (Netemeyer, Heilman, and Maxham 2012).

The positive influence of customer fit on sales performance is likely to be stronger when agreement on service climate is at high levels because the store’s members will tend to perceive adequate support and rewards to accomplish their role, and the various aspects of the environment are highly aligned. However, when disagreement on perceptions of service climate occurs, we predict that employees will continue to demonstrate high loyalty behavior and exhibit high sales performance because they have developed positive relationships with customers, and these positive customer experiences generally translate into higher sales (Netemeyer, Heilman, and Maxham 2012; Schneider et al. 2005). However, we expect that the sales performance in these stores will be lower compared to stores that exhibit a high agreement on service climate. Therefore, we posit the following hypotheses:

Hypothesis 6a: Agreement regarding perceptions of service climate elicits a higher sales performance (via turnover) when the customer fit is high, rather than when it is low.

Hypothesis 6b: Disagreement regarding perceptions of service climate elicits a lower sales performance (via turnover) when the customer fit is high, rather than when it is low.

Method

Procedures and Participants

The sample comes from a major international retailer based in Canada. A web-based survey was conducted. Human resource representatives sent invitation letters to the managers and employees working in the retailer’s Canadian and U.S. stores to enlist their collaboration. This letter included the web link for the survey site. A total of 1,715 employees from 433 stores responded to the survey. Because of missing values, data from 1,619 respondents were used in the analyses. The respondents were predominantly female (79%), with a mean age of 23.4 years (standard deviation [SD] = 5.4), working full time (68%). They had accumulated, on average, 2.1 years of service (SD = 2.5), and 72% left the organization in the 1-year period following the survey. Because the hypotheses are focused on the store level, we retained only the stores in which the three following conditions were met: (1) three employees or more responded to the survey, (2) the store manager agreed to participate in the study, and (3) complete information was provided on store turnover and sales performance. The final sample consisted of 753 frontline employees and 125 managers working in 125 stores, for an average team size of 5.8 employees per store. The leaders’ average age was 27 years, and 75% of the leaders were female. The leaders’ average seniority was 3.1 years. Furthermore, no significant differences in demographic characteristics were found between the original and the studied samples (e.g., full time: .28 vs. .27; work hours: 18.4 vs. 18.2; female: 79% vs. 78%). We also found no substantial differences between the initial sample and studied stores in terms of turnover rate (.52 vs. .50) and sales performance (CAD$1,219 per employee vs. CAD$1,257).

Measurement Instruments

For all indicators, respondents had to state their degree of agreement on a scale ranging from 1 (completely disagree) to 7 (completely agree).

Service climate perceptions

Perceptions of service climate were evaluated with the 7-item Global Service Scale developed by Schneider, White, and Paul (1998), which is a 7-point Likert-type scale (1 = poor to 7 = excellent). Items included the following: “Rate the efforts made by your company to assess the quality of the service it provides” and “Rate the job knowledge and skills of your fellow employees to deliver excellent quality service.” We calculated the average ratings across all items and team members and for each manager in every store. Cronbach’s α for this scale was .93. We aggregated individual employees’ perceptions to the store level to form the measure of service climate. The median level of rwg(j) was .91, the intraclass correlation coefficient (ICC1) was .14, and the ICC2 was .68, providing support for aggregating to the store level. Each store manager was invited to answer an identical set of 7 items evaluating their perceptions of the level of service climate in the store.

Customer fit climate

The E-C fit climate was evaluated with a 3-item fit scale built on that of Cable and DeRue (2002). Items included the following: “The values of the customers correspond to those of the people who currently work in your brand” and “To what extent do you feel that customers who enter this store correspond or fit to employees?” Because the items refer to team members rather than the individual, our measure is analogous to a referent shift construct (Chan 1998). We calculated the average ratings across all items and store employees in every store. Cronbach’s α for this scale was .93. We aggregated the individual employees’ perceptions to the store level to form the measure of customer fit climate. The median level of rwg(j) was .91, the ICC1 was .16, and the ICC2 was .58, providing support for aggregating to the unit level.

Store turnover

The turnover data were provided by company records, and turnover was assessed as the percentage of employees who voluntarily left each unit. Typically, collective turnover was measured as a turnover rate by dividing the number of leavers during the period by the workforce size. We were provided with turnover data for twelve months following the survey.

Stores’ sales performance

Following previous research (Ployhart, Weekley, and Ramsey 2009; Schneider et al. 2005), sales data, provided by company records, were collected for each store in the sample in the form of sales per quarter. Because the stores varied in size, we created a standardized sales score by adjusting for store size. More specifically, we calculated sales per employee by taking the stores’ quarterly sales and dividing them by the average number of sales per employee at the beginning of the study. This index is frequently used to measure productivity (Ployhart, Weekley, and Ramsey 2009). Sales data were collected for twelve months following the survey.

Control variables

We collected data on average age and tenure, percentage of male versus female employees, and percentage of full-time versus part-time workers because research suggests that these demographic variables are more likely to foster important workplace attitudes and behaviors in the retail industry (e.g., Lucas et al. 1987; Zeytinoglu et al. 2004). The results indicate that average employee tenure (b = −.22, p < .05) was significantly related to turnover. However, neither average age (b = .02, p > .05) nor the percentage of full-time workers (b = −.11, p >.05) nor gender composition (b = .06, p > .10) was significantly related to turnover. Following recent recommendations and research findings (Becker 2005; Carlson and Wu 2012; Vogel, Rodell, and Lynch 2016) regarding the superfluous inclusion of control variables, we did not include control variables in our models. We tested hypotheses related to turnover both with and without average seniority as a control variable, and the direction of results and their significance were fairly similar (with average tenure: service climate: −.06, p < .01; without tenure: −.054, p < .01). Given the weak influence of demographic variables, results are reported without them. Table 1 presents the unit-level descriptive statistics and correlations among the study variables.

Table 1.

Means, Standard Deviations, and Correlations Among Variables.

Variables	Mean	SD	1	2	3	4
Employees-rated service climate	6.01	.60
Manager-rated service climate	5.75	.80	.23**
Employees-customer fit	5.87	.48	.45**	.03
Store turnover	0.46	.30	.02	−.03	−.03
Sales efficiency	0.91	.42	.12**	.07	−.01	−.29**

**p < .01.

Analyses

To test the effects of customer service agreement, we used polynomial regression and response surface analysis (Edwards and Parry 1993), which allows for a three-dimensional rather than a two-dimensional examination of the relationships between combinations of predictors and outcome variables and enables tests of nonlinearity in different combinations of relationships (Rhoades-Shanock et al. 2010). The general form of the regression equation is as follows: Z = b₀ + b₁SE + b₂SM + b₃SE² + b₄SE × SM + b₅SM², where Z is the dependent variable (turnover in store), SE and SM are store employee–rated and store manager–rated service climate perceptions, respectively, and SE², SE × SM, and SM² represent three second-order terms. Consistent with Edwards and Parry (1993), we centered predictors at the midpoint of the scale before calculating the three secondary polynomial terms to reduce multicollinearity. The polynomial response surface was evaluated along four surface values as follows (Edwards and Parry 1993): a₁ (SE = SM, b₁ + b₂, the slope of the line of perfect agreement), a₂ (SE = SM, b₃ + b₄ + b₅, the curvature along the line of agreement), a₃ (SE = −TM, b₁ − b₂, the direction of the difference), and a₄ (SE = −SM, b₃ − b₄ + b₅, the curvature of the line of disagreement).

To test the indirect effect of (dis)agreement regarding perceptions of service climate on unit sales through turnover, we used the block variable approach proposed by Edwards and Cable (2009). We created a block of variables by multiplying the estimated polynomial regression coefficients with the raw data to obtain a weighted linear composite (see Cole, Carter, and Zhang 2013; Matta et al. 2015; Zhang, Wang, and Shi 2012). We then first regressed the turnover on the block of variables to obtain a regression coefficient commonly referred to as the “a” path in mediated models. We next regressed sales performance on the mediating variable (turnover) and the block of variables. The regression coefficient for the mediating variable on the outcome represents the “b” path. We tested the mediation hypotheses with the bootstrapping approach proposed by Hayes (2013). The significance of the indirect effects was tested using bias-corrected confidence intervals (CIs) constructed from 10,000 bootstrap samples (Efron and Tibshirani 1994).

Results

Influence of Agreement and Disagreement Regarding Perceptions of Service Climate on Store Turnover

Hypothesis 1 proposed that store-level turnover would be lower when the store manager’s perception and the employees’ shared perception of service climate are in agreement and high, rather than in agreement and low. The results of the polynomial regression analysis predicting unit turnover are presented in Table 2. The three second-order polynomial terms, specifically b₃ (SE²), b₄ (SE × SM), and b₅ (SM²), were jointly significant in predicting the unit-level turnover (ΔF = 2.7, p < .05). The results in Table 3 reveal that only the curvature along the congruence line was significant (slope a₁ = −.03, p > .05; curvature a₂ = .18, p < .01). The visualization of Figure 2 shows a U-shaped curve along the agreement line and indicates that turnover is higher when the store employees and the store manager agree at either low or high levels of service climate, compared to agreeing at medium levels. More specifically, store turnover decreases when agreement on service climate moves from low to medium levels, and it increases when the agreement moves from medium to high levels. Overall, these results did not provide strong support for Hypothesis 1 because agreement at high levels of service climate lead to levels of turnover that were equivalent to those associated with agreement at low levels.

Table 2.

Path Analysis Results for the Estimated Models.

	Turnover				Sales Efficiency
	1	2	3	4	1	2	3	4	5
Employees-rated service climate (E)	−.05*	−.02	−.01	−.54**	.02	.05	.09	−.15	.13
Manager-rated service climate (M)	.01	.01	.01	.14	.02	−.01	−.01	−.13	−.06
E²		.04**	.04**	.21**		.04	.04	−.02	.09
E × M		−.01	−.01	.13		−.02	−.02	−.26	−.19
M²		.01	.01	−.03		−.05*	−.05*	−.13	−.15
Customer fit (CF)			−.03	−.01			−.07	−.09*	−.09*
E × CF				−.10**				.04	-.01
M × CF				−.02				.02	.01
E² × CF				−.03^†				.01	−.01
E × M × CF				−.02				.05	.03
M² × CF				.01				.02	.02
Turnover									−.52**
R ²	.02	.05	.05	.09	.00	.02	.04	.05	.19
ΔR²		.03*	.00	.04**		.02^†	.02^†	.01	.14**

^†p < .10. *p < .05. **p < .01.

Table 3.

Test of Response Surface Along the Line of Congruence and Incongruence at High and Low Levels of Team-Customer Fit.

Independent Variable	Level of Fit	Slope Surface		Curvature Surface
Independent Variable	Level of Fit	Congruence, a₁	Incongruence, a₃	Congruence, a₂	Incongruence, a₄
Turnover	All	−.03	−.07**	.18**	.22**
	Low	.58**	.64**	.65**	.93**
	High	−.06	−.08	−.26**	.16
Sales efficiency	All	.06	.08	.01	.11*
	Low	.12	.10	.04	.06
	High	.22**	.30**	−.16	−.24

Note. a₁ represents the slope of the surface along the line of congruence (where store employees and manager ratings did not differ). a₂ represents the curvature of the surface along the line of congruence. a₃ represents the slope of the surface along the incongruence line (where store employees and manager ratings differ). a₄ represents the curvature of the surface along the line of incongruence. Values for sales efficiency represent the slope and curvature of indirect effect of service climate congruence/incongruence via turnover. Low: stores 1 SD below customer fit average. High: stores 1 SD above customer fit average.

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

Figure 2.

The influence of (in)congruence in employees’ and manager’s ratings of service climate on turnover.

Hypothesis 2 predicted a significant turnover difference along the disagreement line, such that turnover would be lower under conditions of employee overestimation than manager overestimation. Table 3 reveals that the slope along the disagreement line (SE = −SM) is negative and significant (a₃ = −.07, p < .05), whereas the curvature is significantly positive (a₄ = .22, p < .01). The significant positive curvature indicates that turnover increases sharply when the employees’ shared perception diverges from the manager’s perception, whereas the negative and significant slope provides full support for Hypothesis 2—that turnover is lower when the employees overestimate the service climate. As demonstrated in Figure 2, unit turnover is higher in stores where the manager makes an overestimation of service climate compared to the stores where the employees overestimate the service climate. The positive U-shaped curvature along the disagreement line suggests that turnover increases as a function of the scope of the disagreement in service climate perceptions. Taken together, the results indicate that turnover is low when the manager and the employees agree that the service climate in the store is at medium levels and increases when they disagree and the manager overestimates it.

Moderating Effect of E-C Fit

Hypothesis 3 predicted that the negative effect of service climate agreement on store turnover will be stronger as the perceived fit with customers increases. The results of the moderation analysis in Table 2 reveal that the ΔF value (2.5) in Model 4 (interaction effects model) significantly increased relative to that of Models 3 and 2. As shown in Table 3 and illustrated in Figure 3A, when customer fit is low (−1 SD), the slope of the surface along the agreement line was significantly different from 0 (a₁ = .58, p < .05). The positive sign indicates that turnover is higher when service climate agreement is at high levels compared to when the agreement is at low levels. Moreover, the significant positive curvature along the agreement line at low customer fit (a₂ = .65, p < .01) indicates a U-shaped curve. Figure 3A reveals that store-level turnover is higher when the manager and the employees agree at either low or high levels compared to agreement at medium levels. In summary, when the perceived fit with customers is low, service climate agreement at moderate levels elicits lower turnover compared to agreement at high or low levels.

Figure 3.

The influence of (in)congruence in employees’ and manager’s ratings of service climate on turnover in units with (A) low person-customer fit and (B) high person-customer fit.

Regarding disagreement, the slope and curvature of the surface in cases of low customer fit were both significant (a₃ = .64, p < .01, a₄ = .93, p < .01). The significant positive curvature indicates that turnover increases sharply as the employees’ shared service climate perception diverges from their manager’s, providing full support for Hypothesis 4. The significant positive slope indicates that, when the customer fit is perceived to be low, turnover is higher when the employees overestimate the service climate and is lower when the manager overestimates it (low fit: SE > SM = 5.58 vs. SE < SM = 3.02).

The results were fairly different in cases where perceived E-C fit was high. The curvature along the agreement line was significantly different than 0 (a₂ = −.26, p < .01). Yet, the negative curvature of a₂ indicates an inverse U shape along the agreement line. Figure 3B suggests that turnover is lower when both the manager and the employees agree that service climate is either very high or very low than when they agree that the service climate is at a moderate level. In other words, when perceived customer fit is high, service climate agreement at high or low levels elicits lower turnover than agreement at medium levels. Neither the slope (a₃ = −.08, p > .05) nor the curvature of the surface along the disagreement line at high levels of customer fit was significant (a₄ = .16, p > .05). This result indicates that neither the amplitude nor the direction of the disagreement in the service climate rating influence turnover when unit-level perceptions of customer fit are high. The nonsignificant curvature along the incongruence line provides support for the buffering effect of customer fit when there is disagreement on service climate perceptions.

Indirect Effect of (Dis)agreement on Sales Performance Through Store-Level Turnover

Hypothesis 5 predicted that store-level turnover partially mediates the relationship between service climate (dis)agreement and store-level sales performance. Beginning with the total effect of service climate agreement on store sales performance, Table 2 (Model 2) indicates that the three second-order polynomial terms, b₃ (SE²), b₄ (SE × SM), and b₅ (SM²), were jointly marginally significant in predicting sales performance (ΔF = 2.3, p < .07). Figure 4 reveals that neither the slope (a₁ = .06, p > .05) nor the curvature (a₂ = .01, p > .05) along the agreement line was significant, indicating that sales performance is not significantly affected by the level and direction of service climate agreement. However, results do reveal a significant curvature along the incongruence line (SE = − SM, slope a₄ = .11, p < .01, see Figure 4). This positive curvature indicates that sales performance increases as employees’ shared perception of service climate diverges from that of the manager. Unexpectedly, sales performance was lower in stores where service climate perceptions were in agreement (SE = SM; 1.06) in comparison to those where such perceptions were in disagreement (SM > SE; 1.26).

Figure 4.

The influence of (in)congruence in employees and manager’s ratings of service climate on sales performance.

We next estimated the effect of the mediator on sales performance. Results of Model 5 presented in Table 2 reveal that store-level turnover was negatively related to sales performance over and above the effects of the polynomial terms and perceived customer fit (b = −52, p < .01). We assessed whether turnover mediated the relationship between service climate (dis)agreement and sales performance using the PROCESS tool (Hayes 2013), following the procedure previously described in the Analysis section. To provide further support for Hypotheses 6a and 6b, we assessed the indirect moderated effect by using the block variable approach (Edwards and Cable 2009; Vogel, Rodell, and Lynch 2016). Despite the marginally significant relationship between the block of variables for the service climate perceptions and store-level turnover (path a = .02, p < .06), and the significant negative relationship between turnover and sales performance, the indirect effect of polynomial block variables through turnover (lower bound and upper bound [−.05, .01]) was not significant because the 95% confidence interval (CI) includes 0. Thus, our results fail to provide support for Hypothesis 5.

The Moderated Mediation Relationships

Hypotheses 6a and 6b predicted that the indirect effects of service climate (dis)agreement on sales performance through turnover would be moderated by the level of customer fit, such that the positive indirect effect of agreement is stronger when perceived customer fit is high, and the negative indirect effect of disagreement is stronger when perceived customer fit is low. We followed procedures recommended for testing moderated mediation hypotheses using polynomial regression (e.g., Vogel, Rodell, and Lynch 2016). When adding turnover as the mediator, including the service climate perceptions polynomial terms moderated by customer fit, its effect was found to be significant (β = −.52, p < .01, see Step 5 in Table 2). As shown in Table 3 and displayed in Figure 5A and B, when the E-C fit is low, neither the slope (a₁ = .12, p > .05) nor the curvature (a₂ = .04, p > .05) was significant. This indicates that service climate agreement has no significant effect on sales performance when customer fit is low. In contrast, when customer fit is high, the advantage of this agreement on sales becomes significant (slope a₁ = .22, p < .01). This significant slope indicates that, when controlling for the effect of turnover, sales performance is higher in stores where employees and the manager agree on service climate at high levels rather than at low levels, but only when perceived fit with customers is high. These results provide support for Hypothesis 6a.

Figure 5.

The influence of (in)congruence in employees’ and manager’s ratings of service climate on sales performance in units with (A) low person-customer fit and (B) high person-customer fit.

With respect to disagreement, when perceived customer fit was low, neither the slope (a₃ = .10, p > .05) nor the curvature (a₄ = .06, p >.05) of the indirect effect along the disagreement line was significant. When perceived customer fit was high, the slope (a₃ = .30, p < .01), but not the curvature (a₄ = −.24, p > .05), of the effect along the disagreement line was significant. Thus, sales performance was not significantly affected by service climate disagreement when perceived customer fit was low. However, when perceived customer fit was high, sales performance was higher when the disagreement resulted from employee overestimation rather than manager overestimation (high fit: SE > SM = 2.15 vs. SE < SM = .95). Taken together, when accounting for the effect of store-level turnover, disagreement regarding service climate elicits higher sales performance only when customer fit is perceived to be high, providing support for Hypothesis 6b. Our results indicate that when a disagreement occurs, sales performance is higher when employees overestimate rather than underestimate the service climate and they perceive greater fit with customers.

To further provide full support for Hypotheses 6a and 6b, we assessed the indirect moderated effect by using the block variable approach (Edwards and Cable 2009; Vogel, Rodell, and Lynch 2016). The results provided by the PROCESS tool (Hayes 2013) indicate a nonsignificant indirect effect both at the low level (estimate = 1.62, 95% CI [−.37, .36]) and at the high level (estimate = −6.2, 95% CI [−.31, .19]).

Supplemental Analysis

Scholars on service research have begun to examine the influence of “horizontal service climate strength,” that is, variance in perceptions of service climate between individuals at the same level and the relationship between service climate level and employee and customer outcomes (e.g., Drach-Zahavy and Somech 2013; Schneider, Salvaggio, and Subirats 2002). A logical extension of this research would be to examine whether the degree of “horizontal climate strength” moderates the influence of “vertical climate strength,” that is, the disagreement between the manager and employees regarding service climate.

According to Mischel’s (1976) concept of strong/weak situations, strong situations are those in which people perceive events or situations in a similar manner, whereas weak situations entail differences (high variance) in perceptions. Moreover, individual differences play a determinant role in shaping behavior in weak situations but not so in strong situations. As such, we expect that a strong horizontal service climate would buffer the negative effect of vertical service climate disagreement on store turnover, whereas a weak horizontal service climate would amplify the negative effect of vertical service climate disagreement. When there is consensus among employees regarding the high value of customer service (e.g., strong horizontal service climate), we may expect turnover to be weakly affected by a weak vertical service climate (e.g., disagreement between store employees and the manager). In contrast, when horizontal service climate is weak (high variance in perceptions), employees do not perceive service practices and expectations in a similar manner leading to increased confusion. This ambiguous situation is more likely to be amplified when there is a large divergence between employees and the manager regarding the importance of customer service. These stores will likely experience a higher turnover because neither coworkers nor their manager may provide the assurance that help, support, and rewards will be sufficient to accomplish the expected service role.

Our results revealed a significant increase in model fit (ΔF = 3.1) in the interaction effects model compared to the reference model with no interaction. Our results indicate that when the horizontal service climate is strong, that is, variance in service climate is low (−1 SD), neither the slope (a₃ = .70, p > .05) nor the curvature (a₄ = 1.1, p > .05) of the surface along the vertical service climate disagreement line was significantly different than 0. These findings suggest that a strong horizontal service climate may buffer the negative influence of vertical service climate divergences on turnover. By contrast, when the horizontal service climate strength is weak, that is, variance in service climate is high (+1 SD), both the slope (a₃ = −4.53, p < .01) and the curvature (a₄ = .42, p < .01) of the surface along the vertical disagreement line were significantly different from 0. The significant positive curvature indicates that turnover increases sharply when both the vertical and the horizontal service climate disagreement increase. Furthermore, when vertical service climate disagreement occurs, the detrimental effect of a weak horizontal service climate strength on turnover is stronger when the manager overestimates the service climate, in comparison to when employees overestimate it (ES > SM = 1.52 vs. SE < SM = 19.6). Taken together, our analysis suggests that a weak horizontal service climate has the potential to amplify the dysfunctional effect of manager overestimation on turnover, whereas a strong horizontal service climate appears to mitigate the negative effect of vertical service climate divergences on turnover.

To provide further support for the indirect moderated effect, we used the block variable approach (Edwards and Cable 2009; Vogel, Rodell, Lynch 2016). The results provided by the PROCESS tool (Hayes 2013) indicate a nonsignificant indirect effect both at the low level of horizontal service climate strength (estimate = −.67, 95% CI [−.35, 1.9]) and at the high level (estimate = 8.6; 95% CI [−.19, .31]).

Discussion

Despite the importance of service climate in the marketing and organizational behavior literatures (Bowen and Schneider 2014), and the benefits of retaining employees in the service industry (Subramony and Holtom 2012), researchers have yet to examine how (dis)agreement between employees’ shared service climate and the store manager’s perception of service climate relates to sales performance. Moreover, the potential moderating role of perceived E-C fit in influencing this relationship has not yet been explored.

Our results revealed that turnover decreases when service climate agreement between employees and their manager moves from low to medium levels and increases when agreement reaches high levels. Furthermore, turnover increases and sales performance decreases as this vertical service climate divergence become larger. We also found that the perceived fit with customers plays a significant but complex role in the relationship between the vertical service climate (dis) agreement and store turnover and subsequently sales performance. Supplemental analyses have also shown that store-level turnover increases sharply when vertical and horizontal service climate disagreements both increase.

Theoretical Implications

This study makes important contributions to theory and research on customer service systems. Most of the previous research on service has focused on how resources can be invested to attain higher customer service quality. We highlighted an important gap in the literature, namely, how agreement and disagreement between store managers and employees regarding the service climate may affect collective outcomes, over and above the main effects of employees’ and managers’ perceptions.

First, our study challenges the pervasive assumption that a positive appreciation of service features is a sufficient condition to elicit more positive behaviors and higher sales performance. In contrast to the traditional service climate perspective (e.g., Hong, Liao, and Jiang 2013), our results suggest that promoting vertical agreement in customer service perspectives, between the employees and their manager, may be a more promising avenue for improving the performance of retail businesses.

Second, this study makes a theoretical contribution to P-E fit theory. Consistent with the ASA framework (Schneider 1987), we found that turnover decreased as stores moved from agreement at low levels to agreement at moderate levels. When store employees and their manager shared the view that their unit made some efforts to provide a supportive customer environment, this alignment signaled to team members that they were in the right place, thereby positively influencing their decision to remain (Schneider 1980). However, unexpectedly, turnover was higher in stores where the customer service climate ratings moved from agreement at medium levels to high levels. With few exceptions (e.g., Byza et al. 2019), previous research has overlooked the influence of extreme perceptions on agreement at the store level of analysis. One possible explanation for this unexpected finding is that sometimes “too much of a good thing is not always better” (Grant and Schwartz 2011). This theoretical perspective has pointed out that an excess of positive things can yield less favorable outcomes. We may not rule out that when the service climate is very high, expectations regarding customer service may even be excessive. The job requirements in terms of skills, effort, and performance are more likely to be perceived as difficult, if not impossible to satisfy. Such expectations and requirements are likely to elicit a higher voluntary and involuntary turnover. By testing the E-C fit as a critical boundary condition, this study has provided an important insight into why extreme service climate perceptions (very high) are associated with higher store-level turnover. We found that turnover was higher in stores with a low customer fit and where both the manager and the employees agreed that service climate was high.

Stores that highly value customer service generally seek candidates who embrace service values and the values of their customers. However, when a significant proportion of the members perceive that they have a low fit with customers, this suggests a serious problem in the hiring process and/or a high workforce shortage. This high turnover may come either from excessive errors during the hiring process or from abnormal dismissal decisions targeted at those whose behavior and performance do not meet customer service expectations. A part of this turnover can also be voluntary, resulting from employees’ awareness that they are in the wrong workplace.

Conversely, our analyses revealed that when both employees and the manager agree that their stores invest heavily in customer service, employee retention, and even sales performance, are better if an effort is made to recruit people perceiving high similarities with customers. This suggests functional levels of employee retention and turnover in these units, probably because they are better able to attract, select, and retain people with higher levels of customer service orientation and to adopt a comprehensive customer service configuration (Schulte et al. 2009).

Third, our study challenges the notion that agreement on goals, values, and preferences or opinions leads to better outcomes than disagreement. Contrary to the main ASA assumption (Schneider 1987), this study has shown that turnover was lower in stores where employees overestimated the service climate, and higher where the store manager overestimated it. This result may indicate that people make their place when they hold a very positive view of their working environment. However, the ASA model posits that organizations seek solutions to mitigate the negative effect of disagreements (Vogel, Rodell, and Lynch 2016). Consistent with this view, we found that E-C fit is an important critical boundary condition that helps people make their place when a disagreement regarding customer service climate exists. Vertical disagreement was found to be more detrimental to workforce stability when perceived E-C fit was low rather than high. This result is important because it suggests that greater perceptions of customer fit may stimulate workforce stability even when there is disagreement with management on service features. Scholars have proposed that E-C fit may increase the emotional attachment and responsibility toward customers (Oveis, Horberg, and Keltner 2010). Such positive regard and concern toward customers are more likely to engender high job embeddedness and motivation to remain despite conflicting perceptions on customer service priorities and rewards.

We also found lower turnover in stores where agreement regarding service climate was either very high or very low and where the E-C fit was perceived to be high. This finding suggests that some employees have decided to remain because the service expectations and rewards are congruent with their profile. However, it is more difficult to explain why the stores in which employees’ customer service perceptions diverge from their manager’s also appear successful in reducing turnover when employees see greater interpersonal compatibility with their customers. As suggested above, given that high customer fit may elicit a greater emotional attachment and responsibility toward customers (Oveis, Horberg, and Keltner 2010), some employees may have decided to remain despite their poor match with the service context. It is possible that, in the service industry, E-C fit is an important predictor of job embeddedness and even more relevant for retention than fit with the organization or the community (Mitchell et al. 2001). A noteworthy finding is that sales performance was lower in stores where the parties agreed that the service climate was low and no particular effort was made to recruit people with a profile similar to that of their customers.

Fourth, we contribute to the literature on disagreement by showing that divergences between employees and their manager regarding service climate may foster sales performance in some particular conditions. To our knowledge, this study is one of the first to find that disagreement regarding service perceptions has a positive influence on sales performance when the manager overestimates the service climate. Why does disagreement on customer service climate (when SM > SE rather than when SE > SM and even versus SE = SM) exert a positive influence on sales performance? One possible explanation is that formal leaders of organizations have more customer service experience and a better understanding of service policies and delivery expectations than most frontline employees. Despite the conflicting points of view between the store manager and employees, the employees are more likely to adopt the manager’s perspective in these instances because of their manager’s power and in-depth knowledge of the organization’s service culture and of the customers’ needs and behaviors. The positive influence of the store manager’s service perspective on sales performance is probably stronger in retail stores employing a large inexperienced and younger frontline workforce.

The picture was fairly different when the E-C fit dimension was taken into account. When customer fit was low, sales performance was neither significantly affected by agreement nor by disagreement regarding the service climate. However, when customer fit was high, the positive influence of manager overestimation of service climate on sales performance was strongly reduced, whereas the influence of employees’ overestimation of climate on sales performance was enhanced. This finding makes an important contribution to the service literature since it suggests that retail stores with vertical disagreement regarding service priorities and resources can nevertheless obtain high sales performance when employees share similar values and personalities with the customers. This finding also suggests that when employees hold a more positive view of service climate than their manager, stores may increase sales performance significantly if important efforts are made to recruit people with a profile similar to that of their customers.

Fifth, this study makes an important contribution to the P-E fit literature by examining a neglected fit referent, namely, E-C fit. The P-E fit literature has generally focused on the influence of individuals’ perceptions of P-O and P-J fit (Kristof-Brown, Zimmerman, and Johnson 2005) or on customer-perceived similarities with employees (e.g., Netemeyer, Heilman, and Maxham 2012). This article adds new insights to the literature on collective fit and highlights the relevance of examining E-C similarity in the service industry. A noteworthy finding is that customer fit was negatively associated with sales performance when the service perceptions’ polynomial terms were taken into account. We may speculate that a high similarity with customers may stimulate excessive customer concerns, compassion, and altruistic actions (Oveis, Horberg, and Keltner 2010), and less directed selling behaviors. Future research is needed to validate such explanations.

Sixth, we contribute to the literature on service climate strength by showing that a weak horizontal service climate tends to amplify the negative effect of disagreement. Previous research has demonstrated that variability in service perceptions moderates the influence of employee perceptions of service climate on several employee and customer outcomes (Drach-Zahavy and Somech 2013; Schneider et al. 2002). Contrary to this body of research, we found no significant evidence that this interaction may affect collective turnover and sales performance. Our findings indicate that turnover was lower in stores where horizontal service climate strength was weaker and the manager overestimated the service climate. This result is promising because it suggests that a strong divergence between employees regarding expected behaviors and rewards associated with customer service may elicit lower turnover when the store manager has a more optimistic perception of these features than the employees.

Finally, our research adds to the turnover literature. As expected, high store-level turnover was associated with low unit sales per employee. Most turnover scholars have argued that excessive turnover may hamper customers’ service quality perceptions and satisfaction because leavers are replaced with nonfamiliar newcomers and selling experience is lost (see Kacmar et al. 2006; Koys 2001). It is likely that the lower quality of service provided by inexperienced newcomers, combined with the diversion of the remaining staff owing to the changing workplace, negatively influenced sales performance in the sampled stores (Shaw et al. 2005).

Practical Implications

From a practical perspective, our results suggest some useful information for managers who must deal with disagreements regarding the store’s engagement in customer service. First, when organizations invest heavily in customer service excellence, obtaining a perfect agreement between stakeholders may offer a greater strategic advantage in comparison with when customer service is a low priority. However, obtaining high alignment in customer service perceptions in the organization is not an easy task and is not always better. When employees held a more optimistic view than that of their store manager, disagreement on the level of customer service climate did not necessarily produce poor effects, conditional on the existence of employees’ shared characteristics with customers and a strong service climate. The practical implication is that service organizations may reap some benefits by regularly sharing information about service expectations, rewards, and resources to foster a positive customer service image among frontline employees. Managers should be trained to communicate adequately with store members to provide them with complete information about the organization’s policies, practices, and procedures related to the delivery of high-quality service. However, the organization must continually assess whether its customer service policies and practices are perceived as excessive and dysfunctional.

Second, the complex implications of agreement and disagreement on service climate highlight the importance of collecting data among various customer service stakeholders to understand the extent of the differences and their underlying reasons, and to better identity appropriate solutions. Managers might also supplement such formal surveys by using formal and informal focus groups to acquire more insights into why differences in service perceptions exist and how to reduce them (Benlian 2014).

Third, organizations pursuing a service quality strategy of excellence should place a high priority on attracting, selecting, and promoting individuals whose values and personality are consistent with those of the customers. Our study has also highlighted the importance of recruiting store managers that endorse the customer service vision of the organization and to promote those who show the greatest enthusiasm for customer service policies and practices.

Fourth, our study highlights the benefit of controlling employee turnover. In practical terms, we estimated that a 1 SD decrease of turnover (from 35% to 17%) corresponded to a 67% SD increase in sales per store per week or a gain of $972 per week. For this organization, with its 702 stores, this represents a potential sales gain of $682,344 per week.

Limitations and Future Research

An important strength of this study is that we assessed variables from a variety of sources (i.e., leaders and followers reported their perceptions of service climate, and the company provided turnover and sales data), such that this study does not suffer from a strong common method variance bias. Like any study, however, this one is not without its limitations. First, the study was conducted in multiple stores of a single large retail organization; thus, the generalization of our findings to other organizations and environments may be restricted. Future research should examine a wide range of industry settings to validate our findings. This sample provided a conservative test of the theoretical model by reducing between-unit variance (Grizzle et al. 2009).

Second, the cross-sectional design of our study precludes conclusions as to effect causality. We may not rule out, for example, that agreement regarding service climate has a reciprocal causal influence on turnover. When the turnover of store managers and employees is very high, this instability may impede the alignment of perceptions, which in turn may disrupt important psychological processes, such as trust, support, and fairness. Moreover, high turnover weakens ASA processes because the organization would likely attract and select people on idiosyncratic and ambiguous criteria. Future research, using a longitudinal design, will offer better assurance of the direction of causality. Another potential weakness of this study is that we were unable to use more proximal outcomes such as customer-perceived service quality and customer satisfaction and behaviors.

In terms of opportunities for future research, researchers may study other aspects of customer service as we tested agreement/disagreement on generic measures related to service policies and procedures, expected behaviors and rewards, and service leadership (Bowen and Schneider 2014). However, little is known about the specific influence of each service feature. For instance, is the experience of reward and recognition policies more influential than tools and technologies used to support service delivery? Therefore, future research should examine how agreement and disagreement regarding various individual service facets affect important individual and organizational outcomes.

Another promising avenue would be to assess multiple stakeholder perspectives, namely, differences between store managers and the organization, store employees and customers, and store managers and customers. Doing so will allow scholars to examine the relative consequences of disagreement among people who are involved directly or indirectly in customer service delivery. The present study focused on perceived employee similarity with customers. However, an emerging stream of research has begun to examine perceived customer similarity with employees. Future research on the experience of fit types, as main predictors or moderators, may open up new and interesting research questions. For example, is employee-perceived (dis)similarity with customers more predictive of employees’ behaviors such as turnover and customer-directed behavior? Or is customer-perceived (dis)similarity with employees more predictive of customer behaviors such as loyalty and spending?

Conclusion

Employees’ and store manager’s positive perceptions of service climate are important, but how these perceptions differ also matters because disagreements are prevalent phenomena in organizations. This study is one of the first to examine the consequences of perceptual (dis)agreement regarding service climate for store performance. In the present study, we also investigated the moderating role of perceived customer similarity and horizontal service climate strength in such relationships. The results show that service climate agreement, at moderate levels, may elicit lower collective turnover. The benefit of agreement is amplified when the fit with customers is perceived as high. Results also indicate that an increasing vertical disagreement regarding the level of service climate is associated with higher dysfunctional store outcomes. However, vertical service climate disagreement is associated with higher positive outcomes when employees share similarities with customers and lower outcomes when the horizontal service climate is weak. This study also highlights the detrimental effect of turnover on sales performance and underlines the relevance of assessing perceptual agreement and disagreement to reap the benefits of investments in customer service delivery.

Supplemental Material

Supplemental Material, JSR._september._2019._Executive_summary._Tremblay - Is Seeing Eye to Eye Always Beneficial? How and When (Dis)agreement on Service Climate Influences Store Turnover and Sales Performance

Supplemental Material, JSR._september._2019._Executive_summary._Tremblay for Is Seeing Eye to Eye Always Beneficial? How and When (Dis)agreement on Service Climate Influences Store Turnover and Sales Performance by Adam Rapp, Thomas L. Baker, Nathaniel N. Hartmann, Michael Ahearne and Michel Tremblay in Journal of Service Research

Footnotes

Appendix

Acknowledgments

The authors would like to thank the reviewers of this article for their valuable comments and suggestions, and Kevin Hill and Xavier Rocheleau-Parent for their helpful support and research assistance.

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) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: The work was supported by the Social Sciences and Humanities Research Council of Canada (grant number 435-2018-1531).

ORCID iD

Michel Tremblay

Supplemental Material

Supplemental material for this article is available online.

References

Bashshur

M. R.

Hernández

González-Romá

(2011), “When Managers and Their Teams Disagree: A Longitudinal Look at the Consequences of Differences in Perceptions of Organizational Support,” Journal of Applied Psychology, 96 (3), 558–573.

Becker

T. E.

(2005), “Potential Problems in the Statistical Control Variables in Organizational Research: A Qualitative Analysis with Recommendations,” Organizational Research Methods, 8 (3), 274–289.

Benlian

(2014), “Are We Aligned…Enough? The Effects of Perceptual Congruence between Service Teams and Their Leaders on Team Performance,” Journal of Service Research, 17 (2), 212–228.

Boon

Biron

(2016), “Temporal Issues in Person-Organization Fit, Person-Job Fit and Turnover: The Role of Leader-Member Exchange,” Human Relations, 69 (12), 2177–2200.

Borucki

C. C.

Burke

M. J.

(1999), “An Examination of Service-Related Antecedents to Retail Store Performance,” Journal of Organizational Behavior, 20 (6), 943–962.

Bowen

Schneider

(2014), “A Service Climate Synthesis and Future Research Agenda,” Journal of Service Research, 17 (1), 5–22.

Byrne

(1971), The Attraction Paradigm. New York: Academic Press.

Byza

Dörr

Schuh

Maier

(2019), “When Leaders and Followers Match: The Impact of Objective Value Congruence, Value Extremity, and Empowerment on Employee Commitment and Job Satisfaction,” Journal of Business Ethics, 158 (4), 1097–1112.

Cable

DeRue

(2002), “The Convergent and Discriminant Validity of Subjective Fit Perceptions,” Journal of Applied Psychology, 87 (5), 875–884.

10.

Cable

Parsons

C. K.

(2001), “Socialization Tactics and Person-Organization Fit,” Personnel Psychology, 54 (1), 1–23.

11.

Carlson

(2012), “The Illusion of Statistical Control: Control Variable Practice in Management Research,” Organizational Research Methods, 15 (3), 413–435.

12.

Carter

M. Z.

Mossholder

K. W.

(2015), “Are We on the Same Page? The Performance Effects of Congruence between Supervisor and Group Trust,” Journal of Applied Psychology, 100 (5), 1349–1363.

13.

Chan

(1998), “Functional Relations among Constructs in the Same Content Domain at Different Levels of Analysis: A Typology of Composition Models,” Journal of Applied Psychology, 83 (2), 234–246.

14.

Chuang

Liao

(2010), “Strategic Human Resource Management in Service Context: Taking Care of Business by Taking Care of Employees and Customers.” Personnel Psychology, 63 (1), 153–196.

15.

Cole

Carter

Zhang

(2013), “Leader-Team Congruence in Power Distance Values and Team Effectiveness: The Mediating Role of Procedural Justice Climate,” Journal of Applied Psychology, 98 (6), 962–973.

16.

Cordery

J. L.

Morrison

Wright

B. M.

Wall

T. D.

(2010), “The Impact of Autonomy and Task Uncertainty on Team Performance: A Longitudinal Field Study,” Journal of Organizational Behavior, 31 (2-3), 240–258.

17.

Dean

(2004), “Links between Organizational Variables in Service Delivery,” International Journal of Service Industry Management, 15 (4), 332–350.

18.

Drach-Zahavy

Somech

(2013), “Linking Task and Goal Interdependence to Quality Service: The Role of Service Climate,” Journal of Service Management, 24 (2), 151–169.

19.

Eden

(1984), “Self-Fulfilling Prophecy as a Management Tool: Harnessing Pygmalion,” Academy of Management Review, 9 (1), 64–73.

20.

Edwards

Cable

(2009), “The Value of Value Congruence,” Journal of Applied Psychology, 94 (3), 654–677.

21.

Edwards

Parry

(1993), “On the Use of Polynomial Regression Equations as an Alternative to Difference Scores in Organizational Research,” Academy of Management Journal, 36 (6), 1577–1613.

22.

Efron

Tibshirani

R. J.

(1994), An Introduction to the Bootstrap. Boca Raton, FL: CRC press.

23.

Gibson

Cooper

Conger

(2009), “Do You See What We See? The Complex Effects of Perceptual Distance between Leaders and Teams,” Journal of Applied Psychology, 94 (1), 62–76.

24.

Gracia

Cifre

Grau

(2010), “Service Quality: The Key Role of Service Climate and Service Behavior of Boundary Employee Units,” Group & Organization Management, 35 (3), 276–298.

25.

Grant

Schwartz

(2011), “Too Much of a Good Thing: The Challenge and Opportunity of the Inverted U,” Perspectives on Psychological Science, 6 (1), 61–76.

26.

Grizzle

Zablah

Brown

Mowen

Lee

(2009), “Employee Customer Orientation in Context: How Environment Moderated the Influence of Customer Orientation on Performance Outcomes,” Journal of Applied Psychology, 94 (5), 1227–1242.

27.

Hausknecht

J. P.

Trevor

C.O.

(2011), “Collective Turnover at the Group, Unit and Organizational Levels: Evidence, Issues, and Implications,” Journal of Management, 37 (1), 352–388.

28.

Hausknecht

J. P.

Trevor

C. O.

Howard

M. J.

(2009), “Unit-Level Voluntary Turnover Rates and Customer Service Quality: Implications of Group Cohesiveness, Newcomer Concentration, and Size,” Journal of Applied Psychology, 94 (4), 1068–1075.

29.

Hayes

(2013), Introduction to Mediation, Moderation, and Conditional Process Analysis. A Regression-Based Approach. New York: The Guilford Press.

30.

Holtom

B. C.

Burch

T. C.

(2016), “A Model of Turnover-Based Disruption in Customer Services,” Human Resource Management Review, 26 (1), 25–36.

31.

Hong

Liao

Jiang

(2013), “Missing Links in the Service Profit Chain: A Meta-Analytic Review of the Antecedents, Consequences, and Moderators of Service Climate,” Journal of Applied Psychology, 98 (2), 237–267.

32.

Liden

R. C.

(2011), “Antecedents of Team Potency and Team Effectiveness: An Examination of Goal and Process Clarity and Servant Leadership,” Journal of Applied Psychology, 96 (4), 851–862.

33.

Jaewon

(2016), “Perceived Customer Participations and Work Engagement: The Path through Emotional Labor,” The International Journal of Bank Marketing, 34 (7), 1009–1024.

34.

Jamal

Adelowore

(2008), “Customer-Employee Relationship: The Role of Self-Employee Congruence,” European Journal of Marketing, 42 (11/12), 1316–1345.

35.

Jiang

Hong

Liao

Liu

(2016), “Do It Well and Do Right: The Impact of Service Climate and Ethical Climate on Business Performance and the Boundary Conditions,” Journal of Applied Psychology, 101 (11), 1553–1568.

36.

Jiang

Liu

McKay

Mitchell

(2012), “When and How Is Job Embeddedness Predictive Turnover? A Meta-Analytic Investigation,” Journal of Applied Psychology, 97 (5), 1077–1096.

37.

Jiang

Hoegg

Dahl

Chattopadhyay

(2009), “The Persuasive Role of Incidental Similarity on Attitudes and Purchase Intentions in a Sales Context,” Journal of Consumer Research, 36 (5), 778–790.

38.

Kacmar

Andrews

Van Rooy

Steilberg

Cerrone

(2006), “Sure Everyone Can Be Replaced…But at What Cost? Turnover as a Predictor of Unit-Level Performance,” Academy of Management Journal, 49 (1), 133–144.

39.

Keely

J. R.

Barsade

S. G.

(2001), “Mood and Emotions in Small Groups and Work Teams,” Organizational Behavior and Human Decision Processes, 86 (1), 99–130.

40.

Koys

(2001), “The Effects of Employee Satisfaction, Organizational Citizenship Behavior, and Turnover on Longitudinal Effectiveness: A Unit-Level Longitudinal Study,” Personnel Psychology, 54 (1), 101–114.

41.

Krebs

(1975), “Empathy and Altruism,” Journal of Personality and Social Psychology, 32 (6), 1134–1146.

42.

Kristof-Brown

A.L.

C. S.

Schneider

(2018), “Fitting In and Doing Good: A Review of Person–Environment Fit and Organizational Citizenship Behavior Research,” in The Oxford Handbook of Organizational Citizenship Behavior, Podsakoff

MacKenzie

S. B.

Podsakoff

N. P.

, eds. New York: Oxford University Press, 353–369.

43.

Kristof-Brown

A. L.

Seong

Degeest

Park

W. W.

Hoond

(2014), “Collective Fit Perceptions: A Multilevel Investigation of Person-Group Fit with Individual-Level and Team-Level Outcomes,” Journal of Organizational Behavior, 35 (7), 969–989.

44.

Kristof-Brown

A. L.

Zimmerman

Johnson

(2005), “Consequences of Individual’s Fit at Work: A Meta-Analysis of Person-Job, Person-Organization, Person-Group, and Person-Supervisor Fit,” Personnel Psychology, 58 (2), 281–342.

45.

Lucas

Parasuraman

Davis

Enis

(1987), “An Empirical Study of Salesforce Turnover,” Journal of Marketing, 51 (3), 34–59.

46.

Mathieu

J. E.

Heffner

T. S.

Goodwin

G. F.

Salas

Cannon-Bowers

J. A.

(2000), “The Influence of Shared Mental Models on Team Process and Performance,” Journal of Applied Psychology, 85 (2), 273–283.

47.

Matta

F. K.

Scott

B. A.

Koopman

Conlon

D. E.

(2015), “Does Seeing “Eye to Eye” Affect Work Engagement and Organizational Citizenship Behavior? A Role Theory Perspective on LMX Agreement,” Academy of Management Journal, 58 (6), 1686–1708.

48.

McKay

Avery

Morris

(2009), “A Tale of Two Climates: Diversity Climate from Subordinates and Managers’ Perspectives and their Role in Store Unit Sales Performance,” Personnel Psychology, 62 (4), 767–791.

49.

Mischel

(1976), “Toward a Cognitive Social Model Learning Reconceptualization Personality,” in Interactional Psychology and Personality, Endler

N. S.

Magnuson

, eds. New York: Wiley, 166–207.

50.

Mitchell

Holtom

Lee

Sablynski

Erez

(2001), “Why People Stay: Using Job Embeddedness to Predict Voluntary Turnover,” Academy of Management Journal, 44 (6), 1102–1121.

51.

Netemeyer

Heilman

Maxham

(2012), “Identification with the Retail Organization and Customer-Perceived Employee Similarity: Effects on Customer Spending,” Journal of Applied Psychology, 97 (5), 1049–1058.

52.

Ostroff

Shin

Kinicki

A. J.

(2005), “Multiple Perspectives of Congruence: Relationships between Value Congruence and Employee Attitudes,” Journal of Organizational Behavior, 26 (6), 591–623.

53.

Oveis

Horberg

Keltner

(2010), “Compassion, Pride, and Social Intuitions of Self-Other Similarity,” Journal of Personality and Social Psychology, 98 (4), 618–630.

54.

Park

Shaw

(2013), “Turnover Rates and Organizational Performance: A Meta-Analysis,” Journal of Applied Psychology, 98 (2), 268–309.

55.

Ployhart

Weekley

Ramsey

(2009), “The Consequences of Human Resource Stocks and Flows: A Longitudinal Examination of Unit Service Orientation and Unit Effectiveness,” Academy of Management Journal, 52 (5), 996–1015.

56.

Rhoades-Shanock

Baran

B. E.

Gentry

W. A.

Pattison

S. C.

Heggestad

E. D.

(2010), “Polynomial Regression with Response Surface Analysis: A Powerful Approach for Examining Moderation and Overcoming Limitations of Difference Scores,” Journal of Business and Psychology, 25 (4), 543–554.

57.

Salanova

Agut

Peiró

J. M.

(2005), “Linking Organizational Resources and Work Engagement to Employee Performance and Customer Loyalty: The Mediation of Service Climate,” Journal of Applied Psychology, 90 (6), 1217–1227.

58.

Schaufeli

W. B.

Bakker

A. B.

(2004), “Job Demands, Job Resources, and their Relationship with Burnout and Engagement: A Multi-Sample Study,” Journal of Organizational Behavior, 25 (3), 293–315.

59.

Schneider

Macey

W. H.

Young

S. A.

(2006), “The Climate for Service: A Review of the Construct with Implications for Achieving CLV Goals,” Journal of Relationship Marketing, 5 (2-3), 111–132.

60.

Schneider

Ehrhart

M. G.

Mayer

D. M.

Saltz

J. L.

Niles-Jolly

(2005), “Understanding Organizational-Customer Links in Service Settings,” Academy of Management Journal, 48 (6), 1017–1032.

61.

Schneider

Salvaggio

Subirats

(2002), “Climate’ Strength: A New Level for Climate Research,” Journal of Applied Psychology, 87 (3), 220–229.

62.

Schneider

White

Paul

(1998), “Linking Service Climate and Customer Perceptions of Service Quality: Test of a Causal Model,” Journal of Applied Psychology, 83 (2), 150–163.

63.

Schneider

(1987), “The People Make the Place,” Personnel Psychology, 40 (3), 437–453.

64.

Schneider

(1980), “The Service Organization: Climate Is Critical,” Organizational Dynamic, 9 (autumn), 52–55.

65.

Schulte

Ostroff

Shmulyian

Kiniki

(2009), “Organizational Climate Configurations: Relationships to Collective Attitudes, Customer Satisfaction, and Financial Performance,” Journal of Applied Psychology, 94 (3), 618–634.

66.

Seong

Kristof-Brown

A. L.

Park

W. W.

Shin

(2015), “Person-Group Fit: Diversity Antecedents, Proximal Outcomes, and Performance at the Group Level,” Journal of Management, 41 (4), 1184–1213.

67.

Seong

Choi

(2014), “Effects of Group-Level Fit on Group Conflict and Performance: The Initiating Role of Leader Positive Affect,” Group and Organization Management, 39 (2), 190–122.

68.

Shaw

Duffy

Johnson

Lockhart

(2005), “Turnover, Social Capital Losses and Performance,” Academy of Management Journal, 48 (4), 594–606.

69.

Shin

(2008), “Effects of Team-Level Person-Group Organization and Person-Job Fit on Team Organizational Citizenship Behaviors and Team Efficacy,” Korean Journal of Management, 16 (2008), 1–35.

70.

Sowinski

Fortmann

Lezotte

(2008), “Climate for Service and the Moderating Effect of Climate Strength on Customer Satisfaction, Voluntary Turnover, and Profitability,” European Journal of Work and Organizational Psychology, 171 (1), 73–88.

71.

Subramony

Holtom

(2012), “The Long-Term Influence of Service Employee Attrition on Customer Outcomes and Profits,” Journal of Service Research, 15 (4), 460–473.

72.

Tett

Burnett

(2003), “A Personality Trait-Based Interactionist Model of Job Performance,” Journal of Applied Psychology, 88 (3), 500–517.

73.

Vogel

R. M.

Rodell

J. B.

Lynch

(2016), “Engaged and Productive Misfits: How Job Crafting and Leisure Activity Mitigate the Negative Effects of Value Incongruence,” Academy of Management Journal, 59 (5), 1561–1584.

74.

Zeytinoglu

Lillevik

Seaton

Moruz

(2004), “Part-Time and Other Factors Affecting the Workplace,” Industrial Relations, 59 (3), 516–543.

75.

Zhang

Wang

Shi

(2012), “Leader-Follower Congruence in Proactive Personality and Work Outcomes: The Mediating Role of Leader-Member Exchange,” Academy of Management Journal, 55 (1), 11–130.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB