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Heiner Evanschitzky, Christopher Groening, Vikas Mittal and Maren WunderlichServices

How Employer and Employee Satisfaction Affect Customer Satisfaction: An Application to Franchise

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How Employer and EmployeeSatisfaction Affect CustomerSatisfaction: An Application toFranchise Services

Heiner Evanschitzky1, Christopher Groening2, Vikas Mittal3, andMaren Wunderlich4

AbstractIn small-service settings, how do owner satisfaction, front-line employee satisfaction, and customer satisfaction relate to oneanother? The authors use generalized exchange theory (GET) to examine how satisfaction levels of these three constituents arereciprocated. The authors examine a European franchise system comprising 50 outlets, 933 employees, and 20,742 customers.Their results show two important findings. First, the effect of owner-franchisee’s satisfaction on customer satisfaction is fullymediated by front-line employee satisfaction. Thus, managers of a service outlet can strongly impact the satisfaction and beha-vioral intentions of their customer base, even without direct contact with them. Second, the link between customer satisfactionand purchase intention is moderated by employee satisfaction at an outlet. The link between customer satisfaction and customerpurchase intentions is almost twice as strong when employees are satisfied than when they are not. Thus, there is a ‘‘double-positive effect:’’ not only does higher employee satisfaction at an outlet directly lead to higher customer satisfaction but it alsoindirectly strengthens the association between customer satisfaction and their repurchase intentions.

Keywordscustomer satisfaction, employee satisfaction, manager satisfaction, franchisee satisfaction, exchange theory, purchase intentions,service-profit chain

For service businesses, satisfying and retaining high-quality

employees while growing the firms’ customer base are key suc-

cess factors. The satisfaction experienced by small business

owners or managers may directly influence several aspects of

the business, particularly front-line employees1 and customers.

How are satisfaction levels among employers, employees, and

customers related to one another? Do they have a direct rela-

tionship to each other or are these relationships mediated?

We investigate these issues in a franchise system. Franchise

systems account for more than 40% of retail sales in the United

States (Coughlan et al. 2001). There are approximately 3,000

franchise systems with 700,000 franchise units in Europe

(International Franchise Association IFA 2008). Our theoreti-

cal interest in front-line employee satisfaction is motivated

by the argument that employee satisfaction may affect cus-

tomer satisfaction (Brown and Lam 2008), which in turn drives

a firm’s financial performance (Anderson and Mittal 2000). As

a small business owner, the owner-franchisee must manage

both employee satisfaction and customer satisfaction to opti-

mize business performance.

Against this background, we address the following issues.

First, do owner-managers maximize their own satisfaction at

the expense of employee and/or customer satisfaction? An

agency theoretic perspective (Brickley, Dark, and Weisbach

1991) suggests that an owner-franchisee may maximize his

satisfaction at the expense of employee satisfaction (e.g.,

through lower pay and benefits). Organizational studies have

found a weak to negative correlation between supervisor satis-

faction and employee satisfaction (Campion 1991). Similarly,

owner-franchisees may decide to maximize customer satisfac-

tion while reducing employee satisfaction. This may, however,

be strategically harmful, if employee satisfaction and customer

satisfaction complement each other to improve organizational

performance via increased customer purchase.

1 Aston Business School, Aston Triangle, Birmingham2 Robert J. Trulaske, Sr. College of Business at the University of Missouri,

Columbia, MO3 Jones Graduate School of Business, Rice University, Houston, TX4 T-Mobile International AG, Landgrabenweg, Bonn, Germany

Corresponding Author:

Vikas Mittal, J. Hugh Liedtke Professor of Marketing, Jones Graduate School of

Business, 250 McNair Hall, Rice University, Houston TX 77005

Email: [email protected]

Journal of Service Research14(2) 136-148ª The Author(s) 2011Reprints and permission:sagepub.com/journalsPermissions.navDOI: 10.1177/1094670510390202http://jsr.sagepub.com



Second, how is owner-franchisee satisfaction associated

with both customer satisfaction and employee satisfaction?

This area of research builds upon the research on the effects

of service environments on employee satisfaction. Liao and

Chuang’s work (2004) most closely corresponds to this exam-

ination. While Liao and Chuang (2004) offer valuable insight

into this area, their research did not measure manager/supervi-

sor/owner satisfaction, therefore no assessment of this relation-

ship could be made. Moreover, they measure service climate

rather than job satisfaction. Therefore, Liao and Chuang

(2004) differ substantially from this investigation. This study

investigates the mediated nature of the relationship among

owner satisfaction, employee satisfaction, and customer

satisfaction.

Third, research shows the relationship between customer

satisfaction and purchase intentions to be highly variable

(Keiningham et al. 2006; Mittal and Kamakura 2001). We posit

employee satisfaction to be one systematic moderator that can

explain the variability in the link between customer satisfaction

and customer purchase intentions. Based on the direct and indi-

rect effect of employee satisfaction, we document a double-

positive effect from higher employee satisfaction for a firm.

The direct benefit occurs because improving employee satis-

faction can directly improve customer satisfaction. The indirect

benefit accrues because employee satisfaction can strengthen

and enhance the association between customer satisfaction and

customer purchase intentions.

We draw on generalized exchange theory or GET (Bearman

1997; Ekeh 1974; Marshall 1998), which examines indirect,

reciprocal exchange relationships among three or more

exchange partners. We test our theoretical framework using

data from a single franchise system consisting of 50 franchisees

with a total of 933 employees and 20,742 customers.

Theoretical Background

Franchise Organizations

We use the term franchising to describe business-format fran-

chising: an owner-franchisee, who is typically a small-

business owner, licenses an entire way of doing business under

a brand name from the franchisor. In return for paying financial

benefits (e.g., royalties) to the franchisor, the owner-franchisee

receives benefits such as advertising, new product develop-

ment, and field service support for the franchisees. Several per-

spectives have been used to examine franchising (for an

overview, see Combs, Michael, and Castrogiovanni 2004).

Economists have examined factors affecting the decision to

franchise (e.g., Oxenfeldt and Kelly 1968) or the emergence of

franchising as a governance mechanism for organizations. In

marketing, it has been argued that higher owner-franchisee

satisfaction leads to higher morale, greater cooperation and

efficiency, and reduced conflict in the system (Hunt and Nevin

1976). Low owner-franchisee satisfaction results in suboptimal

financial and nonfinancial outcomes due to opportunistic beha-

vior (Spinelli and Birley 1996).

We define owner-franchisee satisfaction as the overall

assessment by the owner-franchisee of his role as an owner

of a franchise. This assessment may comprise areas such as

relationship with the franchisor, supporting services provided

by the franchisor, and other franchisees. As described later,

we use separate items to measure overall owner-franchisee

satisfaction and its antecedents. Similarly, we define overall

employee satisfaction as the overall job assessment by an

employee as an employee of the franchise-owner. As described

later, antecedents of employee satisfaction include supervision,

work organization, and perception of the team climate. Finally,

overall customer satisfaction is defined as an overall evaluation

of the customer’s experience with the organization. Its antece-

dents include assortment, service quality, and price.

Generalized Exchange Theory (GET)

The traditional view of exchange especially in marketing is

dyadic (Bagozzi 1974). In contrast, GET focuses on ‘‘a chain

of indirect, univocal, reciprocal transfers among at least three

actors’’ (Marshall 1998, p. 274). In generalized exchange,

‘‘there is no one-to-one correspondence between what two

actors directly give to and receive from each other. A’s giving

to B is not reciprocated by B’s giving to A, but by C’s giving to

A, where C is a third party’’ (Takahashi 2000, p. 1106). In other

words, there is indirect reciprocation such that the original ben-

eficiary may reciprocate to a person other than the one who

provided the benefit. Thus, while both generalized and

restricted exchange are identical with regard to actors having

expectations of equality of reciprocity, generalized exchanges

differ because there are three or more parties involved and

because of the indirect pathways of reciprocity (Ekeh 1974).

Generalized exchange has been used to understand phe-

nomena such as kinship in an African gerontocracy (Bearman

1997) and evolution of fairness-expectation in relationships

(Takahashi 2000). Within marketing, the only application of

generalized exchange is in social marketing: Marshall

(1998) studied parental support for a public school among

parents whose children did not attend that public school.

However, generalized exchange is well suited to understand

small-service businesses such as franchise operations as they

involve three critical exchange partners: the owner-

franchisee, front-line employees, and customers.

Generalized Social Exchange in a Franchise Network:Hypotheses

Exchanges can involve economic benefits such as lower prices,

product features, or service quality, as well as social benefits

that customers receive. According to a GET perspective, the

benefits that a highly satisfied owner-franchisee provides to

enhance employee job satisfaction is expected (by the owner-

franchisee) to be reciprocated by employees to customers in the

form of customer satisfaction enhancing behaviors. Similarly,

the enhanced satisfaction that customers experience due to

employee behaviors are expected to be reciprocated to the

Evanschitzky et al. 137



franchise-outlet in terms of positive behavioral intentions.

Satisfaction experienced by the owner-franchisee should grow

due to the increase in customer purchase behavior.

In franchises, recognition of indirect reciprocity may hap-

pen through two mechanisms. First, both customers and

employees develop social schemas about the generalized

exchange network within the franchise outlet (Krackhardt and

Kilduff 1999). Janicik and Larrick (2005) show that people

learn the indirect and transitive nature of the social schemas

embodying generalized exchanges with the understanding that

receiving something from one party (employee) may create

obligations to a different party (the owner-franchisee). Second,

Larsson and Bowen (1989) argue that preexisting scripts enable

organizations to set the appropriate behavioral norms for cus-

tomers as well as for service employees. For example, through

communication to customers, franchisees may stress the impor-

tance of their own employees meeting customer needs. To their

employees, owner-franchisees can emphasize that, as a service

agent of the organization, the employees’ primary goal is to sat-

isfy their customers. Recognizing the agentic relationship, the

customer reciprocates benefits to the franchise-organization

through actions like patronizing the franchise again.

The indirect, reciprocal model of generalized exchange is

illustrated in Figure 1A through three paths. First, an employee

who is highly satisfied with his job (because of actions of the

owner-franchisee) could reciprocate indirectly by satisfying the

firm’s customers (Link A). Second, if the customer feels satis-

fied, he will reciprocate indirectly to the owner-franchisee by

exhibiting potential actions that may be measured via purchase

intentions (Link B). And finally, if the owner-franchisee is sat-

isfied through customer actions, he will reciprocate to the

employees such that they are more satisfied (Link C). The the-

oretical foundations of the GET perspective can be traced to

organizational support theory (OST), which states that

employees maintain beliefs that the firm cares about their

well-being and values their contributions (Rhoades and

Eisenberger 2002). Consequently, employees feel an obliga-

tion to assist the firm in achieving its objectives (Eisenberger

et al. 2001) through customer satisfaction. Accordingly,

owner-franchisees who are highly satisfied should also have

employees who are highly satisfied, which in turn should

enhance customer satisfaction. Formally:

Hypothesis 1: The impact of owner-franchisee satisfaction

on customer satisfaction will be fully mediated via

front-line employee satisfaction.

Figure 1B shows how we empirically test the links of the the-

oretical model shown in Figure 1A. Note that a dyadic

exchange model does not provide a theoretical basis for posit-

ing a mediated relationship. Interestingly, Brown and Lam

(2008) offer three predominant approaches to understanding

issues related to customer satisfaction and service organiza-

tions. These are emotional contagion, service-profit chain, and

service climate; all of these take a dyadic perspective that

ignores the indirect reciprocity among the multiple actors

involved. Theoretically, the mediating mechanism embedded

in GET clarifies why customers who have benefited from the

satisfying behaviors of employees, do not simply engage in

mutually beneficial transactions with the employee to the detri-

ment of the franchise organization.

Customer Satisfaction and Customer PurchaseIntentions: Employee Satisfaction as a Moderator

While positing employee satisfaction as an antecedent of cus-

tomer satisfaction, GET theory also posits employee satisfac-

tion as a moderator of the link between customer satisfaction

and customer purchase intentions. As explained earlier, cus-

tomers develop social schemas about reciprocal obligation

between the owner-franchisee and the front-line employee.

As such, indications that employees are dissatisfied with their

jobs should negatively affect the likelihood of future customer

patronage of the franchise. In contrast, satisfied employees

can provide signals to customers that reinforce the customer

satisfaction–purchase intention link, making it stronger. Con-

sequently, employee satisfaction should moderate the impact

of customer satisfaction on purchase intentions, such that the

link between satisfaction and purchase intention will be

weaker when employees are dissatisfied. In other words, even

when the level of customer satisfaction experienced by cus-

tomers is identical, their purchase intention toward the firm

may vary based on the extent to which the firm’s employees

are satisfied. Note that this moderating effect is over and

above the direct impact of employee satisfaction on customer

satisfaction.

A

B

OverallCustomer

SatisfactionLink A

Link C

Link B

OverallEmployee

Satisfaction

OverallOwner-Franchisee

Satisfaction

OverallEmployee

Satisfaction

CustomerPurchaseIntentions

OverallCustomer

Satisfaction

OverallOwner-Franchisee

Satisfaction

Figure 1. A. A generalized exchange model of franchisee satisfaction,employee satisfaction, and customer satisfaction. B. Model specification.

138 Journal of Service Research 14(2)



Theoretically, GET is consistent with OST (Eisenberger

et al. 2001), whereby vigilant customers can observe if an orga-

nization has fulfilled its obligations toward its employees by

satisfying the employees’ needs. Observing this, satisfied cus-

tomers may display stronger purchase intentions toward orga-

nizations that fulfill their obligations toward employees.

Thus, employee satisfaction may act to strengthen the impact

of customer satisfaction on customer purchase intentions.

Based on the above discussion we posit:

Hypothesis 2: The link between customer satisfaction and

customer purchase intention is moderated by employee

satisfaction at a specific outlet such that the relationship

between customer satisfaction and customer purchase

intention is likely to be stronger for customers associated

with higher employee satisfaction at a specific outlet than

for customers associated with (relatively) lower

employee satisfaction at a specific outlet.

Study Sample and Background

The study is set within the context of a European retail fran-

chise system with a system-wide annual turnover of roughly

5 billion Euros. The franchise system consists of about 300

outlets, each having between 40 and 60 employees in a setting

where customers shop for various do-it-yourself home items.

Due to confidentiality issues, further details are precluded.

The locations of the outlets are very similar in terms of envi-

ronmental factors, competitive intensity in particular. More-

over, the assortments and the price levels are very similar as

well. The franchisor allowed us to collect data from three

sources: (a) survey data from owner-franchisees, (b) survey

data from employees, and (c) survey data from customers at

each outlet.

Sample

First, the franchisor provided a randomly chosen list of 150

franchisees, each of whom was mailed a standardized survey.

Next, a self-administered questionnaire was given to the

employees at each outlet. To reduce social desirability bias,

employees answered the surveys anonymously. Each survey

had a unique outlet identifier so that the affiliation of an

employee to a specific outlet could be determined by the

researcher. Third, a customer satisfaction survey was con-

ducted by means of a self-administered questionnaire. A code

on the survey verified the affiliation of a customer to a specific

outlet. The association of each employee and customer to a par-

ticular outlet is critical to our analysis, as described later.

Our final sample consists of 50 owner-franchisees, for a

response rate of 33%. From the 2,294 employees of these 50

franchise outlets, we received 933 usable employee satisfac-

tion questionnaires, a return rate of about 40%. Finally, we

received completed questionnaires from 20,742 customers.

Thus, an average of 415 customers per owner-franchisee

responded.

Measures

All items use a 5-point Likert-type scale (1 ¼ very satisfied/

fully agree; 5 ¼ very unsatisfied/fully disagree). The scales are

described below:

Customer purchase intention. Based on Evanschitzky and

Wunderlich (2006), we directly measured the construct with

two items: purchase intention and cross-buying intention.

Overall customer satisfaction. The 2 items for overall satisfac-

tion were taken from a scale used by Bettencourt and Brown

(1997). We also included three antecedent constructs for over-

all customer satisfaction: service quality, assortment/outlet

appearance, and price. Items for these are based on Westbrook

(1981).

Overall employee satisfaction. The two items for overall

employee satisfaction were taken from Wangenheim,

Evanschitzky, and Wunderlich (2007). Additionally, items for

three antecedents of overall employee satisfaction were

included: supervision, organization of work, and team climate.

These measures were taken from Smith, Kendall, and Hulin

(1969).

Overall owner-franchisee satisfaction. For overall owner-

franchisee satisfaction we used two items from Jambulingam

and Nevin (1999). We included items for three antecedent con-

structs: relationship to other franchisees, relationship to fran-

chisor, and field service. These items are based on Ruekert

and Churchill (1984), Geyskens, Steenkamp, and Kumar

(1999), and Wadsworth and Haines (2000).

As described later, the measurement models for all key con-

structs supported the conceptualization introduced above. All

scale items are shown in the Appendix. Tables 1 and 2 provide

descriptive data for the various constructs.

Appendix A shows that the scales exhibit composite reliabil-

ities ranging from .78 to .94. Cronbach’s alpha values range

from .82 to .94. These values exceed the threshold proposed

in the literature (Nunnally 1978). Discriminant validity was

met using the criterion proposed by Fornell and Larcker

(1981, p. 46).

Data Aggregation Issues

The data present specific methodological challenges. For each

franchise, there is a clear pairing between the owner-franchisee

and the employees. If there was a similar pairing between each

employee and the customers served by that employee, an

approach such as hierarchical linear modeling (HLM) could

be used to analyze the data in a single model. However, such

a customer-employee pairing is not possible for two reasons.

First, for this organization, it is common that one employee

is in contact with more than one customer and one customer

is in contact with more than one employee. Therefore a clear

pairing, even though statistically desirable, does not occur.

Second, to maintain customer confidentiality, the sponsoring




firm allowed us to link each customer back to the owner-franchise,

not to a specific employee. Thus, for each employee and for

each customer, the respective owner-franchisee can be identified.

However, for each customer, a specific employee cannot be

identified, or vice versa.

In general, there are three ways of handling our data

structure. First, we could ignore the hierarchical structure by

assuming that all observations from the three data sets are

independent. That would imply the disaggregation of our data

to the customer level. The number of observations would then

Table 1. Descriptive Statistics of Scale Items

M SD

Items(1) Overall Franchisee Satisfaction

Overall direct measure (based on Jambulingam and Nevin 1999)Overall, how satisfied are you with your decision to be a franchisee at ( . . . )? 2.19a .81Taking everything together, I am a ( . . . ) franchisee. 2.41 .92

Antecedents (based on Wadsworth and Haines 2000)How satisfied are you with the relationship to other franchisees? 2.64 .73How satisfied are you with your everyday work? 2.64 .73How satisfied are you with the market performance of your franchise system? 2.45 1.10How satisfied are you with your relationship to the franchisor? 2.78 1.09How satisfied are you with the services offered by the franchisor? 3.72 1.68How satisfied are you with franchisor’s field service? 4.40 1.49How satisfied are you with the franchise fee with respect to services offered by the franchisor? 2.67 1.14

(2) Overall Employee SatisfactionOverall direct measure (based on Netemeyer et al. 1997; Wangenheim, Evanschitzky, and Wunderlich 2007)

Overall, how satisfied are you as an employee of ( . . . )? 2.13 .97Taking all experiences together, I am a ( . . . ) employee. 2.29 .99

Antecedents (based on Smith, Kendall, and Hulin 1969)The working atmosphere in our outlet is very good. 2.27 .91The flow of work in our outlet is very good. 2.27 .91All employees in our outlet have the competence to make decisions to react flexibly to customer wants. 2.08 .91I am provided all material and equipment necessary to do my job. 1.76 .83All imperfections in our operations are resolved swiftly. 1.92 .85Our outlet encourages making suggestions for improvements. 2.64 1.23I feel like being a team member in my outlet. 1.81 .89My colleagues support me in helping my customers. 2.03 .91My superiors are ‘‘living examples’’ of our company’s goals. 1.76 .91My superiors are ‘‘living examples’’ of customer orientation. 1.78 .90My superior is open-minded towards me. 1.91 1.03My superior always helps me in case of difficulties. 1.88 1.05I can count on my superior’s word. 1.79 .92My superior values my work performance. 2.08 1.04Employees’ opinions are considered by the superiors when making decisions for the outlet. 2.32 1.01

(3) Overall Customer SatisfactionOverall direct measure (based on Bettencourt and Brown 1997)

Overall, how satisfied are you with ( . . . )? 2.00 .68Taking all experiences together, I am ( . . . ) with ( . . . ). 1.99 .68

Antecedents (based on Westbrook 1981)How satisfied are you with clarity of arrangements in the store? 2.01 .65How satisfied are you with the choices provided in the assortment? 2.01 .65How satisfied are you with the cleanliness? 1.82 .68How satisfied are you with the ease of finding service employees? 2.45 .75How satisfied are you with the quality of products offered? 1.94 .65How satisfied are you with the friendliness of employees? 1.74 .66How satisfied are you with the professional assistance? 2.07 .61How satisfied are you with the prices of products? 2.60 .69

(4) Purchase IntentionItems (based on Evanschitzky and Wunderlich 2006)

Would you repurchase from ( . . . )? 2.01 .68Would you intend to buy other products from ( . . . )? 1.98 .65

Note. aAll items were measured using 5-point Likert-type scales anchored at 1 ¼ very satisfied or fully agree to 5 ¼ very unsatisfied or fully disagree, meaning thatlarger numbers indicate lower levels of (e.g.) satisfaction.




be 20,742. This might overestimate the significance of effects

(Luke 2004). A second way of handling the nested structure of

our data is to eliminate dependency by averaging over the low-

est level, here the owner-franchisee level (the total number of

observations would then be 50). That in turn would underesti-

mate effects by removing much of the variance in the data (van

Duijn, van Busschbach, and Snijders 1999).

A third way is to analyze data at the level of the mediator.

Since the goal of this study is to focus on the mediating role

of overall employee satisfaction, we aggregate customer data

to the employee level. This approach is fully consistent with

previous research (e.g., Homburg and Stock 2004, 2005).

By so doing, we avoid overestimating the effects between over-

all employee and customer satisfaction since the variation in

overall customer satisfaction ratings cannot be explained by the

overall satisfaction rating of a particular employee (recall that

there is no matching or pairing of employees and customers).

We also disaggregated franchisee satisfaction data to the

employee level. By so doing, we assumed that one owner-

franchisee influences all of his employees in a similar manner

(see Kamakura et al. 2002 for a similar approach).

Next, we assessed whether the degree of agreement among

individual customers within an owner-franchisee was large

enough to justify aggregation. We used intra-class correlation

(ICC) as well as inter-rater agreement (Freiss’ Kappa) to assess

aggregation issues. Results in Table 3 display high values for

ICC (between 0.82 and 0.91) for all of the constructs measured

at the individual customer level but nested within outlets (cus-

tomer purchase intention, overall customer satisfaction, ser-

vice, assortment, and price). Moreover, Fleiss’ Kappa ranges

from .46 to .81, displaying moderate to good levels of agree-

ment. Overall, these results support aggregation (James 1982).

The final data set consists of 933 observations, correspond-

ing to one observation for each employee. Data aggregation,

while necessary to test mediation (Hypothesis 1), also limits

our ability to model unobserved heterogeneity. It can also limit

our ability to fully capture the information available in different

levels of the data set (e.g., customer level, employee level, and

outlet level). To address this issue, we estimated a series of HLM

models for (a) customer purchase intentions, (b) customer satis-

faction, and (c) employee satisfaction. These models are sum-

marized in the section entitled ‘‘alternative models’’ later.

Reassuringly, both analyses support identical conclusions.

Results

Antecedent Effects

For all three overall satisfaction constructs, we first assessed

antecedent effects. The drivers and the path coefficients of the

drivers of overall owner-franchisee satisfaction, employee

satisfaction, and customer satisfaction are summarized in

Table 4.

Overall Owner-franchisee satisfaction. Overall owner-

franchisee satisfaction was specified as having three antece-

dents: ‘‘relationship to other franchisees,’’ ‘‘relationship to the

franchisor,’’ and ‘‘field service.’’ Fit criteria are well above the

minima proposed by Hair et al. (2006; Adjusted Goodness of

Table 2. Correlations Among Constructs

Overall Customer Satisfaction Overall Employee SatisfactionOverall Owner-Franchisee

Satisfaction

A B C D E F G H I J K L

A. Overall Customer Satisfaction 1B. Price .06 1C. Assortment/Outlet Appearance .49** .55* 1D. Quality .23* .53* .66* 1E. Overall Employee Satisfaction .19* .11* .14* .11* 1F. Supervision .13* .21* .15** .19** .09 1G. Team .12* .11* .12* .17* .65** .67** 1H. Organization .13* .21* .14** .20** .19* .72** .71* 1I. Overall Owner-Franchisee Satisfaction .10* .13* .05 .10* .03 .02 .03 .04 1J. Field Service .05 .22* .09* .11* .05 .03 .02 .06 .21* 1K. Relationship to Franchisor .08 .07 �.12* �.09* .04 .05 .00 �.01 .32** .45** 1L. Relationship to Franchisees .10* .11* .32** .05 .01 �.02 �.03 .04 .07 .29* .22* 1

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

Table 3. Agreement Between Individual Customers

Mean Squares ICC

Intention Between 2.87 .83Within 0.27

Overall satisfaction Between 5.50 .86Within 0.40

Service Between 10.21 .91Within 0.51

Assortment Between 4.58 .90Within 0.25

Price Between 7.29 .82Within 0.71

Note. ICC ¼ intra-class correlation.




Fit Index [AGFI] ¼ 0.92; Root Mean Residual [RMR] ¼ 0.08;

Normed Fit Index [NFI] ¼ 0.93). We find that ‘‘relationship to

the franchisor’’ and ‘‘field service’’ positively influence overall

owner-franchisee satisfaction. However, ‘‘relationship to other

franchisees’’ (p > .1) is not statistically significant. A possible

explanation for this nonsignificant path is the relatively entre-

preneurial nature of the individual franchisees, therefore mini-

mizing concern with the relationship to other franchisees.

Overall employee satisfaction. Overall employee satisfaction

has three antecedents: ‘‘supervision,’’ ‘‘organization of work,’’

and ‘‘team.’’ All of the fit criteria are met (AGFI ¼ 0.99; RMR

¼ 0.03; NFI ¼ 0.99). We find that ‘‘organization of work’’ and

‘‘team’’ are statistically significant but ‘‘supervision’’ is not.

This is similar to prior results that did not find a positive influ-

ence of leadership quality on overall employee satisfaction

(Schmit and Allscheid 1995).

Overall customer satisfaction. This construct has three antece-

dents: ‘‘service quality,’’ ‘‘assortment/outlet appearance,’’ and

‘‘price.’’ All fit criteria are met (AGFI ¼ 0.99; RMR ¼ 0.02;

NFI¼ 0.99). ‘‘Price’’ exhibits no significant influence on over-

all customer satisfaction, while ‘‘assortment/outlet appear-

ance’’ (path ¼ 0.68, p < .01) and ‘‘service quality’’ (path ¼0.29, p < .01) are highly significant. The nonsignificance of

price may be due to limited price sensitivity in this industry.

Structural Model: Hypothesis Tests

We analyze the structural model using overall measures of each

of the focal constructs, and the results are shown in Figure 2.

For the overall model, the fit criteria (AGFI ¼ 0.98; RMR ¼0.04; NFI ¼ 0.98) are adequate. The model explains 70.25%of the variation in customer-purchase intentions, indicating

adequate predictive validity. This is a conservative test since

the model combines data from three different sources—

owner-managers, employees, and customers.

Hypothesis 1. According to Hypothesis 1, the effect of overall

owner-franchisee satisfaction on overall customer satisfaction

is mediated through overall employee satisfaction. Owner-

franchisee satisfaction has a significant impact on overall

employee satisfaction (0.13, p < .01), and overall employee satis-

faction directly and significantly impacts overall customer

satisfaction (0.24, p < .01).

The path coefficient from overall owner-franchisee satisfac-

tion to overall customer satisfaction is statistically nonsignifi-

cant (p > .10). Using partial and total effects, there is no

significant direct effect from overall owner-franchisee satisfac-

tion on overall customer satisfaction (�0.05, p > .10). The total

effect of overall owner-franchisee satisfaction on overall cus-

tomer satisfaction that is mediated through overall employee

satisfaction is .03 (p < .05). We conclude that the influence

of overall owner-franchisee satisfaction on overall customer

satisfaction is mediated by overall employee satisfaction. Table

5 summarizes these findings.

Hypothesis 2. The second hypothesis posits that overall

employee satisfaction at a specific outlet moderates the impact

of overall customer satisfaction on customer purchase inten-

tions, such that this relationship is stronger when customers are

associated with outlets having relatively more satisfied

employees. To test for moderation, we performed a two-

group causal analysis. The two groups are ‘‘customers associ-

ated with outlets with higher employee satisfaction’’ and ‘‘cus-

tomers associated with outlets with lower employee

satisfaction.’’ These groups were created based on a median

split. We then compared two rival models that differ only with

respect to the effect of customer satisfaction on purchase inten-

tion. One model restricts the parameter to be equal across

groups while in the second model this parameter is allowed

to vary across groups. The restricted model has one more

degree of freedom than the general model. A moderating effect

would be present when the improvement in w2 in moving from

the restricted to the nonrestricted model is statistically signifi-

cant, and the coefficients are in the hypothesized direction.

Consistent with Hypothesis 2, the restricted model that con-

strains the paths to be equal can be rejected in favor of the

unrestricted model (w2(df ¼ 1) ¼ 4.43, p < .05). Further, the path

coefficient from overall customer satisfaction to customer pur-

chase intentions is .48 (p < .05) for customers associated with

outlets with less satisfied employees, almost half of that for cus-

tomers associated with outlets with more satisfied employees

Table 4. Antecedent Effects of Overall Owner-Franchisee, Overall Employee, and Overall Customer Satisfaction

Model Path Coefficient

Overall Owner-Franchisee Satisfaction Relationship to other franchisees ! Overall Owner-Franchisee Satisfaction .02 (n.s.)Relationship to franchisor ! Overall Owner-Franchisee Satisfaction .67**Field service ! Overall Owner-Franchisee Satisfaction .34*

Overall Employee Satisfaction Supervision ! Overall Employee Satisfaction .06 (n.s.)Organization of work ! Overall Employee Satisfaction .72**Team ! Overall Employee Satisfaction .16*

Overall Customer Satisfaction Service quality ! Overall Customer Satisfaction .29**Assortment/outlet appearance! Overall Customer Satisfaction .68**Price ! Overall Customer Satisfaction .01 (n.s.)

Note. n.s. not significant. *Significant at .05 level. **Significant at .01 level.




(.82, p < .05). The differential strength of the association between

customer satisfaction and customer-repurchase intention is shown

in Figure 2A. Thus, Hypothesis 2 is fully supported.

Alternative Analysis: Covariates and Data Reaggregation

We also reestimated the model by including outlet size as a

covariate for each of the structural hypotheses. The results

remained virtually unchanged, and the covariate was statisti-

cally nonsignificant for all of the paths (p > .15).

Additionally, we reestimated the model using customer-

level and outlet-level data. In the customer-level data, all the

effects were similar and both hypotheses were supported. In the

outlet-level model, the statistical significance of one structural

path decreased to p < .10, but the substantive results remained

unchanged. Taken together, this suggests that the empirical test

of our hypotheses is relatively robust.

Alternative Analysis: HLM Models

A different approach to modeling the three data sets is HLM

that accounts for the fact that customers are embedded in a

franchise store and its employees. Ideally we would apply a

three-level model where customers are embedded with one

employee, and, in turn, this employee is embedded within one

franchise store. As explained earlier, our data do not allow us

to attach specific customers to specific employees. Therefore,

we must apply HLM models three times to measure our links

(see Figure 1). The equations for the models can be written as

follows:

B

A

OverallCustomer

Satisfaction

OverallOwner−Franchisee

Satisfaction

OverallEmployee

Satisfaction

CustomerPurchaseIntentions

0.13p < 0.01 0.24

p < 0.01

0.74**p < 0.01

n.s.

n.s.

0.73p < 0.01

0.07p < 0.050.35

p < 0.01

Figure 2. A. Model results. B. Customer satisfaction and repurchase intentions: Moderating role of employee satisfaction. Regular font ¼ HLMresults; Italics¼ SEM results. **Coefficient values for subgroup analysis using SEM are as follows: 0.48, p <.01 for low employee satisfaction; 0.82,p <.01 for high employee satisfaction. HLM ¼ hierarchical linear modeling; SEM ¼ structural equation modeling.

Table 5. Test of Hypotheses in the Total Model

Hypotheses Proposed Effect Path Coefficient

Overall Customer Satisfaction ! Overall Customer Purchase Intention þ .74**Overall Employee Satisfaction ! Overall Customer Satisfaction þ .24**Overall Owner-Franchisee Satisfaction ! Overall Employee Satisfaction þ .13**Overall Owner-Franchisee Satisfaction ! Overall Customer Satisfaction n.s. n.s.Overall Owner-Franchisee Satisfaction ! Overall Employee Satisfaction !

Overall Customer Satisfactionmediation Total effect: .031*

Note. n.s. ¼ not significant. *Significant at .05 level. **Significant at .01 level.




Customer Purchase intention model:

Level 1 model:

Customer Purchase Intentionij ¼ b0 jþ b1jðCSATÞijþ rij

Level 2 model (random slope):

b1j ¼ g10 þ g11ðESATÞjþ u1j

Customer satisfaction model:

Level 1 model:

CSATij ¼ b0 þ b1 Assortment=Outlet Appearanceð Þijþ b2 Service Qualityð Þijþb; Priceð Þijþrij

Level 2 model (random intercept):

b0j ¼ g00 þ g01ðESATÞjþ g02ðOFSATÞjþ u0j

Employee satisfaction model:

Level 1 model:

ESAT ¼ b0 þ b1ðSupervisionÞijþ b2ðOrganization of WorkÞijþ b3ðTeamÞijþ rij

ð1Þ

Level 2 model (random intercept):

b0j ¼ g00 þ g01ðOFSATÞjþ u0j ð2Þ

Where:

CSAT ¼ customer satisfaction

ESAT ¼ employee satisfaction

OFSAT ¼ owner-franchisee satisfaction.

Results

When we examined the variation between classes, we found an

acceptable level of variation (design effects between 4.23 and

10.86). Therefore, HLM is appropriate to use here. Table 6

summarizes the findings that are based on three data sets with

n ¼ 54 franchisees, n ¼ 1,055 employees (nested in 54 fran-

chise outlets), and n ¼ 19,191 customers (nested in 54 fran-

chise outlets).2 The HLM results are incorporated in Figure

2A as well.

Hypothesis 1. According to Hypothesis 1, the effect of overall

owner-franchisee satisfaction on overall customer satisfaction

is mediated through overall employee satisfaction. Results

indicate a significant impact of overall owner-franchisee satis-

faction on overall employee satisfaction (g01 ¼ 0.35,3 p < .01),

a significant impact of overall employee satisfaction on overall

customer satisfaction (g02 ¼ 0.07, p < .05), as well as a non-

significant impact of owner-franchisee satisfaction on overall

customer satisfaction (g01 ¼ 0.02, n.s.). Note, the different

models use different levels of data and thus, formal tests of

mediation may not be appropriate. Nonetheless, the results are

consistent with the earlier results from structural equation mod-

eling (SEM).

Hypothesis 2. The second hypothesis posits that overall

employee satisfaction at a specific outlet moderates the impact

of overall customer satisfaction on customer purchase inten-

tions, such that this relationship is stronger when customers

are associated with outlets having relatively more satisfied

employees. Overall customer satisfaction has a strong posi-

tive impact on purchase intentions (g00 ¼ 0.73, p < .001). The

purchase intention model shows that average employee satis-

faction at an outlet moderates the relationship between cus-

tomer satisfaction and purchase intention as signified by a

significant slope effect (g11 ¼ 0.02, p < .001) in the HLM

model.

Overall the HLM4 and SEM results are fully consistent

with each other. While the SEM results provide a cleaner test

of mediation, they are limited in their ability to address unob-

served variability among the constructs. The HLM model

addresses this latter limitation, although it is not well suited

to test mediation. Reassuringly, the consistency in both sets

of analysis reinforces the support for Hypotheses 1 and 2.

Discussion

We make two important contributions. First, we show that the

effect of owner-franchisee satisfaction on customer satisfaction

is mediated by employee satisfaction. Thus, owners who are

satisfied have a positive multiplier effect on customer loyalty

Table 6. HLM Model Results

Coefficient

Model for Repurchase Intentions (b0)Intercept (g00) 2.05**

CSAT (b1)Intercept (g10) 0.73**ESAT (g11) 0.02*

Model for Customer Satisfaction (b0)Intercept (g00) 1.95**ESAT (g01) 0.07*OFSAT (g02) 0.02 n.s.

Assortment/Outlet Appearance (b1)Intercept (g10) 0.50**

Service Quality (b2)Intercept (g20) 0.27**

Price slopes (b3)Intercept (g30) 0.06**

Model for Employee Satisfaction (b0)Intercept (g00) 2.48**OFSAT (g01) 0.35**

Supervision (b1)Intercept (g10) 0.11**

Organization of Work (b2)Intercept (g20) 0.30**

Team (b3)Intercept (g30) 0.22**

Note. CSAT ¼ customer satisfaction; ESAT ¼ employee satisfaction; HLM ¼hierarchical linear modeling; OFSAT ¼ owner-franchisee satisfaction; n.s. ¼not significant.*Significant at .05 level. **Significant at .01 level.




through both satisfied employees and satisfied customers.

More importantly, we do not find support for a direct effect

of owner satisfaction on customer satisfaction. This implies

that without the support of satisfied front-line employees,

franchise-owners or managers are unlikely to have satisfied

customers with strong behavioral purchase intentions.

Future research should investigate situations in which the

mediated role of employee satisfaction in linking owner satis-

faction with customer satisfaction can be weak or strong. The

size of the service business may be a key factor. For instance,

we investigated relatively large outlets with more than 40

employees. However, in a very small business with one or two

employees, the owner may have substantial direct contact with

customers. In such cases, the mediating effects postulated in

Hypothesis 1 should be weaker.

Second, past research has conceptualized employee satisfac-

tion only as an antecedent of customer satisfaction. In contrast,

we show a double-positive effect from improving employee

satisfaction. Academics and managers may assume that

employees have a role in satisfying customers, but they cannot

influence customer purchase intentions. This systematically

underestimates the importance of employee satisfaction.

Improving employee satisfaction not only increases the aver-

age customer satisfaction score but also nearly doubles the

impact of customer satisfaction on customer purchase inten-

tions (see Figure 2B). This latter impact, if ignored, can lead

a firm to systematically underestimate the beneficial impact

of investments made in improving employee satisfaction. Since

employees are one of the largest expenses in many service busi-

nesses, it is even more critical to estimate the full benefits of

improved employee satisfaction to make sound resource invest-

ments. Theoretically, when may this moderating effect may be

stronger or weaker? For example, in service settings where cus-

tomers only have a brief interaction with employees, their

assessment of employee satisfaction may not be as relevant.

This is particularly true for services such as banking, where the

interface is gradually shifting to be more of a self-service tech-

nology concept.

Finally, as with all empirical studies, our study is not with-

out limitations. First, there are time lags between the three sur-

veys: first, owner-franchisees were surveyed; 3 months later

employees were surveyed, and customers were surveyed after

another 3 months. However, true longitudinal data over multi-

ple periods may be needed to draw strong causal inferences.

Second, we examine a single franchise system in one industry.

This precluded comparative analyses of differences based on

factors such as organizational culture and industry type. In

addition, inclusion of behavioral and financial metrics for

assessing the model would have been desirable. The behavioral

and financial consequences of customer satisfaction and pur-

chase intentions are well established in the literature (Anderson

and Mittal 2000). We expect they will apply to this setting as

well. Third, there is a possibility of demand artifacts in any

survey-based approach. However, to the extent that we use data

from three separate sources, concerns of common method var-

iance may be mitigated. We hope that future research will build

on this work to further address these limitations and improve

our understanding of this research area.

Appendix

Table A1. Scale Items and Reliabilities

Scale Item Alpha

CompositeReliability

(CR)

AverageVarianceExtracted

(AVE)

Overall Owner-FranchiseeSatisfactionOverall franchisee satisfaction

Overall, how satisfied areyou with your decision to be afranchisee?

– .83 .71

Taking everything together,I am a ( . . . ) franchisee.Relationship to franchisor

How satisfied are you withyour everyday work?

How satisfied are you withthe market performance ofyour franchise system?

How satisfied are you withyour relationship to thefranchisor?

.90 .82 .51

How satisfied are you withthe services offered by thefranchisor?

How satisfied are you withthe franchise fee with respectto services offered by thefranchisor?Relationship to otherfranchisees

How satisfied are you withthe relationship to otherfranchisees?

– – –

Field serviceHow satisfied are you with

franchisor’s field service?– – –

Overall Employee SatisfactionOverall employee satisfactionOverall, how satisfied are you

as an employee of ( . . . )?– .89 .80

Taking all experiencestogether, I am a ( . . . )employee.Supervision

My superiors are ‘‘livingexamples’’ of ourcompany’s goals.

My superiors are ‘‘livingexamples’’ of customerorientation.

My superior is open-mindedtowards me.

(continued)




Table A1 (continued)

Scale Item Alpha


(CR)


(AVE)

My superior always helpsme in case of difficulties.

.94 .94 .70

I can count on my superior’sword.

My superior values my workperformance.

Employees’ opinions areconsidered by thesuperiors when makingdecisions for the outlet.

Organization of workThe flow of work in our

outlet is very good.All employees in our outlet

have the competence tomake decisions to reactflexibly to customerwants.

I am provided all materialand equipment neces-sary to do my job.

.82 .85 .54

All imperfections in ouroperations are resolvedswiftly.

Our outlet encouragesmaking suggestions forimprovements.

TeamThe working atmosphere in

our outlet is very good.I feel like being a team

member in my outlet..82 .80 .59

My colleagues support me inhelping my customers.

Overall Customer SatisfactionOverall customer satisfaction

Overall, how satisfied areyou with ( . . . )?

– .91 .83

Taking all experiencestogether, I am ( . . . )with ( . . . ).

Assortment/outlet appearanceHow satisfied are you with

clarity of arrangementsin the store?

How satisfied are you withthe choices provided in theassortment?

.91 .84 .56

How satisfied are you withthe cleanliness?

How satisfied are you withthe quality of productsoffered?

Service Quality

(continued)

Table A1 (continued)

Scale Item Alpha


(CR)


(AVE)

How satisfied are you with theease of finding serviceemployees?

How satisfied are you with thefriendliness ofemployees?

.92 .78 .54

How satisfied are you with theprofessional assistance?

PriceHow satisfied are you with the

prices of products?– – –

Purchase IntentionWould you repurchase from( . . . )?

– .86 .76

Would you intend to buyother products from( . . . )?

Acknowledgments

The authors thank Gopalkrishnan R. Iyer, Seth W. Norton, Tomas J.

Page, Aric Rindfleisch, and Florian von Wangenheim for their com-

ments. Special thanks are due to the International Center for Franchis-

ing and Cooperation (F&C), Muenster (Germany) for supporting the

empirical analysis.

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:

This research was supported by German Ministry for Education and

Research (BMBF – FKZ 01 FD 0678).

Notes

1. We use the terms owner-manager, owner-franchisee, employer,

and owner interchangeably, as they tend to be the same person for

a majority of small-service franchise businesses. Front-line

employees are those employees who directly interact with custom-

ers. However, for the sake of simplicity, we will refer to them as

employees throughout this article.

2. The slight differences in the sample sizes are due to missing values

when aggregating data for the SEM analysis. Results do not change

when using the exact same sample sizes for the HLM and for the

SEM.

3. In line with HLM reporting, all coefficients are unstandardized.

4. As suggested by a reviewer, we also reestimated the HLM model

recursively, that is, using the predicted values from each preced-

ing model in the conceptual chain as inputs in the next model in

the chain. Reassuringly, the results are virtually identical to those

reported in Table 6.




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Bios

Heiner Evanschitzky is Professor and Chair of Marketing at Aston

University, UK and Visiting Professor at the University of St. Gallen,

Switzerland. Previously he worked as Professor of Marketing at the

University of Strathclyde, UK. Heiner received his PhD as well as his

Habilitation from the University of Muenster, Germany. His research

revolves around service-profit-chain issues as well as service market-

ing, retailing, marketing metrics, relationship marketing, and research

methods. He has published in leading journals such as Journal of Mar-

keting, Journal of Service Research, Journal of Retailing, Journal of

Business Research, Industrial Marketing Management, and Journal

of Personal Selling and Sales Management.

Christopher Groening is Assistant Professor of Marketing at the

Robert J. Trulaske, Sr. College of Business at the University of Mis-

souri. He has published in the Journal of Marketing. Chris’s current

academic research investigates stakeholder influence on the financial

outcomes of a firm.

Vikas Mittal is J. Hugh Liedtke Professor of Marketing at the Jones

Graduate School of Business, Rice University and Adjunct Professor

of Family Medicine at Baylor College of Medicine.

Maren Wunderlich is Head of CRM Program Management at the

Deutsche Telekom AG. Previously, she worked as Senior Manager

CRM Strategy & Performance Analysis at Premiere Fernsehen GmbH

& Co KG. She received her PhD from the University of Muenster,

Germany.




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