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Service quality control mechanisms infranchise networksRoberto Sánchez Gómez a , Isabel Suárez González b & LuisVazquez Suárez ba Sección de Organizacion de Empresas , University Carlos III deMadrid , Facultad de Ciencias Sociales y Jurı´dicas, C/ Madrid126, 28903, Getafe, Spainb Departamento de Administración y Economı´a de la Empresa ,University of Salamanca , Campus Miguel de Unamuno s/n,edificio FES, 37007, Salamanca, SpainPublished online: 05 Oct 2010.

To cite this article: Roberto Sánchez Gómez , Isabel Suárez González & Luis Vazquez Suárez (2011)Service quality control mechanisms in franchise networks, The Service Industries Journal, 31:5,713-723, DOI: 10.1080/02642060902833338

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Service quality control mechanisms in franchise networks

Roberto Sanchez Gomeza�, Isabel Suarez Gonzalezb and Luis Vazquez Suarezb

aSeccion de Organizacion de Empresas, University Carlos III de Madrid, Facultad de CienciasSociales y Jurıdicas, C/ Madrid 126, 28903 Getafe, Spain; bDepartamento de Administracion y

Economıa de la Empresa University of Salamanca, Campus Miguel de Unamuno s/n, edificio FES,37007 Salamanca, Spain

(Received 3 November 2008; final version received 26 January 2009)

This paper reports the study of some factors that influence the control intensity exerted byfranchisors on the service quality provided by the franchised units of their networks andwhat interdependencies exist between the different mechanisms that can be used tomonitor service quality. On the one hand, three control mechanisms of conformancequality are considered, namely audits, mystery shoppers, and mandatory purchase ofinputs and products. On the other hand, polls are used to monitor perceived quality bycustomers. There are two main findings. First, control intensity is greater in thoseindustries in which customers tend to be non-repetitive. Second, four complementaryrelationships are found between control mechanisms: between audits and mysteryshoppers, between audits and polls, between mandatory purchase of inputs or productsand mystery shoppers, and between mandatory purchase of inputs or products and polls.

Keywords: control mechanisms; free-riding; franchising; service quality; conformancequality; perceived quality; mystery shoppers

Introduction

Franchising is a cooperative agreement by which one firm (the franchisor) sells the right to

market goods or services under its brand name and using its business practices to a second

firm (the franchisee) (Combs, Michael, & Castrogiovanni, 2004). Uniformity is the core

element of franchising as a way of doing business, since the franchisees have the obli-

gation to comply with the standards set by the franchisor. In fact, uniformity is the

main attraction of franchising for consumers because it allows them to reduce the

search costs they face when they have no information about the quality of other businesses

or this is costly to obtain. In short, consumers value uniformity and the franchisor has to

ensure that uniformity is maintained across the franchise system.

In order to maintain uniformity, the franchisor has to monitor the service quality level

provided by the units of the network. Control is necessary since franchisees may have

incentives to free-ride on the brand name, which would damage uniformity. Free-riding

includes failure to follow company procedures in terms of quality, service, or advertising,

overcharging customers, and/or lack of effort regarding the appearance of employees or

the workplace (Kidwell, Nygaard, & Silkoset, 2007). For instance, franchisees may be

inclined to free-ride when customers are non-repetitive or when their financial situation

is bad. In other cases, failure to follow standards is a result of a desire for autonomy on

the part of the franchisee. Szulanski and Jensen (2006) describe how a franchisee may

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DOI: 10.1080/02642060902833338

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�Corresponding author. Email: robertosanchez@usal.es

The Service Industries Journal

Vol. 31, No. 5, April 2011, 713–723

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modify recommended practices by the franchisor in order to create fit with the local

environment. They also show that this behaviour has a negative impact on network

growth. Free-riding hazards arise because opportunistic franchisees may benefit from all

the cost reductions derived from free-riding, but its negative consequences (i.e. the

damage to the brand image and, thus, to brand name value) are shared by all the units

of the network since they all share a common brand.

Previous literature on management has posed that control is a key aspect of organiz-

ational design (Eisenhardt, 1985; Jaworski, 1988; Lusch & Jaworski, 1991; Ouchi,

1979). Considering this and the relevance of control to the success of franchise networks,

it is somewhat surprising that few franchising studies have addressed this issue. Bradach

(1997) studied five restaurant chains and documented the use of three formal control

mechanisms by franchisors: audits, mystery shoppers, and management information

systems. Finn and Kayande (1999) compared the reliability of two control mechanisms:

mystery shoppers and polls. They found that the first ones were more reliable than the

second ones, though its cost was ten times higher.

The aim of this research is threefold. First, the authors describe the complete set of

formal control mechanisms used by franchisors to assure that franchisees comply with

the service quality level required. Second, the factors that explain the monitoring intensity

carried out by franchisors of the quality service level provided by their franchisees are

studied. Monitoring intensity should be higher the higher potential for free-riding. Thus,

the goal is to identify which factors increase free-riding hazards by franchisees. Third,

the interdependences between different control mechanisms are examined. In order to

address this objective, we relate the aspects that the franchisor need to control for and

what mechanisms are suitable for that purpose.

The empirical study is based on a sample of franchisors in Spain at the beginning of

2004. There are several differences between this study and those that have addressed

control devices in franchising. On the one hand, this research addresses directly what

control mechanisms are used by the franchisors to control quality service and uniformity,

while the focus in the Bradach (1997) study was to show how dual distribution may con-

tribute to network adaptation. In addition, while Bradach (1997) studied fast-food chains,

this study considers a large diversity of industries in which franchising is present. There-

fore, it allows us to generalize the results obtained about the use of monitoring mechan-

isms in franchise networks. On the other hand, the complete set of control mechanisms

employed by franchisors is examined, while the study of Finn and Kayande (1999)

focused on two of them.

The structure of the rest of the paper is as follows. In the next section, each one of the

different formal control mechanisms that franchisors use to monitor service quality pro-

vided by their franchisees is described. Then the determinants of the monitoring intensity

exerted by franchisors are examined. Next the interdependences between the different

control mechanisms are studied. Finally, the main conclusions are provided.

Control mechanisms of service quality

In general, franchisors’ goals are to earn profits while simultaneously ensuring the main-

tenance of their brand equity. However, franchisees are less directly vested in safeguarding

brand equity unless its dilution manifestly reduces their own sales revenue; consequently,

opportunistic franchisees may attempt to obtain higher levels of short-term profitability

even at the expense of brand equity. The imperfections of alignment necessitate the use

of monitoring techniques (Dant & Nasr, 1998).

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Franchisors can use four different mechanisms to control the service quality level

provided by their franchisees. These are audits, mystery shoppers, polls to clients, and

mandatory purchase of inputs and products by the franchisee to the franchisor or to

suppliers approved by the franchisor.

Audits

Audits consist of visits to franchised units by franchisor representatives in order to verify

the quality of inputs and products and compliance with operational guidelines. For

example, in fast-food chains these audits are known as quality, service, and cleanness

audits (QSC audits). Moreover, these visits constitute an important communicational

device because they also serve as a way of listening to franchisee’s demands.

Mystery shoppers

A mystery shopper is an anonymous, trained observer who enters the franchise establish-

ment posing as an average consumer and, immediately after engaging in what appears to

be a normal customer interaction, completes a detailed report on various aspects of the

service and shopping environment at the outlet (Finn & Kayande, 1999).

Polls

Polls to clients allow the franchisor to obtain information about the satisfaction level of the

consumers with the consumer experience at franchised units.

Mandatory purchase of inputs or products

By obligating franchisees to purchase the inputs or products of the franchisor or of

approved suppliers, the franchisor avoids the problem that franchisees might reduce the

quality of the inputs and products.

Determinants of the use of service quality control mechanisms

Hypotheses

The franchisor needs to monitor the service quality level provided by their franchisees, so

that he/she makes sure that the franchisees do not free-ride. Since control mechanisms are

used in order to maintain network uniformity, the greater the danger to uniformity, that is,

the higher potential for free-riding, the greater their use should be. Three factors are related

to free-riding hazards: the size of the franchise network, the geographical concentration of

the units of the network, and whether the consumers are non-repetitive.

Franchise network size

The higher the size of the franchise network, the more the franchisees have an incentive to

free-ride because it is more costly for the franchisor to detect free-riding, since control

costs increase with the number of units that have to be monitored and the negative conse-

quences of free-riding are shared by a larger number of units.

Therefore, the higher the size of the network, the greater the need to control for free-

riding potential. Since monitoring intensity should increase with the need to monitor the

franchisees, we expect that:

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H1: There is a positive relationship between franchise network size and the monitoring inten-sity by franchisors.

Geographical concentration of the units of the network

All else being equal, the higher the geographical concentration of the units of the network,

the more likely are free-riding hazards. The greater the concentration of units, the greater

the incentive on the part of a franchisee to free-ride at the expense of the others because the

negative consequences of free-riding are shared by all the units since they all share a

common brand.

Since the monitoring intensity should increase with the need to control for free-riding

hazards, and these hazards increase with the geographical concentration of the units, we

expect that:

H2: There is a positive relationship between the geographical concentration of the units of thefranchise network and the monitoring intensity by franchisors.

Non-repetitive consumers

All else being equal, free-riding hazards increase when customers are non-repetitive.

In this case, the free-rider internalizes to a lesser extent the negative consequences of

free-riding (Brickley, 1999; Brickley & Dark, 1987). Therefore, the need to control for

free-riding potential is greater when customers are occasional. This argument leads us

to our third hypothesis:

H3: There is a positive relationship between monitoring intensity by franchisors and sectors inwhich customers are non-repetitive.

Method

The data come from a questionnaire sent to all the franchisors that operated in Spain at the

beginning of 2004 according to the Spanish Franchisors Association (AEF), that is, 642

franchise networks. After a pre-test of the questionnaire with 20 franchisors, we contacted

the rest of the population. In all cases, we contacted with the Expansion Director or Fran-

chise Director of every network and asked him/her to respond to the questionnaire. We

deleted 32 networks, since they told us that they were not a franchise network (11 networks)

and they were not franchising anymore (21 networks). Of the 610 remaining firms, we

received 145 total responses and 138 usable responses (22.62% usable response rate).

Dependent variable

The dependent variable is monitoring intensity of service quality by franchisors, measured

as the sum of the number of the four control mechanisms described in the second section.

Independent variables

We use three independent variables. First, network size is measured as the total number of

outlets of the network, company-owned by both the franchisor and the franchised ones.

Second, the geographical concentration of the units of the network is proxied by (P

xi

wi/P

wi)�100,000, where xi is the number of units of the network in province i divided

by the number of inhabitants in province i; wi denotes the number of units of the

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network in province i (i ¼ 1, . . . 52). Third, whether customers are non-repetitive or

repetitive is proxied by a dummy variable, following the criteria employed by Brickley

and Dark (1987) and Brickley (1999) in other franchising studies. This variable equals

1 for sectors in which customers tend to be non-repetitive (that is, fast-food and

network restaurants and car-rental agencies), and equals 0 for sectors in which customers

tend to be repetitive (i.e. clothing stores).

Table 1 shows the distribution of the dependent variable, that is, the number of control

mechanisms employed by franchisors. Only three franchise networks (2.17%) did not use

any control mechanisms, while 72.46% of the franchise networks employed three or more

control mechanisms.

Table 2 presents the descriptive statistics and correlations. The obligation of the fran-

chisee to purchase the inputs and products from the franchisor or from approved suppliers

and the audits are the most used control mechanisms (84.25% and 83.46%, respectively).

Nonetheless, polls are utilized by a smaller percentage of franchisors (68.50%), and

mystery shoppers are the less-used control mechanism (59.84%). Correlations show

that, consistent with theory, when customers are non-repetitive (1) monitoring intensity

is higher, because the correlation between the repetitive sector and the monitoring inten-

sity variables is negative and significant (r ¼ 0.21, p ¼ 0.013); (2) franchisors use polls

(r ¼ 2 0.17, p ¼ 0.047) and mandatory purchase of inputs and products (r ¼ 2 016,

p ¼ 0.062) significantly more intensively than when customers are repetitive.

The use of polls and the size of the network are positively and significantly correlated

(r ¼ 0.16, p ¼ 0.065). This is probably because the larger the size of the network, the

more profitable the polls are since a large size permits scale economies. Also, it is observed

that the more dispersed the units of the network, the more the franchisors use audits

(r ¼ 2 0.18, p ¼ 0.033) and mandatory purchase of inputs and products (r ¼ 2 0.22,

p , 0.01).

To test the hypothesis concerning the determinants of monitoring intensity, we employ

an ordinal logit model. This technique is appropriate when the dependent variable may be

equal to several discrete values and there is a hierarchical order between them. In particu-

lar, we assume that monitoring intensity is higher when franchisors use four control mech-

anisms than when franchisors use three control mechanisms, and so on. Ordinary least

squares (OLS) regression is not appropriate because, owing to the nature of the dependent

variable, results would be biased.

Table 3 shows the results of the ordinal logit regression. H1, which posited a positive

relationship between the size of the franchise network and monitoring intensity, is not sup-

ported (b ¼ 0.00, p ¼ 0.84). H2, which posited a positive relationship between the geo-

graphical concentration of the units of the network and monitoring intensity, is also not

Table 1. Number of control mechanisms employed by the franchisors (N ¼ 138).

Number of control mechanisms used Number of franchisors (%) % accumulated

0 3 (2.17) 2.171 12 (8.70) 10.872 23 (16.67) 27.543 46 (33.33) 60.874 54 (39.13) 100Total 138 (100)

Note: Mean ¼ 2.98, standard deviation ¼ 1.05.

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Table 2. Descriptive statistics and correlations.

Mean SD Minimum Maximum 1 2 3 4 5 6 7 8

1. Monitoring intensity 2.96 1.07 0 4 1.002. Audits 0.83 0.37 0 1 0.63��� 1.003. Mystery shoppers 0.59 0.49 0 1 0.67��� 0.19� 1.004. Polls 0.68 0.46 0 1 0.65��� 0.29��� 0.17† 1.005. Mandatory purchase of inputs and

products0.84 0.36 0 1 0.56��� 0.21� 0.21� 0.12 1.00

6. Network size 57.53 97.23 3 705 20.03 20.08 0.00 0.16† 20.22� 1.007. Geographical concentration of the

units of the network0.65 1.16 0.01 8.27 20.07 20.18� 0.05 0.09 20.22�� 0.38��� 1.00

8. Repetitive sector 0.79 0.40 0 1 20.21� 20.06 20.13 20.17� 20.16† 0.07 20.04 1.00

�p , 0.05.��p , 0.01.���p , 0.001.†p , 0.1.

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supported (b ¼ 2 0.13, p , 0.05). H3, which posited a higher monitoring intensity in

non-repetitive sectors, is supported (b ¼ 2 1.02, p ¼ 0.016).

Given that the results show that the type of sector does matter when it comes to explain

monitoring intensity, we examine the effect of this variable on the use of each one of the

control mechanisms. Results are provided in Table 4. Franchisors in non-repetitive sectors

use polls and mystery shoppers to a greater extent than do franchisors in repetitive sectors.

Presumably, this is because free-riding hazards are higher when customers are non-

repetitive.

Interdependences between service quality control mechanisms

Service quality dimensions

Franchisors communicate to franchisees how to manage the franchised unit through train-

ing (which takes place in visits to the franchised unit or in company-owned units) and

operational handbooks. Operational features include which inputs have to be utilized,

the dress of the employees, the store window, the lighting, cleanliness, the space distri-

bution, and operational procedures (e.g. how to mix the inputs, how to relate to clients).

Service quality consists of two dimensions: conformance quality and perceived

quality. Conformance quality consists of adjusting to the franchisor’s requirements

about how to manage the unit. This quality dimension includes three aspects: (1) inputs

and products; (2) the store environment and employees’ clothing; (3) operational pro-

cedures to carry out the business, which include all the activities that the franchisee has

to perform since the consumer enters the store until he departs. Perceived quality is the

degree to which customers are satisfied with the service they are provided with.

Table 5 relates the dimensions of service quality to the control mechanisms that

franchisors may use to control service quality. Both audits and mystery shoppers are

Table 3. Ordinal logit regression explaining monitoring intensity (N ¼ 127).

Independent variables Coefficient Standard error z p-Value

Franchise network size 0.0004 0.0021 0.20 0.844Geographical concentration of the network 20.1340 0.1791 20.75 0.454Repetitive sector 21.0281 0.4257 22.41 0.016

Note: Log-likelihood ¼ 2 167.6969, LR x2 (3) ¼ 6.48, prob . x2 ¼ 0.0904, pseudo R2 ¼ 0.0190.

Table 4. Influence of sector type on monitoring intensity (N ¼ 138).

Sector Statistics

Control mechanisms

Audits Mystery shoppers PollsMandatory purchase

of inputs and products

Repetitive x2 0.8584 3.1596† 5.1622� 2.2418F (ANOVA) 0.85 3.19† 5.29� 2.25t 0.9226 1.7852† 2.2989� 1.4986

Note: The sector variable equals 1 in case that the industry is repetitive and equals 0 in case that the industry isnon-repetitive. The null hypothesis is that mean(0) ¼ mean(1). Thus, a positive and significant (negative andsignificant) t value implies that the control mechanism is more used, on average, by franchisors in non-repetitiveindustries (repetitive industries) than in repetitive industries (non-repetitive industries).�p , 0.05.†p , 0.1.

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useful to verify the three elements that comprise conformance quality. However, the use

of these two control mechanisms should be complementary because of three reasons.

First, mystery shoppers can not always verify the degree to which franchisees comply

with those three elements. This problem occurs because not always they can observe

it. In particular, some operational procedures are not carried out in the presence of

clients (e.g. the manipulation of inputs in the kitchen of a restaurant) and the client

cannot enter some store rooms (e.g. the mystery shopper cannot enter the kitchen).

Second, contrary to what occurs in the case of audits, the franchisee does not know

that he/she is being evaluating when it comes to mystery shoppers. Third, audits are

useful not only as a formal control mechanism but also as a way to communicate and

to train and advise franchisees and, thus, enhancing the franchise relationship. As a mech-

anism of initial support, audits are useful to train franchisees, while as an on-going

support mechanism, they are helpful to explain changes in the network policies to fran-

chisees, to gather information about local markets, and to listen to franchisees’ sugges-

tions and complaints.

Polls are complementary to the rest of the control mechanisms. In particular, it can be

expected that a complementary relationship between the use of polls and mystery shoppers

exists. The second ones are useful to evaluate the accomplishment of operational pro-

cedures and store environment standards. Clients are also asked to give their opinion

about these aspects. However, while mystery shoppers evaluate conformance quality

(the fulfilment of standards), polls are helpful to evaluate the degree of quality perceived

by clients; that is, to what extent standards satisfy their expectations. In other words, while

mystery shoppers provide an objective evaluation, polls give a subjective evaluation that is

useful to evaluate the fitness of network policies.

Finally, mandatory purchase of inputs and products allows the franchise to avoid the

possibility that the franchisee employs low quality inputs or products. However, since this

purpose is the only one that this mechanism is useful to the use of this control mechanism

should be complementary with the use of the rest of the control mechanisms.

Taking into account the arguments presented above, we derive the following hypoth-

esis about the complementary use of control mechanisms.

H4: All service quality control mechanisms are complementary to each other.

Table 5. Service quality dimensions and service quality control mechanisms.

Control focus(what is

monitored)

Service quality dimensions

Conformance quality Perceivedquality

Inputsand

products

Storeenvironment and

employees’clothes

Operationalprocedures

Customers’satisfaction

Controlmechanisms(how it ismonitored)

Audits † † †Mystery

shoppers† † †

Polls †Mandatory

purchase ofinputs andproducts

†

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One way to assess complementarities between the use of control mechanisms is to

examine bivariate correlations between each pair of control mechanisms. In case this cor-

relation is positive and significant, it could be concluded that a complementary relation-

ship exists. However, a problem with this methodology is that it does not control for

third unobserved variables that could, in fact, derive the correlation. In this case, the analy-

sis of bivariate correlations could be biased and thus lead us to wrong conclusions. To

solve this problem, we use unconditional correlations as used in previous work (Arora

& Gambardella, 1990; Arrunada, Garicano, & Vazquez, 2001). For this purpose, we

perform four logit regressions, in which the dependent variables are control mechanisms

(audits, mystery shoppers, polls, and mandatory purchase of inputs and products) and the

explanatory variable are the same in each regression (network size, the geographical con-

centration of the units of the network, and whether the sector is non-repetitive or repeti-

tive). Then we calculate the conditional correlations, that is, the correlations between

the standardized residuals of these logit regressions.

Table 2 shows bivariate correlations. All the six correlations show the expected posi-

tive sign and five of the six correlations are significant (all except the correlation between

polls and mandatory purchase of inputs and products). Conditional correlations are dis-

played in Table 6. All the six correlations show the positive expected sign, though only

four are significant. Now the correlation between polls and mandatory purchase of

inputs and products is significant, while both the correlation between audits and mandatory

purchase of inputs and products and the correlation between polls and mystery shoppers

are not significant.

Conclusions

This paper has studied the factors that explain the intensity of control of service quality

provided by franchisees and the interdependencies between the control mechanisms

employed by franchisors. This study mainly contributes to three things. First, with

respect to the determinants of control intensity, it has been found that franchisors

control service quality more intensively when customers are non-repetitive. In particular,

franchisors in non-repetitive industries utilize mystery shoppers and polls more frequently

than franchisors in repetitive industries. Second, a theoretical contribution is that the

relationship between the two different dimensions of service quality (namely, confor-

mance quality and perceived quality) and the different control mechanisms of it have

been examined. This is useful for future research, which examine the relationship

between control intensity and performance. If the theory presented is correct, those

Table 6. Conditional correlations between control mechanisms (N ¼ 127).

AuditsMysteryshoppers Polls

Mandatory purchase of inputsand products

Audits 1.00Mystery shoppers 0.20� 1.00Polls 0.27�� 0.12 1.00Mandatory purchase of inputs

and products0.13 0.21� 0.14† 1.00

�p , 0.05.��p , 0.01.†p , 0.1.

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networks that monitor both dimensions of service quality should have better performances

than those networks that monitor only one of them, all else being equal.

Finally, in relation to the interdependences between control mechanisms, it has been

observed that four complementary relationships exist: first, between audits and mystery

shoppers; second, between audits and polls; third, between mandatory purchase of

inputs or products and mystery shoppers; fourth, between mandatory purchase of inputs

or products and polls.

However, this study is not without limitations. First, the frequency of use of each

control mechanism is not considered. Unfortunately, the authors do not have this data.

Second, an issue not examined in this work is whether other incentive mechanisms and/

or safeguards influence the intensity of control. For example, incentives and controls

are substitutes or complements? The researchers have not found a significant and positive

relationship between geographical concentration of the units of the network and control

intensity. It is possible that other incentive mechanisms, like multi-unit franchising,

affect the monitoring intensity. If the units that a multi-franchisee owns are geographically

close, the likelihood of free-riding hazards on the part of the franchisee are reduced

because if in that case the geographical proximity between units entails that the multi-

unit franchisee would internalize to a greater extent the negative consequences of free-

riding (i.e. the lost of clients) than if there was a great dispersion between the units.

Thus, if the risk of free-riding is low, the need to monitor these outlets would be lower

and thus the control intensity would be lower too. In conclusion, the authors hope that

this research encourages other researchers to study the interdependencies between govern-

ance mechanisms in franchising, which is necessary to assess the determinants of every

governance mechanism.

Acknowledgements

Financial support from the Spanish Commission for Science and Technology and the

European Regional Development Fund (ERDF) through research grants SEJ2004-

03888/ECON and SEJ2007-63879/ECON is gratefully acknowledged.

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