The Mediating Effect Of

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The Mediating Effect of

Satisfaction on Consumers

Switching Intention

Carmen Antn, Carmen Camarero, and Mirtha Carrero

University of Valladolid, Spain

ABSTRACT

Most previous research on consumers switching intention has

focused on individual variables that have immediate effects on consumers

intentions or behaviors, rather than analyzing it as a complex

phenomenon. This article provides evidence that some service

provider behaviors precipitate relationship dissolution, whereas

other behaviors create a predisposition to switch. This different

effect is observed through the mediating effect of customer satisfaction.

While poor service quality and low firm commitment undermine

consumer satisfaction and have only an indirect effect on

switching intentions, price unfairness and anger incidents have

a strong effect on switching, both directly and indirectly through

satisfaction. Implications are discussed for customer relationship

management. 2007 Wiley Periodicals, Inc.

Research in relationship marketing has for some time now argued that


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creating and developing relationships contributes to the success of firms

(Morgan & Hunt, 1994). Some authors maintain that firms can even use

relationship marketing as a competitive advantage (Day, 2000). This

interest in the relational approach of exchanges has led to a proliferation

of studies examining all types of relational phenomenon in both consumer

and industrial markets: the creation of relationships (Ganesan,

1994), the determinants of loyalty (McDougall & Levesque, 2000; Sirohi,

McLaughlin, & Wittink, 1998), the strategies firms adopt to achieve customer

Psychology & Marketing, Vol. 24(6): 511538 (June 2007)

Published online in Wiley InterScience (www.interscience.wiley.com)

2007 Wiley Periodicals, Inc. DOI: 10.1002/mar.20171

511

commitment (Sharp & Sharp, 1997; Yi & Jeon, 2003), or the value firms

can generate by building customer loyalty (Reichheld & Sasser, 1990;

Sin et al., 2002), among others.Within this wide range of proposals and

tendencies, however, there is a surprising scarcity of research analyzing

why relationships end.

In the case of industrial relationships, relationship dissolution has

attracted more attention from researchers (Gassenheimer, Houston, &

Davis, 1998; Heide & Weiss, 1995;Michell, Cataquet,& Hague, 1992;Perrien,

Paradis, & Banting, 1995; Ping, 1995). Halinen and Thtinen (2002) point

out in this respect that analyzing the dissolution process is very important

in industrial markets, since firms must frequently consider terminating


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inefficient relationships because of their implicit costs.

In the case of consumer relationships, in contrast, the phenomenon

does not appear to have provoked as much interest in the literaturethe

studies by authors such as Hocutt (1998), Keaveney (1995),Mittal and

Lassar (1998), and Bansal and Taylor (1999, 2002) are exceptions. And

this in spite of the fact that in certain services,when customers terminate

relationships the firm may incur high costs. Keaveney (1995) indicates

that when firms lose a customer they are not only losing future earnings

and incurring the cost of finding new customers, they are also probably

losing a loyal customer, which means giving up high margins. Over

time, loyal customers increase their expenditure in the firm, and they

become less price-sensitive and less costly. Keaveney and Parthasarathy

(2001) likewise warn that consumers switching behavior in services markets

can be particularly serious when the service is delivered continuously,

such as in insurance, banking, public services, medical insurance, telecommunications,

or generally in services in which customers take out a subscription.

A premature end to the relationship may mean that customers

end up costing the firm more than they bring in. The problem becomes

more serious if we consider consumers greater access to information and

their growing capacity to choose the best option. Customers are becoming

increasingly intolerant of inconsistency or mediocrity, and they can

choose to dissolve the relationship as soon as any problem arises. In


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this respect, Roos (2002) points out that there are critical relationships,

i.e., relationships that are more likely to end because of their context,

which includes the ability of competitors and customers to adapt to

changes.

In this perspective, the objective of the current work is to deepen our

understanding of the process whereby consumers dissolve their relationship

with their service provider. Thus, this study proposes and tests a

model that considers dissolution as a phenomenon in which there are

determinant factors of the switching intentionpoor service quality, unfair

pricing, low perceived commitment, and critical episodesand mediating

factorssatisfaction. Other determinants of relationship termination and

switching have been considered in the literature, for example awareness

of alternatives or the consumers search for variety (Bansal, Taylor, &

ANTN, CAMARERO, AND CARRERO

Psychology & Marketing DOI: 10.1002/mar

512

James, 2005; Bansal & Taylor, 1999; Jones, Mothersbaugh, & Beatty, 2000).

The current work is focused exclusively on determinant factors relating to

the firms behavior and its relationship with its customers, ignoring other

aspects such as consumer preferences, attitudes, or behaviors with regard

to the product or service. Specifically, the following questions are examined:

How do service quality, perceived price, commitment, anger episodes, and

consumer satisfaction intervene to produce switching intentions? Does the


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consumers satisfaction/dissatisfaction have a mediating function between

the determinant factors and the consumers switching intentions?

The work, which attempts to contribute to knowledge about relationship

dissolution by responding to these questions, is organized as follows.

In the first section, the dissolution process and the determinant

factors of that process are analyzed. The nature of satisfaction as a mediator

is discussed in the second section, along with the proposed model of

dissolution. Subsequently, the model is tested with data from a sample

of automobile-insurance buyers and the results are analyzed. The work

ends with a section presenting the main conclusions and the management

implications.

RELATIONSHIP DISSOLUTION IN CONSUMER MARKETS

The relationship marketing literature has offered various models of the

processes by which these relationships form and develop (Dwyer, Schurr,&

Oh, 1987; Landeros, Robert, & Plank, 1995). The most widely-cited model

is undoubtedly Dwyer, Schurr, and Oh (1987), which identifies five stages

in an interactive process that they generalize for all buyer-seller relationships:

awareness, exploration, expansion, commitment, and dissolution.

According to these authors, dissolution can be present in any of these

stages, even once all of them have been overcome. If commercial relationships

can be compared to a marriage, then unfortunately they can at

times also be expected to end in divorce (Dywer, Schurr, & Oh, 1987).


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Hocutt (1998), from social penetration theory, maintains that members continue

to deepen their relationships as long as the expected benefits exceed

the expected costs. The relationships are dissolved when this is no longer

the case.

This dissolution stage has also been seen as a process. Coulter and

Ligas (2000) identify three stages in the long dissolution stage: (1) the

breakdown trigger, i.e., any factor that starts off the switch; (2) the breakdown

phase, marked by negative and positive experiences, as well as by

inertia, when relationship members evaluate both the transaction and

the psychological costs of switching; and (3) the determinant incident, i.e.,

any factor that makes the customer end the relationship.

In these definitions of the dissolution process the authors are beginning

to glimpse the possible existence of different factors and experiences:

some gradually undermine the relationship and push it towards the

CONSUMERS SWITCHING INTENTION


513

switching intention, while others precipitate the termination. But

researchers studying the dissolution of interfirm or firm-consumer relationships

have not yet empirically analyzed the degree of intervention of

the influencing factors in relationship dissolution. The literature on

dissolution antecedents has focused on specific factors: changes in the

service, in the quality, in the price (Keaveney, 1995; Kelley, Hoffman, &


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Davis, 1993; Rust & Zahorik, 1993), changes in the staff (Keaveney, 1995;

Perrien, Paradis, & Banting, 1995), commitment (Hocutt, 1998), and dissatisfaction

(Crosby & Stephens, 1987; Mittal & Lassar, 1998; Ping, 1995).

Clearly, a large number of factors operate simultaneously in the dissolution

process. Roos (1999), after analyzing the experiences of numerous

consumers using the critical incident method, argues that relationship

dissolution has three types of determinant: determinants pushing consumers

to switch suppliers, determinants that encourage them to remain

in the relationship (pullers), and swayers, which act so that after the

switch the consumer resorts to their old supplier occasionally. In a very

similar line, Halinen and Thtinen (2002) theoretically argue for the

need to categorize the antecedents of dissolution in three levels: predisposing

factors, precipitating factors, and attenuating factors of the switching

intention. Finally, Bansal, Taylor, and James (2005) present a model

based on a migration model from the human geography literature to

examine push, pull and mooring variables in service switching.

Before describing these antecedents of switching intention a short

digression is needed to clarify that the study of the dissolution process

differs markedly from the models explaining consumer loyalty or commitment.

Variables having positive outcomesloyalty or retentionmay

have an asymmetric effect when we examine negative outcomes

dissolution (Bansal & Taylor, 1999). Duck (1981) indicates that while


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growth in relationships depends on interaction, decline can result from

the action of one partner alone. Moreover, relationship decline will presuppose

the existence of a relationship and thus assumes the existence

of something that has had an evolution and can only decline in a way that

is a reflection of its evolution.

DETERMINANT FACTORS OF RELATIONSHIP DISSOLUTION

There are certain factors that encourage consumers to end their relationships.

These factors can act continuously over time, creating unease

in the consumerfactors that predisposeor alternatively, they can

arise abruptly, accelerating the consumers intention to terminate the

relationshipfactors that precipitate. Thefactors that predispose to

relationship dissolution are factors that create the conditions in which

individuals pay more attention to certain elements that will precipitate

dissolution. Duck (1981), in the context of personal relationships, and

Halinen and Thtinen (2002), in the context of business relationships,



514

indicate that predisposing factors already exist when parties enter into

a relationship, making it vulnerable to breakdown. These factors

could also appear during the relationship; but their effect is not immediate

as they need the accumulation of several incidents to be considered by

the consumer. The factors that predispose may be related to the


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fulfillment of the tasks inherent to the relationshipdeficiencies in

delivering the service quality required or desired by the consumeror

to the dyadic relationshipdecrease in the commitment and interest

demonstrated by the firm in the relationship. Thefactors that precipitate

dissolution are events pushing the consumer to take measures to

end the relationship (Duck, 1981; Halinen & Thtinen, 2002; Halinen,

Havila, & Salmi, 1999). They may be sudden and dramatic, or form

part of a series of events pushing the consumer towards switching suppliers.

Like in the previous case, they are failings in the fulfillment

of the taskssudden price raisesor deficiencies in the interaction in

the relationshipsporadic conflicts or episodes that demonstrate the

firms lack of interest in the clientwhich provoke consumers anger

and lead them to take immediate measures. In the current proposal, it

is considered that the main predisposing factors are deficiencies in the

quality of the service (Hess, Ganesan, & Klein, 2003), and the firms poor

efforts to maintain the relationship (Dwyer, Schurr,& Oh, 1987); while the

precipitating factors are the perception of price unfairness (Keaveney,

1995), and the experience of episodes of dissatisfaction or critical

incidents (Roos, 1999, 2002).

Poor Service Quality

The quality of the service, from the perspective of Grnroos (1990), is

conceptualized from two dimensions: the technical quality (what is delivered


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to the consumer) and the functional quality (how it is delivered). The

most widely-employed measure of this variable is the one proposed by

Parasuraman, Zeithaml, & Berry (1988)the SERVQUAL scale, which

consists of five dimensions (tangibles, reliability, responsiveness, assurance,

and empathy). But this scale has led to some controversy. Brady and

Cronin (2001), for example, criticize it and propose an alternative.

These authors contend that the perceived service quality is instead

made up of three dimensions: the outcome, interaction, and physical environment

qualities. Outcome quality is defined as what the customer

obtains when the productive process ends; interaction quality refers to

the interaction that takes place while the service is being delivered; and

environment quality refers to the conditions of the environment where

the service is delivered or the product is sold.

In line with this last definition of quality,Keaveney (1995) suggests that

consumers voluntarily exit a relationship because of personal dissatisfaction

with the quality of the service receivedoutcomeor with the

service providerinteraction. Many researchers have also suggested



515

that the quality of the customer-organization interaction affects the

customers response to failings in services (Berry, 1995; Kelley & Davis,

1994). The literature on loyalty also indicates that customers value the


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companys resources and skills very highlyresources and skills that

are manifested in the service quality (Mittal & Lassar, 1998).High quality

can motivate consumers to strengthen their relationship with their

service provider (Hess, Ganesan, & Klein, 2003; Bell, Auh, & Smalley,

2005), or not (a result obtained by Cronin & Taylor, 1992). What does

seem to be clearer is that poor quality or changes in the firms quality

levels provoke a change in consumers attitudes towards the firm

and probably a change in their behavior, as is demonstrated by Bansal,

Taylor, and James (2005), Dabholkar and Walls (1999), Roos (1999), or

Zeithaml, Berry, and Parasuraman (1996).

Low Organization Commitment to Customer

In the relationship marketing literature commitment is understood

as the desire to develop and maintain long-term exchange relationships,

a desire that materializes in the realization of implicit and

explicit promises, as well as sacrifices in favor of the economic and social

well-being of all the parties having some interest in the relationship

(Anderson & Weitz, 1992; Dwyer, Schurr, & Oh, 1987; Morgan &

Hunt, 1994;Walter & Ritter, 2000). The organizations commitment refers

to its interest in the consumers and its efforts to maintain their loyalty

by adapting to their specific needs, offering frequent communication,

special treatment, and full information. This attitude from the firm is a

result of the assumption that consumers can obtain more value from a


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relationship of continuing loyalty, and may therefore forgo the opportunity

to choose another supplier to fulfill their needs (Sheth & Parvatiyar,

1995). When consumers perceive added value in the firms efforts to offer

them special treatment to foster their loyalty, they will not switch suppliers.

Indeed in some cases the firms efforts to build customers loyalty

and keep them satisfied excludes any other type of relationship that the

consumer might contemplate with any of the firms competitors (Wathne,

Biong, & Heide, 2001; Dwyer, Schurr, & Oh, 1987), which makes the

switching intention even more improbable. In contrast, it can be also

maintained that low commitment on the part of the firm reflects its lack

of interest in the consumers and will lead to disenchantment, dispelling

any intention of loyalty. Breakdown can result from a faulty relational

process and consequent dissatisfaction with the relationship itself (Duck,

1981). Not only may expectations about the purpose of the relationship

and the quality delivered be disconfirmed, but also expectations about correct

or appropriate behaviors. In that line, Rusbult, Zembroke, and Gunn

(1983) found a low commitment to be a significant predictor of relationship

ending. Also, according to Michalskis (2004) findings in banking

services, significant reasons for ending are failures in interactions, not

in core services.




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Unfair Price

There are two tendencies with respect to consumers perception of the

price of the product. The first maintains that consumers regard high prices

as a signal of high quality and vice versa (Dodds, Monroe,& Grewal, 1991;

Teas & Agarwal, 2000); while the second, in contrast, suggests that low

prices can also function as a signal of good value for money (Kirmani & Rao,

2000). In either case, whether a low price is perceived as low quality or a

high price is perceived as abusive, when customers are dissatisfied with

the value for money or perceive the price to be unfair, their intention will

be to switch suppliers (Campbell, 1999; Homburg, Hoyer, & Koschate,

2005). Keaveney (1995) suggests that consumers voluntarily switch suppliers

because of their personal dissatisfaction with the price paid. This

dissatisfaction arises when the consumers perceive the price to be unfair

or excessively higher than alternative options. Athanassopoulos (2000)

and Bansal, Taylor, and James (2005) also show that among the reasons

consumers switch suppliers, price-related issues are important. Buyers

will be conscious of the savings opportunities that other options provide,

and the chance to make savings can become a substantial concern (Wathne,

Biong, & Heide, 2001), as well as the motive for an immediate switch.

Anger Incident

Roos (1999, 2002) analyzes critical incidents as a method for studying consumers


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switching decisions. These critical incidents or episodes can affect

consumers behavior, and specifically their intention to dissolve the relationship,

either completely or partially. These critical incidents can become

anger incidents when the events or episodes have provoked anger and

manifest dissatisfaction in the consumer. Bougie, Pieters, and Zeelenberg

(2003) show that anger is an emotion that, according to emotions theory

(Roseman, Wiest, & Swartz, 1994), encloses specific experience content.

Anger is associated with feelings (as if they would explode), thoughts

(thinking of how unfair something is), action tendencies (feel like behaving

aggressively, letting go), actions (complaining) and emotivational

goals (wanting to get back at someone). According to their study, anger

also mediates in the relation between consumers dissatisfaction with the

service and their behavioral responseending the relationship.

Having analyzed these four factors, it is maintained that the intensity of

these variables effects on switching intention is unequal. The perceived

failings in the service quality and in the firms commitment provoke

disenchantment and unease, and influence consumers intention to switch

suppliers; however, this influence is probably not very strong, insofar as

the consumer does not consider imminent action.As quality and commitment

comprise several dimensions, the perception of changes in quality and commitment

is not instantaneous. It is the sum of several factors and, as a

result, the consequences of such changes could be slower and more long-term


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than the effect of other immediate changes. In fact, the connection between

quality and exit seems to be weak because many events happen before a customer

decides to end the relationship (Bansal & Taylor, 1999). Michalski

(2004) refers in these cases to creeping relationship ending, because the

customer has a broad tolerance zone, and several negative incidents are

involved in the ending process. In contrast, raising the prices to levels considered

unfair, or a situation of anger or conflict, are more likely to provoke

an immediate reaction among consumers and their intention to switch suppliers

immediately. Price changes are easier for customers to observe and

detect than quality and commitment changes,which require a global evaluation.

This quick perception is most evident in cases when customers take

out a subscription and the price is paid before receiving the service, such

as in insurance, public services, medical insurance, or telecommunications.

In these cases, pricing becomes the first and most visible signal of the firms

activity. Hence, the perception of price changes and price unfairness is

instantaneous, and its effect on switching behavior is therefore more immediate.

Rotemberg (2005) indicates that consumers react negatively and with

anger to price increases when they become convinced that prices are unfair.

In the context of services, customers high sensitivity to prices has also been

demonstrated. Gerrard and Cunningham (2004) show that pricing is one


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of the main incidents that provoke switching behaviors in the banking

industry. Also, Lowengart, Mizrahi, and Yosef (2003) indicate that when

the difference between the price and the optimal reference price is small and

scarcely detectable by consumers, retailers may do better not to practice price

manipulations. As for anger incidents, their stronger effect on switching

intentions is predictable. Michalski reports customers strong emotional

reactions and sudden relationship ending in the case of unacceptable interactions

with the firm. Thus, the following hypothesis is proposed:

H1: The factors predisposing consumers to relationship dissolution

(poor service quality and perception of low commitment) will have

less influence on switching intention than the precipitating factors

(price unfairness and anger incident).

SATISFACTION AS MEDIATING VARIABLE IN

DISSOLUTION PROCESS

According to Baron and Kenny (1986), a variable has a mediator function

in a particular process if it explains the relation between the

antecedents and the results. The variables acting as mediators in the dissolution

process seem to be both the result of the determinant factors

and the antecedents of dissolution. Their direct effect on dissolution

comes mainly from the fact that they are the consequence of the

determinant variables, the true causes of the switch. But their function



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518

in the process should not be understood as merely to transmit the effects

of the determinant factors. Mediating factors are more than this: they are

the focus on which the causes determining relationship termination

converge; they then transform into a new and different concept that can

modify the final effect of such causes on dissolution. The loyalty literature

has traditionally regarded satisfaction as the mediator in the path

towards consumer commitment. By analogy, it might be expected this

variable to also play that role in the dissolution process.

Consumer satisfaction continues to be a vital objective in the marketing

community, since it is a critical focus for designing effective marketing programs

(Oliver, 1999), as well as companies predominant means of

detecting and controlling the probability of customer defection (Capraro,

Broniarczyk, & Srivastava, 2003). However, the effect of satisfaction on

loyalty has been shown to be more complex than it seems at first (Fournier

& Mick, 1999; Mittal & Kamakura, 2001). According to Burnham, Frels,

and Majahan (2003), firms are caught in a satisfaction trap, a myopic

belief that satisfaction and service quality are the only tools available for

retaining customers. Given this uncertainty about satisfactions role in

consumer retention processes, there is increasing interest in understanding

its role in dissolution processes.

At the theoretical level, satisfaction is a concept that has been amply


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debated in the literature. Numerous definitions have been proposed

(Oliver, 1997; Vanhamme, 2000), which tend to diverge from each other

(Szymansky & Henard, 2001). In the most recent definitions, the dual

nature of satisfaction is recognized, in other words a cognitive and an

affective character, as well as a relative nature, since it is the result of

comparing a subjective experience with a previous base of reference

(Oliver, 1993). For the purpose of the current work it is considered that

satisfaction is achieved when the consumers expectations about the performance

of the product or service being consumed are met or exceeded;

that it is a sensation or feeling generated both by cognitive and emotional

aspects of the product or service; and that it is a cumulative

evaluation of the sum of diverse aspects of the product or service.

On the basis of the hierarchical knowledge-attitude-behavior model,

the role of satisfaction is better understood as a mediator between

consumers experience and their behavior (Bloemer & de Ruyter, 1998;

Hellier et al., 2003; Lam et al., 2004; Olsen, 2002). Olsen (2002) demonstrates

that satisfaction acts as a mediator variable between service

quality and the intention to continue buying from the same supplier,

since quality only affects loyalty indirectly, through satisfaction. Harris

and Goode (2004) and Lam et al. (2004) also confirm satisfactions mediating

role in the relation between perceived quality or value and loyalty.

Thus, with the previously mentioned reasoning it is suggested that


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consumers satisfaction will mediate between the determinant factors of

relationship termination and the dissolution itself. This means that it will

simultaneously be the result of the determinant variables and the predictor



519

of dissolution. According to the cumulative satisfaction approach, evaluations

of the service quality, commitment, perceived price, and critical

episode of both a cognitive and emotional nature will all be summed to

produce a global evaluation of the service, which is labeled global

satisfaction.

With regards to the role of (dis)satisfaction as a predictor of dissolution,

it must be noted the controversy and lack of conclusive results in

the literature. Authors such as Capraro, Broniarczyk, and Srivastava

(2003) and Mittal and Lassar (1998) suggest that although there is a relation

between satisfaction and loyalty or consumers switching probability,

the variable is only a weak predictor of consumer repurchase

behavior. They stress the need to find other determinant factors. These

authors indicate that dissatisfied consumers may stay in their relationship

if they do not expect other alternatives to be any better, while

satisfied consumers may opt for other alternatives even if the current

outcome is satisfactory. In contrast to these views, numerous empirical

studies provide evidence that satisfaction does play a role in the


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retention process and repurchase behavior (Bolton, 1998; Jones,

Mothersbaug, & Beatty, 2000; LaBarbera & Mazursky, 1983; Oliver,

1997; Sambandam & Lord, 1995; Yang & Peterson, 2004). The relation

between dissatisfaction and switching seems to be more evident (Ping,

1994, 1995). Whereas satisfied consumers could be reluctant to exit

because there is much to lose, less satisfied consumers may be vulnerable

to moves aimed at increasing supplier attractiveness.

H2: Consumer satisfaction acts as a mediator variable between the

predisposing and precipitating factors of dissolution and the consumers

switching intention.

Also for the mediating effect of satisfaction, there may be different

consumer behaviors when consumers perceive poor service quality or

low commitment (predisposing factors) than when they perceive unfair

prices or an anger episode occurs (precipitating factors). As it has been

said, variables that predispose consumers to end their relationships act

by accumulating unease in consumers until they run out of patience,

and only thenafter a delaydo they influence the switching decision.

According to this reasoning, their repercussion on satisfaction will be

greater than their immediate effect on the switching intention. The intention

to dissolve the relationship will take place through a longer path, i.e.,

the mediating effect of satisfaction in the switching intention will be

high. On the other hand, the variables that precipitate relationship


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dissolution have a much more immediate effect on consumers intention to

end their relationship. Hence their effect on the switching intention will

logically be greater than their effect on satisfaction, so satisfactions

mediating role will be weaker in this case.



520

H3: The mediating effect of satisfaction will be stronger for variables

that predispose to dissolution than for variables that precipitate

dissolution.

Model 1 (see Figure 1) graphically represents the dissolution process

and the mediating role of satisfaction. This model describes the relation

between satisfaction and dissolution directly, while poor quality, low commitment,

unfair price, and anger episode, although they are linked with



521

SATISFACTION

SWITCHING

INTENTION

Model 2

SATISFACTION

SWITCHING

INTENTION

Model 3


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SATISFACTION

SWITCHING

INTENTION

Model 1 PREDISPOSING AND PRECIPITATING

FACTORS

Deficiencies in:

Outcome quality

Interaction quality

Physical environment quality

Price unfairness

Anger incident

Low perceived commitment

PREDISPOSING AND PRECIPITATING

FACTORS

Deficiencies in:

Outcome quality

Interaction quality


Price unfairness

Anger incident


PREDISPOSING AND PRECIPITATING

FACTORS

Deficiencies in:

Outcome quality

Interaction quality


Price unfairness

Anger incident



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-

-

-

-

-

+

+

Figure 1. Mediating effect of satisfaction: rival models.

relationship termination, will only have an indirect effect on dissolution

through satisfaction. Authors such as Bagozzi and Yi (1988) recommend

comparing the result of the model being proposed with other alternatives.

Morgan and Hunt (1994) and Pritchard, Havitz, and Howard (1999)

analyze the mediating function of commitment in this way, comparing the

model that they propose with other rival direct-effects models. For this

purpose, Figure 1 also shows two rival models of the dissolution process.

Model 2 allows testing the direct impact of poor quality, low commitment,

unfair price, and anger episode on both satisfaction and dissolution,

effects that we would expect to be significant. Model 3 responds to

a final question: Are the direct effects of the determinant factors of dissolution

still significant after adding the relationi.e., after opening the

pathbetween satisfaction and dissolution?


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METHOD AND RESULTS

Sample and Data Collection

For the empirical study it was needed to choose a product or service for

which relationship termination is a clear problem from the firms point

of view and a decision that is carefully thought about by the consumer.

Thus, the consumer relationship with automobile-insurance companies

was chosen as the scope of the study. This is a service, as Keaveney and

Parthasarathy (2001) point out, in which customers behavior in switching

suppliers may be particularly worrying for the firm, since it does not

normally recover costs until customers have spent several years with it.

If customers cancel their insurance, the firm can lose a considerable

amount of money. For the rest, it has the characteristics of all services:

intangibilityit is difficult to evaluate even after product purchase and

use; the variability of service quality and prices; the different relational

policies followed by the firms; and the occasional dissatisfaction that

may be felt for a service that does not match customer expectations. All

this means that consumers can question the decision they have made

on more than one occasion and consider switching suppliers. Other studies

have also analyzed the behavior of customers of insurance companies

(Verhoef, Franses,& Hoekstra, 2002; Hellier, et al., 2003), or of buyers

of medical insurance (Capraro, Broniarczyk, & Srivastava, 2003). Capraro,

Broniarczyk, and Srivastava (2003) note that the fact that insurance


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contracts need to be renewed annually gives consumers the frequent

opportunity to consider switching companies.

For the data collection, individuals that have bought automobile insurance

were surveyed. Survey-takers were employed and they obtained a

sample of 247 appropriate individuals. A total of 45.9% of the sample

habitually contact with their insurance firm through its offices, 37% do

so by telephone, 16.3% through an insurance broker, and only 0.7% of

them use the Internet.



522

Variable Measurement

In the appendix, a full list of the variables intervening in our study are provided.

All the items were measured using 5-point Likert-type scales.Next,

the process followed for creating and validating each variable is described.

Switching Intention. Relationship dissolution was measured in the

decision-making stage, when consumers consider switching suppliers.

The stage involves intentions, so it cannot be assured that the consumer

will actually dissolve the relationship in the near future. But this approach

does allow undertaking a cross-sectional analysis, and it is in line with previous

research (Hellier et al., 2003; Hocutt, 1998; Jones, Mothersbaugh,&

Beatty, 2000; Mittal & Lassar, 1998; Ping, 1994, 1995). The measurement

scale used was based on the scale proposed by Ping (1995).


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Poor Service Quality. Measuring service quality still seems to be a

controversial topic, as it has been mentioned. In our case, Brady and

Cronins (2001) proposal was adopted, which combines those of Grnroos

(1990) and Parasuraman, Zeithaml, and Berry (1988) and implies that the

perception of service quality is founded on three dimensions: the outcome,

interaction, and physical environment qualities. These three dimensions

define the base of the perceived service quality, and other second-order

dimensions may underlie them.Taking this approach, these three aspects

of quality were measured adapting the scale used by these authors.

Low Perceived Commitment. The scale for the firms commitment as

perceived by the consumer was built especially for this current work.There,

different aspects that the relationship marketing literature attributes to

a service providers relational orientation policy were included, on the basis

of items proposed by several authors (Anderson & Weitz, 1992; Gundlach,

Achrol, & Mentzer, 1995; Kumar, Scheer,& Steenkamp, 1995 and Mohr &

Spekman, 1994): willingness to invest; shared information; loyalty and

commitment to the customer; or perceived desire to continue.

Price Unfairness. The consumers perception of an unfair price and

poor value for money were each measured by a separate indicator. These

indicators were built for this current study starting from the results

obtained by Keaveney (1995) in her descriptive study of consumers

motives for terminating relationships.


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Perceived quality, commitment and price were measured by indicators

formulated in positive terms, so that strongly agree indicates a perception

of high quality, strong commitment, or a fair price, while strongly

disagree indicates the precise opposite of these. The fact that these items

were formulated in positive terms, to be subsequently recoded, allows the

use of the scales that were proposed in the literature when these concepts

were introduced. On the other hand, it is considered that formulating these



523

items in negative terms could be understood by the respondents as indicating

extreme states of dissatisfaction, which would likely be confused

with what we have labeled critical episode. Bansal,Taylor, and James (2005)

take a similar approach.

Anger Incident. This variable was measured using a single indicator,

in which respondents were asked to state if they had had any recent

experience with their supplier that had upset them and caused them to

lose confidence in the firm.

Satisfaction. A single item coming from Olivers (1997) satisfaction scale

was used to measure consumers global or cumulative satisfaction with

their insurance company. Compared to measuring satisfaction by evaluating

different aspects of the product or service, various authors have

opted to use a single item to measure global satisfaction (Athanassopoulos,


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2000; Ganesh, Arnold, & Reynolds, 2000; Mittal & Kamakura, 2001).

Although most of the proposed scales have been validated previously

in the literature, each of them was subjected to a validation process here.

For this, a confirmatory factor analysis (Lisrel 8.7) was performed,

following the procedure recommended by Anderson and Gerbing (1988).

The items proposed for measuring service quality, perceived price, and

perceived commitment were previously recoded, such that higher values

in the items indicated poor quality levels, greater price unfairness,

and lack of commitment. This codification allows representing negative

factors at the origin of consumers switching intentions (Bansal, Taylor,

& James, 2005) and to test the hypotheses in the proposed direction.

To test the validity of the measurement scales a confirmatory factor

model was estimated, the results of which are shown in Table 1. Although

the chi-square statistic is significantconceivably as a result of the size

of the samplethe lambda values and the remaining goodness-of-fit

indicators confirm the convergent validity of these scales.

After validating the convergence of the scales, the correlation matrix

of the factors resulting from each scale was calculated. Table 2 shows

the correlation matrix of all the variables, as well as the reliability values

Cronbach alphas and variance extractedin each case.

In all cases the variance extracted of each variable exceeds the value

of its squared correlation with the other variables, which justifies the


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discriminant validity of the scales (Anderson & Gerbing, 1988).

Estimation of Rival Structural Models

The following step in the analysis was to estimate the rival structural

models, following the procedure described by Anderson and Gerbing

(1988). In order to show that certain factors predispose consumers to

dissolve relationships, while others precipitate their switching decision,

we carried out the estimation following a hierarchical process. First, the

rival models were estimated to determine the effect of the variables that



524



525

Table 1. Confirmatory Factor Analysis.

Variable Items_ tGoodness of fit

Outcome quality QUA1 0.903 16.86

QUA2 0.831 15.05

Interaction quality QUA3 _

QUA4 0.882 15.32

QUA5 0.745 12.53

Physical environment QUA6 0.659 9.85

quality QUA7 0.940 13.42

Perceived commitment COM1 0.637 10.51_2(109) _ 195.37

COM2 0.594 9.63 (p_ 0.000)


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COM3 0.793 13.95 GFI _ 0.922

COM4 0.660 10.95 AGFI _ 0.880

COM5 0.708 12.09 CFI _ 0.982

RMSEA _ 0.054

Price PRI1 0.863 15.90

PRI2 0.939 17.96

Switching intention SWI1 0.875 13.94

SWI2 0.447 6.90

SWI3 0.788 13.23

Anger incident INC1 0.975 _

Satisfaction SAT1 0.975 _

predispose to dissolution, i.e., poor perceived quality and low perceived

commitment (Table 3). Then, they were introduced perceived price unfairness

and anger episode, variables that precipitate dissolution (Table 4).

On the other hand, and as is has been mentioned previously, to verify the

mediating effect of satisfaction a number of conditions must hold (Baron &

Kenny, 1986; Pritchard, Havitz, & Howard, 1999): (1) the antecedent

variables should have a significant effect on satisfaction; (2) satisfaction

should have a significant effect on switching intention (these first two conditions

are examined in Model 1); (3) the antecedent variables should

have a significant direct effect on switching intention (Model 2); and (4)

the previously significant effects of the antecedent variables on switching

intention should become nonsignificant when the path between satisfaction

and switching intention is opened (Model 3).


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Table 3 shows, for the three models, that although the chi-square statistic

is significantprobably a consequence of the sample sizethe values

of other indicatorsGFI, AGFI, CFI, and RMSEAare within recommended

limits, indicating a good fit. But it is Model 2, the direct-effects

model, which presents the worst goodness-of-fit indicators. The differences

between Models 1 and 3 are minimal, and the chi-square difference test is

non-significant. In spite of this, there is sufficient evidence to say that the

conditions are present for the existence of a clear mediating effect of satisfaction

in the case of the variables that predispose to dissolution (Baron &

Kenny, 1986). According to Model 1, the relation between satisfaction and

dissolution is significant, as are the effects of poor outcome quality and low

Table 2. Correlation Matrix.

Poor Poor Poor physical

Switching outcome interaction environment Low Price Anger

intention quality quality quality commitment unfairness incident Satisfaction

Switching intention 1.000

Poor outcome quality 0.408 1.000

Poor interaction quality 0.285 0.554 1.000

Poor physical environment 0.128 0.324 0.463 1.000

quality

Low commitment 0.344 0.495 0.522 0.353 1.000

Price unfairness 0.424 0.495 0.306 0.190 0.581 1.000

Anger incident 0.359 0.324 0.250 0.035 0.232 0.257 1.000

Satisfaction _0.470 _0.629 _0.490 _0.396 _0.568 _0.526 _0.397 1.000


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Cronbach alpha 0.725 0.855 0.858 0.765 0.832 0.895

Variance extracted 0.794 0.761 0.951 0.678 0.500 0.812



527

perceived commitment on satisfaction, too. The direct effects of poor outcome

quality and low perceived commitment on switching intention are significant

in Model 2, while they are no longer so in Model 3, where the relation

between satisfaction and dissolution is admitted.

Table 4 reports the results of the estimation of the three rival models after

introducing perceived price unfairness and anger incident, variables that

precipitate relationship termination. First, Model 1, the model reflecting

the mediating function of satisfaction, was tested. Looking at the results

of the estimation, it can be confirmed that apart from poor interaction

quality and price unfairness, the determinant factors of termination have

a significant effect on consumers global satisfaction, and in the expected

direction, while satisfaction itself has a negative and significant effect on

the intention to dissolve the relationship. The variables that predispose or

precipitate relationship termination act indirectly on dissolution through

satisfaction. It appears that the first conditions for satisfaction to exert a

mediating effect in the dissolution process are in general fulfilled.

Model 2 presents a significant chi-square statistic and some acceptable

goodness-of-fit indicators that are slightly better than those of Model 1.


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Table 3. Estimation of Rival Models: Predisposing Factors.

Relation (Path)

Model 1 Model 2 Model 3

Direct effects B t B t B t

Poor outcome quality _0.387 _4.900 _0.394 _5.030 _0.386 _4.884

Satisfaction

Poor interaction quality 0.014 0.155 0.034 0.378 0.015 0.170

Satisfaction

Poor physical environment _0.106 _1.712 _0.119 _1.685 _0.108 _1.737

qualitySatisfaction

Low commitment _0.444 _5.988 _0.465 _6.304 _0.443 _5.964

Satisfaction

SatisfactionSwitching _0.537 _8.744 _0.350 _3.195

intention

Poor outcome quality 0.336 3.104 0.192 1.681

Switching intention

Poor interaction quality _0.003 _0.022 0.050 0.416

Switching intention

Poor physical environment _0.103 _1.399 _0.157 _1.882

qualitySwitching intention

Low commitment 0.342 3.437 0.127 1.095

Switching intention

R2 Satisfaction 0.625 0.640 0.624

R2 Switching intention 0.288 0.314 0.329

Goodness of fit

_2 (df) 243.9 (143) (p_ 0.00) 243.7 (140) (p_ 0.00) 234.8 (139) (p_ 0.00)

GFI / AGFI 0.91 / 0.89 0.90 / 0.88 0.91 / 0.89


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RMSEA 0.050 (p_ 0.50) 0.055 (p_ 0.23) 0.051 (p = 0.45)

CFI / PNFI 0.98 / 0.89 0.98 / 0.87 0.98 / 0.87



528

Table 4. Estimation of Rival Models: Predisposing & Precipitating Factors.

Path

Model 1 Model 2 Model 3

Direct effects B t B t B t

Poor outcome quality _0.307 _3.702 _0.308 _3.729 _0.308 _3.704

Satisfaction

Poor interaction quality 0.028 0.309 0.027 0.294 0.030 0.326

Satisfaction

Poor physical environment _0.146 _2.434 _0.145 _2.427 _0.148 _2.473

qualitySatisfaction

Low commitment _0.388 _4.153 _0.388 _4.138 _0.388 _4.116

Satisfaction

Price unfairness _0.038 _0.498 _0.038 _0.487 _0.034 _0.442

Satisfaction

Anger incident _0.217 _4.510 _0.215 _4.469 _0.214 _4.439

Satisfaction

Satisfaction _0.539 _8.751 _0.323 _2.944

Switching intention

Poor outcome quality 0.132 1.171 0.009 0.075

Switching intention

Poor interaction quality 0.092 0.747 0.149 1.211

Switching intention


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Poor physical environment _0.057 _0.700 _0.106 _1.283

qualitySwitching

intention

Low commitment 0.064 0.526 _0.142 _1.015

Switching intention

Price unfairness 0.289 2.800 0.327 3.175

Switching intention

Anger incident 0.260 3.964 0.190 2.739

Switching intention

R2 Satisfaction 0.649 0.650 0.646

R2 Switching intention 0.291 0.372 0.403

Goodness of fit

_2 (df) 223.8 (141) (p_ 0.00) 203.9 (136) (p_ 0.00) 195.3 (135) (p_ 0.00)

GFI / AGFI 0.91 / 0.89 0.92 / 0.90 0.92 / 0.90

RMSEA 0.045 (p_ 0.74) 0.042 (p_ 0.83) 0.039 (p_ 0.90)

CFI / PNFI 0.98 / 0.88 0.98 / 0.85 0.99 / 0.85

Moreover, since the difference between the chi-square values of the two

models (_2(5) _ 19.9) is significant and Model 2s explanation of dissolution

is clearly superior, we must admit that the direct-effects model is

superior to the mediating-effect one. In this model the perceived deficiencies

in service quality and the low commitment do not have a significant

effect on switching intention, while unfair price and anger incident do.

Although poor service quality and low commitment do not appear to have

a direct impact on switching intention, the results obtained in the estimation

of the models for the case of the predisposing variables (Table 3)

show that the presence of unfair price and critical episode is the reason why


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none of the direct effects of perceived deficiencies in service quality and

low commitment on switching intention are significant. These results

seem to be in line with the idea that certain variables have a weak effect

on switching intentionwearing down consumers and predisposing them

to have a negative attitude towards the firmwhile others have a strong

effect on switching intentionprecipitating the decision to change suppliers.

In view of this, Hypothesis H1 is accepted.

Finally, Model 3 was compared with Model 1 and Model 2. Of the three

models, Model 3 presents the best goodness-of-fit indicators. As the differences

in the chi-square statistic are significant (_2(6) _ 28.5) and

(_2(1) _ 8.6), this is the model that best fits the data, and hence the one

that best represents the dissolution process. Model 3 is a mixed model,

combiningfor a more complete explanation of dissolutionthe direct

effects of the determinant variables with the mediating effect of satisfaction.

As Baron and Kenny (1986) propose, the mediating variable (satisfaction)

has a significant effect on the dependent variable (switching

intention), although unfair price and anger episode continue to have a significant

direct effect on switching intention.

In short, from the estimation of these three models, it can be concluded

that of the variables that precipitate dissolution, Baron and Kennys (1986)

conditions are fulfilledand consequently a mediating effect of satisfaction

existsonly for the variable anger incident: it has a direct and significant


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effect on satisfaction (Model 1) and on switching intention (Model 2), although

this latter remains when the relation between satisfaction and switching

intention is opened in Model 3. In the case of price, the only effect that this

variable exerts on switching intention is direct, since, as the test of Model 1

shows, it does not have a significant effect on global satisfaction.

If the estimations made in the two steps are considered together, there

is sufficient evidence to accept Hypothesis H2, except in the case of the

variable unfair price.With regard to the comparison between the variables

that predispose and precipitate relationship dissolution, it has been

shown in the results of the first estimation that for the variables that predispose

to dissolution (outcome quality and commitment) the mediating

effect of satisfaction is clear: All the conditions are fulfilled so that the

mediating effect cancels out the direct effect. In contrast, in the second

estimation, satisfaction does not moderate the effect of unfair price on

switching intention. The anger episode, in turn, affects the switching

intention through satisfaction (mediation), although it continues to have a

significant direct effect, too (the mediating effect does not cancel out the

direct effect). Hence Hypothesis H3 is also accepted, except for the case of

interaction quality and physical environment quality.

DISCUSSION

The present work has aimed to contribute to the study of switching

behavior by services customers. Although research on the topic of


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customer loyalty and retention has led to greater understanding about

firm-consumer relationships, it is also true that research on the dissolution

and termination of relationships has begun to create its own field



529

of study (Bansal & Taylor, 1999; Keaveney, 1995). In this stream, this

work has the aim of demonstrating that the termination process involves

the intervention of some variables that slowly weaken the relationship,

predisposing consumers to ending it, along with other variables that

induce them to switch suppliers immediately, precipitating termination.

The proposed model suggests that poor quality and the perception of

a weak commitment or lack of interest on the part of the firm towards

consumers are variables that predispose to relationship dissolution, insofar

as they progressively undermine consumers trust in the firm. The

empirical test of this model has demonstrated that the direct effect of

these variables on switching intention is not even significant, although

they do positively affect dissatisfaction. Along with these variables, it

has been shown that other factors act as immediate triggers of the switching

intention, namely a price policy perceived as being unfair and consumers

experience of a conflictive event or an episode that generates

their suspicion. Their effect on switching intention is strong and significant.

Thus, these are variables that precipitate the switching intention


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and predominate over any other motive of disenchantment the consumer

may have.

This dual effect (gradual and weak compared to immediate and strong)

on switching intention is confirmed when the mediating role of satisfaction

in the dissolution process is analyzed. In the study carried out here,

there is evidence that the variables that precipitate switching intention

(price and anger episode) have a direct effect on dissolution, and only

anger episode exerts an indirect effect through satisfaction, i.e., only in this

case does the mediating role of satisfaction seem to be confirmed. Unlike

Homburg, Hoyer, and Koschate (2005), who demonstrate the moderator

effect of satisfaction in the relation between price increases and switching

intention, the results appear to suggest that price unfairness has a

strong and direct effect that precipitates the intention to dissolve the relationship

and that satisfaction does not mediate in this relation. In contrast,

the variables that are regarded as predisposing factors of termination

have a weak direct effect on dissolution, and their effect is basically indirect

via the reduction in satisfaction levels. Indeed, one of the dimensions of

qualitythe interaction qualitydoes not appear to have any effect

either direct or indirecton customers switching intentions. Switching

suppliers is provoked by the perception that the outcomes of the service

or the physical means employed by the supplier are inadequate, regardless

of the treatment received. This result is analogous to that obtained


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by Bell, Auh, and Smalley (2005) in their explanation of customer loyalty.

These authors confirm that technical quality (the quality of the service output)

has a strong effect on loyalty, while functional quality (the interaction

between the service provider and customer and the process by which

the core service is delivered) exerts a much weaker effect.

In view of these conclusions, and with regards to the contribution of

this work to the marketing literature, it provides empirical evidence



530

about the switching process of services consumers, a phenomenon that

appears to be more complex than might first have been expected, and that is

in no way comparable to loyalty or customer retention. First, it has been

empirically demonstrated the existence of various determinants of switching:

on the one hand, variables that weaken the relationship and predispose

to dissolution, and on the other, variables that precipitate

dissolution. These categories have already been established in previous

theoretical work, although their differentiated effects have not been

tested until now. A second contribution refers to the role of satisfaction

as intermediate channel through which consumers manifest their unhappiness

prior to termination. The results advance the idea that the intention

to terminate the relationship is immediate when the firm takes

certain measures resulting in unfair pricing or a conflict with the customers,


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but other actions or failings in their performance, for example poor

service quality or low commitment to the customer, do not lead to an

immediate switch. Instead, these factors create dissatisfaction or unhappiness

that is the true cause of the termination in the end.

With regards to the management implications, it hardly needs saying

that the diagnosis of the motives behind consumers decisions to terminate

the relationship may serve as guidelines for companies wishing to avoid

customer defection. As Bansal and Taylor (1999) find, quality is not the

service attribute that most influences consumer intentions. In this line,

it has been shown that the perception of low quality levels and also of the

firms weak commitment undermines consumers satisfaction in the firm

and motivates, to a certain extent, their desire to switch suppliers, but

other factors have greater impact on consumers intentions: the perception

of an unfair price and the experience of critical episodes. This does

not mean that the former variables play no role in consumer intentions,

but rather that their effect is weakened in the presence of problems that

consumers regard as more important. Firms should strive to determine

the price range acceptable to their customers and to preventor resolve

as well as possibleany negative experiences that the consumers may

have with the firm. Continuing dissatisfaction with the firm on the part

of consumers as a consequence of a quality that does not match expectations

does not influence the individual as much as a one-off incident


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in which the consumer experiences strong unease and suspicion towards

the firm. Similarly a change in the price policy can lead consumers to

take the irreversible decision to switch suppliers. In short, companies

should make every effort to improve their customers perception of the

service, and above all ensure that they do not experience situations that

provoke irritation, unease, or extreme unhappiness.

To conclude, as limitations of the workandfuture lines of research,

firstly, it should be mentioned the analysis of the effect of switching

intention on actual consumer behavior. In this respect, past work such

as that of Bansal and Taylor (1999) has already suggested that intention

has a weak effect on real behavior. This leads the researchers to consider



531

the need to deepen the understanding of the variables that stop consumers

from ending their relationships and lead them to remain, even

when there is a switching intention. In this type of analysis it is useful

to have longitudinal data available, as they guarantee a more detailed

analysis of the process consumers follow towards dissolution. Another

limitation of the current work is that it considers the predisposing and

precipitating variables in the same time period. This prevents determining

the long-term effect of these factors, as well as the consumers tolerance

threshold to each of themtolerance of poor quality, of excessive


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prices, low commitment, or conflictive episodes. For this, it would be useful

to employ new methodologiesspecifically experimentation or the

study of critical incidents (Roos, 1999)that enhance understanding of

the causal effects of the different types of variable on switching intention.

Finally, another line of research continuing on from the current work

would be to analyze the role played by certain consumer or relationship

aspects in relationship termination. Specifically, variables such as consumers

experience and involvement or switching costs have been proposed

as moderators of the switching process. Other variables, such as

awareness of the alternatives, may well have a mixed effect: as direct

determinants of switching intention (an effect already demonstrated in

the literature), or as moderators between switching intention and actual

termination behavior.

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APPENDIX. Variable Measurement.

Variables Item Description Mean SD

Dependent

Switching intention SWI1 I have considered changing companies 2.05 1.33

SWI2 I have no intention to renew with this company 2.34 1.56

SWI3 I intend to insure my automobile with another company in the future 2.03 1.33

Independent

Outcome quality* QUA1 My company responds quickly to my needs 3.63 1.07

QUA2 When I have had a problem my company has responded efficiently 3.72 1.15

Interaction quality* QUA3 The attitude of this companys employees demonstrates their 3.58 1.06

willingness to help me

QUA4 The attitude of this companys employees demonstrates that they 3.35 1.05

understand my needs.

QUA5 This companys workers are very competent 3.38 0.98

Physical environment QUA6 The offices and branches of my company are modern and well-equipped 3.54 1.07

quality* QUA7 The offices of my company give an image of professionalism 3.42 1.06

Perceived commitment* COM1 The company maintains a frequent and constant relationship with me 2.37 1.16

COM2 The company gives me full and useful information about its products 2.83 1.24

COM3 I think the company is committed to me as a customer 2.87 1.12

COM4 I feel I get special benefits for being a good customer 2.62 1.24

COM5 The company is flexible in adapting its offer to my specific needs 2.68 1.07

Price* PRI1 The price I pay for the service I receive from the insurance company is fair 2.90 1.22

PRI2 The service I receive is good value for money 3.09 1.17

Anger incident INC1 I have recently had an experience with this company that angered me 2.14 1.30

Mediator

Satisfaction SAT1 Extent to which I am satisfied with this insurance company 2.22 1.04

(*) Recoded variables.


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