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A model of customer loyalty in

the retail banking marketAsuncion Beerli, Josefa D. Martn and Agustn QuintanaUniversity of Las Palmas de Gran Canaria,

Facultad Ciencias Economicas y Empresariales,Las Palmas de Gran Canaria, Canary Islands, Spain

Keywords Customer loyalty, Customer satisfaction, Costs, Quality

AbstractOn the basis of empirical research carried out in the retail banking market, this paperproposes a structural equations model enabling us to reach the conclusions that satisfactiontogether with personal switching costs are antecedents leading directly to customer loyalty, with the

former exerting the greatest influence; and perceived quality is a consequence of satisfaction. Atthe same time, the paper shows that the degree of elaboration in the bank selection process does nothave a moderating influence on the causal relationships between satisfaction/switching costs andcustomer loyalty.

IntroductionIn the highly competitive, complex and dynamic environment of the bankingindustry, the very slight differences which exist in financial services andproducts together with an increasingly demanding customer have led to a greattransformation in the industry. The traditional product-oriented bank isbecoming increasingly customer-oriented in accordance with the basic

principles of relational marketing, which focuses on customer loyalty as itsmain goal. In this sense, Gilmore (1997) considers that constantcustomer-oriented behaviour is a requisite for improving the implementationof quality in services marketing. Indeed, factors such as financial products anddistribution have attained similar levels of development and technology andhave thus been relegated to a secondary role as reference points fordistinguishing between one bank and another (Rodrguez Sanchez andRodrguez Parada, 1993). In this sense, Barnes and Howlett (1998) argue that,given that many financial services are parity offerings, it can be stated that acustomer is unlikely to be overly impressed by core product attributes when allcompanies are providing similar offerings.

The main objective of this paper is to identify the key factors that influencethe extent to which customers are loyal towards their banks. The customers ofmarket leaders in retail banking will form the subject of our research. To thisend, we have carried out empirical analyses of the complex interdependencerelationships that exist among the different variables, or factors, which explaincustomer loyalty in the retail banking market, using a methodology based onstructural equation models.

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A model ofcustomer loyalty

253

Received March 2001Revised July 2001,

January 2002

European Journal of Marketing

Vol. 38 No. 1/2, 2004

pp. 253-275

q Emerald Group Publishing Limited

0309-0566

DOI 10.1108/03090560410511221
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Prior to developing the model, we carried out a review of the most importantcontributions to academic literature about causal relationships between loyaltyand its antecedents. We reached the conclusion that customer satisfactiontogether with barriers or the switching costs were the key factors affectingloyalty. Similarly, there is a theoretical framework which considers thatperceived quality is one of the indirect antecedents of loyalty that has a directinfluence on customer satisfaction, although the nature of the causalrelationship between quality and customer satisfaction is the subject of greatacademic debate. While quality researchers claim that satisfaction is anantecedent of quality (Carman, 1990; Parasuraman et al., 1988; Bitner, 1990),researchers in the field of customer satisfaction have exactly the opposite pointof view (Woodside et al., 1989; Reidenbach and Sandifer-Smallwood, 1990;Cronin and Taylor, 1992; Fornell, 1992; Anderson and Sullivan, 1993). In thelight of this, several authors stress the desirability of further comparison of the

causal relationships between these two concepts, all of which has led us toexplore, as an additional objective of this paper, the direction of thisrelationship with new empirical evidence.

Finally, and with a view to examining more closely the relationships whichexist between customer loyalty and its antecedents, we decided to analyse thepossible influence on such relationships that the degree of elaboration in thebank selection process could have.

Theoretical backgroundThe increasing importance of relational marketing in recent years, particularly

in the servicing and manufacturing industries, has been accompanied by abundle of works on customer loyalty. Several authors emphasize the positiverelationship existing between customer loyalty and business performance(Reichheld and Sasser, 1990; Reichheld, 1993; Sheth and Parvatiyar, 1995).Loyal customers not only increase the value of the business, but they alsoenable it to maintain costs lower than those associated with attracting newcustomers (Barroso Castro and Martn Armario, 1999).

Generally, loyalty has been, and continues to be, defined as repeatpurchasing frequency or relative volume of same-brand purchasing. Manydefinitions in the literature suffer from the problem that they record what the

consumer does, and none taps into the psychological meaning of loyalty(Oliver, 1999).According to Jacoby and Kyner (1973), brand loyalty is the biased (i.e.

non-random) behavioural response (i.e. purchase), expressed over time, bysome decision-making unit, either on the part of an individual, family ororganization, with respect to one or more alternative brands out of a set of suchbrands, which means that it is necessary to distinguish between exclusivityand loyalty and a function of psychological processes which involves the

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evaluation of different alternatives using specific criteria. Similarly, Oliver(1999, p. 35) defines loyalty as:

. . . a deeply held commitment to rebuy or repatronize a preferred product/service consistently

in the future, thereby causing repetitive same-brand or same brand-set purchasing, despitesituational influences and marketing efforts having the potential to cause switching behavior.

Jacoby and Chestnut (1978) have explored the psychological meaning of loyaltyin an effort to distinguish it from behavioural (i.e. repeat purchase) definitions.Their analysis concludes that consistent purchasing as an indicator of loyaltycould be invalid because of happenstance buying or a preference forconvenience, and that inconsistent purchasing could mask loyalty if consumerswere multi-brand loyal.

Therefore, loyalty is a concept that goes beyond simple purchase repetitionbehaviour since it is a variable which basically consists of one dimensionrelated to behaviour and another related to attitude, where commitment is theessential feature (Day, 1969; Jacoby and Kyner, 1973; Berne, 1997). Accordingto Jacoby and Chestnut (1978), Solomon (1992) and Dick and Basu (1994), thecombination of these two components enables us to distinguish two types ofcustomer loyalty concepts:

(1) loyalty based on inertia, where a brand is bought out of habit merelybecause this takes less effort and the consumer will not hesitate to switchto another brand if there is some convenient reason to do so; and

(2) true brand loyalty, which is a form of repeat purchasing behaviourreflecting a conscious decision to continue buying the same brand, and itmust be accompanied by an underlying positive attitude and a high

degree of commitment toward the brand.

Inertia means the consumer is buying the same brand, not because of truebrand loyalty, but because it is not worth the time and trouble to search for analternative. A competitor who is trying to change a buying pattern based oninertia can often do so rather easily, because little resistance to brand switchingwill be encountered if some reason to do so is apparent (Solomon, 1992). On theother hand, under low involvement conditions brand loyalty may reflect onlythe convenience inherent in repetitive behaviour rather than commitment to thebrand purchased. Relatively uninvolved consumers are less likely to be brandloyal and will be more likely to be brand switchers (Traylor, 1981).

In relation to true brand loyalty, Oliver (1999), based on the traditionalconsumer attitude structure, considers that all three decision-making phasesmust point to a focal brand preference if true brand loyalty exists. Thus:

(1) the brand attribute ratings (beliefs) must be preferable to competitiveofferings;

(2) this information must coincide with an affective preference (attitude) forthe brand; and


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(3) the consumer must have a higher intention (conation) to buy the brandcompared with that for alternatives.

Compared to an inertia situation where the consumer passively accepts a

brand, a true brand loyal consumer is actively involved with his or herfavourite.

In the retail banking market, the length of relationship between bank andcustomer is a common feature. The tradition of the industry has been for banksand other financial services organisations to engage in long-term customerrelationships. In agreement with Stewart (1998), the reasons for suchrelationship longevity are open to interpretation. While genuine preference andloyalty may have been instrumental, so also could ignorance, inertia anddependence.

There has been a growing interest in recent years in analysing the factorsinfluencing customer loyalty. As a result, there are numerous works in

marketing which have attempted to explain the relationships between brandloyalty and the various variables regarded as antecedents, the most significantof which are customer satisfaction, and, to a lesser degree, switching costs(Bearden and Teel, 1983; LaBarbera and Mazursky, 1983; Kasper, 1988;Bloemer and Lemmink, 1992; Cronin and Taylor, 1992; Fornell, 1992; Olivaet al., 1992; Anderson and Sullivan, 1993; Bloemer and Kasper, 1993, 1995;Boulding et al., 1993; Berne, 1997; Oliver, 1999).

Customer satisfaction is a concept that has been widely debated in literatureand for which numerous definitions have been made, but researchers have yetto develop a consensual definition of this concept. In this sense, Oliver (1997, p.13) notes that everyone knows what [satisfaction] is until asked to give a

definition. Then it seems, nobody knows.Giese and Cote (2000) suggest in their literature review that consumer

satisfaction comprises three basic components:

(1) the type of response, that is to say, whether the response is cognitive,affective or conative, and its level of intensity, although those authorsconcluded from their validation, carried out by means of group andpersonal interview data, that satisfaction is a summary affectiveresponse which varies in intensity;

(2) the centre of interest or the subject on which the response is focused,which could be based on an evaluation of product-related standards,

product consumption experiences and/or purchase-related attributes(e.g. salesperson); and

(3) the moment in time at which the evaluation is made, which may bebefore choice, after choice, after consumption, after extended experience,or at just about any other time.

This theoretical framework enables us to develop specific definitions adaptedto the conditions of the context specific to each study, which are conceptually

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richer and more empirically useful than a generic definition, making it easier tointerpret and compare empirical results. Along these lines, Halstead et al. (1994)regard satisfaction as an affective response, focused on product performancecompared to some prepurchase standard during or after consumption. Manoand Oliver (1993) establish that satisfaction is an attitude or evaluative

judgement varying along the hedonic continuum focused on the product, whichis evaluated after consumption. Fornell (1992) identifies satisfaction as anoverall evaluation based on the total purchase and consumption experiencefocused on the perceived product or service performance compared withprepurchase expectations over time. Oliver (1997, 1999) regards satisfaction asa fulfilment response/judgment, focused on product or service, which isevaluated for one-time consumption or ongoing consumption.

A concept which is very closely related with satisfaction is perceivedquality, and the differences between these two have not always been very

clearly defined, both having been used on occasion in an indistinct manner. Inan attempt to clarify the distinction between satisfaction and perceived quality,Anderson et al. (1994) consider that satisfaction requires previous consumptionexperience and depends on price, whereas quality can be perceived withoutprevious consumption experience and does not normally depend on price,although in circumstances where there is little available information or wherequality evaluation is difficult, price can be an indicator of quality. In this sense,Spreng and Mackoy (1996), starting from Olivers (1997, 1999) conceptualmodel of service quality and service satisfaction, concluded that theseconstructs are distinct and have different antecedents.

On the other hand, there is a lack of consensus in literature and among

researchers about the causal link between the two constructs. While qualityservice literature claims that customer satisfaction is an antecedent ofperceived quality (Parasuraman et al., 1988; Bitner, 1990; Carman, 1990), otherauthors regard the relationship as being the other way round, in other words,perceived quality is considered an antecedent of customer satisfaction(Woodside et al., 1989; Reidenbach and Sandifer-Smallwood, 1990; Cronin andTaylor, 1992; Fornell, 1992; Anderson and Sullivan, 1993; Gotlieb et al., 1994;Spreng and Mackoy, 1996).

According to Parasuraman et al. (1994), this controversy derives from thetype of evaluation that is carried out in terms of quality and satisfaction, and it

is possible to distinguish between a transaction-specific evaluation and anoverall evaluation as the result of cumulative experience. While service qualityresearchers start from the premise that satisfaction is a transaction-specificevaluation and that quality is an overall evaluation made using a whole set ofcumulative evaluations, researchers focusing on the satisfaction topic tend tohave quite the opposite point of view. Parasuraman et al. (1994), following upthe work of Teas (1993), consider that service quality and satisfaction can beexamined from both transaction-specific as well as global perspectives and


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they suggest that an interesting direction for further research is to analyse thecausal links of these two constructs from both perspectives. Nevertheless, froma theoretical point of view these authors establish that perceived quality is an

antecedent of satisfaction when both constructs are measured in the context ofa transaction-specific perspective.Another brand loyalty antecedent is known as switching costs, which can be

defined as the technical, financial or psychological factors which make itdifficult or expensive for a customer to change brand (Selnes, 1993). Accordingto Alet i Vilagines (1994), the switching costs can be broken down as follows:

. the customers personal costs, referring to tradition and the clients habits,to effort in terms of the time and commitment needed to evaluate newalternatives, to the economic advantages associated with loyalty, to thesocial and psychological risks stemming from making a wrong choice,and to the established contracts with the supplier company; and

. costs associated with the product, such as the costs of redesigning theprocess of production or consumption, investment in relatedequipment, and contractual costs.

When the costs of switching brand are high for the customer, there is a greaterprobability that the customer will remain loyal in terms of repeat purchasebehaviour, because of the risk or expense involved in switching and because ofthe accompanying decrease in the appeal of other alternatives (Wernerfelt,1991; Selnes, 1993; Klemperer, 1995; Ruyter et al., 1996; Anton Martn et al.,1998). However, if loyalty is defined as true loyalty, the relationship between

this construct and the switching costs is not so simple. For example, it mighteasily be that the customer repurchases, but due to his dissatisfaction, he doesnot recommend the product or service to others. Moreover, the effect ofswitching costs on loyalty varies with the type of industry, the category of theproduct and the characteristics of the customer (Fornell, 1992). In the bankingindustry, Sheth and Parvatiyar (1995) found some factors that may inhibitcustomer exit in retail banking; for instance, the length of their relationshipswith the bank; the fact that they knew, and were known by, the branch staff;and the perception that closing/transferring accounts was difficult. Thesefactors, whether real or perceived, act as exit barriers.

Wernerfelt (1991), Selnes (1993) and Klemperer (1995) consider that brandloyalty increases considerably when switching costs and customer satisfactionconverge, although a competitor will find it more difficult to capture a customerof a rival brand when the customers loyalty is based on satisfaction than whenit is based on switching costs. Along these lines, Fornell (1992) establishes twodisadvantages of switching costs that highlight the greater relative weight ofsatisfaction as an antecedent of customer loyalty. These disadvantages are,first, the greater difficulty of capturing new customers when these are

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conscious of the existence of switching costs, and, second, the possibility thatexternal forces can eliminate switching barriers.

Consistent with Anton Martn et al. (1998), in the relationship existingbetween customer satisfaction/perceived switching costs and loyalty, thedegree of elaboration which is followed in the decision-making process canhave a moderating influence. Elaboration is a construct based on theinformation processing theory (Petty and Cacioppo, 1997) and is determined bythe motivation and the ability of a consumer to elaborate on the brand choice(Bloemer and Ruyter, 1998). Motivation can be operationalised by bank choiceinvolvement and ability can be operationalised by bank choice deliberation.Despite the fact that motivation and the ability of a consumer to elaborate onthe choice can be high, if the consumer does not perceive differences amongbrands, the degree of elaboration in the decision-making process may be low.Therefore, to measure elaboration we have also included the dimension related

to the perceived distinction between different brands.Moreover, when the levels of satisfaction and switching costs are equal invalue, consumers that take a longer time to make a decision tend to be moreloyal to the brand chosen because the decision-making process is moreconscious and deliberate. However, this moderating influence can vary withrespect to product categories. Thus, for example, in the work carried out byAnton Martn et al. (1998), after analysing the moderating influence of thedegree of elaboration in the relationship between satisfaction/switching costsand loyalty for three categories of products, they were only able to identify asignificant moderating influence in one of the product categories analysed.Moreover, in the paper on store loyalty by Bloemer and Ruyter (1998), they

concluded that the customer who elaborates more on department storeshopping might take more stores into consideration. This might lead to lessloyalty in the case of a stronger motivation and ability to evaluate a store.Nevertheless, when combined with the amount of satisfaction and as amoderator variable, elaboration strengthens the positive effect of storesatisfaction on store loyalty.

Research designObjectivesThis paper has three objectives related to customer loyalty in the retail banking

market. First, using a structural equation model, we analyse empiricallywhether customer satisfaction and perceived switching costs are antecedents ofcustomer loyalty toward different retail banks. Second, we explore the causaldirection between perceived quality and satisfaction, in order to establishwhether perceived quality is an indirect antecedent of customer loyalty, aconsequence of satisfaction or whether there exists a bidirectional relationshipbetween perceived quality and satisfaction. With this second objective, wewant to add new empirical evidence on the causal relationship between


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perceived quality and satisfaction, with the object of shedding some light onthe subject. Finally, we study the moderating influence that the degree ofelaboration might exert on the causal relationships between loyalty and theaforementioned antecedents.

More specifically, the above-mentioned objectives and the hypothesesderiving from the same are as follows.

Objective 1. To analyse whether satisfaction and switching costs areantecedents of customer loyalty in the retail banking market.

H1.1. The greater the satisfaction, the greater the customer loyalty.

H1.2. The greater the perceived switching costs, the greater the customerloyalty.

Objective 2. To explore the causal direction between perceived quality andsatisfaction.

H2.1. The greater the perceived quality, the greater the customersatisfaction.

H2.2. The greater the customer satisfaction, the greater the perceivedquality.

H2.3. There exists a bidirectional relationship between perceivedsatisfaction and customer satisfaction.

Objective 3. To study the moderating influence that the degree of elaborationcan have on the causal relationships between customer satisfaction/perceivedswitching costs and loyalty.

H3.1. The greater the degree of elaboration, the greater the positive impactof satisfaction on loyalty.

H3.2. The greater the degree of elaboration, the greater the positive impactof perceived switching costs on loyalty.

MethodologyData were gathered from personal interviews using a structured questionnaire.The customers of the six banks with the largest market share, in thegeographical zone in which this study was carried out, were selected as the

target population. These are Banco Bilbao-Vizcaya, Banco Central-Hispano,Banesto, Banco de Santander, Caja de Canarias and La Caixa. The main reasonfor selecting the clients of those banks is that those six banks have 71.68 percent of all the bank branches in the geographical region of the study, accordingto the data of the Internal Report of the Caja de Canarias (2001). None of thebanks whose clients are not included in the sample has more than 2 per cent ofthe total number of bank branches. The final sample consists of 576 individualswho stated that they were habitual customers of one of the aforementioned

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banks. Those clients were selected according to age, education and occupation,which were all proportional to the actual population of the region. Thesampling error was ^4:16 per cent at the 95.5 per cent level. The interviewswere carried out in situ, at the main door of the branches. We carried out thesame number of surveys for each of the banks in order to be able to obtain anacceptable sample size of the clients of each bank.

The items of the scales and its reliabilities measured with Cronbachs alphaare reported in Table I.

Loyalty was measured indirectly by means of an attitude scale, which, asBerne (1997) points out, is the most commonly used system of measurement dueto the difficulty involved in obtaining sequential information about purchaserepetition. To do this we used a seven-point, three-item Likert scale, whichmeasures resistance to switching bank, individuals loyalty attitude and thedegree to which they would recommend the bank that they use. These variables

measure the degree of commitment toward the bank and intention to continuewith the relationship. Therefore, following the properties of true brand loyaltyestablished by Oliver (1999), the first item attempts to inversely measure theintention to continue the relationship with the present bank (conation), and theother two items measure affective preference for the bank (attitude). We have notevaluated the brand attribute rating (beliefs) because of problems caused by thelength of the questionnaire and because an in-depth study of the clients beliefswas not the main objective of this work. However, attitudes are a directconsequence of beliefs, and so, when measuring the affective component, we are,albeit indirectly, considering the cognitive component of loyalty.

In order to evaluate customer satisfaction with their bank we followed

Fornell (1992) and used a seven-point, three-item Likert scale which measuresgeneral satisfaction with the banking entity, the degree to which the bankconfirms customers expectations, and the gap which customers consider toexist between the bank they use and what they regard as being the perfect orideal bank. We have used Fornells (1992) scale because it incorporates thethree aspects of satisfaction most widely used in the literature. In this way, andin line with the basic components of satisfaction established by Giese and Cote(2000), the scale used complies with the following characteristics:

. the type of response is affective;

. the centre of interest is based on an evaluation of bank consumption

experiences; and. the moment of evaluation is after extended experience.

Perceived quality was measured based on an overall evaluation as the result ofcumulative experience of the customer, using a 20-item SERVPERF scaleadapted to the banking industry. Although this scale has a high number ofitems, we have not reduced it because we consider that it was important tomaintain the original SERVPERF scale. This scale has five components


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Loyalty Alpha = 0.7829L1 I do not like to change to another bank because I value the selected bankL2 I am a customer loyal to my bank

L3 I would always recommend my bank to someone who seeks my adviceSatisfaction Alpha = 0.8106S1 To what extent does this bank live up to your general expectations of it?S2 Imagine the perfect bank. How far and/or close does this bank come to your ideal?S3 Given your experience with this bank, how satisfied or dissatisfied are you with it

overall?

Quality Alpha = 0.9373Q1 Xs physical facilities are attractive and comfortableQ2 X has modern-looking equipmentQ3 Xs employees are tidy in appearanceQ4 Materials associated with the service are visually appealing at XQ5 X insists on error-free records

Q6 When you have a problem, X shows a sincere interest in solving itQ7 Employees of X solve your problems when they promise to do soQ8 X provides its services at the time it promises to do soQ9 X performs the service right the first timeQ10 Employees of X give you prompt serviceQ11 Employees of X are always willing to help youQ12 Employees of X are never too busy to respond to your requestsQ13 Employees of X tell you exactly when services will be performedQ14 The behaviour of employees of X instills confidence in customersQ15 Employees of X are constantly courteous to youQ16 Employees of X have the knowledge to answer your questionsQ17 X gives you individual and personal attentionQ18 X has operating hours convenient to all its customers

Q19 X has your best interests at heartQ20 Employees of X understand your specific needs

Switching costs Alpha = 0.8039SC1 To change to another bank involves investing time in searching for information about

other banksSC2 To change to another bank involves much effort in deciding which other bank to useSC3 To change to another bank involves a risk in choosing another bank which might turn

out not to satisfy me

Degree of elaboration in the bank selection processDegree of deliberationDEL 1 When I selected my bank, I made a previous comparison with other bank entities

DEL 2 When I selected my bank, I did a previous analysis of the advantages and disadvantagesof the chosen bank in comparison with other bank entities

Degree of involvementI1 The first time that I chose a bank, it was a very important decision for me

Degree of differentiation between bank entitiesDIF 1 I think there are significant differences between different banks

Note: X denotes the name of the main bank

Table I.Scales and reliabilitycoefficients

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(tangibles, reliability, responsiveness, assurance and empathy) and wasadopted since it is still the most widely used instrument, having beendeveloped from data collected across five separate service categories, one ofwhich was retail banking. Furthermore, some studies show that this scale is agood interpretation of perceived quality in retail banking (Llorens Montes,1996; Yavas et al., 1997; Bloemer et al., 1998. In accordance with the codes of thevariables which can be seen in Table I, tangibles correspond with labels Q1 toQ4, reliability with labels Q5 to Q9, responsiveness with labels Q10 to Q13,assurance with labels Q14 to Q16, and finally, empathy with labels Q17 to Q20.After carrying out an exploratory factorial analysis of this scale, we were ableto isolate three factors, which represent 59.4 per cent of explained variance. Thefirst of these factors accounts for some 47.8 per cent of the variance and coversthe dimensions of reliability, responsiveness and assurance with the bankingentity; the second factor explains 6.6 per cent of the variance and deals with the

dimension related to empathy; and finally, the third factor accounts for 5 percent of the variance and represents the tangibles of the banking entities. Thedifferences which exist between the theoretical dimensions of the scale andthose obtained in our research could be due to the fact that the dimensionalityof the service quality scale varies from industry to industry (Babakus andBoller, 1992). Along these lines, Carman (1990) and Buttle (1995) identified anumber of dimensions that differ from the five included in the SERVPERFscale. As the number of dimensions of this scale does not coincide with thetheoretical dimensions, and the percentage of explained variance is relativelyreduced, we opt to use all the items of the SERVPERF scale in our structuralequations model.

With respect to switching costs, and using the typology proposed by Alet iVilagines (1994), we have included the personal switching costs that are mostdirectly related to the industry that is the subject of our research. We have thusused a seven-point, three-item Likert scale to evaluate the time required tosearch for information about other banks, the effort involved in deciding onanother bank and the risk of making a mistake with the switch.

Finally, in order to measure the degree of elaboration in the bank selectionprocess, we used three seven-point Likert sub-scales in accordance with AntonMartn (1998) to measure the following three dimensions:

(1) the degree of deliberation in the bank selection process;

(2) the degree of involvement in the choice of bank; and

(3) the degree of differentiation which exists between the different bankentities.

Results and discussionIn order to analyse the antecedents of customer loyalty in the retail bankingmarket and to explore the direction which exists in the relationship betweenperceived quality and customer satisfaction we have applied the structural


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equations model, first because it enables us to estimate the multiple and crossedrelationships which exist between dependent and independent variables, andsecond, for its capacity to represent constructs not observed in these relationshipsand to take into account measurement error in the estimation process.

Before specifying the structural equations model we tested out the reliability ofthe scales to be used by means of the Cronbachs alpha, as can be seen in Table I.The coefficients obtained demonstrate that the indicators used to measure thedifferent constructs are reliable since their values oscillate between 0.7829 and0.9373. The high Cronbachs alpha for the SERVPERF scale is influenced by thehigh number of scale items; however, the SERVPERF scale has been extensivelyapplied in numerous studies because of its good psychometric properties.

With the aid of the literature review, we have proposed a causal model usingthe software AMOS 3.6 in which we propose that customer satisfaction andswitching costs are antecedents of customer loyalty and that there exists a

bidirectional relationship between customer satisfaction and perceived quality.We used a correlation matrix, shown in the Appendix, as the starting point,since because it is a standardised variance-covariance matrix it enables us tomake direct comparisons of regression coefficients between the variablesincluded in the model. While many researchers propose a two-stage structuralmodelling process in which the measurement and structural models are keptseparate, in our study, and in the line of Hair et al. (1990), we will make asimultaneous estimation of the measurement and structural models based onthe strength of extensive theoretical support which exists for the use of such amodel and on the high degree of reliability of the measurements used.

Figure 1 displays the resulting causal model with its standardised regression

coefficients, together with the global fit measures for the model which are usedto verify the quality of the fit via the correspondence between the observedcorrelation matrix and that which is reproduced using the proposed model. Asmeasurements of fit we obtained a chi-square value of 414.814 with 375 degreesof freedom (p 0:076). This value was obtained for a sample of 170 individuals,bearing in mind that the recommended sample size for obtaining a validcontrast with the chi-square statistic using the maximum likelihood criterion is100-200. This is because, when the sample size is increased above this limit, themaximum likelihood criterion becomes increasingly sensitive, while the fit ofthe model is adversely affected (Hair et al., 1999). In fact, the values of the

remaining measures of the global fit of the model are exactly the same for asample size of 576 as for one of 170, with the exception of the standardisedchi-square (CMIN/DF), which obviously increases in value when the sample sizeis increased, and the Tucker-Lewis Index (TLI), which changes from 0.982 to0.879 when the sample size is increased to 576. In our model the values obtainedfor the goodness of fit index (GFI 0:849) and the root mean square residual(RMR 0:068) indicate a good absolute fit of the model. Regarding theincremental fit measurements, which compare the proposed model with the

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independence model, we obtained values close to, or superior t,o the 0.9 valuegenerally considered acceptable. Finally, the values of the last twomeasurements, AGFI 0:825 and CMIN=DF 1:106, indicate that the modelis parsimonious, since the value of the first is close to 0.9 while the second fallsin the recommended interval between 1 and 2.

Once the global fit has been accepted, we can proceed to evaluate separatelyeach of the latent variables, analysing their convergent validity by evaluating

the weights of the indicators and their reliability and variance. Thus, inaccordance with Anderson and Gerbing (1988), we assume that convergentvalidity exists when the regression weights of a constructs measurements arestatistically significant, in other words, when the critical ratio (CR) of thevariables observed against their respective latent variables is over 1.96 at the0.05 level. In our case, as can be observed from the data displayed in Table II,all the critical ratios of the indicators of constructs satisfy this criterion, and theconvergent validity of the measurements can thus be demonstrated, the

Figure 1.

Regression model(standardised values)


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proposed relationships between indicators and constructs having been verified.

With regard to reliability and variance, the data displayed in Table III

demonstrate that the different indicators are sufficient in the representation of

the constructs, since the reliability values exceed the recommended values of0.70 and the variances are superior to or close to the 0.5 level.

Starting from the premise that the goodness of fit is high (R2 72:7 percent), we will proceed to analyse the hypotheses related to the first two

objectives of this study.

First, and with respect to loyalty antecedents, the relationships between

satisfaction/switching costs and loyalty display positive and statistically

Regression weights EstimatesStandarddeviation

Criticalratio (CR)

Standardisedestimates

Loyalty

Switching 0.145 0.052 2.800 0.182Loyalty Satisfaction 0.765 0.079 9.695 0.833Satisfaction Quality 0.239 0.542 0.441 0.231Quality Satisfaction 0.615 0.317 1.938 0.635SC1 Switching 0.849 0.072 11.762 0.823SC2 Switching 1.000 0.949S3 Satisfaction 1.000 0.866S1 Satisfaction 0.913 0.078 11.742 0.791L3 Loyalty 1.000 0.807L2 Loyalty 0.804 0.099 8.122 0.645Q6 Quality 0.908 0.077 11.804 0.761Q7 Quality 0.992 0.073 13.547 0.831Q8 Quality 0.858 0.079 10.869 0.719

Q11

Quality 1.000 0.838Q12 Quality 0.927 0.076 12.182 0.777Q13 Quality 0.810 0.081 10.039 0.679Q14 Quality 0.960 0.075 12.868 0.805Q15 Quality 0.914 0.077 11.915 0.766Q16 Quality 0.898 0.077 11.619 0.753Q10 Quality 0.941 0.076 12.464 0.789SC3 Switching 0.565 0.074 7.582 0.557L1 Loyalty 0.914 0.098 9.310 0.735S2 Satisfaction 0.724 0.084 8.645 0.627Q5 Quality 0.574 0.087 6.566 0.482Q1 Quality 0.475 0.090 5.308 0.398Q4 Quality 0.589 0.087 6.764 0.494

Q3

Quality 0.690 0.084 8.169 0.579Q9 Quality 0.810 0.081 10.047 0.679Q18 Quality 0.588 0.087 6.753 0.493Q19 Quality 0.729 0.083 8.748 0.611Q2 Quality 0.390 0.091 4.287 0.327Q20 Quality 0.767 0.082 9.339 0.643Q17 Quality 0.803 0.081 9.919 0.673

Note: Squared multiple correlation (R2) = 72.7 per cent

Table II.Results of regressionmodel

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significant regression coefficients. Satisfaction has a greater weight on loyaltythan switching costs (0.833 and 0.182 respectively), which leads us to accept

H1.1 and H1.2.Second, in order to test out the hypotheses related to the direction of the

relationship between perceived quality and customer satisfaction, we mustpreviously verify the stability of the non-recursive model between these twolatent variables. In this way, we obtained a stability index of 0.147 which, beinglower than 1, indicates that the regression coefficients are stable. The datadisplayed in Table II show that there exists a positive and statisticallysignificant relationship within the satisfaction-perceived quality relationship,thus verifying H2.2. The perceived quality-satisfaction relationship, althoughpositive, is not statistically significant, meaning that H2.1 and H2.2cannot beverified. These results, which are in contrast to the suggestions of Woodsideet al. (1989), Reidenbach and Sandifer-Smallwood (1990), Cronin and Taylor

(1992), Fornell (1992) and Anderson and Sullivan (1993), indicate that whenperceived quality and satisfaction are measured in a global perspective,satisfaction is an antecedent of perceived quality and not vice versa, as hasbeen proposed by Carman (1990), Parasuraman et al. (1988) and Bitner (1990).

In order to address our third objective, which was to analyse the moderatinginfluence which the degree of elaboration in the bank selection process has onthe relationships between loyalty and customer satisfaction/switching costs,we carried out a multiple regression analysis using the following equation

L a bSAT cSC dCLUS eCLUS SAT fCLUS SC

where:

L = Customer loyalty

SAT = Customer satisfaction

SC = Switching costs

CLUS = variable dummy which defines belonging either to the group ofcustomers with a high degree of elaboration in the decision-making(1) or to the low level group (0).

In order to classify the customers into two categories according to the degree ofelaboration of their decision making, we applied a K-means cluster analysis to

the four variables that make up the scale used. The results can be observed in

Latent variables Reliability of the constructs Variance of the constructs

Perceived quality 0.940 0.450Satisfaction 0.809 0.589Switching costs 0.824 0.619Loyalty 0.778 0.541

Table III.Reliability of latent

variables


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Table IV. The 288 individuals who make up Cluster 1 display a greater degreeof elaboration in the decision-making process than the 287 individuals whomake up Cluster 2. Similarly, an ANOVA demonstrates that there aresignificant differences between the two groups for each of the variables used inthe division process (p # 0:001). From the cluster, we have created dummyvariable CLUS, which has a value of 1 when individuals show a high degree ofelaboration and a value of 0 when the degree of elaboration is low.

The results of the multiple regression, which are displayed in Table V,indicate that the degree of elaboration does not have a moderating influence onthe relationships between satisfaction/switching costs and loyalty, which leadsus to reject H3.1 and H3.2. One possible explanation for these results could bederived from the industry which we chose as the subject for this research, sincethe intangible nature of banking services could have a conditioning effect on thedegree of elaboration in the bank selection process. We could therefore state that

deliberation in bank selection and the perception of differences between rivalentities are far more complex processes than for other categories of products.

ConclusionsThe aim of this research, which is based on the retail banking market, was tocarry out an empirical analysis of the factors determining customer loyalty,using a structural equation modeling. We have tried to contribute to theacademic literature by considering customer loyalty not only as a frequency ofrepeated purchase, but also including the psychological meaning of loyalty. Inthis sense, we have differentiated between the two types of concept of customerloyalty (loyalty based on inertia and true brand loyalty). Moreover, along theselines, we analysed the influence on customer loyalty, not only of satisfaction,which is the most widely studied factor in academic literature, but also of the

Cluster DIF1 I1 DEL1 DEL2 n

Cluster 1 3.715 4.535 5.576 5.670 288Cluster 2 3.199 3.014 2.056 2.216 287

Table IV.Size and profiles of theclusters

Independence variables Betas Standard deviations Standardised betas t-value p-value

SAT 0.762 0.054 0.594 14.065 0.000SC 0.164 0.046 0.156 3.557 0.000CLUS 20.591 0.486 20.181 21.216 0.224CLUS*SAT 0.030 0.085 0.047 0.355 0.723CLUS*SC 0.084 0.068 0.135 1.239 0.216Constant 0.156 0.297 0.525 0.599

Notes: F 86.75 (p 0.000); Squared multiple Correlation R2 43:47 per cent

Table V.Results of multipleregression

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switching costs, which are most directly related to the banking industry.Similarly, and taking into account the great controversy which exists aboutwhether perceived quality is an antecedent exerting an indirect influence onloyalty and a direct influence on satisfaction, or whether, to the contrary, it is aconsequence of satisfaction, we have attempted to explain the causal directionof the relationship existing between perceived quality and satisfaction.

The results of the proposed model, whose validity has been demonstrated bythe relatively acceptable levels of the indicators of the absolute, incrementaland parsimony fits and by its high explanatory value, demonstrate that bothsatisfaction and switching costs can be regarded as loyalty antecedents.Nevertheless, the influence exerted by satisfaction is far greater than that ofswitching costs.

With respect to the direction of the relationship between satisfaction andperceived quality, our model demonstrates that there is only a positive and

statistically significant relationship in this link. Thus, when these two constructsare measured in a global perspective, satisfaction is an antecedent of perceivedquality in the retail banking market, and not vice versa. A possible theoreticalexplanation of this result is that the satisfaction construct supposes an evaluative

judgement of the value received by the customer. Perhaps a customer perceives ahigh level of quality and is not satisfied because of the economic sacrifice madeto obtain the service. Moreover, a high level of perceived quality may notimplicate a high level of satisfaction if the quality does not meet customer needs.Furthermore, if a customer is satisfied, he will tend to value the perceived qualitymore positively in order to be congruent with himself and to avoid dissonance.

In this study, we also explored the possible moderating influence which the

degree of elaboration in the bank selection process could exert on therelationship between customer loyalty and its antecedents, using a multipleregression analysis, and we reached the conclusion that, in the retail bankingmarket, the degree of elaboration does not exert any moderating influence.

Limitations and managerial implicationsThe results of this research are limited to and conditioned by the context in whichthe empirical work was carried out, and we would therefore recommend futureresearch to study not only the direct influence of satisfaction and switching costson loyalty, but also the relationship between perceived quality and satisfaction at

both the global and specific perspectives in other industries and for othercategories of products. In the same way, an interesting line of enquiry would be toreplicate the research across the corporate sector of the banking industry.Similarly, we would recommend studying other possible antecedents which couldhave an influence on bank customer loyalty, for example, some of the dimensionswhich constitute brand equity, such as brand image, reputation and awareness; aswell as the market orientation strategy implemented by the bank entities. Suchfactors are important to the process of adding value to service offerings and, hence,


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achieving competitive advantage in retail financial services markets (Devlin, 2000).Gardener et al. (1999) argue that, in the new financial environment, there is also agreater focus on banks achieving added value and improving their public image.Issues relating to the elements of the offering that should be emphasised whenadding value may be particularly important in the case of services. For offeringswhich are highly intangible, either mentally, or cognitively, as well as physically,options for adding value, and hence, achieving competitive advantage, may belimited due to customer reliance on experience and credence qualities during thepurchase decision. Financial services are arguably highly typical of serviceofferings in general, with more complicated financial services in particular beinghighly intangible as well as problematic in terms of consumer cognition (Devlin,2000). According to Nguyen and LeBlanc (1998), in financial services, futureresearch might consider a better knowledge of how customer satisfaction, servicequality, and value interact to influence image assessments and loyalty, which

promises to provide useful insights for formulating competitive strategy.Finally, we would draw attention to the possibility of carrying out furtherresearch to analyse the effect of other possible moderating variables in therelationship between loyalty and its antecedents, such as, for example, thepsycho-demographic characteristics of individuals like the degree of financialknowledge on the part of customers in the retail banking market.

Our findings have several managerial implications. The impact ofsatisfaction on loyalty is considerably stronger than the cost of switching.This implies that banks should place greater emphasis on achieving high levelsof customer satisfaction than on creating switching barriers. This is because,on the one hand, loyalty is based mainly on satisfaction, and on the other,

switching costs present the additional disadvantage of the difficulty ofattracting new customers when these are aware of the existence of such costs,and the possibility that outside forces may eliminate the barriers erected byswitching costs. Nevertheless, the direct positive relationship betweenswitching costs and loyalty may imply that banks could undertake actionsthat increase switching costs for their customers, such as establishing preferredcustomer programmes, which can also contribute to increasing customersatisfaction. In this sense, Barnes and Howlett (1998) argue that the loyaltyprogrammes would be customer-focused and the companies would examine:

. the manner in which the customer defines a relationship;

.

whether the conditions under which the company interacts withcustomers are conducive to forming relationships; and

. the factors which contribute most to quality relationships.

On the other hand, while there may not be a direct relationship between overallservice quality and satisfaction response, the banks should not overlook theimportance of quality, whenever the quality improvement efforts are orientedto meet the customers needs.

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0.3

714

0.2

90

6

0.4

084

0.0

475

0.0

767

0.1

172

0.3

545

0.2

796

0.3

012

0.2

154

0.3

815

0.3

809

0.2

823

0.5

145

0.3

601

0.2

991

0.2

61

0

0.3

782

0.0

719

0.1

295

0.0

566

0.2

942

0.2

239

0.2

951

0.1

848

0.2

509

0.2

517

0.2

537

0.3

519

0.5

194

0.3

969

0.2

93

5

0.4

932

0.0

916

0.1

556

0.1

297

0.4

179

0.3

083

0.2

085

0.2

119

0.3

426

0.3

508

0.3

250

0.4

526

0.4

826

0.4

333

0.3

46

2

0.4

323

0.1

205

0.1

235

0.0

901

0.4

253

0.3

450

0.1

769

0.2

090

0.3

256

0.2

933

0.2

708

0.5

076

(co

ntinued)

Table AI.Correlation matrix

EJM38,1/2

274


23/23

Table AI.1.0

000

0.6

396

1.0

000

0.5

672

0.6

316

1.0

000

0.6

336

0.5

209

0.5

222

1.0

000

0.7

145

0.5

951

0.5

552

0.7

291

1.0

000

0.6

295

0.5

691

0.5

003

0.7

171

0.7

091

1.0

000

0.5

249

0.5

427

0.4

657

0.5

664

0.5

634

0.5

598

1.0000

0.6

486

0.5

390

0.5

007

0.6

381

0.6

921

0.6

194

0.5257

1.0

000

0.6

349

0.4

891

0.4

577

0.6

174

0.6

960

0.6

145

0.4730

0.7

181

1.0

000

0.6

110

0.5

349

0.5

295

0.5

369

0.5

979

0.5

386

0.5048

0.6

552

0.6

294

1.0

000

0.5

431

0.4

409

0.4

392

0.5

205

0.5

540

0.4

823

0.4963

0.5

591

0.4

926

0.5

560

1.0

000

0.3

677

0.3

338

0.3

295

0.3

970

0.3

568

0.3

765

0.3577

0.3

775

0.3

387

0.4

084

0.3

778

1.0

000

0.4

842

0.4

096

0.4

072

0.4

519

0.4

367

0.4

349

0.4809

0.4

562

0.3

978

0.4

837

0.4

886

0.4

684

1.0

000

0.5

022

0.4

291

0.4

130

0.5

034

0.5

246

0.4

996

0.5199

0.4

974

0.4

508

0.4

776

0.4

421

0.3

736

0.5

730

1.0

000


275

a_model of customer loyalty

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