bank service quality

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Journal of Retailing and Consumer Services 12 (2005) 373–383

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Measuring service quality of banks: Scale development and validation

Osman M. Karatepea,�, Ugur Yavasb, Emin Babakusc

aSchool of Tourism and Hospitality Management, Eastern Mediterranean University, Gazimagusa, Turkish Republic of Northern Cyprus,

Via Mersin 10, TurkeybDepartment of Management and Marketing, College of Business, East Tennessee State University, Johnson, TN 36714, USA

cDepartment of Marketing and Supply Chain Management, Fogelman College of Business and Economics, The University of Memphis,

Memphis, TN 38152, USA

Abstract

By employing a multi-stage, multi-phase, and multi-sample approach, this paper reports on the construction of a service quality

scale. Customer perceptions of service quality of retail banks in Northern Cyprus serve as the study setting. The parsimonious 20-

item four-dimensional scale consisting of service environment (four items), interaction quality (seven items), empathy (five items),

and reliability (four items) exhibits sound psychometric properties. Scale development procedures and managerial applications of

the derived scale are discussed.

r 2005 Elsevier Ltd. All rights reserved.

Keywords: Service quality; Banking; Scale development; Northern Cyprus

1. Introduction

A deliberate attempt to study services marketing andservice quality issues dates back to the mid-1960s(Rathmell, 1966). However, interest on the topic hasgained considerable momentum within the past twodecades or so. This is not surprising. On the one hand,delivery of high service quality to customers offers firmsan opportunity to differentiate themselves in competi-tive markets. On the other hand, high service qualityresults in customer satisfaction and loyalty, greaterwillingness to recommend to someone else, reduction incustomer complaints, and improved customer retentionrates (see, for example, Bitner, 1990; Danaher, 1997;Headley and Miller, 1993; Levesque and McDougall,1996; Magi and Julander, 1996; Zeithaml et al., 1996).Today, service quality is considered a critical measure of

e front matter r 2005 Elsevier Ltd. All rights reserved.

tconser.2005.01.001

ing author. Tel.: +90392 630 1116;

5 1584.

esses: [email protected] (O.M. Karatepe),

.etsu.edu (U. Yavas), [email protected]

organizational performance and continues to compel theattention of practitioners and academics (Lassar et al.,2000; Yavas and Yasin, 2001).Unlike goods quality, which can be measured with

some objectivity, service quality is abstract and elusive.The unique features of services such as inseparability ofproduction and consumption, intangibility, and hetero-geneity make measurement of quality a very complexissue. In the absence of objective measures, firms mustrely on consumers’ perceptions of service quality toidentify their strengths and/or weaknesses, and designappropriate strategies. This makes development ofpsychometrically sound and managerially useful instru-ments to measure service quality imperative.The purpose of this paper is to develop and test a

service quality instrument by using the retail bankingservices in Northern Cyprus as a case in point. Thisobjective is consistent with growing sentiments fordeveloping context-specific (e.g., industry and/or cul-ture-specific) service quality measures in light of thedifficulties involved with universal/global measures(Aldlaigan and Buttle, 2002; Babakus and Boller,1992; Robinson, 1999; Winsted, 1997). The stages

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ARTICLE IN PRESSO.M. Karatepe et al. / Journal of Retailing and Consumer Services 12 (2005) 373–383374

outlined in Churchill’s (1979) now-classic paradigm fordeveloping better measures of marketing constructs areemployed in accomplishing this objective. In the past,Churchill’s (1979) paradigm has been used to developnot only measures of other marketing constructs(Webster, 1990, 1993) but service quality measures aswell (Aldlaigan and Buttle, 2002; Parasuraman et al.,1988).In the next section, we provide a review of the relevant

literature. This is followed by the method and results ofan empirical study. We conclude the paper with adiscussion of the implications of the results andsuggestions for future research.

2. Relevant literature

A canvassing of the growing body of literature onservice quality suggests that two schools of thoughtdominate the extant thinking. One is the Nordic schoolof thought based on Gronroos’s (1984) two-dimensionalmodel. And the other is the North American school ofthought based on Parasuraman et al.’s (1988) five-dimensional SERVQUAL model. Considering othersignificant conceptual and empirical works in the area,it appears that service quality encompasses (1) custo-mers’ experiences with the tangibles, reliability, respon-siveness, assurance, and empathy aspects of the servicesdelivered by a firm (Parasuraman et al., 1988); (2)technical and functional quality (Gronroos, 1984); (3)service product, service environment, and servicedelivery (Rust and Oliver, 1994); and (4) interactionquality, physical environment quality, and outcomequality (Brady and Cronin, 2001).Our review of this body of literature points out two

major limitations. First, as noted by Babakus and Boller(1992), there is a need to develop industry-specific

measures of service quality. This is particularly im-portant from a managerial perspective (Shemwell andYavas, 1999). Because many of the questions in existinginstruments (notably SERVQUAL batteries) intendedto be applied across situations/services just do not applyin a specific context and force researchers to drasticallyalter the items (Babakus and Boller, 1992; Babakus andMangold, 1992; Carman, 1990; McAlexander et al.,1994). However, as Shemwell and Yavas (1999) cogentlyargue, the more specific the scale items are in a servicequality instrument and the more applicable they are to amanager’s own contextual circumstance, the better s/hewill be able to use the information. Thus, instead oftaking an existing instrument and trying to fit it to thecontext, a better approach is to develop an instrumentspecifically for the focal service. While many studies inbanking measure service quality by replicating oradopting Parasuraman et al.’s (1988) SERVQUALmodel (see, for example, Angur et al., 1999; Athanasso-

poulos, 1997; Blanchard and Galloway, 1994; Donthuand Yoo, 1998; Lloyd-Walker and Cheung, 1998;Marshall and Smith, 1999; McDougall and Levesque,1994; Newman and Cowling, 1996; Yavas and Benken-stein, 2001), a few studies address this weakness andpresent new models or approaches to the measurementof service quality in general and in banking in particular.For instance, Mersha and Adlaka (1992) applied the

Delphi technique to a sample of MBA students togenerate attributes of poor and good service quality.They then converted the 12 attributes thus identifiedinto scales and analyzed students’ perceptions of servicequality in five services, one of which was retail banking.The authors concluded that the list of attributes theygenerated was similar to the five dimensions ofSERVQUAL (i.e., tangibles, reliability, responsiveness,assurance, and empathy). In another study, Avkiran(1994) developed a multi-dimensional instrument formeasuring customer-perceived quality in retail branchbanking. Using SERVQUAL as a starting point andthen adding items that he extracted from a qualitativestudy commissioned to establish quality service stan-dards, Avkiran (1994) followed an iterative process andidentified staff conduct, credibility, communication, andaccess to teller services as the final dimensions of servicequality. The scale developed by Bahia and Nantel (2000)based on expert opinions revealed six dimensions ofservice quality. These were termed: effectiveness andassurance, access, price, tangibles, service portfolio, andreliability.More recently, Aldlaigan and Buttle (2002), based on

the technical and functional service quality schemaproposed by Gronroos (1984), developed a scale tomeasure service quality perceptions of bank customers.Their study resulted in SYSTRA-SQ, which consists ofservice system quality, behavioral service quality, servicetransactional accuracy, and machine service quality.As can be inferred from the statement of its purpose,

our study builds upon these works and, by applying aniterative procedure, develops a service quality instru-ment specifically for retail banking in Northern Cyprus.Such a comprehensive effort to develop a new scale tomeasure service quality in the particular setting was alsoencouraged by a number of bank managers in NorthernCyprus whom we contacted during the initial phases ofthe current study. After examining the copies of existinginstruments we provided them, the managers clearlyindicated the need for a tailor-made measure for theNorthern Cyprus context.Second, there is a need to develop service quality

measures that are country/culture specific. This isbecause, as is the case with other marketing andmanagement constructs and measures (Benkhoff, 1997;Hofstede, 1990; Yavas, 1997), quality constructs/mea-sures in general (Yavas and Konyar, 2002), and servicequality constructs/measures in particular (Mattila,

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1999a) that are developed in one culture (notably awestern culture) may not be applicable in a differentcultural setting. Drawing attention to this limitation ofextant research, Mattila (1999b) argues that the defini-tion of service quality depends on consumers’ culturalheritage, particularly on variations along power distanceand communication context. Malhotra et al. (1994)share this view and posit that the cultural differences(e.g., individualism/collectivism, power distance) be-tween countries are likely to have varying effects onthe definition of service quality. This is shown to be truein a research by Winsted (1997) who compared Japaneseand US consumers. Focusing on provider behaviors asindicators of service encounter quality, Winsted (1997)not only identified new quality dimensions that had notbeen a part of service quality concept until then, but alsodemonstrated that the number and meanings of servicequality dimensions varied between US and Japaneseconsumers. For instance, the ‘‘authenticity’’ dimension,which refers to genuineness of service providers’behaviors, was an important component of servicequality for Japanese consumers while this dimensiondid not surface in the case of the US consumers. Despitesome cross-cultural commonalities (Espinoza, 1999), theweight of evidence suggests that culture plays asignificant role on the definition of the service qualityconstruct (Kettinger et al., 1995). In recognition of this,calls are made to develop culture-specific measures ofservice quality (Winsted, 1997). Indeed, Imrie et al.(2002) recently stated that managers should avoidemploying the SERVQUAL scale globally and insteadthey should develop ‘‘a new, culturally boundedmeasure of service quality’’ (p. 17).Our study develops a service quality measure speci-

fically for the Turkish (Northern Cyprus) setting. Itshould be noted that this is not the first study dealingwith service quality measurement issues in Turkey andNorthern Cyprus. Yet it differs from previous studies inone very important respect. While all previous studiestook an existing instrument as is (or translated it intoTurkish) (Akan, 1995; Johns et al., 2004; Karatepe andAvci, 2002; Kozak et al., 2003; Yavas and Bilgin, 1996;Yavas and Arsan, 1995), the present study develops ameasure that represents the first comprehensive effort tounderstand how service quality assumes meaning in thiscultural context. It should also be added that severalprevious studies dealing with service quality in banking(Yavas and Bilgin, 1996) and other service industries(Johns et al., 2004; Karatepe and Avci, 2002) in theTurkish/Northern Cyprus setting failed to replicate thefive-dimensional structure purported in the SERVQ-UAL scale. Even those few studies which were able toreplicate the five-dimensional structure reported otherpsychometric problems. For instance, while Kozak etal.’s (2003) study which examined service quality ofairlines in Northern Cyprus was able to partially

support the five-dimensional structure of SERVQUAL,their study failed to provide evidence for discriminantvalidity. Likewise, Yavas and Arsan (1995) tested thedimensionality of the SERVQUAL scale in banking andfound a five-factor solution. Yet, most of the items didnot load on their underlying dimensions. At a time whenservice quality becomes a pressing issue in Turkishbanking (Babakus et al., 2003), our study can providemanagers with a much needed specific instrument. Also,our study addresses the voids in the literature and addsto the compendium of knowledge in the area.

3. Study

3.1. Step 1: qualitative study (item generation)

To generate items that comprise the domain of servicequality in retail banking services, a team of interviewersconducted one-on-one interviews with a judgmentalsample of 86 bank customers. The interviews were audiotape-recorded. In these interviews, based on theirexperiences and prior dealings with banks, participantswere asked to talk about their expectations from bankservices.To code the qualitative data thus obtained, similar to

prior studies (Brady and Cronin, 2001; Richins, 1997), acontent analytic approach was employed. In the firststage, after listening to the tapes, three independentcoders prepared paragraphs/field notes. All three codersagreed on the overall content of each paragraph/fieldnote. In the second stage, the same coders generated atotal of 56 items and agreed on 43 of these items yieldingan inter-judge reliability coefficient of .91. After a closerscrutiny, three coders agreed that 12 of the 43 itemshighly overlapped. After elimination of highly redun-dant items, this reexamination resulted in a total of 31items. In the final stage, three coders were asked tocategorize the 31 items into groups based on contentsimilarities of items. The three coders, working indivi-dually and then as a group, identified five distinctcategories. Transcripts and items in each category werefurther examined by a team of researchers to assign ahigher-level meaning to each category. This exercise ledto the identification and labeling of the followingdimensions of service quality: service environment (fouritems), interaction quality (eight items), reliability (fiveitems), empathy (10 items), and technology (four items).Table 1 presents a listing of these items.

Service environment refers to the appearance of theservice providers and appearance of the interior andexterior of the bank facilities. Interaction quality

encompasses attitudes and behaviors of the serviceproviders and their interaction style with customers.Empathy is defined as individualized attention given tocustomers and willingness of the bank personnel to help

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Table 1

Item-to-total correlations and varimax-rotated factor loadings (First stage, n ¼ 115)

Items Item-to-total correlations Factor loadings

F1 F2 F3 F4 F5

Q01. The exterior of this bank is visually appealing 0.48 — 0.66 — — —

Q02. The interior of this bank is visually attractive 0.56 — 0.69 — 0.32 —

Q03. Employees of this bank have neat appearances 0.49 — 0.68 — — —

Q04. The interior of this bank is spacious 0.36 — 0.42 — — —

Q05. The ATMs of this bank are technologically well-equipped 0.36 — 0.33 — — 0.61

Q06. There is an adequate number of employees in this bank 0.28 — — — — 0.65

Q07. There is an adequate number of ATMs in this bank 0.34 — — 0.40 — 0.61

Q08. The computerized system in this bank functions properly 0.42 0.30 — — 0.57 0.42

Q09. Employees of this bank have the knowledge to respond to problems 0.61 0.55 0.39 — — —

Q10. Employees of this bank are polite to customers 0.49 0.81 — — — —

Q11. Employees of this bank are experienced 0.65 0.62 0.31 — — —

Q12. Employees of this bank instill confidence in customers 0.70 0.67 0.34 — — 0.31

Q13. Employees of this bank are understanding of customers 0.58 0.84 — — — —

Q14. Employees of this bank serve customers in good manner 0.59 0.82 — — — —

Q15. There is a warm relationship between employees of this bank and customers 0.60 0.86 — — — —

Q16. This bank does not make its customers stand in a queue for a long time 0.48 — — 0.75 — —

Q17. Employees of this bank enact transactions on a timely manner 0.68 0.33 — 0.76 — —

Q18. Employees of this bank always help customers 0.68 0.64 — 0.45 — —

Q19. Employees of this bank provide individualized attention to customers 0.69 0.58 0.40 0.41 — —

Q20. Employees of this bank are willing to solve customer problems 0.64 0.59 — 0.43 — —

Q21. Employees of this bank provide error-free service 0.56 0.53 0.41 — — —

Q22. This bank is financially dependable 0.19 — — — 0.59 —

Q23. Employees of this bank carry out customer transactions confidentially 0.48 — 0.36 — 0.44 —

Q24. Employees of this bank provide customers with precise information 0.64 0.46 0.47 — 0.51 —

Q25. This bank informs customers about its financial operation accurately 0.48 — — — 0.56 —

Q26. This bank has convenient working hours 0.15 — 0.43 0.35 �0.51 —

Q27. Employees of this bank provide equal treatment to all customers 0.45 — 0.63 — — —

Q28. Employees of this bank know customers’ needs. 0.56 0.32 0.58 — — —

Q29. Employees of this bank are sensitive to customers’ needs 0.74 0.57 0.43 0.33 — —

Q30. Employees of this bank meet customer requests quickly 0.69 0.59 0.50 — — —

Q31. The internet banking services of this bank are widespread 0.06 — — — — —

Eigenvalue 10.50 2.48 1.78 1.70 1.57

% of variance explained 35.01 8.28 5.95 5.66 5.22

Coefficient alpha 0.91 0.73 0.82 0.73 0.44

Note: Items 1–4 represent ‘service environment’. Items 5, 7, 8, and 31 refer to ‘technology’. Items 9–15 and 30 represent ‘interaction quality’. Items 6,

16–20, and 26–29 represent ‘empathy’. Items 21–25 refer to ‘reliability’. The factor loadings less than .30 are not shown. Reliability coefficients

(coefficient alpha) are based on the a priori designation (as designated by coders) of the items to their respective dimensions.

O.M. Karatepe et al. / Journal of Retailing and Consumer Services 12 (2005) 373–383376

customers and resolve their problems in a timelymanner. Reliability refers to dependability of serviceand accuracy of records and information. Finally,technology dimension was defined as the quality ofATMs and the proper functioning of computerizedsystems.

3.2. Step 2: quantitative study: first stage

Data for the initial refinement of the 31-iteminstrument were obtained from a sample of 115customers of a large bank as they exited the bank aftercompleting a transaction there. Every third customerleaving the premises was approached to collect the data.This sample size, relative to the number of initial scale

items, compares favorably with sample sizes used byother studies in the early stages of scale development(Parasuraman et al., 1988; Webster, 1990). The majorityof the respondents (75 percent) were between the ages of17–46 and male (65 percent). Little over one-half hadcollege and 35 percent high school degrees. The sampleprofile, in terms of age and education composition, wasrepresentative of the bank’s customer population.The questionnaire administered to the respondents

consisted of two parts. The first part was designed tomeasure customers’ assessments of their bank’s servicequality with respect to the items identified during thequalitative phase of the study. There is a debate inliterature on whether the expectations, or the percep-tions, or the gap between the two constitute a better


measure of service quality. In this study, service qualitywas measured using ‘‘perceptions-only’’ approach.Specifically, service quality items were transformed intoLikert-scales and the respondents were asked to indicatetheir perceptions of their bank on each item using a five-point scale ranging from ‘‘5 ¼ strongly agree’’ to‘‘1 ¼ strongly disagree’’.The choice of performance-only scores was based on

the widely discussed methodological and theoreticalconcerns associated with the use of expectations scores(Babakus and Boller, 1992; Cronin and Taylor, 1992,1994; Parasuraman et al., 1994; Robinson, 1999) as wellas the difference (gap) scores (Brown et al., 1993; Teas,1993, 1994). Indeed, after a thorough review of the priorliterature and evidence from three new studies theyconducted, Brady et al. (2002) authoritatively declaredthat the ‘‘performance-only’’ measures of service qualityare superior to other approaches.The second part of the survey included three single-

item measures relating to overall service quality, overallcustomer satisfaction, and purchase intention. Re-sponses to overall service quality item were elicited ona five-point scale ranging from ‘‘5 ¼ very good’’ to‘‘1 ¼ very poor’’. Responses to customer satisfactionitem were elicited on a five-point scale ranging from‘‘5 ¼ extremely satisfied’’ to ‘‘1 ¼ extremely dissatis-fied’’. Finally, responses to purchase intention itemwere elicited on a five-point scale ranging from‘‘5 ¼ very high’’ to ‘‘1 ¼ very low’’.Churchill (1979) suggests that purification of an

instrument should start with the computation ofcoefficient alphas. This was done for the five dimensionsidentified by the coders. The coefficient alphas rangedfrom .44 to .91 across the five dimensions (Table 1).Following reliability analysis, exploratory factor analy-sis (principal components with varimax rotation) wasapplied to the data. As shown in Table 1, this analysisresulted in a five-factor solution. However, itemsrepresenting technology dimension did not emerge as aviable factor as indicated by low factor loadings and/orhigh cross-loadings. In light of factor analysis resultsand poor reliability (.44), the technology dimension wasdiscarded altogether. In addition, one item each frominteraction quality and reliability dimensions and fiveitems from empathy dimension were deleted due to highcross-loadings or factor loadings below .50. The fourfactors thus retained were: service environment (fouritems), interaction quality (seven items), empathy (fiveitems), and reliability (four items).Confirmatory factor analysis using LISREL (Jores-

kog and Sorbom, 1993) was then applied to the four-factor measurement model to further test dimensionalityas well as convergent and discriminant validity. Asshown in Table 2, the results of the confirmatory factoranalysis demonstrated a moderate fit of the four-factormeasurement model to the data on the basis of a number

of fit statistics (w2 ¼ 391.65, df ¼ 164, GFI ¼ .74,AGFI ¼ .67, NFI ¼ .73, NNFI ¼ .78, CFI ¼ .81,IFI ¼ .81, SRMR ¼ .092, RMSEA ¼ .11). Further-more, the magnitudes of the factor loading estimatesranged from .37 to .92 where a majority of the factorloadings were higher than .70. And all t-values weregreater than 2.00. Pairwise confirmatory factor analysesand w2 difference tests revealed that the dimensions aredistinct. Hence, confirmatory factor analyses resultsprovide evidence regarding convergent and discriminantvalidity of the measure (Anderson and Gerbing, 1988).Also, as reported in Table 2, internal consistencyreliability estimates exceeded the .70 cut-off valuerecommended by Nunnally (1978).Additional assessment of the scale was undertaken

using composite scores for each dimension, which werecalculated by averaging scores across items representingthat dimension. The correlations among the fourdimensions of the scale ranged from .37 (serviceenvironment and interaction quality) to .62 (empathyand interaction quality). The correlations betweenservice quality composite dimension scores and theoverall service quality (range between .50 and .60),customer satisfaction (range between .49 and .60), andpurchase intention (range between .40 and .58) providedfurther evidence for the viability of the scale. Collec-tively, the results from the initial sample are highlyencouraging regarding the reliability, convergent, anddiscriminant validity of the scale. Hence, the entire scalewas used without further alteration during the secondstage of the quantitative study.

3.3. Step 3: quantitative study: second stage

To further evaluate the 20-item scale and its psycho-metric properties, a large-scale study was undertaken.Prior to data collection, managements of 10 banks werecontacted and permission was sought to interview theircustomers on the premises right after completing atransaction. Eight banks granted permission to theresearch team. The number of respondents to be drawnfrom each bank was determined proportional to thenumber of customers of each of the banks. And, againevery third customer leaving the premises was ap-proached to collect the data. To get a representativesample of customers, data collection took place duringall operating hours. After a 3-month period, usableresponses were obtained from a total of 1220 customers.This sample size is much larger than the sample sizesused in similar scale development studies (Parasuramanet al., 1988, 1991; Webster, 1990) and well exceeds the1000 observations sample size guideline recommendedfor factor analysis (Tabachnick and Fidell, 1996) as wellas the 10 to 1 ratio of sample size to number of scaleitems guidelines suggested by Nunnally (1978). Eighty-four percent of the respondents were between the ages of

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Table 2

Scale items, reliabilities and confirmatory factor analysis results (first stage, n ¼ 115)

Scale items Standardized loadings T-values Coefficient alpha

Service environment (SERENV) 0.73

The exterior of this bank is visually appealing 0.80 9.31

The interior of this bank is visually attractive 0.92 11.18

Employees of this bank have neat appearances 0.44 4.67

The interior of this bank is spacious 0.37 3.91

Interaction quality (INTQUAL) 0.91

Employees of this bank have the knowledge to respond to problems 0.59 6.78

Employees of this bank are polite to customers 0.78 9.69

Employees of this bank are experienced 0.67 7.84

Employees of this bank instill confidence in customers 0.73 8.86

Employees of this bank are understanding of customers 0.84 10.89

Employees of this bank serve customers in good manner 0.84 10.83

There is a warm relationship between employees of this bank and

customers

0.87 11.42

Empathy (EMP) 0.85

This bank does not make its customers stand in a queue for a long

time

0.52 5.76

Employees of this bank enact transactions on a timely manner 0.76 9.22

Employees of this bank always help customers 0.88 11.55

Employees of this bank provide individualized attention to customers 0.78 9.67

Employees of this bank are willing to solve customer problems 0.83 10.59

Reliability (REL) 0.76

Employees of this bank provide error-free service 0.67 7.70

Employees of this bank carry out customer transactions confidentially 0.57 6.24

Employees of this bank provide customers with precise information 0.89 11.23

This bank informs customers about its financial operation accurately 0.64 7.17

Model fit statistics w2 ¼ 391.65, df ¼ 164, GFI ¼ 0.74, AGFI ¼ 0.67, NFI ¼ 0.73,

NNFI ¼ 0.78, CFI ¼ 0.81, IFI ¼ 0.81, SRMR ¼ 0.092, RMSEA ¼ 0.11

Note: Each item is measured on a five-point scale ranging from ‘‘5 ¼ strongly agree’’ to ‘‘1 ¼ strongly disagree’’. All loadings are significant at the .01

level.


17 and 46. The majority of the respondents (66 percent)were male. Forty-two percent of the respondents hadcollege and 45 percent high school degrees. Thedemographic breakdown of the sample is representativeof retail bank customers in Northern Cyprus.Similar to the process employed in the first stage, we

first computed coefficient alphas. As shown in Table 3,these coefficients ranged from .81 to .92. In addition, allcorrected item-to-total correlations ranged from .46 to.75. In light of these results, there was no compellingreason to delete any items. Confirmatory factor analysiswas employed to examine dimensionality, convergent,and discriminant validity. The results of the confirma-tory factor analysis demonstrated a reasonable fit of thefour-factor measurement model to the data on the basisof a number of fit statistics (w2 ¼ 1354.60, df ¼ 164,GFI ¼ .90, AGFI ¼ .87, NFI ¼ .92, NNFI ¼ .92,CFI ¼ .93, IFI ¼ .93, SRMR ¼ .047, RMSEA ¼ .077).The magnitudes of the standardized loadings rangedfrom .50 to .83 and all t-values were higher than 2.00,indicating convergence of items with their respectiveunderlying dimensions. As can be seen from Table 3, the

overwhelming majority of the standardized loadingswere above .70. Pairwise confirmatory factor analyses ofthe dimensions provided support for discriminantvalidity of the scale (Anderson and Gerbing, 1988).The scale was subjected to further validity assessment

using composite scores for each dimension, which werecalculated by averaging scores across items representingthat dimension. As can be seen from Table 4, thecorrelations among the underlying dimensions rangedfrom .52 (service environment and reliability) to .76(interaction quality and empathy). The correlationsamong the dimensions (intra-construct correlations) ofthe scale are consistently higher than their correlationswith customer satisfaction and purchase intention (inter-construct correlations). Hence, the scale meets afundamental requirement for convergence and discrimi-nation in measurement (Bagozzi, 1981).Fig. 1 provides a partial nomological network and the

results of additional analysis to address nomologicalvalidity issues. The literature suggests that perceivedquality has a direct influence on purchase intention(Zeithaml et al., 1996) as well as an indirect effect via the

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Table 3

Scale items, reliabilities and confirmatory factor analysis results (second stage, n ¼ 1220)

Scale items Standardized loadings T-values Coefficient alpha


The exterior of this bank is visually appealing 0.72 26.78

The interior of this bank is visually attractive 0.80 31.08

Employees of this bank have neat appearances 0.67 24.30

The interior of this bank is spacious 0.71 26.25

Interaction quality (INTQUAL) 0.92

Employees of this bank have the knowledge to respond to problems 0.70 27.60

Employees of this bank are polite to customers 0.81 33.92

Employees of this bank are experienced 0.72 28.58

Employees of this bank instill confidence in customers 0.79 32.28

Employees of this bank are understanding of customers 0.82 34.68

Employees of this bank serve customers in good manner 0.83 34.78

There is a warm relationship between employees of this bank and

customers

0.80 33.32

Empathy (EMP) 0.83

This bank does not make its customers stand in a queue for a long time 0.50 17.80

Employees of this bank enact transactions on a timely manner 0.69 26.44

Employees of this bank always help customers 0.83 34.69

Employees of this bank provide individualized attention to customers 0.81 33.62

Employees of this bank are willing to solve customer problems 0.77 30.65

Reliability (REL) 0.81

Employees of this bank provide error-free service 0.73 27.93

Employees of this bank carry out customer transactions confidentially 0.69 26.25

Employees of this bank provide customers with precise information 0.82 33.00

This bank informs customers about its financial operation accurately 0.68 25.36

Model fit statistcis w2 ¼ 1354.60, df ¼ 164, GFI ¼ 0.90, AGFI ¼ 0.87, NFI ¼ 0.92,

NNFI ¼ 0.92, CFI ¼ 0.93, IFI ¼ 0.93, SRMR ¼ 0.047,

RMSEA ¼ 0.077

Note: Each item is measured on a five-point scale ranging from ‘‘5 ¼ strongly agree’’ to ‘‘1 ¼ strongly disagree’’. All loadings are significant at the .01

level.

Table 4

Means, standard deviations and correlations of study variables

(Second stage, n ¼ 1220)

Variables: 1 2 3 4 5 6


Interaction quality (INTQUAL) 0.60 1.00

Empathy (EMP) 0.54 0.76 1.00

Reliability (REL) 0.52 0.71 0.70 1.00

Customer satisfaction (CSAT) 0.51 0.65 0.62 0.61 1.00

Purchase intention (PINTENT) 0.50 0.65 0.65 0.62 0.71 1.00

Mean 3.54 3.94 3.70 3.91 3.95 3.84

Standard deviation 0.87 0.77 0.80 0.71 0.69 0.79

Note: Composite scores for each measure were obtained by averaging

scores across items representing that measure, except for customer

satisfaction and purchase intention. The scores range from 1 to 5. A

higher score indicates a more favorable response. All correlations are

significant at the .01 level.

O.M. Karatepe et al. / Journal of Retailing and Consumer Services 12 (2005) 373–383 379

mediating role of customer satisfaction (Brady andRobertson, 2001). Using this simple nomological net-work, we tested a structural model with the four

composite dimension scores as indicators of servicequality. The results in Fig. 1 show that the model fits thedata rather well (w2 ¼ 18.66, df ¼ 8, p ¼ :017;SRMR ¼ .011, GFI ¼ .99, AGFI ¼ .99, NFI ¼ 1.00,NNFI ¼ 1.00, CFI ¼ 1.00, RMSEA ¼ .033), and boththe direct and indirect effects of service quality onpurchase intentions are significant. That is, the standar-dized regression coefficients from: (1) service quality tocustomer satisfaction (g1 ¼ :74; t ¼ 22:5); (2) servicequality to purchase intention (g2 ¼ :45; t ¼ 13:5); and (3)customer satisfaction to purchase intention (b ¼ :41;t ¼ 14:6) are all statistically significant. Furthermore, itmakes theoretical sense that service quality has itsstrongest effect on customer satisfaction since satisfac-tion is a mediator between service quality and purchaseintention. In addition, 55 percent of the variance incustomer satisfaction is accounted for by service quality,and 64 percent of the variance in purchase intention isexplained by service quality and customer satisfactionjointly. Finally, an examination of standardized load-ings in Fig. 1 suggests that interaction quality is themost important indicator of service quality (l2 ¼ :88),

ARTICLE IN PRESS

SQUAL CUSTSAT PURCINT

γ1= 0.74 (t=22.5)

γ2 = 0.45 (t=13.5)

β = 0.41 (t=14.6)

INTQUAL

EMP

REL

λ 1=.66***

λ 2=0.88 (t=25.9)

λ 3=0.85 (t=25.2)

λ 4=0.81 (t=24.2)

SERENV CSAT PINTENT

Proportion of variance explained (R2) in: Customer satisfaction (CUSTSAT): 0.55 Purchase intention (PURCINT): 0.64

Model fit statistics: 2=18.66 (df=8, p=0.017)

SRMR=0.011 GFI=0.99 AGFI=0.99 NFI=1.00 NNFI=1.00 CFI=1.00

RMSEA=0.033

χ

Fig. 1. Assessing nomological validity of the service quality measure: the relationships among service quality (SQUAL), customer satisfaction

(CUSTSAT), and purchase intention (PURCINT) constructs. Note: Since customer satisfaction and purchase intention were measured using single

items, their error variances were set to zero in the structural model. Hence, their standardized loadings on their respective latent constructs were 1.00

by definition. T-values are shown in parentheses except for the loading of service environment (SERENV), which was initially fixed to 1.00 to set the

metric for the underlying service quality construct.


followed by empathy (l3 ¼ :85), reliability (l4 ¼ :81),and service environment (l1 ¼ :66).

4. Discussion

This study developed a 20-item survey instrument tomeasure bank customer perceptions of service quality inNorthern Cyprus. The results showed that servicequality could be conceptualized and measured as afour-dimensional construct consisting of service envir-onment, interaction quality, empathy, and reliability.The scale exhibited high internal consistency reliabilityand met rigorous conceptual and empirical criteria forconstruct validity including content, convergent, dis-criminant, and nomological validity.Our results showed that interaction quality is the most

important dimension of service quality followed byempathy, reliability, and service environment. Thenumber of distinct dimensions, their meaning, and theirorder of importance show some similarities anddifferences with prior conceptualizations includingGronroos (1984), Parasuraman et al. (1991), Bradyand Cronin (2001), Rust and Oliver (1994), andAldlaigan and Buttle (2002). There is a clear conver-gence in terms of conceptual meaning between ourservice environment dimension and the ‘tangibles’dimension of SERVQUAL. This dimension is the leastimportant indicator of service quality in this study as

well as previous studies using SERVQUAL (e.g.Parasuraman et al., 1991). Empathy and reliabilitydimensions in the current and SERVQUAL scales arealso conceptually similar. In the present study, empathywas found slightly more important than the reliabilitydimension whereas SERVQUAL studies consistentlyidentified reliability as the most important indicator ofservice quality. Interaction quality appears to overlapwith the combined SERVQUAL dimensions of ‘respon-siveness’ and ‘assurance’.Additionally, interaction quality identified in the

current study is similar to that of Gronroos’s (1984)functional quality. Several dimensions reported in ourstudy are similar to those of Aldlaigan and Buttle(2002). For example, their behavioral service quality issimilar to our interaction quality, and our reliability issimilar to their service transactional accuracy. Finally,service environment dimension in Rust and Oliver(1994) and physical environment quality in Brady andCronin (2001) are conceptually similar to our serviceenvironment dimension.A common theme emerging from these comparisons is

that the meaning of service quality may have someuniversal aspects as demonstrated by the similarities inthe underlying dimensions. However, significant varia-tions may exist regarding the complexity (i.e., thenumber of underlying dimensions) of service qualityconcept and the importance attached to each dimensionfrom one context to another. A comparison of the


current study with those that were conducted in thebanking sector in Turkey (a very similar culture andsimilar customer demographics) using SERVQUAL(Yavas and Arsan, 1995; Yavas and Bilgin, 1996)reveals that the service quality measure developed inthis study provides a more specific view since it wasguided by items suggested by bank customers in the firstplace. The items in Yavas and Bilgin (1996) produced athree-dimensional depiction of service quality with noapparent identification with the presumed SERVQUALdimensions. While Yavas and Arsan (1995) found a five-dimensional structure, the items did not load on theappropriate factors designated in SERVQUAL. Ourstudy produced a viable measure of retail bankingservice quality within the cultural context of NorthernCyprus.The technology dimension of service quality was

initially considered based on the qualitative stage of thestudy. However, it did not emerge as a viable dimensionin the later stages when subjected to empirical criteria.This result is potentially due to the fact that technology-based services (e.g., video-banking, internet-banking,telephone-banking) are not widely available and, wher-ever available, internet sites are not easy to navigate.Furthermore, the use of technology in this sector ishampered by poor electrical infrastructure. Frequentpower outages render ATMs useless and cause frustra-tion among customers. Also down-times and other‘‘glitches’’ in computer systems are common occurrencesin Northern Cyprus. However, bank consumers areaware of the benefits that technology can provide andthis dimension of service quality will assume a moredistinct meaning in the future as technology infrastruc-ture improves in the country. Hence, future studiesshould pay attention to technology as a potentiallycritical dimension of service quality.The current study provides some useful insights for

managerial action. First, bank managers can rely on thisindustry-specific scale in order to measure servicequality delivered to their customers. By examiningperformance scores on each attribute within and acrossdimensions, improvement needs can be identified.Second, from a strategic standpoint, bank managerscan determine the relative importance of the four servicequality dimensions in predicting customer satisfactionand customer loyalty. By doing so, bank managers candetermine which service quality dimension(s) theyshould pay most attention to. Third, multi-branch bankorganizations can use the current scale to evaluateservice quality delivered to customers in differentbranches and track the relative performance of variousbranches over time. Fourth, bank managers can employthe service quality scale to identify distinct customerclusters or segments with varying perceptions aboutservice quality. Cluster profiles can provide valuableinformation on how to approach each segment for

quality improvement initiatives. Focusing marketingefforts on the most unhappy cluster(s), for instance, mayprovide immediate relief for reducing defection rates(Brady and Cronin, 2001). Fifth, the service quality scalecan also be administered to frontline employees andtheir customers simultaneously to compare customerperceptions of service quality with frontline employeeperceptions. Finally, from a competitive standpoint,bank managers can use the existing scale to assess theirstrengths/weaknesses relative to competitors acrossservice quality dimensions.

5. Concluding comments

It should be underscored that given the premise thatreplication research is the mainstay of the scientificmethod and that empirical generalizations are central toknowledge development, our results can hardly beconsidered conclusive. Certainly more studies areneeded to further validate the four-factor service qualitymeasure derived in this study. In addition, while wefollowed well-established procedures throughout ourstudy, at the qualitative stage, employment of theapproach advocated by Zimmer and Golden (1988)might have been better. It is conceivable that using thesame coders also as judges during the coding process inselecting and developing the items may have partiallyconfounded our item pool.This study provides full support for neither the North

American nor the Nordic school of thought regardingthe dimensionality of service quality or the meanings ofquality dimensions. However, the dimensions identifiedin this study show similarities to other service qualitymeasures such as SERVQUAL and SYSTRA-SQ. Thissuggests that there may be some potentially universalfacets of service quality and that perhaps we may notneed to develop specific measures from scratch for eachcontext. Instead, existing knowledge base may provide auseful starting point for adaptations to new contexts.Future research can shed further light on these issues.

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