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ÿþAn executive summary for managers and SERVQUAL revisited: a critical executives can be found review of service quality at the end of this article Patrick Asubonteng, Karl J. McCleary and John E. Swan Introduction As competition becomes more intense and environmental factors become more hostile, the concern for service quality grows. If service quality is to become the cornerstone of marketing strategy, the marketer must have the means to measure it. The most popular measure of service quality is SERVQUAL, an instrument developed by Parasuraman et al. (1985; 1988). Not only has research on this instrument been widely cited in the marketing literature, but also its use in industry has been quite widespread (Brown et al., 1993). Service quality as SERVQUAL is designed to measure service quality as perceived by the perceived by the customer. Relying on information from focus group interviews, Parasuraman customer et al. (1985) identified basic dimensions that reflect service attributes used by consumers in evaluating the quality of service provided by service businesses. As an example, among the dimensions were reliability and responsiveness, and the businesses included banking, credit cards and appliance repair. Consumers in the focus groups discussed service quality in terms of the extent to which service performance on the dimensions matched the level of performance that consumers thought a service should provide. A high quality service would perform at a level that matched the level that the consumer felt should be provided. The level of performance that a high quality service should provide was termed consumer expectations. If performance was below expectations, consumers judged quality to be low. To illustrate, if a firm s responsiveness was below consumer expectations of the responsiveness that a high quality firm should have, the firm would be evaluated as low in quality on responsiveness. Parasuraman et al. s (1985; 1988) basic model was that consumer perceptions of quality emerge from the gap between performance and expectations, as performance exceeds expectations, quality increases; and as performance decreases relative to expectations, quality decreases (Parasuraman et al., 1985; 1988). Thus, performance-to-expectations  gaps on attributes that consumers use to evaluate the quality of a service form the theoretical foundation of SERVQUAL. Important to both The purpose of this paper is to provide a review of the SERVQUAL research managers and on service quality in the following areas: researchers (1) definition and measurement of service quality, and (2) reliability and validity of SERVQUAL measures. The issues we address are of importance to both service managers and researchers. Service quality is important to marketers because a customer s The authors would like to thank T. Dawn Bendall for her contributions to this paper. The authors also offer their appreciation to the Editor and three anonymous reviewers for recommendations that substantially improved this paper. 62 THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996, pp. 62-81 © MCB UNIVERSITY PRESS, 0887-6045 evaluation of service quality and the resulting level of satisfaction is thought to determine the likelihood of repurchase and ultimately affect bottom- line measures of business success (Iacobucci et al., 1994). It is important for management to understand what service quality consists of, its definition, and how it can be measured. If management is to take action to improve quality, a clear conception of quality is of great value. A vague exhortation to customer contact employees to  improve quality may have each employee acting on his/her notion of what quality is. It is likely to be much more effective to tell a service contact employee what specific attributes service quality includes, such as responsiveness. Management can say, if we can improve our responsiveness, quality will increase. Vital to quality Valid and reliable measurement of service quality is vital to quality management management. As an illustration, if employee training or a change in work procedures to enhance quality is undertaken, it would be important to measure customer perceptions of quality before and after the quality action was taken to see if the goal had been achieved. A reliable measure is one that is consistent, that is if quality did not change, the measure of quality would not change. A valid measure is a measure in which the score generated by the measurement process reflects the  true value of the property that one is attempting to measure. As an example of the importance of reliability and validity, consider Jones whose weight was measured in a physician s office at 165 pounds and the physician said,  you should be no more than 160 pounds. Jones tries to lose weight, but Jones scale at home is unreliable and poor Jones wonders why the diet works one week, but not the next. Next, suppose Jones scale was not valid, low by five pounds; Jones thinks the problem is solved, but it is not. Definition and measurement of service quality (SQ) Definition of SQ Three underlying themes Parasuraman et al. (1985) suggested three underlying themes after reviewing the previous writings on services: (1) service quality is more difficult for the consumer to evaluate than goods quality, (2) service quality perceptions result from a comparison of consumer expectations with actual service performance, and (3) quality evaluations are not made solely on the outcome of service; they also involve evaluations of the process of service delivery (p. 42). Parasuraman et al. (1988) defined perceived service quality as  global judgment, or attitude, relating to the superiority of the service (p. 16). Different views on Swartz and Brown (1989) drew some distinctions between different views service quality on service quality, drawing from the work of Grönroos (1983) and Lehtinen and Lehtinen (1982) concerning the dimensions of service quality.  What the service delivers is evaluated after performance (Swartz and Brown, 1989, p.190). This dimension is called outcome quality by Parasuraman et al. (1985), technical quality by Grönroos (1983), and physical quality by Lehtinen and Lehtinen (1982).  How the service is delivered is evaluated during delivery (Swartz and Brown, 1989, p. 190). This dimension is called process quality by Parasuraman et al. (1985), functional quality by Grönroos (1983), and interactive quality by Lehtinen and Lehtinen (1982). The  what (physical, technical, and outcome quality) are difficult to evaluate for any service. For example, in health services the service THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 63 provider s technical competence, as well as the immediate results from many treatments, is very difficult for a patient (who is a customer) to evaluate, either before or after the delivery of the service. Owing to this lack of ability to assess technical quality, consumers and purchasers rely on other measures of quality attributes associated with the process of health service delivery  the  how . Thus, patients and other consumers rely on attributes such as reliability and empathy. Definition of service In this paper, service quality can be defined as the difference between quality customers expectations for service performance prior to the service encounter and their perceptions of the service received. Service quality theory (Oliver, 1980) predicts that clients will judge that quality is low if performance does not meet their expectations and quality increases as performance exceeds expectations. Hence, customers expectations serve as the foundation on which service quality will be evaluated by customers. In addition, as service quality increases, satisfaction with the service and intentions to reuse the service increase. Measurement of service quality: SERVQUAL scale The SERVQUAL instrument was designed to measure service quality across a range of businesses. Parasuraman et al. (1985; 1988) measured the quality of services provided by the following: " retail banks, " a long-distance telephone company, " a securities broker, " an appliance repair and maintenance firm, and " credit card companies. Design of SERVQUAL The SERVQUAL scale was produced following procedures recommended instrument for developing valid and reliable measures of marketing constructs ( Brown et al., 1993). Parasuraman et al. concluded from their 1985 study that consumers evaluated service quality by comparing expectations to performance on ten basic dimensions. The scale (Parasuraman et al., 1988) was developed by, first, writing a set of about 100 questions that asked consumers to rate a service in terms both of expectations and of performance on specific attributes that were thought to reflect each of the ten dimensions. Next, the data were analyzed by grouping together sets of questions that all appeared to measure the same basic dimension, such as reliability. Use of factor analysis Factor analysis was a major tool as it provides a means of determining which questions are measuring dimension number one, which questions are measuring dimension number two and so on, as well as which questions do not distinguish between dimensions and the number of dimensions in the data. Questions that were not clearly related to a dimension were discarded. A revised scale was administered to a second sample, questions were tested and the result was a 22-question (item) scale measuring five basic dimensions of reliability, responsiveness, empathy, assurance and tangibles both on expectations and performance. Since both expectations are measured using 22 questions, and performance is rated using 22 parallel questions, 44 questions in total are used. As an example, the pair of questions measuring reliability for banks was as follows: (1) Expectations: these institutions should be dependable. (2) Performance: (a specific bank) is dependable. 64 THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 The customer rating a bank would indicate his or her extent of agreement or disagreement with each statement with 7 indicating  strongly agree and 1  strongly disagree , with 6, 5, 4, 3, 2 for a rating between  strongly agree to  strongly disagree . Quality was measured as performance-expectations for each pair of questions and the summary score across all 22 questions was the measure of quality. As an example, if the performance score was 6 and the expectations score was also 6, the bank would have met expectations, high service quality, for a quality score = 0. Testing reliability Parasuraman et al. (1988) also tested their SERVQUAL scale for reliability and validity. The major test of reliability was coefficient alpha, a measure of the extent of internal consistency between, or correlation among, the set of questions making up each of the five dimensions, such as the five reliability questions. The minimum reliability that is acceptable is difficult to specify. If reliability is low, such as below 0.60, one is faced with the choice of investing time and money in additional research in an attempt to develop a revised measure with greater reliability, or using the measure, recognizing that fluctuations in measured quality may be due only to measurement rather than a change in quality. High reliabilities, such as 0.90 or above, are desirable. Testing validity In principal, the validity of a bathroom scale is easy to test as one could simply place a standard weight on the scale and see if the scale gave the correct value. The validity of a measure of service quality is difficult to test as a proven criterion is not available. The general approach to testing the validity of marketing scales is to measure the agreement between the measure of interest, SERVQUAL, and a second measure of quality, convergent validity and/or a measure of a variable that should be related to quality, concurrent validity. Parasuraman et al. (1988) provided evidence of convergent validity as they measured agreement between the SERVQUAL score and a question that asked customers to rate the overall quality of the firm being judged and also concurrent validity, whether the respondent would recommend the firm to a friend. Other measures of validity have been used in research on SERVQUAL and are discussed later in this article. An overview of SERVQUAL applications SERVQUAL adopted for SERVQUAL has been adapted to measure service quality in a variety of use on a variety of settings. Health care applications are numerous (Babakus and Mangold, settings 1992; Bebko and Garg, 1995; Bowers et al., 1994; Clow et al., 1995; Headley and Miller, 1993; Licata et al., 1995; Lytle and Mokwa, 1992; O Connor et al., 1994; Reidenbach and Sandifer-Smallwood, 1990; Woodside et al., 1989). Other settings include a dental school patient clinic, a business school placement center, a tire store, and acute care hospital (Carman, 1990); independent dental offices ( McAlexander et al., 1994); at AIDS service agencies (Fusilier and Simpson, 1995); with physicians (Brown and Swartz , 1989; Walbridge and Delene, 1993); in large retail chains (such as kMart, WalMart, and Target) (Teas, 1993); and banking, pest control, dry cleaning, and fast-food restaurants (Cronin and Taylor, 1992). Disagreements between the studies have focussed on two major issues, the dimensions of service quality and linkage between satisfaction and quality. Disagreement concerning the proposed linkage between quality and satisfaction has led to a division over causality, with one group supporting the proposition that quality leads to satisfaction (Woodside et al., 1989), and THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 65 the other group supporting the proposition that satisfaction leads to quality (Bitner, 1990). Others suggest that quality and satisfaction are determined by the same attributes (Bowers et al.,1994). The issue of the dimensions of service quality has concerned the number of Basic dimensions that comprise service quality basic dimensions that comprise service quality. Recall that Parasuraman et al. (1988) found that the 22 questions formed five dimensions. Some studies have found more than five dimensions, while other research has suggested fewer dimensions (see Tables I-III). Regardless of disagreement, important findings across studies include support for the premiss that: Service attributes Ai ’! Important actions (behaviors)Bi. In health care, these  important actions include willingness to return and willingness to recommend (Woodside et al.,1989). Bowers et al. (1994), and Reidenbach and Sandifer-Smallwood (1990) found that the SERVQUAL outcomes of switching and word-of-mouth behavior were related to service quality. In addition, while there is no agreement on the exact linkages, attributes, and dimensions of quality and satisfaction, most researchers agree that service quality comprises attributes that are both measurable and variable. Comparison of Parasuraman et al. (1985; 1988) studies with other studies using SERVQUAL The SERVQUAL scale has been used in a variety of studies in different settings to assess customer perceptions of service quality. All studies have not examined the scale s psychometric properties; however there are a few recent exceptions (Babakus and Boller, 1992; Babakus and Mangold, 1992; Brensinger and Lambert, 1990; Carman, 1990; Cronin and Taylor, 1992; Finn and Lamb, 1991; Headley and Miller, 1993; Lytle and Mokwa, 1992; McAlexander et al., 1994; O Connor et al., 1994; Taylor and Cronin, 1994; Walbridge and Delene, 1993). Tables I-III provide a comparative summary. In addition to summarizing the contexts and procedures used in various studies, Tables I-III reveals areas of consensus as well as unresolved issues regarding SERVQUAL s psychometric properties. Reliability and validity measures Reliability Relaibility coefficients The Cronbach s alpha reliability coefficients for the five SERVQUAL dimensions are similar across studies (e.g. Babakus and Boller, 1992; Babakus and Mangold, 1992; Bowers et al., 1994; Carman, 1990; Cronin and Taylor, 1992; Finn and Lamb, 1991; Headley and Miller, 1993; Lytle and Mokwa, 1992; McAlexander et al., 1994; O Connor et al., 1994; Taylor and Cronin, 1994) and at least of the same magnitude as those reported in Parasuraman et al. (1988). These findings validate the internal reliability or cohesiveness of the scale items forming each dimension. Some researchers (e.g. Babakus and Boller, 1992; Babakus and Mangold, 1992; Carman, 1990) have suggested that overall reliability can be improved by changing negatively stated items to positively stated items. The lowest reliability is 0.59 reported by Finn and Lamb (1991) and the highest reliability is 0.97 reported by Babakus and Mangold (1992). 66 THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 The application of SERVQUAL has produced mixed findings in the health care setting. Some studies (Babakus and Mangold, 1992; Bowers et al., 1994) have demonstrated that SERVQUAL is reliable in the health care arena. In contrast, O Connor et al. (1993) reported inadequate reliability with the tangibles scale and found that the reliability quality dimension was not a significant predictor of customer satisfaction. Validity There are several different forms of validity that can serve as criteria for assessing the psychometric soundness of a scale: discriminant validity, face validity, and convergent and concurrent validity (Peter and Churchill, 1986). Discriminant validity The findings from most studies (Tables I-III) differ from the original study with respect to SERVQUAL s discriminant validity. Most studies imply greater overlap among the SERVQUAL dimensions  especially among responsiveness, assurance, and empathy  than implied in the original study (Peter et al., 1993). The number of distinct dimensions based solely on the factor analysis results is not the same across studies. It varies from two in the Babakus and Boller (1992) study to eight in one of the four settings studied by Carman (1990). Possible reasons for The variation across studies may be due to differences in data collection and variation across studies analysis procedures (Tables I-III). Another explanation may be that respondents may consider the SERVQUAL dimension to be conceptually unique. If their evaluations of a specific company on individual scale items are similar across dimensions, fewer than five dimensions will result as in the Babakus and Boller (1992) study. Alternatively, if their evaluations of a company on a scale of items within a dimension are sufficiently distinct, more than five dimensions will result, as in Carman s (1990) study. In other words, differences in the number of empirically derived factors across studies may be due primarily to across-dimension similarities and/or within- dimension differences in customers evaluations of a specific company involved in each setting (Peter et al., 1993). Two potential problems As already stated, Carman (1990), and Babakus and Boller (1992) have with discriminant validity questioned the use of difference scores in multivariate analysis. Peter et al. (1993) identify two potential problems with discriminant validity that can arise through the use of difference scores. One problem is common to all measures while the other is unique to measures formed as linear combinations of measures of other constructs. The common problem relates to how the reliability of measures affect discriminant validity. Low measure reliability attenuates correlations between constructs. Thus, a measure with low reliability may appear to possess discriminant validity simply because it is unreliable. Since difference score measures are usually less reliable than non-difference score measures, they can be particularly subject to this phenomenon. Any correlation between a difference and another variable is an artefact of the difference score and the other variable (Johns, 1981). Since difference score measures will not typically demonstrate discriminant validity from their components, their construct validity is questionable. Face validity SERVQUAL s face validity, a subjective criterion reflecting the extent to which scale items are meaningful and appear to represent the construct being THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 67 Parasuraman et al. Finn and Lamb Babakus and Mangold Babakus and Boller Headley and Miller Study (1985; 1988) Carman (1990) (1991) (1992) (1992) (1993) Data collection study Customers of telephone Customers of a dental Customers of four retail Customers of a Customers of an Customers of medical sample(s) co., securities brokerage, school patient clinic, a store types: stores like hospital electric and gas utility services insurance co., banks and business school kMart, WalMart, etc., co. repair and maintenance placement center, a tire JC Penney, Sears, etc., store and a hospital Dillards, Foley s, etc. and Saks, Neimann- Marcus, etc. Sample size Ranged from 298 to 487 Ranged from 74 to 600+ Ranged from 58 to 69 443 689 159 usable pre- and post- across companies across settings across settings encounter responses, 11 primary care physicians Questionnaire format Similar to PZB (1988) Similar to PZB (1988) in Similar to PZB (1988) Similar to PZB (1988) Similar to PZB (1988) Similar to PZB (1988) format the placement center Major wording changes Negatively worded No major changes in the No major changes Negatively worded No major changes No major changes, except questions SERVQUAL items questions changed to for languages necessary to retained, however, a positive form switch between a generic several of the items provider reference and a added were transaction- specific provider of medical specific (rather than services general attitude statements as in the original SERVQUAL) Original SERVQUAL 22 items Ranged from ten to 17 All 22 items 15 pairs of matching All 22 items All 22 items item retained across settings expectation-perception items (Continued) Table I. Comparison of Parasuraman et al. (1985; 1988) studies with other SERVQUAL replication studies 68 THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 Parasuraman et al. Finn and Lamb Babakus and Mangold Babakus and Boller Headley and Miller Study (1985; 1988) Carman (1990) (1991) (1992) (1992) (1993) Response scale Seven-point scale Seven-point scale Five-point scale Five-point scale Seven-point scale Seven-point scale Questionnaire Mail survey Self-administered by Telephone survey Mail survey Mail survey Mail survey administration respondent on-site Data analysis Principal-axis factor Principal-axis factor LISREL confirmatory Principal-axis factor Principal-axis factor Principal-axis factor analysis Procedure for assessing analysis followed by analysis followed by factor analysis of analysis followed by analysis followed by followed by oblique factor-structure oblique rotation oblique rotation five-dimensional oblique rotation; oblique rotation; rotation; measurement model LISREL confirmatory LISREL confirmatory LISREL confirmatory Basis for initial number PZB s (1988) Five- Factors with eigenvalues PZB s (1988) Five- PZB s (1988) Five- PZB s (1988) Five- Factors with eigenvalues of of factors extracted dimensional structure greater than 1 dimensional structure dimensional structure dimensional structure 1 or greater Reliability 0.87-0.90 Mean 0.75 (across 35 0.59-0.83 0.89-0.97 0.67-0.83 0.58-0.77 coefficients Scales derived through (Cronbach s alphas) factor analysis) Final number of Five Between six and eight LISREL model fit for Not clear five-dimensional Not clear Six dimensions dimensions depending five-dimensional structure factor structure; LISREL on setting poor (no alternative factor fit poor structures examined) Validity Convergent  Q (i.e. P-E) Not examined Not examined Not examined Convergent  total Q Not examined scores on the five scores (across all 22- dimensions explain 0.57- items) correlates 0.59 0.71 of variance in overall with overall quality quality on a ten-point scale. scores on a four-point scale. Concurrent  Q scores Concurrent  correlations related to hypothesized to of Q and P scores with presence of service quality satisfactory complaint solusion are 0.58 and 0.6 Table I. THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 69 Lytle and Mokwa Cronin and Taylor Brensinger and McAlexander et al. Study Bowers et al. (1994) (1992) (1992) Lambert (1990) O Connor et al. (1994) (1994) Data collection Patients of an army Customers of health-care Customers of banking, Purchasers of motor Entire medical staff, Patients of two independent study sample (s) hospital (fertility) services pest control, dry carrier services administrative staff, general dental offices cleaning, fast food patient-contact employees, and established adult patients of a physician- owned multispecialty group medical clinic Sample size 298 559 660 170 775 346 Questionnaire Similar to PZB (1988) Similar to PZB (1988) Similar to PZB (1988) Similar to PZB (1988) Similar to PZB (1988) Similar to PZB (1988) format format format and Cronin and Taylor (1992) Major wording No major changes No major changes, No major changes, No major changes No major changes No major changes changes except for language except normative changes and several expectation measure items added used for 22-attribute (what  should be ) Original SERVQUAL All 22 items, as well as 15 pairs of matching All 22 items All 22 items 22 items All 22 items item retained items in Caring and expectation-perception Outcomes items Response scale Seven-point scale Five-point scale Seven-point semantic Seven-point scale Seven-point scale Seven-point scale differential scale (Continued) Table II. Comparison of Parasuraman et al. (1985; 1988) studies with other SERVQUAL replication studies 70 THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 Lytle and Mokwa Cronin and Taylor Brensinger and McAlexander et al. Study Bowers et al. (1994) (1992) (1992) Lambert (1990) O Connor et al. (1994) (1994) Questionnaire Mail survey Mail survey In-home personal Mail survey Mail survey Mail survey administration interviews Data analysis Regression analysis Principal-axis factor Principal-axis factor Principal-axis factor Canonical discriminant LISREL Procedure for assessing analysis followed by analysis followed by analysis followed by functions factor structure oblique rotation; oblique rotation: oblique rotation LISREL confirmatory LISREL confirmatory Basis for initial Not examined Factors with eigenvalues PZB s (1988) five- PZB s (1988) five- PZB s (1988) five- PZB s (1988) five- number of factors greater than 1 dimensional structure dimensional structure dimensional structure dimensional structure extracted Findings reliability Not examined Overall high means 0.74-0.83 0.64-0.88 0.79-0.92 0.82 SERVQUAL to coefficients scores for the 0.91 SERVPERF (Cronbach s alphas) observable variables Final number of Five Seven Five Five Five Ten dimensions Validity Not examined Not examined Not examined Convergent  Q Not examined Not examined scores on the five dimensions explain: 0.39 of variance in four-point overall quality scale Table II. THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 71 Taylor and Cronin Walbridge and Licata et al. Fusilier and Bebko and Garg Study (1994) Delene (1993) (1995) Clow et al. (1995) Simpson (1995) (1995) Data collection Individuals in shopping Physicians on staff at Patients, primary care Households who had AIDS patients, social Patients in hospital study sample (s) malls who had used two major teaching physicians, and used dental services workers, and family nursing units hospital services within hospitals specialist physicians recently members, who were the last 45 days of a large regional involved with the hospital hospitalizations and had observed the nursing care provided Sample size 116 Study 1 212 558 240 27 262 227 Study 2 Questionnaire format Similar to PZB (1988) Similar to PZB (1988) Similar to PZB (1988) Similar to PZB (1988) Similar to PZB (1988) Similar to PZB (1988) format format Major wording Modified slightly to Two other determinants Modified slightly to No major changes No major changes No major changes changes reflect health care were added to reflect health care setting SERVQUAL items: setting core medical services and professionalism/ skills Original SERVQUAL 22 items 22 items 15 pairs of matching All 22 items 22 items 22 items item retained expectation-perception item Response scale Seven-point Likert scale Ten-point scale Five-point scale Seven-point Likert scale Seven-point scale Seven-point scale (Continued) Table III. Comparison of Parasuraman et al. (1985; 1988) studies with other SERVQUAL replication studies 72 THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 Taylor and Cronin Walbridge and Licata et al. Fusilier and Bebko and Garg Study (1994) Delene (1993) (1995) Clow et al. (1995) Simpson (1995) (1995) Questionnaire Personal interviews Mail survey Mail survey Mail survey Self-administered by Personal interviews administration respondent on-site Data analysis Factor analysis followed Tabulations + t-tests, One-way ANOVA, LISREL Tapes and notes were Loglinear model-difference Procedure for by oblique rotation, analysis of variance, principal components transcribed for coding between perceived and actual assessing factor two-stage least square reliability tests and factor analysis using bell response time (means structure correlations were varimax rotation, and t-tests) conducted MANOVA Basis for initial Five factors of expectation PZB s (1988) five- PZB s (1988) five- PZB s (1988) five- PZB s (1988) five- Not clear number of factors scale and four factors of dimensional structure dimensional structure dimensional structure dimensional structure extracted performance scale Findings reliability 0.74-0.96 (Study 1) 0.53-0.74 0.43-0.73 0.72-0.89 Interrater agreement Mean 0.69-317.29 coefficients 0.71-0.93 (Study 2) was 0.99 (Cronbach s alpha) Final number of Five Five from PZB, 12 Seven Five Not clear dimensions two from Haywood- Fourmer (1988) and Swartz and Brown (1988) Validity Not examined Not examined Not examined Not examined Not examined Not examined Table III. THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 73 measured, was explicitly assessed a priori in most studies (Babakus and Boller, 1992; Carman, 1990; Parasuraman et al., 1988). Typically, feedback from executives (in each of the participating companies) who reviewed the questionnaire confirmed that SERVQUAL  with minor wording changes in few items  had face validity. For example, Babakus and Boller (1992) confirmed the suitability of SERVQUAL for a utility company through preliminary discussions with customers and extensive interviews with company executives and technical personnel. In contrast, Carman s (1990) initial assessment of the scale resulted in his using a subset of the original 22 items (ranging from ten in the dental clinic setting to 17 in the tire store and placement center settings). Some studies do not explicitly discuss SERVQUAL s face validity (e.g. Babakus and Mangold, 1992; Finn and Lamb, 1991). However, the fact that all 22 SERVQUAL items were used in the studies implies support for the meaningfulness of the items in the settings involved. With few exceptions, the SERVQUAL items appear to be appropriate for assessing service quality in different settings. Convergent validity This relates to the extent to which different scale items assumed to represent a construct do in fact  converge on the same construct (Peter et al., 1993). The reliability of a scale as measured by coefficient alpha reflects the degree of cohesiveness among the scale items and is therefore an indirect indicator of convergent validity. As already stated, coefficient alpha values for the five SERVQUAL dimensions are fairly high across studies. Little proof of A more stringent test of convergent validity is whether scale items expected SERVQUAL s convergent to load together in a factor analysis do so (Peter et al., 1993). The factor- validity loading patterns in none of the studies are similar to that obtained in Parasuraman et al. (1988). Thus, there is little proof of SERVQUAL s convergent validity. Some evidence of convergent validity as reflected by the factor-loading patterns in these studies (Babakus and Boller, 1992; Carman, 1990; Headley and Miller, 1993) is weaker because several of SERVQUAL items had very low loadings on the dimensions they were supposed to represent. Finn and Lamb (1991) report overall fit statistics for the LISREL measurement model, but the authors do not provide a factor- loading matrix. For this reason, an assessment of convergent validity in their study by examining factor loadings is not feasible (Peter et al., 1993). Concurrent validity Performs well in This relates to the extent to which SERVQUAL scores are associated as concurrent validity hypothesized with conceptually related measures (Peter et al., 1993). Concurrent validity was examined in several studies (Babakus and Boller, 1992; Brensinger and Lambert, 1990). SERVQUAL performs well in this regard, with few exceptions. For example, in the Babakus and Boller (1992) study, perception scores have stronger correlations with other dependent measures (e.g. overall quality) than do the SERVQUAL scores (i.e. perception-minus-expectation scores). In another study by Brensinger and Lambert (1990) SERVQUAL scores received by motor carriers accounted for only 8 percent of the variance in the share of customers business obtained by those carriers. Several authors (Babakus and Boller, 1992; Carman, 1990; Teas, 1993) have called into question the empirical usefulness of the expectations data. As stated already in this paper, these authors also raise psychometric concerns about the appropriateness of using 74 THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 measures defined as difference scores in multivariate analyses (Parasuraman et al., 1990; 1991). Support for reliability In summary, the findings from studies provide some support for reliability and face validity scores and face validity for the SERVQUAL scores on the five dimensions. Brown et al. (1993) provide the following insights in their assessment of SERVQUAL. First, factor-analysis results relating to the convergent validity of the items representing each dimension are mixed because in several studies the highest loadings for some items were on different dimensions from those in Parasuraman et al. (1988). Second, lack of support for the discriminant validity of SERVQUAL is reflected by the factor-loading patterns, and the number of factors retained is inconsistent across studies. Third, the usefulness of expectation scores and the appropriateness of analyzing gap scores need to be examined. Fourth and last, the findings from across-study comparisons have very important implications for service quality researchers and SERVQUAL users. Managerial implications and recommendations In order to improve quality it is important to have a clear concept of what quality is and how to measure it. Our review of a number of SERVQUAL studies has considered those issues and in this section we discuss the applied value of the research from the practitioner s perspective. Quality has been an elusive concept, however the impressive body of SERVQUAL evidence suggests how consumers judge quality. Knowing how consumers make quality judgements can aid the practitioner in two vital ways. First, on a qualitative basis, knowing what constitutes quality can guide the business person by suggesting how quality might be enhanced. Second, on a quantative basis, the measurement of quality can provide specific data that can be used in quality management. Qualitative use of SERVQUAL How consumers are likely The SERVQUAL definition and concept of quality can aid the manager by to judge the quality of providing general knowledge of how consumers are likely to judge the the business quality of the business. Recall that in judging the quality of a service consumers consider categories of service attributes such as reliability and responsiveness. In addition, consumers take into consideration the level of performance that they think service firms should achieve on the service attributes, that is, consumers have quality expectations. Consumers also compare service-firm performance on the attributes to their expectations, and performance short of expectations signals low quality to the consumer. Recall that our review has suggested that the SERVQUAL dimensions are likely to be industry specific. A first step for practitioners is to see if their industry (hereafter: focal industry) has been included in the studies reviewed in this article or in other recent SERVQUAL work that identified dimensions. If so, the dimensions are known. If not, a decision must be made either to spend some time and money identifying dimensions (see the next subsection) or to select the industry that provides the best match and use those dimensions. With knowledge of the dimensions, the second basic step is to judge the expectations of customers on each dimension and how well the firm performs on the dimensions. Information both on expectations and performance may be obtained by talking to customers and service contact THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 75 employees who have direct experience in dealing with customers. Customer complaints and other communications with managers can be another source of qualitative data. Compare performance A third step is to compare performance with expectations to identify with expectations weakness, dimensions in which performance is short of expectations, where improvement is needed. Also strengths, those dimensions where performance meets or exceeds expectations, should be identified. Plans can be made to reduce weakness and use strengths to gain a competitive edge. Employees can be educated on what service quality consists of and how they can help to improve quality. Quantitative use of SERVQUAL The quantitative use of SERVQUAL can employ the same generic steps as outlined above: (1) determine the dimensions for the focal industry based on the literature or perform a study in which the dimensions are identified; (2) measure for the firm customer expectations and performance on the dimensions; (3) compare expectations with performance to identify strengths and weaknesses in service quality; and (4) take action to correct weaknesses and capitalize on strengths. Framework for judging In addition, a fifth step is to add a framework for judging quality data over quality data over time time and in comparison with other firms. Measuring quality over time is useful in order to see if improvements have been made or if expectations have changed. Comparable data could be obtained for competing firms in order to see how the focal firm is doing relative to competitors. The steps we have just mentioned will be of more value to managers to the extent that SERVQUAL measures are reliable and valid. Our review has discussed those properties of SERVQUAL in some detail. Recall that a reliable measure is one that is consistent, that is, if quality did not change, the measure of quality would not change. As shown in Tables I-III, the reliability of SERVQUAL has been reported for a wide set of industries and as an overall measure of service quality, across all 22 pairs of questions. Reliability has been consistently quite high suggesting that any change over time in the overall quality score is not likely to be just fluctuations in measurement. Reliability on most dimensions has been lower than for the entire set of items, but general reliability has been high enough to provide useful insights. However, if reliability is questionable for certain dimensions for the manager s industry, a fresh attempt to measure reliability may be warranted. Conclusion and summary This paper has attempted to review and integrate studies on service quality in these areas: " definition and measurement of service quality; and " reliability and validity measures. The reviews in the literature suggest that there is still more work to be done to find a suitable measure for service quality. There are more problems with the most popular measure, SERVQUAL, which involves the subtraction of subjects service expectations from the service delivery for specific items. 76 THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 The differences are averaged to produce a total score for service quality. Cronin and Taylor (1992) found that their measure of service performance (SERVPERF) produced better results than SERVQUAL. Their non- difference score measure consisted of the perception items used to calculate SERVQUAL scores. This measures assessed service quality without relying on the disconfirmation paradigm. Future research might examine the relative merit of this approach. There is an issue of whether a scale to measure service quality can be universally applicable across industries. Carman (1990), and Finn and Lamb (1991) note that it takes more than the simple adaptation of the SERVQUAL items to address service quality effectively in some situations. Managers are advised to consider which issues are very important to service quality in their specific environments and to modify the scale as needed. Much of the emphasis in recent research has moved from describing the data Move from describing to testing hypotheses. More elaborate research designs and analytical data to testing hypotheses techniques have been employed. The area seems to be quite challenging to researchers. The validity of data should be established in any study. The area needs improved conceptualization on key constructs and more comparable measures across research efforts. It is important to have a common scale or definition for valid comparison across studies. Future SERVQUAL-related research One fruitful and critical area for future research is the measurement of expectations and the related issue of computing perception-minus- expectation gap scores. Carman (1990) and Babakus and Boller (1992) discuss this subject and make several useful suggestions that are worthy of additional research. There are theoretical aspects to the pros and cons of measuring expectations and perceptions separately and then computing gap scores. From a theoretical standpoint, the appropriateness of using difference scores in multivariate analyses has been questioned on the grounds that such scores might suffer from low reliability and validity. Carman (1990) and Babakus and Boller (1992) echo this concern. However, the findings from various studies indicate that the gap scores along the five SERVQUAL dimensions possess adequate reliability as measured by Cronbach s alpha. Moreover, the studies that examined SERVQUAL s concurrent validity are barely supportive of the gap scores. The major inconsistencies across studies pertain to the factor structures of the gap scores. While the Brensinger and Lambert (1990) study is similar to Parasuraman et al. (1988) in this regard, the other studies are not. Therefore support for gap scores discriminant validity and, to some extent, convergent validity is not mixed (Parasuraman et al., 1990; 1991). Although the SERVQUAL dimensions represent five conceptually distinct Nature and causes of facets of service quality, they are also related, as evidenced by the need for relationships between facets of quality oblique rotations in the various studies to obtain the most interpretable factor patterns (Peter et al., 1993). Another fruitful area for future research is to explore the nature and causes of these interrelationships. Research directed at questions focussing on the nature of the interrelationships among the dimensions can potentially contribute to our understanding of service quality. THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 77 References Babakus, E. and Boller, G.W. (1992),  An empirical assessment of the SERVQUAL scale , Journal of Business Research, Vol. 24, pp. 253-68. Babakus, E. and Mangold, G.W. (1992),  Adapting the SERVQUAL scale to hospital services: an empirical investigation , Health Services Research, Vol. 26 No. 6, pp. 767-86. Bebko, C.P. and Garg, R.K. (1995),  Perceptions of responsiveness in service delivery , Journal of Hospital Marketing, Vol. 9 No. 2, pp. 35-45. Bitner, M.J. (1990),  Evaluating service encounters: the effects of physical surroundings and employee responses , Journal of Marketing, Vol. 54 No. 4, pp. 69-82. Bowers, M.R., Swan, J.E. and Koehler, W.F. (1994),  What attributes determine quality and satisfaction with health care delivery? , Health Care Management Review, Vol. 19 No. 4, pp. 49-55. Brensinger, R. and Lambert, D. (1990),  Can the SERVQUAL scale be generalized to business to business? , in Knowledge Development in Marketing, 1990 AMA s Summer Educators Conference Proceedings. Brown, S.W. and Swartz, T.A. (1989),  A gap analysis of professional service quality , Journal of Marketing, Vol. 53 No. 4, pp. 92-8. Brown, T.J., Churchill, G.A. and Peter, J.P. (1993),  Research note: improving the measurement of service quality , Journal of Retailing, Vol. 69 No. 1, pp. 126-39. Carman, J.M. (1990),  Consumer perceptions of service quality: an assessment of the SERVQUAL dimensions , Journal of Retailing, Vol. 66 No. 1, pp. 33-55. Clow, K. E., Fischer, A. K. and O Bryan, D. (1995),.  Patient expectations of dental services , Journal of Health Care Marketing, Vol. 15 No. 3, pp. 23-31. Cronin, J.J. and Taylor, S.A. (1992),  Measuring service quality: a reexamination and extension , Journal of Marketing, Vol. 56, July, pp. 55-68. Finn, D.W. and Lamb, C.W. (1991),  An evaluation of the SERVQUAL scale in retail setting , in Solomon, R.H. (Eds), Advances in Consumer Research, Vol 18, Association of Consumer Research, Provo, UT. Fusilier, M.R. and Simpson, P.M. (1995),  AIDS patients perceptions of nursing care quality , Journal of Health Care Marketing, Vol. 15 No. 1, pp. 49-53. Grönroos, C. (1983), Strategic Management and Marketing in the Service Sector, Marketing Science Institute, Boston, MA. Headley, D.E. and Miller, S.J. (1993),  Measuring service quality and its relationship to future consumer behavior , Journal of Health Care Marketing, Vol. 13 No. 4, pp. 32-41. Iacobucci, D., Grayson, K. and Ostrom, A. (1994),  Customer satisfaction fables , Sloan Management Review, Vol. 35 No. 4, pp. 93-6. Johns, G. (1981),  Difference scores measures of organizational behavior variables: a critique , Organizational Behavior and Human Performance, Vol. 27, June, pp. 443-63. Lehtinen, U. and Lehtinen, J.R. (1982),  Service quality: a study of quality dimensions , working paper, Service Management Institute, Helsinki. Licata, J.W., Mowen, J.C. and Chakraborty, G. (1995),  Diagnosing perceived quality in the medical service channel , Journal of Health Care Marketing, Vol. 15 No. 4, pp. 42-9. Lytle, R.S. and Mokwa, M.P. (1992),  Evaluating health care quality: the moderating role of outcomes , Journal of Health Care Marketing, Vol. 12 No. 1, pp. 4-14. McAlexander, J.H., Kaldenberg, D.O. and Koenig, H.F. (1994),  Service quality measurement: examination of dental practices sheds more light on the relationships between service quality, satisfaction, and purchase intentions in a health care setting , Journal of Health Care Marketing, Vol. 14 No. 3, pp. 34-40. O Connor, S., Shewchuk, R. and Bowers, M.R. (1993),  A model of service quality perceptions and health care consumer behavior , Journal of Health Care Marketing, forthcoming. O Connor, S.J., Shewchuk, R.M. and Carney, L.W. (1994),  The great gap: physicians perceptions of patient service quality expectations fall short of reality , Journal of Health Care Marketing, Vol. 14 No. 2, pp. 32-9. Oliver, R. (1980),  A cognitive model of the antecedents and consequences of satisfaction decisions , Journal of Marketing, Vol. 17 No. 10, pp. 460-69. Parasuraman, A., Berry, L.L. and Zeithaml, V. (1990),  An empirical examination of relationships in an extended service quality model , Marketing Service Institute working paper, pp. 90-112. 78 THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 Parasuraman, A., Berry, L.L. and Zeithaml, V. (1991),  Refinement and assessment of the SERVQUAL , Journal of Retailing, Vol. 67 No. 4, pp. 420-49. Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1985),  A conceptual model of service quality and its implications for future research , Journal of Marketing, Vol. 49, Fall, pp. 41-50. Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988),  SERVQUAL: a multi-item scale for measuring consumer perceptions of the service quality , Journal of Retailing, Vol. 64 No. 1, pp. 12-40. Peter, P.J. and Churchill, G.A. (1986),  Relationships among research design choices and psychometric properties of rating scales: a meta-analysis , Journal of Consumer Research, Vol. 23, February, pp. 1-10. Peter, P.J., Churchill, G.A. and Brown, T.J. (1993),  Caution in the use of difference scores in consumer research , Journal of Consumer Research, Vol. 19, March, pp. 655-62. Reidenbach, E.R. and Sandifer-Smallwood, B. (1990),  Exploring perceptions of hospital operations by a modified SERVQUAL approach , Journal of Health Care Marketing, Vol. 10 No. 4, pp. 47-55. Swartz, T.A. and Brown, S.W. (1989),  Consumer and provider expectations and experience in evaluating professional service quality , Journal of the Academy of Marketing Science, Vol. 17, Spring, pp. 189-95. Taylor, S.A. and Cronin, J.J. (1994),  Modeling patient satisfaction and service quality , Journal of Health Care Marketing, Vol. 14 No. 1, pp. 34-44. Teas, K.R. (1993),  Expectations, performance evaluation, and consumers perceptions of quality , Journal of Marketing, Vol. 57, October, pp. 18-34. Walbridge, S.W. and Delene, L.M. (1993),  Measuring physician attitudes of service quality , Journal of Health Care Marketing, Vol. 13 No. 1, pp. 7-15. Woodside, A.G., Frey, L.L. and Daly, R.T. (1989),  Linking service quality, customer satisfaction , Journal of Health Care Marketing, December, pp. 5-17. Patrick Asubonteng is at the Graduate School of Management and Department of Health Services Administration, The University of Alabama at Birmingham, Birmingham, Alabama, USA. Karl J. McCleary is at the Graduate School of Management and Department of Health Services Administration, the University of Alabama at Birmingham as well as an Assistant Professor of Health Services Management in the School of Medicine, The University of Missouri at Columbia, Columbia, Missouri, USA. John E. Swan is Birmingham Business Associates Professor of Marketing in the School of Business, the University of Alabama at Birmingham, Birmingham, Alabama, USA. THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 79 This summary has been Executive summary and implications for managers and executives provided to allow managers and executives SERVQUAL: if it ain t broke don t fix it! a rapid appreciation of Businesses now see service quality as an important way to differentiate their the content of this products from those of competitors. As a result much academic effort is article. Those with a given over to the measurement of service quality and Asubonteng, McCleary particular interest in the and Swan add to this body of literature with a review of perhaps the most topic covered may then well known and widely used service quality measure  SERVQUAL. read the article in toto to take advantage of the For the practical manager any measurement system needs simplicity, more comprehensive lucidness and flexibility. Sadly too many of the models, measures and description of the techniques that emerge from academia lack all or some of these features. research undertaken and Managers know (we hope) that, ultimately, the decision is theirs and that its results to get the full any research tool only gives guidance or illumination. Adding more benefit of the material complications tends to reduce the chance of a model s acceptance by the presented practitioner. SERVQUAL is popular with managers because it combines ease of application and flexibility with a clear and uninvolved theory. Managers know that results obtained using the model are probably not objective truth but also that they help identify the direction in which the firm should move and the elements which the service and operations manager should include in any strategy. For all its flaws, SERVQUAL uses ideas which we, as managers, can relate to  tangibility, empathy, responsiveness, reliability and assurance. The model works with either qualitative or quantitative input and provides a clear result through identifying gaps between what the consumer expects and what they actually get. In the end most managers will use a method they are comfortable with rather than a more complex approach claimed as more  robust . Until a better but equally simple model emerges SERVQUAL will predominate as a service quality measure. Asubonteng et al. appear to accept this observation although they do revisit the criticisms of SERVQUAL within the literature. Essentially these criticisms fall into two categories  the model s applicability to all service industries or situations and the lack of validity of the model especially in respect of the dependence or independence of the five main variables. The first of these criticisms suggests that the variables are not consistent across industries. Powpaka (JSM, Vol. 10 No. 2) revealed this problem in his assessment of service industries in Hong Kong and Min (JSM,Vol. 10 No. 3) showed how an alternative system specific to an industry might provide a better result. Ultimately managers should be aware that the model is generic and, as a result, factors specific to an industry need attention. However, the idea that there cannot be generalizations about service businesses is equally flawed. Too many managers reject new ideas or methods because  & things don t work that way in our business . In truth any service manager must consider services reliability and so on. The balance between the various elements of SERVQUAL may vary industry by industry but their relevance should not. The second set of criticisms are more academic. They concern themselves with whether the model stands up to tests of its validity and whether the five elements are sufficient or independent. Like any simple model (the classic 80 THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 4Ps approach to marketing planning springs to mind here) much effort focusses on trying to prove the model either wrong or incomplete. What is sometimes forgotten is that the very simplicity of the model means that the key areas for management to address stand out and are understood by all. Asubonteng et al. follow their review of these criticisms not, for once, by trying to  soup-up SERVQUAL or by proposing a new, overcomplicated methodology, but by showing how managers can incorporate the criticisms into their use of SERVQUAL. The authors set out steps to use the existing SERVQUAL applications to identify dimensions for study and then show how the model can be applied over time. By accepting that certain dimensions of SERVQUAL will prove more significant than others, Asubonteng et al. allow managers to flex the model still further making it a more effective planning tool. After all empathy is more important to hairdressers and reliability to fast-food outlets (Powpaka, JSM, Vol. 10 No. 1) and knowing this enables the choice of service delivery gaps to address becomes easier. Moreover, the authors examine both qualitative and quantitative applications of SERVQUAL. For many businesses starting out on the road to better service quality a qualitative approach makes more sense. Before resources are committed to further research, training and operational changes the manager needs a good feel for the extent of the problem. Ultimately, a quantitative measure is needed to provide the baseline for the measurement of service improvements but the initial qualitative measure means that service improvements can begin in parallel with the quantitative research. Finally, managers should remember that, however robust the statistical basis of the model used, the results merely guide. Research of this kind will not solve a problem of chronically poor service. The answers will illuminate the issues and help show what action might make rapid improvements possible. Too often managers look to research models such a SERVQUAL as proof positive rather than as a diagnostic tool. (Supplied by Marketing Consultants for MCB University Press) THE JOURNAL OF SERVICES MARKETING, VOL. 10 NO. 6 1996 81

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