Service Quality Case Study Vg

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Service Quality: A Case Study of a Bank LOTFOLLAH NAJJAR, UNIVERSITY OF NEBRASKA, OMAHA RAM R. BISHU, UNIVERSITY OF NEBRASKA, LINCOLN © 2006, ASQ

Today’s marketing environment is characterized by increased competition, uncertain economic conditions, and shifts in global trading relationships. The pressure to understand market conditions and customer requirements is growing to the point where organizations will be compelled to exceed, rather than simply meet, customer expectations. In adapting to this pressure, organizations are looking to service initiatives as a way to create or sustain competitive advantages. Measuring customer satisfaction is, therefore, critical to the process of serving the customer and responding faster and better than the competition. The objective of this article is to address the importance of improving service quality in the banking industry. A questionnaire was developed to identify underlying dimensions of bank quality and to assess consumers’ perceptions of the importance of each of these dimensions. Two large banks were selected, with five branches among them. Service quality questionnaires were sent to 800 customers; the overall response rate was 59 percent. A nondifference score of SERVQUAL was used to assess the dimensions of service quality. The results of the service quality analysis show that reliability and responsiveness are the two most critical dimensions of service quality, and they are directly related to overall service quality. Key words: banking industry, service quality

INTRODUCTION Service Quality Cronin and Taylor (1992) support the theory that service quality is an antecedent of customer satisfaction and customer satisfaction exerts a stronger influence on future purchase intentions than does service quality. Customers do not necessarily purchase the highest quality service; they may also weigh convenience, price, and availability factors (Cronin and Taylor 1992). The customer’s personal experience with the service provider (that is, courtesy, waiting time, empathy, responsiveness, and so on) also impacts customer satisfaction (Nowak 1997). Service jobs began exceeding manufacturing jobs in the United States in 1956. Today, service jobs dominate most U.S. business activity. Current Bureau of Labor statistics indicate that the service sector of the U.S. economy accounts for more than 75 percent of U.S. gross domestic product (GDP) and about 80 percent of all U.S. jobs. The industrial age has been replaced by the information age. Super-power economies are advancing with information and service sector growth, while developing economies are still dominated by smoke-stack manufacturing and agriculture. The important question is not whether service is the industry of the future, but rather: “Do U.S. business people understand the principles and practices of service quality well enough to fend off foreign competitors?” Clearly, U.S. business owners do not want to find themselves in a position of playing catch up to other nations, as they did in the 1980s with Japan’s electronics and automobile manufacturing quality. Anecdotal and scientific evidence, however, suggests U.S. business people may be repeating history. For example, the American Society for Quality, Arthur

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Service Quality: A Case Study of a Bank Andersen, and the University of Michigan’s Business School created the American Customer Satisfaction Index (ACSI), which conducts interviews with more than 50,000 consumers about satisfaction with some 200 companies in 35 industries. The ACSI report shows a consistent quarter-by-quarter decline in customer satisfaction since ACSI inception in 1994. Although the insurance industry saw a modest increase in 1998, most other service categories such as restaurants, hospitals, and banking have continued to decline (Lovelock and Wright 1999; Sweat and Hibbard 1999).

Service Quality and Banking Based on the ACSI data and other published studies, the banking industry may have some cause for concern. According to a survey of more than 800 bank customers, the majority believes that service has not improved over the past five years. In fact, many customers believe that customer service has gotten worse. Written complaints to banks were up 8.4 percent from the previous year, and bank customer satisfaction reports revealed that a quarter of all respondents found mistakes on their current accounts (Barret 1997). On the other hand, credit unions have generally received high marks for customer service. Dubroff (1998) cites a Gallup survey, which indicates that credit unions were ranked number one in customer service among all financial institutions for the 14th year in a row. Dubroff also notes that banks often argue the nonprofit status of credit unions in an attempt to obscure the real issues like customer service. There are many reasons for poor service quality across industries. One reason may be an inability to collect or use collected data. For example, in direct opposition to consumer opinion, bank executives perceive themselves and their companies to be doing an excellent job. For example, Allred and Addams (1999) asked executive officers at the top 100 U.S. banks and credits unions about their customer service performance. The researchers found that bank executives gave themselves consistently higher marks than credit union executives in all surveyed areas of customer service. This apparent discrepancy of opinion creates questions about banking service information-gathering effectiveness.

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Service Quality Determinants Goods quality is tangible and can be measured by objective indicators like performance, features, and durability. Service quality, however, is intangible. Hence, the service quality literature defines service quality in terms of subjectivity, attitude, and perception. Zeithaml (1987) explains: “Service quality is the consumer’s judgment about an entity’s overall excellence or superiority. It is a form of attitude, and results from a comparison of expectations to perceptions of performance received.” Lewis and Booms’ (1983) definition clearly states: “Service is a measure of how well the service level delivered matches customer expectations. Delivering quality service means conforming to customer expectation on a consistent basis.” Parasuraman, Zeithaml, and Berry (1985) provide a list of determinants of service quality: access, communication, competence, courtesy, credibility, reliability, responsiveness, security, understanding, and tangibles. The research team conducted a series of pilot studies and found a high degree of correlation between communication, competence, courtesy, credibility, and security. There is also a correlation between access and understanding. So, they combined them into two broad dimensions of assurance and empathy, that is, a total of five consolidated dimensions (Berry, Zeithaml, and Parasuraman 1985): • Reliability: The ability to perform the promised service dependably and accurately. • Responsiveness: The willingness to help customers and provide prompt service. • Assurance: The knowledge and courtesy of employees and their ability to convey trust and confidence. • Empathy: The caring, individualized attention provided to customers. • Tangibles: The appearance of physical facilities, equipment, personnel, and communication materials. They then used these five dimensions as the basis for their 22-item service quality measurement instrument

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Service Quality: A Case Study of a Bank called SERVQUAL, which was originally used for assessing customer perceptions of service quality in service and retailing organizations (Parasuraman, Zeithaml, and Berry 1994a). For each item, a difference score Q (representing perceived quality along that item) was defined as Q = P – E, where P and E are the rating on the corresponding perception and expectation statements, respectively. In 1993, it was argued that “SERVQUAL failed to achieve discriminate validity from its component and the nondifference score measure did not exhibit these problems (Parasuraman, Zeithaml, and Berry 1994b). Moreover, it displayed better than discriminate and nomological validity properties. In sum, it was the preferred alternative” (Brown, Churchill, and Peter 1993). Cronin and Taylor (1992; 1994) argue that measuring service quality using a performance-minus-expectations (SERVQUAL) basis is inappropriate and suggest that a performance-only (SERVPERF) measurement is a better method. Parasuraman, Zeithaml, and Berry (1994a), however, contend that the SERVQUAL scale using the expectations/performance gaps method is a much richer approach to measuring service quality and augment their earlier assertion (Parasuraman, Zeithaml, and Berry 1985; 1988; 1993) that service quality is a multidimensional rather than a unidimensional construct. Unfortunately, the conceptualization and measurement of service quality is not bereft of controversy. Although the debate on service quality began in 1985 in the marketing literature, it was given a major boost by Cronin and Taylor (1992). Subsequent work on service quality (Parasuraman, Zeithaml, and Berry 1993; Cronin and Taylor 1994; Avkiran 1994; Teas 1994; Newman and Cowling 1996; Yavas, Shemwell 1997) notwithstanding, the debate has not yet reached a point of resolution. In its wake, however, it has raised many issues for both academics and practitioners by providing important but somewhat conflicting insights into the conceptual, methodological, analytical, and practical issues related to the service quality concept. The five dimensions of service quality mentioned previously (tangibles, reliability, responsiveness, assurance, and empathy) were the basis for this research. For this research, a nondifference score measure was used for each dimension of service quality in order to achieve discriminate validity from its component.

Research Objective/Questions The objective of this research was to identify underlying dimensions of service quality in the banking industries and to assess the importance of each of these dimensions in the banking industries with the following hypotheses. • H01: The mean of each dimension of service quality does not differ across banks. • H02: The mean of each dimension of service quality does not differ among the branches of the same bank. • H03: The five dimensions of service quality are related to the overall service quality.

METHODOLOGY Survey Instrument The service quality questionnaire was obtained from the marketing department of bank A. It had been used several times in the past and was developed by academic experts. The questionnaire was developed to identify underlying dimensions of bank quality and to assess consumers’ perceptions of the importance of each of these dimensions. The questionnaire covered the five dimensions of service quality, including the overall service quality of the bank. Each question was rated using a Likert-type scale of 0 (poor) to 10 (excellent). This questionnaire has been used effectively in both public and private sectors. SERVQUAL was originally used for assessing customer perceptions of service quality in service and retailing organizations (Parasuraman 1993). For this research, a nondifference score measure was used and the score for each dimension of service quality was computed by taking the average score in items making up the dimension, in this case three items per dimension. The service quality questionnaire is shown in the Appendix.

Sampling and Data Collection Two large regional banks in Nebraska were selected (bank A with three branches and bank B with two branches). To get the cooperation of management and

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Service Quality: A Case Study of a Bank Figure 1 Service quality dimensions for banks.

Number of respondents

Response rate

A (branch 1)

160

92

58%

A (branch 2)

160

81

51%

A (branch 3)

160

73

47%

B (branch 1)

160

117

73%

B (branch 2)

160

105

66%

10 9 8 7 6 5

Table 2 Service quality (All banks). Dimensions

Mean

Std Dev

Responsiveness

7.8625

0.8576

Reliability

7.8219

0.8389

Overall

7.7543

0.8390

Assurance

7.6702

0.7472

Empathy

7.6474

1.1382

Tangible

6.9637

0.8537

Note: Customers were asked to choose the top two

the marketing department they were informed of the objective of the research and how it would benefit them and the organization. A sample of 800 customers was randomly selected from five branches and the service quality questionnaires were mailed to them. The overall response rate was 59 percent. Table 1 shows the breakdown of sample sizes and response rates for the banks and the branches.

Nonresponse Bias To encourage nonrespondents to participate, the first follow-up was conducted by mail and the service quality questionnaires were sent to the customers; 73 responses were received, giving a response rate of 22 percent. The second follow-up was conducted by mail, including an invitation from the bank’s president encouraging customer participation in the survey and emphasizing the importance of the research project. For the second

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Bank A

Mean

Banks

Number of contacted customers

Bank B

Reli Resp Assu Emp Tang Over Dimensions

follow-up survey 75 responses were received, giving a combined response rate of 46 percent for the first and second follow-up. Each set of responses was further divided as “sample 1” and “sample 2.” To assess the nonresponse bias a t-test was performed on both samples using five dimensions of service quality, as well as the overall service quality. No significant differences between the two samples were found.

RESULTS Descriptive Statistics As shown in Table 2, responsiveness, reliability, and overall service quality, respectively, are the most important dimensions of service quality for all the banks based on the mean values. Figure 1 shows that bank A has a higher mean value for all the dimensions of service quality than bank B. • Responsiveness: Figures 2 and 3 show that branch 3 within bank A has a higher mean value than branches 1 and 2 (branch 2 has the lowest) for this dimension. Also, branch 2 within bank B has a higher mean value than branch 1 for this dimension. • Empathy: Figures 2 and 3 show that branch 3 within bank A has a higher mean value than branches 1 and 2 (with branch 1 the lowest) for this dimension. Branch 2 within bank B has a higher mean value than branch 1 for this dimension. • Tangible: Figures 2 and 3 show that branches 2 and 3 within bank A have a higher mean value than branch 1(branch 1 has the lowest) for this dimension.

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Table 1 Customers’ response rate.

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Service Quality: A Case Study of a Bank Figure 2 Service quality dimensions for Bank A. 9 Branch 1

8

Branch 2

7 6

Branch 3 Reli Resp Assu Emp Tang Over Mean

Figure 3 Service quality dimensions for Bank B.

Dimensions

Cronbach α

Reliability

0.79

Responsiveness

0.83

Assurance

0.76

Empathy

0.77

Tangible

0.88

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Table 3 Reliability coefficient for dimensions of service quality.

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Dimensions

8 Branch 1

7

6

Branch 2

Reli Resp Assu Emp Tang Over Dimensions

Reliability Test A measure of construct reliability (Cronbach’s alpha) was computed for each dimension to assess the reliability of the set of items forming that dimension. These α coefficients range from 0.76 to 0.88 (see Table 3 and Appendix). As a rule, alphas of 0.70 or greater represent satisfactory reliability of the items measuring the construct (dimension). Thus, the items measuring the dimensions appear to be sufficiently reliable.

Assessment of Dimensionality The next step of analyses involves an assessment of dimensionality. Bagozzi’s rules for “convergence” and “discrimination” indicate that items representing a distinct dimension should correlate highly with each other in a uniform pattern, and should not correlate as strongly with items representing another dimension (Bagozzi 1981). Sample correlation (Q1-Q15) is shown in Table 4. The correlation matrix follows Bagozzi’s rule.

Factor Analysis Factor analysis was performed using five factor solutions (five common factors), since there are five dimensions of

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Mean

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service quality, as was observed in the original SERVQUAL study. Another convention frequently encountered in packaged computer programs is to set m (number of common factors) equal to the number of eigenvalues of R (correlation matrix) greater than one. The best approach is to retain few rather than many factors, assuming they provide a satisfactory interpretation of the data and yield a satisfactory fit to R (correlation matrix) (Johnson and Wichern 1982). The main purpose of factor analysis is to describe, if possible, the covariance relationships among many variables in terms of a few underlying, but unobservable, random quantities called factors. Factor analysis can be considered an extension of principal component analysis. Both can be viewed as attempts to approximate the covariance matrix. However, the approximation based on the factor analysis model is more elaborate. The primary question in factor analysis is whether the data are consistent with a prescribed structure (Johnson and Wichern 1982). In this article only five factors were chosen with eigenvalues of more than one, as shown in Table 5. The five-factor solution was subjected to Varimax rotation and the rotated factor loading matrices are shown in Table 6. An orthogonal transformation of the factor loadings, and the implied orthogonal transformation of the factors, is called factor rotation, and rotating factors often reveal a simple structure and aid interpretation. The general pattern of loadings in Table 6 for five dimensions (15 items) is fairly stable. Ideally one would like to see a pattern of loadings such that each variable loads highly on a single factor and has small-tomoderate loadings on the remaining factors (Johnson

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Service Quality: A Case Study of a Bank Table 4 Correlations (Pearson). Q1

Q2

Q3

Q4

Q5

Q6

Q7

Q8

Q9

Q10

Q2

28

Q3

45

47

Q4

27

43

59

Q5

12

37

37

70

Q6

1

29

25

50

67

Q7

33

26

35

33

21

22

Q8

24

25

23

35

30

47

55

Q9

18

21

16

26

27

26

48

55

Q10

18

18

20

23

21

24

39

26

29

Q11

8

6

12

-10

-1

6

12

4

3

12

Q12

8

12

20

19

17

17

37

21

28

28

Q13

-15

-9

-8

-13

-4

-9

-12

-16

4

0.4

Q14

-5

-3

-1

8

-5

-7

-10

7

Q15

9

-3

-9

-4

3

-1

-5

0.5 -8

-0.4

Q11

Q12

Q13

Q14

5 -12

4

2

7

-3

13

6

15

-1

-19

-12

Note: Correlations are multiplied by 100.

and Wichern 1982). Reliability (Q1-Q3) has a large loading on the third factor, responsiveness (Q4-Q6) on the first factor, assurance (Q7-Q9) on the second factor, empathy (Q10-Q12) on the fourth factor, and tangible (Q13-Q15) on the fifth factor. It is not always possible to get this structure, although the Varimax rotated loadings in this example provide a nearly ideal pattern.

The General Linear Models

• Responsiveness: Table 7 shows that this dimension of service quality for bank A is significantly different from bank B, but this dimension of service quality for all the branches within each bank is the same except for branches 2 and 3 within bank A. • Assurance: Table 7 shows that this dimension of service quality for bank A is significantly different from bank B, but this dimension of service quality for all the branches within each bank is the same.

The general linear models procedure of ANOVA was used to see the differences of dimensions of service quality between banks and among the branches. The branches were nested within the banks. The level of significance was established at 0.05. The following table shows the ANOVA summary.

• Empathy: Table 7 shows that the two banks and all the branches differ in this dimension of service quality.

• Reliability: Table 7 shows that the reliability dimension for bank A is significantly different from bank B, but the reliability dimension for all the branches within each bank is the same.

• Overall service quality: Table 7 shows that the two banks differ in this dimension of service quality, but all the branches within each bank are the same in terms of overall service quality dimension.

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• Tangible: Table 7 shows that the two banks differ in this dimension of service quality. Only branches 1 and 2 within bank B are the same in terms of tangible dimension.

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Service Quality: A Case Study of a Bank

Stepwise regression analysis was used for linking overall service quality as a dependent variable and five dimensions of service quality (reliability, responsiveness, assurance, empathy, and tangible) as independent variables. The following results were found as shown in Table 8. For all banks, reliability and responsiveness were both significant with R2 = 0.87. For bank A, reliability was significant with R2 = 0. 81. For bank B, reliability was significant with R2 = 0. 81. For bank A’s branch 1, reliability and responsiveness were both significant with R2 = 0. 81. For bank A’s branch 2, reliability was significant with R2 = 0. 83. For bank A’s branch 3, reliability was significant with R2 = 0. 81. For bank B’s branch 1, reliability and responsiveness were both significant with R2 = 0. 80. For bank A’s branch 2, reliability was significant with R2 = 0. 81.

Table 5 Principal component analysis. Varimax rotation

Factor 1

Factor 2

Factor 3

Factor 4

Factor 5

Eigenvalue

2.487

2.342

2.256

1.395

1.136

Proportion

0.17

0.16

0.14

0.09

0.08

Cumulative

0.17

0.33

0.47

0.56

0.64

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Regression

Table 6 Factor analysis (Varimax rotation). Variable

Factor Factor Factor Factor Factor 1 2 3 4 5

Reliability Q1 Q2 Q3

37 27

Responsiveness Q4 Q5 Q6

70 88 85

DISCUSSIONS AND CONCLUSIONS

Assurance Q7 Q8 Q9

The results show that reliability and responsiveness are the two most critical dimensions of service quality and they are directly related to overall service quality. Responsiveness and reliability have been shown to be important factors, supporting previous work by Berry, Zeithaml, and Parasuraman (1985) and Avkiran (1994). Allred and Addams (2000) conducted a similar study in a banking industry in a midwestern city and discovered that assurance, reliability, and responsiveness are the most critical dimensions of service quality. Johnston (1997) conducted a study in the U.K. banking industry to combine the classification of quality factors into satisfiers and dissatisfiers together with relative importance. The factors that may delight customers tend to be concerned more with the intangible nature of the service, commitment, attentiveness, friendliness, care, and courtesy. The main sources of dissatisfaction appear to be cleanliness, aesthetics, integrity, responsiveness, reliability, and security, which are associated with either the more tangible aspects of service or systemic issues. Thus, reliability and responsiveness dimensions of service quality have been shown to be important factors, supporting previous works.

Empathy Q10 Q11 Q12

34

76 60 81 50

-75 -67 -75

36 26

-59

75 77 78

-58

Tangible Q13 Q14 Q15

65 -76 66

Note: All numbers in the table are magnitudes of factor loadings multiplied by 100. Loadings of .25 or less are not shown.

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Table 7 ANOVA table for service quality. Dependent variables Assurance Empathy Overall Reliability Responsiveness Tangible

Independent variables Bank Branches

* * * * * *

*

* *

Note: * = statistically significant at 0.01 level of significance

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Service Quality: A Case Study of a Bank Service quality tools that were used in Table 8 Regression (overall service quality vs. five dimensions this research have been used extensively in of service quality). the other service industries as well as the Stepwise selections R-sq manufacturing industries. The fiveAll banks Overall = .25 + .91 Reliability + .05 Responsiveness .87 dimensional structure could possibly serve as a meaningful framework for tracking a Bank A Overall = .63 + .91 Reliability .81 firm’s service quality performance over Bank B Overall = .768 + .89 Reliability .81 time and comparing this performance Bank A (branch 1) Overall = .14 + .86 Reliability + .11 Responsiveness .81 against the performance of competitors Bank A (branch 2) Overall = .60 + .921 Reliability .83 (Parasuraman, Berry, and Zeithaml 1993). The wording of some individual Bank A (branch 3) Overall = .236 + .96 Reliability .81 items may need to be customized to each Bank B (branch 1) Overall = .77 + .81 Reliability + .082 Responsiveness .80 service setting, and items on some dimenBank B (branch 2) Overall = .009 + .992 Reliability .81 sions should be expanded if necessary for reliability. As was shown before, the response rate of customers from bank B is higher than bank A, and this may cause Reliability is an obvious place to start. Customers want differential biases in data collection. Since the sample to know their resources are safe and within trustworthy sizes are large enough and data are normalized, the institutions. A way to ensure this peace of mind would differential biases in data collection should not have an be to take steps to ensure bank employees are well effect on the analysis. One explanation might be that trained, so each bank associate is able to offer complete bank B customers had a high morale and were satisfied and comprehensive information at all times. Consistent with the service quality or very dissatisfied with the policies combined with a knowledgeable staff will foster service quality. a high degree of institutional cohesion and reliability. Tracking customers and developing creative strateResponsiveness, again when associated with a gies to retain them is very profitable. For example, in well-trained staff and timely answers to service-related 1982, Charles Cawley, the president of the credit card questions, would make significant inroads into causing company MBNA of America, became increasingly various banking institutions be regarded as responsive. frustrated by numerous complaints from defecting Staff should be encouraged to present relevant options customers and took action. Cawley announced to all to banking customers in a manner that does not MBNA employees that the mission of the company resemble salesmanship so much as a desire to serve. would be to keep every customer. To accomplish this Intangibles please customers just as much as tangigoal, a strategy was implemented to call defecting bles in the banking industry. People tend to visit the customers personally and obtain information about same branch of a bank over and over again. Usually, the reason for their defection. Chronic problems were this is a location close to their home or their workplace. determined and prioritized; appropriate changes It is natural that customers become comfortable and were implemented. Eight years later, MBNA’s defechabituated to these branch banks, for the same reason tion rate was reduced to just 5 percent, one of the they develop familiarity with a neighborhood superlowest in the industry. Without making any acquisimarket or convenience store. It makes sense that bank tions, MBNA’s industry ranking went from 38 to 4, and employees would be encouraged to learn to recognize profits increased 16-fold (Reichheld and Sasser 1990). these regular customers, learn their names, and begin Many studies indicate that it costs eight to 10 times to identify their basic service requirements. less to keep a customer than to develop a new one. Learning to understand customers needs will allow Thus, improving service quality leads to the customer bank associates to offer enhanced services, perhaps satisfaction and, ultimately, to customer loyalty.

RECOMMENDATIONS

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Service Quality: A Case Study of a Bank lowering customers’ banking costs and increasing their investment potential. This could also open up the possibility of increased profits for banks, for when perceived as more service and customer oriented, they will, in effect, become a useful and pleasant way to “shop.” In essence, this article argues for continued decentralization of banking services, which would allow convenient access and yet the old-fashioned service of a smaller community. Keeping these smaller branch locations presentable and up-to-date technologically are important factors. The idea of increasing multiple maintenance expenses, in terms of staffing, technology, and the cosmetic upkeep of many branches, must be regarded as a cost of doing business. If the staff inside is pleasant and well-informed, in an aesthetically pleasing environment, then customer satisfaction will be high. Many financial institutions are trending in this direction, even in the face of large banking organizations merging. It will be difficult to merge these two trends, and in the end, a choice may have to be made between service quality and economies of scale. Access has been improved through online banking, though convenience has come at the expense of individualized service. Online banking has not been a universal conversion. Not everyone is convinced of Internet security, and banks must aggressively deal with this issue to enhance perceptions of safety, reliability, and security. The five-dimensional structure could possibly serve as a meaningful framework for tracking a firm’s service quality performance over time and comparing it against the performance of competitors. The wording of some individual items may need to be customized to each service setting. Items on some dimensions should be expanded if that is necessary for reliability. Thus, the banking industries must continuously measure and improve these dimensions in order to gain customers’ loyalty.

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Allred, A., and H. L. Addams. 2000. Service quality at banks and credit unions: What do their customers say? Managing Service Quality 10, no. 1: 52-60.

Parasuraman, A., V. A. Zeithaml, and L. L. Berr y. 1993. SERVQUAL: A multiple item scale for measuring consumer perception of service quality. Journal of Retailing 69, no. 1: 127-139.

Allred, A., and H. L. Addams. 1999. Cost containment and customer retention practices at the top 100 commercial banks, savings institutions, and credit unions. Managing Service Quality 9, no. 5: 15-21.

Parasuraman, A., L. L. Berr y, and V. A. Zeithaml. 1993. Research note: More on improving service quality measurement. Journal of Retailing 69 (Spring): 140-7.

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Service Quality: A Case Study of a Bank Parasuraman, A., V. Zeithaml, and L. Berry. 1988. SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing 64 (Spring): 12-40. Parasuraman, A., V. Zeithaml, and L. Berry. 1985. A conceptual model of service quality and its implications for future research. Journal of Marketing 49 (Fall): 41-50. Reichheld, F.F., and W. E. Sasser. 1990. Zero defections: Quality comes to services. Harvard Business Review: 105-11. Sweat, J., and J. Hibbard. 1999. Businesses are spending heavily on customer service, but many aren’t getting the job done—customer disservice. Information Week (21 June). Teas, K. R. 1994. Expectations as a comparison standard in measuring service quality: An assessment of a reassessment. Journal of Marketing 58 (January): 132-9. Yavas, U., and D. J. Shemwell 1997. Meeting the service quality challenge: Structural problems and solutions. Managing Service Quality 7, no. 4: 198-203. Zeithaml, V. 1987. Defining and relating price, perceived quality, and perceived value. Report no. 87-101. Cambridge, Mass.: Marketing Science Institute.

BIOGRAPHIES Lotfollah Najjar is an assistant professor in the college of information science and technology at university of Nebraska at Omaha. Najjar’s research interests center on: quality information systems (data quality) in the service and manufacturing industries; business process reengineering and IT; data mining; and total quality management and IT in both service and manufacturing industries. His teaching interests include quality information systems; business process reengineering and IT; business data communications; introduction to management information system, quality control, operations management; statistics; and mathematics. He began teaching at UNO in 1989. Najjar earned a doctorate in industrial management systems engineering with a minor in MIS from the University of Nebraska-Lincoln in 2002. He may be contacted by e-mail at [email protected] . Ram Bishu is a professor in the college of engineering at the University of Nebraska–Lincoln. Bishu’s research interests center on ergonomics, information processing, total quality management, and quality control. His teaching interests include quality control, ergonomics, design of experiments, and operations management. Bishu earned a doctorate in industrial management systems engineering from SUNY Buffalo in 1985. He may be contacted by e-mail at [email protected] .

APPENDIX Customer questionnaire Please show the extent to which you think your bank offers the following services. On a scale of 0 to 10, please circle the appropriate rating. Poor 1. Serving you quickly and efficiently 0 1 2. Handling your transaction accurately 0 1 3. Being dependable 0 1 4. Providing clear explanations of services 0 1 5. Solving problems/troubleshooting 0 1 6. Understanding your banking needs 0 1 7. Thanking you for your business 0 1 8. Feeling secure doing business here 0 1 9. Making it easy to do business here 0 1 10. Greeting & acknowledging you promptly 0 1 11. Addressing you by name 0 1 12. Providing friendly and caring service 0 1 13. The location of our bank to you is 0 1 14. Having up-to-date equipment 0 1 15. Accessibility to ATM 0 1 16. Overall service quality 0 1 Thank You

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Najjar