Service quality-bank-case-study-vg

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, INTRODUCTION
and shifts in global trading relationships. The pressure to
understand market conditions and customer require-
ments is growing to the point where organizations will be
Service Quality
compelled to exceed, rather than simply meet, customer Cronin and Taylor (1992) support the theory that service
expectations. In adapting to this pressure, organizations quality is an antecedent of customer satisfaction and cus-
are looking to service initiatives as a way to create or tomer satisfaction exerts a stronger influence on future
sustain competitive advantages. Measuring customer purchase intentions than does service quality. Customers
satisfaction is, therefore, critical to the process of serving
the customer and responding faster and better than the
do not necessarily purchase the highest quality service;
competition. they may also weigh convenience, price, and availability
factors (Cronin and Taylor 1992). The customer’s per-
The objective of this article is to address the importance
of improving service quality in the banking industry.
sonal experience with the service provider (that is,
A questionnaire was developed to identify underlying courtesy, waiting time, empathy, responsiveness, and so
dimensions of bank quality and to assess consumers’ on) also impacts customer satisfaction (Nowak 1997).
perceptions of the importance of each of these dimen- Service jobs began exceeding manufacturing jobs in
sions. Two large banks were selected, with five branches the United States in 1956. Today, service jobs dominate
among them. Service quality questionnaires were sent to
most U.S. business activity. Current Bureau of Labor sta-
800 customers; the overall response rate was 59 percent.
A nondifference score of SERVQUAL was used to assess the tistics indicate that the service sector of the U.S. economy
dimensions of service quality. The results of the service accounts for more than 75 percent of U.S. gross domestic
quality analysis show that reliability and responsiveness product (GDP) and about 80 percent of all U.S. jobs. The
are the two most critical dimensions of service quality, industrial age has been replaced by the information age.
and they are directly related to overall service quality. Super-power economies are advancing with information
Key words: banking industry, service quality 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 them-
selves 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

www.asq.org 35

Service Quality: A Case Study of a Bank

Andersen, and the University of Michigan’s Business
School created the American Customer Satisfaction Service Quality Determinants
Index (ACSI), which conducts interviews with more than Goods quality is tangible and can be measured by
50,000 consumers about satisfaction with some 200 objective indicators like performance, features, and
companies in 35 industries. The ACSI report shows a durability. Service quality, however, is intangible.
consistent quarter-by-quarter decline in customer satis- Hence, the service quality literature defines service
faction since ACSI inception in 1994. Although the quality in terms of subjectivity, attitude, and perception.
insurance industry saw a modest increase in 1998, most Zeithaml (1987) explains:
other service categories such as restaurants, hospitals, “Service quality is the consumer’s judgment about
and banking have continued to decline (Lovelock and an entity’s overall excellence or superiority. It is a
Wright 1999; Sweat and Hibbard 1999). form of attitude, and results from a comparison
of expectations to perceptions of performance
Service Quality and Banking received.”
Lewis and Booms’ (1983) definition clearly states:
Based on the ACSI data and other published studies, the
banking industry may have some cause for concern. “Service is a measure of how well the service
According to a survey of more than 800 bank customers, level delivered matches customer expectations.
the majority believes that service has not improved over Delivering quality service means conforming
the past five years. In fact, many customers believe that to customer expectation on a consistent basis.”
customer service has gotten worse. Written complaints Parasuraman, Zeithaml, and Berry (1985) provide a
to banks were up 8.4 percent from the previous year, list of determinants of service quality: access, communi-
and bank customer satisfaction reports revealed that cation, competence, courtesy, credibility, reliability,
a quarter of all respondents found mistakes on their responsiveness, security, understanding, and tangibles.
current accounts (Barret 1997). On the other hand, The research team conducted a series of pilot studies
credit unions have generally received high marks for and found a high degree of correlation between com-
customer service. Dubroff (1998) cites a Gallup sur- munication, competence, courtesy, credibility, and
vey, which indicates that credit unions were ranked security. There is also a correlation between access and
number one in customer service among all financial understanding. So, they combined them into two broad
institutions for the 14th year in a row. Dubroff also dimensions of assurance and empathy, that is, a total
notes that banks often argue the nonprofit status of of five consolidated dimensions (Berry, Zeithaml, and
credit unions in an attempt to obscure the real issues Parasuraman 1985):
like customer service.
• Reliability: The ability to perform the promised
There are many reasons for poor service quality across
service dependably and accurately.
industries. One reason may be an inability to collect or
use collected data. For example, in direct opposition to • Responsiveness: The willingness to help customers
consumer opinion, bank executives perceive themselves and provide prompt service.
and their companies to be doing an excellent job. For • Assurance: The knowledge and courtesy of employees
example, Allred and Addams (1999) asked executive and their ability to convey trust and confidence.
officers at the top 100 U.S. banks and credits unions
• Empathy: The caring, individualized attention
about their customer service performance. The
provided to customers.
researchers found that bank executives gave themselves
consistently higher marks than credit union executives • Tangibles: The appearance of physical facilities,
in all surveyed areas of customer service. This apparent equipment, personnel, and communication materials.
discrepancy of opinion creates questions about banking They then used these five dimensions as the basis for
service information-gathering effectiveness. their 22-item service quality measurement instrument

36 QMJ VOL. 13, NO. 3/© 2006, ASQ


called SERVQUAL, which was originally used for assess-
ing customer perceptions of service quality in service and Research Objective/Questions
retailing organizations (Parasuraman, Zeithaml, and The objective of this research was to identify underlying
Berry 1994a). For each item, a difference score Q (repre- dimensions of service quality in the banking industries
senting perceived quality along that item) was defined and to assess the importance of each of these dimen-
as Q = P – E, where P and E are the rating on the corre- sions in the banking industries with the following
sponding perception and expectation statements, hypotheses.
respectively. In 1993, it was argued that “SERVQUAL • H01: The mean of each dimension of service quality
failed to achieve discriminate validity from its component does not differ across banks.
and the nondifference score measure did not exhibit
• H02: The mean of each dimension of service quality
these problems (Parasuraman, Zeithaml, and Berry
does not differ among the branches of the same bank.
1994b). Moreover, it displayed better than discriminate
and nomological validity properties. In sum, it was the • H03: The five dimensions of service quality are
preferred alternative” (Brown, Churchill, and Peter 1993). related to the overall service quality.
Cronin and Taylor (1992; 1994) argue that measuring
service quality using a performance-minus-expectations
(SERVQUAL) basis is inappropriate and suggest that a
METHODOLOGY
performance-only (SERVPERF) measurement is a better
method. Parasuraman, Zeithaml, and Berry (1994a), Survey Instrument
however, contend that the SERVQUAL scale using the The service quality questionnaire was obtained from
expectations/performance gaps method is a much richer the marketing department of bank A. It had been used
approach to measuring service quality and augment several times in the past and was developed by aca-
their earlier assertion (Parasuraman, Zeithaml, and demic experts. The questionnaire was developed to
Berry 1985; 1988; 1993) that service quality is a multi- identify underlying dimensions of bank quality and to
dimensional rather than a unidimensional construct. assess consumers’ perceptions of the importance of each
Unfortunately, the conceptualization and measure- of these dimensions. The questionnaire covered the five
ment of service quality is not bereft of controversy. dimensions of service quality, including the overall
Although the debate on service quality began in 1985 in service quality of the bank. Each question was rated
the marketing literature, it was given a major boost by using a Likert-type scale of 0 (poor) to 10 (excellent).
Cronin and Taylor (1992). Subsequent work on service This questionnaire has been used effectively in both
quality (Parasuraman, Zeithaml, and Berry 1993; public and private sectors.
Cronin and Taylor 1994; Avkiran 1994; Teas 1994; SERVQUAL was originally used for assessing customer
Newman and Cowling 1996; Yavas, Shemwell 1997) perceptions of service quality in service and retailing
notwithstanding, the debate has not yet reached a point organizations (Parasuraman 1993). For this research,
of resolution. In its wake, however, it has raised many a nondifference score measure was used and the score
issues for both academics and practitioners by providing for each dimension of service quality was computed by
important but somewhat conflicting insights into the taking the average score in items making up the
conceptual, methodological, analytical, and practical dimension, in this case three items per dimension. The
issues related to the service quality concept. service quality questionnaire is shown in the Appendix.
The five dimensions of service quality mentioned
previously (tangibles, reliability, responsiveness, assur-
ance, and empathy) were the basis for this research. For Sampling and Data Collection
this research, a nondifference score measure was used Two large regional banks in Nebraska were selected
for each dimension of service quality in order to achieve (bank A with three branches and bank B with two
discriminate validity from its component. branches). To get the cooperation of management and

www.asq.org 37


Table 1 Customers’ response rate. Figure 1 Service quality dimensions for banks.
Number of 10
contacted Number of Response
Banks customers respondents rate 9
8 Bank A

Mean
A (branch 1) 160 92 58%
7 Bank B
A (branch 2) 160 81 51% 6

© 2006, ASQ
5
A (branch 3) 160 73 47% Reli Resp Assu Emp Tang Over
Dimensions

© 2006, ASQ
B (branch 1) 160 117 73%

B (branch 2) 160 105 66% follow-up survey 75 responses were received, giving a
combined response rate of 46 percent for the first and
second follow-up.
Table 2 Service quality (All banks). Each set of responses was further divided as “sam-
Dimensions Mean Std Dev ple 1” and “sample 2.” To assess the nonresponse bias
a t-test was performed on both samples using five
Responsiveness 7.8625 0.8576
dimensions of service quality, as well as the overall
Reliability 7.8219 0.8389 service quality. No significant differences between the
Overall 7.7543 0.8390 two samples were found.
Assurance 7.6702 0.7472

Empathy 7.6474 1.1382 RESULTS
© 2006, ASQ

Tangible 6.9637 0.8537

Note: Customers were asked to choose the top two
Descriptive Statistics
As shown in Table 2, responsiveness, reliability, and
overall service quality, respectively, are the most impor-
the marketing department they were informed of the tant dimensions of service quality for all the banks
objective of the research and how it would benefit them based on the mean values.
and the organization. A sample of 800 customers was Figure 1 shows that bank A has a higher mean
randomly selected from five branches and the service value for all the dimensions of service quality than
quality questionnaires were mailed to them. The over- bank B.
all response rate was 59 percent. Table 1 shows the • Responsiveness: Figures 2 and 3 show that
breakdown of sample sizes and response rates for the branch 3 within bank A has a higher mean value
banks and the branches. than branches 1 and 2 (branch 2 has the lowest) for
this dimension. Also, branch 2 within bank B has a
Nonresponse Bias higher mean value than branch 1 for this dimension.
• Empathy: Figures 2 and 3 show that branch 3
To encourage nonrespondents to participate, the first
follow-up was conducted by mail and the service quality within bank A has a higher mean value than
questionnaires were sent to the customers; 73 responses branches 1 and 2 (with branch 1 the lowest) for this
were received, giving a response rate of 22 percent. The dimension. Branch 2 within bank B has a higher
second follow-up was conducted by mail, including mean value than branch 1 for this dimension.
an invitation from the bank’s president encouraging • Tangible: Figures 2 and 3 show that branches 2 and
customer participation in the survey and emphasizing 3 within bank A have a higher mean value than
the importance of the research project. For the second branch 1(branch 1 has the lowest) for this dimension.

38 QMJ VOL. 13, NO. 3/© 2006, ASQ


Figure 2 Service quality dimensions for Bank A. Table 3 Reliability coefficient for dimensions of
service quality.
9
Dimensions

Branch 1 Dimensions Cronbach α
8
Branch 2
7 Reliability 0.79
Branch 3

© 2006, ASQ
6 Responsiveness 0.83
Reli Resp Assu Emp Tang Over
Mean Assurance 0.76

© 2006, ASQ
Empathy 0.77

Figure 3 Service quality dimensions for Bank B. Tangible 0.88

8
service quality, as was observed in the original SERVQUAL
Branch 1 study. Another convention frequently encountered in
Mean

7
Branch 2 packaged computer programs is to set m (number of
common factors) equal to the number of eigenvalues of
© 2006, ASQ

6 R (correlation matrix) greater than one. The best
Reli Resp Assu Emp Tang Over
approach is to retain few rather than many factors,
Dimensions
assuming they provide a satisfactory interpretation of
the data and yield a satisfactory fit to R (correlation
Reliability Test matrix) (Johnson and Wichern 1982).
The main purpose of factor analysis is to describe, if
A measure of construct reliability (Cronbach’s alpha)
was computed for each dimension to assess the relia- possible, the covariance relationships among many
bility of the set of items forming that dimension. These variables in terms of a few underlying, but unobserv-
α coefficients range from 0.76 to 0.88 (see Table 3 and able, random quantities called factors. Factor analysis
Appendix). As a rule, alphas of 0.70 or greater repre- can be considered an extension of principal component
sent satisfactory reliability of the items measuring the analysis. Both can be viewed as attempts to approximate
construct (dimension). Thus, the items measuring the the covariance matrix. However, the approximation
dimensions appear to be sufficiently reliable. 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
Assessment of Dimensionality and Wichern 1982).
The next step of analyses involves an assessment of In this article only five factors were chosen with
dimensionality. Bagozzi’s rules for “convergence” and eigenvalues of more than one, as shown in Table 5. The
“discrimination” indicate that items representing a dis- five-factor solution was subjected to Varimax rotation
tinct dimension should correlate highly with each other and the rotated factor loading matrices are shown in
in a uniform pattern, and should not correlate as Table 6. An orthogonal transformation of the factor
strongly with items representing another dimension loadings, and the implied orthogonal transformation of
(Bagozzi 1981). Sample correlation (Q1-Q15) is shown the factors, is called factor rotation, and rotating factors
in Table 4. The correlation matrix follows Bagozzi’s rule. 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
Factor Analysis would like to see a pattern of loadings such that each
Factor analysis was performed using five factor solutions variable loads highly on a single factor and has small-to-
(five common factors), since there are five dimensions of moderate loadings on the remaining factors (Johnson

www.asq.org 39


Table 4 Correlations (Pearson).
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14

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 5

Q13 -15 -9 -8 -13 -4 -9 -12 -16 4 0.4 -12 4

Q14 -5 -3 -1 0.5 8 -5 -7 -10 7 2 7 -3 13

© 2006, ASQ
Q15 9 -3 -9 -8 -4 3 -1 -0.4 -5 6 15 -1 -19 -12

Note: Correlations are multiplied by 100.

and Wichern 1982). Reliability (Q1-Q3) has a large • Responsiveness: Table 7 shows that this dimension
loading on the third factor, responsiveness (Q4-Q6) on of service quality for bank A is significantly different
the first factor, assurance (Q7-Q9) on the second factor, from bank B, but this dimension of service quality
empathy (Q10-Q12) on the fourth factor, and tangible for all the branches within each bank is the same
(Q13-Q15) on the fifth factor. It is not always possible to except for branches 2 and 3 within bank A.
get this structure, although the Varimax rotated loadings • Assurance: Table 7 shows that this dimension of
in this example provide a nearly ideal pattern. service quality for bank A is significantly different
from bank B, but this dimension of service quality
The General Linear Models for all the branches within each bank is the same.
• Empathy: Table 7 shows that the two banks and all
The general linear models procedure of ANOVA was
used to see the differences of dimensions of service the branches differ in this dimension of service quality.
quality between banks and among the branches. The • Tangible: Table 7 shows that the two banks differ in
branches were nested within the banks. The level of sig- this dimension of service quality. Only branches 1 and
nificance was established at 0.05. The following table 2 within bank B are the same in terms of tangible
shows the ANOVA summary. dimension.
• Reliability: Table 7 shows that the reliability • Overall service quality: Table 7 shows that the
dimension for bank A is significantly different from two banks differ in this dimension of service quality,
bank B, but the reliability dimension for all the but all the branches within each bank are the same
branches within each bank is the same. in terms of overall service quality dimension.

40 QMJ VOL. 13, NO. 3/© 2006, ASQ


Regression Table 5 Principal component analysis.
Varimax Factor Factor Factor Factor Factor
Stepwise regression analysis was used for linking overall rotation 1 2 3 4 5
service quality as a dependent variable and five dimen-
Eigenvalue 2.487 2.342 2.256 1.395 1.136
sions of service quality (reliability, responsiveness, assur-

© 2006, ASQ
ance, empathy, and tangible) as independent variables. Proportion 0.17 0.16 0.14 0.09 0.08
The following results were found as shown in Table 8. Cumulative 0.17 0.33 0.47 0.56 0.64
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 Table 6 Factor analysis (Varimax rotation).
was significant with R2 = 0. 81. For bank A’s branch 1, Factor Factor Factor Factor Factor
reliability and responsiveness were both significant Variable 1 2 3 4 5
with R2 = 0. 81. For bank A’s branch 2, reliability was Reliability
significant with R2 = 0. 83. For bank A’s branch 3, reli- Q1 76
Q2 37 60
ability was significant with R2 = 0. 81. For bank B’s Q3 27 81
branch 1, reliability and responsiveness were both signifi-
Responsiveness
cant with R2 = 0. 80. For bank A’s branch 2, reliability Q4 70 50
was significant with R2 = 0. 81. Q5 88
Q6 85

DISCUSSIONS AND Assurance
Q7
Q8 34
-75
-67
36
26
CONCLUSIONS Q9 -75

The results show that reliability and responsiveness are Empathy
the two most critical dimensions of service quality and Q10 -59 75
Q11 77
they are directly related to overall service quality. Q12 -58 78
Responsiveness and reliability have been shown to be
Tangible
important factors, supporting previous work by Berry, Q13 65
Zeithaml, and Parasuraman (1985) and Avkiran Q14 -76
Q15 66

© 2006, ASQ
(1994). Allred and Addams (2000) conducted a similar
study in a banking industry in a midwestern city and Note: All numbers in the table are magnitudes of factor loadings
multiplied by 100. Loadings of .25 or less are not shown.
discovered that assurance, reliability, and responsive-
ness are the most critical dimensions of service quality.
Johnston (1997) conducted a study in the U.K. banking
Table 7 ANOVA table for service quality.
industry to combine the classification of quality factors
Independent variables
into satisfiers and dissatisfiers together with relative
Dependent variables Bank Branches
importance. The factors that may delight customers tend
to be concerned more with the intangible nature of the Assurance *
service, commitment, attentiveness, friendliness, care, Empathy * *
and courtesy. The main sources of dissatisfaction appear Overall
to be cleanliness, aesthetics, integrity, responsiveness,
*
Reliability *
reliability, and security, which are associated with either
the more tangible aspects of service or systemic issues. Responsiveness * *
© 2006, ASQ

Thus, reliability and responsiveness dimensions of serv- Tangible * *
ice quality have been shown to be important factors,
Note: * = statistically significant at 0.01 level of significance
supporting previous works.

www.asq.org 41


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 five-
dimensional structure could possibly serve All banks Overall = .25 + .91 Reliability + .05 Responsiveness .87

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
(Parasuraman, Berry, and Zeithaml Bank A (branch 2) Overall = .60 + .921 Reliability .83

1993). The wording of some individual Bank A (branch 3) Overall = .236 + .96 Reliability .81

© 2006, ASQ
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 dimen-
Bank 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 RECOMMENDATIONS
differential biases in data collection. Since the sample Reliability is an obvious place to start. Customers want
sizes are large enough and data are normalized, the to know their resources are safe and within trustworthy
differential biases in data collection should not have an institutions. A way to ensure this peace of mind would
effect on the analysis. One explanation might be that be to take steps to ensure bank employees are well
bank B customers had a high morale and were satisfied trained, so each bank associate is able to offer complete
with the service quality or very dissatisfied with the and comprehensive information at all times. Consistent
service quality. policies combined with a knowledgeable staff will foster
Tracking customers and developing creative strate- a high degree of institutional cohesion and reliability.
gies to retain them is very profitable. For example, in Responsiveness, again when associated with a
1982, Charles Cawley, the president of the credit card well-trained staff and timely answers to service-related
company MBNA of America, became increasingly questions, would make significant inroads into causing
frustrated by numerous complaints from defecting various banking institutions be regarded as responsive.
customers and took action. Cawley announced to all Staff should be encouraged to present relevant options
MBNA employees that the mission of the company to banking customers in a manner that does not
would be to keep every customer. To accomplish this resemble salesmanship so much as a desire to serve.
goal, a strategy was implemented to call defecting Intangibles please customers just as much as tangi-
customers personally and obtain information about bles in the banking industry. People tend to visit the
the reason for their defection. Chronic problems were same branch of a bank over and over again. Usually,
determined and prioritized; appropriate changes this is a location close to their home or their workplace.
were implemented. Eight years later, MBNA’s defec- It is natural that customers become comfortable and
tion rate was reduced to just 5 percent, one of the habituated to these branch banks, for the same reason
lowest in the industry. Without making any acquisi- they develop familiarity with a neighborhood super-
tions, MBNA’s industry ranking went from 38 to 4, and market or convenience store. It makes sense that bank
profits increased 16-fold (Reichheld and Sasser 1990). employees would be encouraged to learn to recognize
Many studies indicate that it costs eight to 10 times these regular customers, learn their names, and begin
less to keep a customer than to develop a new one. to identify their basic service requirements.
Thus, improving service quality leads to the customer Learning to understand customers needs will allow
satisfaction and, ultimately, to customer loyalty. bank associates to offer enhanced services, perhaps

42 QMJ VOL. 13, NO. 3/© 2006, ASQ


lowering customers’ banking costs and increasing their Avkiran, N. K. 1994. Developing an instrument to measure customer
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www.asq.org 43


Parasuraman, A., V. Zeithaml, and L. Berry. 1988. SERVQUAL: BIOGRAPHIES
A multiple-item scale for measuring consumer perceptions of
service quality. Journal of Retailing 64 (Spring): 12-40. Lotfollah Najjar is an assistant professor in the college of information
science and technology at university of Nebraska at Omaha. Najjar’s
Parasuraman, A., V. Zeithaml, and L. Berry. 1985. A conceptual research interests center on: quality information systems (data quality)
model of service quality and its implications for future research. in the service and manufacturing industries; business process reengi-
Journal of Marketing 49 (Fall): 41-50. neering and IT; data mining; and total quality management and IT in
Reichheld, F.F., and W. E. Sasser. 1990. Zero defections: Quality both service and manufacturing industries. His teaching interests
comes to services. Harvard Business Review: 105-11. include quality information systems; business process reengineering
and IT; business data communications; introduction to management
Sweat, J., and J. Hibbard. 1999. Businesses are spending heavily on information system, quality control, operations management; statistics;
customer service, but many aren’t getting the job done—customer and mathematics. He began teaching at UNO in 1989. Najjar
disservice. Information Week (21 June). earned a doctorate in industrial management systems engineering
with a minor in MIS from the University of Nebraska-Lincoln in 2002.
Teas, K. R. 1994. Expectations as a comparison standard in
He may be contacted by e-mail at Najjar@unomaha.edu .
measuring service quality: An assessment of a reassessment.
Journal of Marketing 58 (January): 132-9. Ram Bishu is a professor in the college of engineering at the
University of Nebraska–Lincoln. Bishu’s research interests center on
Yavas, U., and D. J. Shemwell 1997. Meeting the service quality
ergonomics, information processing, total quality management, and
challenge: Structural problems and solutions. Managing Service
quality control. His teaching interests include quality control,
Quality 7, no. 4: 198-203.
ergonomics, design of experiments, and operations management.
Zeithaml, V. 1987. Defining and relating price, perceived quality, Bishu earned a doctorate in industrial management systems engi-
and perceived value. Report no. 87-101. Cambridge, Mass.: neering from SUNY Buffalo in 1985. He may be contacted by e-mail
Marketing Science Institute. at rbishu@engunx.unl.edu .

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 Excellent
1. Serving you quickly and efficiently 0 1 2 3 4 5 6 7 8 9 10
2. Handling your transaction accurately 0 1 2 3 4 5 6 7 8 9 10
3. Being dependable 0 1 2 3 4 5 6 7 8 9 10
4. Providing clear explanations of services 0 1 2 3 4 5 6 7 8 9 10
5. Solving problems/troubleshooting 0 1 2 3 4 5 6 7 8 9 10
6. Understanding your banking needs 0 1 2 3 4 5 6 7 8 9 10
7. Thanking you for your business 0 1 2 3 4 5 6 7 8 9 10
8. Feeling secure doing business here 0 1 2 3 4 5 6 7 8 9 10
9. Making it easy to do business here 0 1 2 3 4 5 6 7 8 9 10
10. Greeting & acknowledging you promptly 0 1 2 3 4 5 6 7 8 9 10
11. Addressing you by name 0 1 2 3 4 5 6 7 8 9 10
12. Providing friendly and caring service 0 1 2 3 4 5 6 7 8 9 10
13. The location of our bank to you is 0 1 2 3 4 5 6 7 8 9 10
14. Having up-to-date equipment 0 1 2 3 4 5 6 7 8 9 10
15. Accessibility to ATM 0 1 2 3 4 5 6 7 8 9 10
© 2006, ASQ

16. Overall service quality 0 1 2 3 4 5 6 7 8 9 10
Thank You

44 QMJ VOL. 13, NO. 3/© 2006, ASQ

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