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Service quality and customers’
behavioural intentions
Class and mass banking and implications
for the consumer and society
Koushiki Choudhury
Indian Institute of Management Calcutta, Kolkata, India
Abstract
Customers’
behavioural
intentions
735
Received 9 February 2015
Revised 28 March 2015
6 May 2015
12 May 2015
Accepted 12 May 2015
Purpose – The purpose of this paper is to explore how the different dimensions of service quality
influence customers’ behavioural intentions in the private and public sector banks, that is, in class and
mass banking, respectively, and the implications for the service provider, consumer, society and
consumer policy.
Design/methodology/approach – A contextually modified SERVQUAL instrument was used to
capture customers’ perceptions of service quality followed by exploratory factor analysis to study the
dimensionality of service quality in retail banking. Multiple regression was used to probe the influence
of the dimensions of service quality on customers’ behavioural intentions.
Findings – The study revealed four dimensions of service quality in retail banking, namely,
customer-orientedness, reliability, tangibles and convenience and showed that the service quality
factor customer-orientedness comprising of the responsiveness and attitude of employees is most
important in influencing customers’ behavioural intentions in the case of private sector banks and
reliability of the service is most influential in the case of public sector banks.
Research limitations/implications – Future research can focus on “service excellence” being
extended beyond assessment of the quality of services, towards evaluation of the quality of life outcomes,
to which public organizations contribute, appraisal of the quality of public governance processes and
quality of performance in meeting social objectives.
Practical implications – Retail bank managers must realize the importance of employees providing
competent, reliable service in the case of public sector banks and their responsiveness and behaviour
towards customers in the case of private sector banks, as the keys to foster a culture of service excellence.
Social implications – High-quality financial consumer policy must not only be able to increase
customer satisfaction with financial services but also build security and trust in public administration
through transparent processes and accountability. In this context, with public agencies being regarded
as service providers and citizens as customers, the concept of quality must also visualize public
agencies as catalysts of a responsible and active civic society.
Originality/value – This study explores the relationship between service quality and customers’
behavioural intentions in the private and public sector banks by linking both constructs at their
dimensional level. It highlights major implications for the service provider, society, consumer and
public policy based on the different needs, characteristics and requirements of customers of class and
mass banking, that is, private and public sector banks.
Keywords Society, Service quality, Behavioural intentions, Public sector banks,
Private sector banks, Consumer and policy implications
Paper type Research paper
1. Introduction
1.1 Public policy in the financial sector in India
The Indian financial sector went through a significant structural transformation with
the initiation of financial liberalization in the 1990s. Before that, from the mid-1960s
till the early 1990s, the Indian financial system was regarded as an instrument of
public finance (Agarwal, 2003). The evolution of the Indian financial sector in the period
Asia Pacific Journal of Marketing
and Logistics
Vol. 27 No. 5, 2015
pp. 735-757
© Emerald Group Publishing Limited
1355-5855
DOI 10.1108/APJML-02-2015-0025
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post-independence can be categorized by three distinct phases. During the first period
(1947-1968), the Reserve Bank of India (RBI) consolidated its function as the agency in
charge of regulation, supervision and banking control (Sen and Vaidya, 1997).
After that, the Indian financial sector was characterized by the nationalization of
banks, directed credit and administered interest rates. Mid 1980s onwards, the financial
sector was characterized by consolidation, diversification and liberalization. A more
comprehensive financial sector liberalization programme, however, was initiated by the
Government of India during the early 1990s, culminating in the Narasimham
Committee Report in 1991 (Das and Drine, 2011), that provided the blueprint of
the reforms, especially with regard to banks and other financial institutions.
The liberalization programme comprised of de-controlled interest rates, reduced
reserve ratios and slowly reduced government control of banking operations, while
establishing a market regulatory framework. The major aims of financial liberalization
were to improve the overall performance of the Indian financial sector, to make the
financial institutions more competent and more efficient. The Indian banking sector
has been dominated by the public sector banks in terms of number and asset share.
In terms of asset share, the public sector banks constitute about 70 per cent of the total
commercial banking asset (Das and Drine, 2011).
Before 1994, foreign banks in India were the only benchmark for excellence – the
ambience, the technology, the courtesy. The financial sector reforms in India which
started in 1991-1992, advocated the liberalization of entry norms and suggested that
new banks be permitted in the private sector provided they conformed to the minimum
start-up capital and other requirements. It was felt that a robust banking sector is
essential for achieving the objectives of growth and development. However, it was
asserted that public sector banks would have to continue fulfilling their social
obligations towards the financial growth and development of the economy and its
citizens. Since the implementation of many of the recommendations, many new private
sector banks have been set up, many foreign banks too have set up shop and many
more are waiting in queue to get permission from the RBI. These new banks in India
are characterized by a strong emphasis on the retail side of banking as well as their use
of technology, and the presence of these private banks has served to increase
competitive pressures on the government-owned public sector banks. To these
pressures, which the public sector banks are facing, have to be added the trend towards
globalization, deregulation and the abolition of several types of subsidies in the
provision of financial services, fuelling competitive forces in the banking system.
The consequent increase in competition has made service quality a key differentiating
factor for banks attempting to improve their market and profit positions. In fact,
studies have shown that there is a positive service quality-profitability relationship and
that the intermediate link between service quality and profits is the relationship
between service quality and customers’ behavioural intentions (Zeithaml et al., 1996).
Studying the behavioural responses to service quality can help managers estimate the
financial consequences of investing in service quality. With the rapid change taking
place in the banking industry in India and the presence of more sophisticated
customers in today’s Indian banking scenario, it has become very important especially
for public sector banks in India to determine the service quality factors, which are
pertinent to the customer’s selection process, as with increased competition, customers
are now having greater difficulty in selecting one institution from another. In fact, it is
reasonable to guess that the public sector banks can certainly hope to face increasingly
stiffer competition from the private sector banks in the years to come. Exploring which
facets of service quality have an important bearing on customers’ behavioural
intentions in the private and public banking sectors should therefore help to specify,
control and improve customer-perceived service quality in these two sectors.
Most importantly, since the financial services sector drives the economy it would help
policy makers craft policies that would enable citizens achieve their financial goals.
Thus, considering the societal implications of research on the link between service
quality and customers’ behavioural intentions in the context that the two banking
sectors private and public are competing against each other, it was deemed that it
would be of interest to explore as to how the different dimensions of service quality
influence customers’ behavioural intentions in these two sectors and explore the
implications for public and consumer policy and macro-level planning.
1.2 Service quality and customers’ behavioural intentions
The relationship between overall service quality and certain dimensions of customers’
behavioural intentions have been examined by Cronin and Taylor (1992) and Boulding
et al. (1993). Cronin and Taylor (1992) focused solely on repurchase intentions and reported
non significant relationships whereas Boulding et al. (1993) focused on both repurchase
intentions and willingness to recommend and reported significant and positive ones.
Perceived service quality has been assumed to be a key factor in explaining purchase
intentions, but this relationship has not been fully explained (Cronin et al., 2000). Several
studies have confirmed a link between perceived service quality and behavioural
intentions, but only through value and satisfaction (Patterson and Spreng, 1997), whereas
other researchers have found a direct link between perceived service quality and
behavioural intentions (Boulding et al., 1993; Parasuraman et al., 1988, 1991; Zeithaml
et al., 1996). Service quality is believed to be a critical success factor for organizations to
differentiate themselves from their competitors. In a study of the banking industry, it has
been shown that high-service quality helps in gaining a competitive edge in terms of
higher revenue, customer loyalty and customer retention (Kumar et al., 2010). High levels
of service quality paves the way for customers’ satisfaction, customer loyalty, new
customer attraction, increased market share and profitability for the banking sector
(Kumari and Rani, 2011). Casado-Díaz et al. (2007), modelled the effect of specific emotions
triggered by the service recovery on satisfaction with service recovery in the context of
the banking sector which is facing huge competition and consequent demanding
customers. Casado-Diaz and Nicolau-Gonzalbez (2009), showed that in the banking
sector, the magnitude of service failure, recovery strategies, distributive and procedural
justice, recovery-related emotions and satisfaction with service recovery all have a
significant effect on customers’ choice of the type of response, with the latter showing the
highest impact. However, much of the research on service quality has been in the
developed countries (Herbig and Genestre, 1996; Choudhury, 2013), even though services
are among the fastest growing sectors in emerging countries (Choudhury, 2013). In fact,
the bulk of the research on service quality in banks has been in the context of US and
European banking institutions. At this juncture, it is important to also study banking
institutions based in developing economies like India, which has compartaively recently
liberalized its banking sector. As banks in such countries as India mature, lessons may be
learned from their experiences by banks in developed economies as well as in other
developing countries, as banking becomes more and more globally integrated. In fact,
there exists a gap in the service marketing literature on how consumers evaluate service
quality in contexts and cultures very different from the developed countries, even though
research has begun to explore this area (Bolton and Myers, 2003). Hitherto, studies have
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compared private and public sector banks with regards to financial parameters. Gudep
and Elango (2006) researched on service quality and customer satisfaction amongst the
private, public and foreign banks in India. The results indicated that the foreign and the
new generation private sector banks were serving the customers better. Mengi (2009) in a
study to compare customers’ perceptions of service quality of public and private banks in
Jammu, observed that the customers of public sector banks are more satisfied with their
service quality than those of private sector banks. The study found that responsiveness
and assurance are most important for customer satisfaction. On the other hand, Lo et al.
(2010) found that empathy and assurance had the highest influence on customer
satisfaction in the Malaysian retail banking industry. Levy (2014) found a significant,
direct and negative relationship between the relative usage level of online banking
services and bank loyalty, a positive relationship was found to exist between bank
loyalty and customer satisfaction with online service quality. An indirect positive
relationship was also found to exist between services’ convenience through satisfaction
with online banking service quality. However, very few studies have explored the
relation between customers’ behavioural intentions and service quality and examined the
differences therein, between private and public sector banks, in a comparative analysis.
Choudhury (2014c) in a study of private and public sector banks, explored the relation
between customers’ behavioural intentions and service quality with a small sample size
of customers and banks. In this regard, it would be interesting to study the link between
the individual dimensions of service quality and customers’ behavioural intentions with
a large scale study, with a large representative sample size and greater number of
banks. This study hopes to build on the explicit connections between service quality
dimensions and customers’ behavioural intentions by probing the link between the
individual dimensions of service quality and customers’ behavioural intentions in
the case of public and private sector banks in India and exploring the consequent societal
implications for consumer and public policy. Linking both constructs at their dimensional
level increases the diagnostics of explaining customers’ behavioural intentions.
1.3 Favourable behavioural intentions
1.3.1 WOM communications and purchase intentions. Word-of-mouth, both positive and
negative (Richins, 1983), has been the subject of many marketing studies since the 1960s,
across a wide range of products and services. Mahajan et al. (1990) proposed that consumers
are influenced by two sources: media and WOM communication. WOM behaviour has been
examined less for services than for products, though it has been shown to be invaluable to
service organizations. This is more so if informal channels of communications are the
primary means of disseminating market information and the services are particularly
complex and difficult to evaluate (File et al., 1992).
For most services, existing customers represent by far the best opportunities for
profit growth. As the retention rate goes up, so too does profitability (Reichheld and
Sasser, 1990). The greatest profit impact of long-time customers comes through their
increased purchases and the positive WOM (referrals to other customers) that they
engage in (Reichheld and Sasser, 1990; Reichheld and Kenny, 1990). The WOM
generated by long-term customers act as free advertising, thus saving the firm from
high investments in this area. In fact, WOM is particularly critical for certain services,
such as banks and other financial services; research shows that personal referrals are
responsible for 20-40 per cent of bank customers and are a key factor in selecting
financial service providers (Reichheld and Kenny, 1990).
1.4 Unfavourable behavioural intentions
Customers perceiving service performance to be inferior are likely to exhibit
behaviours signalling they are poised to leave the company. These behaviours include
exiting (switching to a new supplier) and complaining, the latter being viewed by many
researchers as a combination of negative responses that stem from dissatisfaction and
predict or accompany defection (Richins, 1983; Scaglione, 1988). Given that customers
of retail banks have relatively high-switching costs, it is likely that a dissatisfying
experience will evoke a complaint. A study by Richins (1983), on how dissatisfaction
affects WOM communications showed that when the dissatisfaction is serious enough,
consumers tend to complain, and if complaints are encouraged, the provider has a
chance to remedy the legitimate complaints and win back a customer, who might also
make a positive report to others, thus enhancing the goodwill. On the other hand,
if people are dissatisfied with a product or service, and if complaints are discouraged by
the company providing the product or service, then customers will engage in negative
WOM. The result is reduced sales and damaged brand equity. Vyas and Raitani (2014)
concluded that drivers of bank switching behaviour do not work in isolation; rather, it
is an outcome of negative service experience that may be related to any of the factors of
customer satisfaction. By integrating research findings a list of specific indicators of
complaining behaviour can be compiled. According to Singh (1988), dissatisfaction
leads to consumer complaining behaviour that is manifested in private responses
(complaining to acquaintances, friends and relatives) and third-party responses
(complaining to external agencies). Zeithaml et al. (1996), in their studies of the impact
of service quality on particular behaviours, operationalised complaining behaviour in
terms of complaining to others and complaining to external agencies in case of a
problem experienced with the company’s service.
2. Methodology
2.1 Sample design and data collection
For the study reported herein, responses were gathered from customers of four major
banks in the retail banking industry of India (two leading private sector banks – the
Bank A and Bank B and two leading public sector banks – Bank C and Bank D).
All these four banks rank among the largest and strongly profitable banks in India in
the public and the private sectors, respectively; moreover the banks have strong and
significant retail presence. Seven branches for each bank were randomly selected.
The actual names of the banks have been changed in the study, for purposes of
confidentiality. The study was conducted in Kolkata, a key metropolitan city in the
Eastern area of India with a large and diverse population. Questionnaires were
self-administered to customers within the branches of the Bank A, the Bank B, the
Bank C and the Bank D. The branches were considered by the management to be
largely homogeneous with respect to size and service operations. Every other customer
entering the branches was asked to complete the questionnaire. It was ensured that
only existing customers, who had transacted with the bank for at least three years,
filled up the questionnaires. Ultimately, a total of 1,800 customers were contacted
(450 customers filled up the questionnaire in each of the four banks), and the overall
response rate was 52 per cent (936 completed, usable questionnaires). The response rate
varied between the branches of a bank. In the case of public sector banks, in a few
branches, quite a few customers who were approached, refused to fill up the
questionnaire. Demographic profiles of the samples from each bank were reviewed by
the managers in the respective banks and considered to be representative of their
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customer bases. The final sample size in each bank was in 232, 236, 235 and 233 in
Banks A, B, C and D, respectively.
The demographic profiles of the samples from each bank were as follows (Table I).
2.2 Design and development of questionnaire
The questionnaire for the measurement of customer-perceived service quality followed the
basic structure of the SERVQUAL instrument as developed by Parasuraman et al. (1988).
According to Parasuraman et al. (1988, 1991), SERVQUAL provides the basic skeleton
underlying service quality and this skeleton, when necessary, can be adapted or
supplemented to fit the characteristics or specific research needs of a particular
organization, and context-specific items can be used to supplement SERVQUAL. This has
also been advocated by other researchers of service quality, who have echoed that
contextual circumstances have a bearing on the perception of service quality and it is
necessary in this regard to modify some of the items of the SERVQUAL scale and add or
delete items from the scale as required (Carman, 1990). An inventory of service quality
items was identified. Items for measuring customer-perceived service quality were adopted
from the service quality and service marketing literature (Parasuraman et al., 1991) and the
bank marketing literature (Levesque and McDougall, 1996; Yavas et al., 1997; Parasuraman
et al., 1988, 1991; Cronin and Taylor, 1992; Brown et al., 1993; Choudhury, 2008, 2013,
2014a, b, c). The list of items generatedare as follows.
Original list of items for measuring customer-perceived service quality:
(1) YOUR BANK has modern-looking equipment;
(2) YOUR BANK’s physical facilities are visually appealing;
(3) YOUR BANK’s employees are neat – appearing;
(4) materials associated with the service, such as pamphlets and statements, are
visually appealing at YOUR BANK;
(5) when YOUR BANK promises to do something by a certain time, it does so;
(6) when you have a problem, YOUR BANK shows a sincere interest in solving it;
(7) YOUR BANK performs the service right the first time;
(8) YOUR BANK provides its services at the time it promises to do so;
(9) YOUR BANK insists on error-free records;
(10) employees of YOUR BANK tell you exactly when services will be performed;
(11) employees of YOUR BANK give you prompt service;
(12) employees of YOUR BANK are always willing to help you;
Bank
Sex – male (%)
Sex – female (%)
Mean age
Self-employed (businessmen, doctors, lawyers) (%)
Table I.
Profiles of the banks’ Salaried (%)
Others (Homemakers, retired persons, students) (%)
customers
Bank A
Bank B
Bank C
Bank D
51
49
40.45
35
49
16
53
47
40.73
38
45
14
52
48
41.56
12
62
26
51
49
41.76
14
59
27
(13) employees of YOUR BANK are never too busy to respond to your requests;
(14) the behaviour of employees of YOUR BANK instills confidence in customers;
(15) you feel safe in your transactions with YOUR BANK;
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(16) employees of YOUR BANK are consistently courteous with you;
(17) employees of YOUR BANK have the knowledge to answer your questions;
(18) YOUR BANK gives you individual attention;
(19) YOUR BANK has operating hours convenient to all its customers;
(20) YOUR BANK has employees who give you personal attention;
(21) YOUR BANK has your best interests at heart;
(22) employees of YOUR BANK understand your specific needs;
(23) YOUR BANK has convenient branch locations; and
(24) it is very easy to get in and out of YOUR BANK quickly.
A few items from this original list (above list) were dropped, because they were either
vague, repetitive or difficult to comprehend to respondents, in a pilot study done with
30 customers from the Bank A, 32 customers from the Bank B, 30 customers from the
Bank C and 32 customers from the Bank D. These items which were considered vague,
repetitive or difficult to comprehend to respondents, were dropped after being reviewed
by the researcher, social scientists and experts in marketing and statistics. Two items
were added; one of this was “your bank has a large ATM network”, as all the customers
surveyed in the pilot study indicated that this issue was very important with regards to
banking services. The majority of the respondents also indicated that presence of internet
banking services should be included in the questionnaire as they felt that it was important.
Scale development procedure recommended by Churchill (1979) and Parasuraman
et al. (1988) was followed. An inventory of service quality items was identified. The initial
pool of items generated were then iteratively assessed for internal consistency (by means
of coefficient α estimates) and factor analysed using randomly drawn samples of banks’
customers. The process was continued until the scales exhibited acceptable measurement
properties. The result was a final group of 16 items that were arrived at to measure service
quality in this study and this instrument was referred to as the modified service
quality (MSERVQUAL) scale (below list). The items of the MSERVQUAL scale:
(1) Variable description:
•
V1. YOUR BANK’s physical facilities are visually appealing (physical
facilities);
•
V2. materials associated with the service, such as pamphlets and
statements, are visually appealing at YOUR BANK (materials);
•
V3. YOUR BANK has convenient branch locations (branch locations);
•
V4. YOUR BANK has a large ATM network (ATM network);
•
V5. when you have a problem, YOUR BANK shows a sincere interest in
solving it (responsiveness);
•
V6. YOUR BANK performs the service right the first time (right service);
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•
V7. when YOUR BANK promises to do something by a certain time, it does
so (dependability);
•
V8. employees of YOUR BANK tell you exactly when services will be
performed (service timing);
•
V9. employees of YOUR BANK give you prompt service (prompt service);
•
V10. you feel safe in your transactions with YOUR BANK (safety);
•
V11. employees of YOUR BANK are consistently courteous with you
(courteousness);
•
V12. employees of YOUR BANK have the knowledge to answer your
questions (knowledge);
•
V13. YOUR BANK has operating hours convenient to all its customers
(operating hours);
•
V14. YOUR BANK has employees who give you personal attention
(personal attention);
•
V15. employees of YOUR BANK understand your specific needs (ability to
understand); and
•
V16. YOUR BANK has a strong internet banking facility (internet banking).
V Stands For variable. The abbreviated names of the variables appear in parenthesis in
the above list.
Feedback from the managers in each of the participating banks who reviewed the
questionnaire confirmed that the MSERVQUAL had face validity. The questionnaire
was administered in a pilot study to 31 customers from each of the four banks.
Reliability (Cronbach’s α) for the MSERVQUAL scale was tested for each of the four
banks, for the private sector banks as a whole (both the private sector banks
clubbed together), for the public sector banks as a whole (both the public sector banks
clubbed together) and for the entire sample. The results are depicted in Table II.
It can thus be seen that the reliability figures are very high, all above the recommended
lower limit of 0.70 (Nunnally, 1978).
2.3 Factor analysis of the SERVQUAL scores
In this study, for each customer, SERVQUAL scores were generated. A description of
the 16 SERVQUAL items used in this study is presented in the above list. Factor
analysis of the SERVQUAL scores for the items was conducted to reveal the
Bank
Table II.
Reliability scores for
MSERVQUAL
Bank A
Bank B
Bank D
Bank C
Private sector
Public sector
Total pilot study sample
Cronbach’s α
0.9643
0.8777
0.9764
0.9214
0.9243
0.9265
0.9223
underlying dimensions of customer-perceived service quality, and was followed by a
Varimax rotation. In this study, 70 per cent cumulative variance was chosen as the
satisfactory level. Discriminant validity was assessed following Fornell and Larcker
(1981) by comparing the average variance extracted for each factor with the variance
shared between the remaining factors. All the service quality dimensions in this study
met the criteria for discriminant validity.
2.4 The influence of service quality on customers’ behavioural intentions
Multiple regression analysis was carried out, to explore the linkage between
customer-perceived service quality and customers’ behavioural intentions. The factor
scores of the service quality factors obtained in the factor analysis represented
the independent variables, whereas customers’ behavioural intentions represented the
dependent variables. Customers’ behavioural intentions were operationalised by WOM
communications, purchase intentions and complaining behaviour. In order to interpret
and cross-validate the findings of the quantitative study a qualitative follow-up study
was conducted. In-depth interviews were held with 15 customers from each of the four
banks in the study, in order to further elucidate and throw light on the relationships
between the service quality and behavioural intentions’ dimensions, and the
information gathered from the interviews was used to facilitate the interpretation of
the results of the survey.
2.5 WOM communications
In this study, customers’ willingness to engage in WOM about their banks was
captured by the following questions, with anchors at 1 (not at all likely) and 7
(extremely likely):
•
“How likely are you to say positive things about YOUR BANK to others?”;
•
“How likely are you to recommend YOUR BANK to someone who seeks your
advice?”; and
•
“How likely are you to encourage friends and relatives to do business with YOUR
BANK?”
It has been assumed that all the above items are equally weighted.
2.6 Purchase intentions
In this study, customers’ purchase intentions were captured by the following questions,
with anchors at 1 (not at all likely) and 7 (extremely likely):
•
“How likely are you to continue doing business with YOUR BANK?”;
•
“How likely are you to do more business with YOUR BANK?”; and
•
“How likely are you to consider YOUR BANK as the first choice to buy services?”
It has been assumed that all the above items are equally weighted.
2.7 Complaining behaviour
In this study, customers’ complaining behaviour was captured by the following
questions with anchors at 1 (not at all likely) and 7 (extremely likely):
•
“How likely are you to complain to others if you experience a problem with
YOUR BANK’s services?”;
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•
“How likely are you to complain to an external agency (consumer organization/
newspaper/government agency) if you experience a problem with YOUR BANK’s
services?”; and
•
“How likely are you to convince your friends and relatives not to use YOUR
BANK’S services if you experience a problem with YOUR BANK’s services?”
It has been assumed that all the above items are equally weighted.
Reliability was tested for the three-item WOM scale, the purchase intentions scale
and the complaining behaviour scale in the pilot study done with 50 customers from
each of the four banks. Reliability was tested for each of the four banks, for the private
sector banks as a whole (both the private sector banks clubbed together), for the public
sector banks as a whole (both the public sector banks clubbed together) and for the
total pilot study sample. The results are depicted in Table III.
2.8 Private and public sector banks: the influence of customer-perceived service quality
on customers’ behavioural intentions
The linkages between customer-perceived service quality and customers’ behavioural
intentions were explored for the two categories of private and public sector banks.
To maintain internal consistency throughout the work, the factors obtained from the
factor analysis done on the entire data set of 720 customers were used, in order to have
the same factor structure throughout the study and so that when the linkages between
customer-perceived service quality and customers’ behavioural intentions are compared
between the private and public sectors, the factors per se would remain the same. In case
of the private sector, factor scores generated for the customers of the two private sector
banks (Bank A and Bank B) were pooled and in case of the public sector, factor scores
generated for the customers of the two public sector banks (Bank D and Bank C) were
pooled. This pooling resulted in 362 customers for the private sector and 358 customers
for the public sector. Multiple regression analysis was then carried out for each sector; the
factor scores of the service quality factors represented the independent variables,
whereas customers’ behavioural intentions represented the dependent variables. SPSS
was used for doing the factor analysis and multiple regressions.
3. Results
3.1 Factor analysis of the SERVQUAL scores
For each customer, SERVQUAL scores were generated. A SERVQUAL score is
obtained by subtracting the expectation score from the perception score for each
SERVQUAL item. Factor analysis was conducted with the SERVQUAL scores for the
Bank
Table III.
Reliability scores for
the scales
Bank A
Bank B
Bank C
Bank D
Private sector
Public sector
Total sample
Cronbach’s α for
WOM scale
Cronbach’s α for purchase
intentions scale
Cronbach’s α for complaining
behaviour scale
0.9324
0.9645
0.8534
0.9233
0.9037
0.9127
0.9283
0.8424
0.8754
0.8242
0.9876
0.8548
0.8540
0.8961
0.8424
0.9532
0.8853
0.9645
0.9038
0.9270
0.9189
entire set of 720 customers. A description of the 16 SERVQUAL items is presented in
the above list. Factor analysis of the SERVQUAL scores for the SERVQUAL items was
conducted, and was followed by a Varimax rotation to examine the dimensionality of
the items. A four-factor solution was obtained, and the 16 items could be reconfigured
into four dimensions, namely, customer-orientedness, reliability, tangibles and
convenience. The factor loading matrix is presented in Table IV.
The first factor, customer-orientedness, was defined by five scale items and was
primarily related to the attitude and skills of the employees providing the service.
The second factor, reliability, was constructed by five scale items, which were primarily
associated with the concept of providing reliable services to customers. The third
factor, tangibles, was constructed by two scale items, which were primarily associated
with the visual appeal of the banks’ physical facilities and communication materials to
the customers. Finally, the fourth factor, convenience, encompassed three items related
to the convenience of the banks’ branch locations, presence of internet banking services
and the spread of the banks’ ATM networks. The reliability coefficient (Cronbach’s α),
of the MSERVQUAL scale used in this study, was 0.9274 for the entire sample.
The bank wise reliability coefficients (Cronbach’s α) for the MSERVQUAL scale used in
this study were as follows:
Banks
Cronbach’s α
Bank A
0.9587
Bank B
0.9198
Factor 1 customerorientedness
Bank D
0.9312
Component
Factor 2
Factor 3
reliability
tangibles
Prompt service
0.643
Courteousness
0.754
Ability to understand
0.753
Knowledge
0.834
Responsiveness
0.673
Personal attention
0.618
Right service
0.684
Dependability
0.844
Service timing
0.676
Safety
0.686
Operating hours
0.643
Physical facilities
0.867
Materials
0.776
Branch locations
Internet banking services
ATM network
Eigenvalues
7.43
1.15
0.96
Percentage of variance
explained
26.34
22.65
11.62
Cumulative percentage of
variance explained
26.34
48.99
60.61
Cronbach’s α
0.9273
0.9242
0.8233
Notes: Cumulative variance was 70.84 per cent. Rotated component matrix
Customers’
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intentions
745
Bank C
0.9113
Factor 4
convenience
0.951
0.845
0.613
0.89
10.23
70.84
0.8423
Table IV.
Results of the
factor analysis
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3.2 Private and public sector banks: an analysis of the influence of customer-perceived
service quality on customers’ behavioural intentions
Multiple regression analysis was carried out in order to explore the linkages between
customer-perceived service quality and customers’ behavioural intentions in case of the
private and public sector banks, studied in this study. The exercise was intended to
explore sectoral differences if any between the private and public sector banks with
regards to the influence of customer-perceived service quality on customers’
behavioural intentions. The reliability coefficient (Cronbach’s α) of the MSERVQUAL
scale was 0.9137 for the private sector and 0.9118 for the public sector. The reliability
coefficient (Cronbach’s α) of the three-item WOM scale was 0.9126 for the private
sector and 0.9217 for the public sector. The reliability coefficient (Cronbach’s α) of the
three-item purchase intention scale was 0.9138 for the private sector and 0.9047 for the
public sector. The reliability coefficient (Cronbach’s α) of the three-item complaining
behaviour scale was 0.9056 for the private sector and 0.9240 for the public sector.
3.3 Private sector banks: effect of customer-perceived service quality on customers’
behavioural intentions
To explore the linkage between customer-perceived service quality and customers’
behavioural intentions, factor scores generated (for the factors obtained from the factor
analysis done on the entire data set of 720 customers) for the customers of the two
private sector banks (Bank A and Bank B) were pooled. The factor scores of the service
quality factors represented the independent variables, whereas customers’ behavioural
intentions represented the dependent variables (Table V).
It is thus evident from the adjusted R2, that the model explains 60.3 per cent of the
variance in customers’ willingness to engage in WOM about their banks.
The Anova table indicated that the multiple regression model is statistically
significant and that the independent variables have a systematic association with the
dependant variable.
In case of private sector banks, the regression coefficients indicated in Table II offer
strong support for the facts that:
Table V.
Private sector banks:
an analysis of the
influence of
customer-perceived
service quality
on WOM
•
all the four independent variables are significant predictors of customers’
willingness to engage in WOM about their banks;
•
the service quality factor customer-orientedness is the most important factor for
influencing WOM about the banks;
Constant
Customer-orientedness
Reliability
Tangibles
Convenience
Estimate
5.162
0.934
0.425
0.324
0.121
SE
0.104
0.025
0.064
0.103
0.023
Prob
0.000
0.000
0.000
0.000
0.034
Model summary
R
R2
Adjusted R2
SE of the estimate
0.786
0.617
0.603
0.4582
Note: Independent variables: customer-orientedness, reliability, tangibles and convenience; dependent
variable: WOM (word-of-mouth)
•
the service quality factor reliability is the second most important factor for
influencing WOM about the banks;
•
the service quality factor tangibles is the third most important factor for
influencing WOM about the banks; and
•
the service quality factor convenience is the fourth most important factor for
influencing WOM about the banks.
Customers’
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intentions
747
It is thus evident from the adjusted R2, that the model explains 47.7 per cent of the
variance in customers’ purchase intentions. The Anova table indicated that the
multiple regression model is statistically significant and that the independent variables
have a systematic association with the dependant variable.
In case of private sector banks, the regression coefficients indicated in Table VI offer
strong support for the facts that:
•
the independent variables customer-orientedness and reliability are significant
predictors of customers’ purchase intentions;
•
the service quality factor customer-orientedness is the most important factor
for influencing customers’ purchase intentions;
•
the service quality factor reliability is the second most important factor for
influencing customers’ purchase intentions; and
•
the service quality factor tangibles and convenience are non significant for
influencing customers’ purchase intentions.
It is thus evident from the adjusted R2, that the model explains 54.2 per cent of the
variance in customers’ complaining behaviour. The Anova table indicated that the
multiple regression model is statistically significant and that the independent variables
have a systematic association with the dependant variable.
In case of private sector banks, the regression coefficients indicated in Table VII
offer strong support for the facts that:
•
the three independent variables customer-orientedness, reliability and tangibles
are significant predictors of customers’ complaining behaviour;
•
the service quality factor customer-orientedness is the most important factor for
influencing customers’ complaining behaviour;
Constant
Customer-orientedness
Reliability
Tangibles
Convenience
Estimate (standardized coefficients)
5.274
0.974
0.637
0.125
0.132
SE
0.125
0.124
0.107
0.116
0.075
Prob
0.000
0.000
0.000
0.117
0.143
Table VI.
Private sector banks:
an analysis of the
Model summary
influence of
2
2
R
R
Adjusted R
SE of the estimate
customer-perceived
0.694
0.481
0.477
1.01
service quality on
Note: Independent variables: customer-orientedness, reliability, tangibles and convenience; dependent customers’ purchase
intentions
variable: purchase intentions
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•
the service quality factor reliability is the second most important factor for
influencing customers’ complaining behaviour;
•
the service quality factor tangibles is the third most important factor for
influencing customers’ complaining behaviour; and
•
the service quality factor convenience is non significant for influencing
customers’ complaining behaviour.
3.4 Public sector banks: effect of customer-perceived service quality on customers’
behavioural intentions
To explore the linkage between customer-perceived service quality and customers’
behavioural intentions, factor scores generated (for the factors obtained from the factor
analysis done on the entire data set of 720 customers) for the customers of the two
public sector banks (Bank C and Bank D) were pooled. The factor scores of the service
quality factors represented the independent variables, whereas customers’ behavioural
intentions represented the dependent variables (Table VIII).
It is thus evident from the adjusted R2, that the model explains 60.5 per cent of the
variance in customers’ willingness to engage in WOM about their banks. The Anova
table indicated that the multiple regression model is statistically significant and that
the independent variables have a systematic association with the dependant variable.
Estimate (standardized coefficients)
SE
Prob
Constant
2.344
0.101
0.000
Table VII.
Customer-orientedness
0.972
0.104
0.000
Private sector banks: Reliability
0.564
0.062
0.000
an analysis of
0.282
Tangibles
0.101
0.011
the influence
Convenience
0.126
0.053
0.116
of customerModel summary
perceived service
R
R2
Adjusted R2
SE of the estimate
quality on
0.741
0.549
0.542
0.8165
customers’
complaining
Note: Independent variables: customer-orientedness, reliability, tangibles and convenience; dependent
behaviour
variable: customers’ complaining behaviour
Table VIII.
Public sector banks:
an analysis of the
influence of
customer-perceived
service quality
on WOM
Constant
Customer-orientedness
Reliability
Tangibles
Convenience
Estimate
4.916
0.622
0.843
0.267
0.167
SE
0.145
0.065
0.043
0.074
0.101
Prob
0.000
0.000
0.000
0.007
0.102
Model summary
R
R2
Adjusted R2
SE of the estimate
0.791
0.626
0.605
1.0281
Note: Independent variables: customer-orientedness, reliability, tangibles and convenience; dependent
variable: WOM (word-of-mouth)
In case of public sector banks, the regression coefficients indicated in Table V offer
strong support for the facts that:
•
the three independent variables, reliability, customer-orientedness and tangibles
are significant predictors of customers’ willingness to engage in WOM about
their banks;
•
the service quality factor reliability is the most important factor for influencing
WOM about the banks;
•
the service quality factor customer-orientedness is the second most important
factor for influencing WOM about the banks;
•
the service quality factor tangibles is the third most important factor for
influencing WOM about the banks; and
•
the service quality factor convenience is non significant for influencing WOM
about the banks.
Customers’
behavioural
intentions
749
It is thus evident from the adjusted R2, that the model explains 54.7 per cent of the
variance in customers’ purchase intentions. The Anova table indicated that the
multiple regression model is statistically significant and that the independent variables
have a systematic association with the dependant variable.
In case of public sector banks, the regression coefficients indicated in Table IX offer
strong support for the facts that:
•
the two independent variables, reliability and customer-orientedness are
significant predictors of customers’ purchase intentions;
•
the service quality factor reliability is the most important factor for influencing
customers’ purchase intentions;
•
the service quality factor customer-orientedness is the second most important
factor for influencing customers’ purchase intentions; and
•
the service quality factors tangibles and convenience are non significant for
influencing customers’ purchase intentions.
It is thus evident from the adjusted R2, that the model explains 57.1 per cent of
the variance in customers’ complaining behaviour. The Anova table indicated that
the multiple regression model is statistically significant and that the independent
Constant
Customer-orientedness
Reliability
Tangibles
Convenience
Estimate (standardized coefficients)
4.756
0.468
0.934
0.242
0.232
SE
0.115
0.116
0.113
0.136
0.132
Prob
0.000
0.000
0.000
0.114
0.118
Model summary
R
R2
Adjusted R2
SE of the estimate
0.743
0.552
0.547
1.36
Note: Independent variables: customer-orientedness, reliability, tangibles and convenience; dependent
variable: customers’ purchase intentions
Table IX.
Public sector banks:
an analysis
of the influence of
customer-perceived
service quality on
customers’ purchase
intentions
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variables have a systematic association with the dependant variable. In case of public
sector banks, the regression coefficients indicated in Table X offer strong support for
the facts that:
•
the three independent variables, reliability, customer-orientedness and tangibles
are significant predictors of customers’ complaining behaviour;
•
the service quality factor reliability is the most important factor for influencing
customers’ complaining behaviour;
•
the service quality factor customer-orientedness is the second most important
factor for influencing customers’ complaining behaviour;
•
the service quality factor tangibles is the third most important factor for
influencing customers’ complaining behaviour; and
•
the service quality factor convenience is non significant for influencing
customers’ complaining behaviour.
4. Conclusion
The study shows that dimensions of service quality are important determinants for
behavioural intentions. Even though SERVQUAL has been studied in the banking
context, the explicit connections between service quality dimensions and customers’
behavioural intentions has been relatively under-researched in the banking sector.
This study aimed to probe the link between the individual dimensions of service
quality and customers’ behavioural intentions in the case of public and private sector
banks in India and explore the consequent societal implications for consumer and
public policy. Linking both constructs at their dimensional level increases the
diagnostics of explaining customers’ behavioural intentions.
In this study, the comparative analysis of the relation between service quality and
customers’ behavioural intentions in private and public sector banks show that for
influencing WOM, purchase intentions and complaining behaviour, in the case of private
sector banks, customer-orientedness is the most important factor while for public sector
banks, reliability is the most important factor. The factor customer-orientedness is
basically concerned with employees’ attitudes towards their customers. The service
quality factor reliability is related to the banks’ ability to perform the promised service
accurately and dependably. In this study, a modified SERVQUAL scale was used in a
context (the Indian retail banking sector) entirely different from the one in which
Table X.
Public sector banks:
an analysis of the
influence of
customer-perceived
service quality on
customers’
complaining
behaviour
Constant
Customer-orientedness
Reliability
Tangibles
Convenience
Estimate (standardized coefficients)
3.113
0.669
0.876
0.235
0.197
SE
0.112
0.057
0.086
0.103
0.104
Prob
0.000
0.000
0.000
0.002
0.037
Model summary
R
R2
Adjusted R2
SE of the estimate
0.761
0.579
0.571
1.02
Note: Independent variables: customer-orientedness, reliability, tangibles and convenience; dependent
variable: customers’ complaining behaviour
Parasuraman et al. (1991) had conducted their studies. This may explain the emergence of
service quality dimensions different from the ones identified by them.
Most of the private sector banks devote resources and attention to a small set of
comparatively wealthy retail and corporate customers, while a huge percentage of people
in India remain without access to formal, secure financial services. Private sector banks
do not target the poor as a market until they find ways to serve them profitably, which
they often do not. Moreover, their branch network is not even 10 per cent of an average
public sector bank. Their limited numbers of branches are only in those areas of
the country where their presence enhances the bank’s profits. This study reflects that for
the customers of public sector banks, a substantial portion of who are nowhere as
wealthy as the customers of the private banks, what is crucial is protection of their very
limited hard-earned money. Hence the factor reliability, comprising of variables like a
feeling of safety in the transactions with the bank, performing the service reliably, turned
out to be more important than the service quality factor customer-orientedness
characterized by personalized services, prompt service, employees giving personal
attention and employees having the knowledge to respond to customers’ needs, the latter
being more important when the bank offers complex state-of-the art products and
services as in the case of private sector banks. The point to note here is that what
constitutes good service quality in the private sector may not be the same in the public
sector, and quality management concepts may have to be modified in case of the public
sector to meet the unique needs of its customers.
In case of the private sector banks in this study, about 37-38 per cent of the customers
are self-employed (as opposed to about 11-12 per cent in the case of the public sector
banks), consisting mainly of well-to-do businessmen as well as doctors, lawyers and
consultants. It is an established fact that it is in the hands of the self-employed group that
the purchasing power lies. Both the two private banks studied have several marketing
practices and an impressive array of cutting edge products which are suitable for and
geared towards the self-employed group, especially businessmen and relatively affluent
groups of customers. Premium accounts where the customer has to maintain a
substantial minimum average quarterly balance – around 700 times more than what one
has to maintain in a public sector bank and he gets multiple benefits and waivers such as
free cash or cheque delivery or pickups, free cheque clearing between metros, free courier
facility, free funds transfers up to certain amounts, free cheque books, demand drafts and
bank statements whenever customers require them and home delivery of the same,
enhanced ATM withdrawal limits – these are commonly offered by private sector banks.
These services provided are useful for many businessmen, as they offer a range of
value-added features as well as flexibility. Moreover, better mobile and internet banking
services (many public sector banks do not have these), provisions for paying utility or
other bills online, better online investment and trading sites all serve to attract relatively
affluent people. Stronger and more effective inter-branch, intercity banking, a feature of
these banks, is also convenient for businessmen who often have to travel quite
frequently. Both the private banks in this study pay special attention to their high-net
worth customers who are required to maintain minimum balances which are around
500-600 times more than in public sector banks. This feature serves to exclude people
who will find it difficult to maintain these balances from being customers of private
sector banks. HNW customers are provided with a gamut of personalized services, as
well as relationship managers who provide a one-stop solution for them. The banks
are also focusing on the customers of their corporate salary accounts and giving them
many incentives, and depending upon the status of the company, are even waiving
Customers’
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off the minimum balance requirements. Hence it can be seen that the marketing
practices of these two private banks are geared towards the relatively affluent people.
Now for this base of customers it is reasonable to assume that they may be
time-pressed and hence factors such as the promptness and responsiveness of the
service is expected to be very important so as to make it convenient for them to carry
out their banking transactions in spite of their busy schedules. The customers of
these banks state that the reason they started transacting with private banks is
because they expect to be specially treated in the sense of being given a priority when
they come to the bank and to get faster and more efficient service, than what a public
sector bank gives them. The very term “private bank” itself denotes to them
efficiency, and they are willing to and can afford to lock up a large amount of money
for those services. These reasons can perhaps explain as to why for customers of the
private sector banks, customer-orientedness is the most important service quality
factor for influencing behavioural intentions.
In case of the public sector banks, minimum balances that are to be maintained in the
savings, current and fixed deposit accounts are about 500-600 times lower than that for
HNW customers of private sector banks. For instance, at the Bank C, the customer can
open a savings account with a minimum deposit of INR500 for metro, urban and
semi-urban branches and INR250 for rural branches with cheque book facilities. Without
cheque book facilities, the rates are even lower. In fact, a few public sector banks have
started having a “no minimum balance required policy” for all customers. Again, although
technological advances (such as provision of ATM services) provide customers with
automatic and impersonal services, customers, especially those of the public sector banks
a majority of who are not so well-educated, and/or perhaps older in age (because pension
of retired government employees is paid only through public sector banks) and not so
comfortable with technology, still need direct help from the banks’ employees to solve
their problems and concerns. They often want to communicate with the banks’ employees
via traditional communication media, like telephone and mostly face-to-face meetings.
An important finding from the in-depth interviews was that a majority of the customers
explained that the most important reason they transact in public sector banks in spite of
the crowded conditions, the heat, long queues, very long waiting times and often quite
unresponsive and tardy service is the feeling of safety that they get, the assurance that
their very hard-earned money will be protected and secure. These are therefore the areas
which the government has to pay attention to so as to strengthen and enable the public
sector banks to cater to the specific set of needs which are unique to their customer base,
comprising the “masses” of India. However, at the same time, the challenge that public
sector banks face is that besides serving the masses, they also serve well-off customers
who value the “security” that public sector banks offer, but who post-liberalization of the
Indian banking sector, demand responsive, personalized, fast service and services like
“banking delivered at your home” akin to that provided by private sector banks. However,
public sector banks often fail miserably in this regard. As one manager of a public sector
bank put it: “we are into mass banking and not class banking”. This is another area that
the government at the macro level has to reflect on as it crafts enablers for public sector
banks to remain competitive while fulfilling their social objectives.
4.1 Implications for public and consumer policy
This study raises important implications for public and consumer policy. Consumer
policy considerations traverse virtually everything the financial services sector does,
yet governments often make many consumer policy decisions without specific data and
research regarding the financial marketplace. The important point to note, however, is
that, crafting of consumer policy for a country as large, complex, populous and diverse
as India is intrinsically much more complex than in a smaller political entity. Besides
serving well-off customers, public sector banks in India serve economically
disadvantaged customers as well with objectives that are social rather than purely
commercial, unlike their private sector counterparts. Public sector banks maintain huge
branch networks which serve rural areas and even the most remote corners of
the country in order to provide access to banking services for all. Most importantly,
the minimum balances that one requires to maintain in public sector banks is
decreasing day by day with the aim to encourage the economically disadvantaged,
poorer sections of society to keep even their very meagre savings in a bank instead of
falling prey to fly-by-night operators who give these poor and illiterate people false
promises of very high returns and then elope with their money.
Priority sector lending is another initiative of the Government of India to nurture the
social banking concept. Public sector banks are required to take a big role here and ensure
credit delivery to priority sectors like agriculture, small scale and cottage industries, small
businesses, as well as finance education and schooling amenities, housing, healthcare and
other facilities like sanitation and clean water for the weaker sections of society and
entrepreneurial projects by women. Microfinancing, with its promise of financial
sustainability and provision of informal and flexible financial services to the poor is also
one of the growing areas in the portfolio of public sector banks. Hence there is the
imperative to have the right regulations in place in creating the appropriate environment
for banks to provide adequate and timely finance at reasonable rates as well as cater to
the special needs of a large section of its customers who are quite different from the
customers of private sector banks, in order to attain the objectives of social and economic
development for its customers. As mentioned earlier, the test that public sector banks face
is that besides serving the masses, they also serve affluent customers, who in this
competitive phase of the Indian financial sector demand responsive, customized, more
effective and speedy service like that offered by private sector banks. This is another
challenge area that macro-level policy formulation has to consider so that public sector
banks remain competitive while satisfying their social objectives.
All said and done, when one of the major reasons behind public and consumer policy
in the banking sector in India is to protect the unprivileged customers’ interests, the
public sector banks need to be supported and strengthened in order to continue fulfilling
their roles for social service, satisfying their customers’ unique needs and meeting their
social objectives while concurrently being able to compete with private sector and foreign
banks. The areas for strengthening and development could include instituting delivery
channels that are far-reaching, yet inexpensive to set up, ensuring the preservation of the
branch network of the banking system to ensure that banking services continue to reach
the remote corners of the country, providing a wider range of focused financial services
to poor customers, responding to their needs for assurance, safety and hand-holding and
enhancing the ability to handle transactions at low cost. Private and foreign banks enjoy
certain privileges compared to the public sector banks. Being late entrants they have not
been tied down by constraints in technology infusion, and they enjoy comparatively
more freedom in the matter of recruitment of professionals on attractive remuneration
packages. Last but not the least, public sector banks have to deal with huge customer
bases and daily branch transactions worth at least 60 times more than in private sector
banks in terms of the number of customers served per day in a typical branch. On top of
that public sector banks are required to maintain an extensive network throughout the
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country, even in the most inaccessible, unprofitable regions. These are certain areas
where public sector banks suffer a disadvantage and these should be addressed from a
public and consumer policy perspective. A significant input into a bank is its people.
Being a service industry, the quality of services is directly related to the quality of people
and their ability to satisfy the customer. Hiring and training of employees is one crucial
area that needs to be looked into for the public sector banks which are facing the
pressures of competition. For instance, this study highlights the importance of a feeling
of safety in the transactions with the bank in the case of public sector banks. What this
means in terms of training and evaluating employees should be given thought to in
policy formulation. In the case of public sector banks especially, which have a unique
challenge in the different categories of customers it serves, (for instance with regards to
financial positions – the well-off and not so well-off and the very poor), policy needs
to address the question of how frontline staff need to be more attentive to and aware of
the differences between different segments of customers and provide information and
services in more customized, targeted ways. Most importantly, it is necessary
to recognize the importance of quality to not only services and service delivery but also to
policy formulation. From this larger perspective, an excellent public organization is not
simply one which is an excellent service provider but which also discharges its political
and social responsibilities to its electorate. Hence in the case of crafting of public and
consumer policy in the area of banking service quality, quality indicators should not only
focus on monitoring service quality as provided by individual organizations but also on
the quality of services provided by the overall financial service system in the country.
Moreover, high-quality financial consumer policy must not only be able to increase
customer satisfaction with financial services but also build security and trust in public
administration through transparent processes and accountability. In this context, with
public agencies being regarded as service providers and citizens as customers, the
concept of quality must also visualize public agencies as catalysts of a responsible
and active civic society.
5. Limitations of the research and directions for further research
Future research can focus on “service excellence” being extended beyond assessment
of the quality of services towards evaluation of the quality of life outcomes to which
public organizations contribute, appraisal of the quality of public governance
processes and quality of performance in meeting social objectives. The findings of the
current study also deserve replication across other countries with different cultures,
in order to explore how service quality influences customers’ behavioural intentions,
in the context of both private and public sector banks and explore the consumer
policy implications therein. This study was primarily quantitative. In future
research, in-depth interviews can be carried out in to capture aspects of customers’
perception of service quality and their behavioural intentions that are not possible to
cover with SERVQUAL and similar quantitative studies. The analytical procedure
itself, i.e., a factor analysis of difference scores of SERVQUAL has received
considerable attention in the literature in the recent years. Even though SERVQUAL
has been reported to have greater diagnostic power to highlight areas for managerial
interventions in the event of service quality shortfalls, the SERVPERF scale
according to many researchers, provide a more convergent and discriminant valid
explanation of the service quality construct. In future research, both SERVPERF and
SERVQUAL may be compared to assess the profile, overall service quality, areas of
service quality shortfall and number of factors obtained.
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Customers’
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Further reading
Choudhury, K. and Pal, M.N. (2009), “Exploring the dimensionality of service quality: an application
of TOPSIS in the Indian banking industry”, Asia-Pacific Journal of Operational Research,
Vol. 26 No. 1, pp. 115-133.
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Corresponding author
Dr Koushiki Choudhury can be contacted at: koushiki@iimcal.ac.in
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