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8/3/2019 IJSEM20105_Nuseir et al[1].[1]
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Int. J. Services, Economics and Management, Vol. X, No. Y, XXXX
Copyright © 200X Inderscience Enterprises Ltd.
The effect of e-service quality on customers�satisfaction in banks operating in Jordan:an empirical investigation of customers� perspectives
Mohammed T. Nuseir
School of Management,
New York Institute of Technology,
Amman, Jordan
Email: [email protected]
Mamoun N. Akroush*
Talal Abu-Ghazaleh College of Business,
German-Jordanian University
P.O. Box 921951, Amman 11192
Jordan
Email: [email protected]
*Corresponding author
Bushra K. Mahadin
Faculty of Banking and Financial Sciences
The Arab Academy for Banking and Financial Sciences,Amman, Jordan
Email: [email protected]
Abdullah Q. Bataineh
Faculty of Administrative Studies,
Amman Arab University for Graduate Studies,
Amman, Jordan
Email: [email protected]
Abstract: The aim of this research is to examine the relationship between thee-service quality dimensions and customer satisfaction of banks in Jordan.
Using a structured questionnaire, the primary data was collected from457 customers who had e-banking transactions with banks in Jordan. Multipleregression analysis was employed to test the research model and hypotheses.The research findings indicate that e-service quality dimensions that arewebsite attributes, reliability, perceived risk, responsiveness and customisationhave a positive and significant effect on the banks overall customers�satisfaction and its elements individually. The findings also indicated that thestrongest predictors, based on beta values, of e-service quality dimensionson the overall banks customers� satisfaction and its individual elements areresponsiveness, website attributes and customisation, respectively. Researchresults, conclusions, practical recommendations, contributions to e-servicequality research and future research opportunities are also discussed.
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Keywords: e-service quality; e-customer satisfaction; responsiveness; website
design; customisation; financial services; banks; Jordan.
Reference to this paper should be made as follows: Nuseir, M.T.,Akroush, M.N., Mahadin, B.K. and Bataineh, A.Q. (XXXX) �The effect of e-service quality on customers� satisfaction in banks operating in Jordan:an empirical investigation of customers� perspectives�, Int. J. Services, Economics and Management , Vol. X, No. Y, pp.xxx�xxx.
Biographical notes: Mohammed T. Nuseir is an Assistant Professor of E-Marketing and International Marketing at New York Institute of Technology,Jordan. He is a trainer in several corporations on implementing e-marketingstrategies, sales management skills and cross-cultural marketing. He has alsosupervised graduate students� theses and has experience in teaching andlecturing both graduate and undergraduate in many universities. He holds hisPhD degree in international business and marketing and a Master�s degree
in technology management both from the USA. He also holds a postgraduatedegree in e-marketing studies from British Columbia, Canada.
Mamoun N. Akroush is an Associate Professor of Marketing Strategy at TalalAbu-Ghazaleh College of Business, the German-Jordanian University. He isVice Dean of Talal Abu-Ghazaleh College of Business. He received his PhDfrom the University of Huddersfield, England. His research interests includemarketing strategy, marketing knowledge management, services marketing andstrategic marketing planning. He has published several research papers in thefield of marketing in international and national refereed business journals.He is an expert in marketing strategies and plans, customer service andmarketing research. He is involved in many consulting and training projectswith international organisations and bodies specifically the United NationsDevelopment Programs in the Middle East.
Bushra K. Mahadin is currently a full-time Marketing Lecturer at theFaculty of Banking and Financial Sciences at the academy. She holds her BA degree in business administration, and an MBA degree in businessadministration/marketing from the University of Jordan. Her main researchinterest is studying consumer behaviour, and her current research activitieslie within the fields of e-service quality and e-marketing. Prior to joining theacademia, she acquired practical experience in a number of fields includingresearch, consulting, branding, advertising, lecturing and training throughworking in both the private and public sectors.
Abdullah Q. Bataineh holds an MBA/marketing degree from the ArabAcademy in banking and financial sciences, and a bachelor�s degree fromApplied Science University, Jordan. He worked in sales, customer service andsales promotion in several types of businesses in Jordan. His research interestsare in e-marketing, sales promotion and sales management. He has just joined
the Amman Arab University for Graduate Studies in Jordan as a graduate student.
1 Introduction
In today�s world of fierce competition, rendering quality service is key of subsistence and
success, prior research shows that cardinal accent of both academia and business
focused essentially on ascertaining the customers� perception of service quality and
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subsequently contriving strategies to meet and surmount customer expectancies.
Numerous organisations have started venturing into multifarious approaches toameliorate the quality of their service (Sureshchandar et al., 2001). The research
literature on service quality and satisfaction is copious, with various contributions from
numerous researchers over the past few years. However, the SERVQUAL instrument of
Parasuraman et al. (1988), a 22-item scale that measures service quality along five
dimensions, forms the key stone for all other works. The SERVQUAL five dimensions
are tangibles, reliability, responsiveness, assurance and empathy. The entire approach
was formulated on the tenet that customers entertain expectations of performances on
service dimensions, observe performance and later form performance perceptions
(Sureshchandar et al., 2001). In contrast to the above, only a limited number of scholarly
articles deal directly with how customers assess e-service quality and its antecedents and
consequences (Parasuraman et al., 2005).
Less than a decade ago, the internet was a curiosity presenting interesting questions
about the future directions of service operations management, since then service
delivered via the internet has quickly emerged as an important class of service operations
(Field et al., 2004). Boyer et al. (2002) defined e-services as all interactive services that
are delivered on the internet using advanced telecommunication, information and
multimedia technologies. As with other services, e-service customers need to be able to
assess the quality of e-service in order to make informed buying decisions. The ability to
access reliable information about service quality is especially critical since the poor
quality of many e-services has already been documented (Field et al., 2004). In this paper
and drawing on previous conceptual and empirical research of e-service quality, we have
developed e-service quality and customer satisfaction model, and hypotheses to be
investigated in banks operating in Jordan. The idea of this research has emerged to
respond to important calls from e-service quality authors who have argued that more
empirical research is needed in this area.
2 The research problem
Based on a thorough examination of e-service quality literature review, the research
problem is concerned with examining the relationship between the e-service quality
dimensions and customers� satisfaction in the banks that have e-transactions with their
customers in Jordan. This examination has revealed that there is a need to conduct
empirical research in the area of e-service quality in business sectors and to examine if it
has an effect on customers� satisfaction (e.g. Dillon and Reif, 2004; Parasuraman et al.,
2005; Bauer et al., 2006; Huei-Chen, 2007). In Jordan, there is a severe competition
between banks and they are really interested in the e-business in general and in providing
reasonable quality of e-services in particular. Initial discussions with recognised banks inJordan revealed that they are interested to understand the elements of e-service quality
they provide, and the extent to which customers are satisfied about the quality of
e-transactions. Consequently, this research paper is an attempt to answer the following
questions:
1 What are the e-service quality dimensions in the banks of Jordan?
2 Are customers satisfied about the quality of e-transactions?
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3 Is there any relationship between the e-service quality dimensions and the
overall customers� satisfaction?
4 Is there any relationship between the e-service quality dimensions and the
individual elements of customers� satisfaction?
5 What are the most influential dimensions of e-service quality on the overall
customers� satisfaction, and its individual elements?
3 The research objectives
The research aims to achieve the following objectives:
1 To identify the e-service quality dimensions in the banks of Jordan.
2 To identify the level of customer satisfaction about the quality of e-transactions
in the banks of Jordan.
3 To investigate the relationship between the e-service quality dimensions and
the overall customers� satisfaction, and its elements individually.
4 To reveal the most influential dimensions of e-service quality on the overall
customers� satisfaction, and its elements individually.
3.1 E-service quality literature
The e-service quality literature review has revealed that it has an effect on banks financial
performance, customers� satisfaction and loyalty. There is a reasonable body of e-service
quality literature that has investigated either its relationship with performance or
customer satisfaction in several business sectors. Phau and Poon (2000) discussed the
factors that influence the choice between a retail store and the in home shopping methods
such as mail/phone, and the internet. Some of which include socioeconomic and
demographic factors, perceived purchase risk, product type and distribution methods,
personal traits or characteristics, shopping or delivery time. They have also indicated that
the internet, as a marketing channel, has both unique characteristics and characteristics
that are shared with other marketing channels. For instance, it has the ability to store
large amounts of information at different location and provide information to the
consumer on demand. There is also the advantage of a physical distribution medium
for certain goods (e.g. software) with relatively low entry and establishment cost for
sellers. Their literature review findings suggest that online marketing should be perceived
by five components that are promotions, one-to-one contact, closing, transaction andfulfilment.
McQuitty and Peterson (2000) referred to Georgia Institute of Technology recent
study which found that the quality of information, ease of ordering and reliability were
more important to respondents than security. This finding may be explained by the fact
that respondents tended to have considerable online experience and hence are probably
aware that internet security has been increasingly effective over time. Conversely, a
recent study found that security was the most important factor (www.ey.com/industry/
consumer/internetshopping.pdf), which demonstrates the considerable uncertainty
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regarding most aspects of online shoppers and retailers. Another observation from
the Georgia Institute of Technology study was that although many people performedsubstantial online browsing with no immediate intent of purchase. They also used the
internet for browsing when there was intent to purchase. This suggests that retailers can
and should use web pages to attract shoppers even if many website visitors are only
browsing. Milloy et al. (2002) indicated that among the notable concerns identified by
consumers when making purchasing decisions on the web are security of financial
transaction and privacy, mainly for credit cards and other personal information. The
security of online payment systems is cited as key reason for consumers not engaging in
online purchasing and generally being distrusting of e-retailing.
Van Riel et al. (2003) conducted an empirical investigation on e-service quality
expectations. The researchers distributed online questionnaires to predominantly college
students and recent college graduates. They focused on a commonly used electronic
service which is online flight reservations using a sample of 159 college students. Thequestionnaire measured the overall disposition of the participants towards e-service and
the levels of e-service quality that they deemed adequate and desirable. Their study used
an adapted version of the SERVQUAL model five dimensions to adjust the investigation
to e-service quality expectations. The e-service quality dimensions in their study were
tangibility, reliability, empathy, customisation, security and responsiveness. Based on the
research findings, the researchers recommend that companies improve the quality of their
services continuously, making sure they compete at the level of the highest standards in
the market. For e-services, the dimensions relating to reliability and security of the
service deserve greatest attention. Opportunities to delight customers, by exceeding
desired quality levels, appear to exist in those dimensions that have the lowest desired
quality levels, i.e. design of the user interface and customisation.
Further research has also tackled the issue of online service from a customer point
of view. Sarel and Marmorstein (2003) argued that banks seem to be continuouslyimproving the service, offering more capabilities and increasing reliability. Several
consumers reported that having access to faster internet connections, at home or at work,
made the experience much better. The adoption of digital subscriber line connections, for
example, helped consumers resolve some of the problems. They have classified the user
groups into three groups: active users, light users and non-users. They have found that
banks have invested heavily in developing online capabilities hoping to be able to
migrate customers to the new cheaper delivery system. Clear deficiencies were identified
by consumers in this system. The following factors were found of sound importance
in this study: perceived relative advantage (or felt need), complexity, compatibility,
communicability, perceived risk, divisibility and prospects.
Dillon and Reif (2004) classified the factors that influence a consumer purchase
decision and online shopping behaviour into four clusters of purchase perceptions. Theseclusters are product understanding, shopping experience, and customer service and
consumer risk. Dillon and Reif (2004) study sought to develop a better understanding
of the factors motivating young people to select e-commerce vendors for commodity
purchases by exploring attitudes, demographic characteristics and purchase decision
perceptions. Their findings indicated that young adults with history of e-commerce
purchasing experience have a more positive attitude towards online buying than do
young adults without e-commerce purchasing experience. The research indicated that
reliability occurs when the customers perceive that there is high probability that the
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service provider will deliver precisely what is being promised within the proper time.
Internet purchases of tangible goods present unique challenges compared with traditional brick and mortar retail store purchases. Consumers do not have the ability to inspect the
goods prior to purchasing them. Instead internet purchases must rely on mediated
representations of the goods being purchased which are normally dependent on third
parties for delivery of purchased goods and may question the convenience of product
returns. The research has also discussed that customer service affects purchase decisions
through vendor knowledge and responsiveness. These two elements are embodied in
the way that the service provider anticipates and responds promptly and effectively
to customers� needs and requests, providing the customer with knowledge necessary to
make purchase. Field et al. (2004) carried out a comprehensive literature review on the
e-service quality dimensions that were investigated in previous research. They found that
the e-service quality dimensions that were website design and attributes, reliability,
responsiveness, customer service, customisation, website security and website perceivedrisk. They also found that previous studies investigated either some dimensions or several
dimensions of e-service quality in different e-business sectors.
Sarel and Marmorstein (2004) discuss previous studies that examined consumers�
beliefs about, and behaviour towards, banks� online service offerings. By focusing on the
�voice of the customer�, they found two important and interrelated insights. Firstly, it
became clear that the consumer innovators who adopted this new category of bank
service were fundamentally dissimilar to the next wave of customers that banks sought to
bring online. Specifically, the first wave of adopters was largely cyber-consumers who
were favourably predisposed to performing this, or almost any other, activity online.
Prospective adopters, on the other hand, are less aware of the potential benefits, are
concerned about costs and risks involved and do not necessarily share a �felt need� for the
service. Secondly, while early adopters are now largely satisfied with online banking
service, they can hardly be described as raving fans; very little spontaneous word-of-mouth communication is forthcoming. Collectively, these findings help explain the very
disappointing rate of consumer adoption of online banking through 2002 and believe the
inevitability of the diffusion of these banking services to the majority of consumers. They
indicated that given the fact that most prospects were not convinced about the value of
online banking, it is important for banks to communicate the benefits to prospects.
Banks were expected to entice customers and provide them with reasons to consider this
new service. They distinguished between �list of functions�, �benefits� and �links only�.
Functions are lists of capabilities (e.g. check balances, transfer money), whereas benefits
are defined here as outcomes (time savings, control, saving money, etc). �Links only�
implies that no information about the online service was provided on the front page;
instead, only a link to a different page was available. Surprisingly, they mentioned in
2002, 34.7% of all banks provided �links only� with no additional information on thefront page. About one-third of the banks provided a list of functions available to
customers. Only 32% of the banks provided benefit descriptions or incentives to consider
the service on the front page. In 2003, the information provided on the front page had not
changed materially. Benefits are still used in only one-third of the websites. There has
been a slight decline in the list of functions and an increase in �links only�. Clearly, the
majority of banks still do not believe it is important to highlight the benefits. Almost all
banks, at some point, provided a list of capabilities or benefits. They conclude that most
US banks have focused their marketing efforts on simply making the service available
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and informing consumers about this availability. Sites were designed to be functional
with little attempt to communicate real benefits to consumers. In most cases, the initialonline experience did very little to persuade or encourage customers to try the service.
One of the comprehensive research efforts on e-service quality is an exploratory
study carried out by Parasuraman et al. (2005). This study has empirically tested a
multiple-item scale called (E-S-Qual) for assessing service quality of online shopping
providers. Two stages of empirical data revealed that two different scales were necessary
for capturing electronic service quality. The basic (E-S-Qual) � which was developed
after conducting two focus group interviews with graduate students at a major university
in the Eastern USA, then administering an online questionnaire which yielded a total of
549 responses � resulted in a 22-item scale of four dimensions that are efficiency,
fulfilment, system availability and privacy. The second scale, E-R-S-QUAL, is salient
only to customers who had no routine encounters with the sites, it sought measuring
the quality of recovery services provided by websites and contains 11 items in three
dimensions that are responsiveness, compensation and contact. The researchers
conducted additional empirical research to further examine the scales structures and
properties and found both scales demonstrated good psychometric properties based on
findings from a variety of reliability and validity tests. However, the researchers indicate
that E-R-S-QUAL should be viewed as a preliminary scale because the small samples of
customers with recovery service experience at the sites used in later stages of scale
testing which did not permit a comprehensive psychometric assessment of that scale.
Furthermore, the researchers selected only amazon.com and walmart.com for the
confirmatory phase of their research which were the most visited websites at the time,
but they both had low incidence of problem encounters.
Bauer et al. (2006) suggested a comprehensive conceptual framework that captured
relevant quality aspects of the virtual service transaction. They suggested that the
e-service quality transactions consists of four major stages, namely information phase,agreement phase, fulfilment phase and after-sales phase (for further details, see study of
Bauer et al., 2006). They also tried to fill into the gaps they have found into other
previous research, especially aspects related to enjoyment of websites use and after-sales
support. Therefore, the research integrated hedonic quality aspects, which resulted from
intrinsic shopping motives. Their strong influences on perceived value indicates that
shopping behaviour cannot be described as purely goal oriented and rational as suggested
by many other researchers. Instead hedonic and emotional motives play an important
role. The researchers conducted 30 semi-structured interviews with online shopping users
that focused on tapping consumers� feelings and expectations regarding online shopping.
The quantitative data was collected by a structured questionnaire where the respondents
judged the performance of 53 quality attributes on a five-point Likert scale. The
dimensions of eTransQual were functionality/design, responsiveness, reliability, process
and website enjoyment. However, Bauer et al. (2006) said that further studies could testthe eTransQual scale for other populations of web users like browsers and non-buyers in
order to confirm the generalisability of the results, which has been a limitation to this
research because it has only focused on those who made actual purchases with a
shopping site.
Sarel and Marmorstein (2006) made attempts to tackle online security as a major
problem for financial institutions worldwide. The researchers argued that account
hijacking and online fraud are on the rise. Financial losses in the banking industry due to
attacks have been estimated in 2003 to be about US$ 1.2 billion in the USA alone.
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Studies also indicated that security concerns are a major issue for an increasing number
of consumers. The rapid growth in phishing attacks threatens the future of online banking. In the absence of an adequate response, banks are likely to incur even greater
costs and experience a significant decline in consumer trust. They discussed the
assessments of the actual and consumer perceived threats along with the available
technical solutions provided. They recommended the need to involve the consumer in
managing security concerns. The findings of the research paper indicate that many banks
are not meeting the challenges facing them and significant opportunities for improvement
exist. Smaller banks, in particular, are failing to take the necessary actions.
Huei-Chen (2007) discussed dimensions of consumer perceived online risks that are
usually considered from customers� perspective. Personal risk, it refers to the possibility
that the consumer will be harmed or injured by either the product or the shopping
process. Privacy risk, it reflects the degree to which a consumer sacrifices their privacy
when they are required to provide confidential information in the course of makinga retail ecommerce transaction, and performance risk that embodies the consumer
perception that a product or service may fail to meet expectations (the fear of not getting
what they want). Huei-Chen (2007) conducted an online survey to test their conceptual
model; a questionnaire was developed and administered mostly to undergraduate
business students in four universities. They returned 427 usable questionnaires out of
651 sent questionnaires. They found that Chinese consumers� exposure to online
products is relatively new, and it appeared that their searching experience online is
reducing their perceived risk of quality concerns and it affects their choice of private
label brands.
3.2 Customer satisfaction
There has been a reasonable research interest on e-customer satisfaction within thee-service quality context. Customer satisfaction is a cumulative construct that is affected
by service expectations and performance perceptions in any given period and is affected
by past satisfaction from period to period. It plays an important role in such a competitive
industry because it closely affects customer loyalty. Ha (2006) argues that despite the
overwhelming quantity of literature surrounding the concept of satisfaction, some
�key issues� have either gone unresolved or have recently been brought into question.
One such issue is the question, �what is the actual satisfaction model on the web?�
(Ha, 2006). He argued that although satisfaction is recognised as an important facet of
marketing, there is no general agreement of how the concept should be defined. This lack
of a concise definition further validates the supposition that satisfaction does not mean
the same thing to everyone. Consequently, in this study, we utilised a recent perspective
to define e-satisfaction as the degree of customer contentment with regard to his/her prior purchase experience with a given electronic commerce firm. Literatures of customer
satisfaction indicated that customer satisfaction is one of the most important financial and
nonfinancial indicators that show that an organisation is in the right direction. Several
empirical studies found that customer satisfaction leads to increase businesses profits
margins (Rust et al., 1995), profitability (Zeithaml et al., 1996), return on investment
(Anderson et al., 1994; Anderson et al., 1997) and customers� loyalty and retention rates
(Zeithaml, 2000).
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An empirical investigation of customers� perspectives
One of the important issues in customer satisfaction literature is how to measure
customer satisfaction. Examining relevant customer satisfaction literature has revealedthat there are two dominant approaches being used to measure it. First, expectations and
disconfirmation approach (Parasuraman et al., 1988; Ha, 2006). One of the most
widely studied antecedents of satisfaction is pre-purchase expectation. Expectations
have become the central construct of consumer satisfaction research. Expectations for
service performance represent a priori standard that consumers bring to a consumption
experience. Within the marketing literature, expectations appear most widely in
definitions of service quality and consumer satisfaction, but here they can range from
being subjective desires to more objective predictions disconfirmation of expectations
usually means that service performance falls short of (or exceeds) what a consumer
expected when making a purchase decision with negative (or positive) implications for
the experience. Therefore, it seems plausible that a service performance exceeding
expectations can cause pleasure and a shortfall in performance can cause displeasure.Second, perceived performance (Cronin and Taylor, 1992), in this approach, expectations
are compared to perceived performance in order to arrive at an evaluation. Performance
here refers to the customers� perceived level of service quality relative to the price
they pay. Perceived performance is affected by characteristics of the service and
circumstances surrounding its acquisition.
Previous research of customer satisfaction has used both approaches and each one
has its own strengths and weaknesses. For example, several authors have found that
the expectations and disconfirmation approach suffers from some conceptual,
methodological, reliability and validity problems (e.g. Carman, 1990; Newman, 2001).
The perceived performance approach, it relies heavily on measuring customers�
satisfaction based on the actual performance of a product or service from customers�
perspectives (Cronin and Taylor, 1992; Gilbert et al., 2004). This approach seems to be
relatively to have stable reliability and validity and does not suffer from manymethodological problems. In addition, this approach has been used in leading studies of
customers� satisfaction (e.g. Cronin and Taylor, 1992; Gilbert et al., 2004; Bennett and
Rundle-Thiele, 2004; Keiningham et al., 2005). Consequently, this approach is used in
our study as well as in e-service quality studies.
Ha (2006) carried out a study using a survey-based procedure to collect data for a
number of websites. The final instrument was administered as an email: web fill-out form
in 2003 in Korea. The survey was designed to include a number of different websites
based on consumer experience, which included auctions, bookstore and travels. A total of
680 subjects were randomly sent emails of which 229 (33.6%) returned as valid. The
findings show that customer satisfaction directly affects the outcome variables without
the mediating role of perceived service quality. More specifically, service quality is not a
requirement, but a sufficient condition. The researchers also point out that service qualitymight not be an antecedent of customer satisfaction because service quality is more
abstract than customer satisfaction and it is likely to be influenced by variables such as
advertising, other forms of communication and the experience of other consumers.
Chea and Luo (2006) argue that in today�s turbulent e-commerce environment,
possessing cutting edge technology and value added services are not sufficient anymore.
Online companies need to have a long-term client relationship strategy and constantly
understand customer retention behaviour and know how to satisfy customer needs to
keep them coming back. Their study examined six constructs as follows: continuance
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intention (user intention to continue using the service), disconfirmation (user perception
of congruence between expectations of e-service use and its actual performance),satisfaction (user affect with, feeling about, prior e-service use), perceived usefulness
(user perception of expected benefits of e-service use), negative affectivity (a stale and
pervasive individual difference characterised by tendency to experience aversive
emotional state) and perceived switching cost (consumer perception of the time, money
and effort, associated with changing service provider). They employed an online
survey, and data was collected from undergraduate students, in total 108 students
participated in the survey. They confirmed the expectancy confirmation theory in the
sense that customer satisfaction is determined by the degree of customer confirmation or
disconfirmation with the level of service provided by an e-service provider when using
an e-service. Their results also show that customer satisfaction in turn influences the
intention to continue to use an e-service. Perceived usefulness of an e-service influences
continuance intention directly and indirectly through the mediating effect of satisfaction.Zhang et al. (2006) addressed the social and technological context of online
purchasing issues. For example, they used satisfaction and intention to address the
social impact of using e-service systems; perceived convenience, perceived security
and website characteristics to emphasise the technological impact of e-service systems;
and, finally, prior experience and computer skills to emphasise personal factors to an
e-service system. They indicate that, technology is a tool that allows companies to
automate service delivery process and transaction processes. Their research model
contains constructs of perceived convenience, perceived security, website design
characteristics, user satisfaction and intention. They collected data from two large public
universities in the USA, one in the Southeast and the other in the Northeast. A total of
1550 subjects were asked to participate in the survey. They concluded that, e-service is a
field with great potential, with numerous tools and technologies available to businesses
that want to succeed in it. Businesses need to make wise decisions about choosing theright technology to manage the services their company provides on the internet. Like
many other new internet-enabled activities, e-services come with benefits and pitfalls.
Although e-services are effective in reaching more users at relatively low cost, users
frequently find them impersonal. Thus, it is important to make sure that users are
satisfied with the quality of services received online. The study found that user
satisfaction towards e-services was affected by perceived convenience, perceived security
and user characteristics. The perceived convenience of an e-service site is influenced by
site characteristics, including ease of use and responsiveness. Also, user satisfaction
significantly affected future-use intention. Based on the previous discussion, it is
clear that e-customer satisfaction is an important consequence of e-service quality.
Furthermore, the e-customer satisfaction needs to be understood thought measuring the
overall e-customer satisfaction and its elements individually in the context of e-servicequality.
4 The research model and hypotheses
Based on the e-service quality literature review and customers� satisfaction and the
research problem and objectives, a research model is developed to be empirically tested.
Figure 1 shows the research model.
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An empirical investigation of customers� perspectives
Figure 1 The proposed research model
Independent Variables Dependent Variable
Website Attributes
Reliability
Responsiveness
Customisation
Perceived Risk Customer Satisfaction
Proposing the aforementioned model, this paper builds on the critical examination of
the e-service quality literature review including empirical work and conceptual gaps;
it is argued that e-service quality has a positive effect on customers� satisfaction
among several businesses. The majority of the discussed literature review has indicated
that well-designed and managed e-service quality leads to customers� satisfaction.
Accordingly, within the banking sector of Jordan, this paper proposes that the
relationship between the e-service quality and customers� satisfaction can be studiedthrough examining the relationship between e-service quality dimensions that are as
follows: website attributes, reliability, perceived risk, responsiveness and customisation
and customers� satisfaction. Building on this argument, the existence of these dimensions
will positively affect customers� satisfaction. Consequently, it can be hypothesised that:
H1: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the overall customers�
satisfaction.
The literature review of both e-service quality and customer satisfaction indicated that
customer satisfaction is a multidimensional construct. This paper proposes that customer
satisfaction is measured based on overall satisfaction and its elements individually in
relation to e-service quality dimensions examined in the context of commercial banks of Jordan. In other words, customers could experience a �general satisfaction� with the
quality of e-banking services that banks provide but not satisfied with some elements of
e-service quality. At the same time, a bank should be able to understand the most
influential dimensions of e-service quality on customers� satisfaction either collectively
or its elements individually. Consequently, the individual elements of banks customers�
satisfaction regarding the quality of provided e-banking services should be investigated
to provide strategic insights related to the effect of e-service quality on customers�
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satisfaction elements individually. Building on this argument, the e-service quality
dimensions will positively affect the website attributes and design element of customers�satisfaction. Consequently, it can be hypothesised that:
H2: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the website attributes
and design element of customers� satisfaction.
E-service quality literature has also indicated that it is a multidimensional construct and
its dimensions have various effects on customers� satisfaction. A well-designed e-service
quality dimensions will positively affect customers� satisfaction related to website
reliability. The rationale behind this argument is that high quality of e-banking services is
a major driver of customers� satisfaction website reliability and they can rely on it in
making future transactions. Consequently, it can be hypothesised that:
H3: There is a relationship between e-service quality dimensions (website attributes,reliability, perceived risk, responsiveness and customisation) and the reliability element
of customers� satisfaction.
A further examination of e-service quality literature indicates that perceived risk is one of
the major issues in customers� minds while making electronic transactions especially in
banks. The main issue in this context is that one of the critical activities of e-service
quality, from the customers� perspectives, is the level of perceived risk when customers
make e-banking business. This level of perceived risk is related to the total quality of
e-banking services that has a strong effect on customers� satisfaction. In banking,
customers tend to perceive high level of risk due to the fact that there is a considerable
level of technological complexity, banking services are intangible and the transactions
are related to customers� �money� that is of great concern from their perspective.
Consequently, it can be hypothesised that: H4: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the perceived risk
element of customers� satisfaction.
With regard to customer satisfaction concerning responsiveness, e-service quality and
satisfaction previous research and theoretical ground indicate that one of the major
drivers of e-service quality initiatives and programs in banks is to provide convenience,
speed of service, save time and costs for customers. Therefore, high quality of e-banking
services requires creating high level of responsiveness which affects customers�
satisfaction and future purchase intentions. The essence of this argument is that
customers become involved in e-banking transactions since e-banking is convenient for
them and banks should have high level of responsiveness consistently and around the
clock; 24 hours a day, 7 days a week and 365 days a year. Having said that, theresponsiveness element of customers� satisfaction is a critical success factor for banks
to provide high quality of e-banking services. Consequently, it can be hypothesised that:
H5: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the responsiveness
element of customers� satisfaction.
With regard to customisation, it is argued that banks should customise their banking
services based on customers� needs and wants and consider any technological changes to
compete in today�s competitive business environment. Today�s banks need to pay great
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attention to the pace of unprecedented technological advancements, changing customers�
needs and unstable competitive positions in the marketplace in order to matchcompetitive forces in the marketplace and meet demanding customers� needs. Therefore,
banks need to examine the effect of their e-banking service quality on customers�
satisfaction concerning banks� customised services to reveal their ability in handling
customers� needs and requests and tackling competitive e-banking services. This is so
crucial to improve customers� satisfaction rate in relation to e-banking service quality
which has a major impact on the current customers� intentions to repeat interaction and
encourage potential customers to make electronic transactions in future, which is
fundamental for future banking business. This is to say that high quality of e-banking
services will have a positive impact on customers� satisfaction concerning customisation.
Consequently, it can be hypothesised that:
H6: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the customisationelement of customers� satisfaction.
Finally, banks recognise that one of the fundamentals of successful e-banking business in
the current competitive business environment is providing high quality of e-banking
services that leads to increasing efficiency and effectiveness. Hence, the extent of
customers� satisfaction concerning e-banking services is the cornerstone of improving the
quality of e-banking services and increasing customers� satisfaction, retention and
loyalty. Building on the e-service quality and satisfaction literature, it is argued that
there is crucial to examine the influence of e-service quality dimensions on customers�
satisfaction regarding the banking services delivered to customers. Consequently, it can
be hypothesised that:
H7: There is a relationship between e-service quality dimensions (website attributes,reliability, perceived risk, responsiveness and customisation) and the banking services
element of customers� satisfaction.
5 The research methodology
5.1 The research population and sample
The research population is all banks� customers who have either comprehensive banking
services transactions or some of them, not just obtaining information about the banking
services, over the banks� websites. According to the Association of Banks in Jordan
Website (2008), there are 23 banks operating in the Jordanian market. The researchers
made several attempts to obtain lists of customers who have e-transactions with the banks, but were unable to obtain them because of the banks privacy, topic sensitivity,
secrecy and competition reasons. Contacts were made with the banks indicated that they
have e-banking services transactions with their customers. The banks were officially
contacted to participate in the research survey through allowing the researchers to
administer the survey to their customers. The banks agreed to participate and administer
the survey, but were conservative to give the researchers access to their databases.
Consequently, the sampling process was done through using area sampling as a form of
the cluster sampling technique. We divided the population of the banks into geographical
areas as the following: Greater Amman Area, West Jordan, Northern Jordan and South of
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Jordan. Preliminary interviews with experts in the banks revealed that the majority of the
e-transactions are being carried out in the banks branches and e-branches in the Greater Amman Area. Greater Amman Area is representative of all other areas of Jordan since it
has diversity and people of Amman have come from all parts of the country. Using a
two-step area sampling approach, the research survey is carried out in Greater Amman
Area as a representative geographical area of the population of Jordan. Within Greater
Amman Area, random areas were selected from which the research sample was selected.
The process was managed by the banks with full coordination with the researchers. Table
1 shows the research population, sampling and response rate. From Table 1, the response
rate was 63.4%; 720 questionnaires were delivered to the banks� customers (through the
banks themselves) from which 457 questionnaires were returned and valid for the
analysis.
Table 1 Research population, sample, questionnaires and response rate
BanksQuestionnaires
sent Questionnaires
returned Non-returned questionnaires
Response rate(%)
Union Banks for Saving & Investment
20 12 8 60
Bank of Jordan 40 25 15 62.5
Jordan Kuwait Bank 60 47 13 67.5
Jordan Investment &Finance Bank
20 8 12 40
Arab Jordan Investment Bank 20 9 11 45
The Housing Bank for Trade & Finance
60 44 16 60
Jordan Islamic Bank for Finance & Investment
20 10 10 50
Jordan Commercial Bank 30 21 9 70
Jordan Ahli Bank 30 18 12 60
Capital Bank of Jordan 40 28 12 70
Arab Bank 80 64 16 80
Islamic International Arab Bank 30 12 18 40
Cairo Amman Bank 40 19 21 47.5
Arab Banking Corporation 20 11 9 55
Societe General Bank-Jordan 20 14 6 70
HSBC 30 23 7 76.6
Rafidain Bank 20 7 13 35Egyptian Arab Land-Bank 20 6 14 30
Bank Audi SAL 20 12 8 60
National Bank of Kuwait 20 11 9 55
Standard Chartered 40 32 8 80
Citibank 20 13 7 65
Bloom Bank 20 11 9 55
Total 720 457 263 63.4
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5.2 Data collection methods
The primary data was collected through a questionnaire which was specifically
developed for the purpose of this research. The questionnaire was highly structured in
which questions were fixed-response alternative questions that required the respondents
to select from specific responses. Five-point Likert scale was used (Aaker et al., 2001;
Churchill, 2001). The type of research is a cross-sectional design in which the collection
of data from the banks� customers was carried out only once.
5.3 The research variables operational definition
In order to develop an operational definition for each variable included in the research
model, five-point Likert scale was used (runs from �Strongly Agree� given the score of
�5� to �Strongly Disagree� given the score of �1�). The dimensions of e-service quality
were determined based on previous empirical work that provided strong grounds for not
inventing new ones. The operational definition of e-service quality dimensions was
developed based on previous conceptual and empirical studies that were carried out on
the research topic (e.g. Dillon and Reif, 2004; Parasuraman et al., 2005; Bauer et al.,
2006; Huei-Chen, 2007). Five dimensions of e-service quality were identified from the
literature as independent variables. The same procedure was followed to operationalise
the customer satisfaction variable as a dependent variable. Five-point Likert scale was
used (runs from �Very Satisfied� given the score of �5� to �Very Dissatisfied� given the
score of �1�). Several e-customer satisfaction studies were consulted to operationalise this
construct (e.g. Chea and Luo, 2006; Ha, 2006; Zhang et al., 2006).
5.4 Developing and administering the questionnaire
The questionnaire was developed based on guidelines provided by marketing researchers
(e.g. Hair et al., 1998) and based on previous empirical research in the field of e-service
quality. The design of the questionnaire was tested based on the pilot study work of a
judgmental sample of the banks� customers, which was not included in the final analysis.
In addition, managers in the banks examined the questionnaire as well as consulting
academics in Jordanian universities to examine the relevancy of the questionnaire to the
study objectives. The research questionnaire is attached in Appendix A. Soft and hard
copies of the questionnaires were personally delivered to the banks and the research
objectives were explained to each one (Sekaran, 2003; Malhotra, 2004). The primary data
collection process lasted around four-month period from January to April 2008.
5.5 Statistical methods
The data analysis strategy has used a set of appropriate statistical techniques and methods
that are able to achieve our study objectives. The unit of analysis in our study is �the bank
customer� who made e-transactions with the bank/s to obtain different types of banking
services over the bank website. In order to prepare our data for appropriate analysis, strict
data cleaning and preparation procedures were followed (Hair et al., 1998). The statistical
methods used to analyse the data and to test the hypotheses are all parametric tests, for
example multiple regression analysis.
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6 Validity and reliability
6.1 Validity
The validity of the instrument and scales were assessed by face validity and content
validity. Face validity � the research instrument was presented to a number of academics
in the marketing and e-marketing field as well as experts in the banks in Jordan. They
were asked about the appropriateness and ability of the instrument and scales to achieve
the research objectives. They were asked about the instrument design, layout and
contents and ability to understand its questions. After receiving feedback, miner
refinements were carried out on the questionnaire, then it was ready for the empirical
work; providing evidence of face validity. Content validity � according to Churchill
(2001), content validity is examined through the procedures used to develop the research
instrument. The procedures used by the researchers to develop the research instrument
are: first, reviewing most relevant previous empirical and theoretical literatures in the
field of e-service quality upon which the operational definition for each variable was
generated; second, conducting the pilot study work before starting the major fieldwork to
test the instrument and third, at the beginning of each section in the study instrument,
complete instructions were given to the banks� customers related to how to complete the
questionnaire.
6.2 Reliability
The reliability of the research instrument was assessed by examining the Cronbach�s
alpha coefficient (Sekaran, 2003). The values of Cronbach�s alpha range from 0 to 1.
Table 2 shows the reliability coefficients for all the research variables. Table 2 shows that
the reliability coefficients of all the research variables were above the cut off point, 60%,of alpha used in this research. The reliability coefficients for the all variables ranged from
0.634 to 0.787. Consequently, the research instrument and variables are of reasonable
reliability and have internal reliability coefficient.
Table 2 Reliability coefficients for the research variables � Cronbach�s alpha
E-service quality variables Number of items Reliability coefficients
Website attributes 6 0.634
Reliability 7 0.775
Perceived risk 4 0.787
Responsiveness 5 0.660
Customisation 6 0.665Overall e-service quality 28 0.885
Customer satisfaction 6 0.788
7 Examining the regression assumptions
In order to use parametric statistical tests such as multiple regression, there
are assumptions that should be met to perform such robust tests. The assumptions
of using multiple regression analysis are carefully examined according to statistical
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methodologies which are recommended by well-known researchers (e.g. Hair
et al., 1998). Those researchers argue that the analysis of residuals provides the bestinformation about regression models� errors which are used to examine the regression
analysis assumptions. The assumptions are as follows: (1) the normal distribution
assumption � this assumption was examined by using a statistical test for the standardised
residuals to reveal if they are significantly deviated from the normal distribution. The
test of Shapiro-Wilk is used to test the normal distribution of standardised residuals.
The test results, which are shown at the regression analysis tables, indicated that the
standardised errors are normally distributed; the P values are all larger than 0.05, which
provide evidence that the errors are not significantly deviated from normality. (2) The
multicollinearity assumption � this assumption is tested through Variance Inflation
Factor (VIF) and tolerance throughout all the regression models in the research. VIF
measures how much the variance of regression coefficients are independent measures.
If the VIF is more than 5 and the tolerance is less than 0.20 in a regression model, thisindicates a problem of multicollinearity (Hair et al., 1998). All the VIF and tolerance in
the regression models were calculated and indicated that the multicollinearity is not of a
great concern in this research. This is evidenced when the VIF values are ranged between
1.421 and 2.159 and the tolerance values are ranged between 0.463 and 0.704 (see the
multiple regression analysis results in the tables). (3) The independent errors assumption
� this assumption is tested by Durbin-Watson statistic. If the value of the test is ranged
between 1 and 3, then assumption is met. If the value of the test is close to 2, which is the
best, this assumption is strongly met. If the value of the test is less than 1 or more than 3,
this assumption is not met and the errors are not independent. This test is run in all the
regression models in the research that indicated that this assumption is met providing
evidence that the errors are independent (see the regression analyses tables).
8 Analysis and findings
To test the research model and hypotheses, several multiple regression analyses models
were run to examine the effect of independent variables on dependent variables.
H1: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the overall customers�
satisfaction.
Table 3 shows results of the multiple regression analysis of the independent variables on
the overall customer satisfaction, as a dependent variable. The multiple regression model,
R square is 0.544, is significant at 0.000. The regression findings indicate that there is a
significant and positive relationship between all the independent variables and the overallcustomers� satisfaction. Consequently, the overall findings and results provide support
for accepting H1. Table 3 shows that 54.4% of the variation in the overall customer
satisfaction is explained by the independent variables. The findings indicate that
responsiveness (beta is 0.341, significant at 0.000), customisation (beta is 0.235,
significant at 0.003) and website attributes (beta is 0.197, significant at 0.006) are the
strongest predictors of variations in the overall customer satisfaction, respectively.
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Table 3 Multiple regression analysis-dependent variable is overall customer satisfaction
Analysis of variance
Multiple R R square Adjusted R
square Shapiro-Wilk Durbin-Watson F Value Sig. F H1 result
0.737 0.544 0.526 0.095 1.66 31.436 0.0000 Accepted
Independent variables in the multiple regression equation
Standardised coefficients Collinearity statisticsIndependent variables
Beta T value Sig. T Tolerance VIF
Website attributes 0.197 2.815 0.006 0.704 1.421
Reliability 0.011 0.131 0.896 0.463 2.159
Perceived risk 0.206 2.449 0.016 0.490 2.041
Responsiveness 0.341 4.797 0.000 0.683 1.464Customisation 0.235 3.047 0.003 0.584 1.713
H2: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the website attributes
and design element of customers� satisfaction.
Table 4 shows results of the multiple regression analysis of the independent variables
on the website design and attributes element of customer satisfaction, as a dependent
variable. The multiple regression model, R square is 0.204, is significant at 0.000. The
regression findings indicate that there is a significant and positive relationship between
all the independent variables and the website design and attributes element of customers�
satisfaction. Consequently, the overall findings and results provide support for accepting
H2. Table 4 shows that 20.4% of the variation in the customer satisfaction related to thewebsite design and attributes is explained by the independent variables. The findings
indicate that responsiveness (beta is 0.298, significant at 0.002) and customisation
(beta is 0.253, significant at 0.014) are the strongest predictors of variations in the
website design and attributes element of customer satisfaction, respectively.
Table 4 Multiple regression analysis-dependent variable is satisfaction relatedto website design
Analysis of variance
Multiple R R square Adjusted R
square Shapiro-Wilk Durbin-Watson F Value Sig. F H2 result
0.451 0.204 0.173 0.084 1.85 6.750 0.0000 Accepted
Independent variables in the multiple regression equationStandardised coefficients Collinearity statisticsIndependent variables
Beta T value Sig. T Tolerance VIF
Website attributes 0.103 1.116 0.267 0.704 1.421
Reliability 0.130 1.136 0.258 0.463 2.159
Perceived risk 0.035 0.314 0.754 0.490 2.041
Responsiveness 0.298 3.167 0.002 0.683 1.464
Customisation 0.253 2.492 0.014 0.584 1.713
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H3: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the reliability element of customers� satisfaction.
Table 5 shows results of the multiple regression analysis of the independent variables on
the reliability element of customer satisfaction, as a dependent variable. The multiple
regression model, R square is 0.217, is significant at 0.000. The regression findings
indicate that there is a significant and positive relationship between all the independent
variables and the reliability element of customers� satisfaction. Consequently, the overall
findings and results provide support for accepting H3. Table 5 shows that 21.7% of the
variation in the customer satisfaction related to reliability is explained by the independent
variables. The findings indicate that the website attributes and design (beta is 0.370,
significant at 0.000) and responsiveness (beta is 0.260, significant at 0.006) are the
strongest predictors of variations in the reliability element of customer satisfaction,
respectively.
Table 5 Multiple regression analysis-dependent variable is satisfaction related to reliability
Analysis of variance
Multiple R R square Adjusted R
square Shapiro-Wilk Durbin-Watson F value Sig. F H3 result
0.466 0.217 0.188 0.086 2.07 7.336 0.0000 Accepted
Independent variables in the multiple regression equation
Standardised coefficients Collinearity statisticsIndependent variables
Beta T value Sig. T Tolerance VIF
Website attributes 0.370 4.035 0.000 0.704 1.421
Reliability 0.020 0.175 0.862 0.463 2.159
Perceived risk 0.080 0.730 0.467 0.490 2.041
Responsiveness 0.260 2.792 0.006 0.683 1.464
Customisation 0.044 0.433 0.666 0.584 1.713
H4: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the perceived risk
element of customers� satisfaction.
Table 6 shows results of the multiple regression analysis of the independent variables on
the perceived risk element of customer satisfaction, as a dependent variable. The multiple
regression model, R square is 0.366, is significant at 0.000. The regression findings
indicate that there is a significant and positive relationship between all the independent
variables and the perceived risk element of customer satisfaction. Consequently, the
overall findings and results provide support for accepting H4. Table 6 shows that 36.6%
of the variation in the perceived risk of customer satisfaction is explained by the
independent variables. The findings indicate that the responsiveness (beta is 0.400,
significant at 0.000) and website attributes and design (beta is 0.262, significant at 0.002)
are the strongest predictors of variations in the perceived risk element of customer
satisfaction, respectively.
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Table 6 Multiple regression analysis-dependent variable is satisfaction related
to perceived risk
Analysis of variance
Multiple R R square Adjusted R
square Shapiro-Wilk Durbin-Watson F value Sig. F H4 result
0.605 0.366 0.342 0.098 2.27 15.217 0.0000 Accepted
Independent variables in the multiple regression equation
Standardised coefficients Collinearity statisticsIndependent variables
Beta T value Sig. T Tolerance VIF
Website attributes 0.262 3.165 0.002 0.704 1.421
Reliability 0.041 0.407 0.685 0.463 2.159
Perceived risk 0.067 0.675 0.501 0.490 2.041
Responsiveness 0.400 4.767 0.000 0.683 1.464
Customisation 0.120 1.325 0.188 0.584 1.713
H5: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the responsiveness
element of customers� satisfaction.
Table 7 shows results of the multiple regression analysis of the independent variables
on the responsiveness element of customer satisfaction, as a dependent variable. The
multiple regression model, R square is 0.352, is significant at 0.000. The regression
findings indicate that there is a significant and positive relationship between all
the independent variables and the responsiveness element of customer satisfaction.
Consequently, the overall findings and results provide support for accepting H5. Table 7shows that 35.2% of the variation in the responsiveness element of customer satisfaction
is explained by the independent variables. The findings indicate that the responsiveness
(beta is 0.370, significant at 0.000) and perceived risk (beta is 0.297, significant at 0.004)
are the strongest predictors of variations in the responsiveness element of customer
satisfaction, respectively.
Table 7 Multiple regression analysis-dependent variable is satisfaction relatedto responsiveness
Analysis of variance
Multiple R R square Adjusted R
square Shapiro-Wilk Durbin-Watson F value Sig. F H5 result
0.594 0.352 0.328 0.110 2.17 14.365 0.0000 Accepted
Independent variables in the multiple regression equation
Standardised coefficients Collinearity statisticsIndependent variables
Beta T value Sig. T Tolerance VIF
Website attributes 0.035 0.414 0.680 0.704 1.421
Reliability 0.115 1.121 0.264 0.463 2.159
Perceived risk 0.297 2.966 0.004 0.490 2.041
Responsiveness 0.370 4.368 0.000 0.683 1.464
Customisation 0.126 1.378 0.171 0.584 1.713
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H6: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the customisationelement of customers� satisfaction.
Table 8 shows results of the multiple regression analysis of the independent variables on
the customisation element of customer satisfaction, as a dependent variable. The multiple
regression model, R square is 0.423, is significant at 0.000. The regression findings
indicate that there is a significant and positive relationship between all the independent
variables and the customisation element of customer satisfaction. Consequently, the
overall findings and results provide support for accepting H6. Table 8 shows that 42.3%
of the variation in the customisation element of customer satisfaction is explained by the
independent variables. The findings indicate that the responsiveness (beta is 0.251,
significant at 0.002), the websites attributes and design (beta is 0.204, significant at
0.011) and customisation (beta is 0.198, significant at 0.024) are the strongest predictors
of variations in the customisation element of customer satisfaction, respectively.
Table 8 Multiple regression analysis-dependent variable is satisfaction relatedto customisation
Analysis of variance
Multiple R R Square Adjusted R
square Shapiro-Wilk Durbin-Watson F value Sig. F H6 result
0.651 0.423 0.401 0.067 2.17 19.376 0.0000 Accepted
Independent variables in the multiple regression equation
Standardised Coefficients Collinearity statisticsIndependent variables
Beta T value Sig. T Tolerance VIF
Website attributes 0.204 2.590 0.011 0.704 1.421Reliability 0.084 0.865 0.388 0.463 2.159
Perceived risk 0.129 1.365 0.175 0.490 2.041
Responsiveness 0.251 3.144 0.002 0.683 1.464
Customisation 0.198 2.286 0.024 0.584 1.713
H7: There is a relationship between e-service quality dimensions (website attributes,
reliability, perceived risk, responsiveness and customisation) and the banking services
element of customers� satisfaction.
Table 9 shows results of the multiple regression analysis of the independent variables on
the e-banking services element of customer satisfaction, as a dependent variable. The
multiple regression model, R square is 0.363, is significant at 0.000. The regression
findings indicate that there is a significant and positive relationship between all theindependent variables and the e-banking services element of customer satisfaction.
Consequently, the overall findings and results provide support for accepting H7. Table 9
shows that 36.3% of the variation in the e-banking services element of customer
satisfaction is explained by the independent variables. The findings indicate that the
perceived risk (beta is 0.465, significant at 0.000) and customisation (beta is 0.251,
significant at 0.006) are the strongest predictors of variations in the e-banking services
element of customer satisfaction, respectively.
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Table 9 Multiple regression analysis-dependent variable is satisfaction related
to e-bank services
Analysis of variance
Multiple R R square Adjusted R
square Shapiro-Wilk Durbin-Watson F value Sig. F H7 result
0.603 0.363 0.339 0.059 1.71 15.048 0.0000 Accepted
Independent variables in the multiple regression equation
Standardised coefficients Collinearity statisticsIndependent variables
Beta T value Sig. T Tolerance VIF
Website attributes 0.080 0.972 0.333 0.704 1.421
Reliability 0.040 0.388 0.699 0.463 2.159
Perceived risk 0.465 4.691 0.000 0.490 2.041
Responsiveness 0.055 0.649 0.518 0.683 1.464
Customisation 0.251 2.765 0.006 0.584 1.713
9 Results discussion
The multiple regression analyses findings indicate that there is a positive and significant
relationship between the e-service quality dimensions (website attributes, reliability,
perceived risk, responsiveness and customisation) and the overall customer satisfaction
and its individual elements. All the research hypotheses H1�H7 were accepted providing
evidence of this positive relationship. The empirical findings indicate that the e-service
quality dimensions have an important role to play on the banks customers� satisfactionwhile making e-transactions to obtain banking services. The findings provide support for
the e-service quality literature review that advocates that a well-designed, reliable,
secure, highly responsive and customised bank website would be able to provide high
quality of banking services that have a positive effect on the overall customers�
satisfaction and its individual elements. The multiple regression analyses findings
indicate that, based on beta values and significance, responsiveness is the most influential
dimension (predictor) of the e-service quality dimensions on the overall customers�
satisfaction and its elements individually. The e-service quality literature, and our
research, advocated that the more responsive a bank in dealing with all the e-transactions,
the higher customers� satisfaction would be perceived. Consequently, responsiveness is
one of the crucial dimensions of e-service quality that have a significant impact
on customers� satisfaction. However, to create a highly responsive bank for the
e-transactions, a bank should design a customer-oriented website, has accessible and
responsive employees, skilful and well-experienced staff in the e-transactions, and
respond to all customers� requirements and complaints quickly and professionally.
Based on beta values and significance, the second strongest variable of the e-service
quality variables that has contributed to the overall customers� satisfaction and its
elements individually is the bank website attributes and design. This finding provides a
strong support to the service quality literature review that advocated that a well-designed
website would have a positive effect on customers� satisfaction. A bank website should
be easy to handle and view, easy to make all the necessary electronic contacts, attractive,
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well-coloured in a professional manner and should convey a bank�s image. This requires
a very important issue that the banks management should realise that a bank�s website isthe silent communicator with customers and a permanent marketing tool that affects
customers� attitudes and then satisfaction. Consequently, a well-designed bank website
equipped with the greatest marketing sense and customer orientation would have a
crucial effect on customers� satisfaction. Also, based on beta values and significance,
the third strongest variable of the e-service quality variables that has contributed to
the overall customers� satisfaction and its elements individually is customisation. This
finding provides a strong support for the e-service quality literature review that advocates
that a well-customised bank website has a positive effect on customers� satisfaction.
Customisation enables customers to fine-tune their e-transactions based on needs and
wants to achieve the required level of satisfaction. Consequently, the banks should
pay high attention to technological infrastructure and update it periodically to suite
customers� needs and different market segments. Furthermore, special requests and needsshould be available on a bank website to satisfy customers and make them loyal;
otherwise they may switch to other competitors. However, website customisation does
not happen unless a bank take customers needs and wants into consideration. In other
words, the most important element of a bank website customisation process is customers�
inputs through understanding their needs, wants, suggestions and feedback to make
continuous improvement.
The findings, based on beta values and significance, indicate that reliability and
perceived risk did not have a significant impact on the overall customers� satisfaction
nor its elements individually, but the findings indicate that their effect is still positive.
To some extent, these results did not provide strong support for the e-service quality
literature that advocated their role on customers� satisfaction. A possible interpretation
for these results is that customers view all the e-service quality dimensions as important
drivers of their satisfaction, but when it comes to the most important elements of e-service quality dimensions on their satisfaction it seems that the responsiveness,
website design and customisation exert the strongest effect on customers� satisfaction.
Finally, an important finding to report here is that there is a positive and significant
relationship between the e-service quality dimensions and customers� satisfaction
concerning the e-banking services transactions. Based on beta values and significance,
the perceived risk (website security) is the most influential predictor of e-service quality
dimensions on customers� satisfaction related to e-banking services. This provides a
strong support for the e-service quality literature that advocated that the perceived risk,
security and privacy of transactions on the website have a positive effect on customer
satisfaction. It should be noted here that the perceived quality had a positive but not
significant effect on the other elements of customers� satisfaction. Meanwhile, the
perceived risk is the strongest predictor on customers� satisfaction regarding e-bankingservices. A possible interpretation for this result is that customers view the perceived
risk and website security as essential elements to make successful e-transactions over
a bank website alongside the other dimensions of e-service quality that affect customers�
satisfaction, for example responsiveness and customisation.
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10 Conclusions
E-service quality has become an important research area of the e-marketing field and as
one of the recent research areas emerged as an outcome of the information technology
advancement. Several authors of marketing and e-service quality have argued and found
that it has a positive and significant effect on customers� satisfaction in different business
sectors. The main objective of this research was to investigate the relationship between
the e-service quality dimensions (website design and attributes, reliability, perceived
risk, responsiveness and customisation) and the overall customers� satisfaction and its
individual elements in the banks of Jordan. Another objective was to identify the
strongest predictors of the e-service quality dimensions on customers� satisfaction.
Based on the research objectives, model, statistical analyses and findings, a number of
conclusions can be outlined. First, e-service quality is one of the strategic aspects of any
bank�s e-business since it has a positive and significant on the overall customers�satisfaction and its elements individually. Banks management should recognise the
technical and marketing elements of the e-service quality dimensions that have a crucial
effect on customers� satisfaction. Second, e-service quality dimensions (website design
and attributes, reliability, perceived risk, responsiveness and customisation) have a
positive and significant effect on the banks overall customers� satisfaction and individual
elements of customers� satisfaction. Third, there is a positive and significant relationship
between e-service quality dimensions and the banks customers� satisfaction elements
individually that are as follows: a bank website attributes and design, reliability,
perceived risk and security, responsiveness, customisation and e-banking services.
Fourth, the strongest predictors, based on beta values, of e-service quality dimensions
on the overall banks customers� satisfaction and its elements individually are
responsiveness, website design and attributes, and customisation, respectively. Fifth, the
strongest predictors, based on beta values, of e-service quality dimensions on the banks
customers� satisfaction concerning e-banking services are perceived risk and security,
and customisation, respectively. Sixth, the banks need to recognise that successful
e-transactions over their websites require soft and hard skills that should be able to
satisfy customers and make them loyal. Information technology skills and expertise are
so important to make successful e-transactions, but they should be combined with
marketing and managerial skills and expertise that are of value from the customers�
viewpoint. This is to say that, even the website is well-designed, secure and reliable, if
the bank staff are not responsive and the customers cannot customise the banking
services over the website based on their needs and want, they will not be able to make
successful e-transactions and of high quality. Seventh, the banks� customers are willing
to make banking business over their websites, but the banks should encourage them
through providing high quality of e-banking services. When the customers find secure,easy to handle, responsive, reliable and customised website, they are willing to do
banking business over the website since it provides them values and benefits,
convenience, save time, cost and efforts.
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11 Recommendations
Based on the empirical findings of our research, we recommend the followings:
1 The banks in Jordan have to place higher emphasis on the dimensions of e-banking
services that require soft and hard skills and capabilities. Providing high quality of
banking services requires high quality of website design and attributes, reliability,
low perceived risk and high security, high responsiveness and customisation.
2 The banks in Jordan need to recognise that successful and high quality of e-banking
transactions require strong sense of marketing orientation and the customer should
be at the heart of every activity over the website.
3 The banks in Jordan should pay high attention to responsiveness as the major driver
of customers� satisfaction in the banking business. To create a highly responsive
bank for the e-transactions, a bank should design a customer-oriented website, hasaccessible and responsive employees, skilful and well-experienced staff in the
e-transactions, and respond to all customers� requirements and complaints quickly
and professionally.
4 The banks in Jordan need to pay attention to the website design and attributes and
customise them based on a thorough understanding of customers needs and wants to
make them satisfied related to their e-transactions.
5 The banks in Jordan should emphasis on having highly secure websites that
will enable the customer to make highly secure transactions over the website. The
rationale behind this recommendation is that the perceived risk (website security)
is the most influential predictor of e-service quality dimensions on customers�
satisfaction concerning e-banking services.
6 The banks in Jordan should understand the e-customers� satisfaction on two levels,
namely the overall customers� satisfaction and the customers� satisfaction elements
individually. The essence of this recommendation is that the banks� customers may
be satisfied about e-banking services transactions in general but may not be satisfied
about specific elements of the transaction, for example responsiveness. The best
approach is to breakdown the e-customer satisfaction into specific elements (as the
authors did in this study) that would enable the bank to understand the level of
satisfaction or dissatisfaction in order to enhance high levels of satisfaction and
improve low levels of satisfaction.
7 The banks in Jordan need to recognise that the e-service quality dimensions
and achieving high levels of e-customers� satisfaction requires a skilful blend of
marketing, managerial, information technology, customer service and technical
competencies, skills, and experience to achieve a bank long-term aspirations.
12 Contribution
This research is thought to have contributed to the e-service quality literature in
three aspects. First, from an academic standpoint, this research has fulfilled some gaps
that emerged from e-service quality literature that needed more empirical research
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especially in developing countries business environments, for example Jordan. Second,
from an empirical standpoint, this research is the first empirical study that investigatedthe relationship between e-service quality dimensions and overall customers� satisfaction
and its elements individually in banks of Jordan. Third, from an applied/professional
standpoint, this research has offered banks� managements in Jordan, for the first time,
strategic insights and implications regarding the e-service quality practices, dimensions
and overall customers� satisfaction and its elements individually. Consequently, banks
of Jordan have significant insights on e-service quality and satisfaction which can
be utilised as major inputs that banks� managements should carefully examine while
developing and implementing e-service quality strategies for banking services.
13 Limitations and future research
Although this research has achieved its objectives, limitations and future research are
outlined. The generalisability of the research results are limited to the banks of Jordan
and cannot be generalised to other business sectors inside and outside Jordan. However,
previous research focused on carrying out studies on the e-service quality area in single
or homogenous business sectors/characteristics in order to reach to accurate results and
findings. Future research can replicate the study�s model on other business sectors or
conduct comparative studies among them to reveal the e-service quality dimensions
and their effect on customers� satisfaction. Another limitation is that the study�s
model included only five dimensions of e-service quality and their effect on customer
satisfaction. A good area of research in the future is to find out if there are more
dimensions of e-service quality that affect customers� satisfaction. Furthermore, future
research efforts can examine the relationship between e-service quality dimensions and
banks performance (and/or organisations� performance in other business sectors) frommanagers� perspectives as well as examining their effect on customer loyalty and
retention from customers� perspectives. Future research efforts can also examine if the
relationship between the e-service quality dimensions and customers� satisfaction is
indirect. In other words, are there any moderating or mediating variables that may affect
this relationship and why?
Acknowledgements
The authors gratefully acknowledge the salutary effects on the paper of the comments
of two anonymous reviewers. Addressing these comments has improved the article.
The authors would also like to thank the IJSEM editor.
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Appendix A: The research questionnaire
The independent variables
E-service quality dimensions and statements
The website attributes
1 It is easy to deal with the bank�s e-services
2 The bank�s website design is easy to link and interact
3 The bank�s website pages have adequate and suitable colors
4 The bank�s website pages have clear fonts
5 The bank�s electronic services develop your computer skills
6 The bank�s website contains un-clear technical phrases
Reliability
7 I trust the e-banking services presented on the bank�s website
8 The bank is highly credible in delivering e-banking services as promised
9 The bank�s e-services allow banking transactions around the clock 10 The bank delivers the desired e-banking service to customers
11 The bank�s e-services accuracy enhances my confidence in its services
12 There are multiple errors on the bank�s website during e-service delivery
13 The bank information on the website are updated continuously
Perceived risk
14 The bank uses advanced technology in developing e-banking services
15 The bank�s e-services are highly secure
16 The bank protects its clients� personal information
17 The bank charges low credit cards commissions when making money transactions
Responsiveness
18 The bank�s e-service transactions are not legally protected
19 The website responds quickly to clients requirements
20 The website offers the availability of an online customer services representativeto respond to customer enquiries
21 The website customer service representatives are skilful and well-experienced
22 There are ATM machines in all the Bank�s branches
Customisation
23 There are ATM machines in all the Bank�s branches
24 The credit cards are issued within 24 hours of filling the application form
25 The e-banking services are customised according to clients requirements
26 The bank�s e-services are changed according to changes in clients needs and wants
27 The bank�s e-services are changed according to changes in technology
28 The bank�s website offers special treatment for highly loyal clients
The dependent variable
Customer satisfaction1 Overall, the extent which you are satisfied with the e-banking transactions
2 The extent which you are satisfied with the website characteristics related to design and easeof use
3 The extent which you are satisfied with the bank�s e-service related to reliability and confidence
4 The extent which you are satisfied with the bank�s e-service related to securityduring transactions
5 The extent which you are satisfied with the bank�s e-service related to speed and responsiveness
6 The extent which you are satisfied with the bank�s e-service is positively correlatedwith the information related to e-banking services