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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


*Corresponding author

Bushra K. Mahadin

Faculty of Banking and Financial Sciences

The Arab Academy for Banking and Financial Sciences,Amman, Jordan


Abdullah Q. Bataineh

Faculty of Administrative Studies,

Amman Arab University for Graduate Studies,

Amman, Jordan


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.



M.T. Nuseir et al.

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



An empirical investigation of customers� perspectives

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?



M.T. Nuseir et al.

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




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



M.T. Nuseir et al.

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




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.



M.T. Nuseir et al.

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).




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



M.T. Nuseir et al.

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.




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�



M.T. Nuseir et al.

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:


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:


reliability, perceived risk, responsiveness and customisation) and the responsiveness


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




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:


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


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



M.T. Nuseir et al.

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




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.



M.T. Nuseir et al.

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




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.


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.



M.T. Nuseir et al.

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


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



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



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





reliability, perceived risk, responsiveness and customisation) and the reliability element of customers� satisfaction.


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



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





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


reliability, perceived risk, responsiveness and customisation) and the perceived risk



the perceived risk element of customer satisfaction, as a dependent variable. The multiple



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.



M.T. Nuseir et al.

Table 6 Multiple regression analysis-dependent variable is satisfaction related

to perceived risk




0.605 0.366 0.342 0.098 2.27 15.217 0.0000 Accepted





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


reliability, perceived risk, responsiveness and customisation) and the responsiveness


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




0.594 0.352 0.328 0.110 2.17 14.365 0.0000 Accepted





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





reliability, perceived risk, responsiveness and customisation) and the customisationelement of customers� satisfaction.


the customisation element of customer satisfaction, as a dependent variable. The multiple



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


Multiple R R Square Adjusted R


0.651 0.423 0.401 0.067 2.17 19.376 0.0000 Accepted


Standardised Coefficients Collinearity statisticsIndependent variables


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


reliability, perceived risk, responsiveness and customisation) and the banking services



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.



M.T. Nuseir et al.

Table 9 Multiple regression analysis-dependent variable is satisfaction related

to e-bank services




0.603 0.363 0.339 0.059 1.71 15.048 0.0000 Accepted





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,




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.



M.T. Nuseir et al.

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.




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



M.T. Nuseir et al.

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

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