Customer Satisfaction with Internet Bank

Customer Satisfaction
with Internet Banking
in Brunei Darussalam:
Evaluating the Role of Demographic Factors

Afzaal H. Seyal
Institute of Technology Brunei

Md. Mahbubur Rahim
Monash University, Australia
ABSTRACT

The pioneering study highlights the online banking customers’ satisfaction and investigates
the demographic factors that are significant predictors in assessing online banking customers’
satisfaction in Brunei Darussalam. The study uses a survey approach methodology of four
hundred customers of the four major banks in Brunei Darussalam. Data from the individual customers confirms that 31% of them are using Internet banking and 46% of the
respondents are satisfied with Internet banking. Factors such as income level, Internet
experience, age and educational level are significant determinants of overall satisfaction
with online banking. However, gender has no impact in determining the overall satisfaction. The model tested with hierarchical regression analysis has a good fit with 66% of
variance being explained by all the independent variables towards the customers’ satisfaction. Based upon the results some recommendations were made.
Keywords: online banking, e-customer satisfaction, Brunei Darussalam

@ 2011 e-Service Journal. All rights reserved. No copies of this work may be distributed
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INTRODUCTION

Internet banking refers to the practice of conducting financial transactions by customers
over the Internet through a bank’s website (Shao, 2007). One key characteristic of internet
banking is that customers are not required to use any proprietary software installed in their
computers for accessing banking services. Internet banking is gaining growing popularity
particularly among retail customers due to: a) its 24/7 availability and low transaction
costs (Talmor, 1995), and b) its ability to serve as a convenient alternative channel (Leonard, 2002). In short, internet banking is not constrained by time and place (Hiltunen et
al., 2002). As a result, this form of banking has attracted considerable adoption by the retail banking customers. For instance, an estimated one million internet banking users are
reported in South Africa (Goldstuck, 2004). In the South Asian region evidence suggests
its growing adoption. In Malaysia, Dahlan et al. (2002) found Internet banking a new experience for Malaysian banking customers. In Hong Kong, Chan and Lu (2004) reported
that basic transactions and securities trading are the most popular types of operations that

Hong Kong customers carry out in Internet banking. The uptake of internet banking is
also growing in Australia where some sources indicate the existence of millions of users
(Sathye, 1999). In Thailand, Koedrabruen and Raviwongse (2002) found that in more
than half of their sample, Internet users are very interested in using Internet banking facilities for fund transfers, payments for goods purchased and to pay utility bills and also found
that there was potential growth for retail Internet banking. In Singapore, Tan and Teo
(2000) reported that Internet banking was started in 1998 and since then there has been
tremendous growth of Internet service users and the services offered by the local banks.
Recognizing the growing popularity of internet banking, a large number of studies
have looked at how various factors influence customers’ adoption decisions. We however
argue that, given the evidence of increased adoption of internet banking, it is now appropriate to move beyond adoption factors. Our argument is consistent with the views expressed by Shao (2007), who in a meta-analysis of literature on internet banking, identified
the dominance of factor-based research and called for further research to examine postadoption issues associated with internet banking. We thus urge that greater attention be
paid to understand customer satisfaction with internet banking among adopters. This is
because internet banking has created highly competitive market conditions for bank providers (Beckett et al., 2000) and the changed market conditions demand that banks better
understand how best they should use internet banking to support the changing needs of
their customers and to retain retail adopters. In fact, Mattila (2001) concedes customer
satisfaction to be a key to the success of internet banking. In addition, several e-business
researchers Buys and Brown (2004), Linsdgaard and Dudek (2003) and Lawis, (2002)
strongly suggest for the analysis of user satisfaction to attract and increase the number of
online customers.

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We further conjecture that satisfaction with internet banking is likely to be influenced by the demographic profile of customers. Our assertion is rooted in the findings of
the contemporary e-business and IT literature which suggest that end-users’ satisfaction
with internet-enabled IT systems (such as various forms of B2C and B2E applications) is
affected by demographic factors. Our belief is also consistent with the views of the diffusion of innovation (DOI) researchers (e.g. Rogers, 1985) who suggest that demographic
variables often affect the uptake of new innovations. It is thus important to evaluate the
influence of demographic factors in relation to internet banking in order to find out how
various constructs that comprise customer satisfaction are affected by those factors. We
believe that the intention of customers (who are initial adopters) to continue to use internet banking could be seriously affected when internet banking fails to satisfy their changing requirements. According to David (2007), culture is known to have an impact on
customers’ behavior and satisfaction. As a result, it is essential to determine the current
level of customer satisfaction with internet banking and address how various demographic factors affect customer satisfaction.
In the light of the above discussion, it seems particularly true within the context of
Brunei Darussalam, a small sultanate located in South East Asia, where major banks
have introduced internet banking operations in recent years and that no empirical studies have ever been undertaken in Brunei to assess any aspects of internet banking usage or
satisfaction from the customers’ perspective. The technology adoption in Brunei Darussalam reflects a distinctive pattern compared to the other Asia-Pacific economies and

more commonly embedded within its own culture. Although the study does not include
cultural dimension of Hofstede’s typology, however, we can borrow the notion to
strengthen our point to explore Bruneian IT adoption. According to Hofstede, (2001)
societies such as Brunei has medium to high power distance index (PDI) and uncertainty
avoidance index (UAI) which creates an environment that are highly rule-oriented with
laws in order to reduce the amount of uncertainty. In these societies, role of demographics have a vital affect on the technology acceptance (Cardon & Marshall, 2008). This
was also noticed among several other Brunei-based studies among students to study software piracy (Rahim et al., 1999), students’ attitudes (Seyal et al. 2002) and Internet
usage (Seyal & Rahman, 2003) that demographical variables remained significant.
Therefore, the aims of the research reported in this paper are: a) to determine the
current level of customer satisfaction with internet banking operations offered by major
banks operating in Brunei Darussalam, b) to identify those demographic factors that can
explain variations in the customer satisfaction with internet banking, and c) to pinpoint
those constructs of customer satisfaction which are significantly affected by customer
demographic factors. By addressing these research questions, we hope to contribute in
building a cumulative body of knowledge on the success of internet banking. From a
practitioner’s viewpoint, an improved understanding of customer satisfaction with
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Table 1: Summary of the existing literature on internet banking

internet banking will help the bank management to identify the areas of improvement in
their future internet banking offerings.
The paper is organized as follow: after the introduction, a brief but critical analysis
of the relevant literature on internet banking is presented. We then briefly describe the
measuring of customer satisfaction with internet banking and provide an overview of the
economy, infrastructure and internet banking in Brunei Darussalam. Next, we describe
our research approach. We then present and discuss the research findings. Finally, we
conclude with recommendations for practitioners and researchers alike.
LITERATURE ANALYSIS

The literature on internet banking is steadily growing and a content analysis of the literature is recently reported by Shao (2007). We extend Shao’s synthesis by critically analyzing the existing literature and noting that studies on internet banking can be grouped
into five broad categories depending on the themes of investigation. These include: a)

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adoption factors affecting decision of potential customers, b) behavioral issues of customers towards internet banking, c) drivers of banks to introduce internet banking, d) impact of internet banking on bank performance, and e) characteristics of internet banking
websites. In the following sections, we now briefly describe each of these categories with
several representative studies highlighting the broad theme of each category and a summary is produced in Table 1. We, however, acknowledge that our review is by no means
exhaustive but our analysis of the literature is an attempt to identify the broad trends in
the current internet banking literature.
The first category, which dominates the existing internet banking literature, focuses
on the factors that affect the decision of potential individual customers to adopt/use internet banking. In general, the factors include the attributes of innovation (e.g. complexity,
security, ease of use, perceived usefulness) and the characteristics of adopters (i.e. demographic profile). Studies of Sethye (1999), Liao et al. (1999), Tan and Teo (2000), Chung
and Paynter (2002), Ramayah et al. (2003) and Cheah et al. (2005) represent this stream
who used theoretical arguments drawn from such theories as Theory of Reasoned Action
(TRA), Technology Adoption Model (TAM) and Theory of Planned behavior (TPB) to
explain an individual’s adoption of internet banking. These studies are characterized by
cross-sectional surveys and use of statistical techniques. The findings of this stream of studies are important because a deep understanding of the factors encouraging/inhibiting customers to adopt internet banking practices is useful to bank management. This stream of
studies, however, does not indicate how satisfied the customers are with internet banking.
The second stream of literature focuses on the behavior issues of adopters with internet banking. In particular, this group of studies determines the attitude and satisfaction of customers with internet banking. The works of Mols (1998), Liao and Cheung
(2002), Buys and Brown (2004), and Arunachalan and Sivasubramanian (2007) represent this stream. These studies, too, rely on cross-sectional surveys and examine such issues as customer attitudes, customer satisfaction, and customers’ sensitivity to price and
customers’ expectations of quality attributes from internet banking. The strength of
these studies is that they shed useful light on post-adoption aspects of internet banking.
However, these studies did not look at how various demographic factors may affect those

behavioral aspects.
Unlike the previous two streams of research, the third stream considers internet
banking from the bank management perspective. This stream of studies looks at the motivators/drivers of banks for introducing internet banking services. Typical works representing this stream of research include the studies of Aladwani (2001), Corrocher (2002)
and Furst et al. (2002). This stream reports that the primary motivators of internet
banking include customer-oriented and market-oriented conditions. This stream also
seeks to explain why some banks choose to offer a relatively wider array of internet banking products and services.
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Similar to the previous stream, the fourth stream of research is concerned with internet banking from bank management perspective. It, however, focuses on the impact of
internet banking on bank performance. The works of Furst et al. (2002) and Swierczek
et al. (2005) are notable examples of this line of research. Swierczek et al. (2005) investigated the relationship between IT, productivity and bank profitability in the two groups
of Asia-Pacific banks and found that both banks through pervasive use of internet banking have increased productivity and received both strategic and operational benefits. On
the other hand, Furst et al. (2002) revealed that internet banks have better accounting
efficiency ratio and higher returns on equity than non-Internet banks.
Finally, the fifth stream of research is concerned with the characteristics of the internet banking websites. For instance, Diniz (1998) surveyed the websites of 121 banks
in the United States and grouped the functionality offered by the internet banking websites into three areas: information delivery, transaction, and customer relationship. According to Diniz, large banks are doing better at the basic and intermediary level. In
Malaysia, Suganthi et al. (2001) found that all domestic banks have a web presence but
only four of the ten major banks had transactional capabilities. The remaining sites were

at informational level. In another study, Awamleh and Fernandes (2005) evaluated websites of foreign and local banks in the United Arab Emirates (UAE) and stressed more on
the infrastructure and interface of the internet banking with the customers.
Our research reported in this paper falls into the second stream of research identified above. We, however, seek to extend this stream by examining the influence of several
demographic variables in explaining the variations in customer satisfaction with internet
banking in the context of the Brunei Darussalam.
AN OVERVIEW OF THE ECONOMY, E-BUSINESS INFRASTRUCTURE
AND INTERNET BANKING IN BRUNEI DARUSSALAM

Brunei Darussalam is strategically located between two technological hubs (i.e. Singapore and Malaysia). It has a total population of nearly 0.390 million (Brunei Statistical
Year Book, 2005) with economic activity dominated by the oil and gas sector. The gross
domestic product per capita was B$ 23,865 (US$1=1.560) in 2004. Brunei is culturally
different not only from those of the western nations but also from several of Asia-Pacific
countries. Realizing the limitation as to the size of the domestic market, Brunei business
environment is determined to utilize the Internet as a major development tool. The government has conceived an IT vision and has taken a range of measures to improve the IT
infrastructure and the Internet business environment in the country.
Coping with the regional (ASEAN and APEC) economies the Government of His
Majesty is very determined with its e-Government program. The Brunei government envisioned the e-ASEAN program in 2001 with the major aim of facilitating the establishment of an ASEAN information infrastructure and to develop capacity building and

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Table 2: Key statistics of banks operating in Brunei Darussalam

e-Society programs. In order to achieve this vision, the government has allocated B$788
million or US$450 million for e-Government and setup Brunei Darussalam Information
Technology (BIT) Council to gear up the task of e-Government in the 21st century (EG21)
(www.bit.gov.bn). BIT Council aims to promote effective IT application, facilitating best
practice in the private sector and reducing the cost of doing business to business and business to consumer and has planned to achieve 50% of e-Business program. According to
world Internet users’ statistics, the total number of internet users in Brunei Darussalam is
135,000 thus making 33.5% of the total population penetration in 2007 (www.internetworldstats.com). According to Brunei Year book (2006), every third house has a PC.
In 2001, Brunei banking and finance industry accounted for 5% of B$ 389 million
of country’s GDP. Interestingly, Brunei Darussalam has no central bank. However, the
government via Banking Act and Finance Companies Act regulates the banking activities to ensure stable and fiscally sound business environments. A total of nine banks,
many of which are branches of major global players, currently serve Brunei population.
In addition, there are four finance companies in operation to supplement the banks in
providing financial services to the Brunei residents (www.bifc.finance.gov.bn). Table 2
provides some useful statistics of major banks operating in Brunei Darussalam. It can be

noticed that except for Standard Chartered bank all major banks have established internet banking operations in Brunei Darussalam. All the major three banks that have

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internet baking operations offer such services as fund transfers, credit card activities,
statements of accounts and bill payment.
RATIONAL OF INCLUSION OF DEMOGRAPHIC FACTORS
AND OF CUSTOMER SATISFACTION

The fundamental assertion underlying our research model is that customer satisfaction
with internet banking is likely to differ depending on their demographic factors. A total
of five demographic factors were considered important which have previously been reported to be related to user satisfaction with IT and e-business applications. They include: gender, age, income, educational level and internet experience. Although, the
inclusion of the demographics were significant predictors of several IS applications (Sherman et al. 2000; Nayak, et al. 2006), however, it has produced conflicting results as well
(Shaw and Grant, 2002; Ono and Zabdny, 2003; McMurtrey et al. 2008). Within the
context of e-banking, a study report (www.researchnews.osu.edu/archive/ebanking.htm)
at Ohio State University examined the role that factors such as age, income, and educational level play in consumer’s adoption of e-banking technology and found that it is not
only the demographics but their personal attitude about the technology that remained
significant for e-banking adoption. Lee (2010) studied the role of demographics on the

perception of e-Commerce adoption in South Korea and found that effects of demographic factors have moderated in information technology attitude towards the benefits
of EC and its adoption regardless of gender, age, education and income level.
Based on above assertions our research model includes these variables and detailed
explanations are offered below describing how each of these factors may affect customer
satisfaction with internet banking.
Gender
The IS literature is full on the various gender-based studies and researchers have studied
the variable from various dimensions. There is a debate concerning the impact of gender
on the study of attitudes towards computer use and it was found that males had positive
computer attitudes as compared to female towards computer use (Key, 1992; Bell, 1995,
Seyal et al. 2000). Shashaani, (1997) found that men tend to be more interested in computers than women on average contributing to gender difference in Internet use. Gefen
and Straub, (1997) and Venkatesh and Morris, (2000) found gender difference in individual adoption and sustained usage of technology in the work place. Teo and Lim
(2000) and Teo (2001) found that males tend to use more internet activities as compared
to female. Ono and Zavodny (2002) found that women were significantly less likely to
use the Internet than men at home or elsewhere. Dahlan et al. (2002) in their study of
Malaysian bank employees found males were more ready in data mining as compared to

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female employees. Ramayah and Jantan (2004) found males exhibit higher use of the
Internet in messaging, browsing and downloading activities. However, Awamleh and
Fernandes (2005) did not support gender differences among Internet banking customers’ satisfaction study in UAE.
Age
Age is considered a significant variable among various IS adoption studies in studying the
attitudes towards computers (Kay, 1992) and the Internet (Mukherjee and Nath, 2003).
However, in the various studies it has produced varying results. According to the 1998
Household Internet Use Survey (The Daily, 1999) in Canada the age group 35–54 were
most likely to use the Internet followed by the under 35 years of the age. Krut et al. (1998)
found that age, gender and race were positively associated with technology usage. Teo
(2001) supported age as a crucial factor in Internet adoption. However, Ramayah and Jantan (2004) found that age is negatively associated with the students’ use of the Internet.
Income
Several previous studies in Information Systems studied the impact of income as one of
the factors associated with the use of computers and the Internet. Teo (2001) found that
income level was a significant factor in Internet use. Awamleh and Fernendes (2005) noticed income appeared to be a significant factor in transaction security among customers’
satisfaction.
Educational Level
Several researchers have highlighted the importance of education not only in the formation
of positive attitude toward the technology usage but also as a factor that is significant in the
actual usage of Information Technology. Kay (1992) has reported that in general, people
with higher educational qualifications have a favorable predisposition in regards to computer use. Al-Jabri et al. (1997) and Seyal et al. (2002) have found the relationship of educational qualifications with positive attitudes towards the use of the computer. Mendoza
and Toledo (1997) in their study of demographics and behavior of the Chilean Internet
population found a significant relationship between higher education and Internet usage.
Internet Experience
Prior experience in both computer and Internet strengthens the individual belief in terms
of using subsequent technological innovations such as Internet businesses and Internet
banking. Taylor and Todd (1995) discovered that experienced users with the similar systems would have higher intention to use the system. Whereas, Venkatesh and Davis, (1996)
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suggested the external factors such as computer experience had a direct effect on behavioral
components in terms of technology usage. Black et al. (2001) found that previous experience with the Internet is one of the strongest influencing factors that effect Internet banking adoption. Similarly, in Malaysia, Ndubisi et al. (2001) and Ramayah, et al. (2003) have
examined various external factors that affect the technology acceptance and found prior
experience with technology is significantly related with the technology adoption.
Customer Satisfaction
The MIS researchers over the last three decades have been conducting various studies
surrounding the evaluation of IS success (Swanson, 1974, Schewe, 1976, Delone and
McLean, 1992). They linked the IS success to the overall satisfaction level of the end-user
(Ives et al. 1983). At the outset, because of the absence of a proper measurement the researchers used the users’ perception as a measure of the success of IS. Later on, MIS researchers focused on the development of instrument to measure both user information
system satisfactions (Bailey and Pearson, 1983; Ives, et al. 1983; Doll et al. 1994) and
end-user computing satisfaction (e.g., Doll and Torkzadeh, 1988; Doll et al. 1994;
Etezedi-Amoli and Farhoomand, 1996). Within the context of e-banking Mattila,
(2001) concedes that customers’ satisfaction is a key to success in Internet Banking and
banks will use different media to customize products and services to fit customers’ specific needs in future. Similarly, Hiltumen et al. (2004) have remarked that there are at
least two major human computer interaction (HCI)s whereas, Lindgaard and Dudek,
(2003) emphasizes that now is an ideal time for HCI researchers to analyze user satisfaction because there is a growing interest in how to attract and increase the number of online customers in e-business and e-commerce. They also stress that HCI researchers
should reveal a structure of user satisfaction, determine how to evaluate it and conclude
how it is related to the overall user experience of online customers.
In the early days, Bailey and Pearson (1983) developed a semantic differential instrument measuring overall computer user satisfaction. Ives et al. (1983) later produced a
condensed form of Bailey and Pearson (1983) instrument. Doll and Torkzadeh (1988)
suggests that Ives et al.’s instrument was designed for traditional data processing environments and measures general user satisfaction with EDP staff and services, information
products and user involvement rather than measuring satisfaction with specific applications. Doll and Torkzaddeh, (1988) found that Ives et al.’s (1983) instrument ignores important “ease of use” aspects of the man-machine interface in EUC environments. Hence
Doll and Torkzaddeh (1988) developed a 12–item and five factors instrument for measuring end-using computing satisfaction. These factors measure five components of end-user
satisfaction such as: content, accuracy, format, ease of use and timeliness. The instrument
that has both higher reliability and validity was however, faced with various conceptual

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issues that was raised by Etezedi-Amoli and Farhoomand (1991) but test-retest studies
have further demonstrated the reliability and stability of the instrument (Doll and
Torkzaddeh, 1991; Hendrickson et al 1994). Etezedi-Amoli and Farhoomand (1996) developed another instrument to measure end user computing satisfaction that uses six factors. They proposed that in the end-using computing evaluation of the systems’ success
can best be made by its users as they are the ones to evaluate as to what changes the new
system brings in the working environments and its relationship with the customers. However, Doll and Torkzadeh EUCS instrument was used by number of previous researchers
(Dowing, 1997, 1999; Igbaria and Tan 1997; Gelderman, 1998; McHaney et al. 1999).
Literature review further reveals that with the proliferation of the Internet businesses and allied services various researchers have developed instrument to measure customer information satisfaction (Palvia, 1996; Lele, 1987; Spreng et al. 1996; Giese and
Gote 2000). There is no doubt in saying that the Internet and Web-computing has drastically changes the working and functioning of the various organizations across the globe.
Although there is a big competition among the business firms within and across various
business sectors to establish web presence on the Internet and to reach millions of the customers on the super highway thus making the ubiquitous computing a virtual reality.
Wang and Tang (2001) developed an instrument to measure customer satisfaction toward
websites. They have a view that both previously developed instrument by Ives et al. (1983)
and Doll and Torkzadeh (1991) was specifically designed to measure EUS within the organization. Wang and Tang (2001) therefore developed and empirically validated a 21–
item, seven factors instruments for measuring information satisfaction with websites that
market digital products and services. Based on their premise, Brown and Buys (2005)
measured the customer satisfaction with the Internet banking websites in South Africa
and empirically tested the 19–item, five factors instrument that measures customer support, security, ease of use, transaction and payment and information content and innovation. In addition few other studies have focused on websites users’ satisfaction in general
(Liao & Cheung, 2002) and online banking in particular (Cheah et al., 2005).
From the above discussion based upon the review of literature, it is evident that
measuring customers’ satisfaction is the primary goal of EUC. Several instruments are
available to measure it since its inception of 1983 till today with the latest of Brown and
Buys (2005). Nevertheless, the selection of the instrument is left out at the discretion of
the researchers. Our work, however, is based upon the instrument provided by Doll and
Torkzadeh’s (1988) measure of user satisfaction for the following reasons: First, the review of the literature reveals many successful stories for measuring user satisfaction but in
the realm of end user computing the work of Doll and Torkzadeh (1988, 1991) remain
the standard as the instrument has sufficient parsimony and predictive validity as reported by the studies mentioned above. Secondly, as Gelderman (1998) point out that
EUS instrument measure satisfaction with an individual application and this eliminate
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the need for adaptation of the instrument. Thirdly, as our study aims to target population from several demographical layers therefore we agree with the suggestions of Raymond (1985) to use an instrument that should be simple short and easy to answer and
that Doll and Torkzadeh’s (1988) instrument was selected for this study.
In the past very few studies have combined the two basic streams of information system that is the user satisfaction and the role of demographics in predicting satisfaction
within the context of Internet banking. Therefore there exists a gap on the empirical studies focusing on online banking customers’ satisfaction using standard satisfaction construct
and the role of the demographical variables within the South-Asian context. To best of our
knowledge, no prior study exists in the Brunei Darussalam. Therefore, to fill-in the gap,
the present study was launched to determine the online banking customer’ satisfaction in
Brunei Darussalam. It will be relevant for the readers if we briefly discuss the following:
It is evident from the above information that Internet-banking in Brunei is still at
an infancy stage. However, gradually it is gaining in confidence with the increasing number of satisfied customers. It is, however, deemed necessary to find an answer to the following research questions so that based upon the study findings we could recommend
some implications for the relevant authorities:
1. To access and determine the online banking customers’ satisfaction.
2. To access and determine the various demographic factors that lead to Internetbanking customers’ satisfaction.
METHODOLOGY

The Instrument
The study undertakes the instrument used by Doll and Torkzadeh, 1988 that measures
end user satisfaction across five components: content, accuracy, format, ease of use and
timeliness using twelve questions with Likert-type scales. All questions relating to satisfaction on the survey used a 5-point Likert scale, with “1” being extremely dissatisfied to
“5” being extremely satisfied. The instrument consisting of demographical profile and
five different constructs of measuring over all satisfaction such as: content, accuracy, format, ease of use and timeliness. Table 3 summarizes the basic descriptive statistics of
these constructs.
Sample
Five hundred questionnaires were sent to various members of community groups randomly from business employees of public and private sector organizations, educationists,
students, and professionals such as doctors, scientists, journalists and the general public
in July–August 2009. We received four hundred questionnaires; however, twenty were

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Table 3 Descriptive Statistics

dropped out because they were not filled-in properly. Therefore three hundreds and
eighty questionnaires were retained for the purpose of the research with the response rate
of 76%. The response rate was found satisfactory for the logical deduction of the analysis. Table 5 reflects the demographical and organizational profile of the respondents.
Instrument reliability and validity
Several techniques were used to assess the reliability coefficient, Cronbach (1951) (a),
and to assess face, construct and convergent validity. In order to ascertain face validity,
an initial questionnaire was passed through routine editing after it was given to the panel
of experts consisting of two academics from the Business Department of the Institute of
Technology, one HR practitioner and a few senior bank officers located in the close proximity of the author’s work place. They were asked to respond to the questionnaire and
very few comments in fact were received and some minor changes were done to enhance
the clarity. Table 4 shows the reliability coefficients and convergent validity for the various constructs.
Table 4 Pearson Correlations and AVE Table for Discriminant Validity
No of original
scale items

Alpha

1

2

3

4

Content (1)

4

.78

0.87

Accuracy (2)

2

.80

.78

0.79

Format (3)

2

.82

.63

.66

0.89

Ease of Use (4)

2

.78

.68

.74

.60

0.86

Timeliness (5)

2

.77

.79

.71

.73

.75

5

0.86

Correlation is significant at the 0.01 level (2-tailed), Diagonal represents average variance
extracted in bold

There are several types of validity measures that include face validity and constructs validity. Campbell and Fiske (1959) propose two types of validity: convergent and
discriminating validity. Convergent validity is measured by average variance extracted

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for each construct during the reliability analysis that should be 0.5 or 50% or better.
Table 4 show the reliability values for the various constructs with variance extracted in
diagonal format given in bold. Cronbach’s (α) for the constructs ranged from 0.79 to
0.86 indicating a sufficient level of reliability and convergent validity of all constructs. In
general, results show that both validities are satisfied.
FINDINGS AND ANALYSIS

Three hundred and eighty questionnaires received were analyzed using SPSS version 13
for descriptive analysis, correlation and multiple regression analysis to assess customers’
satisfaction. Table 5 describes the demographic characteristics of respondents.
The results in Table 5 indicate that only 44% of customers are satisfied with the
online banking. The majority of the respondents are young females having a first degree.
They have access to the Internet, possess adequate knowledge and skill and belong to an
income group ranging from $3000 and above per month and are government servants.
Table 5 shows other demographics.
Statistical Analysis
In line with the principles of multivariate data analysis, we conducted a zero-order correlation between the independent demographical variables and the dependent variable,
customers’ satisfaction, before conducting the hierarchical regression analysis to answer
our first research question. The main reason for the correlation analysis is to find the directional support for the predicated relationship and to show that collinearity among the
independent variables is sufficiently low so as not to affect the stability of regression analysis (Hair et al. 1979). From the correlation analysis it was reported that none of the
variables are highly-inter-correlated, so the problem of multicollinearity does not exist
thus fulfilling Hair et al.’s (1979) criterion that says that variables to qualify for multicollinearity should have a coefficient of correlation 0.80 or higher.
Prior to the regression analysis, data were screened for outliers. Cases with a standard
deviation greater than 2 and cases with missing values were removed. The result of hierarchical regression analysis is given in Table 6. The table data further concluded that four out
of five variables are significantly contributing toward the regression equation. The variable
gender remained insignificant. The effect of multicollinearity was studied by examining
the VIF values for each of the regression coefficients. It was found that values for all the coefficients were all less than 10 and as such multicollinearity was not a problem and did not
distort the regression analysis. The model has high predictive power with a significant F
ratio indicating a good fit of the model and being statistically significant in explaining customers’ satisfaction toward online banking. The Beta’s (standardized coefficient) indicate
the relative importance of the independent variables in explaining customers’ satisfaction.

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Table 5 Showing demographical and other organizational data

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Table 6 Hierarchical Regression Analysis for Customers’ Satisfaction

R 2 = 66%. Adj. R 2 = 64%. Dependent Variable: Customer Satisfaction

In addition about 66% of the variance is shared by the four independent variables indicating that the model is effective in predicting adoption.
DISCUSSION

The first objective of the study was to access and determine online banking customers’
satisfaction. This was achieved through the use of the construct used by Doll and Torkzadeh, 1988. The multi-dimensional construct has both content and construct validity and
sufficient reliability and confirms the structure and dimensionality of the user satisfaction
and provides evidence that customers’ satisfaction is a robust measure of user satisfaction
(Doll & Torkzadeh, 1988). On this scale online banking customers’ satisfaction was measured and it was found that around 50% of the customers are satisfied. However, only
42% are satisfied with the clarity and content of the websites. The result therefore partially
supports Liao and Cheung, (2002) that user experience, involvement, user friendliness
and accuracy are important quality attributes toward Internet-based e-banking.
To fulfill the second objective of the study to assess and to determine the role of
demographical variables towards the overall customers’ satisfaction, hierarchical regression analysis was used. It was found that four out of five demographical variables such as:
age, educational level, income level and prior experience with Internet significantly determine the overall customers’ satisfaction. Our results therefore partially support Awamleh
and Fernandes (2005) that security, convenience, age, income and number of years as an
Internet banker contribute toward customer satisfaction of Internet banking in UAE.
Our results are inline with Berger and Gensler’s (2007) work on Internet banking customers in Germany that online banking customers are younger, better educated, their
occupational and income status and belong to the urban areas are significant. In our regression analysis the Beta coefficients explain the relative importance of each independent variable. The highest beta coefficient in our analysis in Table 5 shows that in
comparison age ranks first due to its high value followed by the prior Internet experience,
followed by income level and finally educational level. The result also shows that the regression model has significant predictive power with 66% of the total variance being explained by the four variables. Surprisingly, the variable gender remained insignificant

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besides the fact that 57% of the respondents are females and this does not support prior
studies of Ramayah and Jantan (2004), Dahlan et al. (2002) and Cheah et al. 2005.
However, our results support prior study of Awamleh and Fernandas, (2005) that gender
does not appear to be a factor in determining satisfaction with the Internet banking.
The study, as secondary finding, highlights the problems associated with the online banking as perceived by the users. The users are concerned about the security features not properly addressed in some of the banks’ websites and several others mentioned
about their lack of knowledge about the Internet and the low speed of the Brunet (the
main ISP in the Brunei).
CONCLUSION

This study is the first of its kind conducted in Brunei Darussalam and has fulfilled its objectives. It has evaluated demographical factors that are significant in determining the
satisfaction of customers in using Internet banking. Banks in Brunei Darussalam do not
use their websites strategically to improve customer relationship or add real value. Online
customers are concerned about the lack of security features, slow speed of the Internet, and
lack of Internet skill. All these can be addressed by the management of the relevant financial institutions and once started using strategically the banks can further gear up the
confidence of online customers and more and more customers will turn to online banking
in Brunei Darussalam. Once customers are convinced about the multifarious advantages
of online banking, they will start asking for this service from their banks which will increase the pressure on the bank authorities to keep their customers satisfied. The banks
can further provide some incentives to their online customers to attract more non-users
such as some promotion or lucky draws to increase their satisfied customers’ base.
Limitation: Researchers such as Etezadi-Amoli and Farhoomand, (1996) state that
the primary purpose for measuring end-user computing satisfaction is to predict certain
behaviors and measurement of end-user computing satisfaction and it should be more
closely tied to attitude-behavior theory. The present research does not consider the attitudinal dimension of the customers so does not predict the customers’ behavior directly
and would be undertaken by the future researchers. In addition the present research does
not undertake the variables such as; security of the transactions and perceived risk that
need to addressed in the future research.
PRACTICAL IMPLICATIONS

The study results provide empirical evidence and several implications to the management
of the banks. The findings suggest that four of the five demographical variables such as age,
educational level, income and Internet experience are significant predictors of customer
satisfaction toward e-banking. This important finding aids to several e-banking marketing
issues such as understanding the behavioral segment in designing the promotional
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strategies. The behavioral segment can group customers in term of usage, loyalty, benefits
sought and customers’ satisfaction. Bank authorities using this aspect can further devise
the strategies to better match customers’ needs, better opportunities for growth, retaining
existing customers and finally to gain the market segment. Bank can develop better customer’s relationship by knowing the customers’ satisfaction on e-banking.
In addition, bank authorities can design an extensive customer orientation and
training programs for both types of customers who are educated, young, high earning
and have previous Internet experience in order to retain them as satisfied customers with
the other groups of prospective customers of using the e-banking who are older in age,
belongs to lower income, and are less educated and possess no prior Internet experience.
In fact, these potential customers always have an anxiety of using e-services. So given
them special programs and incentive with massive campaign, bank authorities could further enhance their customers base and achieve the critical mass.
ACKNOWLEDGEMENT

The authors are thankful to Mike Cross for his valuable comments and editing the early
version of this manuscript.
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