Antecedents to E-
Banking

AN EXAMINATION OF THE ANTECEDENTS OF ELECTRONIC
BANKING TECHNOLOGY ACCEPTANCE AND USE A Dissertation
Presented to the Faculty of the College of Business Administration
Of Touro University International
In Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy By
Jeanette Taft
October 24, 2007
UMI Number: 3293730
3293730
2008
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several community boards of directors including the Better Business Bureau; California
Association of Public Hospitals; Emergency Medical Care Consortium; Operation PAR;
Athena Society, and Mental Healthcare Inc.
Antecedents to E-
Banking
v
ACKNOWLEDGMENTS
It would have been impossible to accomplish a research project of this extensive
nature had it not been for the support, advice, and input of others. I am most appreciative
to my research committee consisting of Dr. Suzanne Peterson, who graciously accepted
to be the chair of the committee, and guided, encouraged, and directed me in an
incomparable manner. The committee members, Dr. William Reay, whose keen insight
and probing input guided the process; and Dr. Kendra Reed, whose detailed analysis,
direction, and patient guidance greatly facilitated this process. Each of these committee
members brought their unique areas of expertise in the development of this study, to my
benefit. Additionally, Dr. Gerald Thomas graciously agreed to be a reader; my sincerest
gratitude to him for his timely responses; his proof reading and editing was critical to
enhancing project readability.
My appreciation also extends to the faculty of Touro University; each course
broadened my sphere of knowledge, and prepared me for the rigors of the dissertation.
Special acknowledgement goes to Dr .Donna M. Blancero, with whom I began the
proposal process; she made learning fun: and to Dr. Joshua Shackman, who as Director of
the PhD program was always available to answer my questions, and greatly facilitated the
process in so many ways. My gratitude also is extended to Anne Marie Ziadie, librarian,
whose assistance was invaluable as she assisted in my research. To My cohort, Dr. Shelia
Lewis, who illuminated the path for me to follow, I offer my sincerest “thank you”.
I must acknowledge the support, encouragement, and understanding of Dr.
Richard Davila, my boss, and Director of Springfield College, School of Human
Services, Tampa campus. Dr. Davila gave generously of his time and advice, provided
Antecedents to E-

Locus of control and computer self-efficacy 8
Computer self-efficacy and e-banking technology acceptance and use 10
Demographic factors and e-banking computer self-efficacy 10
Theoretical Framework 11
The Technology Acceptance Model 12
Current study’s model 13
Contribution to knowledge 14
Research Questions 14
Chapter 2 – Review of Literature 17
The Technology Acceptance Model 17
TAM Extensions 19
Current model’s extension of the TAM 21
Impact of Technology on the Banking Industry 23
Phone banking 26
Electronic bill payment 27
On-line banking 30
Computer Self –Efficacy and Prior training 33
Self-efficacy 33
Computer self-efficacy 35
Effect of prior training on computer self-efficacy 38
Effects of EB Prior Training on EB Acceptance and Use 41
The effect of Perceived Ease of Use on Computer Self-efficacy 42
Effects of Perceived Ease of Use on E-Banking Acceptance and Use 44
Effect of EB Computer Self Efficacy on EB Acceptance and Use 45
Locus of Control 46
Locus of control and e- banking computer self-efficacy 48
Locus of control and EB acceptance and use 49
Demographic Factors 50
Gender and EB computer self-efficacy’s effect on EB acceptance and use. 51
Age and EB computer self-efficacy effect on e-banking’s acceptance and use 53

Scale Reliabilities 77
Correlational Analysis 79
Hypotheses Testing 80
Diagnostic Tests 80
Hypothesis 1 80
Hypothesis 2 81
Hypothesis 3 82
Hypothesis 4 83
Hypothesis 5 84
Hypothesis 6 85
Hypothesis 7 86
Hypothesis 8 87
Hypothesis 9 88
Hypothesis 10 89
Hypothesis 11 89
Summary of Hypothesis Testing 90
Results summary 90
Chapter 5 – Discussion 92
Discussion 92
Theoretical Contributions 93
EBCSE influences EBAU 94
Antecedents to E-
Banking
ix
PTEB Influences EBAU 95
PEUEB Influences EBCSE 95
Limitations 96
Recommendations for the Banking Industry 98
Future Research Directions 98
References 101


Antecedents to E-
Banking
xi
LIST OF FIGURES
Figure 1 -A Theoretical Model 22
Figure 2. Mediation analyses on EBCSE and the relationship between PTEB and EBAU
after controlling for Race and Income 68
Figure 3. Mediation analysis on EBCSW and the relationship between PEUEB and
EBAU, after controlling for Race and Income 69

Antecedents to E-
Banking

ABSTRACT

This research extends the Technology Acceptance Model (TAM) as applied to a specific
type of technology: electronic banking. The study suggests four antecedents to
individuals’ acceptance and use of electronic banking: electronic banking-specific
computer self efficacy; prior training in electronic banking; perceived ease of use of
electronic banking technology, and locus of control. The investigation further seeks to
determine if age and gender influence these variables while controlling for race and
income. Results of the statistical analysis is important for practitioners and researchers, in
that electronic banking-specific computer self efficacy, as well as prior training in e-
banking were both found to predict individuals’ acceptance and use of electronic banking
at a statistically significant level. Additionally electronic banking-specific computer self
efficacy was found to predict perceived ease of use of electronic banking. The results
provided two important insights into the model: age and gender did not influence
outcome variables; and neither did race and income. The data have implications for
practitioners and researchers in lending further understanding of the factors that affect

From the consumers’ perspective, e-banking provides many benefits to
individuals, such as immediate access to accounts and balances, ability to conduct remote
banking transactions and investments, and completion electronic applications (Donner &
Dudley, 1997). With e-banking, time and location become irrelevant (Jayawardhena &
Foley, 2000) given that these services can be accessed at any time; regardless of where
the individual happens to be located. The prospect of around-the-clock access to bank
services and the convenience of transacting business from anywhere in the world should
be especially appealing to consumers, given that the flexibility that e-banking allows
seems to fit our increasingly mobile lifestyle.
At the organizational level, the implementation of e-banking allows banks to
respond to varied consumer needs at numerous locations simultaneously. The intentions
of the banking industry are that these technologies should make banking easier to use and
more convenient for customers than traditional services (Meuter, Ostrom, Roundtree, &
Bitner, 2000). E-banking is pivotal in assisting banks in their transition from multiple
locations to a lucrative and global marketplace (Giannakoudi, 1999). Bank industry
leaders implementing e-banking anxiously seek to take advantage of the decreases in
personnel costs, with the concomitant projections of substantial technology-derived cost
savings when compared to the traditional bricks-and-mortar facilities (Sarel &
Marmorstein, 2002).
Perspectives on the value that electronic banking transactions offer organizations
vary widely, including enhanced image (Flavian, Torres, & Guinaliu, 2004); customer
retention (Fuhrman, 2000); continuous communication between bank and customer
(Giannakoudi, 1999); competitive advantage based on efficiency gains in several
Antecedents to E-Banking 3 operational areas (Jayawardhena & Foley, 2000); and enhanced customer services (Chan
& Lu, 2004). Electronic-banking also frees personnel from simple, repetitive, routine
tasks, allowing them to devote more time to revenue-generating activities (Sarel &
Marmorstein, 2002).

industry. In the last few decades, corporations have significantly increased their
investment in IT (Ndubisi, 2005), and these investments are often substantive and not
without risk (Jackson, Chow, & Leitch, 1997). However, similar to the banking industry,
other businesses also report that despite the large amounts of capital invested in IT, the
expected return on their investment has not been realized, mainly because employees do
not always use the technology (Anonymous, 2000); executives contend they see no
linkage between their duties and what IT does (Pijpers, Bebelmans, Heemstra, and
Montfort, 2001); or that it is oftentimes difficult to gauge users’ acceptance when
introducing new technology (James, Pirim, Boswell, Reithel, & Barkhi, 2006).
Similarly, Taylor (2004) argues that businesses continue to be troubled by
technology systems that either fail or that perform at a less than optimal level. Taylor
further argues that typically when a new technology is introduced in the business world,
the sequence of events is as follows: first the what, where, and when, and occasionally
the why of the new technology is announced; this announcement is followed by the
Antecedents to E-Banking 5 rumor mill, then the formal communication, and lastly individuals’ speculations based on
prior experiences. This combination of factors has a lasting effect on how well the new
technology is accepted. Given that this study posits that PT influences technology
acceptance and use, another area of generalizability of this study would be for businesses
to examine the effect that PT has on TA when introduced in the cycle of events leading
up to new technology implementation.
Further to the generalizability of this study to other industries and other
technologies, lower-than- projected utilization of varying technologies has also been
reported in other industries, and the review of literature reveals that industries other than
banking also grapple with understanding the factors that influence users’ acceptance and
use of their industry-specific technology. Even in the workplace of skilled professionals
such as physicians, where IT plays an important role, these organizations have not been
able to pinpoint the factors that contribute to TA (Yi, Jackson, Park, & Probst, 2006).

computer self-efficacy (EBCSE) affects e-banking acceptance and use (EBAU). Said
differently, this study examines the effects that PTEB, PEUEB, and LOC have on
EBCSE, and consequently the effect that EBCSE has on e-banking technology
acceptance and use given the boundaries by which the theory may or may not apply (i.e.,
age and gender). The study will control for the demographic variables of race and
income.
Antecedents to E-Banking 7 For purposes of this study, technology acceptance is defined as the actual use of
any or all of the three e-banking services investigated (i.e., TB, EBP, OLB). Use of e-
banking is differentiated from intention, or attitude towards use of e-banking products.
Study variables
Prior training and computer self-efficacy.
Compeau and Higgins (1995) define CSE as an individual’s judgment about his or
her capability to use a computer. Many studies focused on CSE have found a positive
correlation between prior training (PT) and CSE (Agarwal, Sambamurthy, & Stair, 2000;
Bolt, Killough, & Koh, 2001; Bornet, 1998; Gist, Schwoerer, & Rosen, 1989; Hollis,
1996; Igbaria & Parasuraman, 1989; Jay, 1989; Jones, 1998; Machin, 2002; Simmers &
Anandarahan, 2001; Torkzadeh & Koufteros, 1994; Torkzadeh, Pflughoeft, & Hall, 1999;
Valasek, 1989). Specifically, CSE has been found to be highly susceptible to various
training approaches such as behavior modeling (Bolt, et al., 2001; Gist, et al., 1989);
goal-oriented training (Hollis, 1996); training transfer strategies (Machin, 2003); and
individualized instruction (Bornet, 1998).
This study considers PT to be any formal or informal training provided to an
individual prior to using e-banking technology (PTEB) for purposes of increasing his or
her e-banking acceptance and use. Because training outcomes are mainly dependent on
facilitating or inhibiting factors unique to each individual (Bornet, 1998), this study will
examine how PTEB affects individuals’ EBAU.
Antecedents to E-Banking 8

orientation).
In studying the relationship between LOC and CSE, Gist et al. (1989) found that
individuals with an internal LOC required fewer repetitions of accomplished
performances, and this mastery is an attribute of CSE that leads to improved
performance. Knowledge of the relationship between internal LOC and CSE could serve
to increase awareness of EBAU antecedents, and could lead to increased use of this
technology, thus benefiting customers and banks. Specifically, Wesley, Krockover, &
Hicks (1985) found that internally oriented individuals exhibit increased knowledge of
varying aspects of computer use, and Eduljee (1995) found that LOC is a predictor of
computer attitudes. Given that using the internet is necessary for accessing e-banking
services. Hoffman, Novak, & Schlosser’s (2003) finding that LOC explains an
individual’s web use is an important finding to this study. More importantly, Bellman
(1998) found that LOC increases an individual’s ability to predict the frequency and
variety of communication technologies used at home, also a critical finding for this study,
given that e-banking activities are most likely to take place in the home. Despite the call
to integrate both LOC and CSE in research studies (Haidt & Rodin, 1999; Judge, Bono &
Thoresen, 2002;), researchers have not thoroughly addressed this issue; and to this
researcher’s knowledge, no other study has examined the relationship between LOC,
CSE, and EBAU.
Antecedents to E-Banking 10 Computer self-efficacy and e-banking technology acceptance and use.
CSE has been used to predict users’ perceptions about their acceptance and use of
information technology (Venkatesh & Davis, 1996). Given the use of e-banking’s
technology dependence on computer use, this study posits that e-banking’s –specific CSE
(EBCSE) influences EBAU because individuals with high levels of CSE are more apt to
use technology more extensively (Bani, 2005), exhibit higher performance levels when
task complexity is high (Bolt, et al., 2001) such as e-banking; and CSE influences actual
computer use (Compeau & Higgins, 1995) which is a requisite skill for e-banking use.

technology acceptance. TAM explores factors affecting computer acceptance in a manner
that is general, and explains computer users within a wide array of populations who
engage in a broad range of computer technologies; TAM is at the same time theoretically
justified and parsimonious (Davis, Bagozzi, & Warshaw, 1989). In other words, while
SCT focuses on individuals’ ability to regulate themselves, TAM provides a platform for
tracing the effects that external factors have on individuals’ internal beliefs, attitudes, and
intentions (such as PEU and PU) as it relates to technology acceptance.
Specifically, using both the theoretical frameworks of SCT (Bandura, 1986) and
TRA (Fishbein & Azjen, 1976), this dissertation adds to TAM (Davis, 1989) in the
Antecedents to E-Banking 12 following ways: (1) Applying e-banking to TAM, and (2) Examining possible
antecedents of the TAM as it relates to e-banking acceptance and use.
The Technology Acceptance Model
Davis (1989) introduced and established the soundness of a new scale to measure
the constructs of perceived usefulness (PU) and PEU; hence, the TAM was developed
(Ndubisi & Jantan, 2003). PU refers to an individual’s belief that use of a particular
technology leads to enhanced performance, whereas PEU is the belief that use of a
determined technology will be effortless (Davis, et al., 1989). To the extent that one
technology is easier to use than another, it will probably be more accepted by users
(Davis, 1989).
Since Davis’s (1989) development of TAM, numerous researchers have extended
the model to examine World Wide Web (WWW) acceptance (Glassberg, 2000); users’
perception of resources (Mathieson, Peacock, & Chin, 2001); effect of computer attitude
and self-efficacy on actual use (Chau, & Hu, 2001); single and multifunction
technologies (Taylor & Todd, 1995); users’ perception of resources (Szajna, 1996);
computer playfulness (Moon & Kim, 2001); cognitive absorption (Agarwal & Karahana,
2000); and perceived enjoyment and product development (Koufaris, 2002).
TAM was chosen for this study because of its parsimony and predictive powers,