An examination of the antecedents of electronic banking technology acceptance and use

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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Antecedents to E-
Banking
Antecedents to E-
Banking


Antecedents to E-
Banking
iv
BIOGRAPHICAL SKETCH
Jeanette Taft’s educational background include a Bachelors in Nursing and a
Masters in Nursing from Hunter College, NY; a Masters in Business Administration from
Pepperdine University, CA; and a PhD in Business Administration from Touro
University International, CA. Ms. Taft’s other educational pursuits include a management
fellowship sponsored by New York University and the California Association of Public
Hospitals.
Ms. Taft is presently assistant professor at Springfield College School of Human
Services, Tampa campus. Prior to this she served as Senior Vice President and Chief
Operating Officer of Tampa General Healthcare; Hospital Administrator, San Joaquin
General Hospital, and Assistant Administrator Merced Community Medical Center. In
1995 she founded and has since managed Taft Management Services, providing
management consulting and training services domestically, in Central and South
America. Awards and recognitions include a Susan B. Anthony award, business field;
Business Woman of Achievement; Top 10 Outstanding Business People, Stockton, CA.
Ms. Taft has been featured in the Best of America’s Compensation Program; Stockton
Record’s Health Advocacy; and the St. Petersburg, FL Times Woman of Achievement.
Her community affiliations include past president of Sun Coast Health Care Executives, a
subsidiary of the American College of Healthcare Executives; past president of Seaport
Rotary; and past president of the Women’s Center, Stockton, CA. She has also served on

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-

Banking
vi
innovative insights, and in many ways facilitated the process, making it possible for me
to complete the requirements of this degree. My dearest friend Carole Smith cajoled,
prodded, encouraged, and in general supported me throughout this process; I owe her my
deepest gratitude for her friendship and her belief in me. My deepest gratitude is also
extended to my husband Terry Large; it would have been impossible to complete the
project without his unselfish support and sacrifice over the duration of my study.
Lastly, I would like to dedicate this project to my family. To my late father
Carlton Taft, who always supported me in all my endeavors; to my mother, Ethel Taft
who taught me to persevere; to my sister Andrea Thomas Taft, whose goal-attaining
approach to her career, and her dedication to excellence have been an inspiration to me;
and to my brother Dr. Carlton Taft who has always modeled hard work and dedication,
and whose professional accomplishments and successes have always been a source of
pride for the family.
Antecedents to E-
Banking
vii
TABLE OF CONTENTS
BIOGRAPHICAL SKETCH iv
TABLE OF CONTENTS vii
List of Tables x
LIST OF FIGURES xi
Chapter 1 – Introduction 1
Profile of Electronic Banking 1
Study Generalizability 4
Description of the Study 6
Study variables 7
Prior training and computer self-efficacy 7
Perceived ease of use and computer self-efficacy 8

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

Effect of combined age and gender on e-banking’s computer self-efficacy 55
Literature Review Summary 55
Antecedents to E-
Banking
viii
Chapter 3 – Research Methodology 57
Introduction 57
Research Design 57
Measures 57
E-Banking Acceptance and Use and Perceived Ease of Use of E-Banking (PEUEB)
Measure 58
Prior Training for E-Banking (PTEB) measure 58
E-banking Computer Self-efficacy measure. 58
Locus of control measure 59
Demographics 60
Sample 60
Procedures 61
Data Analysis 61
Hypotheses 63
IRB Approval 69
Summary 69
Chapter 4 – Results 71
Introduction 71
Sample Descriptives 71
Age 72
Gender 73
Education 73
Control Variables 74
Race 75
Income 76

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

Appendices 133
Appendix A Background Information and E-Banking Experience 134
Appendix B Electronic Banking Questionnaire 138
Appendix C Computer Self Efficacy Measurement 141
Appendix D Locus Of Control Measurement 144


Antecedents to E-
Banking
x
List of Tables
Table 1 Frequencies and Percents of Respondents’ Educational Level 74
Table 2 Frequencies and Percents for Respondents’ Race 75
Table 3 Frequencies and Percents for Respondents’ Income 76
Table 5 Cronbach’s alphas for PTEB, PEUEB, EBSCE, LOC and EBAU 78
Table 6 Correlations between Research Variables 79
Table 7 81
Hierarchical Regression for EBSCE Predicting EBAU controlling for Race and Income
Table 8 82
Hierarchical Regression for PTEB Predicting EBCSE controlling for Race and Income82
Table 9 83
Hierarchical Regression for PTEB Predicting EBAU controlling for Race and Income.83
Table 10 85
Hierarchical Regression for PEUEB Predicting EBCSE controlling for Race and Income
Table 11 86
Hierarchical Regression for PEUEB Predicting EBAU controlling for Race and Income
Table 12 88
Hierarchical Regression for LOC Predicting EBCSE controlling for Race and Income.88
Table 13 Regression for Age Predicting EBSCE 89
Table 14 Summary of Measures used to test hypotheses 91

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

acceptance and use of electronic banking, and provides directions for future research.
Antecedents to E-
Banking
1

Chapter 1 – Introduction
Profile of Electronic Banking
Technological advances have changed the world radically, altering the manner in
which individuals conduct their personal and business affairs (Bandura, 2002). In
particular, over the past two decades the banking industry has invested substantial
resources in bringing information technology to consumers. Responding to deregulation,
rapid global networking, and rising income levels, the banking industry has implemented
new technology-based services called “e-banking” in order to achieve and maintain
strategic advantages (Joseph & Stone, 2003).
E-banking technologies refer to financial activities that involve use of electronic
technology (Lee, 2000), ranging from the now ubiquitous automatic teller machines
(ATMs), to other services such as direct deposit, electronic bill payment, electronic funds
transfer, telephone banking, and on-line banking. These financial electronic technologies
are in differing stages of development. ATMs, a mature e-banking product, have existed
for approximately 30 years and have been widely accepted among consumers.
Conversely, telephone banking, electronic bill payment, and online banking represent
more recent additions to e-banking services, they require competence with computers and
the Internet, and have not enjoyed the same level of consumer acceptance as has ATMs
(Kolodinsky & Hogarth, & Hilgert, 2004). This study’s focus is on telephone banking,
electronic bill payment, and online banking technologies, jointly referred to heretofore as
e-banking.

Antecedents to E-Banking 2

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).

From a financial perspective, e-banking can substantially impact a bank’s bottom-
line. In particular, e-banking lowers operational and administrative costs, thereby creating
considerable cost advantages for the banking industry (Aladwini, 2001). For example,
while a typical banking transaction costs $1.25, a phone transaction costs 54 cents; an
ATM transaction costs 24 cents, and a similar Internet transaction costs a mere 2 cents
(Simon, 2001). The cost of developing a traditional bank is $25 to $30 million compared
to the cost of $6 million to open an Internet bank; further to this point, the cost for
establishing e-banking services in an existing community bank is merely $100,000
(Joseph & Stone, 2003). Thus, from a competitive standpoint, community banks benefit
especially from providing e-banking in that it offers them the opportunity to compete
with larger financial institutions on an equal level (Donner & Dudley, 1997).
Despite the advent of these innovative e-banking technology systems designed to
enhance our lives and facilitate the accomplishment of daily activities, consumer
acceptance has lagged, and the number of consumers using these services has not
increased to the degree expected (Flavian, et al., 2004). Millions of Americans are not
using the e-banking technologies, nor are they expected to do so in the near future
(Kolodinsky, and Hogarth. 2001; Wang, Wang, Lin, & Tang, 2003). In fact, 2002
estimates show that only 22 to 26 percent of households with checking accounts engaged
Antecedents to E-Banking 4


in some form of e-banking, suggesting that more than three out of four households were
still using some form of in-person banking (Anguelov, Hilgert, & Hogarth, 2004).
In spite of the paucity of e-banking utilization, researchers have yet to fully
address the reasons for this resistance. As such, the purpose of this study is to examine
some possible antecedents of consumers’ acceptance and use of three e-banking
technologies: phone banking, electronic bill payment, and on-line banking, hereafter
referred to as PB, EBP, and OLB respectively.
Study Generalizability.
Concern with not achieving projected levels of TA is not unique to the banking

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).

Research on the underutilization of technology has been conducted in the context
of: specific leadership styles, (Schepers, Weitzel, & Ruyter, 2000); education (Gong, XU,
& Yu, 2004; Ong, Lau, & Wang. 2004); medical field (Boonstra, 2003; Chau & Hu,
2001; Hu, Chau, Sheng, & Tam, 1999; Liu & Ma, 2003); e-commerce (Chen, Gillenson,
& Sherrell, 2003; Kloping & McKinney, 2004; McCloskey, 2003/2004; Monsuwe,
Dellaert, & Ruyter, 2004; Shih, 2004); sales force (Robinson, Marshall, & Stamps, 2005;
Taylor & Todd, 1995); the WWW (Fenech, 1998); government services (Carter &
Belanger, 2005; Dimitrova & Chen, 2006; Phang, Kankanhalli, & Li 2006); police
officers (Colvin & Goh, 2005); e-voting (Schaupp & Carter, 2005); executive
performance (Marginson, King, & McAulay, 2001).
Antecedents to E-Banking 6


The above studies present parallel circumstances between underutilization of IT in
various industries, and underutilization of EB in the banking industry. For developers,
implementers and system procurers, understanding the dynamics of users’ TA continues
to be troublesome (Dillon & Morris, 1999); and for banks, as well as for many other
industries, the challenge remains the same: how to determine the factors that enhance TA.
Interestingly, the majority of studies on TA also use the TAM as the theoretical research
framework, thus making this research highly generalizable and applicable to other
industries, especially given Ong, et al’s. (2004) call to validate or examine previous
results of TAM, specifically as it relates to differing technology, user populations, and
organizational contexts.
Description of the Study
This dissertation adds to the growing body of technology acceptance literature by
examining the degree to which the acceptance of a specific form of technology, namely
e-banking, is influenced by individuals’ prior training in how to use e-banking
technology (PTEB), their perceived ease of use of e-banking technology (PEUEB), their
age and gender, as well as how their general locus of control (LOC) affects e-banking
acceptance. In addition, the study also investigates how the mediating role of e-banking

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

Perceived ease of use and computer self-efficacy
Perceived ease of use (PEU) is defined as an individual’s judgment that his or her
interaction with technology will be relatively easy; it reflects the effortlessness with
which an indovodual relates to a specific software system; PEU is considered the
motivating feature in the interactions between humans and computers (Agarwal &
Karahanna, 2000). Notably, PEU is a key factor in the technology acceptance model
(Agarwal, et al., 2000; Hassan, 2006;) in that to the extent individuals perceive a system
to be effortless, they will be more inclined to use it (Davis, 1989); and individual
computer users anchor their PEU strongly to their perceptions about their CSE (Davis,
1989). Specific to the acceptance and use of e-banking, this study posits that the PEUEB
will in turn lead to increased EBCSE.
Germane, to the research, several studies have examined the effect that CSE has
on PEU (Agarwal, et al., 2000; Glassberg, 2000; Gong, et al., 2004; Venkatesh & Davis,
1996; and Wang, 1998; and Wang, et al., 2003). Alternatively, Henry and Stone’s (1994)
study examines the effect of PEU on CSE, thus changing the directionality of the
relationship between these two variables.
Locus of control and computer self-efficacy.
LOC and CSE are individual variable differences posited in this study to influence
an individual’s acceptance and use of e-banking technology. Individual differences are
considered significantly relevant to individuals’ success in computer use, as well as their
interaction with computers (Hong, Thong, Wong, & Tam, 2001/2002). Locus of control
is defined (Rotter, 1966) as a consistently, dependable, steadfast personality trait that
characterizes the degree to which one believes the results or the regulation of
Antecedents to E-Banking 9


circumstances are due to either one’s own actions (internal orientation) or to an external
power that predetermines events, or to the chance-happening of fortunate events (external

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.

While Chan and Lu (2004), and Luarn and Hin’s (2005) study found a positive
correlation between CSE and e-banking use, this relationship has not received much
attention in the research field; hence the thrust of this study.
Demographic factors and e-banking computer self-efficacy
Age and gender are both introduced in this study because these two variables have
been found to have a combined effect on TA (Donnely, 2004; Morris, Venkatesh, &
Ackerman, 2005; Ruth, 1996; Selwyn, Gorard, Furlong, & Madden, 2003; Venkatesh,
Morris, & Davis, 2003). Women and older adults have been traditionally perceived as
being less computer-savvy than their male or younger adult counterparts. Clearly, in
striving to achieve and maintain the competitive advantage accrued by implementing e-
banking technology, banks must attract women as well as men, and customers of all ages.
Determining the boundaries that age and gender impose on CSE and its influence on
EBAU will be critical to banks’ ability to attract and retain new customers to their e-
banking systems. Additionally, examining the effects that age and gender have on e-
Antecedents to E-Banking 11


banking acceptance will provide valuable information for practitioners and researchers
alike.
Theoretical Framework
Two theories build the foundation for this research: 1) the social cognitive theory
(SCT); and 2) the technology acceptance model (TAM). SCT is the belief that individuals
have an internal belief system that allows them to control thoughts, feelings, motivations,
and actions (Bandura, 1986). The CSE construct is grounded in SCT. TAM differs from
SCT in that SCT is a framework that consists of three basic factors: a) individual’s social
cognition, b) individuals’ behavior, and c) individuals’ phenomenological experiences.
The central tenet in SCT is the premise that individuals can regulate their emotions,
thoughts, motivation, and actions (McCormick & Martinko, 2004).
TAM, on the other hand, is grounded in Fishbein and Azjen’s (1976) theory of
reasoned action (TRA), which formed the basis for most of the early research on

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,

which facilitate its application in various circumstances (Ndubisi & Jantan, 2003),
including e-banking (Adamson & Shine, 2003; Lassar, Manolis & Lassar, 2005;
Pikkarainen, Pikkarainen, Karjalouto, & Pahnila, 2004; Wang, et al., 2003).
The original TAM was designed to address individuals in the workplace, an
environment in which behavior is typically more rational than at home. There exists