social cognitive theory perspective


Assessing the determinants of internet banking adoption intentions: A
social cognitive theory perspective
Henry Boateng a, *, Diyawu Rahman Adam b, Abednego Feehi Okoe c,
Thomas Anning-Dorson d
a School of Communication, University of Technology, Sydney, Australia
b Department of Marketing, Garden City University College, Kenyase, Kumasi, Ghana
c Department of Marketing, University of Professional Studies, Accra, Ghana
d Department of Marketing and Entrepreneurship, University of Ghana Business School, Legon, Ghana
a r t i c l e i n f o
Article history:
Received 5 March 2016
Received in revised form
4 September 2016
Accepted 8 September 2016
Available online 15 September 2016
Keywords:
Internet banking
Social cognitive theory
Online customer service
Online banking
Electronic banking
a b s t r a c t
Internet banking adoption is one area that has received attention from scholars. The extant studies have
mainly used technology acceptance models and behavioural theories which do not account for changes
in human behaviour. This study seeks to ascertain the determinants of Internet banking adoption intentions using the social cognitive theory, which accounts for changes in human behaviour. The study
selected the sample from bank customers in Ghana through an intercept approach using structured
questionnaires. A two stage-approach of confirmatory factor analysis and a structural equation modelling
were used in analysing the data. The findings show that websites’ social feature, trust, compatibility with
lifestyle and online customer services have a significant effect on customers’ intentions to adopt Internet
banking. However, ease of use did not have a significant relationship with customers’ intentions to adopt
Internet banking. The significance of the study as well as recommendations for theory, practice and
future studies have been discussed.
© 2016 Elsevier Ltd. All rights reserved.
1. Introduction
Several organizations in recent times have acted in response to
the competitive business environment by implementing e-business
as part of their business strategies (Chong, Ooi, Lin, & Tan, 2010).
One sector that has seen technological innovation both from the
end user and organizational perspectives is the banking sector.
Information Technology (IT) has helped the sector to offer individualized services and at the same time improve service delivery
(World Bank, 2003). Similarly, IT has contributed to innovation and
improved performance in the industry. Malhotra and Singh (2010),
for example, note that Internet banking has transformed the
banking industry worldwide. With the growth of the Internet, it is
to be anticipated that banks will move towards providing online
banking for their customers (Chong et al., 2010). Different academic
researchers have shed light on the reasons leading to Internet
banking adoption, and according to Giovanis, Binioris, and
Polychronopoulos (2012), among the most commonly accepted
approaches are the technology acceptance model (TAM) (Davis,
1989) and the innovation diffusion theory (IDT) (Rogers, 1995).
However, these theories have been criticized for various reasons.
Taylor and Todd (1995), for example, assert that TAM is too
simplistic and does not fully explain people’s understanding of
behavioural intention to adopt a technology and does not account
for the dynamic nature of human behaviour. The purpose of this
study is not to join this debate, but to offer an alternative model
that accounts for the dynamic nature of human behaviour in relation to intentions to adopt Internet banking. This study employs the
social cognitive theory (Bandura, 1989) which is able to explain and
account for the changing users’ behaviour towards technology and
its adoption (Ratten & Ratten, 2007).
Juwaheer, Pudaruth, and Ramdin (2012) note that the empirical
findings from user acceptance research suggest that when users are
presented with a new software package, a number of factors predict
their decision about how and when they will use it. Drawing
inspiration from the social cognitive theory, we argue that bank
* Corresponding author. University of Technology, Sydney, School of Communication, Building 10 level 5, 211.01, 15 Broadway, Ultimo NSW, 2007, Australia.
E-mail addresses: Henry.Boateng@student.uts.edu.au, hboateng@st.ug.edu.gh
(H. Boateng), adamsdeown@gmail.com (D.R. Adam), okoe67@yahoo.com
(A.F. Okoe), thomasdorson@gmail.com (T. Anning-Dorson).
Contents lists available at ScienceDirect
Computers in Human Behavior
journal homepage: www.elsevier.com/locate/comphumbeh
http://dx.doi.org/10.1016/j.chb.2016.09.017
0747-5632/© 2016 Elsevier Ltd. All rights reserved.
Computers in Human Behavior 65 (2016) 468e478
customers’ intention to adopt Internet banking is a function of
social features of website, trust, ease of use, compatibility with
lifestyle, online customer service. Following Mohammadi (2015),
this study defines intentions to adopt Internet banking as the
likelihood that an individual will use Internet banking services.
Dimitriadis and Kyrezis (2011)’s study on Internet banking stresses
the importance of intention to transact telephone banking. In the
work of Lee (2009), it was found that intention to use online
banking is a very important variable in Internet banking adoption.
Thus, the objective of this study is to model the factors explaining
the variations of intention to adopt Internet banking. This study
makes contribution to both theory and practice.
As indicated earlier, most studies on technology adoption and
Internet banking adoption have relied on the TAM, which is incapable/insufficient/incapacitated in explaining or accounting for the
dynamism in users’ behaviour towards technology and its adoption. This study addresses this gap as it is modelled on the social
cognitive theory, which is capable of explaining changes in human
behaviour (Bandura, 1989). It also contributes to technology
acceptance by showing the role of online customer service and
social features of a website in the context of intentions to adopt
Internet banking. Apart from these theoretical contributions,
identifying the variables that explain the variations in Internet
banking adoption intentions will help banks address the changing
needs of bank customers in an online environment. This study,
therefore, explains how the mode of Internet access can be a
boundary condition for Internet banking adoption.
The next section focuses on the theoretical background and
hypotheses development. This is followed by the methodology
used. The findings of the study are presented after that, while the
discussion of the findings follows subsequently. The conclusions,
implications, and limitations are contained in the last section.
2. Theoretical background
Social cognitive theory (SCT), as one of the most powerful theories of human behaviour (Bandura, 1986), serves as the theory for
this study. The primary argument of the SCT is that an individual’s
behavioural intention is a function of not only behaviour, but also of
cognitive personal and environmental factors. Cooper and Lu
(2016) argue that the basic precept of SCT is that behaviour is
regulated by the person through the cognitive processes, and by the
environment through external social situations. Bandura (1986)
promotes the triadic reciprocal determinism through (among)
personal attributes, such as internal cognitive and affective states
and physical attributes, such as external environment factors, and
overt behaviour.
An individual’s perception, beliefs, and expectations mould the
person’s behaviour. That is, how the individual thinks and feels is
associated with the person’s behavioural intentions (Bandura, 1986;
Benight & Bandura, 2004). The theory also implies that an individual’s abilities, knowledge, and skills affect/influence him or her
to engage in certain actions (Bandura,1989; Prussia & Kinicki, 1996).
Bandura (1989) also notes that an individual’s environment, that
is, the factors external to the individual, predicts the person’s
behaviour. This environment includes the physical and social
environment. The physical environment includes the natural and
manmade objects within an individual’s surroundings. The social
environment encompasses the immediate physical surroundings,
social relationships, and cultural milieus within which defined
groups of people function and interact’ (Barnett & Casper, 2001, p.
465). It also includes social norms, access within the community,
peer influence, values, etc. (Bandura, 1991). The social environment
has been conceptualized to include both the virtual and real world
(Narayan, 2013).
The other component of the SCT is behaviour. It is the way
people act or respond to a particular situation or object (Bandura,
1991). It also includes how people respond to technology or technological innovations (LaRose & Eastin, 2004; Ratten & Ratten,
2007). These three components or factors interact with each
other to predict an individual’s action. However, their predictive
capacity is not the same. Furthermore, their influences on each
other do not occur at the same time (Bandura, 1989).
The SCT has been employed in different disciplines, probably
because of its adaptive nature, as it considers human behaviour to
be dynamic (Kock, 2004). For example it has been used widely in
adoption of an e-government system (Loo, Paul, Yeow, & Chong,
2009; Rana & Dwivedi, 2015; Sahu & Gupta, 2007), task
complexity (Bolt, Killough, & Koh, 2001), organizational management (Wood & Bandura, 1989), technological innovation adoption
(Compeau & Higgins, 1999; Ratten & Ratten, 2007), tourism sustainability (Font, Garay, & Jones, 2016) and Internet uses and
gratifications (LaRose & Eastin, 2004). This theory has also been
employed as the theoretical framework to predict customers’ intentions to use computer systems (e.g. Compeau & Higgins, 1995;
Loo et al., 2009; Venkatesh, Morris, Davis, & Davis, 2003). However, it has rarely been used to study Internet banking adoption in
an emerging service context such as in Ghana.
Pincus (2004) asserts that the SCT is built upon the foundations
of individual and group psychological behaviour. Bandura (1986)
explain that this theory is used as a basis to examine the reasons
why individuals adopt certain behaviours. In the light of this and
recognizing the lack of empirical evidence of this model on bank
customers, this study examines the Internet banking adoption intentions of bank customers in the Ghanaian context. It is used in
this study to predict customers’ intentions to use Internet banking
because it explains how individuals’ actions are predicted by the
interaction of personal factors, environment, and behaviour. The
following facets of the theory are particularly relevant to this current study: the development of an individual’s social environment
and cognition, beliefs about the capabilities, personal factors and
motivation via goal system.
3. Research model
Following from the SCT, it is our argument in this study that an
adoption of a particular technology will be influenced by the development of an individual’s social environment and cognition, beliefs
about what the specific technology can offer, personal factors and
motivation through the persons’ goal systems. Therefore, we posit
that Internet banking adoption will be influenced by the social
characteristics of banks’ websites, the level of trust customers have
for the service delivery channel (website), the ease with which they
can navigate the service’s delivery processes on the website, how
compatible the delivery channel is with the customers’ lifestyle and
the overall service quality provided. We further argue that one key
boundary condition for the above adoption to take place in the
presence of the five antecedents is the medium of the Internet access.
Behavioural intentions such as technology adoption can be
influenced by the medium of access (the device used). In Internet
banking, several devices are available through which customers can
enjoy the benefits banks seek to offer. Therefore, the convenience
and enablement provided by Internet access devices can service as
a boundary condition for adoption. As the SCT explains how individuals make sense of social situations, we see the medium of
access as serving as a moderating condition for Internet banking
adoption. We consequently posit that the medium of Internet access will moderate the relationship between Internet banking
adoption and the five antecedents to adoption. Hence, the study
seeks to test the research model in Fig. 1.
H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478 469
4. Hypotheses development
4.1. Websites’ social feature
The social environment is a fundamental component of the SCT
(Bandura, 1991). As we have indicated earlier, the social environment involves the virtual world (Narayan, 2013). In this paper, we
expand the concept of the social environment to include websites’
social features (Park & Kim, 2014). Considering the fact that personal contacts and social interactions are key components of the
Ghanaian culture and communication (Alemna & Sam, 2006;
Hinson, Boateng, & Madichie, 2010), we argue that Internet banking
platforms with social features which enable customers to interact
with each other online relate positively with customers’ intentions
to use Internet banking. Rayport and Jaworski (2001) note that
website design and context are contributing factors to the success
of electronic commerce. Furthermore, studies have shown that
organizations that link their social media pages to their websites
are able to increase traffic to the website (Madichie & Hinson,
2014).
Website features are essential in determining the usage of a
website. Bashir and Madhavaiah (2015) broadly define a website
design as the layout, design, features and characteristics of the fully
transactional website of the bank. Alhudaithy and Kitchen (2009)
conclude that the Internet banking website serves as a platform,
where consumers continuously interact with the host bank and
thus easily perform a series of different banking activities. A website’s social features are defined in this paper as those features that
enable customers to interact and share experiences with fellow
customers. The uptake of Web 2.0 has affected the way most
websites are designed. The more interactive a website is, the more
people are drawn to the website (Kent & Taylor,1998). Some studies
have shown that a website’s sociability has the potential of
increasing traffic to the website and improving customer experience in a shopping environment (Preece, 2000; Sorooshian, Salimi,
Salehi, Nia, & Asfaranjan, 2013). Moreover, personal contacts and
social interaction are central to the lives of most customers in
Ghana (Alemna & Sam 2006; Hinson et al., 2010). Thus, we argue
that social feature of the Internet banking platform is associated
with individuals’ intentions to adopt Internet banking. Thus, we
hypothesize that:
H1. Websites’ social feature is associated with customers’ intentions to adopt Internet banking.
4.2. Trust
Social relationships are a central part of the social environment
in the SCT (Bandura, 1991). In every social environment involving
people and technology, trust becomes a critical issue. Todd (1998)
realized that one key concern of most Internet users is trust; that
is, trust in the service provider and the Internet service (Chai & Kim,
2010). Trust is said to help regulate social relationships between
people and minimizes uncertainty of human behaviour in certain
instances (Lee, Tsai, & Lanting, 2011). Thus, trust is a very vital
concept in Internet banking adoption (Lee et al., 2011) and even
more critical from the perspective of online business (Bashir &
Madhavaiah, 2015). Trust could be defined as the confidence that
an individual may have in the honesty and goodness of a person or
organization. In the context of Internet banking services Bashir and
Madhavaiah (2015) define trust as ‘the assured confidence a consumer has in the Internet banking service provider’s ability to
provide reliable services through the Internet’. Hanafizadeh, Byron,
and Khedmatgozar (2014b) cited Yousafzai, Foxall, and Pallister
(2010) who compared three models (TRA, TPB, and TAM) on
Internet banking adoption with their result emphasizing the
importance of trust. In their work on mobile banking adoption in
Iran, Hanafizadeh, Behboudi, Khoshksaray, and ShirkhaniTabar
(2014a) found that trust was one of the noteworthy antecedents
that explain mobile banking’s adoption in Iran. Lee et al. (2011) and
Liebana-Cabanillas, Mu noz-Leiva, and Rej ~ on-Guardia (2013) in
their study on consumer online banking switching and determinants of satisfaction with e-banking respectively found that
trust is a major determinant of customers’ switching intentions to
Internet banking. Akhlaq and Ahmed (2013) provide further evidence that supports the fact that trust has an effect on Internet
banking adoption in a low-income country context. Based on these
studies, we argue that customers’ trust in the Internet as a secure
platform to conduct banking transactions will affect customers’
intentions to adopt Internet banking. Therefore:
H2. Trust is associated with customers’ intentions to adopt
Internet banking.
4.3. Ease of use
Functioning infrastructures are essential elements of a social
environment, which is associated with an individual’s behaviour
(Barnett & Casper, 2001). In this case, the internet banking platform
Fig. 1. Research model.
470 H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478
can be said to be a central component of the social environment.
The effort required by users to use this platform can affect their
usage intentions (Davis, 1989). A number of essential components
of a website have been proposed by Gibson (2003) to be in place in
spite of the type of business. The author mentions simple website
navigation, fast image download time and fast access to information as those components. This suggests that the ease at which a
customer can use Internet banking is associated with the customer’s intention to use same. Based on the Technology Acceptance
Model, most extant studies have found that ease of use of technology predicts people’s intention to adopt technology (For e.g.
Jaruwachirathanakul & Fink, 2005; Yu, Balaji, & Khong, 2015).
Ease of use is the degree to which the prospective adopter expects the new technology adopted to be a free effort regarding its
transfer and utilization’ (Davis, 1989). Ease of use is defined in this
study as how easy a customer can learn and use Internet banking
services. Jaruwachirathanakul and Fink (2005) discovered the
facilitating and inhibiting factors for adoption of Internet banking
in Thailand. It is further suggested that ease of use is a key factor for
successful Internet banking adoption (Yu et al., 2015). The result of
the study conducted by Bashir and Madhavaiah (2015) in accordance with TAM, suggests that perceived ease of use has a strong
positive effect on Internet banking adoption. Thakur (2014),
Schierz, Schilke, and Wirtz (2010) postulate that perceived ease of
use has been demonstrated to have an effect on attitude. Ease of use
was found to successfully explain the adoption of mobile banking
among Iranian clients (Hanafizadeh et al., 2014a). In a study conducted by Mohammadi (2015), ease of use is identified as an
influential factor and underscores its importance in mobile banking
usage. Liebana-Cabanillas et al. (2013) in their study of the determinants of satisfaction with e-banking established that ease of
use is a determinant of Internet bank usage.
Some studies have, however, noted that there is no relationship
between perceived ease of use and technology adoption and have
thus questioned the overall impact of perceived ease of use in TAM
(Lee, Kozar, & Larsen, 2003; Tiainen, Kaapu, & Ellman, 2013). The
contradictory findings have been explained by gender differences
in user behaviour (Tiainen et al., 2013). Some researchers have
attributed this to what they have termed as the negative cycle of
technology adoption where competences in a particular technology
discourages a person from learning a new technology (Straub,
2009; Tiainen et al., 2013). Nonetheless, in this study ease of use
is expected to have an effect on Internet adoption. Therefore, we
argued that:
H3. Ease of Use is associated with customers’ intentions to adopt
Internet banking.
4.4. Compatibility with lifestyle
According to the SCT, personal factors are key components in
determining human actions (Bandura, 1986). Lerner (1982) notes
that individuals’ personal factors such as age, size, gender, lifestyle,
etc. interact with their social environment to inform their behaviour. Rogers (1995) notes that some people accept an innovation if it
is compatible with their lifestyle. In this case, we argue that
compatibility of an individual’s lifestyle with Internet banking is
associated with the person’s intention to use Internet banking.
Compatibility in this study refers to the situation in which
customers perceive a product or service as relevant to their actions,
ways of thinking and their lifestyle. Hernandez and Mazzon (2007)
suggest that compatibility refers to the degree to which people
perceive that a particular technology is well-matched with the way
they think, act and lead their lives. Chen (2013), and Wessels and
Drennan (2010), in their studies on the factors facilitating and
obstructing the adoption of mobile banking, indicate that
compatibility significantly affects the adoption of mobile banking.
Hanafizadeh et al. (2014b) conclude that the perceived difficulty of
using computers combined with a lack of personalized service is
the most significant barrier to Internet banking adoption among
these customers. Mohammadi (2015) added that ‘the greater the
compatibility of mobile banking with users’ other bank accounts,
the more positive is their attitudes towards it’. Compatibility with
lifestyle was also found to be one of the most significant antecedents explaining mobile banking adoption (Hanafizadeh et al.,
2014a). Consequently, we hypothesize that:
H4. Compatibility with lifestyle is associated with customers’ intentions to adopt Internet banking.
4.5. Online customer services
Drawing inspiration from the virtual social environment
(Narayan, 2013) helps extend the contextual aspect of the SCT
(Bandura, 1986). Since online customer service is important to
some customers in electronic commerce transactions (Avkiran,
1994), we argue that the Internet banking platform with online
customer service features is associated with customers’ intention to
use Internet banking services. Customer service has been an integral part of the service delivery of many traditional organizations as
well as banks. It is normally used to solve, or reduce to the barest
minimum, problems of customers. With the traditional brick and
mortar, customer service is usually rendered at the desk, call centres, automatic call systems etc. Extension of customer service
online could serve as a great bargain, as online customer service has
become an essential part of success for companies conducting
business on the web (Gibson, 2003). Avkiran (1994) had earlier
suggested that customer service quality is expected to be a major
determinant of the performance of banks. Bernett (2000) concludes
that customer service is as essential in the virtual store as it is in the
traditional ‘brick and mortar’ store. There is evidence that suggests
that a substantial number of online shoppers abandon their
transactions because of frustration and lack of assistance from
online retailers (Allen, 2000). Dealing with these problems, Barnes
and Cumby (2002) recommend that electronic commerce companies should ensure that online shoppers get help online and feel
close to the electronic commerce company. In this study, it is
argued that an Internet banking platform where staff welcome and
offer help to the customer to perform his or her transactions
(Avkiran, 1994) has the potential of affecting Internet banking
adoption. Thus we hypothesize that:
H5. Online customer services are associated with customers’ intentions to adopt Internet banking.
4.6. Moderated variable: medium of internet access/device
Several objects such as ‘infrastructure, industrial and occupational structure; labor markets; social and economic processes, etc.
can be found in an individual’s social environment’ (Barnett &
Casper, 2001, p. 465). These objects in totality and with the social
environment are associated with human behaviour (Bandura,
1986). In this view, it can be argued that the device or medium
through which users access the Internet banking is associated with
an individual’s intentions to adopt Internet banking. Some studies
have shown the medium through which access to electronic services affects their usage intentions. Nielsen (1999) for example
noted ‘a bigger screen leads to better usability than a small screen
and that a graphical user interface adds, even more, usability’. This
H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478 471
study considers the medium as a key environmental factor that can
affect the relationship between the cognitive dimensions and the
behavioural outcome. We, therefore, expect the medium of usage to
serve as a boundary condition, which shapes the effect of the
cognitive variables and intention to adopt mobile banking. Chong
et al. (2010) assert that with the increase in asynchronous and
secured electronic transaction technologies, more banks are now
making use of online banking. Electronic devices such as mobile
phones, PDAs (Personal Digital Assistants), laptops, etc. have made
Internet banking accessible for students. This has made it possible
for registered Internet banking users to perform certain banking
transactions like transferring funds, paying bills, printing statements as well as checking account balances among others (Chong
et al., 2010; Mohammadi, 2015). Even though Internet banking
works the same way as traditional banking (Chong et al., 2010) the
convenience characteristics of mobile technologies (mobile phones,
PDAs, smart phones), computers, etc. provide an extraordinary
potential solution to the financial access problem faced by customers in emerging economies such as Ghana (Asongu, 2015; Beck,
Senbet, & Simbanegavi, 2015; Tobbin, 2012). Mobile phones are
also important mechanisms by which young people connect with
others and enhance their self-esteem (Ruleman, 2012; Xie, Zhao,
Xie, & Lei, 2016). Moreover, Internet users in most developing
countries like Ghana access the Internet using the mobile phone.
According to the Social Cognitive theory (Bandura, 1986), an individual’s behavioural intentions or behaviour is as a result of the
interaction among cognitive and other personal factors and an individual’s environmental factors. Thus, we argue that the type of
device that a customer uses to access the Internet and its interaction with websites’ social feature, with trust, ease of use, compatibility with lifestyle and with online customer service help to
explain the variance in Internet banking adoption. Based on this
premise, we propose the following hypotheses:
H6a. Type of device used to access the Internet moderates the
relationship between websites’ social feature and Internet banking
adoption intentions.
H6b. Type of device used to access the Internet moderates the
relationship between trust and Internet banking adoption
intentions.
H6c. Type of device used to access the Internet moderates the
relationship between the ease of use and Internet banking adoption
intentions.
H6d. Type of device used to access the Internet moderates the
relationship between compatibility with lifestyle and Internet
banking adoption intentions.
H6e. Type of device used to access the Internet moderates the
relationship between online customer service and Internet banking
adoption intentions.
4.7. Sampling design and data collection
The respondents of the study consisted of bank customers in
Ghana. There is no updated record or data on bank customers in
Ghana. Therefore, this study sought to use an intercept approach to
capture an adequate sample for this study. Although this approach
is sometimes criticized for its inadequacy in supporting the
generalization of research findings (Trochim & Donnelly, 2008, pp.
144e145), the features of the sample used, the setting and the
procedure we employed for the data collection and analysis
confirm the external validity of the results (Landers & Behrend,
2015). In an intercept approach, potential respondents in data
collection are intercepted (captured/seized/interrupted) before or
after patronizing a particular product or service (Anning-Dorson,
Kastner, & Mahmoud, 2013; Bush & Hair, 1985). This approach allows the researcher to have direct access to the intended respondents and it also helps in the evaluation of the service since
issues under consideration will have been fresh on their minds. In
this study, permission was sought from branch managers of banks
after the study objective had been explained, and respondents were
intercepted as they finished their transaction with the bank.
Selected branches within the capital city of Ghana were chosen to
be part of this study. Since the youth have been identified to be
technology savvy, we decided to focus on bank customers from 20
to 49 years. This age bracket is consistent with those used in similar
studies (see Hernandez, Jim enez, & Martín, 2011; Wang, Minor, &
Wei, 2011). The demographic data of the 600 respondents reflect
the youth and bank customers in Ghana. Most (51.5%) of them were
males whereas (48.5%) were females. Furthermore, most (52.5%)
were within the age 30e39 years. Those from 20 to 29 years
accounted for 27.5% while those from 40 to 49 years constituted
20%. A good number (53.5%) had been banking for more than 19
years, 30.5% had been banking for 10e19 years and 16% had been
banking for 1e9 years. Again, 96.7% had access to the Internet,
while 3.3% did not. Most (80.3%) of them accessed the Internet
using their mobile phones, while 14.0% accessed the Internet using
computers. Similarly, 4.3% accessed the Internet using tablets and
those who used other devices constituted 1.3%. Moreover, a good
number (45.5%) of the respondents had intermediate skills in
Internet usage, 29.0% considered themselves as beginners and
25.5% had advanced skills in Internet usage. Since the respondents
were not ready to disclose their account balance, we decided to
exclude that from the final analysis. Table 1 contains the demographic data of the respondents.
To expedite the data collection, we trained fourth-year undergraduate students to assist in the data collection. They contacted
some of the respondents through an intercept approach in front of
Table 1
Respondents’ demographic data.
Demographic variable Frequency(N) Percentage (%)
Gender
Male 309 51.5
Female 291 48.5
Total 600 100
Age (in years)
20e29 165 27.5
30e39 315 52.5
40e49 120 20.0
Total 600 100
Number of years in banking
1e9 years 96 16.0
10e19 years 183 30.5
20 years and above 321 53.5
Total 600 100
Access to the internet
Yes 580 96.7
No 20 3.3
Total 600 100
Medium/device use to access the internet
Mobile phone 481 80.3
Computers 84 14.0
Tablets 26 4.3
Other devices 9 1.3
Total 600 100
Internet usage literacy
Beginner 174 29.0
Intermediate 273 45.5
Advanced 153 25.5
Total 600 100
472 H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478
banking halls of banks branches in Accra, (the capital of Ghana).
Accra was chosen due to the central role it plays in the economic
and commercial affairs of the Ghanaian economy. The city hosts
headquarters of all banks and is a key economic hub within the
West-Africa sub-region. In 2008, the World Bank estimated that
Accra’s economy alone constituted around US$3 billion of Ghana’s
total gross domestic product (GDP), which is about 20% of the
overall GDP (World Bank, 2008). In the same report, the city also
hosts the largest chunk of the economically active population.
Two branches of banks that have been operating in Ghana for at
least the past 5 years were selected based on the volume of traffic at
the branches. The intention was to capture diverse sets of customers to evaluate the measures for our study. It took one month
(SeptembereOctober 2015) for us to complete the data collection
that involved a total questionnaire of 1000. At the end of the data
collection, we had 600 usable questionnaires, which were used in
the final analysis. To ensure that non-response bias was not a
problem for our study, we followed the recommendations of
Armstrong and Overton (1977) for a response bias test. The filled in
questionnaires returned after the first week and those returned
after the last week of the study were compared. The group means of
these two groups were not significantly different, hence a nonresponse bias was not considered a problem for this study.
5. Measures
The instruments measuring the constructs were adapted from
the extant literature. The items and their sources have been presented in Table 2. The items were measured on a Likert scale using;
1 ¼ strongly disagree, 2 ¼ disagree, 3 ¼ neutral, 4 ¼ agree and
5 ¼ strongly agree. However, the scale measuring the item ‘I think
that Internet banking would be difficult to use’ was reversed coded
during data entry because the question was in a negative form.
5.1. Reliability and validity test
Since all the items measuring the constructs were adapted, we
performed a confirmatory factor analysis to assess the adequacy of
the items. To test the reliability and validity of the measures, the
study used Amos 20 and the maximum likelihood estimation
procedure to examine all scales in a CFA. An exact model fit was
assessed using a chi-square (c2) test. Following Bagozzi and Yi
(2012), a number of approximate fit heuristics were also examined to provide additional information on model fit and the indices
ranged from good to very good. The results showed adequate fit for
the proposed model; c2/df (374.712/174) ¼ 2.154, p < 0.001,
CFI ¼ 0.952, TLI ¼ 0.937, IFI ¼ 0.916, NFI ¼ 0.916 and
RMSEA ¼ 0.044.
Additionally, the adequacy of the measurement model was
ascertained using internal consistency, convergent validity, and
discriminant validity tests. The composite validity test was used to
measure the internal consistency of the constructs. As shown in
Table 2, all the composite reliability values (a) were above the cutoff point of 0.7 (Hair, Black, Babin, Anderson, & Tatham, 2006).
Furthermore, as captured in the diagonals of Table 3, all the values
for the average variance extracted (AVE) were higher than the
squared correlations among the constructs and above the acceptable threshold of 0.5 (Fornell & Larcker, 1981). Moreover, the factor
loadings of the items were above the acceptable value of 0.7 and
there were no cross-loadings (Bagozzi & Yi, 2012; Hair et al., 2006).
Similarly, as shown in Table 3, all the correlation matrices were
below 0.9 (Vance, Lowry, Moody, Beckman, & Read, 2008). The
overall implications of these results are that there is adequate
convergent and discriminant validity and there is no issue with
common method bias (Bagozzi & Yi, 2012; Fornell & Larcker, 1981;
Vance et al., 2008).
5.2. Analysis of model and hypotheses testing
We tested two models, models 1 and 2 using the Structural
Equation Model (SEM). Model 1 measured the association between
the predictor variables (Website social features, trust, ease of use,
compatibility with lifestyle and online customer service) and the
outcome variable (Internet banking adoption intentions). In model
Table 2
Composite validity test.
Constructs Estimate t-values
Social feature (Park and Kim, 2014) a ¼ 0.85
Chatting with other customers online will enrich my internet banking experience 0.860 Fixed
Social aspects of internet banking is important to me 0.780 14.617
I will enjoy conversational interaction on internet banking platform 0.806 15.073
Overall, I will adopt internet banking if there is a social feature 0.767 12.367
Trust (Hanafizadeh et al.,2014a,b) a ¼ 0.79
I would trust my bank to offer secure internet banking 0.709 Fixed
Using internet banking would not divulge my personal information 0.792 12.071
I would find internet banking secure in conducting my transactions 0.675 10.726
I would find internet banking secure in requiring and receiving other information, e.g. bank statements 0.712 11.203
Ease of use (Hanafizadeh et al.,2014a,b) a ¼ 0.78
Learning to use internet banking would be easy 0.796 Fixed
I think that internet banking would be difficult to use (R)* 0.893 10.525
I think it would be simple for me to become skilled at using internet banking 0.692 10.296
Compatibility with lifestyle (Hanafizadeh et al.,2014a,b) a ¼ 0.87
Using internet banking would fit my lifestyle 0.812 Fixed
Using internet banking would fit well with how I like to do my banking 0.891 16.613
Using internet banking would be compatible with most aspects of my banking activities 0.880 16.470
Online customer services (Avkiran, 1994) a ¼ 0.86
I will like to be welcomed when I visit my bank’s website for internet banking 0.812 Fixed
I will like a staff to help me online when using internet banking 0.893 16.809
I will like to have easy access to a staff online when using internet banking 0.734 13.882
Overall, I will like online customer service when using internet banking 0.825 15.673
Intention to adopt (Hanafizadeh et al.,2014a,b) a ¼ 0.84
When you have banking to do, how likely are you to use internet banking? 0.871 Fixed
To the extent possible, I would take advantage of the internet for my banking activities 0.893 17.544
I predict that I would use Internet banking 0.785 15.458
H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478 473
2, we tested the moderation role of the medium in the relationship
among the predictor variables and the outcome variable.
We employed the goodness-fit indices, R2 value and a path coefficient in ascertaining the adequacy of the Structural Equation
Model. The goodness-fit indices for model 1 are as follows; c2/df
(374.712/174) ¼ 1.99, p < 0.001 and the R2value was 0.328. Since
our model was not one of predictive, the relatively low R2 does not
affect our results as low R2 can be a counterbalance to our large
sample size (Hair et al., 2010). Four out of five of the path coefficients were significant. The coefficient path that was not significant was the relationship between ease of use and Internet
banking adoption intentions (b ¼ 0.026, p ¼ 0.507) (see Table 4).
This suggests that hypotheses H3 was not supported.
As proposed, web social features significantly explained the
variation in Internet banking adoption intentions (b ¼ 0.131,
p < 0.001) confirming hypothesis one (H1). Similarly, trust was
significantly associated with Internet banking adoption intentions
(b ¼ 0.105, p ¼ 0.01) supporting hypothesis two (H2). Additionally,
there was a significant relationship between compatibility with
lifestyle and Internet banking adoption intentions (b ¼ 0.171,
p < 0.001) and online customer service and Internet banking
adoption intentions (b ¼ 0.302, p < 0.001) (see Table 4). These
findings support hypotheses four and five (H4 and H5).
5.3. Testing moderation
One way of assessing the moderation effect in SEM, which has
been widely used in management literature, is the multiplicative
approach (see Little, Bovaird, & Widaman, 2006; Boso, Story, &
Cadogan, 2013; Anning-Dorson, 2016). SEM, through a multiplicative approach, was used to analyse the moderating effect relationships. Since this study sought to analyse the effect medium
could have on the relationship between our independent variables
and internet banking adoption intentions, we multiplied each independent variable by medium to assess whether the effect will be
significant or not. Since our intention was to set medium as a
condition for better interpretation of how our independent variables relate with internet banking adoption intentions, the interaction approach offered the best option to achieve our research
objective. Unlike mediation tests, a condition of an intervening
variable relating significantly to the independent variable does not
exist in moderation. Therefore, medium and our independent variable could be interacted to create single indicants for our moderation test. We specifically followed Ping (1995) to create single
indicants for each variable involved in multiplicative interactions,
as these single indicants help reduce model complexity. As a
mitigation measure against possible multicollinearity problems
due to the usage of interactive terms, all measures involved in
multiplicative interactions were mean-centred, as suggested by
Little et al. (2006). The single moderation indicants were therefore
entered into our initial model (model 1) and were then run. To
improve the model fitness of the moderation model, all independent variables were allowed to correlate with each other as such
practice helps improve model fitness (Byrne, 2013). The model 2,
which was used to assess the moderation hypotheses, fit the data
well. The model showed good model-fit indices; c2/df (17.086/
9) ¼ 1.898, p < 0.001, CFI ¼ 0.993, TLI ¼ 0.971, IFI ¼ 0.993,
NFI ¼ 0.985 and RMSEA ¼ 0.039 and therefore could be used to
interpreted the hypothesized moderation relationships. The R2
value was 0.289. With the exception of the interaction between
trust and medium on Internet banking adoption intentions
(b ¼ 0.045, p ¼ 0.330); and ease of use and medium and Internet
banking adoption intentions (b ¼ 0.003, p ¼ 0.936), the rest of the
path coefficients were significant (see Table 5). Based on these results, hypotheses H6b and H6c were not supported.
The path coefficient for interaction between social features of
website and medium on Internet banking adoption intentions was
significant (b ¼ 0.150, p < 0.001). Similarly, the interaction between
compatibility with lifestyle and medium on Internet banking
adoption intentions (b ¼ 0.145, p ¼ 0.002) and online customer
service and medium on Internet banking adoption intentions were
significant (b ¼ 0.319, p < 0.001) (see Table 5). Consequently, hypotheses H6a, H6d and H6e, were supported.
6. Discussion and conclusions
This study aimed at testing hypotheses on the effect of websites’
social feature, trust, compatibility with lifestyle and online
Table 3
Discriminant validity test.
Mean SD 1 2 3 4 5 6 7 8 9
1. Gender 1.49 0.500 e
2. Access to internet 1.03 0.180 0.106** e
3. Medium 1.27 0.603 0.121** 0.157** e
4. Social feature 3.4702 0.84556 0.061 0.068 0.052 (0.6)
5. Trust 3.5801 0.77958 0.013 0.059 0.106** 0.447** (0.54)
6. Ease of use 3.3215 0.62928 0.027 0.091* 0.049 0.265** 0.376** (0.57)
7. Compatibility with lifestyle 3.6414 0.84203 0.090* 0.078 0.086* 0.423** 0.523** 0.395** (0.71)
8. Online customer services 3.9013 0.78698 0.014 0.080 0.117** 0.379** 0.383** 0.392** 0.487** (0.69)
9. Intention to adopt 3.7011 0.82987 0.009 0.116** 0.160** 0.379** 0.390** 0.294** 0.450** 0.499** (0.68)
Variances extracted are on the diagonal; correlation off diagonal. ***p < 0.001; **p < 0.01; *p < 0.05 significance levels.
Table 4
Regression (model 1).
Structural path Estimate p-values
H1 Internet adoption)SF 0.131 ***
H2 Internet adoption)TT 0.105 0.014
H3 Internet adoption)EOU 0.026 0.507
H4 Internet adoption)CML 0.171 ***
H5 Internet adoption)OCS 0.302 ***
NB: SF ¼ Social feature; TT ¼ Trust; EOU ¼ Ease of use; CML ¼ Compatibility with lifestyle; OCS ¼ Online customer services. ***p < 0.001; **p < 0.01; *p < 0.05 significance
levels.
474 H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478
customer services on Internet banking adoption intentions. It also
assessed whether the type of device/medium of access moderates
these relationships. As indicated earlier, SEM was used to test these
association hypotheses.
The findings indicate that web social feature significantly
explained the variation in Internet banking adoption intentions
(b ¼ 0.131, p < 0.001). The interactive nature of the Internet banking
platform has the potential of facilitating conversations among
customers. In this era that customers have come to accept social
interactions on the Internet, incorporating social features to
Internet banking platforms can attract most customers to adopt
internet banking. Social interactions are a part of a traditional
Ghanaian society and this is evidenced in how customers interact
with each other and with employees in the banking halls. Hence
any technological innovation that would seek to enhance that social
aspect of a Ghanaian customer is likely to be adopted. The web
social feature becomes a tool to transfer their interactive nature
from the real traditional setting to the virtual world. This is
confirmed by Alhudaithy and Kitchen (2009) who found that a
bank website serves as a platform where consumers continuously
interact with the host bank and thus easily perform a series of
different banking activities. The social feature of the website makes
it possible for consumers to adopt Internet banking. It can, therefore, be said that the social environment relates closely with consumers’ intentions to adopt internet banking.
The analysis of data also revealed that trust was significantly
associated with Internet banking adoption intentions (b ¼ 0.105,
p < 0.05). This means that trust plays a key role in Internet banking
adoption. Trust is the central element of a social environment. It
reduces uncertainty among individuals in a social setting (Lee et al.,
2011). From the perspective of online business, Bashir and
Madhavaiah (2015) underscore the importance of trust. In a society where unsuspecting people hide behind companies and take
advantage of emerging technologies to defraud customers, customers become more interested in how their investments become
secure. Customers must necessarily trust the technological service
being rendered before patronizing it. Customers trust their banks to
deliver secured services as well as to protect their personal information. Hanafizadeh et al. (2014a) found that trust was one of the
noteworthy antecedents within the social environment that
explain mobile banking adoption in Iran. When transacting business, customers expect secure online transactions.
Moreover, the findings from the analysis disclosed a significant
relationship between compatibility with lifestyle and Internet
banking adoption intentions (b ¼ 0.171, p < 0.001). Customers
favour Internet banking platforms where the service offered fits
their lifestyle. Technology, and technology-based innovations have
become trendy among some Ghanaians (Dzogbenuku, 2013). As a
result, customers are willing to patronize Internet banking insofar
as they see it as trendy; especially those who are technology savvy.
The implication is that when banks are able to develop internet
banking platforms that enhance their lifestyle, there is higher
chance of increased adoption. Using Internet banking should
necessarily be harmonious with how customers do most of their
banking activities. This is in line with the work of Wessels and
Drennan (2010) who indicated that compatibility significantly affects the adoption of mobile banking. Compatibility with lifestyle
was also found to be one of the most significant antecedents
explaining mobile banking adoption by Hanafizadeh et al. (2014a).
In sum, this finding is in conformity with Lerner’s (1982) assertion
that individuals’ behaviour are among others, a result of an interaction of personal factors such as age, gender, lifestyle etc. with
their social environment.
It was also revealed by the analysis that online customer service
plays a major role in customers’ Internet banking adoption
(b ¼ 0.302, p < 0.001). Online customer service has been found by
bank customers to be a critical factor in their decision to adopt
Internet banking. This suggests that customers cherish online
customer service as it makes it possible for the bank to provide help
when the need arises. As a custom in most banks in Ghana, there is
customer service personnel who normally welcome customers to
the banking hall, handle complaints and assist them to perform
their transactions. These practices make customers, as well as
prospective customers, feel a sense of belongingness especially
when their problems or inquiries are adequately attended to.
Customer service has become indispensable in the banking sector
and thus must be transferred onto the virtual world. Allen (2000)
found evidence that suggests that a substantial number of online
shoppers abandon their transactions because of frustrations and
lack of assistance from online retailers. Avkiran (1994) shared the
opinion that where a staff welcomes the customer to the Internet
banking platform, as well as offer help, it potentially affects Internet
banking adoption. Their finding, therefore, confirms the role of
online social environment in influencing customers’ behaviour intentions (Raza & Standing, 2010).
Physical infrastructures are key elements of a social environment. The efforts that an individual must apply to use these infrastructures is associated with their behavioural response towards
such infrastructure (Barnett & Casper, 2001). Hence, we proposed
that there is a relationship between ease of use and Internet
banking adoption. However this study found a non-significant
relationship between ease of use and intentions to adopt Internet
banking. This is probably because the respondents in this study are
more knowledgeable about Internet usage in general and therefore
do not have the feeling that Internet banking will be any different.
Since there may be existing knowledge about similar Internet
platforms, the non-significant relationship found can be attributed
to prior knowledge. Studies such as Straub (2009) and Tiainen et al.,
(2013) have found such prior knowledge as an explanatory variable
for non-significant relationship between ease of use and intention
to adopt. The implication is that banks must assess the level of
existing knowledge about similar technologies as such knowledge
may moderate the ease of usage and intention to adopt. The level of
customer competence in similar technologies can be an enabler or
an obstacle to using Internet banking service.
The study also found that type of device used to access the
internet moderates the relationship between websites’ social features and customers’ intention to adopt internet banking. For
instance, if a device such as a mobile phone or a laptop allows easy
access to social applications and interaction with a customer service agent online, customers are more likely to adopt internet
banking. Studies from the literature (Tobbin, 2012; Weisskirch,
2011) conclude that the convenience characteristics of mobile
technologies provide an extraordinary potential solution to the
financial access problem faced by customers, thus confirming this
finding.
In contrast, however, the study found that the type of device
Table 5
Regression (model 2).
Structural path Estimate p-values
Internet adoption)SF_Medium 0.150 ***
Internet adoption)TT_Medium 0.045 0.330
Internet adoption)EOU_Medium 0.003 0.936
Internet adoption)CML_Medium 0.145 0.002
Internet adoption)OCS_Medium 0.319 ***
R2 ¼ 0.289.
NB: SF ¼ Social feature; TT ¼ Trust; EOU ¼ Ease of use; CML ¼ Compatibility with
lifestyle; OCS ¼ Online customer services. ***p < 0.001; **p < 0.01; *p < 0.05 significance levels.
H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478 475
used to access the internet does not moderate the relationship
between trust and customers’ intention to adopt internet banking.
This finding is in contrast to several findings in the literature which
have concluded that trust is a vital concept in internet banking
adoption and more critical from the perspective of online business
(Yildirim & Zeren, 2015; Lee et al., 2011). It can, however, be said
that type of device for access does not moderate the relationship
between trust and customers’ intention to adopt internet banking,
because customers are more likely to use their personal devices,
considered as more trustworthy, for online banking.
Again it was found that type of device used to access the Internet
did not moderate the relationship between ease of use and Internet
banking adoption intentions. On the other hand, there are studies
that indicate that ease of use of a device can facilitate or inhibit the
adoption of Internet banking (Bashir & Madhavaiah, 2015;
Jaruwachirathanakul & Fink, 2005; Yu et al., 2015). It is expected
that a mobile device’s screen size, for example, should be important
to most Internet users. This finding may be attributable to the fact
that customers in this study context used their personal devices
and this carries an implicit trust in these devices. It is also important to note that there is no significant relationship between ease of
use and customers’ intention to adopt internet banking.
The study found that type of device used to access the internet
moderates the relationship between compatibility with lifestyle
and customers’ intention to adopt internet banking. As indicated by
Hernandez and Mazzon (2007), compatibility refers to the degree
to which people perceive that a particular technology is well
matched with the way they think, act and lead their lives. In this
respect, individuals consider the type of device they use as either
inhibiting or facilitating the adoption of internet banking.
It was found that the type of device used to access the internet
moderates the relationship between online customer service and
internet banking adoption intentions. For an online customer service to be effective, certain essential components are required,
including single website navigation, fast image download times,
and fast access to information (Gibson, 2003). This may explain why
the type of device used moderates the relationship between online
customer service and customers’ intention to adopt.
The study has expanded our understanding of factors that
explain the variations in people’s intentions to adopt Internet
banking. It also implies the need for banks, electronic commerce
companies, and corporate website designers to consider incorporating social features such as those that allow customers to recognize and interact with each other as they transact business online.
Although most bank websites and other e-commerce websites have
chat features, this phenomenon is not common in developing
countries like Ghana. In situations where they exist, this feature is
limited to the interaction between a customer and a service provider. Again, banks must consider offering customer service online
just as it happens in real-time. This will reduce the rate at which
online customers abandon their transactions. Also, banks should
instil trust and confidence in their customers in terms of protecting
their finances, financial information, and personal details. Again,
they should build a secure Internet banking systems in order to
encourage Internet banking adoption.
This study has some limitations, but these limitations do not
render the findings invalid. Firstly, the study does not measure
actual adoption of Internet banking. However, it is the actual usage
that can inure to the profitability of the banks. Therefore, future
studies should considering using these models to study actual
adoption of Internet banking. Again the study did not specifically
consider the moderating role of individual mediums of Internet
devices. Future studies can consider researching into the moderating role of specific Internet devices.
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Henry Boateng is currently a PhD student at the University of Technology, Sydney. His
research experience covers Customer Knowledge Management, Electronic business
and Commerce and Internet application in marketing. He can be reached at: Department of Marketing and Customer Management, University of Ghana Business School, P.
O. Box LG 78, Legon, Ghana.
H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478 477
Diyawu Rahman Adam holds an Mphil Degree (Marketing). He is currently a lecturer
at Garden City University College, Kenyase-Kumasi. His research interest include:
customer orientation, e-banking, e-business and financial service marketing among
others.
Abednego Feehi Okoe currently serves as the Pro Vice Chancellor, University of Professional Studies-Accra. A marketing professional, he holds a Doctorate of Business
Administration. His area of research covers branding, services marketing, strategic
marketing and consumer issues.
Thomas Anning-Dorson, PhD, works with the Department of Marketing and Entrepreneurship, University of Ghana Business School. His area of research covers
Competition, Innovation, Retailing, Service Management, and Emerging Markets.
478 H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478

Assessing the determinants of internet banking adoption intentions: A
social cognitive theory perspective
Henry Boateng a, *, Diyawu Rahman Adam b, Abednego Feehi Okoe c,
Thomas Anning-Dorson d
a School of Communication, University of Technology, Sydney, Australia
b Department of Marketing, Garden City University College, Kenyase, Kumasi, Ghana
c Department of Marketing, University of Professional Studies, Accra, Ghana
d Department of Marketing and Entrepreneurship, University of Ghana Business School, Legon, Ghana
a r t i c l e i n f o
Article history:
Received 5 March 2016
Received in revised form
4 September 2016
Accepted 8 September 2016
Available online 15 September 2016
Keywords:
Internet banking
Social cognitive theory
Online customer service
Online banking
Electronic banking
a b s t r a c t
Internet banking adoption is one area that has received attention from scholars. The extant studies have
mainly used technology acceptance models and behavioural theories which do not account for changes
in human behaviour. This study seeks to ascertain the determinants of Internet banking adoption intentions using the social cognitive theory, which accounts for changes in human behaviour. The study
selected the sample from bank customers in Ghana through an intercept approach using structured
questionnaires. A two stage-approach of confirmatory factor analysis and a structural equation modelling
were used in analysing the data. The findings show that websites’ social feature, trust, compatibility with
lifestyle and online customer services have a significant effect on customers’ intentions to adopt Internet
banking. However, ease of use did not have a significant relationship with customers’ intentions to adopt
Internet banking. The significance of the study as well as recommendations for theory, practice and
future studies have been discussed.
© 2016 Elsevier Ltd. All rights reserved.
1. Introduction
Several organizations in recent times have acted in response to
the competitive business environment by implementing e-business
as part of their business strategies (Chong, Ooi, Lin, & Tan, 2010).
One sector that has seen technological innovation both from the
end user and organizational perspectives is the banking sector.
Information Technology (IT) has helped the sector to offer individualized services and at the same time improve service delivery
(World Bank, 2003). Similarly, IT has contributed to innovation and
improved performance in the industry. Malhotra and Singh (2010),
for example, note that Internet banking has transformed the
banking industry worldwide. With the growth of the Internet, it is
to be anticipated that banks will move towards providing online
banking for their customers (Chong et al., 2010). Different academic
researchers have shed light on the reasons leading to Internet
banking adoption, and according to Giovanis, Binioris, and
Polychronopoulos (2012), among the most commonly accepted
approaches are the technology acceptance model (TAM) (Davis,
1989) and the innovation diffusion theory (IDT) (Rogers, 1995).
However, these theories have been criticized for various reasons.
Taylor and Todd (1995), for example, assert that TAM is too
simplistic and does not fully explain people’s understanding of
behavioural intention to adopt a technology and does not account
for the dynamic nature of human behaviour. The purpose of this
study is not to join this debate, but to offer an alternative model
that accounts for the dynamic nature of human behaviour in relation to intentions to adopt Internet banking. This study employs the
social cognitive theory (Bandura, 1989) which is able to explain and
account for the changing users’ behaviour towards technology and
its adoption (Ratten & Ratten, 2007).
Juwaheer, Pudaruth, and Ramdin (2012) note that the empirical
findings from user acceptance research suggest that when users are
presented with a new software package, a number of factors predict
their decision about how and when they will use it. Drawing
inspiration from the social cognitive theory, we argue that bank
* Corresponding author. University of Technology, Sydney, School of Communication, Building 10 level 5, 211.01, 15 Broadway, Ultimo NSW, 2007, Australia.
E-mail addresses: Henry.Boateng@student.uts.edu.au, hboateng@st.ug.edu.gh
(H. Boateng), adamsdeown@gmail.com (D.R. Adam), okoe67@yahoo.com
(A.F. Okoe), thomasdorson@gmail.com (T. Anning-Dorson).
Contents lists available at ScienceDirect
Computers in Human Behavior
journal homepage: www.elsevier.com/locate/comphumbeh
http://dx.doi.org/10.1016/j.chb.2016.09.017
0747-5632/© 2016 Elsevier Ltd. All rights reserved.
Computers in Human Behavior 65 (2016) 468e478
customers’ intention to adopt Internet banking is a function of
social features of website, trust, ease of use, compatibility with
lifestyle, online customer service. Following Mohammadi (2015),
this study defines intentions to adopt Internet banking as the
likelihood that an individual will use Internet banking services.
Dimitriadis and Kyrezis (2011)’s study on Internet banking stresses
the importance of intention to transact telephone banking. In the
work of Lee (2009), it was found that intention to use online
banking is a very important variable in Internet banking adoption.
Thus, the objective of this study is to model the factors explaining
the variations of intention to adopt Internet banking. This study
makes contribution to both theory and practice.
As indicated earlier, most studies on technology adoption and
Internet banking adoption have relied on the TAM, which is incapable/insufficient/incapacitated in explaining or accounting for the
dynamism in users’ behaviour towards technology and its adoption. This study addresses this gap as it is modelled on the social
cognitive theory, which is capable of explaining changes in human
behaviour (Bandura, 1989). It also contributes to technology
acceptance by showing the role of online customer service and
social features of a website in the context of intentions to adopt
Internet banking. Apart from these theoretical contributions,
identifying the variables that explain the variations in Internet
banking adoption intentions will help banks address the changing
needs of bank customers in an online environment. This study,
therefore, explains how the mode of Internet access can be a
boundary condition for Internet banking adoption.
The next section focuses on the theoretical background and
hypotheses development. This is followed by the methodology
used. The findings of the study are presented after that, while the
discussion of the findings follows subsequently. The conclusions,
implications, and limitations are contained in the last section.
2. Theoretical background
Social cognitive theory (SCT), as one of the most powerful theories of human behaviour (Bandura, 1986), serves as the theory for
this study. The primary argument of the SCT is that an individual’s
behavioural intention is a function of not only behaviour, but also of
cognitive personal and environmental factors. Cooper and Lu
(2016) argue that the basic precept of SCT is that behaviour is
regulated by the person through the cognitive processes, and by the
environment through external social situations. Bandura (1986)
promotes the triadic reciprocal determinism through (among)
personal attributes, such as internal cognitive and affective states
and physical attributes, such as external environment factors, and
overt behaviour.
An individual’s perception, beliefs, and expectations mould the
person’s behaviour. That is, how the individual thinks and feels is
associated with the person’s behavioural intentions (Bandura, 1986;
Benight & Bandura, 2004). The theory also implies that an individual’s abilities, knowledge, and skills affect/influence him or her
to engage in certain actions (Bandura,1989; Prussia & Kinicki, 1996).
Bandura (1989) also notes that an individual’s environment, that
is, the factors external to the individual, predicts the person’s
behaviour. This environment includes the physical and social
environment. The physical environment includes the natural and
manmade objects within an individual’s surroundings. The social
environment encompasses the immediate physical surroundings,
social relationships, and cultural milieus within which defined
groups of people function and interact’ (Barnett & Casper, 2001, p.
465). It also includes social norms, access within the community,
peer influence, values, etc. (Bandura, 1991). The social environment
has been conceptualized to include both the virtual and real world
(Narayan, 2013).
The other component of the SCT is behaviour. It is the way
people act or respond to a particular situation or object (Bandura,
1991). It also includes how people respond to technology or technological innovations (LaRose & Eastin, 2004; Ratten & Ratten,
2007). These three components or factors interact with each
other to predict an individual’s action. However, their predictive
capacity is not the same. Furthermore, their influences on each
other do not occur at the same time (Bandura, 1989).
The SCT has been employed in different disciplines, probably
because of its adaptive nature, as it considers human behaviour to
be dynamic (Kock, 2004). For example it has been used widely in
adoption of an e-government system (Loo, Paul, Yeow, & Chong,
2009; Rana & Dwivedi, 2015; Sahu & Gupta, 2007), task
complexity (Bolt, Killough, & Koh, 2001), organizational management (Wood & Bandura, 1989), technological innovation adoption
(Compeau & Higgins, 1999; Ratten & Ratten, 2007), tourism sustainability (Font, Garay, & Jones, 2016) and Internet uses and
gratifications (LaRose & Eastin, 2004). This theory has also been
employed as the theoretical framework to predict customers’ intentions to use computer systems (e.g. Compeau & Higgins, 1995;
Loo et al., 2009; Venkatesh, Morris, Davis, & Davis, 2003). However, it has rarely been used to study Internet banking adoption in
an emerging service context such as in Ghana.
Pincus (2004) asserts that the SCT is built upon the foundations
of individual and group psychological behaviour. Bandura (1986)
explain that this theory is used as a basis to examine the reasons
why individuals adopt certain behaviours. In the light of this and
recognizing the lack of empirical evidence of this model on bank
customers, this study examines the Internet banking adoption intentions of bank customers in the Ghanaian context. It is used in
this study to predict customers’ intentions to use Internet banking
because it explains how individuals’ actions are predicted by the
interaction of personal factors, environment, and behaviour. The
following facets of the theory are particularly relevant to this current study: the development of an individual’s social environment
and cognition, beliefs about the capabilities, personal factors and
motivation via goal system.
3. Research model
Following from the SCT, it is our argument in this study that an
adoption of a particular technology will be influenced by the development of an individual’s social environment and cognition, beliefs
about what the specific technology can offer, personal factors and
motivation through the persons’ goal systems. Therefore, we posit
that Internet banking adoption will be influenced by the social
characteristics of banks’ websites, the level of trust customers have
for the service delivery channel (website), the ease with which they
can navigate the service’s delivery processes on the website, how
compatible the delivery channel is with the customers’ lifestyle and
the overall service quality provided. We further argue that one key
boundary condition for the above adoption to take place in the
presence of the five antecedents is the medium of the Internet access.
Behavioural intentions such as technology adoption can be
influenced by the medium of access (the device used). In Internet
banking, several devices are available through which customers can
enjoy the benefits banks seek to offer. Therefore, the convenience
and enablement provided by Internet access devices can service as
a boundary condition for adoption. As the SCT explains how individuals make sense of social situations, we see the medium of
access as serving as a moderating condition for Internet banking
adoption. We consequently posit that the medium of Internet access will moderate the relationship between Internet banking
adoption and the five antecedents to adoption. Hence, the study
seeks to test the research model in Fig. 1.
H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478 469
4. Hypotheses development
4.1. Websites’ social feature
The social environment is a fundamental component of the SCT
(Bandura, 1991). As we have indicated earlier, the social environment involves the virtual world (Narayan, 2013). In this paper, we
expand the concept of the social environment to include websites’
social features (Park & Kim, 2014). Considering the fact that personal contacts and social interactions are key components of the
Ghanaian culture and communication (Alemna & Sam, 2006;
Hinson, Boateng, & Madichie, 2010), we argue that Internet banking
platforms with social features which enable customers to interact
with each other online relate positively with customers’ intentions
to use Internet banking. Rayport and Jaworski (2001) note that
website design and context are contributing factors to the success
of electronic commerce. Furthermore, studies have shown that
organizations that link their social media pages to their websites
are able to increase traffic to the website (Madichie & Hinson,
2014).
Website features are essential in determining the usage of a
website. Bashir and Madhavaiah (2015) broadly define a website
design as the layout, design, features and characteristics of the fully
transactional website of the bank. Alhudaithy and Kitchen (2009)
conclude that the Internet banking website serves as a platform,
where consumers continuously interact with the host bank and
thus easily perform a series of different banking activities. A website’s social features are defined in this paper as those features that
enable customers to interact and share experiences with fellow
customers. The uptake of Web 2.0 has affected the way most
websites are designed. The more interactive a website is, the more
people are drawn to the website (Kent & Taylor,1998). Some studies
have shown that a website’s sociability has the potential of
increasing traffic to the website and improving customer experience in a shopping environment (Preece, 2000; Sorooshian, Salimi,
Salehi, Nia, & Asfaranjan, 2013). Moreover, personal contacts and
social interaction are central to the lives of most customers in
Ghana (Alemna & Sam 2006; Hinson et al., 2010). Thus, we argue
that social feature of the Internet banking platform is associated
with individuals’ intentions to adopt Internet banking. Thus, we
hypothesize that:
H1. Websites’ social feature is associated with customers’ intentions to adopt Internet banking.
4.2. Trust
Social relationships are a central part of the social environment
in the SCT (Bandura, 1991). In every social environment involving
people and technology, trust becomes a critical issue. Todd (1998)
realized that one key concern of most Internet users is trust; that
is, trust in the service provider and the Internet service (Chai & Kim,
2010). Trust is said to help regulate social relationships between
people and minimizes uncertainty of human behaviour in certain
instances (Lee, Tsai, & Lanting, 2011). Thus, trust is a very vital
concept in Internet banking adoption (Lee et al., 2011) and even
more critical from the perspective of online business (Bashir &
Madhavaiah, 2015). Trust could be defined as the confidence that
an individual may have in the honesty and goodness of a person or
organization. In the context of Internet banking services Bashir and
Madhavaiah (2015) define trust as ‘the assured confidence a consumer has in the Internet banking service provider’s ability to
provide reliable services through the Internet’. Hanafizadeh, Byron,
and Khedmatgozar (2014b) cited Yousafzai, Foxall, and Pallister
(2010) who compared three models (TRA, TPB, and TAM) on
Internet banking adoption with their result emphasizing the
importance of trust. In their work on mobile banking adoption in
Iran, Hanafizadeh, Behboudi, Khoshksaray, and ShirkhaniTabar
(2014a) found that trust was one of the noteworthy antecedents
that explain mobile banking’s adoption in Iran. Lee et al. (2011) and
Liebana-Cabanillas, Mu noz-Leiva, and Rej ~ on-Guardia (2013) in
their study on consumer online banking switching and determinants of satisfaction with e-banking respectively found that
trust is a major determinant of customers’ switching intentions to
Internet banking. Akhlaq and Ahmed (2013) provide further evidence that supports the fact that trust has an effect on Internet
banking adoption in a low-income country context. Based on these
studies, we argue that customers’ trust in the Internet as a secure
platform to conduct banking transactions will affect customers’
intentions to adopt Internet banking. Therefore:
H2. Trust is associated with customers’ intentions to adopt
Internet banking.
4.3. Ease of use
Functioning infrastructures are essential elements of a social
environment, which is associated with an individual’s behaviour
(Barnett & Casper, 2001). In this case, the internet banking platform
Fig. 1. Research model.
470 H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478
can be said to be a central component of the social environment.
The effort required by users to use this platform can affect their
usage intentions (Davis, 1989). A number of essential components
of a website have been proposed by Gibson (2003) to be in place in
spite of the type of business. The author mentions simple website
navigation, fast image download time and fast access to information as those components. This suggests that the ease at which a
customer can use Internet banking is associated with the customer’s intention to use same. Based on the Technology Acceptance
Model, most extant studies have found that ease of use of technology predicts people’s intention to adopt technology (For e.g.
Jaruwachirathanakul & Fink, 2005; Yu, Balaji, & Khong, 2015).
Ease of use is the degree to which the prospective adopter expects the new technology adopted to be a free effort regarding its
transfer and utilization’ (Davis, 1989). Ease of use is defined in this
study as how easy a customer can learn and use Internet banking
services. Jaruwachirathanakul and Fink (2005) discovered the
facilitating and inhibiting factors for adoption of Internet banking
in Thailand. It is further suggested that ease of use is a key factor for
successful Internet banking adoption (Yu et al., 2015). The result of
the study conducted by Bashir and Madhavaiah (2015) in accordance with TAM, suggests that perceived ease of use has a strong
positive effect on Internet banking adoption. Thakur (2014),
Schierz, Schilke, and Wirtz (2010) postulate that perceived ease of
use has been demonstrated to have an effect on attitude. Ease of use
was found to successfully explain the adoption of mobile banking
among Iranian clients (Hanafizadeh et al., 2014a). In a study conducted by Mohammadi (2015), ease of use is identified as an
influential factor and underscores its importance in mobile banking
usage. Liebana-Cabanillas et al. (2013) in their study of the determinants of satisfaction with e-banking established that ease of
use is a determinant of Internet bank usage.
Some studies have, however, noted that there is no relationship
between perceived ease of use and technology adoption and have
thus questioned the overall impact of perceived ease of use in TAM
(Lee, Kozar, & Larsen, 2003; Tiainen, Kaapu, & Ellman, 2013). The
contradictory findings have been explained by gender differences
in user behaviour (Tiainen et al., 2013). Some researchers have
attributed this to what they have termed as the negative cycle of
technology adoption where competences in a particular technology
discourages a person from learning a new technology (Straub,
2009; Tiainen et al., 2013). Nonetheless, in this study ease of use
is expected to have an effect on Internet adoption. Therefore, we
argued that:
H3. Ease of Use is associated with customers’ intentions to adopt
Internet banking.
4.4. Compatibility with lifestyle
According to the SCT, personal factors are key components in
determining human actions (Bandura, 1986). Lerner (1982) notes
that individuals’ personal factors such as age, size, gender, lifestyle,
etc. interact with their social environment to inform their behaviour. Rogers (1995) notes that some people accept an innovation if it
is compatible with their lifestyle. In this case, we argue that
compatibility of an individual’s lifestyle with Internet banking is
associated with the person’s intention to use Internet banking.
Compatibility in this study refers to the situation in which
customers perceive a product or service as relevant to their actions,
ways of thinking and their lifestyle. Hernandez and Mazzon (2007)
suggest that compatibility refers to the degree to which people
perceive that a particular technology is well-matched with the way
they think, act and lead their lives. Chen (2013), and Wessels and
Drennan (2010), in their studies on the factors facilitating and
obstructing the adoption of mobile banking, indicate that
compatibility significantly affects the adoption of mobile banking.
Hanafizadeh et al. (2014b) conclude that the perceived difficulty of
using computers combined with a lack of personalized service is
the most significant barrier to Internet banking adoption among
these customers. Mohammadi (2015) added that ‘the greater the
compatibility of mobile banking with users’ other bank accounts,
the more positive is their attitudes towards it’. Compatibility with
lifestyle was also found to be one of the most significant antecedents explaining mobile banking adoption (Hanafizadeh et al.,
2014a). Consequently, we hypothesize that:
H4. Compatibility with lifestyle is associated with customers’ intentions to adopt Internet banking.
4.5. Online customer services
Drawing inspiration from the virtual social environment
(Narayan, 2013) helps extend the contextual aspect of the SCT
(Bandura, 1986). Since online customer service is important to
some customers in electronic commerce transactions (Avkiran,
1994), we argue that the Internet banking platform with online
customer service features is associated with customers’ intention to
use Internet banking services. Customer service has been an integral part of the service delivery of many traditional organizations as
well as banks. It is normally used to solve, or reduce to the barest
minimum, problems of customers. With the traditional brick and
mortar, customer service is usually rendered at the desk, call centres, automatic call systems etc. Extension of customer service
online could serve as a great bargain, as online customer service has
become an essential part of success for companies conducting
business on the web (Gibson, 2003). Avkiran (1994) had earlier
suggested that customer service quality is expected to be a major
determinant of the performance of banks. Bernett (2000) concludes
that customer service is as essential in the virtual store as it is in the
traditional ‘brick and mortar’ store. There is evidence that suggests
that a substantial number of online shoppers abandon their
transactions because of frustration and lack of assistance from
online retailers (Allen, 2000). Dealing with these problems, Barnes
and Cumby (2002) recommend that electronic commerce companies should ensure that online shoppers get help online and feel
close to the electronic commerce company. In this study, it is
argued that an Internet banking platform where staff welcome and
offer help to the customer to perform his or her transactions
(Avkiran, 1994) has the potential of affecting Internet banking
adoption. Thus we hypothesize that:
H5. Online customer services are associated with customers’ intentions to adopt Internet banking.
4.6. Moderated variable: medium of internet access/device
Several objects such as ‘infrastructure, industrial and occupational structure; labor markets; social and economic processes, etc.
can be found in an individual’s social environment’ (Barnett &
Casper, 2001, p. 465). These objects in totality and with the social
environment are associated with human behaviour (Bandura,
1986). In this view, it can be argued that the device or medium
through which users access the Internet banking is associated with
an individual’s intentions to adopt Internet banking. Some studies
have shown the medium through which access to electronic services affects their usage intentions. Nielsen (1999) for example
noted ‘a bigger screen leads to better usability than a small screen
and that a graphical user interface adds, even more, usability’. This
H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478 471
study considers the medium as a key environmental factor that can
affect the relationship between the cognitive dimensions and the
behavioural outcome. We, therefore, expect the medium of usage to
serve as a boundary condition, which shapes the effect of the
cognitive variables and intention to adopt mobile banking. Chong
et al. (2010) assert that with the increase in asynchronous and
secured electronic transaction technologies, more banks are now
making use of online banking. Electronic devices such as mobile
phones, PDAs (Personal Digital Assistants), laptops, etc. have made
Internet banking accessible for students. This has made it possible
for registered Internet banking users to perform certain banking
transactions like transferring funds, paying bills, printing statements as well as checking account balances among others (Chong
et al., 2010; Mohammadi, 2015). Even though Internet banking
works the same way as traditional banking (Chong et al., 2010) the
convenience characteristics of mobile technologies (mobile phones,
PDAs, smart phones), computers, etc. provide an extraordinary
potential solution to the financial access problem faced by customers in emerging economies such as Ghana (Asongu, 2015; Beck,
Senbet, & Simbanegavi, 2015; Tobbin, 2012). Mobile phones are
also important mechanisms by which young people connect with
others and enhance their self-esteem (Ruleman, 2012; Xie, Zhao,
Xie, & Lei, 2016). Moreover, Internet users in most developing
countries like Ghana access the Internet using the mobile phone.
According to the Social Cognitive theory (Bandura, 1986), an individual’s behavioural intentions or behaviour is as a result of the
interaction among cognitive and other personal factors and an individual’s environmental factors. Thus, we argue that the type of
device that a customer uses to access the Internet and its interaction with websites’ social feature, with trust, ease of use, compatibility with lifestyle and with online customer service help to
explain the variance in Internet banking adoption. Based on this
premise, we propose the following hypotheses:
H6a. Type of device used to access the Internet moderates the
relationship between websites’ social feature and Internet banking
adoption intentions.
H6b. Type of device used to access the Internet moderates the
relationship between trust and Internet banking adoption
intentions.
H6c. Type of device used to access the Internet moderates the
relationship between the ease of use and Internet banking adoption
intentions.
H6d. Type of device used to access the Internet moderates the
relationship between compatibility with lifestyle and Internet
banking adoption intentions.
H6e. Type of device used to access the Internet moderates the
relationship between online customer service and Internet banking
adoption intentions.
4.7. Sampling design and data collection
The respondents of the study consisted of bank customers in
Ghana. There is no updated record or data on bank customers in
Ghana. Therefore, this study sought to use an intercept approach to
capture an adequate sample for this study. Although this approach
is sometimes criticized for its inadequacy in supporting the
generalization of research findings (Trochim & Donnelly, 2008, pp.
144e145), the features of the sample used, the setting and the
procedure we employed for the data collection and analysis
confirm the external validity of the results (Landers & Behrend,
2015). In an intercept approach, potential respondents in data
collection are intercepted (captured/seized/interrupted) before or
after patronizing a particular product or service (Anning-Dorson,
Kastner, & Mahmoud, 2013; Bush & Hair, 1985). This approach allows the researcher to have direct access to the intended respondents and it also helps in the evaluation of the service since
issues under consideration will have been fresh on their minds. In
this study, permission was sought from branch managers of banks
after the study objective had been explained, and respondents were
intercepted as they finished their transaction with the bank.
Selected branches within the capital city of Ghana were chosen to
be part of this study. Since the youth have been identified to be
technology savvy, we decided to focus on bank customers from 20
to 49 years. This age bracket is consistent with those used in similar
studies (see Hernandez, Jim enez, & Martín, 2011; Wang, Minor, &
Wei, 2011). The demographic data of the 600 respondents reflect
the youth and bank customers in Ghana. Most (51.5%) of them were
males whereas (48.5%) were females. Furthermore, most (52.5%)
were within the age 30e39 years. Those from 20 to 29 years
accounted for 27.5% while those from 40 to 49 years constituted
20%. A good number (53.5%) had been banking for more than 19
years, 30.5% had been banking for 10e19 years and 16% had been
banking for 1e9 years. Again, 96.7% had access to the Internet,
while 3.3% did not. Most (80.3%) of them accessed the Internet
using their mobile phones, while 14.0% accessed the Internet using
computers. Similarly, 4.3% accessed the Internet using tablets and
those who used other devices constituted 1.3%. Moreover, a good
number (45.5%) of the respondents had intermediate skills in
Internet usage, 29.0% considered themselves as beginners and
25.5% had advanced skills in Internet usage. Since the respondents
were not ready to disclose their account balance, we decided to
exclude that from the final analysis. Table 1 contains the demographic data of the respondents.
To expedite the data collection, we trained fourth-year undergraduate students to assist in the data collection. They contacted
some of the respondents through an intercept approach in front of
Table 1
Respondents’ demographic data.
Demographic variable Frequency(N) Percentage (%)
Gender
Male 309 51.5
Female 291 48.5
Total 600 100
Age (in years)
20e29 165 27.5
30e39 315 52.5
40e49 120 20.0
Total 600 100
Number of years in banking
1e9 years 96 16.0
10e19 years 183 30.5
20 years and above 321 53.5
Total 600 100
Access to the internet
Yes 580 96.7
No 20 3.3
Total 600 100
Medium/device use to access the internet
Mobile phone 481 80.3
Computers 84 14.0
Tablets 26 4.3
Other devices 9 1.3
Total 600 100
Internet usage literacy
Beginner 174 29.0
Intermediate 273 45.5
Advanced 153 25.5
Total 600 100
472 H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478
banking halls of banks branches in Accra, (the capital of Ghana).
Accra was chosen due to the central role it plays in the economic
and commercial affairs of the Ghanaian economy. The city hosts
headquarters of all banks and is a key economic hub within the
West-Africa sub-region. In 2008, the World Bank estimated that
Accra’s economy alone constituted around US$3 billion of Ghana’s
total gross domestic product (GDP), which is about 20% of the
overall GDP (World Bank, 2008). In the same report, the city also
hosts the largest chunk of the economically active population.
Two branches of banks that have been operating in Ghana for at
least the past 5 years were selected based on the volume of traffic at
the branches. The intention was to capture diverse sets of customers to evaluate the measures for our study. It took one month
(SeptembereOctober 2015) for us to complete the data collection
that involved a total questionnaire of 1000. At the end of the data
collection, we had 600 usable questionnaires, which were used in
the final analysis. To ensure that non-response bias was not a
problem for our study, we followed the recommendations of
Armstrong and Overton (1977) for a response bias test. The filled in
questionnaires returned after the first week and those returned
after the last week of the study were compared. The group means of
these two groups were not significantly different, hence a nonresponse bias was not considered a problem for this study.
5. Measures
The instruments measuring the constructs were adapted from
the extant literature. The items and their sources have been presented in Table 2. The items were measured on a Likert scale using;
1 ¼ strongly disagree, 2 ¼ disagree, 3 ¼ neutral, 4 ¼ agree and
5 ¼ strongly agree. However, the scale measuring the item ‘I think
that Internet banking would be difficult to use’ was reversed coded
during data entry because the question was in a negative form.
5.1. Reliability and validity test
Since all the items measuring the constructs were adapted, we
performed a confirmatory factor analysis to assess the adequacy of
the items. To test the reliability and validity of the measures, the
study used Amos 20 and the maximum likelihood estimation
procedure to examine all scales in a CFA. An exact model fit was
assessed using a chi-square (c2) test. Following Bagozzi and Yi
(2012), a number of approximate fit heuristics were also examined to provide additional information on model fit and the indices
ranged from good to very good. The results showed adequate fit for
the proposed model; c2/df (374.712/174) ¼ 2.154, p < 0.001,
CFI ¼ 0.952, TLI ¼ 0.937, IFI ¼ 0.916, NFI ¼ 0.916 and
RMSEA ¼ 0.044.
Additionally, the adequacy of the measurement model was
ascertained using internal consistency, convergent validity, and
discriminant validity tests. The composite validity test was used to
measure the internal consistency of the constructs. As shown in
Table 2, all the composite reliability values (a) were above the cutoff point of 0.7 (Hair, Black, Babin, Anderson, & Tatham, 2006).
Furthermore, as captured in the diagonals of Table 3, all the values
for the average variance extracted (AVE) were higher than the
squared correlations among the constructs and above the acceptable threshold of 0.5 (Fornell & Larcker, 1981). Moreover, the factor
loadings of the items were above the acceptable value of 0.7 and
there were no cross-loadings (Bagozzi & Yi, 2012; Hair et al., 2006).
Similarly, as shown in Table 3, all the correlation matrices were
below 0.9 (Vance, Lowry, Moody, Beckman, & Read, 2008). The
overall implications of these results are that there is adequate
convergent and discriminant validity and there is no issue with
common method bias (Bagozzi & Yi, 2012; Fornell & Larcker, 1981;
Vance et al., 2008).
5.2. Analysis of model and hypotheses testing
We tested two models, models 1 and 2 using the Structural
Equation Model (SEM). Model 1 measured the association between
the predictor variables (Website social features, trust, ease of use,
compatibility with lifestyle and online customer service) and the
outcome variable (Internet banking adoption intentions). In model
Table 2
Composite validity test.
Constructs Estimate t-values
Social feature (Park and Kim, 2014) a ¼ 0.85
Chatting with other customers online will enrich my internet banking experience 0.860 Fixed
Social aspects of internet banking is important to me 0.780 14.617
I will enjoy conversational interaction on internet banking platform 0.806 15.073
Overall, I will adopt internet banking if there is a social feature 0.767 12.367
Trust (Hanafizadeh et al.,2014a,b) a ¼ 0.79
I would trust my bank to offer secure internet banking 0.709 Fixed
Using internet banking would not divulge my personal information 0.792 12.071
I would find internet banking secure in conducting my transactions 0.675 10.726
I would find internet banking secure in requiring and receiving other information, e.g. bank statements 0.712 11.203
Ease of use (Hanafizadeh et al.,2014a,b) a ¼ 0.78
Learning to use internet banking would be easy 0.796 Fixed
I think that internet banking would be difficult to use (R)* 0.893 10.525
I think it would be simple for me to become skilled at using internet banking 0.692 10.296
Compatibility with lifestyle (Hanafizadeh et al.,2014a,b) a ¼ 0.87
Using internet banking would fit my lifestyle 0.812 Fixed
Using internet banking would fit well with how I like to do my banking 0.891 16.613
Using internet banking would be compatible with most aspects of my banking activities 0.880 16.470
Online customer services (Avkiran, 1994) a ¼ 0.86
I will like to be welcomed when I visit my bank’s website for internet banking 0.812 Fixed
I will like a staff to help me online when using internet banking 0.893 16.809
I will like to have easy access to a staff online when using internet banking 0.734 13.882
Overall, I will like online customer service when using internet banking 0.825 15.673
Intention to adopt (Hanafizadeh et al.,2014a,b) a ¼ 0.84
When you have banking to do, how likely are you to use internet banking? 0.871 Fixed
To the extent possible, I would take advantage of the internet for my banking activities 0.893 17.544
I predict that I would use Internet banking 0.785 15.458
H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478 473
2, we tested the moderation role of the medium in the relationship
among the predictor variables and the outcome variable.
We employed the goodness-fit indices, R2 value and a path coefficient in ascertaining the adequacy of the Structural Equation
Model. The goodness-fit indices for model 1 are as follows; c2/df
(374.712/174) ¼ 1.99, p < 0.001 and the R2value was 0.328. Since
our model was not one of predictive, the relatively low R2 does not
affect our results as low R2 can be a counterbalance to our large
sample size (Hair et al., 2010). Four out of five of the path coefficients were significant. The coefficient path that was not significant was the relationship between ease of use and Internet
banking adoption intentions (b ¼ 0.026, p ¼ 0.507) (see Table 4).
This suggests that hypotheses H3 was not supported.
As proposed, web social features significantly explained the
variation in Internet banking adoption intentions (b ¼ 0.131,
p < 0.001) confirming hypothesis one (H1). Similarly, trust was
significantly associated with Internet banking adoption intentions
(b ¼ 0.105, p ¼ 0.01) supporting hypothesis two (H2). Additionally,
there was a significant relationship between compatibility with
lifestyle and Internet banking adoption intentions (b ¼ 0.171,
p < 0.001) and online customer service and Internet banking
adoption intentions (b ¼ 0.302, p < 0.001) (see Table 4). These
findings support hypotheses four and five (H4 and H5).
5.3. Testing moderation
One way of assessing the moderation effect in SEM, which has
been widely used in management literature, is the multiplicative
approach (see Little, Bovaird, & Widaman, 2006; Boso, Story, &
Cadogan, 2013; Anning-Dorson, 2016). SEM, through a multiplicative approach, was used to analyse the moderating effect relationships. Since this study sought to analyse the effect medium
could have on the relationship between our independent variables
and internet banking adoption intentions, we multiplied each independent variable by medium to assess whether the effect will be
significant or not. Since our intention was to set medium as a
condition for better interpretation of how our independent variables relate with internet banking adoption intentions, the interaction approach offered the best option to achieve our research
objective. Unlike mediation tests, a condition of an intervening
variable relating significantly to the independent variable does not
exist in moderation. Therefore, medium and our independent variable could be interacted to create single indicants for our moderation test. We specifically followed Ping (1995) to create single
indicants for each variable involved in multiplicative interactions,
as these single indicants help reduce model complexity. As a
mitigation measure against possible multicollinearity problems
due to the usage of interactive terms, all measures involved in
multiplicative interactions were mean-centred, as suggested by
Little et al. (2006). The single moderation indicants were therefore
entered into our initial model (model 1) and were then run. To
improve the model fitness of the moderation model, all independent variables were allowed to correlate with each other as such
practice helps improve model fitness (Byrne, 2013). The model 2,
which was used to assess the moderation hypotheses, fit the data
well. The model showed good model-fit indices; c2/df (17.086/
9) ¼ 1.898, p < 0.001, CFI ¼ 0.993, TLI ¼ 0.971, IFI ¼ 0.993,
NFI ¼ 0.985 and RMSEA ¼ 0.039 and therefore could be used to
interpreted the hypothesized moderation relationships. The R2
value was 0.289. With the exception of the interaction between
trust and medium on Internet banking adoption intentions
(b ¼ 0.045, p ¼ 0.330); and ease of use and medium and Internet
banking adoption intentions (b ¼ 0.003, p ¼ 0.936), the rest of the
path coefficients were significant (see Table 5). Based on these results, hypotheses H6b and H6c were not supported.
The path coefficient for interaction between social features of
website and medium on Internet banking adoption intentions was
significant (b ¼ 0.150, p < 0.001). Similarly, the interaction between
compatibility with lifestyle and medium on Internet banking
adoption intentions (b ¼ 0.145, p ¼ 0.002) and online customer
service and medium on Internet banking adoption intentions were
significant (b ¼ 0.319, p < 0.001) (see Table 5). Consequently, hypotheses H6a, H6d and H6e, were supported.
6. Discussion and conclusions
This study aimed at testing hypotheses on the effect of websites’
social feature, trust, compatibility with lifestyle and online
Table 3
Discriminant validity test.
Mean SD 1 2 3 4 5 6 7 8 9
1. Gender 1.49 0.500 e
2. Access to internet 1.03 0.180 0.106** e
3. Medium 1.27 0.603 0.121** 0.157** e
4. Social feature 3.4702 0.84556 0.061 0.068 0.052 (0.6)
5. Trust 3.5801 0.77958 0.013 0.059 0.106** 0.447** (0.54)
6. Ease of use 3.3215 0.62928 0.027 0.091* 0.049 0.265** 0.376** (0.57)
7. Compatibility with lifestyle 3.6414 0.84203 0.090* 0.078 0.086* 0.423** 0.523** 0.395** (0.71)
8. Online customer services 3.9013 0.78698 0.014 0.080 0.117** 0.379** 0.383** 0.392** 0.487** (0.69)
9. Intention to adopt 3.7011 0.82987 0.009 0.116** 0.160** 0.379** 0.390** 0.294** 0.450** 0.499** (0.68)
Variances extracted are on the diagonal; correlation off diagonal. ***p < 0.001; **p < 0.01; *p < 0.05 significance levels.
Table 4
Regression (model 1).
Structural path Estimate p-values
H1 Internet adoption)SF 0.131 ***
H2 Internet adoption)TT 0.105 0.014
H3 Internet adoption)EOU 0.026 0.507
H4 Internet adoption)CML 0.171 ***
H5 Internet adoption)OCS 0.302 ***
NB: SF ¼ Social feature; TT ¼ Trust; EOU ¼ Ease of use; CML ¼ Compatibility with lifestyle; OCS ¼ Online customer services. ***p < 0.001; **p < 0.01; *p < 0.05 significance
levels.
474 H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478
customer services on Internet banking adoption intentions. It also
assessed whether the type of device/medium of access moderates
these relationships. As indicated earlier, SEM was used to test these
association hypotheses.
The findings indicate that web social feature significantly
explained the variation in Internet banking adoption intentions
(b ¼ 0.131, p < 0.001). The interactive nature of the Internet banking
platform has the potential of facilitating conversations among
customers. In this era that customers have come to accept social
interactions on the Internet, incorporating social features to
Internet banking platforms can attract most customers to adopt
internet banking. Social interactions are a part of a traditional
Ghanaian society and this is evidenced in how customers interact
with each other and with employees in the banking halls. Hence
any technological innovation that would seek to enhance that social
aspect of a Ghanaian customer is likely to be adopted. The web
social feature becomes a tool to transfer their interactive nature
from the real traditional setting to the virtual world. This is
confirmed by Alhudaithy and Kitchen (2009) who found that a
bank website serves as a platform where consumers continuously
interact with the host bank and thus easily perform a series of
different banking activities. The social feature of the website makes
it possible for consumers to adopt Internet banking. It can, therefore, be said that the social environment relates closely with consumers’ intentions to adopt internet banking.
The analysis of data also revealed that trust was significantly
associated with Internet banking adoption intentions (b ¼ 0.105,
p < 0.05). This means that trust plays a key role in Internet banking
adoption. Trust is the central element of a social environment. It
reduces uncertainty among individuals in a social setting (Lee et al.,
2011). From the perspective of online business, Bashir and
Madhavaiah (2015) underscore the importance of trust. In a society where unsuspecting people hide behind companies and take
advantage of emerging technologies to defraud customers, customers become more interested in how their investments become
secure. Customers must necessarily trust the technological service
being rendered before patronizing it. Customers trust their banks to
deliver secured services as well as to protect their personal information. Hanafizadeh et al. (2014a) found that trust was one of the
noteworthy antecedents within the social environment that
explain mobile banking adoption in Iran. When transacting business, customers expect secure online transactions.
Moreover, the findings from the analysis disclosed a significant
relationship between compatibility with lifestyle and Internet
banking adoption intentions (b ¼ 0.171, p < 0.001). Customers
favour Internet banking platforms where the service offered fits
their lifestyle. Technology, and technology-based innovations have
become trendy among some Ghanaians (Dzogbenuku, 2013). As a
result, customers are willing to patronize Internet banking insofar
as they see it as trendy; especially those who are technology savvy.
The implication is that when banks are able to develop internet
banking platforms that enhance their lifestyle, there is higher
chance of increased adoption. Using Internet banking should
necessarily be harmonious with how customers do most of their
banking activities. This is in line with the work of Wessels and
Drennan (2010) who indicated that compatibility significantly affects the adoption of mobile banking. Compatibility with lifestyle
was also found to be one of the most significant antecedents
explaining mobile banking adoption by Hanafizadeh et al. (2014a).
In sum, this finding is in conformity with Lerner’s (1982) assertion
that individuals’ behaviour are among others, a result of an interaction of personal factors such as age, gender, lifestyle etc. with
their social environment.
It was also revealed by the analysis that online customer service
plays a major role in customers’ Internet banking adoption
(b ¼ 0.302, p < 0.001). Online customer service has been found by
bank customers to be a critical factor in their decision to adopt
Internet banking. This suggests that customers cherish online
customer service as it makes it possible for the bank to provide help
when the need arises. As a custom in most banks in Ghana, there is
customer service personnel who normally welcome customers to
the banking hall, handle complaints and assist them to perform
their transactions. These practices make customers, as well as
prospective customers, feel a sense of belongingness especially
when their problems or inquiries are adequately attended to.
Customer service has become indispensable in the banking sector
and thus must be transferred onto the virtual world. Allen (2000)
found evidence that suggests that a substantial number of online
shoppers abandon their transactions because of frustrations and
lack of assistance from online retailers. Avkiran (1994) shared the
opinion that where a staff welcomes the customer to the Internet
banking platform, as well as offer help, it potentially affects Internet
banking adoption. Their finding, therefore, confirms the role of
online social environment in influencing customers’ behaviour intentions (Raza & Standing, 2010).
Physical infrastructures are key elements of a social environment. The efforts that an individual must apply to use these infrastructures is associated with their behavioural response towards
such infrastructure (Barnett & Casper, 2001). Hence, we proposed
that there is a relationship between ease of use and Internet
banking adoption. However this study found a non-significant
relationship between ease of use and intentions to adopt Internet
banking. This is probably because the respondents in this study are
more knowledgeable about Internet usage in general and therefore
do not have the feeling that Internet banking will be any different.
Since there may be existing knowledge about similar Internet
platforms, the non-significant relationship found can be attributed
to prior knowledge. Studies such as Straub (2009) and Tiainen et al.,
(2013) have found such prior knowledge as an explanatory variable
for non-significant relationship between ease of use and intention
to adopt. The implication is that banks must assess the level of
existing knowledge about similar technologies as such knowledge
may moderate the ease of usage and intention to adopt. The level of
customer competence in similar technologies can be an enabler or
an obstacle to using Internet banking service.
The study also found that type of device used to access the
internet moderates the relationship between websites’ social features and customers’ intention to adopt internet banking. For
instance, if a device such as a mobile phone or a laptop allows easy
access to social applications and interaction with a customer service agent online, customers are more likely to adopt internet
banking. Studies from the literature (Tobbin, 2012; Weisskirch,
2011) conclude that the convenience characteristics of mobile
technologies provide an extraordinary potential solution to the
financial access problem faced by customers, thus confirming this
finding.
In contrast, however, the study found that the type of device
Table 5
Regression (model 2).
Structural path Estimate p-values
Internet adoption)SF_Medium 0.150 ***
Internet adoption)TT_Medium 0.045 0.330
Internet adoption)EOU_Medium 0.003 0.936
Internet adoption)CML_Medium 0.145 0.002
Internet adoption)OCS_Medium 0.319 ***
R2 ¼ 0.289.
NB: SF ¼ Social feature; TT ¼ Trust; EOU ¼ Ease of use; CML ¼ Compatibility with
lifestyle; OCS ¼ Online customer services. ***p < 0.001; **p < 0.01; *p < 0.05 significance levels.
H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478 475
used to access the internet does not moderate the relationship
between trust and customers’ intention to adopt internet banking.
This finding is in contrast to several findings in the literature which
have concluded that trust is a vital concept in internet banking
adoption and more critical from the perspective of online business
(Yildirim & Zeren, 2015; Lee et al., 2011). It can, however, be said
that type of device for access does not moderate the relationship
between trust and customers’ intention to adopt internet banking,
because customers are more likely to use their personal devices,
considered as more trustworthy, for online banking.
Again it was found that type of device used to access the Internet
did not moderate the relationship between ease of use and Internet
banking adoption intentions. On the other hand, there are studies
that indicate that ease of use of a device can facilitate or inhibit the
adoption of Internet banking (Bashir & Madhavaiah, 2015;
Jaruwachirathanakul & Fink, 2005; Yu et al., 2015). It is expected
that a mobile device’s screen size, for example, should be important
to most Internet users. This finding may be attributable to the fact
that customers in this study context used their personal devices
and this carries an implicit trust in these devices. It is also important to note that there is no significant relationship between ease of
use and customers’ intention to adopt internet banking.
The study found that type of device used to access the internet
moderates the relationship between compatibility with lifestyle
and customers’ intention to adopt internet banking. As indicated by
Hernandez and Mazzon (2007), compatibility refers to the degree
to which people perceive that a particular technology is well
matched with the way they think, act and lead their lives. In this
respect, individuals consider the type of device they use as either
inhibiting or facilitating the adoption of internet banking.
It was found that the type of device used to access the internet
moderates the relationship between online customer service and
internet banking adoption intentions. For an online customer service to be effective, certain essential components are required,
including single website navigation, fast image download times,
and fast access to information (Gibson, 2003). This may explain why
the type of device used moderates the relationship between online
customer service and customers’ intention to adopt.
The study has expanded our understanding of factors that
explain the variations in people’s intentions to adopt Internet
banking. It also implies the need for banks, electronic commerce
companies, and corporate website designers to consider incorporating social features such as those that allow customers to recognize and interact with each other as they transact business online.
Although most bank websites and other e-commerce websites have
chat features, this phenomenon is not common in developing
countries like Ghana. In situations where they exist, this feature is
limited to the interaction between a customer and a service provider. Again, banks must consider offering customer service online
just as it happens in real-time. This will reduce the rate at which
online customers abandon their transactions. Also, banks should
instil trust and confidence in their customers in terms of protecting
their finances, financial information, and personal details. Again,
they should build a secure Internet banking systems in order to
encourage Internet banking adoption.
This study has some limitations, but these limitations do not
render the findings invalid. Firstly, the study does not measure
actual adoption of Internet banking. However, it is the actual usage
that can inure to the profitability of the banks. Therefore, future
studies should considering using these models to study actual
adoption of Internet banking. Again the study did not specifically
consider the moderating role of individual mediums of Internet
devices. Future studies can consider researching into the moderating role of specific Internet devices.
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Henry Boateng is currently a PhD student at the University of Technology, Sydney. His
research experience covers Customer Knowledge Management, Electronic business
and Commerce and Internet application in marketing. He can be reached at: Department of Marketing and Customer Management, University of Ghana Business School, P.
O. Box LG 78, Legon, Ghana.
H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478 477
Diyawu Rahman Adam holds an Mphil Degree (Marketing). He is currently a lecturer
at Garden City University College, Kenyase-Kumasi. His research interest include:
customer orientation, e-banking, e-business and financial service marketing among
others.
Abednego Feehi Okoe currently serves as the Pro Vice Chancellor, University of Professional Studies-Accra. A marketing professional, he holds a Doctorate of Business
Administration. His area of research covers branding, services marketing, strategic
marketing and consumer issues.
Thomas Anning-Dorson, PhD, works with the Department of Marketing and Entrepreneurship, University of Ghana Business School. His area of research covers
Competition, Innovation, Retailing, Service Management, and Emerging Markets.
478 H. Boateng et al. / Computers in Human Behavior 65 (2016) 468e478

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