Factors influencing the adoption of electronic banking in vietnam

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Development | 359

Factors Influencing the Adoption
of Electronic Banking in Vietnam
PHAN THUY KIEU
International University - Vietnam National University Ho Chi Minh City

NGUYEN DINH KHOI
International University - Vietnam National University Ho Chi Minh
City

PHAM THI BICH UYEN
International University - Vietnam National University Ho Chi Minh
City

NGO DANG HOAN THIEN
International University - Vietnam National University Ho Chi Minh
City

Abstract
The paper mainly adopts the extension of the theory of reasoned action from
prior studies. The first version modifies Technology Acceptance Model with
Decomposed Theory of Planned Behavior and Perceived Risk in which eight
constructs including Actual Usage, Behavioral Intention, Attitude toward using,
Perceived Behavioral Control, Subjective Norm, Perceived Usefulness, Perceived
Ease of Use, and Perceived Risk are used to examine which constructs directly
influence the adoption of electronic banking by individuals in Vietnam. After
analyzing 405 valid questionnaires with SPSS and AMOS software version 20, the
study, developed based on two common models of behavioral studies, shows that
seven out of eight hypotheses are significant to the direct relationship between

intention and attitude. In addition, Perceived Risk is considered a barrier factor of
using e-banking. The paper also suggests the groundwork for further studies in
Vietnam.

Keywords:

electronic banking; traditional banking; tra; tam; tpb; perceived risk; Vietnam


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1. Introduction
One of the most important phenomena of this age is revolutionizing of
traditional banking through the developing of electronic communication
and access of huge individuals to the Internet. The rapid technological
progress and development in the global financial market (Ozuru, 2010;
Jonhson, 2005) has led to a new chapter on today’s trend in the banking
industry. Telecommunication and technological innovations allow banks
approach their customers and provide them with not only general
information but also the chance to experience interactive retail banking
transactions. With the convenience and efficiency, e-banking has become
an important channel to sell products and services, where customers do
not need to queue up and even suffer their constrained manner contacted
to make the bank due to offering “anytime, anywhere” banking facilities
(Lassar et al., 2005). Serving customer without the need of frontline staffs
while banks benefits from staff reduction, lesser branch sizes and paperrelated works (Tan and Teo, 2000) are the great main motivation to use the
online banking (Bruno, 2003).
Today, personal service and convenience are still the critical factors in
the banking relationship, but they are defined differently. Consumers still
want to bank with a financial institution, but they do not necessarily want

to go to the bank. They are utilizing computers and technology. They are
now comfortable with personal computers and other electronic devices.
They expect fast, efficient, and accurate service and the only way to cost
effectively provide the instant, quality service that customers demand. For
all these reasons, the banks delivery systems are completely changing. A
better understanding of factors that influence e-banking adoption in highly
developing market like Vietnam may help to further increase the adoption
rates in countries with improving infrastructures and economies (Davis,
1989; Mathieson, 1991).
The rest of this paper is organized as follows. Section 2 describes
relevant literature in the area of consumer behavior in the acceptance of
e-banking, including of e-commerce and information technology;
theoretical models of information technology usage. Section 3 discusses
hypothesis development and the theoretical foundation of our research
model. In section 4, it draws the research methodology. Section 5 is the
results of data analysis, and Section 6 contains managerial implications
and discussion. The final section is the conclusions and directions for
future research.
2. Literater review

2.1. E-commerce, e-banking, and adoption of information
technology
2.1.1 E-commerce is the trading or facilitation of trading in products or
services using computer networks via the Internet.
With the popularity of the Internet, many enterprises and individuals are
involved in e-commerce. Up to present, applications of e-commerce have
achieved lots of substantial progresses. E-commerce is playing a very


important role in the economic development. Large numbers of buyers and

sellers


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interact with each other through digital transactions. These interactions
promote the evolution and shape complex structures of e-commerce
market.
2.1.2. Electronic banking (E-banking)
Electronic Banking is simply the use of electronic means to transfer
funds directly from one account to another, rather than by check or cash
(Daniel, 1999). The rapid advanced in technology in banking industry
forced players to re-formulate the information technology strategies that
they employ to remain competitive. Consequently, e-banking becomes
more popular that most commercial banks must pursue. However, the
transaction in the branch is still the most common method used for bank
transactions in Vietnam in relation the Vietnamese habits and culture to
restrain the use of banking services.
Moreover, e-banking services in Vietnam started late as compared to
many developed countries. The use of e-banking has brought many
benefits among which include: no barrier limitations; convenient; lower
cost; modern practices and fast services. As a result, customers prefer the
use of e-banking because it saves time; it makes possible for the use of
innovative product or service at a low transaction fee. Besides, many
commercial banks have to upgrade the information technology with higher
security quality to keep their current customers and attract new
customers.
2.1.3. User acceptance or adoption of information technology
Saga and Zmud (1994) declared that consumers’ acceptance or

adoption of information technology is defined as ‘‘the act of receiving
information technology use willingly”. The findings from user acceptance
research suggest that when users are presented with a modern software
package, a number of factors influence their decision about how and when
they use it. In the past two decades, several theories have emerged that
offer deeper insights into acceptance of information technology. Among
these theories, the technology acceptance model (TAM) has received more
attention. Several theories reveal the factors that may affect consumers’
willingness to use an online financial service. They consist of (1) Theory of
Reasoned Action (Fishbein and Ajzen, 1975); (2) Decomposed Theory of
Planned Behavior (Taylor et al. 1995); (3) The first modified version of
Technology Acceptance Model;
2.1.4. New opportunities for banking sectors in Vietnam
The commercial banks in Vietnam need to expand more modern products
rather than deliver information and prior basics services. However, to improve
and diversify e-banking services requires huge investment in information
technology. This is a barrier to introduce new value added services such as
selling insurance, investment products, or market stock quotes. Telephone
banking can bring financial services to the home or office, especially if they
are affordable screen phones. By noticing how much interest the customer
expresses, the banks can apply Interactive videos to the customer to maintain
personal contact while still lowering the expense of delivery service. With an
interactive video, commercial banks can reduce labor force in their branch.
Complex life insurance products,


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open brokerage accounts, customized services can be widely available
where needed. The interactive videos will be cost effective expertise. The

internet allows banks to offer products to customers outside the normal
customer base of a branch. Banks are aware of the customer’s need for
these services and plan to make them available before other sources do.
2.1.5. Drawbacks
First of all, commercial banks are facing with some potential dangers
and issues to be taken into account. Because of increasingly allowed
customers to bank outside of traditional bank facilities like Automated
Teller Machines (ATM) or electronic home banking systems. Nevertheless,
customers only contact with their banks through (rather unsophisticated)
electronic interfaces. This also leads to the major difficulties in integrating
the legacy systems of a typical bank and selling additional products to
customers (cross-selling). For example, the insurance companies took the
opportunity of that to grab business from banks, selling savings products
to customers through their extensive distribution network. Similarly, the
decrease in human interaction with customers could also lead to a less
sophisticated understanding of their needs, as they are not always able to
express comments, criticisms or requests for new products while
interacting with machines.
2.2. Theoretical models of information technology usage
The first-line research has employed intention-based models, which use
Behavioral Intension to predict usage and in turn, focus on the
identification of the determinants of intention, including: (1) The theory of
reasoned action (TRA) is a behavioral intention model, developed by
Fishbein and Ajzen (1980) to predict human behavior in general; including
the performance of any voluntary act, unless intent changes between
assessment and performance of that behavior and whether a behavior will
occur (Ajzen and Fishbein, 1980; Fishbein and Ajzen, 1975). Moreover,
Sheppard et al. (1988) point out that the TRA was effective in predicting
different behaviors (e.g., study a few hours, go to a weekend job, or write
a letter). In TRA, attitude (ATT) towards a behavior and subjective norm

(SN), are identified as determinants of behavior.

Figure 1. The theory of reasoned action
(2) The First modified version technology acceptance model (TAM1). TAM is
an adaptation of TRA to explain specifically computer-usage behavior (Davis,
1989). In the TAM, Davis proposed Perceived Usefulness (PU) and Perceived
Ease of Use (PEOU) as two theoretical constructs affecting ATT towards a
technology, which affects the users’ behavior intention (BI) to the technology.
PU is a


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strong predictor of behavioral intentions in different environments while
TAM describes PEOU has an indirect effect through PU and ATT on the BI.
TAM has become a widely used model for predicting the acceptance and
use of information systems, and has recently been applied to predict
internet adoption. Unfortunately, the orignal TAM does not take into
account prior experience, age, gender and other personal characteristics.
That is why the researchers adapt the first modified version TAM (TAM1).

Figure 2. The First modified version of technology acceptance
model

However, TAM1 has still not tested with actual measures of usage
behavior fully. There are studies claimed that TAM’s fundamental
constructs are unable to explain fully the variances in intention. Moreover,
one key benefit of using TAM1 to understand system usage behavior is
that it allows other factors to be incorporated easily into its basic

framework, if desired, to explain better the effects of external variables on
system usage (Hong, 2001), as well as factors influencing the extent of
use of the internet in financial services (McKechnie, 2006). As a result of
this, it is necessary to integrate TPB and TAM for the conceptual model
measured the willingness, attitudes and intentions towards using ebanking (Pavlou, 2003; Jaruwachirathanakul, 2005; Verhagen, 2006; Kim,
2006). Furthermore, this integration will be combined with other
behavioral constructs to verify how technology factors affect to adopt ebanking in Vietnam
(3) That is why the second line of research is added to predict user
intention. The theory of planned behavior (TPB) was developed by Ajzen
(1988). The theory proposes a model which can measure how human actions
are guided. It predicts the occurrence of a particular behavior, provided that
behavior is intentional. The extension of the original TRA led to the formation
of as the introduction of a new construct with three factors: ATT, SN and
Perceived behavioral control (PBC), which reflects perceptions of internal and
external constraints on behavior. In the TPB, Ajzen (1991) incorporates PBC as
a determinant of behavioral intention toward behavior. In the contrary,
intention in turn relies on attitudes, SN and PBC (Ajzen, 2006). However, the
researchers also choose Decomposed TPB (DTPB) of Taylor and Todd (1995),
showed the effective guidance and fuller understanding of technology usage.
The core concept of the DTPB is based on the assumption that individuals
make rational decisions and their actions are also based on the systematic


use of information and resources available to them. Figure 3 illustrates the
decomposed theory of planned behavior.


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Figure 3. Decomposed theory of planned behavior (Ajzen, 1991)

(4) The theory of perceived risk
Considering the importance of Perceived Risk, proposed by Bauer
(1960), suggested in the context of consumer behavior benefits are often
accompanied by risk, this research extends an area of information systems
by looking into this factor integrated to the research framework of the ebanking in Vietnam. Risk is the combination of the probability of an event
and its consequence when there is at least the possibility of negative
consequences (Asnar, 2008). Perceived Risk is the uncertainty that
consumers confront when they are not capable of forecasting the
consequences of purchase decisions. In a marketing (Lim, 2003) defines
perceived risk as the nature and amount of risk perceived by a consumer
in contemplating a particular purchase action.
Perceived risk is a major affecting intention to adopt or continue using a
good or a service, including financial risk, performance risk, physical risk,
social risk, psychological risk and time risk (Gan, 2006). In the online context,
prior studies suggest the inclusion of perceived risk due to its importance in
influencing online consumer behavior (Pavlou, 2003; Schlosser et al., 2006),
especially in the area of e-banking (Gerrard et al., 2003). Existing studies
have produced mixed results on the role of perceived risk in the transacting
online (Yousafzai et al., 2003; Chen and Dhillon, 2003).

2.3. The definition of concepts
Constructs
1. Perceived usefulness

2. Perceived ease of use

3. Subject Norm

4. Attitude

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Constructs
5. Perceived Behavior Control
6. Behavioral Intention
7. Behavioral Usage
8. Perceived Risk

3. Hypothesis development and research framework

3.1. The development of hypotheses
3.1.1. Perceived Usefulness and Perceived ease of use to adopt using ebanking
Perceived Usefulness (PU) has formally been defined as the extent to
which a user subjectively believes that the use of a new technology or a
system will be useful or will improve his/her performance. In terms of PU,
there is also extensive research in the information systems community
that provides evidence of its significant effect on usage intention (Lee,
2009; Cheng, 2006; Wang, 2003; Chang, 2010). The ultimate reason
people employ e-banking that they find the system useful to their banking
transactions. Meanwhile, Perceived Ease of Use (PEOU) is defined as the
degree to which an individual believes that using a technology or a system
will be effortless (Hamid, 2008; Huang, 2011; Lee, 2009; Shen, 2010). Gu
and Suh (2009) proposed that the systems need to be both easy to learn
and easy to use to make the e-banking systems more useful.
With high reliability of PEOU and PU as effective factors, Davis (1989)
found that these two factors have strong relationship with actual usage of
information technology systems. Firstly, PU has stronger correlation with

usage of computer technology in comparison with PEOU because users
always paid more attention to the necessity of using a technology.
Secondly, PU also seen as being directly impacted by PEOU as the ease in
a system usage creates a potential impact on users’ perception of the
usefulness of a system. Based on this logical inference, the study proposed
the first hypothesis:
H1: Perceived ease of use and Perceived usefulness positively influence
the use of e-banking.
3.1.2. Perceived Usefulness and Attitude towards using e-banking
PU has not only been among the great priority in the use of e-banking
but also a major factor that affects attitude towards acceptance of
information systems. Previous authors (Taylor and Todd, 1995;
Parthasarathy, 1998; Karahanna, 1999, and Hardgrave, 2003) found that
only PU (Relative advantage) was a significant determinant of attitude
towards using e-banking. Therefore, we proposed the second hypothesis:


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H2: Perceived usefulness positively influences attitude towards using ebanking
3.1.3. Perceived usefulness and Behavioral Intention to use e-banking
Several works have shown that PU is an important antecedence to
behavioral intention to adopt and use technology (Davis, 1989, Venkatesh,
2000). In the e-banking context, it is presumed that the level of usefulness
which e-banking offers above regular banking methods could affect
intentions towards adoption and usage.
Across many empirical tests of TAM, perceived usefulness has a
significant relationship with usage intentions. Therefore, the following
hypothesis is tested:
H4: Perceived usefulness positively influences Behavioral Intention to use

e-banking
3.1.4. Attitude towards using and Behavioral Intention to use e-banking
Behavioral intention, as defined as a person’s intention to perform a
certain behavior, can be used to predict corresponding behavior as long as
the behavior is under volitional control, i.e., if the person can perform the
behavior voluntarily (Ajzen, 1980). Consequently, “intention is assumed to
capture the motivational factors that influence a behavior; they are
indicators of how hard people are willing to try, or how much of an effort
they are planning to exert, so as to engage in a behavior” (Ajzen, 1991).
The intention strength is decided by the subjective probability that a
person will implement the behavior, and this is weighted by setting the
subject along with a subjective probability involving the relationship
between the person and the behavior. As mentioned before, a person’s
intention to perform a certain behavior is influenced by the person’s
attitude and the subjective norms toward the behavior. Empirical
researches support the strong relationship between behavioral intention
and behavior (Fishbein, 1975).
TAM emphasized that a positive attitude directly affects an individual’s
intention to use the information systems. Thus, attitude towards using
information system is the fundamental predictor of the users’ behavior intention to use. Moreover, previous authors imply that attitudes directly
impact the intentions to adopt internet banking (Tan and Teo, 2000;
Hernandez, 2007). Consequently, the study proposes that:
H3: Attitude toward using positively influences Behavioral Intention to use
e-banking.
3.1.5. Perceived Behavioral Control and Behavioral Intention
TPB asserts that it is possible to measure Perceived Behavioral Control people’s perception of the ease or the difficulty in performing the behavior of
interest (Ajzen, 1991). PBC is as an exogenous variable that has both a direct
effect on actual behavior and an indirect effect on actual behavior through
intentions (Haghighinasab, 2009). Firstly, the indirect effect is based on the
assumption that PBC has motivational implications for behavioral intentions.

When people believe that they have little control over performing a behavior
due to a lack of requisite resources and opportunities, their intentions to


perform the behavior would be low, even if they have favorable attitudes
and/or the


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subjective norms to the performance of the behavior. Hence, the structural
link from PBC to Behavioral Intention actually reflects the influence of
control on actual behavior through intentions. Secondly, the direct path
from PBC to Actual usage is explained by the manifestation of the actual
control of an individual over the behavior.
Ajzen (1985) offers the following rationale for this direct path. The first
reason, if intention is held constant, the effort needed to perform the
behavior is likely to increase with PBC. In addition, PBC often serves as a
substitute for actual control, and the author hypothesized that PBC should
help to predict actual usage if perceived control is an accurate estimate of
actual control. Customers’ self-measurement of skills, opportunities and
resources to adopt and use e-banking are the adequate consideration to
engage in this particular behavior (Mathieson, 1991). Hence, PBC is among
the key determinants of Behavioral intention, especially in e-banking
context.
H6: Perceived Behavioral Control positively influences Behavioral
Intention to use e-banking.
3.1.6. Subjective Norm and Behavioral Intention to use e-banking
The significance of social influences on the individual via the

appearance of a subjective norm is also examined in the TPB. The role of
Subject norm as a determinant of IT usage is somewhat unclear.
Subjective norm (SN) mentions the “person’s perception of the social
pressures that put on him to performing the behavior in question” (Ajzen,
1980). Subjective norms can be weighted directly by asking respondents
to evaluate the importance of surrounding people approval or disapproval
for their performance in a given behavior (Ajzen, 1988).
Some researchers fail to identify the significant correlation of SN on
intention (Davis, 1989; Shim, 2001; Shih and Fang, 2004) whereas others
reveal a significant relationship (Taylor and Todd, 1995; Vijayasarathy,
2000). However, these results have been the fact that there were no real
consequences. Although ambiguousness still surrounds this construct, this
study will include SN in the theoretical framework with the following
hypothesis:
H5: Subjective Norm positively influences Behavioral Intention to use ebanking.
3.1.7. Perceived Risk and Attitude towards using e-banking
Attitude is populated to be the first antecedent of behavioral intention. It is
"an individual’s positive or negative feelings about performing the target
behavior” (Fishbein, 1975). Attitude toward behavior is a function of the
product of one’s salient beliefs that performing the behavior will lead to
certain outcomes and an evaluation of the outcomes. Therefore, a person who
has strong beliefs that positive consequences will derive from performing the
behavior will have a positive attitude toward the behavior. On the contrary, a
person who has strong beliefs that negative outcome will stem from the
behavior will demonstrate a negative attitude. The role of perceived risk has
been investigated widely in the business arena in understanding customers’
intended and actual purchase behavior. Perceived risk has been


conceptualized in the literatures in various means. Moreover, risk level

associated with certain dimensions will be elevated under a different context.
Although studies


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showed perceived risk as an important factor that influences online
shopping behavior (Doolin, 2005), there are still limited studies to identify
risk dimensions in this context (Cases, 2002).
Moreover, studies indicated perceived risk as an important influences
online banking adoption (Cunningham, 2005; Polatoglu, 2001). Accepting
the key role of perceived risk in e-banking, finding an operational
segmenting variable that could both reduce customers risk perception and
increase influence e-banking adoption, would be great managerial interest.
Some prior studies found that perceived risk is negatively influenced
attitude (Schmiege, 2009; Abroud, 2010). Thus, the same hypothesis is
tested in this study:
H7: Perceived Risk negatively influences Attitude toward using e-banking.
3.1.8. Behavioral intention and Actual Usage e-banking
In previous studies, the behavioral intention to use is found to be a
predictor of actual use and has been used as a dependent variable in
several studies (Agarwal, 1997; Davis, 1989; Karjaluoto, 2002). In ebanking context, it is presumed that an individual with high intention to
adopt e-banking will use it more frequently. In other words, behavioral
intention will increase the number of times using services within a specific
period of time. Thus, the last hypothesis is tested:
H8: Perceived behavioral intention positively influences the number of times
of e-banking usage.

3.2. Research model
From the above hypotheses, we develop the research framework

presented in Figure 4.

Figure 4. Research framework
4. Research methodology

4.1. Scale development
The questionnaire consisted of 48 items adapted from previous
literatures with minor modifications. Factors from TAM model (Perceived
Ease of Use, Perceived Usefulness, Attitude toward e-banking and
Intention to use e-banking) is adapted mostly from Cheng et al. (2006).


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Subjective Norm was constructed based on the questions of Wu & Chen
(2005) and Nor & Pearson (2007). Perceived Behavior Control was adapted
from Wu & Chen (2005), Shih & Fang (2004). In addition, Trust is a wellknown construct on the usages of internet, thus it is built from Amin
(2007), Jahangir and Begum (2008); Yousafzai et al. (2009). Perceived risk
is set up based on Featherman and Pavlou (2003). These items were
measured using 5-point Likert scale multiple choices, anchored by strongly
disagree and strongly agree. Lastly, the actual usage was measured by
getting information on the frequency of using electronic banking of
respondents.
4.2. Scale validation
Firstly, a phrase of exploratory qualitative analysis was conducted by
interviewing with experts in banking industry. Employing a semi-structured
questionnaire, researchers aim to fully understand the issue of e-banking in
Vietnam context. The results are utilized to modify the questions.

Subsequently, pilot test of 69 individuals, including 5 experts who play
major roles in determining strategic direction in implementing Internet
banking for corporate business groups, 15 managers of leading Internet
banking service providers, 17 staffs and 32 customers, was employed to
adjust the logic in the questions once more. The result is a fully-developed
questionnaire for the primary fieldwork.
4.3. Sample size and sampling method
The sample size was calculated by a formula
2

∗ (p) ∗ (1 − p)

Sample size = ss =

In that:
The confidence level of 95% => z= 1.96
P: the percentage of respondent who actually fill in the questionnaire. In
this study, p is expected to be 0.7 thanks to the convenience sampling
method that this research adopts.
C: the maximum margin of error accepted. In this study, c =0.05 (5%)

With these statistics, the least sample size of this study equals 322
respondents.
The sampling technique to be employed is convenience sampling
methods as it can achieve a large number of respondents in an effective
and quick approach and a higher response rate. Specifically, we deliver the
questionnaire to users of e-banking services and bankers via the
occupation and the relationship of the researchers.
4.4. Data analysis method
For the proposed theoretical model, the appropriate technique is the

structural equation modeling (SEM). This research utilizes two statistical softwares: SPSS and AMOS 20 and the collected data are carefully examined
through multiple steps. First of all, the data is analyzed using SPSS 20 to


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investigate the latent constructs (through EFA) (Gorsuch, 1983). The
constructs extracted in the EFA is then examined thoroughly as suggested
by Anderson and Gerbing (1988). Secondly, the CFA is carried out to
scrutinize the reliability, convergent and discriminant validity and the level
of fitness. With respects to the fitness of the model to the data, all
goodness-of-fit statistics satisfied the required thresholds (CMIN/df < 2;
GFI, CFI >0.9; AGFI > 0.9, RMSEA < 0.05), indicating good fit between the
model and the observed information (Hu and Bentler, 1999; Hair et al.,
2010). Lastly, structural equation modeling is implemented to predict the
proposed hypothesis from the validated set of data. The results are
summarized in Table 2 and 3.
5. Results
Turning to the validity assessment of the data, the study investigates
both convergent and discriminant validity given their different purposes.
The convergent validity ensures that the observed items effectively reflect
their underlying factor. As shown in Table 1, the composite reliability is
higher than 0.7 and the average variance extracted (AVE) is higher than
0.5. Further, the standardized regression weight of each item is higher
than 0.5. Thus the convergent validity is achieved. In the test of
discriminant validity, square root of AVE of a construct is taken is
compared in the correlation table. Table 1 demonstrated the correlation
table with the square root of AVE in diagonal. The square root of AVE
higher than the highest coefficient correlation of that construct with others
indicates that the data safely passes the discriminant validity test.

Table 1
Regression weight, Cronbach’s alpha, AVE and CR
Construct

Perceived Usefulness

Subjective Norm

Intention

Perceived Behavior Control


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Construct

Attitude toward e-banking

Perceived Ease of Use

Perceived Risk

Overall Goodness-of-fit
CMIN/df: 1.108
GFI: 0.947; CFI: 0.991; TLI: 0.990
RMSEA: 0.016

Table 2

Correlation table
Perceived Ease of Use
Perceived Usefulness
Subjective Norm
Intention
Perceived Behavioral Control
Attitude toward e-banking
Perceived Risk

Moving to the last step, structural equation modeling is employed to
analyze the proposed path in the conceptual framework. All hypotheses
adapted from the well-developed TAM model are accepted with the p-value
lower than 0.05. Among the factor in the TBP model, Perceived Behavioral
Control does not have a significant impact with Intention. Lastly, trust
strongly correlates with Attitude and Perceived Risk also manifests a
significant and negative impact with Attitude. Table 3 illustrate the
hypothesis testing results.


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Table 3
Hypothesis testing results
Hypothesis
Perceived Ease of Use -> Perceived Usefulness
Perceived Usefulness -> Attitude
Perceived Risk -> Attitude
Attitude -> Intention
Perceived Usefulness -> Intention
Subjective Norm -> Intention

Perceived Behavioral Control -> Intention
Usage Intention -> Actual Use
*** p < 0.0001; **p < 0.01; *p < 0.05; n/s p > 0.05

In line with previous studies on TAM model in electronic banking
context, the high level perceived ease of use lead to an increase in the
perception of usefulness (Gu and Suh, 2009). PU then manifested
significant impacts on both attitude and behavioral intention, which is
furnished by very high regression weight of 0.425 and 0.304 respectively.
This result is similar to previous scholars such as Taylor and Todd (1995),
Hardgrave (2003), and Venkatesh (2000). Lastly, the direct, one-way
relationship of attitude, behavioral intention and actual usage was also
confirmed in this study, identical to Tan and Teo (2000). This indicated the
well-established theory that favorable attitude will lead to higher intention
of performing an action and eventually to the actual performance of such
action.
Among the other two constructs manifested from the TPB framework,
only subjective norm manifested significant positive relationship with
Behavioral intention in this study. Thus, the H6 is confirmed with the
standardized regression weight of 0.128. Obviously, Vietnam has a
collectivism culture, and the approval of surrounding people plays a crucial
role in the intention to act of an individual. Perceived behavioral control,
however, has no impact (H7 with the standardized regression weight of
0.055). That means in this context, PBC is not as an additional determinant
of intentions and behavior towards using e-banking in Vietnam.
Last but not least, the negative effect of perceived risk to behavioral
intention is confirmed, as H8 is significant in this study. A frightening
perception of a negative outcome is what prevented people from using ebanking services. Risk-adverse is a nature in Asian country and Vietnam is
no exception. Noticeably, the impact is quite strong, with the significant
level below 0.01 and the standardized regression weight of -0.102. To be

successful in e-banking services, most banks have to deal with the
perceived risk in customers’ mindset. Figure 5 shows the testing results
with denoting the significant levels.


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Figure 5. Result for hypothesis testing

6. Discussions and implications
From this result, this study draws out meaningful recommendations for
both theoretical and managerial aspects. First of all, the study would
enable the banks executives and the policy makers of the bank and
financial institutions to be aware of e-banking as a product of electronic
commerce. The e-banking services should be user-friendly and effortlessto-use to meet customer satisfaction and needs. Moreover, e-banking
services should cover at least most of the functions original banking
method, and several superior functions so that it appears to be more
useful on customers’ perception. The fundamental for this is a good
technological framework to build the whole service. Secondly, an attempt
to decrease perceived risk on customers has also proven to be efficient
based on the result of this study. All information of customers, including
personal information and details of transactions should be kept up most
confidentiality. Furthermore, the systems should be reliable so that
customers cannot perceive any risk of e-banking. Most importantly,
marketing effort should be utilized to increase customers’ awareness of
those striking features, thus decreasing their fear of risks.
In brief, the implication of this study is to increase the adoption rate of
e-banking, banking institutions need to improve services that affect
consumer’s intention to adopt and continue usage. This may be especially

challenging for bank managers in Vietnam, where e-banking services are
still considered new innovations. However, with the rapid development of
information technology, banks have been beginning to rely heavily on
conducting banking transactions electronically.
7. Conclusion and further research
The modern design of electronic banking systems needs to incorporate
capabilities for customer understanding and for proactive selling of new
products because electronic business transactions can


374 | Policies and Sustainable Economic Development

only be successful if financial exchanges between buyers and sellers can
occur in a simple, universally accepted, safe and cheap way. Firstly,
marketing activities should not only focus on its targeted customers but
also the potential customers that are important to them, as well as those
they are admired given the role of Subjective Norm on Intention. In a
collectivist environment like in Vietnam, social influences play an
indispensable role to the intention and the actual behavior of any
individual. Secondly, this work will contribute extremely to the existing
literature on the general application of e-banking services in the modern
business. In addition, this model presented has opened the research
landscape to a wide range of opportunities.
Particularly, e-banking behavior is a complex and multifaceted process
the knowledge and understanding of which has developed incrementally
over time. The final decision of an individual to adopt or to reject ebanking may be also influenced by cognitive, psychological aspects.
Hence, the further research should be focused on customer’s emotional
and contextual processes. Finally, it is also concentrated on Trust,
especially two key items, including Perceived Security, Perceived Privacy,
contributed to Trust of users towards e-banking.

Appendix
Measurement scales and their source
Perceived Ease of Use

Perceived Usefulness

Attitude toward ebanking


Usage Intention


Policies and Sustainable Economic
Development | 375

Subjective Norm

Perceived
Control

Perceived Risk

Actual Usage

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