(Luận văn thạc sĩ) factors influencing the adoption of electronic banking in vietnam

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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 paper-related 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 e-banking (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 e-banking 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

Definition

Authors

1. Perceived usefulness

refers to the degree to which a person believes that
using a particular system will enhance his or her job
performance

Davis, 1989;

2. Perceived ease of use

the degree to which an individual the degree to
which a person believes that using a particular
system will be free of effort

Davis, 1989;

3. Subject Norm

the person’s perception that most people who are
important to him think he should or should not
perform the behavior in question

Fishbein and Ajzen, 1975

4. Attitude

an individual’s positive or negative feelings
(evaluative affect) towards using the technology

Fishbein and Ajzen, 1975


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Constructs

Definition

Authors

5. Perceived Behavior Control

reflects perceptions of internal and external
constraints on behavior

Ajzen, 1985; 1991

6. Behavioral Intention

a person’s subjective probability that he will perform
some behavior.

Fishbein and Ajzen, 1975

7. Behavioral Usage

Use is generally measured by the frequency,
duration, and intensity of e-banking usage.

Taylor and Todd, 1995

8. Perceived Risk

In the context of e-banking, perceived risk is defined
as the potential of loss in the pursuit of a desired
outcome from using electronic banking services

Bauer, 1960; Viswanath
Venkatesh et al., 2003

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 e-banking
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 e-banking
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’ selfmeasurement 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 e-banking.
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


368 | Policies and Sustainable Economic Development

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 e-banking 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 well-known 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
Sample size = ss =

𝑍 2 ∗ (p) ∗ (1 − p)
𝑐2

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 soft-wares: 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
Regression
Weight

Construct

Critical Ratio

Perceived Usefulness

Cronbach ‘s
alpha
0.829

PU2

0.851

PU4

0.715

14.758***

PU1

0.727

15.024***

PU3

0.676

13.831***

Subjective Norm
SN1

0.785

SN2

0.751

13.998***

SN3

0.748

13.951***

SN4

0.648

12.151***

Intention
INT2

0.886

INT1

0.805

17.618***

INT3

0.773

16.952***

Perceived Behavior Control
PBC3

0.845

AVE
0.555

Construct
Reliability
0.832

0.819

0.539

0.823

0.620

0.677

0.862

0.730

0.475

0.725


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Regression
Weight

Critical Ratio

PBC1

0.593

8.505***

PBC4

0.600

8.541***

Construct

Cronbach ‘s
alpha

AVE

Construct
Reliability

0.784

0.558

0.790

0.720

0.500

0.741

0.724

0.541

0.701

Attitude toward e-banking
ATT2

0.836

ATT1

0.721

12.569***

ATT3

0.676

12.065***

Perceived Ease of Use
PEOU3

0.797

PEOU2

0.769

10.398***

PEOU4

0.513

8.732***

Perceived Risk
PR3

0.677

PR2

0.900

2.776***

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

Table 2
Correlation table
PEOU

PU

SN

INT

PBC

ATTT

Perceived Ease of Use

0.705

Perceived Usefulness

0.375

0.745

Subjective Norm

0.097

0.016

0.734

Intention

0.187

0.374

0.132

0.823

Perceived Behavioral Control

-0.045

-0.132

-0.244

-0.012

0.689

Attitude toward e-banking

0.208

0.431

0.100

0.313

0.003

0.747

Perceived Risk

-0.033

-0.161

0.016

-0.069

-0.009

-0.167

PR

0.736

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.


372 | Policies and Sustainable Economic Development

Table 3
Hypothesis testing results
Hypothesis

Regression Weight

Critical Ratio

Result

Perceived Ease of Use -> Perceived Usefulness

0.382

6.083***

Supported

Perceived Usefulness -> Attitude

0.425

7.142***

Supported

Perceived Risk -> Attitude

-0.102

-1.892**

Supported

Attitude -> Intention

0.171

2.689**

Supported

Perceived Usefulness -> Intention

0.304

4.874***

Supported

Subjective Norm -> Intention

0.128

2.246**

Supported

Perceived Behavioral Control -> Intention

0.055

0.944(n/s)

Rejected

Usage Intention -> Actual Use

0.217

4.140***

Supported

*** 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, oneway 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 e-banking 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.

Policies and Sustainable Economic Development | 373

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 effortless-to-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 e-banking 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

It is easy for me to learn how to use e-banking

Cheng et al. (2006)

My interaction with e-banking is clear and understandable
E-banking has many flexible ways to search your required
information
I find e-banking easy to do what I want to do
Overall, I find e-banking easy to use
E-banking allows me to manages my account more

efficiently

Perceived Usefulness

Cheng et al. (2006)

Using e-banking enables me to accomplish banking
transactions quickly
Using e-banking for my banking service increases my
productivity
I find e-banking useful for my banking activities
Attitude
banking

toward

e-

Using e-banking is a wise idea.

Cheng et al. (2006)

Interacting with e-banking is fun
I look forward to those aspects of my job that require me
to use e-banking
I like the idea of using e-banking

Usage Intention

I intend to use e-banking in the next three months

I intend to use e-banking if the cost and times is reasonable
for me
The low risk involved in using e-banking will enable me to
continue to use it

Moon and Kim (2001);
Pikkarainen et al. (2004);
Cheng et al., (2006)


Policies and Sustainable Economic Development | 375

I still prefer to use e-banking than withdraw money from
cashier in a bank.
I will frequently use e-banking in the future
I believe that e-banking will be more relevant in the future
I will robustly recommend others to use e-banking
Subjective Norm

I use e-banking because of the proportion of coworkers who
use
People who are important to make think that I should use
e- banking (my family/friend/colleague)

Wu and Chen(2005); Nor et
al.(2008); Nor and Pearson
(2007)

The senior management of my bank has been helpful in the
use of e-banking

The organization has supported the use of e-banking
Perceived
Control

Behavioral

I have the knowledge to use e-banking
I have the resource to use e-banking
I have the ability to use e-banking
I think that using Electronic banking would be entirely
within my control

Perceived Risk

E-banking servers may not perform well because of slow
download speeds, the servers’ being down or because the
web site is undergoing maintenance

Shih and Fang (2004);
Jaruwachirathanakul
and
Fink (2005); Wu and Chen
(2005)

Featherman
(2003)

and

Pavlou

When transferring money on Internet, I am afraid that I
will lose money due to careless mistakes such as wrong
input of account number and wrong input of the amount of
money
I feel apprehensive about using e-banking
I’m sure that if I decided to use e-banking and something
went wrong with my transactions, my friends, family and
colleagues would think less of me
Actual Usage

What is your actual frequency of use E-banking services?

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