Factors influencing the adoption of electronic banking in vietnam

The first version modifies Technology Acceptance Model with Decomposed Theory of Planned Behavior and Perceived Risk in which eight constructs including Actual Usage, Behavioral Intentio

Factors Influencing the Adoption

of Electronic Banking in Vietnam

PHAN THUY KIEU

International University - Vietnam National University Ho Chi Minh City - phanthuykieu2006@gmail.com

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

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

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,

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

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

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 e-banking 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

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

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:

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

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 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

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)