Internet banking adoption in ho chi minh city an application of unified theory of acceptance and use of technology (utaut) model

Thus, the purpose of this paper is to investigate the effects of performance expectancy, effort expectancy, social influence, facilitating conditions, perceived credibilityand anxiety on

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

-

Nguyen Thi Phuong Tra

INTERNET BANKING ADOPTION

IN HO CHI MINH CITY:AN APPLICATION OF UNIFIED THEORY OF ACCEPTANCE AND USE

OF TECHNOLOGY (UTAUT) MODEL

MASTER OF BUSINESS (Honours)

Ho Chi Minh City – 2014

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

-

Nguyen Thi Phuong Tra

INTERNET BANKING ADOPTION

IN HO CHI MINH CITY: AN APPLICATION OF UNIFIED THEORY OF ACCEPTANCE AND USE

OF TECHNOLOGY (UTAUT) MODEL

i

ACKNOWLEDGMETS

Firstly, I would like to express my deepest appreciation to my supervisor Dr Nguyen Thi Nguyet Que for her professional guidance, valuable advice, continuous encouragement, and motivating support that made this thesis possible

I would like to extend deep senses of gratitude to Professor Nguyen Dong Phong, Dr Tran Ha Minh Quan, Professor Nguyen Dinh Tho and lecturers who have taught and

me valuable knowledge and experience during the period of Master of Business course at International School of Business

Special, thanks to all of my dear friends in MBUS 2011 class, who share with me useful material, response and experience to conduct this study

I would like to express my grateful thanks to my friends and all the customersin three banking who participated in filling the questionnaires and provided the valuable information for this study

Personally, I wish to express my deep gratitude to my parents, my husband and two younger brothers for their spiritual support and encouragement during the time of study Specially, I must express my gratitude to Cao Thi Ngoc Anh, mother - in - law, for her taking care of my son since I was pregnant until now when my child is 17 months old So, I was able to complete the course on time I also wish to thank all those people who spent their time and generous support making this thesis project a dream come true

Ho Chi Minh City, Vietnam,

21 April 2014

Nguyen Thi Phuong Tra

ii

PLAGIARISM STATEMENTS

I would like to declare that, apart from the acknowledged references, this thesis either does not use language, ideas, or other original material from anyone; or has not been previously submitted to any other educational and research programs or institutions I fully understand that any writings in this thesis contradicted to the above statement will automatically lead to the rejection from the MBA program at International School

of Business University of Economics, HCMC

iii

COPYRIGHT STATEMENT

This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognize that its copyright rests with its author and that no quotation from the thesis and no information derived from it may be published without the author’s prior consent

© Nguyen Thi Phuong Tra / ISB-MBUS/2011-2013

iv

ABSTRACT

Purpose: Internet banking is becoming a new focuses as the number of Internet users

and its benefits is increasing worldwide and its benefits However, the degree of intent

to use Internet marketing is still a question of interest Thus, the purpose of this paper

is to investigate the effects of performance expectancy, effort expectancy, social influence, facilitating conditions, perceived credibilityand anxiety on behavioural intention to use Internet banking in Viet Nam and the developing Asian countries with good internet infrastructure Totally, 300 questionnaires were distributed to customers

of Bank for Investment and Development of Viet Nam (BIDV), Asia commercial bank (ACB) and Military Commercial Joint Stock Bank (MBBank),278 questionnaires were collected and 242 questionnaires were used for the final analysis The results from analysis of them based on multiple linear regression show that all five factors i.e performance expectancy, social influence, facilitating conditions, perceived credibilityand anxietyhave an impact on behavioural intention to use Internet banking Knowing the determinants on Internet banking adoption could help banking companies to improve their service to attract more users Besides, the use of Internet banking could reduce the frequency to bank that indirectly reduces cost

Keywords: Internet banking, performance expectancy, effort expectancy, social

influence, facilitating condition, perceived credibilityand anxiety

v

TABLE OF CONTENT

-o0o -

ACKNOWLEDGMETS i

COPYRIGHT STATEMENT iii

ABSTRACT iv

TABLE OF CONTENT v

LIST OF TABLES ix

LIST OF ABBREVIATIONS x

1 CHAPTER 1: INTRODUCTION 1

1.1 Research background 1

1.2 Problem statement 2

1.3 Research objective 3

1.4 Research scopes and methodology 4

1.5 Thesis structure 5

2 CHAPTER 2: LITERATURE REVIEW AND HYPOTHESIS 7

2.1 Theoretical foundation 7

2.1.1 The Theory of Reasoned Action (TRA) 7

2.1.2 Theory of Planned Behavior (TPB) 8

2.1.3 Technology Acceptance Model (TAM) 9

2.2 The Unified Theory of Acceptance and Use of Technology (UTAUT) 10

2.3 Development of research hypotheses 12

2.3.1 Performance expectancy 13

2.3.2 Effort expectancy 14

2.3.3 Social influence 14

2.3.4 Facilitating conditions 16

vi

2.3.5 Perceived credibility 17

2.3.6 Anxiety 18

2.3.7 Behavioral intention to use Internet banking 19

2.4 Summary of research model and hypotheses 19

2.5 Summary 21

3 CHAPTER 3: RESEARCH METHODOLOGY 22

3.1 Research design process 22

3.2 Development of questionnaires 23

3.2.1 Measurement scale 23

3.2.2 Draft questionnaires 25

3.3 Pilot study 25

3.4 Main survey 26

3.4.1 Sample size 26

3.4.2 Sampling method 27

3.5 Data analysis method 28

3.5.1 Reliability 29

3.5.2 Exploratory factor analysis (EFA) 29

3.5.3 Multiple regression analysis 30

3.6 Summary 31

4 CHAPTER 4: DATA ANALYSIS 32

4.1 Descriptive data analysis 32

4.2 Reliability analysis 34

4.3 Exploratory factor analysis (EFA) 37

4.3.1 Exploratory factor analysis results for measurement scales of independent factors 37

vii

4.3.2 EFA analysis results for measurement scales of dependent factors (behavioral

intention to use Internet banking) 40

4.4 Correlation and regression 41

4.4.1 Correlation analysis 41

4.4.2 Regression assumption testing 43

4.4.3 Multiple linear regression analysis (MLR) 44

4.5 Final research model 48

4.6 Summary 49

5 CHAPTER 5: CONCLUSIONS AND IMPLICATIONS 50

5.1 Conclusions of research 50

5.2 Research contribution 52

5.3 Managerial implications 53

5.4 Limitations and recommendations for future research 56

REFERENCES 58

APPENDICES 65

Appendix A: Summarizes the Unified Theory of Acceptance and Use of Technology (UTAUT) model 65

Appendix B: Guidelines for in-depth interview 67

Appendix C: List of interviewers 69

Appendix D: Questionnaire (English Version) 70

Appendix E: Questionnaire (Vietnamese Version) 72

Appendix F: Results of EFA testing for independent variables 74

Appendix G: Results of EFA testing for dependent variables 76

Appendix H: Multiple regression analysis 77

viii

LIST OF FIGURES

Figure 2.1: Theory of Reasoned Action from Fishbein and Ajzen (1975,1980) 8

Figure 2.2: Theory of Planned Behavior (Ajzen, 1985) 9

Figure 2.3: Technology Acceptance Model (Davis et al, 1989) 10

Figure 2.4: Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003) 12

Figure 2.5: The proposed research model with hypotheses 19

Figure 3.1: Research procedure 22

Figure 4.1: Final research model 49

ix

LIST OF TABLES

Table 3.1: Construct and corresponding items 23

Table 4.1: Mode of data collection 32

Table 4.2: Type of gender 33

Table 4.3: Type of age 33

Table 4.4: Type of education 34

Table 4.5: Type of income 34

Table 4.6: Reliability analysis result 36

Table 4.7: KMO and Bartlett's test of independent variables 37

Table 4.8: Rotated component matrix of independent 38

Table 4.9: KMO and Bartlett’s test of dependent variables 40

Table 4.10: Total variance explained 40

Table 4.11: Rotated component matrix of dependent variable 40

Table 4.12: Correlations analysis 42

Table 4.13: Model summary of multiple linear regression analysis 45

Table 4.14: ANOVA of multiple linear regression analysis 45

Table 4.15: Coefficient of multiple linear regression analysis 46

Table 4.16: Hypothesis summary 48

IBS Internet Banking Services

HCMC Ho Chi Minh City

KMO Kaiser-Meyer-Olkin

OBS Online Banking Services

MBBANK Military Commercial Joint Stock Bank

PC Perceived Credibility

PE Performance Expectancy

SI Social Influence

TAM Technology Acceptance Model

TPB Theory of Planned Behavior

TRA Theory of Reasoned Action

UTAUT Unified Theory of Acceptance and Use of Technology

1 CHAPTER 1: INTRODUCTION 1.1 Research background

Internet banking is an innovative service, which has been perpetuated by the development and diffusion of the Internet communication technology Internet banking services not only allow customers to carry out a range of banking activities such as managing bank accounts and transactions without leaving their desks (Weir et al., 2006), but also a very cost-efficient way for banks to provide their customer services (Yakhlef, 2001)

Internet banking offers customers the advantages of lower costs, location and time convenience, the ease and speed of completing transactions As one percent increase in the retention of Internet banking acceptance will typically bring 18 percent reduction in operating cost (Bhattacherjee, 2001), indifference towards consumers’ adoption of Internet banking services may result in a big loss to the financial institutions Therefore, the development of Internet banking services is most important in bank management

From year 2000 to 30 June 2012, the total Internet user growth is 566.4% worldwide The largest proportion (44.8%) of Internet users was from Asia followed by Europe (21.5%) and North America (11.4%) Viet Nam, an Asian country was among the Top 20 highest number of Internet users from 2010 to 30 June 2012 In year 2000, Viet Nam Internet users recorded 200,000 and increased to 31,034,900 in June, year 2012 This showed an increase of 155 times in 12 years (Internet World Stats, 2012)

Internet banking was first launch by Viet Nam in may, 2002 to provide Internet banking services to bank holders According to the commercial banks survey of Nielsen Global in 2012, there is less than 1.02% banking customers using Internet banking

services This rate is very low if compared with the number of Internet subscribers nationwide at the end of June 2012 This figure is also still very low when compare with developed nations in Asia It means that Internet banking service in Viet Nam is a potential market in future Hence, the need to understand the factors influencing to use Internet banking services is indispensable

1.2 Problem statement

The Internet banking plays a significant role in the Banking industry According to Yasuharu(2003), implementation of information technology and communication networking has brought about a revolution in the functioning of the banks and the financial institutions.The transition to electronic banking has therefore become a necessity for banks as it offers major opportunities in terms of competitive advantage and

it also allows banks to develop a stronger and more durable business relationship with its customers

However, despite of the numerous benefits, the acceptance of Internet banking in Vietnam is relatively low when comparing to West and the United States In Asian region, most studies concentrated to developed Asian countries (Singapore, Hong Kong, Taiwan, Malaysia, ect ) than developing country like Vietnam in the last twenty years.Thus, understanding the reason for acceptance or non-acceptance of new technologies by people is one of the greatest challenges Hence, there is a necessity to research about the behavioral intention to use Internet banking in Ho Chi Minh City, Viet Nam.That is also the motivation for developing this research

Most studies focused narrowly on the positiveaspects of Internet banking services For example, AbuShanab and Pearson (2009) focused on the effects of trust, relative advantage and attitude toward using Internet banking services Additional dimensions

were added to the UTAUT model such as voluntariness of use (Anderson and Schwager, 2004);perceived credibility and anxiety (Yeow et al., 2008), self-efficacy, anxiety, perceived trust, perceived risk, personal innovativeness and locus of control (AbuShanad and Pearson, 2009); trust (Foon and Fah, 2011) On the other hand, the research’s findings of Yeow et al (2008)have proved that perceived credibility and anxiety add to the UTAUT model in Malaysia This is market that posses many similar traits to Vietnam’s market Moreover, the motivation of this study also derives from the lack of studies in terms of Internet banking in Vietnam from the UTAUT model There are very few studies, for examples, the research of Khuu and Nguyen (2011)showed that performance expectancy, social influence, perceived credibility and anxiety significantly impact customers’ intention to adopt Internet banking In addition, effort expectancy and self-efficacy do not affect the intention to use Internet banking

Therefore, this study aims to test the influences of UTAUT model (performance expectancy, effort expectancy, social influence, facilitating conditions) and two additional dimensions(perceived credibility and anxiety) on behavioral intention to use Internet bankingin Ho Chi Minh City, Viet Nam.This issue is important because the results help the banks with marketing strategies encourage customers to use Internet banking in the future

1.3 Research objective

The objectives of this study are to investigate and confirm the factors affecting behavioral intention to use Internet banking in Ho Chi Minh City, Viet Nam The study will investigate these factors usingUTAUT models More specifically, it aims to:

- Examine the impact of performance expectancy on behavioral intention to use Internet banking

- Examine the impact of effort expectancy on behavioral intention to use Internet banking

- Examine the impact of social influence on behavioral intention to use Internet banking

- Examine the impact of facilitating conditions on behavioral intention to use Internet banking

- Examine the impact of perceived credibility on behavioral intention to use Internet banking

- Examine the impact of anxiety on behavioral intention to use Internet banking

1.4 Research scopes and methodology

This study was conducted in Ho Chi Minh City, the largest economic center of Vietnam Sample of study is the customersthat have bank accounts and understand about Internet banking servicesbut do not use Internet banking services Time and cost restricting, a database of three banks including Bank for Investment and Development of Viet Nam (BIDV), Asia Commercial Bank (ACB) and Military Commercial Joint Stock Bank (MBBank)

The study design into two phases: first was qualitative phase (in-depth interview), second was quantitative phase (main survey) In-depth interviews are conducted with ten people Main study is quantitative research with sample size of 300 respondents.The next step is analyzing the collected data The data of this research is processed using SPSS 22.0 software with three main stages First, Cronbach’s alpha method will be used to test

reliability of the measurement scale Then, Explore Factor Analysis (EFA) will be used to test validity of the measurement scale and for data reduction purpose Final, Multiple Linear Regression(MLR) will be used to test the relationship between variables in this research model

1.5 Thesis structure

The content of this study is 05 chapters The first is the introduction of the study The second is the literature review and hypotheses Following is the research methodology The next part is data analysis The final chapter is conclusions and implications is discussion of research findings and recommendations for future research comprise the final section of this research

Chapter 1 – Introduction

This chapter reflects the current situation of Internet banking services in Vietnam

It leads to proposal for the research problem, research objectives, research scope and significance of this study also presented in this section

Chapter 2 – Literature review

This chapter focuses on explaining each variable in the model and the reasons for their selection Moreover this chapter will show information about the model and hypothesis will be tested in this research

Chapter 3 – Research methodology

The study design, development of survey questions, qualitative research The measurement scale factor applied to the study will be clearly identified Also, determine

how to collect data and analyze the data collected to test the hypotheses proposed in chapter 2

Chapter 4 – Data analysis

This section discussed the data collection methods used to test hypotheses, and analyze the data received, the reliability and multiple regressions

Chapter 5 –Conclusion and implications

This chapter includes the conclusions and managerial implications The limitations are recognized to direct in the future Lastly, thesis has proposed further research on the

subject area

2 CHAPTER 2: LITERATURE REVIEW AND HYPOTHESIS

Before carrying out the survey on the effect factors of behavioral intention to use Internet banking, this chapter provides a theoretical background about Unified Theory of Acceptance and Use of Technology model (UTAUT) Based on these, the conceptual research model and hypotheses are constructed

2.1 Theoretical foundation

The technology acceptance literature documents a rich collection of models and theories that could be used to explain the adoption of information technology innovations (Venkatesh et al., 2003) To understand technology adoption, Venkatesh et al (2003) empirically compared eight competing models named:the Theory of Reasoned Action (TRA), the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM), the Model of PC Utilization (MPCU), the Motivation Model (MM), the Innovation Diffusion Theory (IDT), the Social Cognitive Theory (SCT) and a combined model of TAM and TPB (C-TAM- TPB) in Appendix A summarizes these models.Examples of some of the most influential models include the theory of reasoned action (TRA); the theory of planned behavior (TPB), the technology acceptance model (TAM) (El-Gayar, O., Moran, M., & Hawkes, M., 2011)

2.1.1 The Theory of Reasoned Action (TRA)

The Theory of Reasoned Action developed by Fishbein and Ajzen (1975, 1980) derived from previous research that started out as a theory of attitude, which led to the study of attitude and behavior The Theory of Reasoned Action is a model for the prediction of behavioral intention, spanning predictions of attitude and predictions of

behavior The components ofTRA are three general constructs: behavioral intention(BI), attitude toward behavior(A): “an individual’s positive or negative feelings (evaluative affect) about performing the target behavior” (Fishbein and Ajzen, 1975, p.216), and subjective norm(SN): “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, p.302)

Figure2.1: Theory of Reasoned Action (Ajzen& Fishbein, 1975)

TRA suggests that a person's behavioral intention depends on the person's attitude about the behavior and subjective norms (BI = A + SN) If a person intends to do a behavior then it is likely that the person will do it

2.1.2 Theory of Planned Behavior(TPB)

The Theory of Planned Behavior builds on the TRA(Ajzen, 1985) The Theory of Planned Behavior is a theory predicts deliberate behavior, because behavior can be deliberative and planned TPB is well - established and proven in both social science and information technology literature to explain and predict user behavioral intentions (Mykytyn and Harrison, 1993) The factors that determine intention are the individual’s attitude toward the behavior (A), the subjective norm (SN) and perceived behavior

Actual Behavior

Behavioral Intention

Attitude Toward Behavior

Beliefs and

Evaluations

Subjective Norm Normative Beliefs

and Motivation

control (PBC) Perceived behavior control is “the perceived ease of difficulty of performing the behavior” (Ajzen 1991,p.188)

Figure2.2: Theory of Planned Behavior (Ajzen& Fishbein, 1985)

According to The Theory of Planned Behavior (TPB) intention is not only affected

by two factors that are subjective attitudes and standards but also by the third factor - the perceived behavioral control The perceived behavioral control represents the resources needed by a person to perform any work, referring to the available resources, the skills, opportunities and perceptions of each who aim to achieve results TPB model is considered a more optimal TRA model in predicting and explaining consumer behavior

in the context of content and research

2.1.3 Technology Acceptance Model (TAM)

Technology Acceptance Model model was builtby Fred Davis and Richard Bagozzi(Bagozzi et al.,1992; Davis, 1989) This model is derived from TRA and TPB in the field of electronic banking in the country TAM proposes a model to explain why a user accepts or reject information technology (Davis, 1989 and Davis et al., 1989) TAM focuses on explaining behavior intention to use a specific technology or service; it has become a widely used model for user acceptance and use

Behavior

Behavioral Intention

Attitude

Behavioral

Beliefs

Subjective Norm Normative Beliefs

Perceived Behavioral Control Control Beliefs

Figure2.3: Technology Acceptance Model (Davis et al, 1989)

TAM model is used for the use of a new technology (Davis, 1989) Compared with previous TRA and TPB, TAM is the model most commonly used to explain the behavior of the system used, particularly the field of E-banking

- Perceived ease of use: The degree to which a person believes that using a particular system would be free from effort

- Perceived usefulness: The degree to which a person believes that using a particular system would enhance his or her job performance

Studies comparing TRA and TPB showed the latter to be a better predictor of behavioral intention (Ajzen & Madden, 1986) Empirical results found that both TPB and TAM exhibited considerable predictive power for adoption intentions, while TAM could predict attitude better than TPB (Mathieson, 1991) TAM when compared with TRA, also explained a larger variance in adoption intentions (Davis et al., 1989)

2.2 The Unified Theory of Acceptance and Use of Technology (UTAUT)

Towards the development of UTAUT by Venkatesh et al (2003), Theory of Reasoned Action (TRA) by Fishbein and Ajzen (1975), Technology Acceptance Model (TAM) by David (1989), Theory of Planned Behavior (TPB) by Ajzen (1991) and the combined TAM and TPB (C-TAM-TPB) by Taylor and Todd (1995) were used

External

variables

Perceived Ease of use

Perceived Usefulness

Attitude Intention to

Moreover, Theory of Diffusion of Innovation (DOI) by Rogers (1995), Social Cognitive Theory (SCT) by Bandura (1986), Motivational Model (MM) by Davis et al (1992) and the Model of PC Utilization (MPCU) by Thompson et al (1991) were also used Meanwhile, Venkatesh et al (2003) derived four main determinants of behavioral intentionand usage as performance expectancy, effort expectancy, and social influence Besides, empirical results of UTAUT model shows that it account for 70% of variance in the usage intention, which make it supersede other antecedent models of UTAUT

Unified Theory of Acceptance and Use of Technology model four key constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions) are direct determinants of usage intention and behavioral intention (Venkatesh et al., 2003)

- Performance Expectancy (PE):the extent to which an individual believes that using the system will help them achieves high performance work (Venkatesh et al., 2003).The constructs in the other models that pertain to performance expectancy are: perceived usefulness (TAM, and combined TAM-TPB)

- Effort expectancy: The degree of ease associated with the use of the system (Venkatesh et al., 2003) The constructs in the other models that capture the same concept are perceived ease-of-use (TAM/TAM2)

- Social influence: The degree to which an individual perceives that important others believe he or she should use the new system (Venkatesh et al., 2003) Similar constructs are represented in existing models: subjective norms (TRA, TAM2, TPB/DTPB, and combined TAM-TPB)

- Facilitating conditions: The degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system (Venkatesh

et al., 2003) This definition captures three different constructs in existing models: perceived behavioral control (TPB/DTPB and combined TAM-TPB) and facilitating conditions (MPCU)

Figure2.4: Unified Theory of Acceptance and Use of Technology(Venkatesh et al., 2003)

2.3 Development of research hypotheses

Because UTAUT has been empirically tested and proven superior to other prevailing competing models (Venkatesh et al., 2003; AbuShanab & Pearson, 2009; Yeow et al., 2008; Venkatesh & Zhang 2010; Foon & Fah 2011), this study chooses UTAUT as a theoretical foundation to develop the hypotheses

Based on the literature review, Unified Theory of Acceptance and Use of Technology, this research proposes the research model indicated in Figure 2.5, including the six factors that have impact on behavioral intention to use Internet banking Fourfactor oforiginal UTAUT model including performance expectancy, effort

Use Behavior Behavioral

Age Gender

expectancy, social influence, and facilitating conditionsare from Venkatesh et al.(2003) Two additional dimensionsperceived credibility and anxietyadapted from Yeow et al (2008)

2.3.1 Performance expectancy

The first independent variable, performance expectancy can be defined as user perception that a technology can increase productivity (Raman & Don, 2013) It reflects the assessment of the benefits received when initiatives are accepted or use Internet banking offers many benefits to customers as customers can perform many financial transactions Moreover, accessibility is an important aspect associated with the performance expectancy of Internet banking (Polatoglu& Ekin, 2001; Raman& Don, 2013) As discovered by Polatoglu & Ekin(2001), the Internet enables users to visit an online banking website at any time and from any location more easily and efficiently In comparison with traditional banking, Internet banking is able to reach far more people and keep away people from waiting in lines So, customers feel the work efficiency improved by the time-saving and convenience In other words, this study expect customers aware of Internet banking provided to these utilities, customers have a positive attitude with this technology

In this study’s context, performance expectancy refers to the belief that by using Internet marketing will help users gain benefits such as increased productivity, efficiency, and time saving.The previous studies in the field of Internet banking also confirmed that performance expectancy was a significant positive relationship with behavioral intention

to use Internet banking(AbuShanab& Pearson, 2009; Yeow et al., 2008; Foon & Fah, 2011).This study expects that performance expectancy will have a significant determinant

of behavioral intention to use Internet banking Thus, the following hypothesis H1:

Hypothesis H1: “Performance expectancy has a positive effect on behavioral

intention to use Internet banking”

2.3.2 Effort expectancy

The second variable, effort expectancy, is the degree to which a person believes that using a particular system would be effortless physical and spiritual(Davis,1989).Effort expectancy is expected to have an influence on intention to use the system in the future Effort expectancy is simply the consumer’s perception of how easy or hard it is to use the system (the idea of complexity, e.g Thompson et al 1991) If it is easy it means that using the system would be effortless The interaction required by the system is understandable, and the consumers see themselves becoming skillful at using the system Innovations can be difficult to use at first, but if people believe that they will easily get the system to do what they want it to do, it can be considered effortless Calisir and Gumussoy (2008) affirmed effort expectancy as a key driver of growth in Internet banking acceptance.Other isAbuShanab and Pearson (2009) study on Internet banking in Jordan, Foon and Fah (2011) study on Internet banking adoption in Malaysia They found the relationship between effort expectancy on behavioral intention was significant This study expect that Effort expectancy will have a significant determinant of behavioral intention to use Internet banking Therefore, the following hypotheses test in this study

Hypothesis H2: “Effort expectancy has a positive effect on behavioral intention

to use Internet banking”

2.3.3 Social influence

The third indicator, social influence, is significance in influencing the intention to use IBS varies across studies (Venkatesh & Davis, 2000).Social influence is not a new concept in the literature It is popular especially in technology acceptance scientific field Social influence is understood as the way that other people influence one’s beliefs, feelings and behavior (Mason et al., as cited in Ting et al., 2011) Particularly the people who are important to an individual play an important role in the considerations of whether or not to use a new technological system Also other reference groups such as organizations or the media have an influence on social situations (Thompson et al., 1991; Mathieson, 1991; Taylor & Todd, 1995)

Social influence has been researched in many contexts and results have been mixed with respect to its influence on behavioral intention as it pertains to technology use In the present study’s context, Deng et al (2011), Gao and Deng (2012) and Wong et

al (2013) found the relationship among the constructs as insignificant.On the other hand, personal connections such as family members, supervisors, professors, peers, the university administrator and environment, and even the online community have been identified to facilitate behavior of users (Bagozzi and Dholakia, 2002) towards intention

to use Internet banking These previous studies in the field of Internet banking also assert social influence impacts on behavioral intention to use Internet Banking(AbuShanab & Pearson, 2009; Yeow et al., 2008) This study expect that Social influencewill have a significant positive on behavioral intention to use Internet banking Therefore, the following hypotheses test in this study

Hypothesis H3: “Social influence has a positive effect on behavioral intention to

use Internet banking”

2.3.4 Facilitating conditions

The fourth variable, Facilitating conditionsrefers to the availability of resources such as written documents and technological infrastructure in supporting the use of a new technology (Raman & Don, 2013) In order to encourage Internet banking use, facilitating conditions should present includes ease of access, navigation and searching, more so when proper guidance is provided Other conditions include costs and other resources associated with such use, and the prior knowledge that users must have before they could use Internet marketing.The construct of facilitating conditions was found to be the most important factor affecting Internet

Ajzen (1991) suggested that the facilitating condition construct can be view as the external influence of the environment on one’s perceived controllability (perceived facilitating conditions) In an Internet banking context and from a customer view, we can propose a construct that sumsthe external aspects of the system (Internet banking) as perceived by customers and that is perceived facilitating conditions (PFC) This construct

is not under the control of customers, but they perceive it to affect their performance or utilization of the Internet It is expected that perceived facilitating conditions would exert

a positive influence on behavioral intention to use Internet banking in Vietnam.Facilitating conditions and habit are also good predictors of behavior intention

to use Internet banking These are important factors facilitating conditions found to have

a direct influence on behavioral intention to use ISB (Ajzen, 1991; Yuen et al., 2010; Foon and Fah, 2011) Therefore, the following hypotheses are tested in this study

Hypothesis H4: “Facilitating conditions have a positive effect on behavior

intention to use Internet banking”

2.3.5 Perceived credibility

The fifth variable, perceived credibility, is defined as the degree to which an individual believes an IBS as trustworthy and secure (Yeow et al., 2008) Perceived credibility is an important predictor of behavioral intention to use Internet banking services An increase in the perceived credibility will subsequently improve users’ Internet banking acceptance Therefore, creating customer trust is an essential way to retain existing bank customers (Kumar, 2013; Mukherjee & Nath, 2003).Following, the concept of Wang et al (2003), who distinguished perceived credibility from perceived risks and trust, Luarn and Lin (2005) and Amin et al (2008) supported security and privacy as two important dimensions under the construct of perceived credibility Also, Luarn and Lin (2005) and Amin et al (2008) empirically concluded that perceived credibility significantly affected human intention to use mobile banking

As the literature reveals that different scholars employ different perspectives to assess the concern of security, risk, trust, and credibility, the concern has been conceptualized and assessed from a variety of ways that fully depends on which discipline researchers interpret the concern Given that perceived credibility has been empirically supported and used not only in mobile banking adoption studies (Luarn & Lin, 2005; Amin et al., 2008) but also in many Internet banking studies as discussed in Wang et al (2003), Amin (2009), and Yuen et al (2010), the present study uses perceived credibility to represent individual security, privacy, risk, and trust concerns about Internet banking adoption Accordingly, this study hypothesizes:

Hypothesis H5: “Perceived credibilityhas a positive effect on behavioral intention

to use Internet banking”

2.3.6 Anxiety

The sixth variable, anxiety, is the feeling of nervousness when it comes to using a new technology (Liao and Cheung, 2003) Similarly, Anxiety is a concept most countries also reaffirmed behavior trends using computers (Compeau and Higgins, 1995) In the context of computer usage, technology anxiety is shown to decrease perceived ease of use (effort expectancy) and subsequent behavior intention to use (Venkatesh, 2000; Venkatesh and Bala, 2008) Anxiety is defined as the degree to which an individual becomes anxious when it comes to using IBS (Venkatesh et al., 2003) Anxiety is fear of stolen passwords or mistakes when using online banking services Doyle et al (2005) found that individuals with little or no computer and Internet experience have higher level of anxieties than experienced computer and Internet users

This study argues that Internet service anxiety has an effect on the behavioral intention to use Internet banking services Anxiety can be seen as negative emotional reaction towards performing a behavior (e.g using a Internet banking service) A significant body of literature has highlighted the importance of technology anxiety by demonstrating its influence on intention However users generally overcome their initial anxious feelings and develop favourable perceptions as they become familiar with the technologies (Hackbarth et al 2003)

When individuals have less experience with a new technology, they are forced to rely upon their general beliefs regarding technologies and technology use and, therefore, their attitude may reflect a high degree of anxiety (Lee, Warkentin & Choi, 2004).This study expects that anxietywill have a significant negative on behavioral intention to use Internet banking Therefore, the following hypothesis is identified as follow:

Hypothesis H6: “Anxiety has a negative effect on behavioral intention to use

Internet banking”

2.3.7 Behavioral intention to use Internet banking

Consumers’ self-reported intentions are measured similarly in many other studies Warshaw & Davis (1985) define intention to be “the degree to which a person has formulated conscious plans to perform or not to perform some specified future behaviour” Behavioral intention to use in this study is defined in a rather similar way as

in previous studies as “the individual’s likelihood of using mobile service” (Ajzen & Fishbein, 1980; Venkatesh et al., 2003; Knutsen et al., 2005) The prediction of intention has interested scientists for a long time As in many other acceptance papers in the field, this study also assumes that behavioral intention will have a positive effect on system usage in the future

2.4 Summary of research model and hypotheses

Based on the aboveliterature reviews, the conceptual framework model is proposedin the figure 2.5 and consisting of six hypotheses from H1 to H6 The group factors correspond are independent and quantitative variables, they affect directly on behavioral intention to use Internet banking, a dependent variable

Figure2.5: The proposed research model with hypotheses

Hypothesis H1: “Performance expectancy has a positive effect on behavioral

intention to use Internet banking”

Hypothesis H2: “Effort expectancy has a positive effect on behavioral intention to

use Internet banking”

Hypothesis H3: “Social influence has a positive effect on behavioral intention to

use Internet banking”

Hypothesis H4: “Facilitating conditions have a positive effect on behavior

intention to use Internet banking”

Hypothesis H5: “Perceived credibilityhas a positive effect on behavioralintention

to use Internet banking”

Behavioral Intention

to use Internet Banking

Hypothesis H6: “Anxiety has a negative effect on behavioral intention to use

Internet banking”

2.5 Summary

This chapter reviewshave relationship between performance expectancy, effort expectancy, social influence, facilitating conditions, perceived credibility, anxiety and behavioral intention to use Internet banking The reason for choosing is that the models have been successfully used in several previous researches related to bank customers The reviewed literature works as a good basis in developing a research model to measure the factors that influence customer intention to use Internet banking and their decision on whether or not to use the bank’s Internet banking services The next chapter will discuss about methodology that used to analyze the data and test hypotheses of the research model

3 CHAPTER 3: RESEARCH METHODOLOGY

This chapter showed more detail about the research process In addition, this chapter also provided information of sample such as: sample size, sample approach method in main survey, method of data cleaning after survey Besides that this chapter presented information about questionnaires design, results of pilot process In the end, this chapter also provided methodology for data analysis for this research

3.1 Research design process

This part shows a flowchart of methods used in this research in Figure 3.1.The current study consisted mainly of two stages: a qualitative phase (pilot study) and a quantitative phase (main survey)

Figure 3.1: Research procedure

Main survey

The final questionnaire

Pilot study

Exploratory Factor Analysis

Multiple Regression Analysis

Writing Result

3.2 Development of questionnaires

3.2.1 Measurement scale

All the variables in the model were measured with multiple items, which were developed by other researchers, to adequately capture the domain of constructs Specifically, performance expectancy was measured by six items of Yeow et al (2008); effort expectancy was measured by four items of Foon & Fah (2011), AbuShanab & Pearson (2009); social influence was measured by five items of AbuShanab & Pearson (2009); four items that developed by Yeow et al (2008) were used to measure facilitating conditions; each of two variables perceived credibility and anxiety were measured by four items of Yeow et al (2008); and finally, behavioral intention to use Internet banking was measured by three items that was developed by AbuShanab & Pearson (2009), Foon

& Fah (2011) and Yeow et al (2008) Questions 1 to 30 are measured on five point Likert scale where 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree.Table in below presented a detailed list of indicators used in the measurement model

Table3.1: Construct and corresponding items

Performance

Expectancy

PE1 IBS is convenient and easy to access

Yeow et al (2008)

PE2 I can transfer money anytime and any where PE3 I can save time paying essential bills at the

post office PE4 I can keep a record of my finances PE5 I need not visit traditional banks regularly PE6 I can manage my money online at anytime

Effort

Expectancy

EE1 Internet banking is easy to learn

Foon and Fah (2011), AbuShanab & Pearson (2009)

EE2 Internet Banking is easy to use EE3 Internet Banking saves me a lot of time EE4 It would be easy for me to become skillful at

using IBS

Construct Code Items Items sources

SI2 The senior management of the bank has been

helpful in the use of IBS SI3 People who are important to me think that I

should use IBS SI4 People who influence my behavior think that

I should use IBS SI5 People using IBS have more prestige than

those who do not

FC2 Basic system requirements for using IBS are

met FC3 Specific person (or group) is always

available for assistance FC4 The language in which the document is

written is easily understood

Perceived

Credibility

TR1 I trust in the ability of an IBS to protect my

privacy and personal information

Yeow et al (2008)

TR2 I believe no money will be lost when I

transfer TR3 IBS has enough specialists to detect fraud

and information theft TR4 Other people cannot view my bank account

information

Anxiety

AT1 I am afraid of losing information by hitting

the wrong key

Yeow et al (2008)

AT2 I am worried about the inaccessibility of IBS

web pages AT3 I am afraid of being charged for IBS AT4 I am afraid of making mistakes that I cannot

BI2 I predict that I would use IBS in the next few

months BI3 I plan to use IBS in the next few months

- Part 1: This section includes a consent form and screening questions to identify exactly the target audience of this survey

- Part 2: The main information includes questions based on a scale of measurement that was proposed for the research The items were measured on the five point Likert scale from 1 to 5(1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5

3.3 Pilotstudy

To conduct qualitative research, the Vietnamese version of the survey questionnaire was pre-tested using in-depth interview some customers who have knowledge of Internet banking services The in-depth interviews were conducted with 10

respondents (6 banking experts and 4 customers for answering) to ensure that the final questions would be well understood and valuable in measuring observed variables before launching the main survey The detailed questionnaire was shown to interviews for checking their understanding During the interview, the author also wanted to find out if the chosen measurement scale was suitable for conducting the research in Viet Nam All the comments from the interviewees were gathered with aim to modify the measurement scale Based on the feedback of respondents, the survey questionnaire was slightly modified to make it clearer and more understandable (see appendix B)

After Pilot study, questionnaires were used for survey in large numbers Results of Pilot test proved the good design of questionnaires, and they were used in main survey

3.4 Main survey

3.4.1 Sample size

The researchers in this field agree that this method requires a large sample size because it is based on large sample distribution theory (Raykov and Widaman, 1995) However, the sample size that is much larger than the current call is not clearly defined

In EFA, the sample size is usually determined based on (1) the minimum size and (2) the number of variables included in the analysis

Hair et al (1998) suggested that the minimum sample size for statistical analysis is based on the equation below:

N >= 5*k and N is greater than 100

Whereas:

Applying this formula for 6 independent variables, we have the minimum sample size for multiple regression as follow:n = 50 + 8 x 6 = 98

Summarily,30 variables and 6 independent variables,this research needed 150 observations at least for running EFA and Multiple Regression

3.4.2 Sampling method

The sampling procedure used by the author was convenience sampling through survey.According to Tull and Hawkins (1987) survey research has been the most common method for researchers to collect data

The participants were restricted who have bank accounts and understand about Internet Banking servicesbut do not use Internet Banking servicesin three banks in Ho Chi Minh The study surveys 300 clients of three banks (BIDV, ACB and MBBANK) with five point Likert scale with 1: strongly disagree and 5: strongly agree

To approach target sample, author used her own relationship to contact respondents Data used in the study was collected directly by paper and indirectly viaonline survey to respondent, from December 2013 to January 2014 to conduct the data collection needed for the research process

3.4.3 Questionnairesadministration

Respondents could reply through online and paper survey Respondents were all friends, clients, colleagues, partners or ones that have a direct relationship with author, author administrated responses through calling to push, chat to push and meeting directly to push method so that respondents can response quicker

Respondents could reply directly through email, mail, transferred through chat like: Yahoo, Skype and gave back directly to author In this time, author also checked with participants through calling in order to explain and help participants answer correctly

Data collection was conducted both on week and weekend days during one month 300questionnaires were distributed by paper survey and online survey,278 returned questionnaires, of which 242 were usable The quantitative survey was conducted in HCMC on December 2013 to January 2014

3.5 Data analysis method

The data collected after the cleaning is done, removing the invalid questionnaires and data will be processed using SPSS 22.00 software (Statistical Package for Social Sciences) Data analysis will be carried out through the following steps: