Graduation thesis International Business Economics: Factors influencing consumers' adoption intention of e-wallet in Vinh Long province

FOREIGN TRADE UNIVERSITY HO CHI MINH CITY CAMPUS

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GRADUATION THESIS

Major: International Business Economics

FACTORS INFLUENCING CONSUMERS' ADOPTION

INTENTION OF E-WALLET IN VINH LONG PROVINCE

Student: Tran Nguyen Lan Ngoc Student ID: 1701015545 Class: K56CLC4 Intake: 56 Supervisor: Dr. Pham Hung Cuong

Thesis ID: 343

Ho Chi Minh City, December 2020

FOREIGN TRADE UNIVERSITY HO CHI MINH CITY CAMPUS

SOCIALIST REPUBLIC OF VIETNAM Independence - Freedom - Happiness

Ho Chi Minh City, ….../….../...............

DISSERTATION REMARKS

Student’s full name: Tran Nguyen Lan Ngoc Student code: 1701015545

Subject of the thesis: Factors influencing consumers' adoption intention of e-wallet in

Vinh Long province

Name of the supervisor: Dr. Pham Hung Cuong

Department: ....................................................................................................................

DETAILED REMARKS

1. Student’s attitude and progress during the dissertation schedule:

........................................................................................................................................

2. Responsiveness of scientific content to the research topic:

........................................................................................................................................

3. Format of the dissertation:

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4. The supervisor proposes the score for student’s attitude and progress during the

dissertation schedule:

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Supervisor (Signature with full name)

STATEMENT OF AUTHORSHIP

Except where reference is made in the text of the thesis, this thesis contains no

material published elsewhere or extracted in whole or in part from a thesis by which

I have qualified for or been awarded another degree or diploma.

No other person’s work has been used without due acknowledgements in the

thesis.

This thesis has not been submitted for the award of any degree or diploma in any

other tertiary institution.

Ho Chi Minh City, December 2020

Tran Nguyen Lan Ngoc

ACKNOWLEDGEMENT

First of all, the author would like to express her deep gratitude toward lecturers

of Foreign Trade University, Ho Chi Minh Campus for providing her with a lot of

necessary knowledge in e-commerce, especially in e-wallet so that the author can

have a solid base to fulfill her graduation thesis.

Besides, the author also sends her sincerest thanks to Dr. Pham Hung Cuong

who has supported her with many useful recommendations and clear guidance during

the time the author does the thesis. Without his dedicated and enthusiastic

instructions, this thesis could not be accomplished.

Moreover, the author highly appreciates all respondents who were willing to

spend their valuable time and efforts in completing the survey. Thanks to their

answers, the author could measure factors influencing the intention to adopt e-wallet

and make some assessments toward this topic.

Finally, even though the author has received many helpful supports and tried

her best to carry out this research, the thesis would still have some shortcomings due

to her lack of knowledge and experience. Thus, the author would highly value all

contributive comments for the future development of the research.

TABLE OF CONTENTS

CHAPTER 1: INTRODUCTION ......................................................................... 1

1.1. Research rationale ...................................................................................... 1

1.2. Research background ................................................................................. 3

1.2.1. International research ............................................................................. 3

1.2.2. Domestic research .................................................................................. 4

1.3. Research aims and objectives ..................................................................... 5

1.3.1. Research aims ........................................................................................ 5

1.3.2. Research objectives ................................................................................ 5

1.4. Research object and scope .......................................................................... 5

1.4.1. Research object ...................................................................................... 5

1.4.2. Research scope ....................................................................................... 6

1.5. Research questions ...................................................................................... 6

1.6. Research methods ....................................................................................... 6

1.7. Contribution and significance of the research ........................................... 7

1.7.1. Contribution of the research ................................................................... 7

1.7.2. Significance of the research.................................................................... 7

1.8. Thesis structure ........................................................................................... 8

CHAPTER 2: LITERATURE REVIEW AND RESEARCH MODEL .............. 9

2.1. Overview of e-wallet ................................................................................... 9

2.1.1. Definition of e-wallet ............................................................................. 9

2.1.2. Functions of e-wallet .............................................................................. 9

2.1.3. E-wallets in Vietnam ............................................................................ 10

2.2. Definition of adoption intention ............................................................... 12

2.3. Theoretical models in determining the intention to adopt new technology

.......................................................................................................................... 12

2.3.1. Theory of Reasoned Action (TRA) ...................................................... 12

2.3.2. Social Cognitive Theory (SCT) ............................................................ 13

2.3.3. Technology Acceptance Model (TAM) ................................................ 14

2.3.4. Unified Theory of Acceptance and Use of Technology (UTAUT) ....... 16

2.4. Previous empirical researches on factors influencing intention to adopt e-

wallet ................................................................................................................ 20

2.5. Proposed research model and research hypotheses ................................ 25

2.5.1. Proposed research model ..................................................................... 25

2.5.2. Research hypotheses ............................................................................ 26

CHAPTER 3: METHODOLOGY ...................................................................... 30

3.1. Research procedure .................................................................................. 30

3.2. Preliminary research ................................................................................ 31

3.2.1. Conducting short interviews ................................................................ 31

3.2.2. Pilot survey .......................................................................................... 32

3.2.3. Official measurement scale building .................................................... 33

3.2.4. Official questionnaire .......................................................................... 39

3.3. Official research ....................................................................................... 40

3.3.1. Method of data collection and sampling ............................................... 40

3.3.2. Methods of data analysis ...................................................................... 40

CHAPTER 4: RESEARCH RESULTS.............................................................. 45

4.1. Descriptive statistics analysis ................................................................... 45

4.1.1. Descriptive statistics for e-wallet adoption behaviors ........................... 45

4.1.2. Descriptive statistics of demographic variables .................................... 47

4.1.3. Descriptive statistics of independent variables ..................................... 49

4.1.4. Descriptive statistics of dependent variables ........................................ 50

4.2. Cronbach Alpha’s coefficient analysis ..................................................... 50

4.2.1. Cronbach Alpha’s coefficient analysis for independent variables ......... 50

4.2.2. Cronbach Alpha’s coefficient analysis for dependent variables ............ 54

4.3. Exploratory Factor Analysis (EFA) ......................................................... 55

4.3.1. Exploratory Factor Analysis for independent variables ........................ 55

4.3.2. Exploratory Factor Analysis for dependent variables ........................... 58

4.4. Pearson correlation matrix analysis......................................................... 59

4.5. Multiple linear regression analysis .......................................................... 61

4.5.1. Model testing ....................................................................................... 61

4.5.2. Assumption violation testing ................................................................ 64

4.6. Testing model hypotheses ......................................................................... 65

4.7. Testing the influence of demographic factors on the intention to adopt e-

wallet ................................................................................................................ 66

4.7.1. Independent T-test analysis .................................................................. 66

4.7.2. ANOVA analysis ................................................................................. 66

4.8. Research results discussion ...................................................................... 68

4.8.1. Trust .................................................................................................... 68

4.8.2. Self-efficacy ......................................................................................... 68

4.8.3. Facilitating condition ........................................................................... 69

4.8.4. Social influence.................................................................................... 69

4.8.5. Effort expectancy ................................................................................. 70

4.8.6. Performance expectancy ...................................................................... 70

4.8.7. Perceived risk....................................................................................... 71

CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS ...................... 72

5.1. Conclusions ............................................................................................... 72

5.2. Recommendations ..................................................................................... 73

5.2.1. Enhancing Trust ................................................................................... 73

5.2.2. Enhancing Self-efficacy ....................................................................... 74

5.2.3. Enhancing Facilitating condition .......................................................... 75

5.2.4. Enhancing Social influence .................................................................. 75

5.2.5. Enhancing Effort expectancy ............................................................... 76

5.2.6. Enhancing Performance expectancy ..................................................... 77

5.3. Limitations and orientations for future research .................................... 78

5.3.1. Limitations of the research ................................................................... 78

5.3.2. Orientations for future research ............................................................ 79

REFERENCES .................................................................................................... 81

APPENDIX .......................................................................................................... 91

LIST OF ABBREVIATIONS

MEANINGS

ABBREVIATIONS

ANOVA Analysis of Variance

C-TAM-TPB A model combining TAM and TPB

EFA Exploratory Factor Analysis

E-payment Electronic payment

E-wallet Electronic wallet

Innovation diffusion theory IDT

Kaiser – Meyer - Olkin KMO

The motivational model MM

MPCU The model of PC utilization

State Bank of Vietnam SBV

Social Cognitive Theory SCT

Technology Acceptance Model TAM

The theory of planned behavior TPB

Theory of Reasoned Action TRA

UTAUT Unified Theory of Acceptance and Use of Technology

VIF Variance inflation factor

LIST OF TABLES

Table 2.1 E-wallets in Vietnam until October 2020 ............................................... 11

Table 2.2 The theories and models used to propose UTAUT ................................. 17

Table 2.3 Origin of constructs in UTAUT model ................................................... 18

Table 3.1 Measurement scale for Performance expectancy .................................... 33

Table 3.2 Measurement scale for Effort expectancy ............................................... 34

Table 3.3 Measurement scale for Social influence ................................................. 35

Table 3.4 Measurement scale for Facilitating condition ......................................... 36

Table 3.5 Measurement scale for Trust .................................................................. 36

Table 3.6 Measurement scale for Perceived risk .................................................... 37

Table 3.7 Measurement scale for Self-efficacy ...................................................... 38

Table 3.8 Measurement scale for Adoption intention ............................................. 38

Table 4.1 Time period of adopting e-wallet ........................................................... 45

Table 4.2 Names of adopted e-wallets in Vinh Long province ............................... 46

Table 4.3 Purposes of adopting e-wallets in Vinh Long province .......................... 47

Table 4.4 Cronbach Alpha’s outcome of Performance expectancy ......................... 50

Table 4.5 Cronbach Alpha’s outcome of Effort expectancy ................................... 51

Table 4.6 Cronbach Alpha’s outcome of Social influence ...................................... 52

Table 4.7 Cronbach Alpha’s outcome of Facilitating condition.............................. 52

Table 4.8 Cronbach Alpha’s outcome of Trust....................................................... 53

Table 4.9 Cronbach Alpha’s outcome of Perceived risk ......................................... 53

Table 4.10 Cronbach Alpha’s outcome of Self-efficacy ......................................... 54

Table 4.11 Cronbach Alpha’s outcomes of Adoption intention .............................. 54

Table 4.12 Outcome of indicators for independent variables in EFA ..................... 55

Table 4.13 Rotated Component Matrix .................................................................. 56

Table 4.14 Outcome of indicators for dependent variables in EFA ........................ 58

Table 4.15 Component matrix of dependent variables ........................................... 58

Table 4.16 Pearson correlation matrix ................................................................... 59

Table 4.17 Types and Definitions of variables used in the regression model .......... 61

Table 4.18 Model summary ................................................................................... 62

Table 4.19 ANOVA .............................................................................................. 62

Table 4.20 Regression outcomes ........................................................................... 63

Table 4.21 Hypotheses testing outcome................................................................. 65

LIST OF FIGURES

Figure 2.1 Theory of Reasoned Action .................................................................. 13

Figure 2.2 Social Cognitive Theory ....................................................................... 14

Figure 2.3 Technology Acceptance Model............................................................. 15

Figure 2.4 TAM2................................................................................................... 16

Figure 2.5 Unified Theory of Acceptance and Use of Technology ......................... 19

Figure 2.6 Model proposed by the author .............................................................. 26

Figure 3.1 Research procedure .............................................................................. 30

Figure 4.1 Gender .................................................................................................. 47

Figure 4.2 Age ....................................................................................................... 48

Figure 4.3 Educational level .................................................................................. 48

Figure 4.4 Occupation ........................................................................................... 49

Figure 4.5 Income ................................................................................................. 49

CHAPTER 1: INTRODUCTION

1.1. Research rationale

Non-cash payment has been considered as an inevitable tendency in the

economic development process all over the world, especially in Vietnam. According

to a survey of VISA (2020), Vietnamese have decreased cash payment compared to

the previous year since they have preferred electronic payments (e-payment) such as

contactless payments card (credit card, debit card), mobile banking, electronic wallet.

It is found that consumers do not bring too much cash when going out because there

are more places accepting non-cash payment. Moreover, 74% Vietnamese consumers

are expected to increase non-cash payment in the following twelve months. As

reported by the State Bank of Vietnam (SBV), e-payment has significantly increased

in the first four months in 2020 compared to that in 2019. Particularly, mobile

payment has increased 198.8% in quantity and 21.9% in value (Le Anh, 2020). SBV

has recently requested its branches in cities and provinces to implement plans

promoting non-cash payment, especially in electricity, water, health, education fields

and public services (Nguyen Dai Lai, 2020). There are about 50 banks completing

electronic tax payment connection with tax and custom authorities in 63

provinces/cities; 27 banks and 10 intermediary payment service providers have

cooperated with Vietnam Electricity to collect electricity bills (Hong Anh, 2020).

From those above, it can be clearly indicated that the payment tendency has been

shifting toward using non-cash payment methods. Especially, e-payment has quickly

developed and played an important role in the economy with many types of methods

which can meet consumers’ needs gradually.

Together with the development of non-cash payment, the electronic wallet (e-

wallet) has received much attention from the government, enterprises and consumers

and has become the most popular method among non-cash payment methods.

Vietnamese government has issued the license for e-wallet since 2008, however, only

until 2017, e-wallet has become extremely popular due to its tight connections with

many services. As stated by Le Anh Dung - Deputy Head of Payment Department of

SBV, until the first quarter in 2020, Vietnam has already had 34 e-wallets with 13

million accounts that have been activated and used. Moreover, there have been 225.6

million transactions conducted via e-wallet with a total value of 77.7 thousand billion

VND for the first three months in 2020 in accordance with SBV’s statistics (Duy Vu,

2020). According to a survey of Cimigo, Momo, Moca and ZaloPay are the top three

e-wallets that are widely used in Ho Chi Minh and Ha Noi City. E-wallets are mostly

used to top up mobile phones, make payment for utility bills, and transfer money. On

average, Momo users spend 520 thousand VND per day, followed by Moca users

with 506 thousand VND and ZaloPay users with about 441 thousand VND (Thai Thu,

2020). Based on the value of daily transactions, it can be stated that the demand of e-

wallet adoption in Vietnam has been extremely high. Thus, using the e-wallet for

above mentioned purposes will increase non-cash payment and replace cash payment

in the near future. Le Thi Thuy Sen - Director of Communications Department of

SBV made a commitment that there would be nobody left behind in approaching

financial services (Phuong Linh, 2020). Hence, e-wallet would be also communicated

to people in rural areas and provinces to encourage them to change their payment

habits. The program would be made to be suitable with the habits and cultures of the

regions, and the messages would be easy to understand and close to the people in

remote areas. Therefore, it can be indicated that e-wallet will be the most popular

method among non-cash payment methods which can also be easier to access

consumers even in provinces. On the other hand, due to Covid-19 pandemic,

Vietnamese government has encouraged people to restrain cash payments to protect

themselves. Then, non-cash payment, especially e-wallet will definitely become a

trendy payment method in the current situation.

Although there are some studies on e-wallet in Vietnam, they only focus on

people who live in big cities such as Ho Chi Minh City and Ha Noi City. However,

e-wallet has become popular with people who even live in provinces due to

reasonable policies of Vietnamese government and SBV. It can be indicated that

consumers in rural areas and provinces have become the target consumers of e-wallet

from now. Hence, provinces have become the potential market for e-wallet service

providers to investigate. Therefore, the author decided to deeply study the topic

“Factors influencing consumers’ adoption intention of e-wallet in Vinh Long

province”.

1.2. Research background

1.2.1. International research

Among non-cash payment methods, e-wallet has received most attention and

has been investigated by a lot of researchers in many countries. Based on the findings

of the author, e-wallet has also been considered as a mobile wallet or digital wallet in

international research while it has commonly been considered as e-wallet in Vietnam.

Amin (2009) investigated a study on “Mobile wallet acceptance in Sabah: an

empirical analysis” to explore factors affecting the intention to adopt mobile wallet

in Sabah, Malaysia. The result indicated that perceived usefulness, perceived ease of

use, perceived expressiveness and knowledge of mobile wallet affected the intention

to adopt mobile wallet at 95% significance level. The author also suggested that

perceived self-efficacy, perceived financial cost, perceived enjoyment and normative

pressure could be added to the model to increase other situation applications which

was found to be a limitation of this study.

The research “Adoption of digital wallet by consumers” of Rathore (2016)

declared that convenience in buying online, usefulness of digital wallet and brand

loyalty were three important factors that influenced the adoption of digital wallets of

consumers in India. Additionally, one of the major problems that made consumers

reduce the adoption of digital wallet was dependency on internet connection.

However, the research only focused on the consumers’ behavior of using digital

wallets to make payments for online shopping which could not reveal the factors that

would affect the intention to adopt the digital wallet for other purposes.

Yadav (2017) conducted a research on “Active determinants for adoption of

mobile wallet” and found out that only perceived usefulness has a positive significant

effect on the intention to adopt mobile wallet. Other factors including perceived ease

of use, perceived risk, trust and quality of service were proved to insignificantly

influence Indian consumers’ intention to use mobile wallets. The result was quite

strange compared to other research because perceived ease of use was considered as

a major factor affecting adoption intention of new technologies in general and mobile

wallet in particular in accordance with the theoretical Technology Acceptance Model.

1.2.2. Domestic research

During the research process, the author finds out that there have been limited

studies on e-payment as well as e-wallet in Vietnam. Among a small amount of

research, “A Study of Factors Affecting the Intention to Use Mobile Payment Services

in Vietnam” conducted by Liu and Tai (2016) is the research that should be mostly

mentioned. Based on the finding of this research, perceived usefulness, perceived

ease of use and trust of safety had significant influences on the intention to use mobile

payment. Moreover, convenience of mobility directly affected perceived usefulness

and ease of use which indirectly influenced the intention to adopt mobile payment in

the end. This research has an important meaning to the development of mobile

payment in Vietnam. However, the research did not deeply investigate the e-wallet

field which was a big limitation of the research.

Regarding e-wallet, Nguyen Thuy Dung and Nguyen Ba Hung (2018)

provided an overview of the current situation of e-wallet in Vietnam through a study

“Electronic wallet payment in Vietnam: Situation and Solutions”. The study analyzed

how Vietnamese consumers adopted e-wallet in recent years. With various forms of

topping up and payment, e-wallet had become a familiar payment tool for consumers

those days. Besides, the study also indicated a lot of problems that hindered the

development of e-wallet payment such as lack of synchronization and connection

among service providers, lack of information of e-wallet and guidance on how to use

it and lack of consumers’ trust. The research has reflected an accurate perspective of

the e-wallet situation in Vietnam over the past few years. However, the research did

not investigate what factors would influence Vietnamese consumers’ intention to

adopt e-wallet which was a big shortcoming of the study.

In summary, investigating the factors influencing consumers’ intention to

adopt e-wallet has been very popular in international studies while it is hard to find

any related research on this topic in Vietnam. On the other hand, those factors are

very important because they help service providers access consumers easier and

improve the development of e-wallet payment. Therefore, the research conducted by

the author could help to remedy this shortcoming and encourage more studies on this

field.

1.3. Research aims and objectives

1.3.1. Research aims

The research aims to explore which factors will influence consumers’ intention

to adopt e-wallet and the extent to which those will impact consumers’ behavior, then

suggest some recommendations for improving e-wallet payment in Vinh Long

province. In the current fierce competition, such information will be definitely

valuable and useful for e-wallet service providers who are making every effort to

expand the market and increase the number of e-wallet subscribers.

1.3.2. Research objectives

Firstly, the author will synthesize theoretical models and empirical research

which have been used to explain the intention to adopt new technology in general and

e-wallet in particular. Then, a proposed model and measurement scale will be

established to discover which factors will influence consumers’ adoption intention of

e-wallet in Vinh Long province.

Secondly, the author will conduct a survey to collect data within one month.

The qualified data will be processed by SPSS 20.0 software to examine the

significance of the model. Then, the author can determine the factors and evaluate the

extent to which those factors influence the adoption intention of e-wallet.

Finally, the author will make some suggestions which can help e-wallet service

providers have better understanding of the consumers’ behaviors in Vinh Long

province to improve their competency in the market.

1.4. Research object and scope

1.4.1. Research object

Based on the aim of this paper, the research object is the intention to adopt e-

wallet of consumers in Vinh Long province.

The subjects of the survey are people who live in Vinh Long province and

adopt at least one e-wallet. The reason for the criteria “adopting at least one e-wallet”

is that respondents should have some experiences with e-wallet so that they can give

correct and appropriate answers.

1.4.2. Research scope

In terms of space, the research only focuses on people who live or work in

Vinh Long province. The reason for choosing Vinh Long province is based on the

development of e-wallet adoption under the author’s observation. In Vinh Long

province, there are Vincom center, CGV movie theater, Coopmart supermarket,

Thegioididong store which have encouraged consumers to adopt e-wallet by many

promotional benefits such as discounts, vouchers and refunds. In addition, Electricity

in Vinh Long province has announced that it will temporarily stop collecting

electricity bills at customers’ houses (H.Minh, 2020). Thus, the customers have to

change their cash payment habit into non-cash payment. From the above reasons,

they are such great opportunities to enhance the e-wallet adoption which make Vinh

Long province become a potential market that needs to be investigated.

In terms of time, the research was conducted within 3 months from September

2020 to November 2020. Particularly, the survey was carried out within one month

which was in October 2020 so that the data could be lately updated.

1.5. Research questions

This research is implemented to answer three following questions:

(1) What are the factors influencing the intention to adopt e-wallets of consumers

in Vinh Long province?

(2) To what extent do these factors influence the intention to adopt e-wallets of

consumers in Vinh Long province?

(3) Based on this study, what are the recommendations for e-wallet service

providers to expand their services to consumers in the provinces?

1.6. Research methods

The research was carried out in accordance with two following phases in order

to guarantee the profession of scientific research.

In the preliminary research phase, a qualitative method had been applied.

Firstly, the author reviewed all related theoretical frameworks and previous studies.

Then she selected the most suitable ones to propose a research model together with

hypotheses. After that, the author made a short interview and pilot survey with some

e-wallet users to adjust the questionnaire to be more suitable and easier to understand.

The next phase was the official research which had applied a quantitative

method. The first thing the author did in this phase was to conduct the official survey

based on the official questionnaire to collect primary data. After that, the collected

data would be processed by SPSS 20.0 software to examine Cronbach Alpha’s

coefficient, Exploratory Factor Analysis, Pearson correlation and Multiple Linear

Regression in order to test the reliability of the scale, evaluate the proposed model

and test research hypotheses.

1.7. Contribution and significance of the research

1.7.1. Contribution of the research

The most dominant difference of this research compared to other research

related to this topic is that it is implemented to investigate consumers who live in a

province. Other people often conduct research in big cities such as Ho Chi Minh, Ha

Noi due to its convenience to collect data. However, the author would like to

understand more about the e-wallet adoption situation even in small provinces which

have not received appropriate attention from researchers so that the author can have

a closer perspective to the current situation.

In addition to the theoretical model Unified theory of acceptance and use of

technology (UTAUT) with four main factors including performance expectancy,

effort expectancy, social influence and facilitating condition, the author has added

three other factors including trust, perceived risk and self-efficacy which have been

proved to significantly affect adoption intention in previous studies. The special thing

is that these seven factors have not been put together in a model yet. Therefore, this

is the first time there has been a model combining all these factors.

1.7.2. Significance of the research

Even though adopting e-wallet has become a popular phenomenon in recent

years, there is limited scientific research regarding this topic in Vietnam. Therefore,

this research has significantly contributed to the enrichment of documents about the

e-wallet adoption field which is currently very restricted. It provides future

researchers with knowledge about e-wallet and factors influencing consumers’

intention to adopt e-wallet in Vinh Long province. Therefore, future researchers can

utilize such knowledge as references for their future studies. Moreover, it can also

encourage more people to pay attention to investigate e-wallet on other aspects which

can increase various perspectives regarding this topic.

Besides, this study provides e-wallet service providers with detailed

information to determine the market prospect in Vinh Long province. Therefore,

providers can use it as reference to decide whether they should investigate in this

market. Moreover, based on the finding of this study, providers who are preparing to

penetrate into this market can deeply understand the consumers’ behaviors and

determine what are important factors influencing the consumers’ intention to adopt

e-wallet including performance expectancy, effort expectancy, social influence,

facilitating condition, trust, perceived risk and self-efficacy. Thus, they can promote

appropriate strategies to easily access and attract more customers in provinces which

are also potential and promising markets.

In summary, this research will provide a new insight of the e-wallet field with

many new factors that have not been applied in previous Vietnamese studies. The

author hopes that the research can provide more knowledge about e-wallet adoption

in Vinh Long province so that e-wallet service providers can have more effective

measures to increase e-wallet payment.

1.8. Thesis structure

The graduation thesis consists of 5 chapters:

Chapter 1: Introduction

Chapter 2: Literature review and Research Model

Chapter 3: Methodology

Chapter 4: Research results

Chapter 5: Conclusions and recommendations

Summary of Chapter 1: In the first chapter, the author has pointed out the necessity

and the reasons for choosing this topic. Moreover, the author has described briefly

the research background and stated the aims as well as the objectives of the research.

Then the author has proposed three questions and briefly mentioned the methodology

used in the study. Finally, the author has indicated the contribution and significance

of the research as well as the thesis structure. In the next chapter, theoretical

framework and previous studies will be discussed more detailed.

CHAPTER 2: LITERATURE REVIEW AND RESEARCH MODEL

2.1. Overview of e-wallet

2.1.1. Definition of e-wallet

E-wallet is defined as an electronic wallet that allows consumers to conduct

financial transactions through a mobile device (Amoroso and Magnier-Watanabe,

2012). E-wallet can be considered as a virtual wallet which a consumer can use to

make a payment or top up account through a smartphone. Moreover, e-wallet can

replace a physical wallet to perform basic functions such as storing money and

making payments electronically for utility bills, tickets, purchasing products and

services as well as transferring money (Sharma and Kulshreshtha, 2019). According

to Singh and his partners (2017), e-wallet helps consumers have easier access to

financial services. They can save their personal and banking information and track

the history of payment. This also encourages consumers to adopt e-wallet for their

banking transactions. On the other hand, adopting e-wallet also gives consumers a lot

of benefits such as loyalty benefits, minimum interest rates and cash benefits. E-

wallet can be considered as a trigger to traditional banking because it allows

consumers to transfer money and make payments faster, more conveniently with

lower costs. The benefits of adopting e-wallet are decreasing the demand for

banknotes or cash and supporting governments with better financial transparency

(Shin, 2009). Therefore, the author can conclude that the adoption of e-wallet in our

daily life is a great advantage that can help Vietnam move toward a cashless society.

E-wallet has become an important factor in non-cash payment development strategies

in accordance with Vietnamese policies and regulations.

2.1.2. Functions of e-wallet

There are currently a lot of e-wallets in Vietnamese market with a variety of

functions. Nevertheless, most e-wallets have 4 main functions including money

transferring and receiving, money storing, e-payment making and account query.

After consumers successfully register and activate e-wallet, that e-wallet

account can receive money from many different forms such as recharging directly at

the counter of e-wallet service providers, recharging directly at the counter of the

banks having a connection with such e-wallet service providers or topping up online

from e-wallet accounts that are in the same system, topping up online from bank

accounts that have cooperated with those e-wallet providers, etc. When having money

in e-wallet account, consumers can transfer their money to other e-wallet accounts

that are in the same system or any bank accounts that are connected with such e-

wallet service providers.

Furthermore, consumers can store money in an e-wallet which is considered

as a safe and convenient storage. The amount of money recorded in e-wallet is the

same amount as the value of real money topped up or transferred.

Additionally, consumers can also make online payment as long as there is

available money in e-wallet at that time. This function is really useful because

consumers can do a lot of things with it. Consumers can easily make payment for

purchasing products or services on electronic platforms such as Tiki, Lazada, Shopee,

etc. Moreover, consumers can also make payments for utility bills such as internet,

electricity, water as well as recharge mobile phone. E-wallet can also be used to

purchase online tickets such as movie tickets, train tickets, airplane tickets which can

save time and effort for consumers. Some e-wallets also allow consumers to make

payments for booking hotels, purchasing insurance, tuition fees, etc.

Finally, for account query function, consumers can change their personal

information, passwords, look up balance and track their transaction history. This

function helps consumers feel more secure when adopting an electronic payment tool

like e-wallet.

2.1.3. E-wallets in Vietnam

Since 2008, e-wallet service has been licensed by Vietnamese government to

perform in the market. However, there were only 7 e-wallet providers in 2015 which

proves that e-wallet has suffered slow growth during the first seven years.

Considering this problem, the government has implemented many policies to

encourage the development of e-wallet in Vietnam. As a result, the number of e-

wallet providers has remarkably increased up to 21 providers in 2017. Since then, the

competition has become extremely fierce which has turned e-wallet market into a

lucrative one. A lot of promotional campaigns have been conducted to attract more

consumers which has also been considered as a “money burning” race among big e-

wallet providers. According to SBV, there have been 39 e-wallet providers in

Vietnam until October 2020. The e-wallet competition has become more aggressive

than ever. A large number of e-wallet providers and a potential market have promised

a flourish development of e-wallet in Vietnam. As reported by a survey of Cimigo,

top 3 e-wallet providers are Momo, ZaloPay and Moca which are frequently used in

Ho Chi Minh and Ha Noi City (Thai Thu, 2020). Covid-19 pandemic has negatively

affected most of industries, however, e-wallet service is the one that can gain most

benefits since people have been prone to adopting e-wallet to ensure their safety and

protect themselves. The table 2.1 shows the names of e-wallet providers in Vietnam

(until October 2020).

Table 2.1 E-wallets in Vietnam until October 2020

No. E-wallet No. E-wallet No. E-wallet

VTC Pay SmartPay 1 Napas 14 27

Moca CONNEXION 2 VNPay 15 28

FPT Wallet VitaPay 3 Momo 16 29

4 BANKPAY 17 eMonkey 30 EPay

5 WebMoney Vietnam 18 OnePay 31 ECO

6 Payoo 19 WePay 32 PayMe

7 AIRPAY 20 NganLuong 33 GPay

8 eDong 21 TrueMoney 34 VIDIVA

9 ZaloPay 22 VNPT Pay 35 Foxpay

10 VNPT Ebay 23 VinID Pay 36 Bemo

11 Movi 24 ViettelPay 37 9Pay

12 BaoKim 25 VINATTI 38 AppotaPay

13 Vimo 26 VIMASS 39 CTIN PAY

Source: Compiled by the author using SBV’s statistics (2020)

2.2. Definition of adoption intention

Adoption intention is defined as the consumers’ tendency to accept and utilize

new technologies, especially an e-wallet in this case (Chakraborty and Mitra, 2018).

Adoption intention can have other names such as usage intention or behavioral

intention in other international studies. In prior research, behavioral intention is

proved to have a correlation with actual behavior (Yiu et al., 2007; Al-Maghrabi and

Dennis, 2011; Venkatesh et al., 2012). Therefore, when investigating any behavior of

consumers, it is reasonable to conduct a research on the adoption intention. Then,

based on that result, it is easier to predict the actual behaviors of consumers.

There has been a variety of theoretical models recommended by prior

researchers for determining factors influencing the intention to adopt new

technologies such as mobile banking, e-payment, e-wallet, e-commerce, etc. Among

those, Technology Acceptance Model and Unified theory of Acceptance and Use of

Technology Model are two main models employed by most researchers to investigate

such related studies. The author will present those detailedly in the following part.

2.3. Theoretical models in determining the intention to adopt new technology

2.3.1. Theory of Reasoned Action (TRA)

Theory of Reasoned Action (TRA) was developed by Fishbein and Ajzen

(1980) to investigate the psychology field. The model proposed that individuals’

beliefs and outcome assessment influenced attitudes which in turn influenced the

intention to take an action. Subjective norms were measured by the pressure to

comply with the judgement of people who had important roles in the behavioral

intention of an individual. As a result, both the attitude toward act and subjective

norms influenced the intention to behave of an individual which also affected the

actual behavior in the end. Although the theory was widely used at that time, it had

received many criticisms for its incapability to deal with comprehensive technology

adoption research. TRA was based on the assumption that a person behaved under

full control and there were not any external constraints that influenced the behavior.

In fact, this could not happen in reality due to limited resources and unexpected

things. Therefore, TRA cannot be applied in this research but it can be used as a basis

for other theoretical models.

Figure 2.1 Theory of Reasoned Action

Source: Fishbein and Ajzen (1980)

2.3.2. Social Cognitive Theory (SCT)

Bandura (1986) developed Social Cognitive Theory (SCT) based on Social

Learning Theory of Miller and Dollard (1941). SCT was a triangular model which

presented the mutual relationships among three factors: environment factors, personal

factors and behavior. The three factors interacted and influenced each other during

an individual’s action. An individual used his cognition to evaluate the external

environment. Such evaluation could lead to a specific behavior which was dependent

on how the external environment was. The result of this behavior would affect the

individual’s evaluation for a similar behavior next time. In 1995, Compeau and

Higgins adjusted and proposed that in terms of technology, the computer usage

behavior of an individual was affected by performance-outcome expectancy,

personal-outcome expectancy, self-efficacy, affect and anxiety. The performance-

outcome expectancy meant that a person expected a good result of his behavior while

personal-outcome expectancy indicated that a person expected how his behaviors

influenced his life. Self-efficacy showed the level to which a person believed he could

perform a behavior himself. Affect expressed whether a person liked or disliked a

specific behavior while anxiety expressed the worry to perform a specific behavior.

Although this theory has been applied in many studies, experts have declared that it

should not be used in specific contexts. SCT was judged to be too general and should

be utilized in broad contexts rather than a study of technology adoption. Although the

author will not use SCT as the basis for this study, the model is still used as the ground

for other theoretical models which will be discussed later.

Figure 2.2 Social Cognitive Theory

Source: Bandura (1986)

2.3.3. Technology Acceptance Model (TAM)

Considering the increase in the new technologies, Davis (1989) proposed

Technology Acceptance Model (TAM) based on TRA model of Fishbein and Ajzen

(1980) to investigate factors influencing a person’ intention to adopt new

technologies. TAM has been widely used by researchers when conducting studies on

this field. TAM paid attention to the attitudinal clarification of the intention to adopt

new technologies. The model replaced measures of attitudes by two new measures

which were perceived usefulness and perceived ease of use. These factors reflected

the perception about features of a new technology and its potential adoption of an

individual. Perceived usefulness presented the extent to which a person believed that

adopting a new technology would help him raise his job performance. Perceived ease

of use expressed the degree to which a person believed that adopting new

technologies did not require many efforts. According to the model, the attitude was

affected by these factors which then influenced the intention to adopt and actual

adoption of new technology in the end.

Figure 2.3 Technology Acceptance Model

Source: Davis (1989)

Although TAM has been widely applied in investigating adoption behavior in

many technology fields, the model has been evaluated to have certain limitations. Sun

and Zhang (2006) indicated two main problems existing in the model. The first

problem was that the predictive power of the model was not high. After collecting the

research results from 55 journals, they found that R square of such studies was only

about 40% on average. The second problem was that the correlation among factors in

the model was incompatible in different research fields and subjects. The correlation

in such studies was not always the same as that proposed by TAM. Another

shortcoming of TAM indicated by Lee et al (2003) was that the model could be only

used to conduct a study of one specific technology, one specific subject at one specific

point of time. Therefore, Venkatesh and Davis (2000) proposed TAM2 which was an

extended model of TAM to overcome such weaknesses. During TAM existence,

perceived usefulness was demonstrated to be a strong predictor of the intention to

adopt new technology. Thus, TAM2 included additional variables including

subjective norm, image, job relevance, output quality and result demonstrability to

measure perceived usefulness. Beside perceived usefulness and perceived ease of use,

subjective norm was also another factor that affected the intention to adopt new

technology.

Figure 2.4 TAM2

Source: Venkatesh and Davis (2000)

Although TAM has been the most influential theory in investigating the

intention to adopt technologies, a lot of researchers have indicated limitations of the

model. Burton-Jones and Hubuna (2006) stated that perceived usefulness and

perceived ease of use could not measure all factors that influenced the usage intention,

especially the factors from the external environment. Therefore, the author decides

not to use TAM in this study. However, TAM will be an important ground for the

next theoretical model.

2.3.4. Unified Theory of Acceptance and Use of Technology (UTAUT)

Venkatesh and his partners (2003) realized that researchers had difficulty in

choosing a suitable model so they usually chose to combine some variables from

different models when investigating in technology fields. Considering that a lot of

variables in existing theories and models are similar in nature, Venkatesh and his

partners (2003) decided to synthesize and propose a unified model to explain the

adoption of technology. They integrated eight following theories and models to

establish a new model which was Unified Theory of Acceptance and Use of

Technology (UTAUT). The developers of UTAUT expected that future studies would

simply apply the model in studying technology fields rather than searching and

collecting constructs from a variety of theories and models.

Table 2.2 The theories and models used to propose UTAUT

Theories and models Authors

The theory of reasoned action (TRA) Fishbein and Ajzen, 1980

The technology acceptance model (TAM) Davis, 1989

Social cognitive theory (SCT) Bandura, 1986

Innovation diffusion theory (IDT) Moore and Benbasat, 1991

The theory of planned behavior (TPB) Ajzen, 1991

The model of PC utilization (MPCU) Thompson, Higgins and Howell, 1991

The motivational model (MM) Davis, Bagozzi and Warshaw, 1992

A model combining TAM and TPB Taylor and Todd, 1995a;

Taylor and Todd, 1995b (C-TAM-TPB)

Source: Venkatesh et al. (2003)

The UTAUT model proposed four main constructs including performance

expectancy, effort expectancy, social influences and facilitating conditions.

Performance expectancy was the extent to which a person believed that adopting a

technology would help him achieve benefits. Effort expectancy was the degree that a

person felt it easy to adopt a technology. Social influence was the degree that a person

thought he would adopt a technology because his important people recommended

him to do that. Facilitating condition was the extent to which a person believed that

he had support from organizational and technical infrastructure to adopt a technology.

These four constructs directly influenced behavioral intention which in turn predicted

the actual adoption behavior. Additionally, facilitating condition construct could also

predict the actual adoption behavior directly. Venkatesh et al. (2003) proved that

these four constructs explained the behavioral intention up to 70% which reflected

the appropriateness of this model in determining the factors influencing the adoption

intention of new technology. The table 2.3 describes that each construct in the

UTAUT model has been synthesized, built and developed upon which constructs in

previous existing theories and models.

Table 2.3 Origin of constructs in UTAUT model

Constructs in UTAUT Origin

Performance expectancy Perceived usefulness (from TAM/TAM2 and C-TAM-

TPB)

External motivators (from MM)

Relative advantages (from IDT)

Job-fit (from MPCU)

Outcome expectancy (from SCT)

Effort expectancy Perceived ease of use (from TAM/TAM2)

Complexity (from MPCU)

Ease of use (from IDT)

Social influences Subjective norms (from TRA, TAM2, TPB, C-TAM-

TPB)

Social factors (from MPCU)

Image (from IDT)

Facilitating conditions Perceived behavioral control (from TPB, C-TAM-TPB)

Facilitating conditions (from MPCU) Compatibility

(from IDT)

Source: Compiled by the author

Besides, there were four moderators that significantly influenced four main

effects which were age, gender, experience and voluntariness of use which was a

better development compared to TAM with no moderators. With four moderators, the

model could explain the adoption intention precisely in different contexts. UTAUT

provided a more comprehensive framework for technology adoption studies than

other previous models. Therefore, more and more researchers have chosen to adopt

this model in studying the technology field. UTAUT has been used to investigate the

intention to adopt mobile commerce (Chong, 2013; Chou, Li and Ho, 2018), mobile

payment (Wang and Yi, 2012), mobile banking services (Zhou, Lu and Wang, 2010).

Since such fields are quite relevant to e-wallet, the author believes that UTAUT will

be suitable to study e-wallet.

Figure 2.5 Unified Theory of Acceptance and Use of Technology

Source: Venkatesh et al. (2003)

On the other hand, Venkatesh et al. (2012) extended UTAUT and proposed

UTAUT2 with 3 additional new constructs which were price value, hedonic

motivation and habit. Moreover, they also eliminated the voluntariness moderator

from the model. Along with UTAUT, UTAUT2 has been widely used in a lot of

studies in technology fields. However, many studies proved that the three new

constructs usually insignificantly affected the behavioral intention. Particularly, price

value did not significantly affect the intention to adopt mobile payment (Morosan and

DeFranco, 2016) and mobile commerce (Li and Yang, 2016). Hedonic motivation

was proved to insignificantly affect the intention to accept mobile commerce (Jaradat

and Al Rababaa, 2013), adopt mobile banking services (Mahfuz, Khanam, and

Mutharasu, 2016). Habit was considered to have no significant influence on intention

to adopt mobile payment (Slade, Williams, and Dwivdei, 2013), mobile commerce

(Bendary and Al-Sahouly, 2018). Since there is too much evidence that the three new

factors have insignificant effect on adoption intention, the author decides to use

UTAUT rather than UTAUT2.

In summary, the author decides to adopt UTAUT as the theoretical model in

this thesis due to the following reasons. First, UTAUT is built upon a variety of

theories and models so it can be considered as the most effective model which has

absorbed core values of such previous ones. Secondly, Hino (2015) evaluated that

UTUAT can conceptualize mobile commerce better since it adds more constructs into

the conceptual framework of technology acceptance. Additionally, mobile commerce

is relevant to e-wallet to some extent, therefore, the author believes that UTAUT will

be the most suitable model in studying the intention to adopt e-wallet. On the other

hand, the author will not consider the effect of moderators such as age, gender,

experience, voluntariness on the adoption intention to make the model more simple

and easier. Instead, the author will focus on the relationship of key factors and

behavioral intention to gain a more effective evaluation.

2.4. Previous empirical researches on factors influencing intention to adopt e-

wallet

There have been plenty of studies investigating the factors influencing the

adoption intention of e-wallet on the world. The author will present some selected

papers which use TAM and UTAUT as theoretical models and extend the model with

some additional constructs in chronological order.

Thakur and Srivastava (2014) studied factors influencing adoption intention of

mobile wallet by three main constructs which were adoption readiness, perceived risk

and personal innovativeness. Adoption readiness was developed based on perceived

usefulness, ease of use (from TAM), social influence and facilitating conditions (from

UTAUT). Perceived risk was measured by security risk, monetary risk and privacy

risk. The research found out that adoption readiness was the most important factor

influencing the adoption intention of e-wallet. The next important factor was

perceived risk which was found to negatively influence the intention to adopt e-

wallet. It was found out that monetary risk did not influence perceived risk while both

security and privacy risk significantly influenced perceived risk. Therefore, e-wallet

providers were suggested to use secured socket layer and third-party certification to

minimize risk perception of consumers. Personal innovativeness directly affected

both adoption readiness and behavioral intention. Moreover, it was proved that the

effect of innovativeness was significantly different between users and non-users

which indicated the important role of innovativeness in the adoption intention of e-

wallet. However, the study was limited because it only focused on consumers who

were in big cities with easy access to the internet. Therefore, they suggested that

future research should pay attention to rural areas which had limited access to have

different perspectives of e-wallet adoption.

Madan and Yadav (2016) investigated adoption intention of e-wallet through

the research “Behavioral intention to adopt mobile wallet: a developing country

perspective”. They extended the UTAUT model with five new constructs including

perceived value, perceived risk, perceived trust, perceived regulatory support,

promotional benefits. The result indicated that performance expectancy, social

influence, facilitating conditions, perceived risk, perceived trust, perceived value,

perceived regulatory and promotional benefits had great significant influence on the

intention to adopt mobile wallet. The only factor that did not affect behavioral

intention was effort expectancy which was extremely different from the UTAUT

model and previous research. The reason for this difference was explained by the

authors that consumers did not have many difficulties in dealing with mobile wallet

so they did not require much effort to adopt e-wallet. On the other hand, Madan and

Yadav (2016) stated that the sample of the study might suffer selection bias since it

only had 210 respondents with different demographic groups in a disproportionate

manner. Moreover, they also declared that the study only focused on consumers’

viewpoint while other stakeholders in the mobile wallet industry such as mobile

wallet providers, merchants, technology providers, financial institutions and

government also played important roles in developing mobile wallet adoption.

Therefore, they recommended that future research should pay attention to these

stakeholders to have new perspectives regarding this field.

Chakraborty and Mitra (2018) investigated the research “A study on Consumers

Adoption Intention for Digital Wallet in India” using constructs based on UTAUT

and some previous research. The study indicated that perceived usefulness, perceived

ease of use, social influence, perceived self-efficacy, personal innovativeness and

individual playfulness, attractiveness of alternatives and perceived value all

significantly influenced the intention to adopt digital wallets in India. Some

constructs that were not in the original UTAUT model such as perceived self-

efficacy, personal innovativeness, individual playfulness, attractiveness of

alternatives and perceived value still played important roles in significantly affecting

consumers’ adoption intention of digital wallet. All independent variables explained

81.7% the variance of adoption intention which meant the model had a great

significance. Additionally, based on the cluster analysis, three segments of customers

with their different set of criteria were revealed which helped digital wallet providers

implement different strategies for different customer segments to gain optimal

outcomes. However, the research had a limited sample size with 150 responses which

could not generalize the behavioral intention of all consumers in Indian. Moreover,

the authors also stated that there might be other individual and market-oriented factors

that could affect consumers’ intention to adopt digital wallet. They suggested that

future research should explore other constructs to provide new insight on digital

wallet adoption intention and researchers should pay attention to continuance

intention as well as satisfaction to gain different perspectives regarding digital wallet.

Sharma and Kulshreshtha (2019) continued to study mobile wallet adoption in

India through the research “Mobile wallet adoption in India: An analysis”. The

model proposed nine factors including convenience, safety, complexity, trialability,

compatibility, service quality, privacy, availability of information and ease of use.

However, only four factors had significant influences on adoption intention which

were convenience, ease of use, compatibility and availability information. The study

revealed that consumers found it difficult to adopt mobile wallet. Therefore,

convenience and ease of use would play important roles in encouraging consumers’

intention to adopt mobile wallet. Additionally, mobile wallet was considered useful

when compatibility and availability information were conveyed to consumers in

vernacular languages. Hence, mobile wallet providers should pay more attention to

language features when designing mobile wallet apps to enhance mobile wallet

adoption. On the other hand, it was also found that young people preferred mobile

wallet adoption rather than other age groups. This finding is easy to understand

because young people are more willing to access new things and more capable to

adopt such a technical tool like mobile wallet. Thus, the authors suggested that mobile

wallet providers should bring more innovative features in mobile wallets to attract

more young consumers. Similar to other research, the limitation of this study was

small sample size which could not generalize the whole Indian consumers. The

authors suggested that future research should conduct a comparative study between

mobile wallet adoption in metro and non-metro cities to gain new insight regarding

this topic.

Mahwadha (2019) conducted a research on “Behavioral intention of young

consumers towards e-wallet adoption: An empirical study among Indonesia users”.

The model proposed that perceived usefulness, perceived trust and attitude toward

using would affect behavioral intention to use e-wallet. Based on the research result,

there were a lot of significant relationships among these factors. First, all three factors

were proved to have a positive and significant impact on adoption intention of e-

wallet. On the other hand, perceived trust significantly affected perceived usefulness

while perceived usefulness also influenced attitude toward using as well. E-wallet

providers and banks could use this research as references to improve facilities of the

services, security of transactions and personal data. However, the limitation of this

research was that it was only conducted in Surabaya, East Java-Indonesia so it could

not generalize the intention to adopt e-wallet of all Indonesian young consumers.

Tun (2020) tried to study mobile wallet adoption intention in Myanmar through

the research “An Investigation of Factors Influencing Intention to Use Mobile Wallets

of Mobile Financial Services Providers in Myanmar”. He proposed the model with

six constructs influencing the usage intention which were perceived usefulness,

service quality, user satisfaction, social influence, facilitating conditions and trust.

Based on the result, it was found out that only trust and perceived usefulness had

significant effects on adoption intention, especially trust. He believed that trust would

be the major factor influencing consumers’ intention to adopt mobile wallet since this

country had suffered a terrible financial crisis. Moreover, he stated that when

consumers perceived that mobile wallet was much more beneficial than other kinds

of payment methods, the adoption of mobile wallet would increase significantly.

However, services quality, satisfaction, social influence and facilitating condition did

not have any influence on behavioral intention in this study which is a quite surprising

result compared to previous research. On the other hand, Tun (2020) believed that his

study did not cover enough factors affecting adoption intention of mobile wallet. He

suggested that future research should adopt more constructs such as perceived risk,

perceived value and perceived self-efficacy to study mobile wallet more precisely.

Moreover, since the study was conducted during Covid-19 pandemic period, the

sample size was quite small which was a considerable limitation of the research.

Another limitation of the research was that it only focused on investigating potential

users. Therefore, Tun (2020) suggested other researchers should pay attention to

regular users to gain a different perspective of mobile wallet adoption.

In Vietnam, there are limited studies on e-wallet adoption intentions. The author

can only mention 2 studies on this field. The first one is “Factors influencing

consumers’ intention to adopt e-wallet in Vietnam” studied by Nguyen Thi Linh

Phuong (2013). She adopted the UTAUT model and extended the model with

perceived credibility, perceived costs, government support and utility community.

The first three factors were adapted from previous research on e-commerce while

utility community were adapted from the suggestion of an e-wallet professor in

Vietnam. Based on the result, all factors including performance expectancy, effort

expectancy, social influence, facilitating conditions, perceived credibility, perceived

costs, government support and utility community all significantly influence the

adoption intention of e-wallet in Vietnam with R square at 64.5%. The measurement

scale of this research was based on the results of interviews with professors and group

discussions to propose a questionnaire which was close to the current reality of e-

wallet adoption in Vietnam. This has been considered as one of the first research on

e-wallet in Vietnam which has built a solid ground for future research on this field.

However, the limitations of this research were that the sample size was small and

respondents mostly lived in Ho Chi Minh City which could not represent the whole

Vietnamese users. Therefore, the author suggested that future research should expand

the scope of the survey so that the study could provide more reliable and accurate

results.

Tran Phi Hoang, Tran Anh Tuan, Nguyen Thi Thanh Phuong (2020) conducted

research on “Factors Affecting the Intention of Using Electronic Wallets of

Vietnamese Tourists: a Case in Ho Chi Minh City”. According to the research, there

were five factors influencing usage intention which were perception of usefulness,

perception ease of use, perception of risk, attitude and social influence. The research

result indicated that all above factors had significant effects on the intention to adopt

e-wallet of tourists in Vietnam. The study indicated that consumers were aware of the

benefits brought by an e-wallet but they were also scared of the potential risks.

Therefore, the study recommended that e-wallet providers should meet high standards

of technical structures, modern communication systems and information security to

enhance consumers’ trust in e-wallet services. Moreover, the authors suggested that

e-wallet providers should have many activities to enhance tourists’ awareness about

the usefulness of e-wallet so that it could create a long-term adoption of tourists.

Additionally, it was important to develop connections with distribution

intermediaries such as banks, restaurants, hotels, airlines so that visitors could have

the best experiences with e-wallet services. On the other hand, the limitation of this

research was that it only investigated tourists in Ho Chi Minh City which was a small

scope. Therefore, the authors suggested that future research should be conducted in

other famous tourist attractions such as Da Lat, Da Nang, Vung Tau, Hue, Nha Trang,

etc.

In summary, studies of e-wallet in Vietnam are too restricted compared to a

number of studies with various models and constructs on the world. Therefore, the

author decides to conduct research on e-wallet to close this gap. Besides the UTAUT

model, the author intends to add three new constructs. These are trust, perceived risk

and self-efficacy which have been mentioned and proved to have significant

influences on intention to adopt e-wallet in the above studies (Thakur and Srivastava,

2014; Madan and Yadav, 2016; Chakraborty and Mitra, 2018; Tun, 2020).

2.5. Proposed research model and research hypotheses

2.5.1. Proposed research model

Based on the theoretical models and previous empirical studies on e-wallet,

the author decides to employ the UTAUT model developed by Venkatesh et al. (2003)

as a basic ground. Moreover, the model is also extended with trust, perceived risk and

self-efficacy for better predicting the adoption intention of e-wallet.

The official proposed model is illustrated in the figure 2.6.

Figure 2.6 Model proposed by the author

Performance expectancy

Effort expectancy

Social influence

Adoption Intention Facilitating condition

Trust

Perceived risk

Self-efficacy

Source: Compiled by the author

2.5.2. Research hypotheses

2.5.2.1. Performance expectancy

Performance expectancy is defined as the degree that a technology will benefit

consumers in performing some tasks (Venkatesh et al., 2003). In this case, it can be

considered as the degree that a person believes that adopting an e-wallet to make

payment will enhance and accelerate his performance in conducting daily

transactions. (Madan and Yadav, 2016). Venkatesh and his partners (2003) stated that

performance expectancy is the most important construct in the UTAUT model.

Several studies also adopt performance expectancy to predict adoption intention of e-

wallet and discover that it definitely has a positive significant impact on the intention

to adopt e-wallet (Schierz et al., 2010; Kim et al., 2010; Pham and Ho, 2014; Slade

et al., 2015; Yan and Yang, 2015). Thus, the first hypothesis is proposed as following:

H1: Performance expectancy positively influences the intention to adopt e-wallet

2.5.2.2. Effort expectancy

Effort expectancy is defined as the degree of ease in accordance with adopting

a technology (Venkatesh et al., 2003). In this situation, it can be considered as the

degree a person believes that adopting e-wallet does not require much effort and e-

wallet is easy enough to be adopted in his daily life (Madan and Yadav, 2016).

Venkatesh and his partners (2013) suggests that effort expectancy is also the next

important construct which cannot be eliminated from the model. Many researchers

have proved that effort expectancy positively affects the adoption intention of mobile

commerce, especially e-wallet (Chong, 2013; Megadewandanu, 2016; Chou, Li and

Ho, 2018). Therefore, the second hypothesis is proposed as following:

H2: Effort expectancy positively influences the intention to adopt e-wallet

2.5.2.3. Social influence

Social influence is defined as a person’ adoption of e-wallet will depend on

the opinions of people who are important to that person (Venkatesh et al., 2003). In

this thesis, social influence is the extent to which a person perceives that adoption of

e-wallet was based on recommendations from important people such as family,

relatives, friends, colleagues. The opinion of such people can influence the decisions

whether e-wallet should be continued to use or be stopped using. Social influence has

been demonstrated as a prime determinant of adopting technology services provided

by mobile device, especially e-wallet (Liébana-Cabanillas et al., 2014; Oliveira et al.,

2016; Lwin and Thanabordeekij, 2019; Soodan and Rana, 2020). Based on previous

research, it is found out that consumers are more likely to adopt e-wallet when there

are many important people suggesting them to adopt. Hence, the third hypothesis is

as following:

H3: Social influence positively influences the intention to adopt e-wallet

2.5.2.4. Facilitating condition

Facilitating condition is defined as the degree to which a person perceives that

there are supports from an organizational and technical structure to help him adopt a

new technology (Venkatesh et al., 2003). In this case, facilitating condition is

understood as the perception of a person to have access to necessary resources

required for an effective adoption of e-wallet. It plays an important role in generating

a favorable environment for financial transactions that builds and enhances behaviors

of consumers (Chawla and Joshi, 2019). Many studies have proved that facilitating

condition has a positive effect on the adoption intention of e-wallet and similar

technologies such as mobile banking, mobile commerce (Yang, 2010; Amoroso and

Magnier-Watanabe, 2012; Chong, 2013; Lwin and Thanabordee Kij, 2019; Soodan

and Rana, 2020). Then, the fourth hypothesis is proposed as following:

H4: Facilitating condition positively influences the intention to adopt e-wallet

2.5.2.5. Trust

Trust is the extent to which a person believes that e-wallet service providers

are trustworthy and have reliable security and privacy policies (Madan and Yadav,

2016). Without trust, it is very hard for e-payment, especially e-wallet to gain broader

adoption (Linck et al., 2006). Trust increases the confidence of a person when

adopting new innovation like e-wallet since he is not afraid that his personal

information and money are robbed without his knowledge. Trust is recognized as a

strong predictor to determine adoption intention of e-wallet in a lot of previous

research (Dahlberg et al., 2003; Shin, 2009; Chong et al., 2012; Amoroso and

Magnier-Watanabe, 2012; Xin, 2013; Pham and Ho, 2014). It is expected that

consumers who have trust in service providers are more likely to adopt the service

which is e-wallet in this case. Thus, the fifth hypothesis is proposed as following:

H5: Trust positively influences the intention to adopt e-wallet

2.5.2.6. Perceived risk

Perceived risk is considered as any financial, social, product-associated risks

that a person has to suffer when conducting online transactions (Wu and Wang,

2005). These days, mobile phones or smartphones keep a lot of personal information

which accelerates the matter of security and privacy risk in making any transaction

via e-wallet (Madan and Yadav, 2016). People may be concerned that their money or

personal information might be transferred to a third party when they conduct online

transactions via mobile banking, mobile wallet services (Ramdhony and Munien,

2013; Hanafizadeh et al., 2014). Therefore, many studies have added this factor and

realizes that perceived risk have a significant and negative impact on the intention to

adopt mobile banking as well as e-wallet (Amoroso and Magnier-Watanabe, 2012;

Pham and Ho, 2014; Liébana-Cabanillas et al., 2014; Slade et al., 2015). Hence, the

sixth hypothesis is proposed as following:

H6: Perceived risk negatively influences the intention to adopt e-wallet

2.5.2.7. Self-efficacy

Self-efficacy is defined as the confidence that a person has when adopting a

new innovation (Koksal, 2016). Self-efficacy is taken from the Social Cognitive

Theory of Bandura (1986) mentioned above. In the context of e-wallet, self-efficacy

means that when a person believes that he has necessary knowledge, skills and

abilities to use e-wallet, he is more likely to make an attempt to adopt e-wallet on his

own. Previous research indicated that self-efficacy is one of the most important

factors positively influencing the adoption intention of technology services,

especially e-wallet (Dinev et al., 2009; Makanyeza, 2017; Singh and Srivastava,

2018; Chakraborty and Mitra, 2018). Thus, the final hypothesis is proposed as

following:

H7: Self-efficacy positively influences the intention to adopt e-wallet

Summary of Chapter 2: In this chapter, the author displays an overview of e-wallet

situation in Vietnam. Then she presents theoretical models and previous studies on

the e-wallet field. Based on them, the author selects and develops the most suitable

model and constructs in this context. She draws a proposed model and explains each

construct used, then indicates the relevant hypotheses. The next chapter will discuss

the method of data collecting and data analysis.

CHAPTER 3: METHODOLOGY

3.1. Research procedure

The research includes two main stages which are preliminary and official research.

Figure 3.1 Research procedure

Define the research objectives, aims, scope

Review previous models and research

Propose the model and develop hypotheses

Conduct short interviews with some users Preliminary research

Design pre-measurement scale

Conduct pilot survey

Design the official measurement scale

Design the official questionnaire

Conduct the survey and collect data

Conduct data analysis

Official research

Explain the outcomes

Make some recommendations

Source: Compiled by the author

For preliminary research, the author used a qualitative method to understand

this topic deeply. Firstly, the author defined the aims and objectives of the research,

then indicated the scope of the research due to limited time and resources. Secondly,

it was important for the author to synthesize all theoretical models and previous

studies about e-wallet so that the author could visualize an overall picture of e-wallet

as well as factors influencing adoption intention of e-wallet. Based on such

knowledge, the author could propose her own model together with hypotheses. The

first three steps had already been carried out in Chapter 1 and 2. After that, the author

conducted short interviews with some e-wallet users to gain their perception of e-

wallet. Then, based on the measurement items adapted from previous researchers, the

authors designed a pre-measurement scale. Next, the author conducted a pilot survey

to examine whether respondents could clearly understand the meaning of each item.

After collecting the answers and opinions of people in the interviews and responses

in the pilot survey, the author modified and developed the official measurement scale.

Finally, the author designed the official questionnaire which was used for the official

survey.

For official research, the quantitative method was applied to study this topic

clearly and detailedly. The author collected data by conducting an online survey with

e-wallet consumers in Vinh Long province. After that, the author used SPSS 20.0

software to analyze collected data and examine the hypotheses. Some data analysis

methods which were used in this study were Descriptive statistics, Cronbach Alpha,

Exploratory Factor Analysis, Multiple linear regression, Independent T-test and

Analysis of variance. Then, the author explained research outcomes and compared

them with previous research to make some evaluations. Finally, the author suggested

some recommendations which would be useful for e-wallet service providers to

expand e-wallet adoption in Vinh Long province.

3.2. Preliminary research

3.2.1. Conducting short interviews

The purpose of these interviews is to understand the perception of consumers

about the e-wallet adoption intention. The author conducted face to face interviews

with 10 people who lived in Vinh Long province and had already used e-wallet for a

certain period of time. Each interview took about 10 minutes in which the author gave

interviewees open questions about factors investigated in this study to recognize their

perception about these factors including performance expectancy, effort expectancy,

social influence, facilitating conditions, trust, perceived risk, self-efficacy. The

questions for each factor are described as followings:

• How do you feel about the usefulness of e-wallet in your daily life?

• How do you feel about the effort you have to make to adopt e-wallet?

• Who influences your adoption of e-wallet behavior?

• What resources do you need to adopt e-wallet?

• On what aspects do you trust your e-wallet service providers?

• How do you feel about the risks when adopting an e-wallet?

• How do you believe in yourself when adopting an e-wallet?

All of the interviewees evaluated that all questions are meaningful and

necessary when asking about e-wallet usage which implies that all relevant factors

are essential to study adoption of e-wallet. Most of the answers are quite similar to

the measurement items. However, based on these answers, the author believes that

some items will need to add explanations to be more specific and clearer.

Here are some answers that the author can use to adjust the measurement

items. With question number 1, some benefits of e-wallet adoption were

recommended such as easier and more convenient payment, more discounts and

refunds. For question number 3, there were 7 out of 10 people saying that their

relatives and friends were the ones who influenced their adoption of e-wallet while

the rest said that they were affected by their superiors and professors. For question

number 4, all respondents suggested smartphones, tablets and the internet were the

necessary resources to adopt an e-wallet.

3.2.2. Pilot survey

After the pre-measurement scale was completed based on previous studies, the

author conducted a pilot survey to examine the understanding of respondents about

measurement questions. There were 10 people participating in this test who lived in

Vinh Long province and adopted at least one e-wallet. 6 out of 10 respondents

suggested that the authors should give examples to clarify what were the efficiency

of the payment process and the benefits beyond payment. Therefore, the author

explained the efficacy of the payment process as faster, easier and more convenient

payment while benefits beyond payment were discounts, refunds in accordance with

the answers in the above interview. Moreover, 8 out of 10 respondents were confused

with questions measuring social influence. They could not determine who were

important to them, who influenced their behaviors, whose opinions they valued.

Based on the results of above interview, the author suggested relatives, friends,

colleagues could be the ones who were important to them or influenced their

behaviors while supervisors and professors could be the ones that respondents valued

their opinion. Additionally, 7 out of 10 respondents had problems in understanding

what were necessary resources to adopt an e-wallet. Thus, the author gave examples

of resources which included smartphones, tablets based on the outcome of the

interview. Through the author’s explanation, respondents in the official survey can

understand such questions and easily answer them. The official measurement scale

which was built based on previous studies as well as such interviews and the pilot

survey are described in the next section.

3.2.3. Official measurement scale building

3.2.3.1. Measurement items for Performance expectancy

Performance expectancy is considered as the degree that adopting a

technology, or e-wallet in this case enhances the performance of a person in doing

some tasks (Venkatesh et al., 2003). In this research, the author borrows measurement

items of this construct from Morosan and DeFranco (2016) because she perceives

that they can better represent peculiarities of performance expectancy. Moreover,

based on the above interviews and pilot survey, the author also adds some examples

for PE1 and PE3 to make them easier to understand.

Table 3.1 Measurement scale for Performance expectancy

Code Original Scale Adjusted Scale

PE1

Using mobile payments would increase the efficiency of my hotel stay Using e-wallet would increase the efficiency of my payment process (faster, easier and more convenient payment)

PE2

Using mobile payments would allow me to make more accurate purchases, reservations in hotels Using e-wallet payments would allow me to track the payment process more accurately

PE3 the hotel stay

Using e-wallet would allow me to obtain benefits beyond the payment (vouchers, discounts, refunds)

Using mobile payments would allow me to obtain benefits (for beyond example, using a preferred credit card)

PE4

Overall, I believe that mobile payments are useful when staying in hotels Overall, I believe that e-wallet is useful when making payment for products/service

Source: Compiled by the author using the scale of Morosan and DeFranco, 2016

3.2.3.2. Measurement items for Effort expectancy

Effort expectancy is the extent to which adopting technology does not require

much effort (Venkatesh et al., 2003). In this research, the author adopts the

measurement scale of UTAUT2 model (2012) to determine effort expectancy because

she believes that it will be more precise compared to that in UTAUT model (2003)

due to its latest version. The author has some adjustments on words to make it suitable

in the context of e-wallet.

Table 3.2 Measurement scale for Effort expectancy

Code Original Scale Adjusted Scale

Learning how to use mobile Internet Learning how to use e-wallet is easy EE1 is easy for me for me

My interaction with mobile Internet My interaction with e- wallet would EE2 is clear and understandable be clear and understandable

EE3 I find mobile Internet easy to use I find e-wallet easy to use

It is easy for me to become It is easy for me to become skillful at EE4 skillful at using mobile Internet using e-wallet

Source: Compiled by the author using the scale of Venkatesh et al., 2012

3.2.3.3. Measurement items for Social influence

Social influence means that opinions of important people will influence the

adoption intention of e-wallet (Venkatesh et al., 2003). The author continues to use

the measurement scale of Venkatesh et al. (2012) for this construct due to the updated

characteristics of this model. On the other hand, the author will add some

explanations for SC1, SC2 and SC3 to clarify the mentioned people so that

respondents will not misunderstand the statement.

Table 3.3 Measurement scale for Social influence

Code Original Scale Adjusted Scale

People who are important to me People who are important to me

SC1 think that I should use mobile (relatives, friends, colleagues) think

Internet that I should use e-wallet

People who influence my People who influence my behavior

SC2 behavior think that I should use (relatives, friends, colleagues) think

mobile Internet that I should use e-wallet

People whose opinions that I People whose opinions that I value

SC3 value prefer that I use mobile (superiors, professors) prefer that I use

Internet e-wallet

Source: Compiled by the author using the scale of Venkatesh et al., 2012

3.2.3.4. Measurement items for Facilitating condition

Facilitating condition is the degree to which a person perceives that there are

available organizational and technical structures supporting him to adopt a new

technology or e-wallet in this case (Venkatesh et al., 2003). The author still uses the

scale from UTAUT2 of Venkatesh et al. (2012) for this construct. On the other hand,

based on the interviews and pilot survey, the author decides to make a small

adjustment to FC1. As the author considers, the word “resources” is too general to

determine so it needs to be given some examples to interpret the meaning of that

word.

Table 3.4 Measurement scale for Facilitating condition

Code Original Scale Adjusted Scale

FC1 I have the resources necessary to use mobile Internet I have the resources necessary to use e wallet (for example: smartphone, tablet)

FC2 I have the knowledge necessary to use mobile Internet I have the knowledge necessary to use e- wallet

is compatible with other FC3 Mobile Internet is compatible with other technologies I use E-wallet technologies I use

FC4 I can get help from others when I have difficulties using e-wallet I can get help from others when I have difficulties using mobile Internet.

Source: Compiled by the author using the scale of Venkatesh et al., 2012

3.2.3.5. Measurement items for Trust

Trust is the extent to which a person perceives that e-wallet service providers

are trustworthy regarding security and privacy policies (Madan and Yadav, 2016).

Since the original UTAUT does not include trust construct, the author has to borrow

it from a research on adoption of e-payment in restaurants (Khalilzadeh et al., 2017)

and adjust some words to make it suitable in the context of e-wallet.

Table 3.5 Measurement scale for Trust

Code Original Scale Adjusted Scale

T1 I believe mobile payment service providers keep their promise I believe e-wallet service providers keep their promise

T2 I believe e-wallet service providers keep customers' interests in mind I believe mobile payment service providers keep customers' interests in mind

T3 I believe mobile payment service providers are trustworthy I believe e-wallet service providers are trustworthy

I believe mobile payment service providers will do everything to secure the transactions for users I believe e-wallet service providers will do everything to secure the transactions for users

Source: Compiled by the author using the scale of Khalilzadeh et al., 2017

3.2.3.6. Measurement items for Perceived risk

Perceived risk is considered as any risk that a person has to suffer when having

online transactions (Wu and Wang, 2005). The author continues to use the

measurement scale of Khalilzadeh et al. (2017) for perceived risk. Moreover, the

author also changes some words to make the scale suitable in the context of e-wallet.

Table 3.6 Measurement scale for Perceived risk

Code Original Scale Adjusted Scale

The probability that something will The probability that something will

PR1 go wrong with the performance of go wrong with the performance of

mobile payment is high e-wallet is high

Mobile payment might not perform E-wallet might not perform well

PR2 well and create problems with my and create problems with my

payment process in restaurants payment process during purchasing

The chances of using the mobile The chances of using the e-wallet

PR3 payment and losing control over my and losing control over my personal

personal information privacy is high information privacy is high

My signing up and using mobile My signing up and using e-wallet

payment would lead me to a loss of would lead me to a loss of privacy

PR4 privacy because my personal because my personal information

information would be used without would be used without my

my knowledge knowledge

Source: Compiled by the author using the scale of Khalilzadeh et al., 2017

3.2.3.7. Measurement items for Self-efficacy

Self-efficacy is the confidence of a person to adopt new innovation, especially

e-wallet in this case (Koksal, 2016). The measurement scale for SE is borrowed from

the study of Makanyeza (2017) who studied the intention to adopt mobile banking

services. Therefore, the author needs to adjust some words so that the scale can be

used in the context of e-wallet.

Table 3.7 Measurement scale for Self-efficacy

Code Original Scale Adjusted Scale

I have confidence to use mobile I have confidence to use e-wallet

SE1 banking even if there is no one around even if there is no one around to

to show me how to do it show me how to do it

I easily understand how mobile I easily understand how e-wallet SE2 banking works works

I feel comfortable using mobile I feel comfortable using e-wallet on SE3 banking on my own my own

Source: Compiled by the author using the scale of Makanyeza, 2017

3.2.3.8. Measurement items for Adoption intention

Adoption intention is the consumers’ propensity to accept and utilize new

technologies, especially an e-wallet in this case (Chakraborty and Mitra, 2018). The

author decides to adopt the measurement scale of Venkatesh et al. (2012) to study

this construct. Some words are adjusted to make the scale suitable in the context of

e-wallet.

Table 3.8 Measurement scale for Adoption intention

Code Original Scale Adjusted Scale

I intend to continue using mobile I intend to continue using e-wallet AI1 Internet in the future in the future

I will always try to use mobile Internet I will always try to use e-wallet in AI2 in my daily life my daily life

I plan to continue to use mobile I plan to continue to use e-wallet AI3 Internet frequently frequently

Source: Compiled by the author using the scale of Venkatesh et al., 2012

3.2.4. Official questionnaire

The questionnaire is developed based on previous studies with some

modifications to make it suitable in the context of this thesis. For the purpose of

investigating consumers in Vinh Long province, the questionnaire will be translated

from English into Vietnamese so that respondents can understand the questions and

be more willing to give answers. The translation is examined by the author’s

supervisor to ensure the correctness.

There are four main parts in the questionnaire. The first part includes 3 filtering

questions so that the author can eliminate the inappropriate responses. Respondents

who cannot meet the standards have to stop the survey and only the qualified ones

will have the chance to continue the survey. Therefore, the author can gain reliable

data which leads to an accurate result.

The second part includes 3 questions about e-wallet adoption behaviors so that

the author can have a general understanding about the experience and habit of

respondents. These questions are about the time period of e-wallet adoption, names

of adopted e-wallets and the purposes of adopting e-wallet.

The third part includes 29 statements to evaluate factors influencing the e-

wallet adoption intention based on a 5-point Likert scale. For each statement, a

respondent has to choose his level of agreement between 1 (strongly disagree) and 5

(strongly agree). This type of scale is usually adopted by quantitative research and is

appropriate with the statistical method of data analysis which will be discussed later.

The statements are developed based on the previous studies, short interviews and pilot

survey which are discussed in the above section.

The final part includes 5 questions about personal information such as gender,

age, education level, occupation and income. This part is put in the end of the

questionnaire so that respondents can participate in the beginning with interesting

questions and finish the survey with basic demographic questions which do not

require high cognitive ability.

The detail questionnaire is displayed in the Appendix 1.

3.3. Official research

3.3.1. Method of data collection and sampling

The method of collecting primary data is online survey utilizing Google Form

link. The author distributed the link to target respondents through Zalo, Facebook

during October 2020. Particularly, only people who live in Vinh Long province and

adopt at least one e-wallet are allowed to participate in the survey. The reasons for

this selection were explained in Chapter 1.

Since the population is too large, the author must rely on sampling technique

which is non-probability convenient sampling in this thesis. This type of sampling

method is widely used by most researchers because it is fast, inexpensive, easy and

the subject is available. The author can approach a collection of subjects who are easy

to access and are willing to answer the questionnaire such as her relatives, friends and

acquaintances.

Since this research adopts Exploratory Factor Analysis, it is required that the

sample size must be at least 3-6 times the observed variables (Cattell, 2012). There

are 29 observed variables, therefore, the minimum sample size of this research must

be from 87 to 174. Bollen (1989) suggested the principle for collecting data is 5:1

which means the sample size must be at least 5 times observed variables. With 29

observed variables, it must obtain at least 145 responses in this thesis. For regression

analysis, Green (1991) proposed that the minimum sample size should be 50 + 8*n

(n is the number of independent variables). This study has 7 independent variables,

therefore, the sample size should be at least 106.

3.3.2. Methods of data analysis

After collecting data, the author cleans them by eliminating the inappropriate

responses. Then, qualified data will be processed by the software SPSS 20.0 for the

next analysis steps.

3.3.2.1. Descriptive statistics method

Descriptive statistics are used to describe the basic characteristics of the

collected data which simply summarize the sample and the measures used in the

study. For demographic data, descriptive statistics will be presented in ratio to better

visualize the features of respondents. On the other hand, the outcome of this method

for measurement data will be exhibited in the maximum, minimum, mean value and

standard deviation to generally evaluate respondents’ perception of the constructs

used in the study.

3.3.2.2. Cronbach Alpha’s coefficient

Cronbach Alpha is a measure of internal consistency, or a measure of scale

reliability in other words. The purpose of Cronbach Alpha is to examine whether or

not such observed variables measure the same constructs. The contribution level of

such observed variable to a certain construct is evaluated by Corrected Item – Total

Correlation which allows to eliminate that variable from the model. Nunnally and

Bernstein (1995) proposed that any scale which has Cronbach Alpha’s coefficient

equal or more than 0.6 is acceptable and any observed variable which has Corrected

Item – Total Correlation equal or more than 0.3 is acceptable. An observed variable

should be considered to be eliminated from the model when it has a Corrected item -

Total correlation below 0.3 or Cronbach Alpha’s coefficient after eliminating that

variable is higher than the current one.

3.3.2.3. Exploratory Factor Analysis (EFA)

Exploratory Factor Analysis (EFA) is a statistical technique which aims to

reduce a collection with a number of inter-correlated observed variables to a new

collection with fewer variables which are considered as factors (Hair, 2010). Instead

of studying a variety of variables, a researcher can pay attention to only key factors

which can save a lot of time and effort. There are some required indicators to evaluate

the appropriateness of adopting EFA in the model. The first thing is Kaiser – Meyer

- Olkin (KMO) which measures sampling adequacy for each variable in the model

and for the whole model. Kaiser (1974) indicated that if KMO is nearly 1, EFA is

appropriate for the study and if KMO is below 0.5, EFA should not be adopted in the

study. Therefore, the acceptable range of KMO is 0.5 <= KMO <= 1. Bartlett’s test

is used to examine the hypothesis whether the correlation matrix is an identity matrix

in which there is no correlation among variables. If the significance level is below

0.05, the hypothesis will be rejected which means variables are correlated and implies

that EFA is appropriate in this study. The author decides to adopt Principle

Component analysis to determine the correlation between observed variables and

factors. Eigenvalue is used to determine the number of factors in the study. Only

factors with eigenvalue more than 1 are kept in the model. Total variance explained

indicator must be equal or more than 50% to guarantee the appropriateness of EFA

in the model (Gerbing and Anderson, 1988). Moreover, the author uses Varimax

rotation to test the correlation among factors. Factors loadings are used to determine

the strength of the relationship between observed variables and factors which should

be equal or more than 0.5 (Hair, 2010).

3.3.2.4. Pearson correlation analysis

Pearson correlation analysis is the technique to examine the linear correlation

between independent variables and dependent variables which are required before

conducting regression analysis. If the absolute Pearson’ coefficient is closer to 1, the

correlation between two variables is stronger. This thesis considers the acceptable

correlation with absolute Pearson's coefficient more than 0.3 and significance level

less than 0.05 in accordance with the study of Nguyen Dinh Tho (2011). On the other

hand, Pearson correlation analysis also helps the author recognize the

multicollinearity issue in the model when there is a high correlation between two

independent variables. In this case, the author will check multicollinearity in the

regression analysis using Variance inflation factor (VIF).

3.3.2.5. Multiple linear regression analysis

The author conducts multiple linear regression analysis to study the

relationship between influencing factors and adoption intention of e-wallet of

consumers in Vinh Long province. The author builds a regression equation using R-

square to evaluate the appropriateness of the equation with data and adjusted R-square

to prevent exaggeration of R-square in the model. Moreover, F-Test is adopted to

examine the suitability of the model. If significance level is less than 0.05, it is proved

that the model is significantly appropriate (Hoang Trong, Chu Nguyen Mong Ngoc,

2008).

The independent variables in this study are factors adapted from the EFA step

and the dependent variable is the adoption intention of the e-wallet. The author tests

hypotheses about the relationship between factors and adoption intention by t-test. If

the significance level of an independent variable is equal or lower than 0.05, it can be

inferred that such variable significantly affects the dependent variable and the related

hypothesis is accepted. On the contrary, such hypothesis will be rejected.

The author also uses VIF to test whether there is multicollinearity in the model.

VIF should be lower than 2 to ensure that multicollinearity does not happen in this

case (Nguyen Dinh Tho, 2011). Beside multicollinearity, the author also tests some

assumptions including linearity, normal distribution and autocorrelation of residuals

to guarantee that the regression model will not violate them.

3.3.2.6. Independent T-test and Analysis of Variance (ANOVA)

Independent T-test and Analysis of Variance (ANOVA) are used to test the

influence of demographic factors on the adoption intention of e-wallet. This aims to

determine whether people who belong to different groups in terms of gender, age,

educational level, occupation, income have different adoption intentions of e-wallet.

Independent T-test is applied when there are only two groups in a certain

demographic variable like gender. For Levene Test, if the significance level is less

than 0.05, it is indicated that variance of two groups are different and significance

level at Equal variances not assumed will be applied. Conversely, if the significance

level is equal or more than 0.05, it is indicated that there is no difference in the

variance of two groups and significance value at Equal variances assumed will be

applied. For independent T-test, significance level which is determined in Levene

Test will be compared with critical significant level (usually 0.05). If significance

level is less than 0.05, there is significant difference in mean of two groups while if

it is equal or more than 0.05, no significant difference in mean between two group

exits.

ANOVA is applied when there are more than 2 groups in demographic

variables such as age, educational level, occupation and income. Levene test is used

to examine whether there are any equal variances among groups. If significance level

in this test is equal or less than 0.05, variances are not equal which implies that

ANOVA cannot be applied. If it is more than 0.05, variances are equal which

indicates that ANOVA can be applied in this case. For ANOVA test, if significance

level is equal or less than 0.05, there is enough evidence to prove that there is a

significant difference among groups. On the contrary, if significance level is more

than 0.05, there is not enough evidence to prove the existence of difference among

groups.

Summary of Chapter 3: In this chapter, the author displays the research procedure

with two main stages including preliminary research and official research. In

preliminary research, the author describes how the interviews and pilot survey were

conducted, how the measurement scale and questionnaire were designed. In official

research, the author describes the method of data collection and sampling as well as

method of data analysis including Descriptive statistics, Cronbach Alpha, EFA,

Pearson analysis, Multiple linear regression, Independent T-test and ANOVA. The

outcome of these analyses will be presented in the following chapter.

CHAPTER 4: RESEARCH RESULTS

4.1. Descriptive statistics analysis

The questionnaire was distributed to respondents during October 2020 via

Google Form and 227 responses were collected during that time. However, some of

them were eliminated because they could not meet the requirements. There were 20

responses which could not overcome filtering questions and 16 responses which gave

only one answer for each measurement question. As a result, only 191 qualified

responses remained which could be used for data analysis. After that, all of these

responses were cleaned and encoded in Excel 2016 and then put into SPSS 20.0

software for data analysis.

4.1.1. Descriptive statistics for e-wallet adoption behaviors

Based on questions about e-wallet adoption behaviors, the author finds some

interesting things. Among 191 respondents, there are 87 people who have adopted e-

wallets over 1 years and 47 people who have used e-wallets within one year. These

numbers can indicate that adopting e-wallet has become very popular and familiar

with most residents in Vinh Long province. The table 4.1 shows the time periods that

respondents have adopted e-wallets.

Table 4.1 Time period of adopting e-wallet

Time period Frequency Percentage

3 months 28 14.66%

6 months 19 15.18%

1 year 47 24.61%

Above 1 year 87 45.55%

Source: Compiled by the author using the survey result

Moreover, the author recognized that VNPT Pay is the e-wallet that has been

used mostly in Vinh Long province with 69.63% responses and one person can adopt

more than one e-wallet. This is a surprising result because due to Cimigo’s survey,

Momo, Moca and ZaloPay are the top three e-wallet widely used in Ho Chi Minh and

Ha Noi City. VNPT Pay has not been mentioned much in previous studies and

surveys which only focus on big cities. Therefore, it can be concluded that VNPT Pay

has established a firm position in Vinh Long market with a large number of users

which made a big difference compared to other big cities like Ho Chi Minh and Ha

Noi. Other e-wallet providers should prepare carefully when investigating in this

market. The quantity and percentage of e-wallets that have been adopted by

consumers in Vinh Long province are presented in the table 4.2.

Table 4.2 Names of adopted e-wallets in Vinh Long province

E-wallet Frequency Percentage

VNPT PAY 133 69.63%

80 41.88% Momo

35 18.32% ZaloPay

30 15.71% Viettelpay

16 8.38% AirPay

10 5.24% Moca

9 4.71% VNPay

7 3.66% Ngân Lượng

6 3.14% Payoo

1 0.52% Bảo Kim

Source: Compiled by the author using the survey result

Additionally, it is interesting that most respondents adopt e-wallet to make

online payments for electricity, water, pay TV, Internet, telephone, mobile phone

which accounts for up to 83.77% respondents. This might be due to government

policies that encourage non-cash payment for these utility services which will

establish a cashless society in a near future. On the other hand, 76.44% respondents

also adopt e-wallet to transfer money faster and more easily. Since e-wallet is multi-

functional, a person can also use e-wallet for a lot of purposes at the same time. The

table 4.3 shows the purposes that e-wallets are usually used for.

Table 4.3 Purposes of adopting e-wallets in Vinh Long province

Purposes Frequency Percentage

Transfer money 146 76.44%

160 83.77% Make payment for many utility services (electricity, water, pay TV, Internet, telephone, mobile phone)

76 39.79% Make payment for online purchasing on Tiki, Lazada, Shopee

Top up your accounts (telephone, Grab, etc.), 72 37.70%

(discount, refund, 63 32.98% Receive promotional benefits voucher)

39 20.42% Make payment for offline purchasing (at any stores that accept e-wallet payment)

Make online orders (food, beverage, etc.) 35 18.32%

Purchasing tickets (movie, train, plane tickets 31 16.23%

Make a reservation (hotel, restaurant, etc.) 19 9.95%

Source: Compiled by the author using the survey result

4.1.2. Descriptive statistics of demographic variables

The below charts show characteristics of respondents which include gender,

age, educational level, occupation and income. These variables will be analyzed with

the Independence T-test and ANOVA test to examine the relationship between them

and e-wallet adoption intention.

In terms of gender, there are 85 out of 191 respondents are male which

accounts for 45% and the rest are female with 55%.

Male

45%

Figure 4.1 Gender

Female

55%

Source: Compiled by the author using SPSS 20.0 result

In terms of age, most of the respondents are more than 30 years old.

Particularly, 84 out of 191 respondents are 31 to 45 years old and 59 out of 191

respondents are above 45 years old which accounts for 44% and 31% respectively.

The remaining people who are 18 to 23 years old take 11% and 24 to 30 years old

people take 14%. No respondents are below 18 years old.

Figure 4.2 Age

18-23 years old 11%

31% 24-30 years old 14%

31-45 years old

Above 45 years old

44%

Source: Compiled by the author using SPSS 20.0 result

In terms of educational level, most of respondents have the university degree

which accounts for 74%. People who have post graduate and college degree account

for 12% and 11% respectively. People with high school degree take the lowest

percentage with only 3%.

Figure 4.3 Educational level

High school

College

12% 11%

University

Post graduate 74%

Source: Compiled by the author using SPSS 20.0 result

In terms of occupation, office workers and technical workers are the main

respondents of the survey with 129 out of 191 respondents which accounts for 68%.

Respondents who are managers take 22% while students and unskilled laborers or

homemakers only take 8% and 2% respectively.

Figure 4.4 Occupation

8% 2% Student

22% Unskilled labor/Homemarker

68%

Office worker/Technical worker

Manager

Source: Compiled by the author using SPSS 20.0 result

In terms of income per month, most respondents have medium income from 5

to 10 million VND with 52%. People who have income from 10 to 20 million VND

account for 33% while people with income below 5 million VND and above 20

million VND only take 10% and 5% respectively.

Figure 4.5 Income

Below 5 million VND

5% 10%

5-10 million VND 33%

10-20 million VND 52%

Above 20 million VND

Source: Compiled by the author using SPSS 20.0 result

The detailed statistics for demographic variables are displayed in Appendix 2.

4.1.3. Descriptive statistics of independent variables

The measurement items for independent variables are evaluated by 5-point

Likert scale from 1 (strongly disagree) to 5 (strongly agree). The detailed descriptive

statistics for independent variables are described in Appendix 3. Based on the

outcome, most of observed variables have mean value greater than 3 which indicates

that respondents highly agree with most mentioned factors including performance

expectancy, effort expectancy, social influence, facilitating conditions, trust and self-

efficacy. PE1 has the highest mean value which is 4.69 which expresses that

respondents totally agree with the increase in the efficiency of the payment process.

Among these factors, only perceived risk has the mean value below 3 which

shows that respondents seem to disagree with this factor. PR1 has the lowest mean

value with 2.61 which indicates that respondents are likely to believe that nothing

will go wrong with the performance of e-wallet.

4.1.4. Descriptive statistics of dependent variables

The observed variables of adoption intention have mean value greater than 4

which indicates that respondents strongly agree with adopting e-wallet. AI2 has the

highest mean value at 4.27 which shows that respondents are more likely to adopt e-

wallet in their daily life. The detailed descriptive statistics of dependent variables are

also displayed in Appendix 3.

4.2. Cronbach Alpha’s coefficient analysis

4.2.1. Cronbach Alpha’s coefficient analysis for independent variables

4.2.1.1. Performance expectancy

The Cronbach Alpha’s coefficient of Performance expectancy is 0.78 which is

greater than the threshold of 0.6. Additionally, all observed variables including PE1,

PE2, PE3, PE4 have Corrected item - Total correlation around 0.5 and 0.6 which are

greater than 0.3. Therefore, the measurement scale for Performance expectancy is

reliable and no observed variables are eliminated from the scale. The table 4.4

describes Cronbach Alpha’s outcome of Performance expectancy.

Table 4.4 Cronbach Alpha’s outcome of Performance expectancy

Variables

Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item- Total Correlation Cronbach’s Alpha if Item Deleted

Performance expectancy: Cronbach Alpha = 0.780

PE1 13.39 2.534 0.589 0.733

PE2 13.61 2.249 0.556 0.743

PE3 13.65 2.018 0.624 0.708

PE4 13.58 2.245 0.597 0.721

Source: Compiled by the author using SPSS 20.0 result

4.2.1.2. Effort expectancy

Effort expectancy has Cronbach Alpha’s coefficient at 0.844 which is greater

than 0.6. Moreover, Corrected item - Total correlation indicators of observed

variables including EE1, EE2, EE3, EE4 are also around 0.6 and 0.7 which are more

than 0.3. Hence, Effort expectancy has a reliable scale and no observed variables are

removed from the scale. The table 4.5 describes Cronbach Alpha’s outcome of Effort

expectancy.

Table 4.5 Cronbach Alpha’s outcome of Effort expectancy

Scale Mean Scale Corrected Item Cronbach’s

Variables if Item Variance if - Total Alpha if

Deleted Item Deleted Correlation Item Deleted

Effort expectancy: Cronbach Alpha = 0.844

EE1 12.73 3.860 0.662 0.810

EE2 12.97 3.525 0.658 0.816

EE3 12.87 3.700 0.718 0.785

EE4 12.82 3.961 0.695 0.798

Source: Compiled by the author using SPSS 20.0 result

4.2.1.3. Social influence

The Cronbach Alpha’s coefficient of Social influence is 0.806 which is more

than 0.6. Also, all observed variables of this factor have Corrected item - Total

correlation greater than the threshold of 0.3. Thus, Social influence’s measurement

scale is reliable and all SI1, SI2, SI3 are still kept for the EFA step. The table 4.6

describes Cronbach Alpha’s outcome of Social influence.

Table 4.6 Cronbach Alpha’s outcome of Social influence

Variables

Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item - Total Correlation Cronbach’s Alpha if Item Deleted

Social influence: Cronbach Alpha = 0.806

SI1 7.66 2.405 0.664 0.723

SI2 7.48 2.451 0.595 0.797

SI3 7.52 2.398 0.705 0.683

Source: Compiled by the author using SPSS 20.0 result

4.2.1.4. Facilitating condition

Facilitating condition has Cronbach Alpha’s coefficient at 0.74 which is more

than 0.6. In addition, this factor has four observed variables including FC1, FC2, FC3,

FC4 with Corrected item - Total correlation all greater than 0.3. Then, it can be

indicated that the Facilitating condition has a reliable scale and all observed variables

of this factor will be retained for the EFA step. The table 4.7 describes Cronbach

Alpha’s outcome of Facilitating condition.

Table 4.7 Cronbach Alpha’s outcome of Facilitating condition

Variables

Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item - Total Correlation Cronbach’s Alpha if Item Deleted

Facilitating condition: Cronbach Alpha = 0.740

FC1 12.29 3.766 0.487 0.709

FC2 12.52 3.030 0.611 0.633

FC3 12.62 3.068 0.559 0.665

FC4 12.75 3.210 0.490 0.707

Source: Compiled by the author using SPSS 20.0 result

4.2.1.5. Trust

Cronbach Alpha’s coefficient of Trust is 0.85 which is greater than threshold

of 0.6. Moreover, four observed variables of trust including T1, T2, T3, T4 have

Corrected item - Total correlation more than 0.3. Therefore, Trust is believed to have

a reliable measurement scale and no observed variables of trust are eliminated from

the measurement scale. The table 4.8 describes Cronbach Alpha’s outcome of Trust.

Table 4.8 Cronbach Alpha’s outcome of Trust

Variables

Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item - Total Correlation Cronbach’s Alpha if Item Deleted

Trust: Cronbach Alpha = 0.850

T1 11.89 5.583 0.644 0.828

T2 11.91 4.770 0.724 0.794

T3 11.84 5.147 0.729 0.793

T4 11.94 5.034 0.668 0.819

Source: Compiled by the author using SPSS 20.0 result

4.2.1.6. Perceived risk

Perceived risk has Cronbach Alpha’s coefficient at 0.892 which is also more

than 0.6. Additionally, all observed variables of this factor have Corrected item -

Total correlation around 0.7 which are more than 0.3. Hence, the measurement scale

of Perceived risk is reliable and PR1, PR2, PR3, PR4 variables are not discarded from

the scale. The table 4.9 describes Cronbach Alpha’s outcome of Perceived risk

Table 4.9 Cronbach Alpha’s outcome of Perceived risk

Variables Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item - Total Correlation Cronbach’s Alpha if Item Deleted

Perceived risk: Cronbach Alpha = 0.892

PR1 8.14 8.711 0.752 0.865

PR2 7.99 8.384 0.773 0.857

PR3 8.07 8.226 0.789 0.851

PR4 8.05 8.408 0.736 0.871

Source: Compiled by the author using SPSS 20.0 result

4.2.1.7. Self-efficacy

Cronbach Alpha’s coefficient of Self-efficacy is 0.853 which is greater than

the threshold of 0.6. Furthermore, three observed variables of Self-efficacy have

Corrected item - Total correlation more than 0.3. Thus, it is stated that Self-efficacy

has a reliable measurement scale and SE1, SE2, SE3 are not eliminated from the scale

as well. The table 4.10 describes Cronbach Alpha’s outcome of Self-efficacy.

Table 4.10 Cronbach Alpha’s outcome of Self-efficacy

Variables Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item - Total Correlation Cronbach’s Alpha if Item Deleted

Self-efficacy: Cronbach Alpha = 0.853

SE1 8.35 1.943 0.757 0.771

SE2 8.27 2.294 0.763 0.762

SE3 8.07 2.521 0.672 0.843

Source: Compiled by the author using SPSS 20.0 result

4.2.2. Cronbach Alpha’s coefficient analysis for dependent variables

Adoption intention has Cronbach Alpha’s coefficient at 0.753 which is more

than the threshold of 0.6. In addition, all observed variables of Adoption intention are

around 0.5 and 0.6 which are greater than 0.3. Therefore, Adoption intention is

believed to have a reliable measurement scale and AI1, AI2, AI3 are also kept for the

EFA step. The table 4.11 describes Cronbach Alpha’s outcome of Adoption intention.

Table 4.11 Cronbach Alpha’s outcomes of Adoption intention

Variables

Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item - Total Correlation Cronbach’s Alpha if Item Deleted

Adoption intention: Cronbach Alpha = 0.753

AI1 8.44 1.427 0.574 0.683

AI2 8.18 1.705 0.559 0.700

AI3 8.28 1.435 0.621 0.623

Source: Compiled by the author using SPSS 20.0 result

4.3. Exploratory Factor Analysis (EFA)

4.3.1. Exploratory Factor Analysis for independent variables

All qualified variables accepted after Cronbach Alpha’s coefficient analysis

are put into EFA for deeper analysis. The table 4.12 shows an outcome summary of

indicators to evaluate whether EFA is suitable to adopt in this research. The detailed

outcome of independent variables in EFA will be displayed in the Appendix 4.

Table 4.12 Outcome of indicators for independent variables in EFA

Indicators Outcome Comparison with criteria

KMO index 0.890 0.5 < 0.890 < 1

Significance level of Bartlett’s Test 0.000 0.000 < 0.05

Eigenvalue 1.010 1.010 > 1

Total Variance Explained 71.088% 71.088% > 50%

Source: Compiled by the author using SPSS 20.0 result

According to the EFA outcome, KMO index is 0.890 which is greater than 0.5

and smaller than 1. This satisfies the mentioned condition in Chapter 3 and indicates

that EFA is suitable with the research data. Moreover, the significance level of

Bartlett’s Test is less than 0.05 which proves that observed variables are correlated

with each other. The condition to apply EFA is that different observed variables

reflecting different aspects of a factor must have a correlation with each other,

therefore, this outcome reveals that EFA can be applied in this research. Based on the

result, there are 7 components extracted with Eigenvalue at 1.010 which is greater

than 1 so the condition is satisfied. Besides, Total Variance Explained is 71.088%

which is greater than the criteria at 50% and expresses that 7 extracted components

can explain 71.088% the variation of collected data.

After rotation, the author observes the Rotated Component Matrix and finds

out that 26 observed variables are divided into 7 components. All of them have factor

loadings greater than 0.5 which indicates that the relationships between observed

variables and factors are strongly significant and no observed variables are loaded in

2 components. Therefore, all observed variables are retained together with 7

components. The detailed extraction and rotation outcome will be displayed in

Appendix 4.

The first component comprises 4 observed variables including PR1, PR2, PR3,

PR4. This is the same as a factor proposed by the author, therefore this component is

named as Perceived risk.

The second component contains 4 observed variables including EE1, EE2,

EE3, EE4. This matches the factor proposed by the author; hence, this component is

named as Effort expectancy.

The third component still comprises 4 observed variables including PE1, PE2,

PE3, PE4. The result is the same as the factor proposed by the author, therefore, this

component is named as Performance expectancy.

The fourth component holds 4 observed variables including T1, T2, T3, T4.

This is also similar to the proposed factor so this component is named as Trust.

The fifth component contains only 3 observed variables including SI1, SI2,

SI3. This is the same as the factor proposed by the author, hence this component is

named as Social influence.

The sixth component comprises 3 observed variables including SE1, SE2,

SE3. This matches the factor proposed by the author. Therefore, this component is

named as Self-efficacy.

The last component contains 4 observed variables including FC1, FC2, FC3,

FC4. This is similar to the proposed factor of the author. Thus, this component is

named as Facilitating condition.

The table 4.13 shows the outcomes of rotation.

Table 4.13 Rotated Component Matrix

Component

1 2 3 4 5 6 7

PR2 0.872

PR1 0.835

PR3 0.833

PR4 0.778

Component

1 2 3 4 5 6 7

EE3 0.780

EE4 0.727

EE1 0.695

EE2 0.683

PE4 0.749

PE3 0.743

PE1 0.680

PE2 0.648

T2 0.822

T4 0.736

T3 0.684

T1 0.629

SI1 0.822

SI3 0.791

SI2 0.682

SE1 0.851

SE2 0.832

SE3 0.654

FC2 0.749

FC3 0.728

FC4 0.599

FC1 0.584

Source: Compiled by the author using SPSS 20.0 result

4.3.2. Exploratory Factor Analysis for dependent variables

The outcomes of indicators in terms of dependent variables are shown in Table 4.14.

Table 4.14 Outcome of indicators for dependent variables in EFA

Outcome Comparison with criteria Indicator

KMO index 0.687 0.5 < 0.687 < 1

Significance level of Bartlett’s Test 0.000 0.000 < 0,05

Eigenvalue 2.014 2.014 > 1

Total Variance Explained 67.146% 67.146% > 50%

Source: Compiled by the author using SPSS 20.0 result

Based on the EFA result, KMO index is 0.687 which is more than 0.5 and less

than 1. This satisfies the condition and indicates the sample adequacy is acceptable.

Additionally, the significance level of Bartlett’s Test is less than 0.05 which

demonstrates that observed variables have a correlation with each other and EFA can

be adopted in this study. According to the result, there is only one component

extracted with Eigenvalue at 2.014 which is more than 1 so the condition is satisfied.

Furthermore, Total Variance Explained is 67.146% which is more than the criteria at

50% and indicates that one factor can explain 67.146% the variation of data. Since

there is only one component so it cannot be rotated. That component comprises 3

observed variables with factor loading greater than 0.5 including AI1, AI2, AI3. This

result matches the factor proposed by the author; therefore; the component is named

as Adoption intention. The table 4.15 shows the component matrix of dependent

variables. The detailed result will be displayed in the Appendix 5.

Table 4.15 Component matrix of dependent variables

Factor Item Factor Loading

AI1 0.844

Adoption Intention AI2 0.811

AI3 0.802

Source: Compiled by the author using SPSS 20.0 result

After EFA, there are 7 factors which are determined to have influences on

adoption intention of e-wallet and no observed variables are eliminated from the

model. All of them will be used for the next analysis.

4.4. Pearson correlation matrix analysis

Pearson correlation analysis is adopted to examine the correlation between

independent and dependent variable, particularly between influencing factors and

adoption intention of e-wallet in this case. This is an important step since the

condition to apply regression analysis is that there must be a correlation between

independent variables and dependent variable. Moreover, it can also help to detect

strong correlation among independent variables which can cause multicollinearity

issues. The table 4.16 shows the outcome of the Pearson correlation matrix.

Table 4.16 Pearson correlation matrix

AI PE EE SI FC T PR SE

1 Pearson Correlation 0.587 ** 0.669 ** 0.625 ** 0.652 ** 0.736 ** -0.454 ** 0.668 ** AI

0.000 0.000 0.000 0.000 0.000 0.000 0.000 Sig. (2-tailed)

1 Pearson Correlation 0.587 ** 0.575 ** 0.297 ** 0.479 ** 0.388 ** -0.335 ** 0.418 ** PE

0.000 0.000 0.000 0.000 0.000 0.000 0.000 Sig. (2-tailed)

1 Pearson Correlation 0.669 ** 0.575 ** 0.352 ** 0.518 ** 0.528 ** -0.342 ** 0.488 ** EE

0.000 0.000 0.000 0.000 0.000 0.000 0.000 Sig. (2-tailed)

1 Pearson Correlation 0.625 ** 0.297 ** 0.352 ** 0.349 ** 0.525 ** -0.380 ** 0.464 ** SI

0.000 0.000 0.000 0.000 0.000 0.000 0.000 Sig. (2-tailed)

AI PE EE SI FC T PR SE

1 Pearson Correlation 0.652 ** 0.479 ** 0.518 ** 0.349 ** 0.467 ** -0.231 ** 0.461 ** FC

0.000 0.000 0.000 0.000 0.000 0.001 0.000 Sig. (2-tailed)

1 Pearson Correlation 0.736 ** 0.388 ** 0.528 ** 0.525 ** 0.467 ** -0.484 ** 0.484 ** T

0.000 0.000 0.000 0.000 0.000 0.000 0.000 Sig. (2-tailed)

1 Pearson Correlation - 0.454 ** - 0.335 ** - 0.342 ** - 0.380 ** - 0.231 ** - 0.484 ** - 0.228 ** PR

0.000 0.000 0.000 0.000 0.001 0.000 0.001 Sig. (2-tailed)

1 Pearson Correlation 0.668 ** 0.418 ** 0.488 ** 0.646 ** 0.461 ** 0.484 ** -0.228 ** SE

0.000 0.000 0.000 0.000 0.000 0.000 0.001 Sig. (2-tailed)

** Correlation is significant at the 0,01 level (2-tailed)

Source: Compiled by the author using SPSS 20.0 result

In terms of the relationships with dependent variables, the significance levels

of all independent variables are 0.000 which are less than 0.05. Therefore, all of them

have correlation with dependent variable which is Adoption intention in this case.

Trust has the highest correlation with Adoption intention of e-wallet due to Pearson

coefficient at 0.736. Other factors have moderate correlation with Pearson coefficient

around 0.5 and 0.6, particularly performance expectancy with 0.587, effort

expectancy with 0.669, social influence with 0.625, facilitating condition with 0.652,

self-efficacy with 0.668. However, perceived risk has a weaker correlation with

Adoption intention due to absolute value of Pearson coefficient at 0.454. It is also

recognized that only perceived risk has a negative relationship with adoption

intention while others have a positive one. Based on this result, all these variables can

be used for the next step which is regression analysis.

Regarding the relationships among independent variables, the significance

level of each pair is less than 0.05 which indicates that these independent variables

are correlated with each other and multicollinearity issues can exist. Therefore, the

author will examine this issue in the regression analysis step.

4.5. Multiple linear regression analysis

4.5.1. Model testing

With the aim to identify the relationship between 7 independent variables and

dependent variables, the multiple linear regression using the ordinary least square

method is utilized in this case. The regression model is displayed as following:

AI = B0 + B1.PE + B2.EE + B3.SI + B4.FC + B5.T + B6.PR + B7.SE

Table 4.17 Types and Definitions of variables used in the regression model

Type Variables Definition

AI E-wallet adoption intention Dependent variable

PE Performance expectancy

EE Effort expectancy

SI Social influence

FC Facilitating condition Independent variable

T Trust

PR Perceived risk

SE Self-efficacy

Source: Compiled by the author

4.5.1.1. Model’s appropriateness evaluation

R square and adjusted R square are two indicators used to evaluate the

appropriateness of a model in regression analysis. R square measures the percentage

of the total variance explained by the regression model. Adjusted R square is a better

indicator compared to R square since it can provide a more precise and reliable view

of the relationship by considering the impact of each additional independent variable

on the model. The table 4.18 shows a summary of the model in this research.

Table 4.18 Model summary

R R square Adjusted R square Std. Error of the Estimate Durbin - Watson

0.896 0.803 0.796 0.26295 2.098

Source: Compiled by the author using SPSS 20.0 result

Adjusted R square is 0.796 which expresses that Performance expectancy,

Effort expectancy, Social influence, Facilitating condition, Trust, Perceived risk and

Self-efficacy can explain 79.6% the variation in the intention to adopt e-wallet. The

rest 20.4% is explained by other factors that are not included in the model. Since

adjusted R square is greater than 50%, the model is evaluated to be appropriate in this

research

4.5.1.2. Model’s appropriateness testing

F-test is adopted to test the overall significance of the sample regression with

the following hypothesis:

H0: B1=B2=B3=B4=B5=B6=B7=0 (all slope coefficients are simultaneously zero)

H1: Not at all slope coefficients are simultaneously zero

The outcome of ANOVA is adopted to test this hypothesis. If the significance

of the F-test is smaller than 0.05, H0 will be rejected which indicates that not all slope

coefficients are simultaneously zero and implies that the model is statistically

significant. The table 4.19 shows the outcome of ANOVA.

Table 4.19 ANOVA

Model Sum of Squares df Mean square F Sig.

Regression 51.711 7 7.387 106.843 0.000

Residual 12.653 183 0.690

Total 64.364 190

Source: Compiled by the author using SPSS 20.0 result

According to the result, Sig. of F test is 0.000 which is smaller than 0.05 so

H0 is rejected with significance level at 5%. This indicates that there is at least one

factor in the model significantly influencing the e-wallet adoption intention of

consumers in Vinh Long province. Therefore, the model is proved to be appropriate

in this research.

4.5.1.3. Model’s coefficients assessment

T-test is applied to determine the relationship between 7 independent variables

(performance expectancy, effort expectancy, social influence, facilitating condition,

trust and self-efficacy) and dependent variable (e-wallet adoption intention) with the

significance level at 5%. If sig. of each independent variable is lower than 5%, the

null hypothesis which is that a certain factor does not influence the e-wallet adoption

intention will be rejected. The table 4.20 shows the regression result.

Table 4.20 Regression outcomes

Sig. t Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Model

B Std.Error Beta Tolerance VIF

(Constant) -0.084 -0.343 0.732

PE 0.159 0.051 0.132 3.109 0.002 0.597 1.675

EE 0.140 0.042 0.152 3.314 0.001 0.513 1.949

SI 0.156 0.032 0.199 4.871 0.000 0.643 1.554

FC 0.205 0.042 0.204 4.875 0.000 0.615 1.625

T 0.222 0.037 0.282 6.082 0.000 0.501 1.995

PR -0.032 0.024 -0.052 -1.340 0.182 0.709 1.410

SE 0.164 0.034 0.204 4.842 0.000 0.605 1.654

Dependent Variable: AI

Source: Compiled by the author using SPSS 20.0 result

Based on the result, the significance level of PR is 0.182 which is very high

compared to other variables. Since the figure 0.182 is greater than 0.05, PR is proved

to have no significant influence on AI with the significance level at 5%.

On the other hand, significance level of other independent variables (except

PR) is from 0.000 to 0.002 which is much smaller than 0.05. Therefore, the six

remaining variables including PE, EE, SI, FC, T, SE are proved to have significant

impacts on AI with the significance level at 5%. The standardized coefficients of

these variables are positive so it can be inferred that the relationships between these

variables and dependent variables are positive.

To sum up, there are 6 out 7 independent variables which have significant

effects on the dependent variable. These variables are Performance expectancy,

Effort expectancy, Social influence, Facilitating condition, Trust and Self-efficacy

which are proved to have positive significant influences on e-wallet adoption

intention of consumers in Vinh Long province with significance level at 5%.

4.5.2. Assumption violation testing

4.5.2.1. Multicollinearity assumption

The author uses VIF to determine whether there is multicollinearity issue in

the model. Nguyen Dinh Tho (2011) stated that if VIF is lower than 2,

multicollinearity will not happen. According to the table 4.20, VIF of PE, EE, SI, FC,

T, PR and SE ranges from 1.410 to 1.995 which are lower than 2. Therefore, it can

be concluded that there is no multicollinearity issue in the model and multicollinearity

assumption is not violated in this case.

4.5.2.2. Linearity assumption

A scatter plot of standardized predicted value and residual is used to test

Linearity assumption. If the scatter plot has a linear pattern, this assumption will not

be violated. From the figure of scatter plot (see Appendix 6), the standardized residual

is randomly distributed around the horizontal axis of zero. Thus, the linearity

assumption is not violated.

4.5.2.3. Normal distribution of residuals assumption

Histogram and P-P plot are used to test normal distribution of residuals. For

histogram, if the residual is not skewed, this assumption will not be violated. From

the figure of Histogram (see the Appendix 6), the mean value is 1.20E-14 which is

nearly equal 0 and standard deviation is 0.981 which is nearly equal 1. For P-P plot,

there is a diagonal line and a bunch of little circles. If these little circles follow the

line, this assumption will not be violated. From the figure of P-P plot (see the

Appendix 6), these little circles of residuals concentrate into a diagonal. Based on the

result of the histogram and P-P plot, normal distribution of residuals assumption is

not violated.

4.5.2.4. Autocorrelation assumption

The Durbin Watson Test is adopted to measure the autocorrelation in residuals

from multiple regression. Field (2009) stated that the value which ranges from 1.5 to

2.5 can be considered as normal. From the table 4.18, the value is 2.098 which is in

the proposed range. Therefore, there is no first-order autocorrelation happening in

this case, or in other words, the autocorrelation assumption is not violated.

4.6. Testing model hypotheses

Table 4.21 Hypotheses testing outcome

Hypotheses Beta Significance Result

0.132 0.002 Accepted H1: Performance expectancy has a positive influence the intention to adopt e-wallet

0.152 0.001 Accepted H2: Effort expectancy has a positive influence on the intention to adopt e-wallet

0.199 0.000 Accepted H3: Social influence has a positive influence on the intention to adopt e-wallet

0.204 0.000 Accepted H4: Facilitating condition has a positive influence on the intention to adopt e-wallet

0.282 0.000 Accepted H5: Trust has a positive impact on the intention to adopt e-wallet

-0.052 0.182 Rejected H6: Perceived risk has a negative influence on the intention to adopt e-wallet

0.204 0.000 Accepted H7: Self-efficacy has a positive influence on the intention to adopt e-wallet

Source: Compiled by the author using SPSS 20.0 result

The decision to accept or reject any hypotheses depends on the regression

result. As stated in the above section, there are 6 out of 7 independent variables

including PE, EE, SI, FC, T and SE have significance levels smaller than 0.05 which

indicates that they have significant impacts on dependent variables. To be specific,

such relevant hypotheses including H1, H2, H3, H4, H5 and H7 are accepted which

means Performance expectancy, Effort expectancy, Social influence, Facilitating

condition, Trust and Self-efficacy have a significant impact on e-wallet adoption

intention. Considering the coefficients of these variables, all Beta are positive

indicating that these relationships are also in positive directions which are the same

as the directions proposed by the author. On the other hand, PR has a significance

level at 0.182 which is more than 0.05 so Perceived risk does not significantly

influence the adoption intention. Therefore, H6 is rejected and Perceived risk is

eliminated from the proposed model. The outcome of hypotheses testing is illustrated

in the table 4.21.

4.7. Testing the influence of demographic factors on the intention to adopt e-

wallet

4.7.1. Independent T-test analysis

Gender has only two groups, therefore, Independence T-test will be applied to

test the influence of gender on e-wallet adoption intention. From the table

Independent Sample Test (see Appendix 7), the sig. of Levene’s Test is 0.510 which

is much greater than 0.05. This indicates that the variances of two groups are not

significantly different so the significance level of Equal variances assumed will be

adopted for the following test which is 0.150. For the T-test, since 0.150 is greater

than 0.05, there is no significant difference in the mean of two groups. Or in other

words, there is no difference in e-wallet adoption intention between male and female.

4.7.2. ANOVA analysis

4.7.2.1. Age

Age has four groups, therefore, One way ANOVA will be adopted to test

whether people with different ages have different intentions to adopt e-wallet. In the

table Test of Homogeneity of Variances (see Appendix 7), the sig. of Levene’s test is

0.091 which is greater than 0.05. Therefore, there is no difference in the variances of

four groups which meets the requirement to apply ANOVA. In ANOVA test,

significance value is 0.022 which is lower than 0.05. Hence, it can be indicated that

there are significant differences in e-wallet adoption intention among four groups.

For deeper investigation, the author uses Post Hoc Test, particularly LSD in this case

(see Appendix 7). Looking at Multiple Comparisons table, it is found out that only

the pair between 24-30 years old and 31-45 years old has significance value at 0.008

which is much less than 0.05. Thus, it is proved that there is a significant difference

between these two groups of age. Particularly, people who are 24-30 years old have

different intentions to adopt an e-wallet compared to people who are 31-45 years old.

4.7.2.2. Educational Level

Educational level has four groups so ANOVA will be again adopted to test

whether people who have different educational levels will have different e-wallet

adoption intentions. The outcome from the Test of Homogeneity of Variances (see

Appendix 7) shows sig. of Levene’s Test at 0.679 which is more than 0.05 so the

variances of different educational levels are not significantly different. Therefore, it

can meet the requirements to apply ANOVA. In ANOVA, significance level is 0.969

which is much greater than 0.05. Hence, it cannot be indicated that people who have

different educational levels will have different intentions to adopt e-wallet.

4.7.2.3. Occupation

Occupation also has four groups so the author decides to use ANOVA to test

whether people who have different jobs will have different e-wallet adoption

intentions. From the table Test of Homogeneity of Variances (see Appendix 7), the

significance level of Levene’s Test is 0.687 which is greater than 0.05. So, there are

no differences in the variances of these four groups which implies that ANOVA’s

condition is satisfied. The significance level in ANOVA test is 0.993 which is much

greater than 0.05. Therefore, it can be concluded that people with different jobs do

not have different intentions to adopt e-wallet.

4.7.2.4. Income

Income also has 4 groups so ANOVA is again adopted to test whether people

who have different incomes will have different e-wallet adoption intentions. From

the table Test of Homogeneity of Variances (see Appendix 7), Levene’s test has a

significant level at 0.314 which is more than 0.05. Hence, there are no significant

differences in the variances of these four groups and ANOVA’s requirement is

satisfied. In ANOVA test, the significance level is 0.778 which is greater than 0.05.

As a result, people who have different incomes do not have different intentions to

adopt e-wallet.

4.8. Research results discussion

4.8.1. Trust

From the results, Trust is the factor that has the strongest positive influence on

the intention to adopt an e-wallet of consumers in Vinh Long province with

significance level of 0.000 and coefficient of 0.235. The more trust a person gains,

the more likelihood he intends to adopt e-wallet. This finding is similar with previous

studies when studying the importance of trust to the e-wallet adoption intention (Shin,

2009; Madan and Yadav, 2016; Chawla and Joshi, 2019, Tun, 2020). For technology

services like e-wallet, trust is a sensitive issue and plays an important role in adopting

such services. Consumers are more likely to feel unsafe because they do not have any

control over e-wallet management. Therefore, if the e-wallet service providers can

make them believe that their personal information and money will not be lost when

adopting e-wallet, consumers will have more confidence to adopt an e-wallet.

Moreover, unlike in big cities, consumers in a province like Vinh Long are usually

risk-avoiders. They will not consider the benefits of e-wallet unless they have trust in

e-wallet service providers. Hence, building trust is the most important thing if

providers want to investigate in this market.

4.8.2. Self-efficacy

From the result, Self-efficacy has a significance level of 0.000 and coefficient

of 0.204 which indicates that self-efficacy has a positive significant impact on e-

wallet adoption intention of consumers in Vinh Long province. This finding is

consistent with the research of Chakraborty and Mitra (2018) when studying the

impact of self-efficacy on e-wallet adoption intention. Moreover, it also gives a

similar result with the research of Makanyeza (2017) when he studied the influence

of self-efficacy on the intention to adopt mobile banking. If a person feels more

confident in using an e-wallet, he is more likely to use this service. Confidence in this

case is considered as the ability to adopt an e-wallet on his own. Self-efficacy is

something like self-motivation that encourages the willingness to adopt new things

like e-wallet. It can be inferred that the higher degree of self-efficacy, the more

probability a person intends to adopt an e-wallet. Therefore, the e-wallet provider

should pay attention to increase self-efficacy of consumers to stimulate e-wallet

adoption in Vinh Long province.

4.8.3. Facilitating condition

Facilitating condition has the same standardized coefficient and significance

level with self-efficacy which is 0.204 and 0.000 respectively. Thus, facilitating

condition is proved to significantly influence consumers’ intention to adopt e-wallet

in Vinh Long province. This finding supports some previous research when testing

the influence of facilitating conditions on e-wallet adoption intention (Yang, 2010;

Thakur and Srivastava, 2014; Madan and Yadav, 2016). It is found out that necessary

resources such as knowledge and smartphones are very important when adopting an

e-wallet. Without knowledge about e-wallet, consumers cannot know how to use it

and easily give up adopting it. Without smartphones, there is no chance that

consumers can adopt e-wallet. On the other hand, smartphones are quite popular these

days, so knowledge is the main problem that providers should be concerned about.

Therefore, it is essential that the e-wallet service providers should implement

strategies to enhance knowledge about the e-wallet of consumers in Vinh Long

province.

4.8.4. Social influence

Social influence is the next factor that significantly influences the intention to

adopt an e-wallet of consumers in Vinh Long province with significance level of

0.000 and coefficient of 0.199. The higher level of social influence, the more

likelihood that a person intends to adopt an e-wallet. This finding is consistent with

previous research when studying the impact of social influence on the adoption

intention of e-wallet (Slade et al., 2015; Cao et al., 2016; Lwoga and Lwoga, 2017).

Consumers are found to be affected mainly by their family, friends and colleagues

who are important to them when they decide to adopt new things like e-wallet. If a

person’s family or friends suggests that he should use e-wallet, the rate of e-wallet

adoption will increase. Since social influence is an important factor, e-wallet

providers should promote e-wallet adoption through influential people whose

opinions are widely valued.

4.8.5. Effort expectancy

Effort expectancy has a significance level of 0.001 and coefficient of 0.152

which indicates that it has a positive significant influence on the intention to adopt e-

wallet in Vinh Long province. The higher degree of effort expectancy, the more

probability that a person intends to adopt an e-wallet. This finding is consistent with

previous research studying the impact of effort expectancy on e-wallet adoption

intention (Shin, 2009; Pham and Ho, 2014; Yan and Yang, 2015). If a person

perceives that adopting e-wallet will not require much effort, he is more likely to

adopt it. Consumers prefer simple things which they do not have to spend too much

effort adopting. Particularly, consumers in Vinh Long province are not used to

confusing things and hesitate to use something which is too complex. Therefore, e-

wallet service providers should be concerned about how to make e-wallet easier with

consumers so that they can enhance the willingness to adopt e-wallet of consumers

in provinces.

4.8.6. Performance expectancy

Performance expectancy has a significance level of 0.002 and coefficient of

0.132 which indicates that it significantly influences the intention to adopt e-wallet

of consumers in Vinh Long province. The higher level of performance expectancy,

the more likely a person intends to adopt an e-wallet. This finding supports a lot of

research studying the impact of performance expectancy on adoption intention

(Schierz et al., 2010, Kim et al., 2010; Wang and Yi, 2012). When a person perceives

that adopting an e-wallet can enhance the efficacy of the payment process, he is more

willing to adopt it because he wants to have a faster and more convenient method of

payment. Moreover, other benefits such as discounts, vouchers, refunds also

encourage consumers to adopt e-wallet because they want to take all advantages of

e-wallet. Therefore, promotional benefits would be the key strategies that e-wallet

service providers should implement because consumers in Vinh Long province prefer

anything that they can gain benefits as much as possible.

4.8.7. Perceived risk

Perceived risk is the only factor that insignificantly influences the adoption

intention of e-wallet in Vinh Long province with significance level of 0.182. This

finding is quite surprising because it is inconsistent with the finding of Dahlberg et

al. (2003), Wu and Wang (2005), Xin (2013). However, it supports the research of

Yadav (2017) when he investigated the active determinants for adopting mobile

wallets in India. In this case, the reason that perceived risk does not have a significant

impact on the intention to adopt e-wallet may be the increase in trust of consumers.

It seems e-wallet service providers successfully make consumers believe that their

money and personal information will not be lost when adopting e-wallet.

Additionally, consumers may believe that there will not be anything wrong happening

when a transaction via e-wallet is conducted. Therefore, even though consumers

perceive that e-wallet may be risky, it still does not affect their intention to adopt e-

wallet in Vinh Long province.

Summary of Chapter 4: During this chapter, the author presents the outcome

of data analysis. For descriptive statistics, the author describes an overview of e-

wallet adoption behaviors, demographic variables, independent variables and

dependent variables. For Cronbach Alpha analysis, the author examines the

measurement scale’ reliability of each variable to determine whether any

independent variables or observed variables should be eliminated. After EFA, the

author collects seven independent variables which can be used for the next analysis.

In Pearson analysis, all independent variables have correlations with dependent

variables so all of them will be used for the following analysis. In multiple regression

analysis, 6 out 7 factors are proved to significantly influence the intention to adopt

e-wallet of consumers in Vinh Long province including performance expectancy,

effort expectancy, social influence, facilitating condition, trust and self-efficacy.

Moreover, age is the only demographic factor that influences the e-wallet adoption

intention. Based on these findings, the next chapter will discuss the recommendations

to e-wallet providers, limitations of this research and orientations for future studies.

CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS

5.1. Conclusions

After considering the outcome of this research, the author comes to some

conclusions as follows.

Firstly, this thesis aims to investigate the intention to adopt e-wallet of

consumers in Vinh Long province by using the UTAUT model and some additional

factors. The UTAUT model which includes four main factors has been widely used

as a theoretical framework when studying technology fields like e-wallet. Moreover,

the author also adds three factors which are trust, perceived risk and self-efficacy

based on previous research to have a new perspective about this topic. As a result,

seven factors in the model proposed by the author can explain 79.6% the variation in

the intention to adopt e-wallet while independent variables can explain only 70% the

variation of dependent variables in the original UTAUT model. Therefore, this

research can enhance the literature background of e-wallet studies, especially in

Vietnam where there is a lack of research on this field.

Secondly, it is proved that there are 6 factors significantly influencing

consumers’ intention to adopt e-wallet in Vinh Long province which are performance

expectancy, effort expectancy, social influence, facilitating condition, trust and self-

efficacy. Among those, trust is the most influential factor affecting e-wallet adoption

intention of consumers in Vinh Long province. Consumers care about trust before

considering other factors so e-wallet service providers should pay attention to

enhance consumers’ trust, especially in this case. However, perceived risk is found

to have insignificant impact on the intention to adopt e-wallet. This result is quite

inconsistent with previous research. However, it can be because e-wallet service

providers have successfully created firm beliefs of consumers about e-wallet adoption

in Vinh Long province. Therefore, perceived risk does not influence adoption

intention of e-wallet in this case.

Thirdly, it is quite surprising that among demographic factors, age is the only

one that significantly influences e-wallet adoption intention in Vinh Long province.

It is found out that people who are 24-30 years old have different intentions to adopt

e-wallet compared to people who are 31-45 years old. The reason can be that people

who are 24-30 years old are young so they are more flexible and open to new

technology, especially e-wallet in this case. On the other hand, people who are 31-45

years old are more likely to hesitate to adopt e-wallet since they are usually risk-

avoiders. Therefore, e-wallet service providers should also pay more attention to this

demographic feature to propose a suitable strategy in this market.

On the other hand, when studying e-wallet adoption habits and behaviors, the

author finds out that VNPT Pay is the most commonly used e-wallet in Vinh Long

province. It is a little bit different from previous surveys and research which indicates

that Momo is the most popular e-wallet. However, this may be because those studies

are conducted in big cities like Ho Chi Minh and Ha Noi while this research is

conducted in Vinh Long province. Therefore, there may be differences in consumers’

preferences and differences in e-wallet providers’ strategies in different locations.

In short, the author would like to suggest some recommendations to e-wallet

service providers to enhance e-wallet adoption in Vinh Long province based on these

findings and conclusions in the section 5.2. Moreover, limitations of this research as

well as the orientations for future research would be presented in section 5.3.

5.2. Recommendations

According to the outcomes of this research, the author would like to make some

recommendations to e-wallet service providers so that they can enhance e-wallet

adoption in Vinh Long province. The recommendations are grouped by factors that

are proved to significantly influence the e-wallet adoption intention in this study.

5.2.1. Enhancing Trust

Based on the result, trust is the factor that has the most influence on adoption

intention of e-wallet in Vinh Long province. Therefore, e-wallet service providers

have to do everything to gain and maintain credibility of consumers. They must let

consumers know that they always keep consumers’ interests in mind. In order to

achieve this target, the responsible service personnel should provide personal

attention to consumers when they have problems with e-wallet. They must support

and give detailed advice rather than general advice so that consumers can solve their

own problems. Moreover, the customer service department must be always available

whenever consumers need support so that consumers can feel safe when adopting e-

wallet services. The personnel must have sufficient knowledge so that they can

understand the problems and give right directions. They should help consumers solve

their problems in a considerable and enthusiastic way so that consumers can feel like

they are really cared for by e-wallet providers. These things can increase consumers’

satisfaction about e-wallet services and intentions to continue to adopt e-wallet. On

the other hand, security and privacy are also important factors that influence trust of

consumers. E-wallet providers should continue to improve and upgrade technology

to meet high standards of customer information confidentiality and financial

transactions safety. It is important to generate obstacles as much as possible so that

hackers cannot steal personal information and money from consumers. Providers

should have a system that can monitor all transactions. Whenever any suspicious

transaction is detected, warning notice must be notified to consumers through

messages or emails to ensure that their money is safe. For successful transactions,

messages about remaining balance in the account should be sent so that consumers

can check and control their money. Trust is the first factor that consumers observe to

evaluate whether they should use e-wallet services of a certain provider or not.

Therefore, providers should prepare carefully for this first step to gain firm beliefs of

consumers which are the grounds to increase e-wallet adoption.

5.2.2. Enhancing Self-efficacy

Self-efficacy is found out to influence the intention to adopt e-wallet of

consumers in Vinh Long province. Even though this factor is quite new, it has a

stronger influence on e-wallet adoption intentions than other factors in the model.

Self-efficacy refers to a person’s belief in his capacity to perform a certain behavior.

E-wallet providers should pay attention to increase self-efficacy perception of

consumers because it can encourage their motivation to adopt e-wallet. Consumers

feel more confident when they can know how to use e-wallet on their own which

increases their intention to adopt e-wallet. In order to enhance self-efficacy, e-wallet

providers should make e-wallet apps easy to understand and easy to use so that a

person can adopt them by himself. Moreover, there should be short and clear

instructions on the app to directly guide consumers how to use them so that consumers

do not need to depend on other people’s instructions. The design of the app should be

simple and logical so that consumers are not confused when using each function on

e-wallet apps. Moreover, providers can also post illustrations or articles that describe

how to register and adopt e-wallet on website or fanpage so that consumers can easily

find and follow these instructions.

5.2.3. Enhancing Facilitating condition

Facilitating conditions is one of the factors that e-wallet service providers

should be concerned about. To enhance facilitating conditions, e-wallet providers

should make e-wallet compatible with all kinds of smartphones. Not everyone can

have a modern smartphone so e-wallet apps should be designed to be compatible even

with an old smartphone so that providers will not lose a considerable number of

customers. Moreover, e-wallet providers should implement campaigns to enhance

consumers’ knowledge about e-wallet. For example, e-wallet providers can cooperate

with schools, universities and companies which have target customers to introduce e-

wallet services, benefits that e-wallet can bring to consumers and explain how to use

it. This way can easily popularize e-wallet to a large group of potential customers,

improve their knowledge about e-wallet as well as create motivation to adopt e-wallet

of consumers. On the other hand, staff in the customer service department should be

available 24/7 to help consumers solve their problems through telephone or fanpage.

Hotline is very necessary because it helps consumers contact directly and describe

their problems more clearly and detailedly, especially in emergency cases. Moreover,

personnel can also easily understand the problems and suggest suitable solutions.

5.2.4. Enhancing Social influence

Social influence is an important factor that e-wallet service providers can use

to encourage e-wallet adoption intention in Vinh Long province. It is found out that

people who are important such as family, friends and colleagues strongly affect

consumers’ behaviors. Therefore, programs like “Inviting friends” can be a very

useful strategy that providers can adopt to increase a large number of users. People

are more likely to suggest their friends and family using e-wallet so that they can

receive a lot of benefits such as discounts, vouchers or loyalty scores. One customer

can invite 10 additional customers who can continue to invite 100 additional

customers which is an exponential growth in the number of customers. Hence this

strategy can be the most suitable one in this market. Moreover, e-wallet providers can

cooperate with influential people who are reputable and familiar with consumers such

as famous singers and actors to advertise e-wallets. One of the most common ways

of this strategy is to put the image of a certain e-wallet brand in the music video of a

famous singer. For example, Moca invited Truc Nhan to make an advertisement and

Momo recently put its brand image into a music video of Binz. These two people are

very popular with consumers, especially young consumers so e-wallet brands can

come closer to a large group of potential consumers and attract their intention to adopt

e-wallet. On the other hand, social media are also great channels to access consumers.

E-wallet providers can make advertisements on Facebook, Youtube which have a

great number of users. There should be forums or groups to share experiences of

adopting e-wallet or some articles writing about the benefits of e-wallets. It seems

that consumers are more likely to believe in people who are also consumers. Since

consumers perceive that such sharing does not include advertisements, they believe

it will be trustworthy and are more likely to adopt e-wallet.

5.2.5. Enhancing Effort expectancy

Effort expectancy is also the factor influencing the intention to adopt e-wallet

in Vinh Long province. In order to enhance effort expectancy, e-wallet service

providers should focus on developing e-wallet apps to be easy to use. The features

should be displayed in a logical way so that consumers are not confused when using

it. The interface with colorful images and short language can easily attract consumers’

intention to adopt e-wallet. For the first time usage, instructions should be guided

carefully so that consumers can know how to deal with e-wallet apps. Moreover, there

should be an instruction area on the apps in order to help consumers whenever they

forget how to do something. Consumers usually receive discounts or vouchers when

adopting e-wallet. However, these promotions should be explained clearly the usage

criteria and period as well as the way to use them so that consumers will not

misunderstand which prevents confusing and uncomfortable feelings. Moreover, it is

necessary to develop the payment process by creating the automatically filling

feature. This feature helps to fill consumers’ information in electronic invoices or

purchasing orders automatically in order to save consumers’ time and effort which

can make consumers more satisfied when making transactions via e-wallet.

5.2.6. Enhancing Performance expectancy

Performance expectancy is the last factor that has a significant influence on

intention to adopt e-wallet in this research. E-wallet service providers should pay

attention to make consumers believe that adopting e-wallet is extremely useful. Based

on the survey of this research, consumers in Vinh Long province mostly adopt e-

wallet to make online payment for utility services such as electricity, water,

telephone, internet, etc. Therefore, e-wallet providers should have a close cooperation

with these utility service providers. Particularly, Vinh Long Electricity has stopped

collecting electricity bills at customers’ houses. This new regulation definitely

encourages non-cash payment, especially e-wallet. Thus, e-wallet providers can

discuss with the remaining utility service providers to change the method of collecting

bills from cash to e-wallet payment. If this plan can be successful, e-wallet providers

can gain a numerous number of consumers and drastically increase their profits. On

the other hand, consumers cannot change their habit of cash payment in a short time.

Therefore, e-wallet providers should develop the feature that allows consumers to

make payments via e-wallet at the counters in commercial centers, supermarkets,

restaurants, coffee shops, etc. QR code should be used in this method of payment

because it is easy and quick which enhances the efficiency of the payment process.

In order to achieve this target, providers should cooperate with a large network of

food and beverage services, entertainment services to allow e-wallet payment so that

consumers can increase the frequency of adopting e-wallet to make payments which

can create a new habit of payment for consumers. Moreover, online shopping is also

familiar with consumers in Vinh Long province. Therefore, e-wallet providers should

cooperate with popular e-commerce platforms such as Tiki, Lazada, Shopee to allow

e-wallet payment. This way is very convenient for consumers because they can make

payment early and quickly, then just wait to receive products. Moreover, consumers

may feel that they do not really lose their money since everything is conducted online.

Therefore, e-wallet payment can become a favorite method of payment for these

transactions.

5.3. Limitations and orientations for future research

5.3.1. Limitations of the research

Even though the author tries her best to conduct this research, it still has some

limitations which are unavoidable.

Firstly, the author chooses the sampling method as convenient sampling which

is a non-probability method. Since the sample is created not by random selection, it

cannot be objective and can even include biases which make the result unreliable and

incorrect. Moreover, the sample size is also a big limitation of this research. The

author only gained 191 qualified responses after the survey. This is quite a small

number and it cannot be representative for the population in Vinh Long province.

Moreover, the survey is conducted in just one month and respondents are mostly the

author’s acquaintances. Therefore, the sample cannot reveal all characteristics of e-

wallet consumers in Vinh Long province.

Secondly, the author only investigates people who have already adopted e-

wallets and ignores people who have not used e-wallets yet. However, since the aim

of this research is to study e-wallet adoption intention, it is important to investigate

the perception of even non-users to have more accurate results. Non-users do not have

experience with e-wallet, therefore, their perception of e-wallet adoption intention

must be different from the users. Besides, non-users are also important potential

customers of e-wallet service providers so it is really necessary to discover factors

influencing their intention to adopt e-wallet. However, the author does not investigate

non-users since it is much easier to investigate people who have already adopted e-

wallet. Thus, this is also a big limitation of this research.

Thirdly, by adopting the UTAUT model together with three additional

variables, this model can explain 79.6% the variation in the intention to adopt e-

wallet. Therefore, the remaining 21.4% belongs to other variables that are not taken

into the model. These variables can be discovered if the author can observe more

previous studies or make in-depth interviews with professors in this field. However,

due to limited time and capacity, the author cannot deal with this problem. Hence, the

model proposed by the author still lacks some essential variables which needs to

improve in the future research.

5.3.2. Orientations for future research

According to the limitations of the research, the author would like to suggest

some orientations for research in the future.

Firstly, it is necessary to adopt probability sampling methods in future research

so that it can give more reliable data and accurate results. Moreover, it is necessary

to expand the sample size of the research as much as possible so that the sample size

can become better representative of the population. On the other hand, the time period

conducting the survey should last longer which can be for three to four months to

collect more responses. In addition to family and friends, the survey should be also

distributed to unknown people so that the sample will not be biased and can reveal

all characteristics of consumers.

Secondly, it is necessary to study factors influencing the intention to adopt e-

wallet of non-users in the future. It seems there has not been any research on this field

conducted in Vietnam before. Therefore, this type of research will make a significant

contribution to e-wallet adoption intention in Vietnam. Based on these studies, e-

wallet service providers can have a better understanding of non-users’ behaviors and

implement suitable strategies.

Thirdly, the future research can use other theoretical models such as TAM,

TAM2, UTAUT2 extended with other variables found in previous research so that

researchers can have different perspectives of e-wallet adoption intention. Some

additional variables that the author suggests are service quality, satisfaction,

trialability, compatibility, complexity, availability of information, etc. On the other

hand, making in-depth interviews with professors who have specialized knowledge

about e-wallet in Vietnam can provide new factors which are only appropriate in the

Vietnam context. Based on such factors, researchers can conduct studies closer to the

reality of e-wallet adoption in Vietnam.

Finally, the author suggests that future research should pay attention to study

e-wallet adoption in other provinces rather than big cities like Ha Noi and Ho Chi

Minh to have a wider and more reliable perspective of e-wallet in Vietnam. Beside

studying the intention to adopt e-wallet, it is also essential to study factors influencing

the continuance of adopting e-wallet and the satisfaction when adopting e-wallet.

These two topics are really important to e-wallet services providers so that they can

implement suitable strategies to maintain their customers’ loyalty when adopting

their services.

Summary of Chapter 5: During this Chapter, the author briefly describes the

research outcomes, based on which, the author suggests some recommendations that

e-wallet service providers can utilize when penetrating into the Vinh Long market.

Moreover, the author also mentions some limitations of this study due to restrained

time and money. Considering those limitations, some orientations are provided so

that future research related to this topic can be improved and developed in a better

way.

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APPENDIX

Appendix 1: Survey on factors influencing consumers’ intention to adopt e-

wallet in Vinh Long province

Dear Sir/Madam,

My name is Tran Nguyen Lan Ngoc. I am a senior student at Foreign Trade

University in Ho Chi Minh City. Currently, I am doing my graduation thesis entitled

“Factors influencing consumers' adoption intention of e-wallet in Vinh Long

province”. The aim of this research is to determine factors influencing your intention

to adopt e-wallet as well as their impact on adoption intention.

I would highly appreciate it if you could spend your valuable time in fulfilling

this questionnaire. All your responses are extremely meaningful and useful to the

success of this research. I guarantee that your personal information and responses are

handled confidentially and used only for the aim of this research.

Thank you so much!

Definition of e-wallet

E-wallet is currently one of the most popular non-cash payment methods. Consumers

can make online payment for utility bills, purchasing on Tiki, Lazada, Shopee, or

make offline payment at any stores that accept e-wallet payment. People prefer e-

wallet because it is convenient, time-saving and has a lot of promotional benefits.

Some popular e-wallets are Momo, ZaloPay, Moca, AirPay, VNPay, etc.

PART I: FILTER QUESTIONS

Please mark a tick () to indicate the most suitable answers for the following

questions

1. Do you work or live in Vinh Long province?

 Yes (please continue the survey)  No (please stop the survey)

2. Have you ever heard about e-wallet?

 Yes (please continue the survey)  No (please stop the survey)

3. Have you ever adopted any e-wallet?

 Yes (please continue the survey)  No (please stop the survey)

PART II: E-WALLET ADOPTION BEHAVIORS QUESTIONS

Please mark a tick () to indicate the most suitable answers for the following

questions

1. How long have you been adopting e-wallet?

 For 3 months  For 1 year

 For 6 months  More than 1 year

2. Which of e-wallets have you ever adopted? (More than 1 answer is acceptable)

 Momo  Moca

 ZaloPay  Payoo

 AirPay  VNPay

 VNPT Pay  Nganluong

 Viettelpay  Baokim

 Others (please note down)

.......................................................................................................................

3. What are the purposes in adopting e-wallet? (More than 1 answer is acceptable)

 Transfer money

 Make payment for many utility services (electricity, water, pay TV,

Internet, telephone, mobile phone, etc.)

 Make payment for online purchasing (on Tiki, Lazada, Shopee, etc.)

 Purchase tickets (movie, train, plane tickets, etc.)

 Make online order (food, beverage, etc.)

 Make a reservation (hotel, restaurant, etc.)

 Top up your accounts (telephone, Grab, etc.)

 Make payment for offline purchasing (at any stores that accept e-wallet

payment)

 Receive promotional benefits (discount, refund, voucher, etc.)

 Others (please note down)

.......................................................................................................................

PART III: MEASUREMENT QUESTIONS ON FACTORS INFLUENCING

THE CONSUMERS’ INTENTION TO ADOPT E-WALLET IN VINH LONG

PROVINCE

Please mark only one tick () to indicate the extent to which you agree or disagree

with each following statement

Note:

(1) = Strongly disagree; (4) = Agree;

(2) = Disagree; (5) = Strongly agree

(3) = Neither agree nor disagree;

Statements Answer No.

Performance Expectancy 1 2 3 4 5

1 Using e-wallet would increase the efficiency of my

payment process (faster, easier and more

convenient payment)

2 Using e-wallet payments would allow me to track

the payment process more accurately

3 Using e-wallet would allow me to obtain benefits

beyond the payment (vouchers, discounts, refunds)

4 Overall, I believe that e-wallet is useful when

making payment for products/services

Effort Expectancy 1 2 3 4 5

5 Learning how to use e-wallet is easy for me

6 My interaction with e-wallet would be clear and

understandable

I find e-wallet easy to use 7

It is easy for me to become skillful at using e-wallet 8

Social Influence 1 2 3 4 5

People who are important to me (relatives, friends, 9

colleagues) think that I should use e-wallet

10 People who influence my behavior (relatives,

friends, colleagues) think that I should use e-wallet

11 People whose opinions that I value (superiors,

professors) prefer that I use e-wallet

Facilitating Condition 1 2 3 4 5

12 I have the resources necessary to use e wallet (for

example: smartphone, tablet)

13 I have the knowledge necessary to use e-wallet

14 E-wallet is compatible with other technologies I

use

15 I can get help from others when I have difficulties

using e-wallet

Trust 1 2 3 4 5

16 I believe e-wallet service providers keep their

promise

17 I believe e-wallet service providers keep

customers' interests in mind

18 I believe e-wallet service providers are trustworthy

19 I believe e-wallet service providers will do

everything to secure the transactions for users

Perceived Risk 1 2 3 4 5

20 The probability that something will go wrong with

the performance of e-wallet is high

21 E-wallet might not perform well and create

problems with my payment process during

purchasing

22 The chances of using the e-wallet and losing

control over my personal information privacy is

high

23 My signing up and using e-wallet would lead me

to a loss of privacy because my personal

information would be used without my knowledge

Self-efficacy 1 2 3 4 5

24 I have confidence to use e-wallet even if there is no

one around to show me how to do it

25 I easily understand how e-wallet works

26 I feel comfortable using e-wallet on my own

Adoption Intention 1 2 3 4 5

27 I intend to continue using e-wallet in the future

28 I will always try to use e-wallet in my daily life

29 I plan to continue to use e-wallet frequently

PART IV: PERSONAL INFORMATION

1. Your gender is:

 Female  Male

2. Your age is:

 Below 18 years old  31 – 45 years old

 18 - 23 years old  Above 45 years old

 24 - 30 years old

3. Your level of education is:

 High school  Undergraduate

 College  Post graduate

4. Your occupation is:

 Student  Office worker/ Technical worker

 Unskilled labor/ Homemaker  Manager

5. Your income per month is:

 Below 5 million VND  10 – 20 million VND

 5 – 10 million VND  Above 20 million VND

Thank you so much for taking your time to complete this survey

Appendix 2: Descriptive statistics for demographic variables

Appendix 3: Descriptive statistics for dependent and independent variables

Appendix 4: Exploratory Factor Analysis for independent variables

100

Appendix 5: Exploratory Factor Analysis for dependent variables

101

Appendix 6: Multiple regression outcomes

102

103

Appendix 7: Independent T-test and ANOVA

Independent T-test for Gender

ANOVA for Age

104

ANOVA for Educational level

ANOVA for Occupation

ANOVA for Income

Graduation thesis International Business Economics: Factors influencing consumers' adoption intention of e-wallet in Vinh Long province

Chủ đề:

Báo cáo thực tập tài chính ngân hàng

Báo cáo thực tập tài chính số fintech

FOREIGN TRADE UNIVERSITY HO CHI MINH CITY CAMPUS

GRADUATION THESIS

Major: International Business Economics

FACTORS INFLUENCING CONSUMERS' ADOPTION

INTENTION OF E-WALLET IN VINH LONG PROVINCE

Student: Tran Nguyen Lan Ngoc Student ID: 1701015545 Class: K56CLC4 Intake: 56 Supervisor: Dr. Pham Hung Cuong

Ho Chi Minh City, December 2020

FOREIGN TRADE UNIVERSITY HO CHI MINH CITY CAMPUS

SOCIALIST REPUBLIC OF VIETNAM Independence - Freedom - Happiness

DISSERTATION REMARKS

.........../1

Supervisor (Signature with full name)

STATEMENT OF AUTHORSHIP

Except where reference is made in the text of the thesis, this thesis contains no

ACKNOWLEDGEMENT

MEANINGS

Tài liệu liên quan

Graduation thesis International Business Economics: Factors influencing consumers' adoption intention of e-wallet in Vinh Long province

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Đề án môn học: Nâng cao hiệu quả áp dụng chính sách tài khóa của Chính phủ Việt Nam trong giai đoạn 2021-2023

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