Factors influencing the customers intention to use mobile commerce services in vietnam, an empirical analysis

UNIVERSITY OF ECONOMICS HO CHI MINH CITY
International School of Business
------------------------------

Tran Duc Thuan

FACTORS INFLUENCING THE CUSTOMERS’
INTENTION TO USE MOBILE COMMERCE
SERVICES IN VIETNAM: AN EMPIRICAL ANALYSIS

MASTER OF BUSINESS (Honours)

Ho Chi Minh City - Year 2015


UNIVERSITY OF ECONOMICS HO CHI MINH CITY
International School of Business
------------------------------

Tran Duc Thuan

FACTORS INFLUENCING THE CUSTOMERS’
INTENTION TO USE MOBILE COMMERCE
SERVICES IN VIETNAM: AN EMPIRICAL ANALYSIS

ID: 22120112

MASTER OF BUSINESS (Honours)

SUPERVISOR: Dr. DINH CONG KHAI

Ho Chi Minh City - Year 2015


ACKNOWLEDGEMENTS
The research described in this Master’s thesis was carried out during the second
half of the year 2014 in Ho Chi Minh and Hanoi City. I would like to take this
honor to acknowledge those who always helped, encouraged, and supported me
during writing this thesis, who I will always passionately remember.
First of all, I would like to express my gratitude to my supervisor, Dr. Dinh Cong
Khai, for his guidance, advices and support throughout my thesis. It is due to his
patient encouragement that I was motivated to accomplish my Master’s thesis.
Secondly, I would like to thank all the ISB Research Committee, the lecturers, and
the staff at International School of Business and University of Economics Ho Chi
Minh City for everything you have done for me during the MBA course. Thirdly, I
would like to express my special thanks to my beloved family and friends who
provided support and encouragement throughout this long process. Finally, I would
like to show my thankfulness to those who participated in this study. Your valuable
contributions play an important role for the completion and success of the study.
Ho Chi Minh City, Vietnam,
December 07th, 2014

Tran Duc Thuan

i


ABSTRACT
Mobile commerce (M-commerce) refers to the ability to conduct wireless
commerce transactions using mobile applications in mobile devices. M-commerce
is marking a new era of innovation in business. Advances in wireless technology

have increased the number of people using mobile devices and accelerated the
rapid development of M-commerce conducted with these devices.
The purpose of this study is to investigate the factors influencing the customers’
intention to use M-commerce in Vietnam. In order to evaluate those factors, the
extended Technology Acceptance Model (TAM) that integrates Innovation
Diffusion Theory (IDT) is implemented to investigate what determine users’
adoption of M-commerce, in which we explore the relationships among those
following factors, namely, Perceived Usefulness & Compatibility, Perceived Ease
of Use, Perceived Cost, Perceived Trust toward Intention to Use M-commerce
services. Furthermore, Self – Efficacy was analyzed as a moderator.
The quantitative research method was used. Through the direct and online survey,
data collected from 608 users in Vietnam were tested against the research model
using the hierarchical multiple regression analysis approach. The results strongly
support the proposed conceptual model in predicting customer’s intention to use
M-commerce services. The findings made a contribution in terms of allowing us to
understand the factors that can contribute to the adoption of M-commerce in
Vietnam. This study successfully extends the TAM in the context of M-commerce
by incorporating three additional constructs – Compatibility, Perceived Cost and
Perceived

Trust.

Moreover,

several

implications

for

information

technology/information system acceptance research and M-commerce service
management practices are discussed.
Keywords: Mobile commerce, M-commerce, Perceived Usefulness & Compatibility, Perceived
Ease of Use, , Perceived Cost, Perceived Trust, Behavioral intention.

ii


TABLE OF CONTENTS

ACKNOWLEDGEMENTS ........................................................................................... i
ABSTRACT .................................................................................................................. ii
TABLE OF CONTENTS ............................................................................................. iii
LIST OF FIGURES ..................................................................................................... vi
LIST OF TABLES ...................................................................................................... vii
CHAPTER 1: INTRODUCTION ................................................................................ 1
1.1. Research Background ................................................................................... 1
1.2. Research Motivation .................................................................................... 2
1.3. Statement of purposes and research questions ................................................. 3
1.4. Scope of the study ......................................................................................... 3
1.5. Significance of the study ............................................................................... 3
1.6. Research methodology .................................................................................. 4
1.7. Thesis structure ............................................................................................. 4
CHAPTER 2: LITERATURE REVIEW ..................................................................... 6
2.1. M-commerce ............................................................................................... 6
2.1.1. Mobile Payments ...................................................................................... 7
2.1.2. Mobile Banking ........................................................................................ 8
2.1.3. Mobile Advertising ................................................................................... 8

2.1.4. Mobile Entertainment ............................................................................... 9
2.1.5. Mobile Shopping and Retailing................................................................. 9
2.1.6. Mobile Ticketing .................................................................................... 10
2.1.7. Mobile Learning ..................................................................................... 10
2.2. M-commerce Technologies ....................................................................... 11
2.2.1. General Packet Radio Service (GPRS) .................................................... 11
2.2.2. Wireless Application Protocol (WAP) .................................................... 12
2.2.3. Wireless Local Area Network (WLAN) .................................................. 12
2.2.4. The Third Generation - 3G...................................................................... 13
2.2.5. The Fourth Generation - 4G .................................................................... 13
2.3. Technology Acceptance Model (TAM)...................................................... 13
2.4. Rationale for hypotheses ........................................................................... 15

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2.4.1. Perceived usefulness and the behavioral intention to use M-commerce ... 15
2.4.2. Perceived ease of use and the behavioral intention to use M-commerce ......... 16
2.4.3. Compatibility and the behavioral intention to use M-commerce .............. 16
2.4.4. Perceived cost and the behavioral intention to use M-commerce ............. 18
2.4.5. Perceived trust and the behavioral intention to use M-commerce............. 18
2.4.6. Moderating variable – Self-efficacy ........................................................ 19
2.5. Research Model ......................................................................................... 22
CHAPTER 3: RESEARCH METHODOLOGY ........................................................23
3.1. The research approach and research procedure ........................................... 23
3.2. Measurement scale ...................................................................................... 23
3.2.1. Independent and moderating variables.............................................................. 23
3.2.2. Dependent variable: consumer’s intention to use M-commerce ............................ 24
3.3. Sampling design ......................................................................................... 26
3.3.1. Population ............................................................................................... 26

3.3.2. Sample size .............................................................................................. 27
3.4. Questionnaire design ................................................................................. 27
3.5. Pilot survey ............................................................................................... 28
3.6. Data collection ............................................................................................ 28
3.7. Data analysis method.................................................................................... 29
CHAPTER 4: EMPIRICAL RESULTS & DISCUSSIONS ......................................32
4.1. Samples and Demographics statistics ......................................................... 32
4.2. Reliability analysis .................................................................................... 35
4.3. Exploratory Factor Analysis ...................................................................... 37
4.4. The revised hypotheses and conceptual model ........................................... 39
4.5. Correlation analysis ................................................................................... 43
4.6. Multiple Linear Regression Analysis ......................................................... 44
4.7. Discussions of findings .............................................................................. 47
4.7.1. Discussions of findings for H1, H2, H4, H5 ............................................ 47
4.7.2. Discussions of findings for Moderation of Self-efficacy.......................... 48
CHAPTER 5: CONCLUSION AND RECOMMENDATIONS.................................54
5.1. Conclusions ............................................................................................... 54
5.2. Theoretical implications ............................................................................ 56
5.3. Managerial implications ............................................................................ 56

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5.4. Limitations and recommendations for future researches ............................. 59
REFERENCES ............................................................................................................60
APPENDIX A: QUESTIONAIRE ..............................................................................67
APPENDIX B: DATA ANALYSIS OUTPUT ............................................................74

v

LIST OF FIGURES
Figure 1: Research Model ............................................................................................... 22
Figure 2: Research Procedure .......................................................................................... 24
Figure 3: Revised Conceptual Model............................................................................... 43
Figure 4: The Histogram ................................................................................................. 84
Figure 5: The Normal P-P Plot of Regression Standardized Residual .............................. 85
Figure 6: Scatterplot ........................................................................................................ 85

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LIST OF TABLES
Table 3.1: Sources of Measurement ................................................................................. 25
Table 3.2: Scale items of factors influencing the intention to use M-commerce ............... 25
Table 4.1: The profile of respondents .............................................................................. 33
Table 4.2: The reliability statistics ................................................................................... 36
Table 4.3: KMO and Barlett’s test ................................................................................... 37
Table 4.4: Total Variance Explained ............................................................................... 38
Table 4.5: Rotated Component Matrix............................................................................. 39
Table 4.6: The revised Cronbach’s Alpha summary after EFA ........................................ 40
Table 4.7: Result of factor analysis.................................................................................. 41
Table 4.8: Correlations Matrix ........................................................................................ 43
Table 4.9: Coefficient of multiple linear regression analysis ............................................ 46
Table 4.10: Model summary of multiple linear regression analysis .................................. 46
Table 4.11: Model summary with moderating variable of Self Efficacy ........................... 49
Table 4.12: Hierarchical Regressions result with moderating variable of Self-Efficacy.... 51
Table 4.13: Hypotheses Summary ................................................................................... 52

vii

CHAPTER 1: INTRODUCTION
1.1. Research Background
Mobile Commerce (M-commerce) is a concept that involves different applications,
new technologies and services which are accessible from Internet enabled Mobile
devices. Mobile Commerce is also known as Mobile Electronic Commerce (Zhang
et al., 2012). In other words, M-commerce transactions are basically electronic
transactions conducted using a mobile terminal and a wireless network. Mobile
terminals include all portable devices such as smartphones, laptops, net books,
tablet computers and phablets as well as devices mounted in the vehicles that are
capable of accessing wireless networks and performing M-commerce transactions
(Veijalainen et al., 2006). A simple definition of M-commerce describes it as any
transaction

with

a

monetary

value

that

is

conducted

via

a

mobile

telecommunications network (Müller-Veerse, 1999). M-commerce is a new concept
and emerging in a context of an established norms, rules and standards. With an
increasingly powerful mobile technologies like 3G and the Internet of Things, Mcommerce has emerged as a new business phenomenon and has become a market
with great potential (Zhang et al., 2012). It will continue to extend the way
organizations conduct business, and change the relationships between companies,
customers, suppliers and partners.
A report by the end of 2012 from BI Intelligence took a close look at the dollar
value potential of the mobile commerce market and showed that in the United
States, 29 percent of mobile users had made a purchase with their phones. Tablets
even drove more traffic to online retailers than smartphones, and tablet consumers
spent more per transaction than PC-based shoppers. According to Bank of
America’s forecast, in year 2015, American and European shoppers will spend
$67.1 billion on smartphone and tablet retail purchases. An illustration of a topical
success of M-commerce is Uber. Uber is a ridesharing service headquartered in
San Francisco, United States, which operates in multiple international cities. The
company uses a smartphone application to arrange rides between riders and

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drivers. By August 29, 2014, Uber has been very successful in 45 countries and
more than 200 cities around the world and the estimated value of the company up
to US$18.2 billion. Despite having some legal issues, the company received more
than US$300 million from the venture capital companies like Google Ventures,
Benchmark, and individual investors like CEO of Amazon.com - Jeff Bezos. At

present, Uber is available in Ho Chi Minh City and Hanoi, Vietnam.
In Vietnam, there are a growing number of wireless technology users in mobile
devices, especially smartphones and tablets. Data from the Vietnamese General
Statistics Office (GSO) showed that there were 120 million mobile subscribers in
Vietnam by the end of September 2012, and 16 million 3G subscribers in the
country by May 2012. Ministry of Information and Communications (MIC) has
predicted that there would be 137 million mobile subscribers and 35 million 3G
subscribers by the end of 2017 (MIC, Vietnam Telecommunication Report Q. 1,
2013). According to Spire, a market research and consulting company, Vietnam is
expected to have one smartphone user in every four citizens, increasing the
number of smartphones in use in the local market to 20 million units by 2014.
Consumers have shifted to using smartphones to connect to social networks,
access the Internet and digital entertainment.
1.2. Research Motivation
Despite the rapidly growing number of mobile device users and 3G subscribers in
Vietnam, M-commerce is a relatively new service compared to other markets. The
number of people who choose to adopt or use M-commerce technology is still
rather low in comparison with other countries such as Europe, The U.S., Japan,
South Korea and Singapore, etc. The M-commerce service providers and
marketers in Vietnam are lacking of a clear direction toward understanding the
factors affecting the adoption of M-commerce. The current key providers in the
market have not satisfied the users with the services well enough. Furthermore,
mobile devices and wireless technologies are always changing and becoming
more and more modern and diverse with a rapid speed, but there are not many

2


researchers updating studies about this problem in Vietnam to find out the
effective way to attract Vietnamese customers' intention toward M-commerce use.

To fill those gaps, this research will help find out what factors affect the Vietnam
consumers' intention to use the M- commerce services.
1.3. Statement of purposes and research questions
This study aims to identify factors that can explain the customers’ intention to use
M-commerce in Vietnam. To be able to achieve the stated purpose above,
following research questions will be investigated:
• What factors affect customers' intention to use M-commerce in Vietnam?
• How does the proposed conceptual research model explain the variances of
customer’s M-commerce acceptance intention?
1.4. Scope of the study
The target population of this study includes individuals in Vietnam who are
owners of mobile phones or other mobile devices which can be used to connect
and access to the Internet through a wireless network. Given the limited resources
and time, the empirical data for the study was collected from the universities and
offices in Ho Chi Minh and Hanoi city, Vietnam. Interviewees on this study include
students and white - collar workers.
1.5. Significance of the study
Nowadays, with a very harsh business competition and intensive growing of the
applications of the wireless technologies and mobile devices, this study hopes to
explore the insights of the Vietnamese customers about M-commerce services and
what key factors which affect them in adoption of the services. It will become more
and more important how the users perceive the service and the emotional impact and
pleasure that the service creates and maintains. By explaining usage intention from
consumers’ perspectives, we hope that the findings of this study will help M-

3


commerce practitioners to develop better user accepted M-commerce systems, as well
as provide insights into how to promote advanced information technology to potential

customers. By knowing all these factors, it may help businesses to build effective and
efficient strategies to improve their service quality, to have competitive advantages to
others in the market, to maintain their current market share, and even gain more
market share.
1.6. Research methodology
To analyze the relationship between one construct with another to test the
hypotheses which are proposed in the following parts, the quantitative approach is
employed in this study. Survey questionnaire with multiple choice answers were
designed based on reviewing literatures, previous studies of the same or similar
topics. Pilot survey was conducted. Random sampling was chosen to reduce bias in
the sample. The data collected from the survey was coded, analyzed and
interpreted by IBM SPSS Statistic. Descriptive Statistics, Cronbach Alpha,
Exploratory Factor Analysis (EFA), Pearson’s Correlation Coefficient and
Hierarchical Multiple Regression analyses were employed. More details of the
research methodology are provided in Chapter 3 and the results of the study are
presented in Chapter 4.
1.7. Thesis structure
This study will be divided into five chapters; the content of the chapters will be
organized as follows:
• Chapter 1 presents the overview of research background, research motivation,
research objectives, scope of study, significance of the study, research
methodology and thesis structure.
• Chapter 2 introduces the literature review, rationale for hypotheses as well as the
proposed conceptual research model.
• Chapter 3 illustrates the detailed research methodology: research process,
research design, measurement of the constructs, data collection procedures and

4

data analysis framework.
• Chapter 4 describes empirical results and discussions based on the data
collected: characteristics of the sample, analyzing the reliability and validity,
testing the assumption of regression and testing hypotheses.
• Chapter 5 summarizes the discussions on the research findings, theoretical
contributions, managerial implications, limitations of the study, and the
suggestions for future researches.

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CHAPTER 2: LITERATURE REVIEW
This chapter presents a review of relevant literature associated with Technology
Acceptance Model (TAM) and factors affect customers' intention to use Mcommerce. It consists of definitions related to M-commerce and their subsets,
technology for M-commerce. This chapter also states the hypotheses and proposes
conceptual model for the study.
2.1. M-commerce
For understanding the difference between Electronic and Mobile Commerce, it is
necessary to understand the similarities and differences between the terms
"electronic" and "mobile". The adjective "electronic", used within the specific
contexts of "Electronic Commerce" or “E-commerce”, indicates an "anytime access"
to business processes managed by computer-mediated networks. Furthermore, the
access to such networks is, in this case, stationary. The services are, therefore, not
available independent of the geographic location (Hohenberg and Rufera, 2004).
The adjective "mobile", used within the specific contexts of "Mobile Commerce"
or “M-commerce”, signifies an "anytime and anywhere access" to business
processes managed by computer-mediated networks. The access takes place using
mobile communication networks, making the availability of these services
independent of the geographic location of the users (Stanoevska-Slabeva, 2003;
Hohenberg and Rufera, 2004).

M-commerce is a new concept which is hard to define since there are many
different definitions for it, and there are constantly new definitions arising with
time. For instance, M-commerce is the use of mobile (hand-held) devices to
communicate and conduct transactions through public and private networks
(Balasubramanian et al., 2002). Abu Bakar and Osman (as cited in Wei et al.,
2009) defined M-commerce as exchange or buying and selling of commodities and
services through wireless handheld devices such as cellular telephones and personal
digital assistant (PDAs). M-commerce is seen as an E-commerce over the wireless

6


devices (Varshney and Vetter, 2002). However, Feng et al. (as cited in Wei et al.,
2009) suggested that M-commerce is more than E-commerce due to its different
interaction style, usage pattern and value chain. Feng et al. (as cited in Wei et al.,
2009) stated that M-commerce is a new and innovative business opportunity with
its own unique characteristics and functions, such as mobility and broad
reachability. According to Tiwari and Buse (2007), M-commerce is defined as any
transaction, involving the transfer of ownership or rights to use goods and services,
which is initiated and/or completed by using mobiles access to computer-mediated
networks with the help of mobile devices.
Nowadays, M-commerce is being applied in more and more fields. It has many
applications such as: mobile payments, mobile banking, mobile advertising,
mobile entertainment, mobile shopping and retailing, mobile ticketing and mobile
learning, etc. It is important to describe and understand different types of Mcommerce applications. The followings present an essence of predominant Mcommerce services:
2.1.1. Mobile Payments
Mobile payment, also referred to as mobile money, mobile money transfer, and
mobile wallet, generally refer to payment services operated under financial
regulation and performed from or via a mobile device. Instead of paying with cash,
cheque, or credit cards, a consumer can use a mobile device to pay for a wide

range of services or goods. Mobile payments are expected to become one of the
most important applications in M-commerce (Mallat et al., 2004). Currently, there
are large numbers of smartphones and tablets that have set the stage for a new
move - the payment transactions can be completely performed through a mobile
device. In 2011, the first step of Near Field Communication (NFC) technology was
developed when it was starting to become a new standard, and many major
financial institutions also supported this trend. Most smartphone manufacturers are
releasing products that support NFC technology. Google Wallet has used NFC
technology to help customers pay for their items. In year 2014, Apple has

7


announced mobile payment service, Apple Pay. The service lets MasterCard
cardholders use Apple devices (iPhone 6, iPhone 6 Plus and Apple Watch) to
wirelessly communicate with point of sale systems using NFC for everyday
shopping.
2.1.2. Mobile Banking
Mobile banking is a system that allows customers of a financial institution to
conduct a number of financial transactions through a mobile device such as a
mobile phone or tablet. There are two most common modes used to deliver mobile
banking are WAP banking and SMS banking. The earliest mobile banking services
were SMS banking. Banks provide SMS banking services based on creating SMS
messages which are sent to customer service centers and getting personal account
and related information via customers’ mobile phones (Barnes and Corbitt, 2003).
With the introduction of smartphones with WAP support enabling the use of the
mobile web, banks started to offer mobile banking on this platform to their
customers. WAP banking allows customers to interact via a browser (Barnes and
Corbitt, 2003) and confirm via a PIN and have transactions authorized via
transaction numbers (Laukkanen and Lauronen, 2005). Mobile banking provides

various services such as confirmation of direct payments, stock trading, or
transactions between accounts. Furthermore, they can pay bills and trade equities
using a menu-based interface (Mallat et al., 2004).
2.1.3. Mobile Advertising
Mobile advertising is a form of advertising via mobile phones or other kinds of
mobile devices. It is a subset of mobile marketing. Mobile advertising is a very
important session of M-commerce; it augments location information with
personalization and delivers the obtained history of customers’ purchasing habits.
Advertising on mobile devices has large potential due to the very personal and
intimate nature of the devices and high targeting possibilities (Aalto et al., 2004).
By keeping track of customers’ purchasing habits and current location, a targeted
advertising campaign can be performed. Messages can be sent to all users who are
8


currently in a certain area (identified by advertisers or even by customers) or to
certain customers in all locations. Depending on interests and personality types of
individual users, advertisers could decide whether a “push” or “pull” form of
advertising is more suitable (Varshney, 2003). Most users do not mind being
pushed for mobile location-aware services information, as long as they really
needed the information. (Aalto et al, 2004). It has been demonstrated in several
trials that mobile users are willing to receive advertising messages with incentives
(Varshney, 2003).
2.1.4. Mobile Entertainment
Moore and Rutter (2004) have defined mobile entertainment as any leisure activity
undertaken via a personal technology which is or has a potential to be, networked
and facilitates transfer of data (including voice, sound and images) over
geographic distance either on the move or at a variety of discrete location. Mobile
devices offer the opportunity to play games nearly everywhere. Networked games
allow individual players to interact with other people and to participate in a larger

gaming world, which also provides for new business opportunities (Akkawi et al.,
2004). Mobile music is contained in the mobile entertainment services (MacInnes
et al., 2002). Mobile music services are underlined to try to benefit of the unique
features of mobile network technology, for example, ubiquity, availability,
localization, approachability, and personalization (Baldi and Thaung, 2002).
Customers can purchase their favorite songs on online music stores which are then
transferred right to their mobile devices.
2.1.5. Mobile Shopping and Retailing
Mobile devices extend users’ ability to make transactions across time and location
and create new transaction opportunities. At the current stage of technological
development, customers must ideally be faced with a one-button purchase
experience for mobile shopping (Müller-Veerse, 1999). Mobile retailing is an
interesting M-commerce application. It combines with location identification to
create a new value, for instance, when ordering a taxi or a pizza, the vendor can
9


automatically know where the service is to be delivered. Uber ridesharing service
is an example. Users just need to install Uber application on their smartphones
then can order cars. With a few simple tasks on the phone, the user will have a
luxury car pick-up from and deliver to the desired location with even lower cost
than the taxi fares. Mobile applications can make shopping easier for consumers.
Retailers can increase revenue by capturing more mobile consumers by promoting
applications across channels in the application itself, through email and online
advertising. Retailers can also increase loyalty by saving customers’ time, money
and energy. Moreover, retailers can increase the customers’ awareness and
engagement by successfully develop their applications to make their brand more
accessible to the customers, and contribute to their lives in a meaningful way that
goes far beyond retail sales.
2.1.6. Mobile Ticketing

Mobile electronic purchase or reservation of tickets is one of the most compelling
proposed services, because ticket reservation/ purchasing are hardly a pleasant
experience today. Either one has to go in person to a ticket booth, or has to call an
agency or the outlet. Calling outside opening hour means having to go through a
lengthy IVR (Intelligent Voice Response) system. It is clearly more convenient to
select and book tickets for movies, theatres, opera and concerts, etc. directly from
a mobile device, because often the decision to purchase is made while outside or
on the move among friends (Müller-Veerse, 1999). This is one of the first WAP
applications being seen in various markets. The travel market and especially the
frequent business traveler market are likely to be an early WAP growth market.
Using a WAP handset, train, plane, bus and boat tickets could be booked. Tickets
for culture or sport events could also be reserved in a similar manner.
2.1.7. Mobile Learning
Mobile learning involves the use of mobile technology, either alone or in
combination with other information and communication technology (ICT), to
enable learning anytime and anywhere. O’Malley et al. (2003) defined mobile
10


learning as any sort of learning that happens when the learner is not at a fixed,
predetermined location, or learning that happens when the learner takes advantage
of learning opportunities offered by mobile technologies. Traxler (2005) defined
mobile learning as any educational provision where the sole or dominant
technologies are handheld or palmtop devices. In addition, Sharples et al. (2007c)
defined mobile learning as the processes of coming to know through conversations
across multiple contexts amongst people and personal interactive technologies.
Learning can unfold in a variety of ways: people can use mobile devices to access
educational resources, connect with others, or create content, both inside and
outside classrooms. The smart mobile devices are now capable of playing video
files, which paves the way for providing rich sources of multimedia educational

materials to learners.
2.2. M-commerce Technologies
2.2.1. General Packet Radio Service (GPRS)
GPRS, referring to General Packet Radio Service, is defined by Buckingham
(2000) as a non-voice service that permits to transmit data speedily. In another
word, it is considered as a packet-switch technology allowing data sent to be
broken into small packets which are transmitted by the network between different
positions based on dispatching data within each packet (Tiwari et al., 2006). GPRS
enabled mobile devices, which depend on network coverage of the geographical
areas, always access to network. Those devices do not require a dial-up connection
to obtain information (Buckingham, 2000). Also, Buckingham (2000) stated that an
access to services such as E-mail, Internet-based webpages, music, and office
application is also provided by GPRS. Besides, the volume of the emitted data is
paid only and not the time required in the downloading process when users use
GPRS services.

11


2.2.2. Wireless Application Protocol (WAP)
WAP Forum developed WAP by employing a collective set of applications and
protocol. By using WAP, the interoperability among various wireless networks,
devices, and applications is enabled. Moreover, WAP employs a micro browser
which assists graphics, text, and standard Webpage content. Besides, the WAP
Gateway which is the most crucial technology applied to WAP, is essentially
considered as a border between the Internet and the Network. The Gateway plays a
role as a proxy which delivers WAP requests to protocols operated by the
information server. Also, the WAP Gateway performs as an interpreter between a
mobile device and a web server which interprets and translates the information to
help the server and the mobile device communicate each other (Lei et al., 2004).

According to WAP Forum 2001 (as cited in Wang et al., 2006), WAP presents an
wide industry specification for improving applications which run on mobile
telecommunication network and send Internet contents via mobile devices without
using technologies of network carriers.
2.2.3. Wireless Local Area Network (WLAN)
The WLAN technology is applied to wireless communication and assists data
transmit rates up to 54 megabits per second which is faster than 3G (Kaemarungsi
and Krishnamurthy, 2004). Mostly, developing WLAN systems is based on the
standards presented by the US Institute of Electrical and Electronics Engineers
(IEEE). Besides, Access Points which are known as Hotspots provides the interface
between mobile devices and WLAN. Moreover, the range in which allows users to
connect to WLAN is approximately 100 meters in building blocks and 300 meters
on open ground. Furthermore, WLAN enables subscribers to use data-intensive
mobile applications outside of their house or offices in compared to the standards
of the 3G technology.

12


2.2.4. The Third Generation - 3G
The aim of the 3G technology is to offer a broad range of services such as highspeed internet access, video call and interactive multimedia services (Tiwari et al.,
2006). Thanks to the high speed of data emitted, the 3G technology has become
more suitable for time-critical applications. Tiwari et al. (2006) also mentioned that
the 3G standard is based on a radio access technology called Wideband Code
Division Multiple Access. Those standards use the Direct Sequence Spread
Spectrum (DSSS) in a 5-MHz bandwidth. Moreover, mobile devices are required
to be compatible with the GSM/GPRS standards because 3G can perform strongly
in municipal areas.
2.2.5. The Fourth Generation - 4G
4G, or Fourth G, which stands for fourth-generation wireless communication

technology, allowing data transfer with maximum speed in ideal conditions up to
1.5 Gb/ second. The name 4G was set out by IEEE to express meaning "3G and
beyond". 4G technology is understood as the future standard of wireless devices.
The Japanese operator NTT DoCoMo defines 4G by introducing the concept of
mobile multimedia: anytime, anywhere, anyone; global mobility support;
integrated wireless solution; and customized personal service (MAGIC) (Murota,
as cited in Frattasi, 2006). In the world now, there are two standards of 4G
network's core technology. They are WiMax and Long Term Evolution (LTE).
Both WiMax and LTE are using the advanced transmitting technology to enhance
the ability of reception and operation of equipment and networks. However, each
technology uses a different frequency bank. A wireless network using 4G
technology will have the speed of 4 to 10 times faster than 3G’s, allowing users to
download and transfer high quality animation.
2.3. Technology Acceptance Model (TAM)
As M-commerce is a type of technological innovation (Lin and Wang, 2005);
existing theories and studies on innovation adoption could be used in the studies of

13


M-commerce. One of the most common models used by researchers in the studies
of individual’s adoption of technology is Technology Acceptance Model (TAM),
which was first proposed by Davis in 1989 based on the Theory of Reasonable
Action (TRA) (Ajzen, 1991). The TAM has been used to predict users’ intention to
accept or adopt varieties of technology and information systems, and has also
recently been used to predict the Internet and M-commerce adoption. O'cass and
Fenench (2003) argued that the TAM is appropriate for research areas in Ecommerce applications since E-commerce is based on computer technology. As
scholars indicate that M-commerce is an extension of E-commerce, the TAM can be
applied to M-commerce. The TAM proposed that both the perceived usefulness and
perceived ease of use can be used to predict the attitude towards using new

technology, which in turn affects the behavioral intention to use the actual system
directly (Davis, 1989; Venkatesh et al., 2003).
However, many researches state that TAM itself is insufficient to explain users’
decisions to adopt technologies. Mathieson et al. (2001) argued that the TAM is
limited by the lack of barriers that inhibit the individual from using an information
system (IS) if he or she chooses to do so. One of the approaches uses the TAM as a
base model and extends the model by adding additional variables to it depending
on the types of technologies they studied. This extended TAM maintains the
primary simplicity of the TAM and improves the ability to predict and explain IS
usage at the same time (Mathieson et al., 2001). Kamarulzaman (2007) on his study
of internet shopping adoption drew upon the TAM and included personal and
cognitive influence. Amin (2007) also modified the original TAM by including
perceived credibility and the amount of information on mobile credit card to his
study of mobile credit card usage intentions. Various extensions to the TAM were
also conducted in the study of M-commerce such as those conducted by Wu et al.
(2005) used the TAM as a base and included some factors such as perceived risk,
cost and compatibility. Wei et al. (2009) on his study on mobile commerce
adoption in Malaysia added to the TAM three additional constructs: social
influence, perceived cost and perceived trust which derived from Ajzen’s Theory of
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Planned Behavior (TPB) and Rogers’ Innovations Diffusion Theory (IDT). Schierz
et al. (2010) extended the TAM by including four additional constructs: perceived
compatibility, security, individual mobility and subjective norm. Gil-Lafuente
(2011) modified the TAM by adding three factors: incentives, perceived enjoyment
and social influence. Jeong and Yoon (2013) on his empirical investigation on
consumer acceptance of mobile banking services put perceived credibility, selfefficacy and perceived financial cost to the TAM.
Based on the theoretical and empirical support from the existing studies, this
research will also extend the TAM by including three additional constructs which

we believe are the most important for the studies of M-commerce adoption in
Vietnam, they are compatibility (CO), perceived cost (PC) and perceived trust (PT),
as explained below.
2.4. Rationale for hypotheses
2.4.1. Perceived usefulness and the behavioral intention to use M-commerce
Perceive usefulness (PU) is defined as the degree of which an individual believes
that using a system would improve his or her job performance (Davis, 1989).
The effect of the PU on intention to use (IU) has been validated in many existing
studies (Luarn and Lin, 2005; Lin and Wang, 2005; Guriting and Ndubisi, 2006).
For instance, Wong and Hiew (2005) recommended that the usage of Mcommerce is strongly determined by the usefulness of the mobile service, which
includes ubiquity, personalization, localization, timeliness and network stability.
Wei et al. (2009) examined mobile commerce adoption in Malaysia. In his
findings, PU was empirically found to be the most significant determinant to
predict consumers’ intention to use M-commerce in Malaysia. Thus, based on
findings shown above, it is highly supported that the general results studied in
the TAM are also applied to M-commerce services. Hence, the following
hypothesis is presented:

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H1: Perceived Usefulness has a positive effect on behavioral intention to use
M-commerce.
2.4.2. Perceived ease of use and the behavioral intention to use M-commerce
Another key element in the TAM is the perceived ease of use (PEU). The PEU
refers to the degree to which a user perceives that an information system (IS) is
easy to understand and use (Davis, 1989). The PEU for a system is defined as the
degree to which an individual believes that using a particular technology will be
free of effort. The results of many of the prior empirical studies have demonstrated
that the PEU has a positive correlation with behavioral intention (Davis, 1989;

Venkatesh and Davis, 2000; Gefen, 2000; Gefen et al., 2003; Venkatesh et al,
2003). A few empirical studies tested ease of use as predominant determinant of
intention to adopt (e.g. Agarwal et al., 2000; Karahanna et al., 1999). It is one of
the major behavioral beliefs influencing users’ intention to technology acceptance
in both the original and revised TAM and it has been included in the studies to
determine this influence the M-commerce intent as well. Hong et al. (2006) stated
that the perceived ease of use has an impact on the behavioral intentions to use in
terms of mobile commerce services. Therefore, a hypothesis is suggested to
present this relationship between those variables:
H2: Perceived ease of use has a positive effect on the behavioral intention to
use M-commerce.
2.4.3. Compatibility and the behavioral intention to use M-commerce
Innovations Diffusion Theory (IDT) is one well-known theory proposed by Rogers
(1995). In recent decades, IDT has been widely used for relevant IT and IS
researches (Karahanna et al., 1999). The central concept of innovation diffusion is
the process in which an innovation is communicated through certain channels, over
time, among the members of a social system. IDT includes five significant
innovation characteristics: relative advantage, compatibility, complexity, trial
ability, and observables. These characteristics are used to explain the user’s

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