mobile banking in malaysia
TRANSCRIPT
INTENTION TO USE MOBILE
BANKING IN MALAYSIA: ASSESSING KEY
DETERMINANTS
BY
NEBIL ABDUREZAK AHMED
A research project submitted in partial fulfillment
Of the requirements for the degree of
BACHELOR OF BUSINESS ADMINISTRATION (HONS) B.B.A. (Hons) BANKING & FINANCE
FACULTY OF BUSINESS AND LAW
MULTIMEDIA UNIVERSITY
JANUARY 2011
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Chapter 1
Introduction
1.1 Research background
“The rapid technological advances in mobile-based technologies have created
opportunities for new and innovative mobile services. Some of the most promising,
while still marginally adopted, is mobile banking. Many commercial banks in Malaysia
have tried to introduce mobile banking systems to improve their operations and reduce
costs”, (Amin et al., 2008). Some say that internet is considered the greatest most
effective device innovated by mankind since the discovery of the wheel. Due to the
consistent use of the internet, it has brought about ideas such as implementing mobile
devices in areas like banking, and that is where they come up with Mobile Banking or m-
banking in short. “The mobile banking environments are getting more and more
implicated gradually, New and innovative ideas in mobile banking can lead to useful and
effective approaches and models in business transactions, especially in requirements
elicitation, service provider’s recognition, negotiation and agreements” (Soroornejad and
kharazian, 2010). In this innovative community, mobile devices can access internet from
various locations allowing the users to participate in typical internet-mobile based
activities which also includes Mobile Banking. Watson et al., (2002) stated that mobile
services on consumers because they allow ubiquitous and universal access to information
and services, in addition to the possibility of accessing a unique and personalized
exchange of data. As a result, the use of mobile devices has become a part of most
people’s daily life, and also a technique that helps to keep in touch with the rest of the
world, plus to communicate and network (Shi Yu, 2009).
Mobile banking is a developing mobile technique used in the commercial field,
which has merged information technology and commerce applications together. Rather
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than visiting the traditional bank branch for personal transactions, after mobile banking
was introduced to the world, consumers were able to enjoy special services 24 hours a
day, in a more convenient and sufficient fashion.
Mattila (2003) was interested in investigating the factors that influenced one’s
decision to use mobile phone for banking transactions. Therefore, Mattila (2003)
discovered that “pay bills cheaper”, “have faster data transmission rate” and
“authenticate with mobile phone to Internet bank” were the factors which influenced
individuals to use mobile phones for their banking transactions.
Porteous and Wishart (2006) stated that mobile banking is considered one of the
newest approaches to the stipulation of financial services through ICT, which was likely
possible by the widespread adoption of mobile phones even in low income countries.
Some of the features that mobile banking has covered were fund transfer and bill
payment where customers have the complete freedom to maintain their account via
mobile (Anyasi and Otubu, 2009). The results banking industry have experienced due to
the revolution are minimum balance alerts, account statement enquiry, cheque status
enquiry, account balance enquiry, bill payment alerts and cheque book request (Anyasi
and Otubu, 2009).
Regardless of all the attempts aimed at developing a sufficient and satisfying
mobile banking, and despite its availability, this system can be easily unnoticed. Mobile
banking is still considered new, which leaves Malaysia with a great deal of room for
development. Therefore, there is a need to understand bank customers’ reaction towards
mobile banking and to observe the factors affecting their intentions to use mobile
banking, (Amin et al, 2008).
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1.2 Problem Statement
Regardless to the facts that there has been a lot of research papers conducted on the
topic of Mobile banking abroad, unfortunately only few studies were carried out in
Malaysia. This is probably due to the fact that Mobile banking is to some extent new in
Malaysia. Therefore, the lack of information on this topic resulted in insufficient
knowledge and literature on the key determinants in Mobile banking adoption within
Malaysia. Evidences and conclusions that have been conducted abroad can be somehow
useful but it might not be consistent and accurate in the perspective of mobile banking in
Malaysia. Due to the reasons listed above, more research on this topic should be covered
to validate whether the results from these studies would be reliable to Malaysia.
Besides that, there are also corresponding facts when comparing when comparing
this study with previous studies. For example, Amin et al., (2008) stated that when
deciding whether to accept mobile banking or not, perceived usefulness and perceived
ease of use were to found to be significant factors.
In previous works, several studies supported valid arguments on perceived
credibility. For instance, Wang, et al., (2003) and Luarn and Lin (2005) stated that the
intention to use mobile banking was influenced by security and privacy associated with
mobile banking environment. Mattila (2004) pointed out that the adoption of mobile
banking services were influenced with factors such as data transmission, costs, and
authentication of mobile phone to internet bank, likelihood to conduct banking truly
regardless of time, place, and curiosity towards using the services.
Cheong and Park (2005) indicated in their studies that the success of mobile internet
depends on literally understanding the concerns of customers and classifying the factors
that enhance the use of mobile banking. Laforet and Xiaoyan (2005) on the other hand
investigated the market status for online/mobile banking in China, and with the current
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and anticipated high growth of Chinese electronic banking, it likely has the potential to
develop into a world-scale internet economy.
Laforet and Xiaoyan (2005) indicated that the issue of security was found to be
the most significant factor that induced the Chinese consumers to adopt online banking.
Jayawardhena & Foley (2000) indicated that ensuring security and confidentiality are the
basic prerequisites before any banking activity relating sensitive data can take place.
This paper attempted to assist improvement of mobile banking services through
investigating the customer adoption. In addition, this paper discovered the relationship
between several variables such as perceived usefulness, perceived ease of use,
compatibility, perceived self-efficacy, subjective norms, perceived credibility, perceived
risk and user predisposition, and the adoption of mobile banking. Models such as TAM
and Extended TAM were used and adopted to help classify the variables that will
influence users’ intention to adopt mobile banking.
1.3 Research Questions
1) What are the key factors that influence the intention to use mobile banking
services in Malaysia?
2) What are the opportunities and challenges in mobile banking?
3) How is it best to evaluate a mobile banking application or service in terms of
its adoptability?
1.4 Research Objectives
1) To examine the factors that influences the intention to use of mobile banking
services in Malaysia.
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2) To examine the opportunities and challenges in mobile banking.
3) To evaluate mobile banking service in terms of its adoptability
1.5 Significance of Research
Since the topic of Mobile Banking is relatively new in Malaysia, there are a lot of
gaps which needs to be covered. This paper work is an addition to the limited number of
current literatures on the topic of Mobile Banking in Malaysia. A theoretical model was
presented and also was implemented in order to classify the key determinants of users’
adoption of Mobile Banking. The central aim of this paper was to identify the
determinants of Mobile Banking adoption among the citizens in Malaysia and also aims
to fill the gaps between previous researches that were conducted in Malaysia.
This research can be handy for several parties. Since there are insufficient
previous paper works regarding the factors that influence the adoption of Mobile
Banking in Malaysia, future researchers can use this study as a reference to their work.
Governing bodies can also use this study in order to stimulate the growth of Mobile
Banking. By identifying the factors or determinants, the governing bodies will then have
the advantage of a transparent picture on the scenario Mobile Banking adoption in
Malaysia.
1.6 Scope of the research
The scope of this research includes students of Multimedia University from the
Faculty of Engineering, Faculty of Information Science and Technology and students
from Faculty of Business. The group that will be focused on will be the mobile
subscribers, age between 20 -50.
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The scope also included examining the factors that influence the users’ choice
whether or not to adapt the usage of Mobile banking in their daily lives. The study also
took a glance on various definitions of mobile banking and its history and future in
Malaysia.
1.7 Definition of terms
In this study, the term Mobile Banking is defined as, “Mobile banking (m-banking)
involves the use of a mobile phone or another mobile device to undertake financial
transactions linked to a client’s account. M-banking is one of the newest approaches to
the provision of financial services through ICT, made possible by the widespread
adoption of mobile phones even in low income countries, (Porteous et al., 2006).
The term “internet banking” is defined as; “Internet banking” refers to systems that
enable bank customers to access accounts and general information on bank products and
services through a personal computer (PC) or other intelligent device” (Comptroller’s
Handbook,1999).
1.8 Structure of the Project
The first phase of this research consisted of three chapters, which contains data
regarding the topic. The three chapters were divided into Introduction, Literature review
and the Research Methodology.
Chapter one, was the introduction chapter. It briefly covered the topic of this
research, i.e. Mobile banking or m-banking. This chapter began with the introduction,
which consisted of brief but sufficient information about m-banking. Chapter one also
clarified the problem statement and the research objectives and what are the things need
to be done to achieve them. Significance of research and the scope of the research were
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also covered in this very chapter. Finally, this chapter was concluded with a summary
which explained chapter one in short.
Chapter two was the Literature review. This chapter contained literature reviews from
previous studies conducted related to the topic (m-banking). This chapter started with a
brief introduction about mobile banking. Then it covered a vast amount of data or
literature on mobile banking. Definitions of mobile banking from previous works were
cited in this chapter, not to forget the history and the evolution of mobile banking. On the
other hand, prior researches on mobile banking adoption in USA, Europe and Malaysia
were also covered in this chapter. Models such as Technology Acceptance Model (TAM)
and Extended TAM were elaborated in this chapter which therefore was adopted and
enhanced in this study.
Chapter three covered the Research Methodology, which provided a specified
designation on the instruments used in the data mining process. The conceptual
framework was also covered in this chapter, how the independent variables influence
dependent variables and the suggested hypotheses. Besides that, the questionnaire
design, measurement of the variables, data collection method, data resources, sample
size & population size, units of analysis and data analysis techniques were all covered in
this chapter.
1.9 Chapter Summary
Chapter one provides a brief introduction about mobile banking. It states the scope of
the study which includes students of Multimedia University. This chapter also gives us a
collection of key attributes correlated with the research topic and presents a prelude idea
about our topic. It also explains the course of this research and what is expected from it.
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Chapter 2
Literature review
2.1 Introduction
Financial service is experiencing a period of unprecedented change- new entrants,
new product, downsizing, mergers and acquisitions, in addition to the new delivery
channel: the internet (Birch and Young, 1997). Despite all the millions of dollars that
have been spent on building internet banking system, studies and reports have indicated
that potential users may not use the system in spite of their availability. This points out
the need for further research to identify the factors that determine the acceptance of
Internet banking by the users. (Wang et al., 2003). In this chapter, previous researches
that have been conducted about mobile banking will be analyzed and discussed. Various
definitions and opposing definitions will be discussed thoroughly. In addition, the
background information about mobile banking will be discussed in this chapter. Besides
that, various reasons why consumers choose to adopt mobile banking will be discussed.
The position of mobile banking in other countries plus Malaysia will also be looked at in
this chapter. Moreover, the essential factors that influence mobile banking acceptance
will also be talked about.
2.2 Definition of mobile banking
There is a variety of different explanation for mobile banking; this might be due to
the fact that mobile banking is relatively new. Mwaura (2009) defined M-banking as “the
provision and availment of banking-and financial services with the help of mobile
telecommunication devices. The scope of offered services may include facilities to
conduct bank and stock market transactions, to administer accounts and to access
customised information”. According to Porteous and Wishart (2006), mobile banking is
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“Mobile banking (m-banking) involves the use of a mobile phone or another mobile
device to undertake financial transactions linked to a client’s account. M-banking is one
of the newest approaches to the provision of financial services through ICT, made
possible by the widespread adoption of mobile phones even in low income countries.
Wilcox (2010) defines mobile banking as “the provision of banking services to
customers on their mobile devices”: specifically we mean in the vast majority of
instances “the operation of bank current and deposit or savings accounts”.
Weber and Darbellay (2010), describes the term as “Mobile banking activities fall within
the scope of the banking business, and oversight is provided by the competent financial
market authority for prudential supervision, if the definition of banking activities
encompasses all relevant mobile banking activities.
The features of mobile banking and electronic banking are almost identical due to
the fact that the services provided by both ends are carried out electronically by
computer- intervened networks, which are reachable using telecommunication networks.
The only difference is that mobile electronic devices are the telecommunication
networks used for mobile banking. In Korea, a survey was conducted by Yong and
Gorman (2002), and it was stated that there was relatively a 400 percent increase in the
level of mobile banking service use in 15 months, as revealed in figure 1.1:
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Table 2.2 Use of mobile banking services (unit: cases)
Service December 2000 December 2001 December 2002
Inquiry 200,552 691,883 817,111
EFT 1,746 18,319 25,241
Total 202,298 710,202 842,352
Change -- 251.1 18.6
Note: Transaction cases during the month indicated
Source: The Bank of Korea (2002)
Figure 2.2: use of mobile banking in Korea
Source: Journal of online Information Review, Yong and Gorman (2002)
A recent research in Ireland has established that approximately 1% of
consumers use mobile banking services while almost 90% of their population own
mobile phones (Foley, 2005). The use of mobile banking basically focuses on the basic
functions provided by the mobile banking service rather than the complex ones.
A survey question was asked by a recent Forrester research: “What mobile banking
activities would you mostly be interested in?” as seen in Figure 1.2 (Foley, 2005).
Figure 2.2 mobile banking activities
Source: ireach, www.ireach.ie
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As shown in figure 1.2, the majority of consumers did not use mobile banking at
all. Those who considered using the service used it only for simple functions such as
checking account balances. Complicated functions of mobile banking have not been
reflected on (Foley, 2005).
2.3 Evolution of mobile technology
The first radio telephone was discovered in US at the late 1940s and the main
reason behind that was to connect mobile users in vehicles to the public network. In the
1960s, a new system called Improved Mobile Telephone Service (IMTS) was initiated
by Bell system (Take, 2010). For an easier and more adequate explanation of mobile
technology, the innovation has been simplified and categorized into 4 groups of
generations. Each one of these generations is an advancement or improvement of the
previous generation. These generations are categorized as, first generation (1G), second
generation (2G) and (2.5G), third generation (3G), and finally the fourth generation (4G).
Ashiho (2003) stated that the first generation of mobile technology or 1G had only
voice facility as the main feature and that the mobile phones were based on the analogue
system. During the 1970s, 1G analog system for mobile communications saw two
significant developments: the invention of the microprocessor and digitization of the
control link between the mobile phone and the cell site (S. Take, 2010). In addition to
that, the semi-conductor technology and microprocessors made mobile systems smaller,
lighter, and more sophisticated a reality. The well known among first generation systems
were advanced mobile phone system (AMPS), Nordic mobile telephone (NMT), and
total access communication system (TACS). Besides that, since the introduction of 1G
phones to the world, the mobile market experienced an annual growth rate of 30 to 50
per cent, subscribers rising to nearly 20 million by 1990 (Ashiho, 2003).
In Europe in the early 1990s, 2G phones using global system for mobile
communications (GSM) were used. Ashiho (2003) mentioned that the motivation behind
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developing 2G cellular systems was the need to improve transmission quality, system
capacity, and coverage. Take (2010) stated that “the new system (2G) provided better
quality and higher capacity at lower cost to customers”. GSM was also the first
commercially operated digital cellular system which is based on TDMA (Take, 2010).
GSM was also considered as the most successful family of cellular standards, which
includes GSM900, GSM-railway or (GSM-R), GSM1800 (Ashiho, 2010). The GSM has
also the ability to operate as dual-band or tri-band phones, as they are adaptable to the
local frequency system in the region the user travels through. (The Mobile Phone
Directory. 2009). Just like 1G, the main transmission that controls the airways is speech
transmission, but it has been mentioned that the demand for fax, short message, and data
transmission is growing rapidly (Ashiho, 2003).
Ashiho (2003) adds that 3G technology adjoined multimedia facilities to 2G
phones by allowing applications such as video, audio, and graphics. Take (2010)
mentioned that “ITU’s IMT-2000 global standard for 3G has opened the way to enabling
innovative applications and services (e.g. multimedia entertainment, infotainment and
location-based services, among others)”. Hill (2010) stated that one of the main purposes
behind the development of 3G was to obtain a single network standard rather than
different types of network standards, which was lately adopted in Europe, U.S. and other
areas. A 3G cellular device known as UMTS (Universal Mobile Telecommunications
System) or IMT-2000 appeared to maintain higher data rates and open the gate to
internet style applications (Hill. 2010).
Ashiho (2003) cited that 4G mobile communications will have transmission rates
reaching up to 20 Mbps. Other 4G applications include high-performance streaming of
multimedia content based on agent technology and scaleable media coding methods. Hill
2010, mentioned that by the year 2010, “4G will enable 3D virtual reality; imagine
personal video avatars and the ability to feel as if you are present at an event when
actually you are not. People, places and objects will be able to interact as the cyber and
real-world blend.”
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Table 2.3 Standards used in different Generations of Mobile Technologies
1G 2G 3G
. Paging systems
. Cordless telephone
(CTO, CTI)
. Cordless telephone cell
. Private mobile radio
. Cellular systems
(NMT, AMPS, etc)
. Mobile satellite
systems
(INMARSAT)
. Paging systems
. Cordless telephone (DECT,
PACS)
. WLL
. Private mobile radio (TETRA)
. Cellular systems (GSM, D-
AMPS, PDC, IS-95)
. Mobile satellite systems
(IRIDIUM, ICO,
GLOBALSTAR)
. Single standard under
IMT-2000,
UMTS, MC-
CDMA, TD-
SCDMA
Source:
ASHIHO, L. (2003). Mobile Technology: Evolution from 1G to 4G.
2.4 Mobile Banking in Europe
The adoption of mobile banking ought to rapidly increase in major European
markets. The mobile phone delivery channel symbolizes a challenge for the European
banking industry, permitting institutions to distinguish themselves from rivalries, reduce
costs, and develop customer loyalty. The adoption of mobile banking should increase
rapidly in major European markets over the next few years, from an average of 6% today
to 25% of the Spanish, French, Italian, and British markets by 2010. Regardless,
significant barriers still remains, such as general lack of awareness, technological issues,
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customers’ perception of security, and more importantly, the cost of mobile internet are
major obstacles to mass market mobile banking adoption. If mobile Internet usage
increases, we can expect a large number of users to interact with their banks via their
mobile phones as they currently do online.
2.4 Adoption of Internet Banking and Mobile Banking in Western Europe
European banks have predicted the termination of adoption barriers and have
already launched various mobile banking services using mostly the WAP and SMS
technologies. In UK and Germany only few downloadable applications have been
counted successful. French, Spanish and Italian banks are currently offering a wider
range of mobile services. Nevertheless, there are still many differences between
countries regarding the number and type of mobile banking services offered. Information
and SMS services are the most common at the European level.
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2.5 Mobile banking in Malaysia
Previously, SMS banking was only available at Bank Islam Malaysia Berhad
(BIMB) but now this banking facility is available at most commercial banks in Malaysia.
Lately, Bank Simpanan Nasional (BSN) offered SMS banking to its customers for the
purpose of account balance query, bill payment and more. SMS/Mobile banking was first
introduced in 2004 in Malaysia. Ever since, SMS banking has become an interesting
topic of research, not only in Malaysia but also in other countries (Mattila, 2003;
Kleijnen et al., 2004; Laforet and Li, 2005). Mobile banking is still considered new,
leaving a great deal of room for development in Malaysia. Therefore, there is a need to
understand bank customers’ acceptance of mobile banking and to observe the
determinants affecting their intention to use mobile banking. This type of information
can help commercial banks including BIMB in building of mobile banking that the
customers favor to use, therefore assist them to attract potential users to use the system.
Due to the fierce competition in the banking industry in Malaysia, hence each bank
out to be creative and innovative in order to be competitive enough to stay in the game.
One of the value added services that the commercial banks have considered is mobile
banking or SMS banking. Prior studies have stated the need of mobile banking services
in the society (for example, Amin et al., 2006; Luarn and Lin, 2005; Mattila, 2004).
Previous studies also assisted to lay an understanding on “why mobile banking is
important”? In essence, there were three key determinants. Firstly, mobile banking offers
a new opportunity to banks to extend their services to their customers and therefore
improve their competitiveness (Kohli, 2004). Secondly, mobile banking is considered to
be one of the most value-added and significant mobile services (Datamonitor 2000 as
cited in Lee, et al., 2003). Thirdly, mobile banking offers an interactive banking
transaction (Mattila, 2004). A study conducted in Bank Islam Malaysia Berhad (BIMB)
came up with solutions that would help in improving the adoption of mobile banking in
their respective bank and in Malaysia in general. It was suggested that the bank could
organize training courses for mobile banking, and that it should be available at all the
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branches in Malaysia. The study also discovered that the amount of information on
mobile banking is an influential factor that would affect an individual’s intention to use
mobile banking. Therefore, it is believed that sufficient information on mobile banking
will have a positive impact on the customers. A survey by the Malaysian
Communications and Multimedia Commission exposed that the penetration rate for
mobile users in the country for the second quarter was about 90% -- double the number
of internet penetration (Dhesi, 2008). Dhesi (2008) also states that according to the
survey, the high penetration rate confirmed that mobile phone networks had become an
increasingly popular channel for Malaysians to carry out a plethora of activities beyond
just voice communication and text messaging. Industry players and analysts coincided
that there was a significant level of awareness and usage of mobile phones beyond just as
a communication tool and, therefore divines well as a potential electronic banking
channel. The advantage that mobile banking has over other banking channels is that it
allows customers to perform their banking activities anytime and anywhere.
Standard Chartered Bank Malaysia Bhd (StanChart) country head of consumer
banking Ho Toon Bah informed StarBiz: “StanChart was the first bank in April to offer
smartphone technology mobile banking in the country, underscoring our innovative
approach in leveraging technology to bring new products and services to customers.
“Our customers have embraced this new channel of banking at a rapid pace. Almost
one-third of our Internet banking customers have signed up for mobile banking and we
are confident that this base will grow rapidly as we continue to enhance the range of
services and transactions available on this platform.”
According to Ho, StanChart was looking forward at how the mobile channel could
serve and add convenience to its corporate clients. He mentioned that the group was
developing prototypes of new service models and would quickly release them into the
market, rather than waiting for years to come up with a fool-proof model before rolling it
out.
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Citibank Bhd head of consumer e-business Roy Heong said that mobile banking was
a key growth strategy for both the bank and the group globally. “We are looking into
extending account information and bill payments to a bigger base using text messaging.
“We will also target customers who are looking for more functionality via a J2ME (Java
Platform Micro Edition) application on Java-enabled devices and leveraging on the third-
generation (3G) and General Packet Radio Service infrastructure. “Importantly, the
initiatives proposed must fit into our strategy to ensure high relevance and best-in-class
experience for our customers,’’ Heong added.
To improve its mobile banking channel, OCBC Bank (M) Bhd head of consumer
financial services Charles Sik said the bank’s target now was to promote the service to
its existing customers. “This way, we believe, those who have been a little hesitant in the
beginning will appreciate more quickly why mobile banking really does add depth to the
idea of convenience,” Sik said.
CIMB Bank Bhd last month mentioned that it expected about 1.3 million existing
CIMB Clicks users and new customers to use its newly-launched mobile banking
service. Named “CIMB Clicks Mobile Banking”, it is considered the first to have
internet banking features and capabilities, compared with other mobile banking services
which use SMS to make transactions. Although there are challenges and issues facing
mobile banking, its leverage is huge judging from the phenomenal growth and usage of
mobile phones.
2.5.1 Malaysian Communications and Multimedia Commissions
The Malaysian Communications and Multimedia Commission is the regulator for
congregating communications and multimedia industry based on the powers presented
for in the Malaysian Communications and Multimedia Commission Act (1998) and the
Communications and Multimedia Act (1998). Pursuant to these Acts, the role of the
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Malaysian Communications and Multimedia Commission is to execute and promote the
Government’s national policy objectives for the communications and multimedia sector.
In 2001 MCMC’s role was added to monitor postal services. In addition, MCMC also
acquired the role as a Certifying Agency under the Digital Signatures Act. The key roles
of the MCMC’s in the telecommunications sector are:
Technical regulation, including allocation of frequency spectrum, telephone numbers and
electronic addresses;
Economic regulation includes promotion of competition and prohibition of anti-
competitive conduct. It also includes licensing, enforcement of license conditions for
network and application provider, in addition to ensuring compliance to rules and
performance/service quality.
Social regulation including content development and regulation.
Consumer protection, emphasizing empowerment of consumers and ensuring adequate
protection measures in areas such as dispute resolution, service affordability and
availability.
In Malaysia, the MCMC are the body responsible for regulating the communications
industry, issue licenses and to implement the communications and multimedia laws (MCMC,
n.d). The licensing system allows a licensee to take on market specific activities. for this
reason, it is possible for advancement for Applications Service Providers to come up with
newer and more proficient usage of the Network Structure. There are four categories of
licensable activities as stated on the MCMC’s website.
1. Network Facilities Providers – Owners of facilities like satellite earth stations,
broadband fibre optic cables, telecommunications lines and exchanges,
radiocommunications transmission equipment, broadcasting transmission towers and
equipment and mobile communications base stations. These are the fundamental
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building block of convergence model upon which network, applications and content
services are provided.
2. Network Services Providers – Provide the basic connectivity and bandwidth to support
a diversity of applications. Network services permit connectivity or transport between
different networks. A network service provider is distinctively also the owner of the
network facilities. Nevertheless, a connectivity service may be offered by a person using
network facilities owned by another.
3. Applications Service Providers – Provide specific functions like voice services, data
services, content-based services, electronic commerce and other transmission services.
Applications services are essentially the functions which are delivered to end-users.
4. Content Applications Service Providers – Special subset of applications service
providers including traditional broadcast services and newer services such as online
publishing and information services.
2.5.2 MyICMS 886 Blueprint
The development and widespread usage of Information Communication
Technology ICT are central to the realization of vision 2020 of a knowledge based
economy. The ICT industry is very important in consideration to the growth of the nation
not only because of the revenue and investments which it brings in, but also because it
serves as an important element in the manufacturing process of other goods and services.
Malaysia has been ranked globally, as the third most favored location for outsourcing of
business processes. Besides that, the ICT in a country is often seen and defined as the
competing power of the country. Highlighting those significant facts, the Minister of
Energy, Water and Communications launched MyICMS 886 which is the blueprint for
the communications and multimedia for 2006 through 2010. This blueprint presents an
inclusive strategy that addresses the core characteristics of the industry.
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The Malaysian Information, Communications and Multimedia Services strategy
incorporates eight (8) services, eight (8) Infrastructures and six (6) Growth Areas.
According to the MyICMS 886 blueprint, the eight services are High Speed Broadband,
3G and beyond, Mobile TV, Digital multimedia broadcasting, Digital home, Short range
communications using RFID, VoIP/Internet telephony and Universal Service
Provisioning. To support the compress of these, concentration will be on the provision of
hard infrastructure such as Multi-convergence networks, 3G Cellular Networks and
Satellite Communications Networks. To complement the hard infrastructure, we will also
need to develop and implement the required soft infrastructure comprising of next
generation internet protocol or IPV6, Information and Network Security, Internet
Adoption, Skill Development and Enhanced product and design capabilities. As for
generating growth, the six areas that have been categorized are Content Development,
ICT-Education Hub, Digital Multimedia Receivers, Communication Devices, Embedded
Components, Devices and Foreign Ventures (Ministry of Energy, Water and
Communications, 2006).
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Table 2.5.1 MyICMS 886 Service Goals
2006 2008 2010
1 Digital Homes Home gateway/Soho introduced in 60,000 homes
0.5 homes interwork with
external networks
1M connected homes
2 Short Range Communicati
on
Standards/SpectrumAllocated
Extensive usage in supply chain
management
Widespread use in
various applicati
ons
3 VoIP/Internet Telephony
Established QoS-Voip to PSTN
Service revenue RM
0.8b
Residential and
business service revenue of Rm1b
High Quality and
cheaper voice
servicesRM 1.5b
service revenue
4 USP: Universal Service
Provision
New USP Projects Broadband
internet community
project
Increased Broadba
nd internet
individual acess
60% coverage
for underserved rural houseold
s5 High Speed
Broadband1.3m subscribers
25% households
2.8m subscribers 50%
household
Total Broadba
nd penetration 75%
household
6 3G and Beyond 0.3m subscribers 1.5m subscribe
rs
At least 6m subscrib
ers
7 Mobile TV Further pilot service
Standards
75% mobile users adopt
Multimedia service
anywher
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adopted mobile TV
e, anytime 90% of
total mobile users
8 Digital Multimedia
Broadcasting
Standards adopted DTTB Trials
Initial commercial deployment
60% househol
d coverage
for DTTB
95% househol
d coverage
Source: Ministry of Energy, Water and Communications (2006). The Malaysian Information. Communication and Multimedia Services 886 (MyICMS 886)
Table 2.5.2 MyICMS 886 Infrastructure Goals
2006 2008 200101 Multiservice
Convergence Network (MSCN)
Migration of platform-
based services
Complete migration of
legacy service Fixed-mobile convergence
platform ready
Multiple services, Fully IP-
based
2 3G Cellular Introduction of High Speed Data
High speed mobile data services; Interworking of BWA with
3GPP
Nationwide 3G
services coverage
3 Satellite Networks
National policy on
satellite-based
communications
Satellite as a complementing transmission
medium
Critical services
reachable using
satellite
4 Next Generation Internet Protocol (IPv6)
Pilot of IPv6 services; All ISP are IPv6 enabled
Government agencies
adopt IPv6
Ipv6 full device
and network complian
23
ce5 Home Internet
Adoption“One Home
One Internet Access”
campaign
70% household with internet
access
90% househol
d with internet access
6 Information & Network Security
Information and network security portal installation of network security measures compliance to
international security standards
7 Competence Develop
ment
Initiate programs for competence development upgrading and enhancing competencies develop R&D
capabilities
8 Product Design
and Manufact
uring
Capacity building Original Equipment manufacturing High-tech communication industries
Source: Ministry of Energy, Water and Communications (2006). The Malaysian Information. Communication and Multimedia Services 886 (MyICMS 886)
Table 2.5.3 MyICMS 886 Growth Areas Goals
24
2006 2007 2008 2009 20101 Content
Development Promote creativity and awareness
Strategic alliance with regional partners
Sizeable content export that will contribute to
communications and multimedia industry revenue
2 ICT Education Hub Promote e-learning
Ensure high quality education and training systems
Regional center for ICT education excellence
3 Digital Multimedia Receivers
Adopt open standards configuration for
manufacturing
Local production available in retail market
Recognized producer of digital radio receivers and
set top box
4 Content Development
Prototype communication devices
Malaysian made communication devices
Proliferation of communication devices for
domestic market
5 Embedded Components &
Devices
Promote R&D and commercialization
Widespread use of locally made integrated chip
(IC) products in applications
Export revenue contribute to the growth of GDP
6 Foreign Ventures Marketing & branding to create more visibility
International sub-contracting and outsourcing
Contribution to industry revenue
25
Source: Ministry of Energy, Water and Communications (2006). The Malaysian Information. Communication and Multimedia Services 886 (MyICMS 886)
2.6 Related research on the Variables
Technology Acceptance Model (TAM) and Extended TAM
“The technology acceptance model is an influential extension of Ajzen and
Fishbein’s theory of reasoned action (TRA)”. It was introduced and developed by Fred
Davis in 1986 (Davis et al., 1989). TAM is a model obtained from a theory that
addresses the issue of how users come to accept and use a technology. The model
proposes that when users are presented to a new software package, a number of variables
persuade their decisions about how and when they will use it. Snow et al., (2006) added
that the role of TAM is not only to gain knowledge of how technology is issued within
organizations, but also how practitioners can influence the development process to
positively affect the reception and hence the acceptance of new technologies in a
business environment. There are two specific variables, perceived usefulness and
perceived ease of use, which are assumed to be fundamental factors of user acceptance
(Davis and Arbor, 1989). Bhatti (2007) stated that the TAM’s basic construct doesn’t
fully reflect the precise influences of technological and usage context factors that might
differ the user’s acceptance. Mathieson et al., (2001) argued that the TAM is limited due
to the lack of barriers that controls the individual from using an Information Technology
if they choose too. Moreover, researchers have also mentioned that due to the generality
of TAM, it fails to provide more significant data on user’s opinions and requires
integration with other IT acceptance models to improve its explanatory and specificity
(Mathieson, 1991; Agarwal and Prasad, 1998).
Figure 2.6.1: Technology Acceptance Model
26
Perceived
Usefulness
External Attitude Behavioral Actual
Variables Intention System use
Perceived
Ease of Use
Source: Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly, 13(3), 31-340.
Consequently these two determinants may not fully explain the factors which
expect the acceptance of a technology application such as mobile banking. Previous
studies have extended the original TAM by adding some constructs into the original
TAM model to facilitate understanding of the intention to use mobile banking in
Malaysia. Luarn and Lin (2004) amended the original TAM by adding perceived
credibility which was also defined by Wang et al., (2003), perceived self-efficacy which
was supported by several previous studies (Agrawal et al., 2000; Chau, 2001; Hong et
al., 2001; Johnson & Marakas, 2000)
Figure 2.6.2-: Extended TAM
27
Perceived usefulness
Perceived Usefulness
Davis (1989) defined perceived usefulness as “the degree to which a person
believes that using a particular system would enhance his or her job performance”.
Previous studies have shown that perceived usefulness is an important predecessor to the
intention to adopt and use a technology (Davis et al., 1989; Venkatesh, 1999, 2000;
Venkatesh & Davis, 2000). Potential adopters evaluate the consequences of their
adoption activities based on the enduring desirability of usefulness obtained from the
particular innovation (Chau, 1996; Venkatesh & Davis, 2000). In addition, perceived
usefulness is also known as performance expectancy (Venkatesh, 2003; Morris, 2003;
Davis, 2003), this was based on the expectancy theory that mocks-up the function of
belief in decision making (Porter and Lawler, 1968; Robey, 1979; Vroom, 1964). To
explain that, an innovation is perceived to be of high effectiveness when a particular
adopter believes that there is a direct relationship between use, on one hand, and
performance, productivity, effectiveness and satisfaction, on the other (Lu andYu, 2003).
Although many mobile services are leisure related, services such as new, stock changes
or banking can also stimulate how a user performs a task. In addition, “characteristics
that are inherent to mobile services, such as their personalized and ubiquitous nature,
their portability, and their context awareness potential are likely to contribute to
28
Perceived Ease of Use
Perceived Credibility
Perceived Self-efficacy
Behavioral Intention
Extended Technology Acceptance Model (Extended
TAM)
perceived usefulness of mobile services in ways that have not seen before” (Rao and
Troshani, 2007).
Aderonke and Charles (2010) mentioned that “people tend to use an application to
the extent they believe it will aid their performance”. Amin et al., (2008) stated that
perceived usefulness is strongly correlated with productivity. It suggests that using
computer in the workplace would improve job performance, increase user’s productivity,
enhance job effectiveness and be valuable in the job. Cheong and Park (2005) found that
there exists a positive causality between perceived usefulness and online purchase
intentions. Laurn and Lin (2005) also stated that perceived usefulness has significant
effect in the development of initial readiness to use mobile banking. These studies prove
the significant effect of perceived usefulness in individual reactions to information
technology. Hence, it is quite expected that the reason why people use mobile banking is
because they find it useful. On these bases, the following hypothesis is proposed:
H1: Perceived usefulness will have a positive effect on the behavioral intention to use
mobile banking.
Perceived ease of use
Perceived ease of use refers to the degree to which a person believes that using a
particular system would be effortless (Davis, 1989). In the mobile setting, perceived ease
of use corresponds to the degree to which individuals relate freedom of difficulty with
the use of mobile technology and services in daily usage (Knutsen et al., 2005). Some
mobile devices could be complex or tedious to use, for instance Taylor and Todd (1995)
mentioned that there are facts in the media that says using certain services on a mobile
phone can be tiresome, especially when browsing internet-like interfaces on mobile
devices. Fang et al., (2005) discovered that the nature of an innovation or a task or any
service related to it may persuade its perceived ease of use. For instance, perceived ease
of use affects the intended use of innovation only when it provides intrinsic motivation,
29
but not when it provides extrinsic rewards to its users (Gefen and Straub, 2000). Several
previous studies have shown that there is a positive relationship between perceived ease
of use and usage intention. Luarn and Lin (2005) stated that there is a positive causality
between perceived ease of use and the usage intention. Guriting and Ndubisi (2006)
mentioned that perceived ease of use had a significant positive effect of behavioral
intention to use online banking in Malaysia. Ramayah, et al., (2003) found that perceived
ease of use has a major impact in the development of initial willingness to use internet
banking. Davis et al., (1989) stated that perceived ease of use is an ancestor of perceived
usefulness. Perceived ease of use is assumed to act as a predictor of perceived
usefulness. In addition, both perceived usefulness and perceived ease of use predict
attitude towards using a system (Yan et al., 2009). A system which is more convenient to
use will facilitate more system use and accomplishment of tasks, rather than systems that
are hard to use (Venkatesh and Morris, 2000). The following hypothesis was proposed:
H2: Perceived ease of use will have a positive effect on the behavioral intention to use
mobile banking.
Compatibility
According to Rogers (1995), compatibility is defined as “ the degree to which an
innovation is perceived as being consistent with the existing values, past experiences and
the needs of potential adopters". Compatibility is viewed as an sign of how well the
service or technology fits with the way the customers manage and control their finances
and how it ensemble their lifestyle (Yu, 2009). Individuals are more probable to adopt an
innovation when they find it compatible with their past experience, beliefs and the way
they are accustomed to work (Agarwal and Prasad, 1998; Tornatzky and Klein, 1982).
Compatibility is illustrated to capture the consistency between an innovation and
experience, values, as well as needs of potential adopters (Rogers, 1995). It is a
significant aspect of compatibility that consumers are able to combine services and
30
technologies into their daily life (Jayawardhena & Foley, 1998; Lee et al., 2003; Shon &
Swatman, 1998). Perceived compatibility was discovered to indirectly influence the
user’s intention to mobile banking via perceived ease of use. Moreover, compatibility
was added into the research model and the following hypothesis was proposed.
H3: Compatibility will have a positive effect on the perceived ease of use of mobile
banking.
Perceived Self- efficacy
The importance of perceived ease of use is supported by Bandura (1982) who
defined self efficacy as "judgments of how well one can execute courses of action
required to deal with prospective situations". Studies have also shown that an empirical
evidence of a causal link between computer self efficacy and perceived ease of use exists
(Hanudin, 2007; Reid et al., 2008). The self efficacy of mobile banking is defined as “a
judgment of one’s ability to use a mobile banking service: (Luarn and Lin, 2004). Self
efficacy could include knowledge, skill and abilities needed to use the new IT. The
existence of a relationship between perceived self efficacy and perceived ease of use was
indicated by Davis (1989) and Mathieson et al., (2001). Therefore, perceived self
efficacy may indirectly influence the user’s behavior to use mobile to use mobile
banking via perceived ease of use. The following hypothesis was proposed:
H4: Self – efficacy will have a positive effect on the perceived ease of use of mobile
banking.
Subjective Norm
By definition, Subjective norm can be defined as a person’s observation that
most people who are important to him or her should or shouldn’t perform the behavior
(Fishbein and Ajzen, 1975). The opinions of important referents could comprise the basis
31
for a user’s feelings concerning the effectiveness of an innovation. For instance, if a
superior says that one particular innovation could be useful; such an implication could
affect the prospective of a user’s perception on the usefulness of the innovation (Yi et al.,
2006). Prior studies have discovered the importance of such construct in social science
studies including in banking studies (Amin et al., 2007; Nysveen et al., 2005; Kleijnen et
al., 2004). Amin et al., (2007) found that subjective norm was a key interpreter for
mobile banking use from a Malaysian point of view. Nysveen et al., (2005) stated that
users’ exploiting mobile chatting was due to the usage revealing their personal value as
well as the influence of others on them. Kleijnen et al., (2004) stated in a study on
wireless finance in Netherlands that subjective norm was essential in the development of
peoples’ intention to use wireless finance. Reference groups such as family members,
friends, teachers, and bank tellers make a significant force to encourage an individual to
behave in consistency with their identities (Amin and Ramayah, 2010). Research also
clarifies that the pressure from referent groups to adopt an innovation is effective
because it adds to reducing risk associated with adoption (Ishii, 2004; Lu et al., 2003;
Teo and Pok, 2003). Though the effect of subjective norms (SN) on intention is
indecisive, from previous research there is a significant body of theoretical and empirical
evidence concerning the importance of the function of subjective norm on technology
use, whether its directly or indirectly related (e.g., Taylor and Todd, 1995; Venkatesh
and Davis, 2000; Hsu and Lu, 2004). The comparative influence of subjective norm on
intentions is expected to be stronger for potential users with no previous practice since
they are more likely to rely on the reactions of others in shaping their intentions
(Hartwick and Barki, 1994). If mobile services are supposedly hard to learn and use,
unavoidably it will more or less affect a user’s intention toward adopting. The idea is to
predict whether social influence is a significant consideration in people’s intention to use
the system.
Using the findings of the above studies, we formulated the following hypothesis:
H5: Subjective norm will positively influence intention to use Mobile baking.
32
Perceived Credibility
By definition, perceived credibility is one's judgment on the privacy and security
issues of the mobile banking. Users will at least expect the same level of security that’s
available when banking online through their PC. Both the “Perception issue” (such as,
how lack of security affects the financial institution’s brand) and the real problem (e.g.,
snooping, injection and modification) must be addressed in order to encourage adoption
of mobile banking (Mobile Banking Overview. 2009). The significance of security and
privacy to the acceptance of banking technologies has been illustrated in many banking
studies (Howcroft, et al., 2002; Polatoglu and Ekin, 2001; and Sathye, 1999). As stated
by Wang et al., (2003) security and privacy are the two important dimensions in
perceived credibility. In order to initiate credibility, it is argued that both perceived
security and privacy are required.
Evidences have shown that both security and privacy could become obstacles for
the adoption of mobile services (Fang et al., 2005, Pikkarainen et al., 2004). The
significance of security and privacy to the acceptance of banking technologies has been
noted in many banking studies (Howcroft, et al., 2002; Polatoglu and Ekin, 2001; and
Sathye, 1999). Normally, fear of the lack of security is considered as an important factor
affecting the acceptance. One of these studies was conducted by Ndubisi and Sinti
(2006), they observed internet banking perception among bank customers in Malaysia,
and concluded that the risk was believed to be a weak predictor because of the banks’
assurance over the security of their internet banking. The banks supported that all the
cyber banks in Malaysia endorse this product as a fully secure option with 128-bit
encryption technology. Comparably, Pikkarainen et al., (2004), examined internet
banking from a Finnish perspective and they found that perceived credibility was found
to be not considerably related to internet banking acceptance.
Opposing to the above studies, Ramayah et al., (2006) who examined users and
non-users’ perceptions of internet banking found that security was a key predictor to
33
measure internet banking use by the users. Similarly, Wang et al., (2004) examined the
acceptance of internet banking in Taiwan; they found that PSP (perceived security and
privacy) had a crucial positive effect on behavioral intention to use internet banking.
Ramayah and Ling (2002) stated that the respondents ranked security as one of the
significant factors when adopting Internet banking. Luarn and Lin (2005) also examined
that perceived credibility has significant role in the development of willingness to use
mobile banking.
As mobile banking is considered relatively new, perceived credibility has a
higher ability to predict and analyze the uses’ intention to use mobile banking.
H6: Perceived Security and Privacy will have a positive effect on the credibility of use of
mobile banking.
H7: Perceived credibility will have a positive effect on the behavioral intention to use
mobile banking.
Perceived risk
Initially perceived risk was primarily related to fraud or product or product quality,
but today and as people got engaged in online behavior, perceived risk is largely
associated to financial, psychological, physical, or even social risks in online transactions
(Forsythe and Shi, 2003; Im et al., 2008). Fain and Roberts (1997) defined “risk is a
perception of consumer, not a characteristics of a product” Featherman (2002) stated that
service performance risk (i.e. risk related to service) is the key determinant of e-service
adoption. Wong and Chang (2005) considered that risk generally arises from the
uncertainty that users face when they cannot anticipate the consequences of their
purchase decision. When adopting mobile banking/payment, financial institutions must
weigh and consider the risks. Below, Lawhorn (2010) states that there are several key
areas that should be considered.
34
Third party providers: Mobile payment service providers offer a system for consumes to
transfer value from their current accounts with banks/regulated financial institutions.
These service providers are known as Money Service Businesses (MSBs) and they
function as a financial intermediary. MSBs have to fulfill the laws in the state in which
they are located. If a financial company decides to use an MSB for mobile payment
transactions, they ought to ensure review and earn confidences with the MSB’s
information security practices.
Regulatory and legal liability: Currently the United States as few safeguards against
abuse of mobile payments. There has been little progress in formulating and publicizing
guidance and the traditional money laundering countermeasures are insufficient to
address the impending threat posed by abuse of mobile payments to today’s e-banking
and cashless system.
Fraud/loss prevention: Given the dynamic nature and magnitude of security threats in the
wireless environment, it is crucial that the financial institutions implement intermittent
independent security vulnerability assessments of their mobile payment systems that
recognize apprehensive transactions or payment behaviors. In general, the mobile
payment industry has made several vital improvements in the viability and security of
electronic payments but there are still some major risks to financial institutions adopting
the service today.
Relating to prior studies and group discussions, it is obvious that users’ intention to
use new technology is affected by whether or not such risk does really exist. Based on
the literature, perceived risk could directly influence users’ intention to use mobile
banking. As per this conclusion, the following hypothesis was formulated:
H8: Perceived risk will have a negative effect on behavioural intention to use mobile
banking.
User Predisposition
35
User predisposition refers to the internal factors of an individual user of mobile
services. There are facts stating that successful acceptance of innovations depends as
much on individual adopter differences as on the innovation itself. Personal differences
severely influence adoption. Therefore, recognizing individual differences that impact
technology adoption is significant as it helps categorize segments of adopters who are
more likely to implement technology innovations than others, which in return, helps
providers concentrate on adopter needs more narrowly (Massey et al., 2005).
Furthermore, these individual adopters can act as opinion leaders or change agents to
assist the diffusion of the technology further. User predisposition is divided to a number
of factors including individual’s prior knowledge and familiarity of existing mobile
services, behavioral control, compatibility, image, personal innovativeness, and
perceived enjoyment.
Prior knowledge is critical for the comprehension of the technology and its related
services. Knowledge appears when a potential adopter discovers the existence of an
innovation and gains some understanding concerning its functionality (Herr et al., 1991).
Knowledge comprises of two components, specifically, expertise and familiarity. For
instance, the previous constitutes the number of mobile services-related experiences
accumulated by consumers over time, which consists of exposure to advertising,
information search, and interaction with salespersons. The second represents the
capability to use mobile services, and it includes beliefs about service features (i.e.
cognitive structures) in addition to decision rules for acting on those beliefs (i.e.
cognitive processes) (Alba and Hutchinson, 1987). Adopters’ previous experiences with
a technology or service whether it is a positive or negative experiences, can have a
significant impact on their perceptions and attitudes towards that technology or service
(Lee et al., 2003; Taylor and Todd, 1995)
The other variable is perceived behavioral control, which is a dynamic and socio-
cognitive concept. Perceived behavioral control is an individual’s belief about the
36
“presence or absence of requisite resources and opportunities” (Ajzen and Madden,
1986).
A more recent definition illustrates perceived behavioral control as a construct
which reveals user perceptions of both internal and external limitation of adopting an
innovation (Yi et al., 2006). In the perspective of mobile services adoption, perceived
behavioral control refers to the individual’s perception of how easy or difficult it is to get
mobile services which includes individual’s ability to afford the costs related with
mobile services (Rao and Troshani, 2007) Recent empirical findings proposes that
perceived behavioral control consists of two discrete components, namely, self-efficacy
which is an individual’s judgment of their capability to perform a behavior, and
controllability which represents an individual’s belief if they have the necessary
resources and opportunities to adopt the innovation (Hung et al., 2003; Wang et al.,
(2006). In short, perceived behavioral control signifies a subjective judgment of the
degree of control over a behavior’s performance, not the perceived likelihood that
performing the behavior will produce a given outcome (Ajzen, 1991).
Another variable within the user predisposition construct is compatibility. Rogers
(1995) defines compatibility as the degree to which an innovation is observed to be
consistent with existing values of potential adopters. Generally speaking, high
incompatibility will adversely affect potential adopters of an innovation, which reduces
the likelihood of adoption (Saaksjarvi, 2003). Individuals are most probably to adopt an
innovation when they find it compatible with their prior experience, beliefs and the way
they are accustomed to work (Agarwal & Prasad, 1998; Tornatzky & Klein, 1982). Yu
(2009) states that compatibility is observed as an indicator of how well the service or
technology fits with the way the customers control and manage their finances and how it
suits their lifestyle. Rogers (1995) mentions that compatibility is described to capture the
reliability between an innovation and the experiences, values, as well as needs of
potential adopters. The compatibility construct has also provided a consistent
explanation of technology adoption decisions (Tornatzky & Klein, 1982). In the context
37
of wireless devices, lifestyle compatibility is the level to which adopters believe mobile
devices and services can be assimilated into their daily lives.
Next, personal innovativeness is the intrinsic willingness of an individual to try
out and embrace new technologies and their related services for accomplishing precise
goals. Based on the Innovation Diffusion Theory, personal innovativeness symbolizes
the risk-taking tendency which exists in certain individuals and not in others (Agarwal
and Prasad, 1998; Massey et al. 2005; Parasuraman, 2000). Personal innovativeness
represents a convergence of technology-related beliefs which mutually contribute to
determining an individual’s predisposition to adopt mobile devices and related services
(Rao and Troshani, 2007). Hence, given the same level of beliefs and perceptions about
an innovation, individuals with higher personal innovativeness are more likely to
enhance positive attitudes towards adopting it than less innovative individuals (Agarwal
and Prasad, 1998). The identification of personal innovativeness helps identify different
categories of mobile service adopters are likely to shape the opinions of later ones by
becoming engaged in frequent advise-giving capacities (Brancheau and Wetherbe, 1990;
Yi et al., 2006)
Finally, intrinsic motivators such as perceived enjoyment need to be added to the
model to explain mobile service adoption behavior. Perceived enjoyment refers to the
degree to which using an innovation is perceived to be enjoyable in its own right and is
considered to be an intrinsic source of motivation (Gahtani and King, 1999). Because the
market for innovative mobile consists of both corporate users and consumers, aspects
focusing on perceived enjoyment, forms an important consideration (carlsson et al.,
2005; Pagani, 2004). That is, adopters use an innovation for the delight or enjoyment its
adoption might achieve and, hence, serve as an end unto itself. Further, intrinsic
enjoyment, obtained by playing mobile games for example, satisfies pleasure-oriented
and operates outside valued outcomes or immediate material needs (i.e. extrinsic
motivations), such as improved job performance and increased pay (Mathwick et al.,
38
2001; Moon and Kim, 2001). Previous research proposes that perceived enjoyment is
one of the most significant types of user needs (Anckar and D’Incau, 2002).
H9: User predisposition will have a positive effect on behavioural intention to use mobile
banking
2.7 Summary
In this chapter, there is a compilation of various definitions of mobile banking
taken from previous works. There is a brief but informative discussion on the evolution
and advancement of mobile banking. In addition, this chapter covers out how mobile
banking has turned out to be successful in Western Europe. There is also information on
how mobile banking is performing in Malaysia and how the Government intends to
boost the usage of mobile banking using the MyICMS 886 blueprint. This blueprint
presents an inclusive strategy such as service goals, infrastructure goals and growth areas
goals that address the core characteristics of the industry. It also includes a bridged
description about the technology Acceptance Model (TAM) and the Extended TAM.
This chapter also covers a detailed explanation about the variables affecting the intention
to use mobile banking in Malaysia.
Chapter 3
39
Research Methodology
3.1 Introduction
The objective of this research is to identify the key determinants of Mobile
Banking adoption among users in Malaysia. Therefore, this chapter provides a
description of the methodology used for this research. In this chapter, there is a detailed
indication on the instruments used in the data mining process. Both the conceptual
framework and the theoretical framework are presented in this chapter. There is also
enlightenment on how the independent variables will influence the independent variables
and the suggested hypotheses. Additionally, the questionnaire design, research approach,
data resources, data collection method, measurement of the variables, sampling method,
sample size / population size, unit of analysis and data analysis techniques will also be
elaborately explained in this chapter.
3.2 Conceptual Framework
In order to build a conceptual framework, various factors have been taken into
consideration as potential variables. After extensive studies done abroad, six variables
have been identified as possible key factors of Mobile Banking adoption in Malaysia.
Perceived usefulness is seen as a determinant of consumers’ intention to adopt mobile
banking. Another predicted determinant is perceived ease of use. Perceived
innovativeness is predicted to have an effect on the perceived ease of use. Both
perceived usefulness and perceived ease of use were adopted from the TAM model.
Another estimated determinant of consumers’ intention to use mobile banking is
perceived credibility. Additionally, subjective norm is also seen as a possible
determinant that would persuade consumer adoption. Another possible determinant that
would influence the adoption of mobile banking and was discussed in this chapter is
40
Perceived risk. Finally, the last possible determinant is user predisposition, which might
be influencing the adoption of mobile banking in Malaysia.
Figure 3.2: Theoretical Framework
TAM model has been adopted and additional appropriate constructs have been
added. This section explains in details the justification for the constructs to be integrated
in the research and the hypothesized affiliation amongst these constructs.
3.3 Hypothesis Development
41
Perceived Compatibility
Perceived
Credibility
Perceived
Risk
Subjective
Norms
Perceived
Usefulness
User - Predisposition
Perceived
Self-efficacy
Intention to use Mobile
Banking
Perceived Ease of Use
Perceived Security & Privacy
Perceived Usefulness
Davis (1989) defined perceived usefulness as “the degree to which a person
believes that using a particular system would enhance his or her job performance” (Ibid,
p.320). Previous studies have shown that perceived usefulness is an important
predecessor to the intention to adopt and use a technology (Davis et al., 1989;
Venkatesh, 1999, 2000; Venkatesh & Davis, 2000). Potential adopters evaluate the
consequences of their adoption activities based on the enduring desirability of usefulness
obtained from the particular innovation (Chau, 1996; Venkatesh & Davis, 2000). In
addition, perceived usefulness is also known as performance expectancy (Venkatesh,
2003; Morris, 2003; Davis, 2003), this was based on the expectancy theory that mocks-
up the function of belief in decision making (Porter and Lawler, 1968; Robey, 1979;
Vroom, 1964). To explain that, an innovation is perceived to be of high effectiveness
when a particular adopter believes that there is a direct relationship between use, on one
hand, and performance, productivity, effectiveness and satisfaction, on the other (Lu and
Yu, 2003). Although many mobile services are leisure related, services such as new,
stock changes or banking can also stimulate how a user performs a task. In addition,
“characteristics that are inherent to mobile services, such as their personalized and
ubiquitous nature, their portability, and their context awareness potential are likely to
contribute to perceived usefulness of mobile services in ways that have not seen before”
(Rao and Troshani, 2007).
Aderonke and Charles (2010) mentioned that “people tend to use an application
to the extent they believe it will aid their performance”. Amin et al., (2008) stated that
perceived usefulness is strongly correlated with productivity. It suggests that using
computer in the workplace would improve job performance, increase user’s productivity,
enhance job effectiveness and be valuable in the job. Cheong and Park (2005) found that
there exists a positive causality between perceived usefulness and online purchase
intentions. Laurn and Lin (2005) also stated that perceived usefulness has significant
effect in the development of initial readiness to use mobile banking. These studies prove
42
the significant effect of perceived usefulness in individual reactions to information
technology. Hence, it is quite expected that the reason why people use mobile banking is
because they find it useful. On these bases, the following hypothesis is proposed:
H1: Perceived usefulness will have a positive effect on the behavioral intention to use
mobile banking.
Perceived ease of use
Perceived ease of use refers to the degree to which a person believes that using
a particular system would be effortless (Davis, 1989). In the mobile setting, perceived
ease of use corresponds to the degree to which individuals relate freedom of difficulty
with the use of mobile technology and services in daily usage (Knutsen et al., 2005).
Some mobile devices could be complex or tedious to use, for instance Taylor and Todd
(1995) mentioned that there are facts in the media that says using certain services on a
mobile phone can be tiresome, especially when browsing internet-like interfaces on
mobile devices. Fang et al., (2005) discovered that the nature of an innovation or a task
or any service related to it may persuade its perceived ease of use. For instance,
perceived ease of use affects the intended use of innovation only when it provides
intrinsic motivation, but not when it provides extrinsic rewards to its users (Gefen and
Straub, 2000). Several previous studies have shown that there is a positive relationship
between perceived ease of use and usage intention. Luarn and Lin (2005) stated that
there is a positive causality between perceived ease of use and the usage intention.
Guriting and Ndubisi (2006) mentioned that perceived ease of use had a significant
positive effect of behavioral intention to use online banking in Malaysia. Ramayah et al.,
(2003) found that perceived ease of use has a major impact in the development of initial
willingness to use internet banking. Davis et al., (1989) stated that perceived ease of use
is an ancestor of perceived usefulness. Perceived ease of use is assumed to act as a
predictor of perceived usefulness. In addition, both perceived usefulness and perceived
43
ease of use predict attitude towards using a system (Yan et al., 2009). A system which is
more convenient to use will facilitate more system use and accomplishment of tasks,
rather than systems that are hard to use (Venkatesh and Morris, 2000). The following
hypothesis was proposed:
H2: Perceived ease of use will have a positive effect on the behavioral intention to use
mobile banking.
Compatibility
According to Rogers (1995) compatibility is defined as “the degree to which an
innovation is perceived as being consistent with the existing values, past experiences and
the needs of potential adopters". Compatibility is viewed as a sign of how well the
service or technology fits with the way the customers manage and control their finances
and how it ensemble their lifestyle (Yu, 2009). Individuals are more probable to adopt an
innovation when they find it compatible with their past experience, beliefs and the way
they are accustomed to work (Agarwal and Prasad, 1998; Tornatzky and Klein, 1982).
Compatibility is illustrated to capture the consistency between an innovation and
experience, values, as well as needs of potential adopters (Rogers, 1995). It is a
significant aspect of compatibility that consumers are able to combine services and
technologies into their daily life (Jayawardhena & Foley, 1998; Lee et al., 2003; Shon &
Swatman, 1998). Perceived compatibility was discovered to indirectly influence the
user’s intention to mobile banking via perceived ease of use. Moreover, compatibility
was added into the research model and the following hypothesis was proposed.
H3: Compatibility will have a positive effect on the behavioral intention to use mobile
banking.
Perceived Self- efficacy
44
The importance of perceived ease of use is supported by Bandura (1982) who
defined self efficacy as "judgments of how well one can execute courses of action
required to deal with prospective situations". Studies have also shown that an empirical
evidence of a causal link between computer self efficacy and perceived ease of use exists
(Hanudin, 2007; Reid et al., 2008). The self efficacy of mobile banking is defined as “a
judgment of one’s ability to use a mobile banking service: (Luarn and Lin, 2004). Self
efficacy could include knowledge, skill and abilities needed to use the new IT. The
existence of a relationship between perceived self efficacy and perceived ease of use was
indicated by Davis (1989) and Mathieson et al., (2001). Therefore, perceived self
efficacy may indirectly influence the user’s behavior to use mobile to use mobile
banking via perceived ease of use. The following hypothesis was proposed:
H4: Self – efficacy will have a positive effect on the behavioral intention to use mobile
banking.
Subjective Norm
By definition, Subjective norm can be defined as a person’s observation that
most people who are important to him or her should or shouldn’t perform the behavior
(Fishbein and Ajzen, 1975). The opinions of important referents could comprise the basis
for a user’s feelings concerning the effectiveness of an innovation. For instance, if a
superior says that one particular innovation could be useful; such an implication could
affect the prospective of a user’s perception on the usefulness of the innovation (Yi et al.,
2006). Prior studies have discovered the importance of such construct in social science
studies including in banking studies (Amin et al., 2007; Nysveen et al., 2005; Kleijnen et
al., 2004). Amin et al., (2007) found that subjective norm was a key interpreter for
mobile banking use from a Malaysian point of view. Nysveen et al., (2005) stated that
users’ exploiting mobile chatting was due to the usage revealing their personal value as
well as the influence of others on them. Kleijnen et al., (2004) stated in a study on
45
wireless finance in Netherlands that subjective norm was essential in the development of
peoples’ intention to use wireless finance. Reference groups such as family members,
friends, teachers, and bank tellers make a significant force to encourage an individual to
behave in consistency with their identities (Amin and Ramayah, 2010). Research also
clarifies that the pressure from referent groups to adopt an innovation is effective
because it adds to reducing risk associated with adoption (Ishii, 2004; Lu et al., 2003;
Teo and Pok, 2003).
Using the findings of the above studies, we formulated the following hypothesis:
H5: Subjective norm will positively influence intention to use Mobile banking.
Perceived Credibility
By definition, perceived credibility is one's judgment on the privacy and security
issues of the mobile banking. Users will at least expect the same level of security that’s
available when banking online through their PC. Both the “Perception issue” (such as,
how lack of security affects the financial institution’s brand) and the real problem (e.g.,
snooping, injection and modification) must be addressed in order to encourage adoption
of mobile banking (Mobile Banking Overview. 2009). The significance of security and
privacy to the acceptance of banking technologies has been illustrated in many banking
studies (Howcroft, et al., 2002; Polatoglu and Ekin, 2001; and Sathye, 1999). As stated
by Wang et al., (2003) security and privacy are the two important dimensions in
perceived credibility. In order to initiate credibility, it is argued that both perceived
security and privacy are required.
Evidences have shown that both security and privacy could become obstacles
for the adoption of mobile services (Fang et al., 2005, Pikkarainen et al., 2004). The
significance of security and privacy to the acceptance of banking technologies has been
noted in many banking studies (Howcroft et al., 2002; Polatoglu and Ekin, 2001; and
46
Sathye, 1999). Normally, fear of the lack of security is considered as an important factor
affecting the acceptance. One of these studies was conducted by Ndubisi and Sinti
(2006), they observed internet banking perception among bank customers in Malaysia,
and concluded that the risk was believed to be a weak predictor because of the banks’
assurance over the security of their internet banking. The banks supported that all the
cyber banks in Malaysia endorse this product as a fully secure option with 128-bit
encryption technology. Comparably, Pikkarainen et al., (2004), examined internet
banking from a Finnish perspective and they found that perceived credibility was found
to be not considerably related to internet banking acceptance.
Opposing to the above studies, Ramayah et al., (2006) who examined users and
non-users’ perceptions of internet banking found that security was a key predictor to
measure internet banking use by the users. Similarly, Wang et al., (2004) examined the
acceptance of internet banking in Taiwan; they found that PSP (perceived security and
privacy) had a crucial positive effect on behavioral intention to use internet banking.
Ramayah and Ling (2002) stated that the respondents ranked security as one of the
significant factors when adopting Internet banking. Luarn and Lin (2005) also examined
that perceived credibility has significant role in the development of willingness to use
mobile banking.
As mobile banking is considered relatively new, perceived credibility has a
higher ability to predict and analyze the uses’ intention to use mobile banking.
H6: Perceived Security and Privacy will have a positive effect on the credibility of use of
mobile banking.
H7: Perceived credibility will have a positive effect on the behavioral intention to use
mobile banking.
Perceived risk
47
Initially perceived risk was primarily related to fraud or product or product
quality, but today and as people got engaged in online behavior, perceived risk is largely
associated to financial, psychological, physical, or even social risks in online transactions
(Forsythe and Shi, 2003; Im et al., 2008). Featherman (2002) stated that service
performance risk (i.e. risk related to service) is the key determinant of e-service
adoption. Wong and Chang (2005) considered that risk generally arises from the
uncertainty that users face when they cannot anticipate the consequences of their
purchase decision.
Relating to prior studies and group discussions, it is obvious that users’ intention
to use new technology is affected by whether or not such risk does really exist. Based on
the literature, perceived risk could directly influence users’ intention to use mobile
banking. As per this conclusion, the following hypothesis was formulated:
H8: Perceived risk will have a negative effect on behavioural intention to use mobile
banking.
User Predisposition
User predisposition refers to the internal factors of an individual user of mobile
services. There are facts stating that successful acceptance of innovations depends as
much on individual adopter differences as on the innovation itself. Personal differences
severely influence adoption. Therefore, recognizing individual differences that impact
technology adoption is significant as it helps categorize segments of adopters who are
more likely to implement technology innovations than others, which in return, helps
providers concentrate on adopter needs more narrowly (Massey et al., 2005).
Furthermore, these individual adopters can act as opinion leaders or change agents to
assist the diffusion of the technology further. User predisposition is divided to a number
of factors including individual’s prior knowledge and familiarity of existing mobile
48
services, behavioral control, compatibility, image, personal innovativeness, and
perceived enjoyment.
H9: User predisposition will have a positive effect on behavioral intention to use
mobile banking
3.4 Research Approach
In order to substantiate the hypothesis proposed on the key factors of mobile
banking adoption in Malaysia, it should be scientifically tested. In order for this to
happen, data must be collected from the sample / population to be analyzed.
There are several ways to collect information with the most prominent ways
being via interview and questionnaires. This data is then originated using various
mathematical techniques to find out information. As well as collecting data from the
sample / population, a different way to collect information is through research and by
studying previous work done on the topic to understand their findings and to achieve
more knowledge about the topic.
The sample / population are regularly determined early and are usually hurdled to the
topic we are researching. For example, the topic is about Malaysia, hence limit for the
sample / population will be within the geographical area of Malaysia. The reason for all
this to ensure the data is accurate and not biased in any kind of way.
3.5 Data Resources
Primary data are the data gathered directly from firsthand experience. The
defining characteristic of primary data is that data collected is unique and the research
will stay unrevealed until the study is published. Primary data can be classified into two
49
categories. Qualitative in nature is one of these primary data, which is usually text based.
Or quantitative in nature, which signifies the numerical values. Among the methods of
collecting the primary data are via questionnaires, interviews, observations, group
interviews, case-studies, diaries, critical incidents and portfolios.
Secondary data is data that has already been collected for use in previous
studies. Secondary data can also been divided into two based on their nature. These two
natures are qualitative data which comprises of biographies, personal letters, documents,
diaries, records, published material, computer database, and policy statements. The other
nature is quantitative data, it would include market research, census, and economic
documents, planning documents or specimens.
3.6 Data Collection Method
In this research, the data collection method was implemented through distributing
questionnaires. The motive for using the questionnaires method for collecting data was
because prior work which has been cited in this paper have all chosen this method (Birch
and Young, 1997; Wang et al., 2003; Mwaura, 2009; Wilcox, 2010;
Weber and Darbellay, 2010; Yong and Gorman, 2002; Foley, 2005; Davis et al., 1989;
Venkatesh, 1999; Venkatesh & Davis, 2000; Venkatesh, 2003; Morris, 2003; Davis,
2003; Porter and Lawler, 1968; Robey, 1979; Vroom, 1964; Rao and Troshani, 2007;
Cheong and Park, 2005; Amin et al., 2008; Knutsen et al., 2005; Taylor and Todd, 1995;
Fang et al., 2005; Gefen and Straub, 2000; Guriting and Ndubisi, 2006; Ramayah et al.,
2003; Yan et al., 2009; Agarwal and Prasad, 1998; Tornatzky and Klein, 1982;
Jayawardhena & Foley, 1998; Lee et al., 2003; Shon & Swatman, 1998; Hanudin, 2007;
Reid et al., 2008; Howcroft, et al., 2002; Polatoglu and Ekin, 2001; Sathye, 1999; Fang
et al., 2005, Pikkarainen et al., 2004; Ndubisi and Sinti, 2006; Ramayah and Ling, 2002
There are several advantages which make the questionnaire method most
preferable. Amongst these advantages are it is cost effective, reduce bias (questionnaires
50
are handed out randomly), and it has a large amount of correspondents. There are also
other advantages of questionnaires such as its undisputed, respondents will have time to
think about their response, no prior arrangements are needed when handing out
questionnaires, and questionnaires can cover wide geographic location because it can be
posted, faxed or e-mailed.
3.7 Questionnaire Design
The questionnaire was designed, pre-tested and then administered to a random
sample of mobile service subscribers. The questionnaire was designed to test these
variables, Perceived Usefulness, Perceived Ease-of-use, Perceived Credibility, Perceived
risk, Subjective Norm and User Predisposition and also to collect demographic
information about the correspondents.
Based on Luarn and Lin (2005), the questions for each construct shall be adapted
from prior research. The first section was designed to collect demographic information
of the respondents. There were 5 demographics which will give rough background
information of the sample chosen. The questions covered gender, age, marital status,
education attained, and also income level in the format of close-ended multiple-choice
questions except for age. These questions were adopted from Amin et al., (2006).
As for the second section, the constructs, perceived usefulness questions were
adopted from the works of Taylor and Todd (1995), Khalifa and Cheng (2002), Wang
and Barnes (2007), Kurnia et al., (2006) and Wong and Hiew (2005). For perceived ease-
of-use, the questions were adopted from Luarn and Lin (2005). On the other hand, for
social influences, the questions were adopted from Luarn and Lin (2005), Lin and Wang
(2005) and Wong and Hiew (2005). Additional questions regarding the other variables
were also added. For all the constructs, a five- point Likert-type scale was used, ranking
from 1 (strongly disagree) to 5 (strongly agree). By using the Likert scale, respondents
were able to indicate their level of agreement or disagreement for each statement.
51
3.8 Measurement
For the demographic questions, it was computed using a nominal scale as done by
Haque and Raihan (2004) and Amin et al., (2006). This nominal scale was used to collect
a range of values for values in obtaining age of the correspondents and much more.
For the answers of the questions, it was based on a five-point Likert-type scale,
ranking as 1 (strongly disagree), 2 (disagree), 3 (neutral), 4 (agree), and 5 (strongly
agree), each to factor out a single maximum point, for the measurement of the whole
designs of the questionnaires. Statements that are negatively acknowledged will be
reversed coded during the analysis. This process will be done because according to field,
(2005) negative worded items are necessary to trim down any bias that might occur due
to the fact that respondents have the tendency to read the items in a scenario when they
are phrased the other way around.
Using a Likert-type scale, an attitude statement is given, and then the respondents
choose a point on the scale reflecting his or her position towards the statement. The
reason behind choosing the Likert-type scale was done based on the previous work of
Bhatti, (2007) and Amin et al., (2006).
3.9 Sampling Method
After evaluating all possible methods of sampling, the most proper method for this
research has been identified as convenience sampling method. This sampling method is a
non-probability sampling technique where subjects are selected because of their
convenient accessibility and proximity to the researcher. Convenience sampling
generally assumes a homogenous population, and that one person is most likely like the
other. Distribution of the questionnaires was done through personal administration.
Written questionnaires reduce interviewer bias because there is uniform question
presentation (Jahoda, et al., 1962).
52
3.10 Sample Size/Population
A total of 230 questionnaires were distributed randomly. The target respondents
were those who are able to communicate in English, as the questionnaire will be
constructed using English as the medium. Target respondents were people who own and
use mobile communication devices, such as PDAs, hand phones or smart phones. The
study will be covered within MMU Melaka Campus, which will include students from
various faculties and departments. The distribution method used for this study was paper
based questionnaires.
3.11 Unit of Analysis
For the unit of analysis, the focus group was individuals from the workforce and
students within MMU boundaries, who are mobile service subscribers, aged between 20
– 49 years from various countries, background, religion, gender and age. The reason
behind choosing this range is because based on the Hand Phone User Survey, developed
by the Malaysian Communications and Multimedia Commission, the 20 – 49 age group
has been illustrated as the highest users of mobile phones for 3 years of survey, from the
year 2005 – 2007, the last survey being published was in 2007. Besides this, sources
were students from various faculties, for instance, Faculty of Engineering, Faculty of
Information Science and Technology and Faculty of business and Law. The motive
behind this choice was that most of the students in Multimedia University are internet
savvy, own mobile phone and have easy access to the internet and also Wi-fi around the
campus and at home. The reason why the questionnaires were targeted at individuals and
not corporations is because corporations are usually bound to their personal corporate
culture and changes are usually decided by the management.
53
3.12 Data Analysis Techniques
For the demographic section, Descriptive statistics was implemented to describe
the basic features of the data in the study. Descriptive statistics present simple summaries
about the sample and the measures.
As for the constructs, inferential statistics was used. Inferential statistics are used
in order to make judgments of the probability whether an observed difference between
groups is a dependable one or one that might have happened by chance in this study.
Multiple regression analysis has been chosen to test the hypotheses for the purpose of
this study. The reason behind choosing Multiple regression analysis is because it is
basically applied to analyze relationships between a single dependent variable and a
number of Independent variables (Hair et al., 2005).
To implement data analysis, Statistical Package for the Social Sciences (SSPS) was
adopted. To ensure the accuracy of the data, the data will be entered twice and to be able
to check for any inconsistencies.
3.13 Limitation
A few possible limitations have been identified previously. Firstly, there is a
possibility that all the questionnaires handed out will be answered. Secondly, there might
be candidates in the focus group who are reluctant to answer the questionnaires handed
out. Thirdly, the practice of online facilities generally e-mail might bring a problem
where the recipient does not reply the questionnaire which has been sent to them.
54
3.14 Summary
In this chapter, it gives an elaborated explanation about the method used to collect
the data, procedures used to collect the data and the methods used to analyze the data
acquired from the questionnaires. In order to develop the questionnaire, previous works
regarding the factors of mobile banking have been examined and adopted. Besides this,
the targeted group of individuals chosen to complete the questionnaires were aged
between 20 – 49 have been identified and reasons behind selecting this age group have
also been explained in this chapter. This sampling method, which is snowball sampling
was selected in order to achieve real, accurate and unbiased data.
55
CHAPTER 4
DATA ANALYSIS AND FINDINGS
4.1 Introduction
The objective of this chapter is to confer the data analysis and findings of
this research based on various tests that were conducted on questionnaire items. First,
respondents profile is discussed which includes demographics as well as their mobile
usage. Subsequently, mean analysis for each variable is discussed using the means and
standard deviations of items in each variable. This chapter also discusses Reliability
tests and whether the results are reliable or not. Cronbach’s Alpha was used to conduct
the reliability tests. Correlation of all variables was tested using the Spearman Rho’s
correlation coefficient, which was also used to test for hypotheses. Finally, a summary
of this chapter as well as a summary of the hypotheses results is included.
56
4.2 Descriptive Analysis
Of the 230 questionnaires that were distributed, 200 questionnaires were
returned. However, 10 of them had to be rejected due to missing answers or incorrect
filling-in. This means that there was a response rate of 82.61. Data was analyzed using
the SPSS (Statistical Package for Social Science) software. Table 4.1 below shows a
general demographic profile of the respondents and Table 4.2 on the next page shows
technical profile of respondents.
Table 4.1 Demography profile of respondents
Frequency Percentage Cumulative
Percentage
Gender Male
Female
Total
119
71
190
62.6
37.4
100.0
62.6
100
Age group 15-20 years
21-25 years
26-30 years
31- & above
Total
31
153
4
2
190
16.3
80.5
2.1
1.1
100.0
16.3
96.8
98.9
100.0
Nationality Malaysian
Others
Total
74
116
190
38.9
61.1
100
38.9
100.0
Race Malay
Chinese
Indian
Others
Total
34
35
7
114
190
17.9
18.4
3.7
60.0
100.0
17.9
36.3
40.0
100.0
Marital Single 182 95.8 95.8
57
Status Married
Total
8
190
4.2
100.0
100.0
Faculty FBL
FIST
FET
Total
106
36
48
190
55.8
18.9
25.3
100.0
55.8
74.7
100.0
Monthly
income
RM0-RM500
RM501-RM1000
RM1001-RN1500
RM1501-RM2000
RM2001-RM2500
RM2501 & ABOVE
Total
35
66
38
17
23
11
190
18.4
34.7
20.0
8.9
12.1
5.8
100.0
18.4
53.2
73.2
82.1
94.2
100.0
58
Table 4.2: Respondents’ profile of Understanding m-banking
Frequency Percentage Cumulative
Percentage
Familiarity with
mobile banking
Yes
No
Not that much
Total
118
41
31
190
62.1
21.6
16.3
100.0
62.1
83.7
100.0
Used mobile banking
before
Yes
Never
Once before
A few times
Intending to use in future
Total
79
62
24
21
4
190
41.6
32.6
12.6
11.1
2.1
100.0
41.6
74.2
86.8
97.9
100.0
Used mobile devices <1 year
1-less than 3 years
3-less than 5 years
5 or more years
Total
57
62
25
46
190
30.0
32.6
13.2
24.2
100.0
30.0
62.6
75.8
100.0
Satisfaction from
mobile application
Yes
No
Total
130
60
190
68.4
31.6
100.0
68.4
100.0
Use of mobile
banking
Very unlikely
somewhat likely
not sure
somewhat likely
very likely
Total
21
35
57
56
21
190
11.1
18.4
30.0
29.5
11.1
100.0
11.1
29.5
59.5
88.9
100.0
Most of the respondents are already familiar with mobile banking with
62.1%. Results also have shown that 32.6% have never used mobile banking before,
59
which could be because the banks they are dealing with doesn’t provide this service or
didn’t properly advertise it to its customers. Majority of respondents are satisfied with
their mobile application with a contribution of 68.4%. Respondents that have used
mobile banking before have contributed to a 41.6% which is considered below average.
When the respondents were asked whether they intend to use mobile banking, 29.5%
mentioned that somewhat they’re likely to use mobile banking.
4.2.1 Gender
Figure 4.1 Number and percentage of respondents’ gender
MALE63%
FEMALE37%
From Fig. 4.1 it is evident that the percentage of female respondents was considered low
at only 37%. Of all the 190 respondents, only 71 of them were female. Males on the
other hand were considered higher with 63%, i.e. male respondents were 119 male.
60
4.2.2 Age
Figure 4.2: Respondents age
15-20 years 21-25 years 26-30 years 31- & above0
20
40
60
80
100
120
140
160
31
153
4 2
16.3
80.5
2.1 1.1
Series2Series2
Respondents were mainly young. Those in the range of 21-25 years were the most
respondents. They were 153 in total, which were 80.5% of total respondents. This
percentage could have been due to the fact that the average age of most university
students is in the range of 21-25 years. Those aged 15-20 were the second largest group
having 16.3% or 31 of total respondents. There were only 4 respondents aged at 26-30,
having 2.1% presentation. Finally, those in the age bracket of 31and above were only 2
(1.1%).
61
4.2.3 Nationality
Figure 4.3: Nationality
1 20
20
40
60
80
100
120
74
38.9
116
61.1
MalaysianOthers
There were two categories in nationality of respondents: Malaysians and others.
According to figure 4.3, majority of the respondents were others contributing to 61.1%
or 116 respondents from comprised from different nationalities. Malaysians, who
consists of the three ethnicities (Malay, Chinese and Indians) contributed to 38.9%, i.e.
74 respondents.
62
4.2.4 Race
Figure 4.4: Race
Malay Chinese Indian Others0
20
40
60
80
100
120
34 35
7
114
17.9 18.4
3.7
60
Series2Series2
There were four categories in race or ethnicity of respondents: Malay, Chinese,
Indian and Others. By Others, we refer to the Non-Malaysians. According to figure 4.3,
majority of the respondents were Others contributing to 60%. Chinese with 18.4%
contribution comes after others (Non-Malaysians). Malaysians were too close to the
Chinese with only one respondent behind, they had a total of 35 respondents and 17.9%
of contribution. Respondents from the Indian race were few with only 7 respondents.
4.2.5 Marital Status
63
Figure 4.5: Marital Status
0
20
40
60
80
100
120
140
160
180
200 182
95.8
8 4.2
Series2Series2
Figure 4.5 above shows the marital status of the respondents. Not surprisingly,
majority of the respondents were single with a contribution of 95.8%. This is normal
because most of university level students are single and not yet settled for marriage.
Responses from Married individuals were very few with 4.2% responses.
4.2.6 Faculty
64
Figure 4.6: Faculty
FBL FIST FET0
20
40
60
80
100
120 106
36
48
55.8
18.925.3
Series2Series2
Figure 4.6 shows the faculties of which the respondents are related too. The study
covered three of Multimedia University (Melaka Campus) faculties. FBL (Faculty of
Business and Law) FIST (Faculty of Information Science and technology) and FET
(Faculty of Engineering and Technology). Majority of respondents are from FBL with
a contribution of 55.8% which is equal to 106 respondents in total. Respondents from
FET come next with 48 responses and a contribution of 25.3%. Additionally,
respondents from FIST made a contribution of 18.9% i.e. 36 responses.
65
4.2.7 Monthly Income
Figure 4.7: Monthly Income
RM0-RM500
RM501-RM1000
RM1001-RN1500
RM1501-RM2000
RM2001-RM2500
RM2501 & ABOVE
0
10
20
30
40
50
60
70
35
66
38
1723
11
18.4
34.7
20
8.912.1
5.8
Series2Series2
Figure 4.7 above illustrates income ranges of the respondents. It is evident that least
respondents were in the range of RM2501 & Above (5.8%). This could have been
because these respondents are on Government scholarship, etc. The most respondents
on the other hand were in the range of RM501-RM1000 (34.7%). This is illustrated by
the fact that respondents were students and the income represented the allowance they
get from their guardians (whether they are on scholarships or self-sponsored). The
income was in terms of monthly basis and not annual.
66
4.3 Mean values of respondents
Table 4.3: Mean analysis for perceived usefulness
Item ID Item DescriptionMean
(n=190)Std.
Deviation
PU1 Mobile banking would be useful in conducting
my banking transactions
3.5316 .85854
PU2 Using mobile banking enables me to conduct
banking transactions more quickly
3.6842 .81342
PU3 If I were to adopt mobile banking, it would be a
more effective way to make transactions
3.7000 .86648
PU4 Mobile banking would give me greater control 3.6526 .87006
PU5 Mobile banking would improve the quality of
my decision making
3.4053 .89026
PU6 Using m-banking will allow me to enjoy a
variety of services regardless of my recent
location
3.6421 .88987
PU7 I am able to find mobile connectivity in the
remotest places, including areas where internet
applications is weak
3.4579 .97905
67
Based on the results from table 4.3, apparently most respondents were close to neutral,
when asked if mobile banking would be useful when conducting their banking
transactions with a mean of 3.5316. When asked if using mobile banking enables them to
conduct banking transactions more quickly, majority were also close to neutral with a
mean of 3.6842. The highest agreement rate among subjects stating a mean of 3.7000
tended to agree that if mobile banking were adopted, it would be an effective way to
make transactions. Response regarding mobile banking giving respondents greater
control was positive with a mean 3.6526. Additionally, when asked if mobile banking
would improve the quality of the respondents’ decision making, the mean was close to
neutral with 3.4053. Thought using m-banking will allow them to enjoy a variety of
services regardless of my recent location with a mean of 3.6421. Being able to find
connectivity in the remotest places, including areas where internet application is weak
reporting a mean of 3.4579.
Note: PU (perceived usefulness)
68
Table 4.4: Mean analysis for perceived ease of use
Item ID Item Description
Mean(n=190)
Std. Deviation
PE1 I find banking transactions on mobile phones easy and simple
3.5579 .91102
PE2 I find mobile banking clear and understandable proficient
3.5895 .87281
PE3 It would be easy to do what I want while using mobile banking
3.6211 .79254
PE4 I find mobile banking through cell phone very user friendly
3.4789 .99047
PE5 I find mobile banking less time consuming 3.6737 .89018
PE6 Using mobile banking can be frustrating (R) 2.6579 1.02550
PE7 I find certain services on mobile phones very friendly, especially when browsing internet-like interfaces on mobile devices
3.5579 .95081
Table 4.4 above represents the means and standard deviation of responses about the
variable perceived ease of use. Respondents slightly agreed that finding banking
transactions on mobile phones easy and simple with a mean of 3.5579. Respondents with
a mean of 3.5895 agreed that mobile banking is clear and understandable. They also
agreed that it would be easy to do what they want while using mobile banking with mean
values of 3.6211. Respondents also agreed that they find mobile banking through cell
phone very user friendly with mean values of 3.4789. The highest agreement rate among
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subjects stating a mean of 3.6737 stated that mobile banking is less time consuming.
Majority disagreed that using mobile banking can be frustrating with mean values of
2.6579. Respondents find certain services on mobile phones very friendly, especially
when browsing internet-like interfaces on mobile devices with mean values of 3.5579.
Note: PE (perceived ease of use)
Table 4.5: Mean analysis for perceived compatibility
Item ID Item Description
Mean(n=190)
Std. Deviation
PCO1 I find mobile banking compatible with my beliefs and the way they are accustomed to work
3.4632 .88264
PCO2 I find mobile banking compatible with my past experience
3.2316 .80937
PCO3 With mobile banking, I am able to combine services and technologies into my daily life
3.5789 .78449
PCO4 I believe mobile banking have filled all the gaps caused by internet banking
3.5000 .91865
PCO5 I find mobile banking the best way to manage and control my finances
3.3684 .90913
PCO6 I believe mobile banking perfectly assembles my lifestyle
3.4789 .95235
Table 4.5 above shows the means and standard deviations of the responses regarding the
variable: perceived compatibility. Respondents slightly agreed that mobile banking is
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compatible with their beliefs and the way they are accustomed to their work with mean
values of 3.4632. Most disagreed when asked if mobile banking was compatible with
their past experience 3.2316. Respondents also slightly agreed that they’re able to
combine services and technologies into their daily lives with mean values of 3.5789.
They also agree that mobile banking have filled all the gaps caused by internet banking
with means values of 3.5000. They slightly agreed that mobile banking is the best way to
manage and control their finances with mean values of 3.3684. Respondents to some
extent agreed that they believe mobile banking perfectly assembles their lifestyle with
mean values of 3.4789.
Note: PCO (perceived compatibility)
Table 4.6: Mean analysis for perceived self-efficacy
Item ID Item DescriptionMean
(n=190)Std.
Deviation
PS1 I am familiar with mobile device 3.5895 .98125
PS2 I am familiar with checking my account balances through my mobile device
3.4684 1.02175
PS3 I am familiar with paying bills through my mobile device
3.3000 1.04881
PS4 I am of complete awareness and understanding of the benefits provided by mobile banking
3.4947 .96908
PS5 I am always willing to try new things 3.8632 .91560
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Based on the results from table 4.6, it is clear that most respondents were close to neutral
when asked if they were familiar with mobile devices. When asked if they are familiar
with checking their account balances through their mobile devices, the mean value also
turned out to be somewhat neutral, i.e. 3.4684. Respondents being familiar with paying
bills through their mobile devices reported a mean value of 3.3000. When asked if
they’re of complete awareness and understanding of the benefits provided by mobile
banking, neutrality was also the outcome with mean value of 3.4947. Respondents
willing to try new things showed us the highest agreement rate among subjects stating a
mean of 3.8632.
Note (perceived self-efficacy)
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Table 4.7: Mean analysis for subjective norms
Item ID Item Description
Mean(n=190) Std. Deviation
SN1 People who influence my behavior suggest that I use mobile banking
3.3526 .84005
SN2 If I use mobile banking, most of the people who are important to me will grade it as useful
3.3947 .82742
SN3 If I use mobile banking, most of the people who are important to me will regard it as valuable
3.4158 .91476
SN4 The reason why I chose to use mobile banking is because of the environment I live in
3.5474 .94582
SN5 I find it very critical that my surrounding have a positive perception about using mobile banking
3.4842 .90107
SN6 The media is considered the strongest influence adopters may take into account when choosing mobile banking
3.5474 .84538
Table 4.7 above shows the means and the standard deviations of the various responses
for subjective norms. When asked if people who influence their behavior suggest that
they use mobile banking, mean value appeared to be 3.3526. Respondents were also
slightly neutral with mean value of 3.3947 and 3.4158, when asked if they used mobile
banking, most of the people who are important to them will regard it as useful and
valuable. Respondents slightly agreed when asked if the reason why they chose to use
mobile banking is because of the environment they live in with mean value of 3.5503.
Moreover, respondents tended to agree that they find it very critical that their
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surroundings have a positive perception about using mobile banking, showing a mean of
3.4842. Considering the reason why the respondents chose to use mobile banking is
because of the environment they live in and that media as the strongest influence
adopters may take into account when choosing mobile banking showed mean values of
3.5474 for both questions.
Note: SN (subjective norms)
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Table 4.8: Mean analysis for perceived credibility
Item ID Item Description
Mean(n=190)
Std. Deviation
PC1 I believe that trust affects the demand for m-banking services
3.6789 .93553
PC2 I am comfortable with typing my credit/debit card detail in my mobile for a payment
3.3105 .95585
PC3 I believe that my transactions with mobile banking providers are likely to be safe
3.3421 .94495
PC4 I trust mobile banking providers because they keep my best interest in mind
3.3947 .92980
PC5 I find banking via mobile devices a way to reduce the risk of fraud
3.3368 .94964
PC6 I think that mobile banking providers do not sincerely consider security and privacy concerns
3.3632 1.03878
PC7 Considering security and privacy protection will make it less difficult to use mobile banking
3.3263 .83498
Based on the results from table 4.8, it is clear that most respondents were somewhat
neutral when asked if they believe that trust affects the demand for m-banking services
with mean value of 3.6789. When asked if they were comfortable with typing their
credit/debit card detail in their mobile for a payment, the concluded mean value was
3.3105. Additionally, respondents tended to slightly agree when asked if they believe that
transactions with mobile banking providers are likely to be safe with a mean value of
3.3421. The highest agreement rate among subjects reporting a mean value of 3.3947 was
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when they were asked if they trusted mobile banking providers because they keep their
best interest in mind. Respondents slightly agree that they find banking via mobile
devices a way to reduce the risk of fraud with a mean value of 3.3367. Thinking that
mobile banking providers do not sincerely consider security and privacy concerns came
up with a mean value of 3.3632. Considering security and privacy protection will make it
less difficult to use mobile banking with a mean of 3.3263
Note: PC (perceived credibility)
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Table 4.9: Mean analysis for perceived risk
Item ID Item Description
Mean(n=190) Std. Deviation
PR1 I find using mobile banking in my transactions not risky
3.0842 .97767
PR2 I do not experience any uncertainties or trust issues when making purchasing decisions
3.2789 .86745
PR3 I find it very risky to type in my personal details when using mobile banking
3.4737 .99567
PR4 I believe mobile banking is not secure enough to keep passwords or codes safely
3.6105 .97367
PR5 I believe mobile banking is more secure than internet banking
3.3526 1.07736
Table 4.8 shows us the mean analysis for perceived risk. Respondents find using mobile
banking in their transactions not risky with a mean of 3.0842. Not experiencing any
uncertainties or trust issues when making purchasing decisions had a slight agreement by
the respondents with a mean value of 3.2789. When asked if they find it very risky to type
in their personal details when using mobile banking, it led to mean of 3.4737.
Respondents agreed that mobile banking is not secure enough to keep passwords or codes
safely with the highest rate of agreement among the respondents (mean= 3.6105).
Believing mobile banking is more secure than internet banking, leading to a mean of
3.3526.
Note: PR (perceived risk)
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Table 4.10: Average mean of all variables
Variable Mean (n=190) Std. Deviation
Perceived usefulness 3.7316 .80116
Perceived ease of use 3.6421 .82187
Perceived compatibility 3.6895 .87493
Perceived self-efficacy 3.4211 .97676
Subjective norms 3.6000 .88372
Perceived Credibility 3.8684 .90767
Perceived risk 3.8947 .99175
Average mean and standard deviation of all variables was carried out and results were
shown in table 4.10. Based on the results, perceived risk had the largest mean average of
3.8947. This meant that the majority of the respondents agreed, on average, regarding
the questions asked about the variable. Perceived self-efficacy was the only variable
with a mean average of less than 3.5 having 3.4211. Perceived usefulness had an average
mean of 3.7316. Perceived ease of use on the other hand had a mean average of 3.6421.
Perceived compatibility and subjective norms had average means of 3.6895 and 3.6000
respectively. Perceived credibility had the second largest mean average of 3.8947.
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4.4: Reliability Analysis
Reliability analysis was conducted for this test using the cronbach’s alpha.
The minimum acceptable alpha for scale reliability is 0.60, this is according to Klassen
(2003). All the variables were in the range of 0.60 and above except perceived ease of
use with 0.589. Reliability analysis of perceived usefulness was 0.758, perceived
compatibility had an alpha of .773, perceived self-efficacy was .680, subjective norms
was .719, reliability analysis for perceived risk was .629. Mobile banking adoption, the
dependent variable, had an alpha of .740
Table 4.11 Reliability analysis for all variables
Code Variable No. of
items
Cronbach
Alpha
PU Perceived usefulness 7 .758
PE Perceived ease of use 7 .589
PCO Perceived compatibility 6 .773
PS Perceived self-efficacy 5 .680
SN Subjective norms 6 .719
PC Perceived credibility 7 .698
PR Perceived risk 5 .629
DV Dependent variable 7 .740
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4.5 Normality test
4.6 Correlation analysis
In this research, Pearson correlation analysis was used to identify the relationships
between the variables. Correlation is a statistical technique that used to determine
80
whether and how strongly pairs of variables are related. Correlation coefficient ranges
from -1.00 to + 1.00. A positive correlation result show how a positive relationship
between the variables and a negative correlation result shows a negative relationship
between the variables.
Table 4.12 Correlation matrix
Mean of perceivedusefulness
Mean of perceived ease of use
Mean ofperceivedcompatibility
Mean of perceived self-efficacy
subjective norms
Perceived credibility
Perceivedrisk
Dependent variable
MPUPearson CorrelationSig. 2-tailedN
1
190
MPEPearson CorrelationSig. 2-tailedN
.546**.000190
1
190
MPCO
Pearson CorrelationSig. 2-tailedN
.589**.000190
.567**.000190
1
190
MPSPearson CorrelationSig. 2-tailedN
.574**.000190
.501**.000190
.628**.000190
1
190
MSNPearson CorrelationSig. 2-tailedN
.516**.000190
.361**.000190
.548**.000190
.542**.000190
1
190
MPCPearson CorrelationSig. 2-tailedN
.468**.000190
.386**.000190
.492**.000190
.538**.000190
.567**.000190
1
190
MPRPearson CorrelationSig. 2-tailedN
.247**.000190
.168**.000190
.380
.000190
.422**.000190
.473**.000190
.488**.000190
1
190
MDVPearson CorrelationSig. 2-tailedN
.468**.000190
.442**.000190
.489
.000190
.458**.000190
.460
.000190
.417**.000190
.374**.000190
1
190
** Correlation is significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05 level (2-tailed)
Table 4.12 shows the results of pearson correlation matrix between variables. Based on
the result, it demonstrates that all the independent variables are significant if p-value is
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smaller than 0.01. Therefore, we can conclude that all the independent variables show a
significant and positive correlation towards the dependent variable.
4.6 Regression Ananlysis
Table 4.13: Regression Analysis on R & R Square
R R Square Adjusted R square Std. error of the estimate
Durbin-Watson
0.604a 0.365 0.341 0.45493 1.918
Table 4.13 not only illustrates a statistical test of the model, but also the value of R,
the corresponding R square, and the adjusted R square. The column that is labeled as R
shows the value of the multiple correlation coefficients. It’s generally a simple
correlation between the dependent variable and the independent variables. The adjusted R
square provides an idea of how well the model generalizes and its value is considered
relatively close to the value of R square. The last column of the above table demonstrates
the Durbin-Watson, this statistic helps to identify whether the assumption of the
independent errors is acceptable or rational. The closer the value to 2, the better, and for
this data the value 1.918, which is relatively to close that the assumption has almost been
met.
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Regression Coefficients
Unstandardized coefficients
Collinearity statistics
Model B Std. Error Beta T Sig. Tolerance VIF
Constant
MPU
MPE
MPCO
MPS
MSN
MPC
MPR
0.873
0.142
0.206
0.107
0.044
0.128
0.045
0.144
0.290
0.083
0.087
0.082
0.074
0.081
0.080
0.065
0.143
0.182
0.115
0.051
0.129
0.045
0.160
3.015
1.722
2.357
1.297
0.595
1.573
0.563
2.205
0.003
0.087
0.019
0.196
0.553
0.118
0.574
0.029
0.504
0.587
0.446
0.469
0.518
0.544
0.664
1.984
1.705
2.241
2.131
1.929
1.838
1.506
The first part of table 4.14 shows us estimates for the b values and that these values
specify the individual contribution of each variable to the model. The b values clarify to us
the relationship between the dependent variable (DV) and each independent variable. If the
value is positive, then there is a positive relationship between the independent variables and
the outcome while a negative coefficient indicates a negative relationship. The above data
clearly states that all the variables have positive b values which indicate a positive
relationship between each variable and the dependent variable.
The standardized beta values on the other hand are all measured in standard deviation
units and so are directly comparable. The higher the standardized beta value, the more
impact it has on the model. For instance, MPE with a beta value of 0.182 has more impact
on the model as compared to MPU that contributed to a beta value of 0.143.
The second last column shows the tolerance values, which is the measure of the
correlation between the variables and can diverge between 0 & 1. The closer the tolerances
value for a variable to 0, the stronger the relationship between this variable and the other
independent variables. In addition, tolerance value should be less than 1.0, if not the result
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will indicate multicollinearity problem occurrence. VIF on the other hand, which is found at
the end of the table, is an alternative measure of collinearity in which a large value shows a
strong relationship between the variables
Summary of hypotheses
Hypotheses Decision
H1 The usefulness of mobile banking will influence my intention to use it. Supported
H2Perceived ease of use will influence my decision to adopt mobile banking.
Not
Supported
H3 Perceived compatibility will play a significant role in determining my intention to use mobile banking
Supported
H4 I don’t need to be thought how to use mobile banking Supported
H5 Subjective norms will influence my decision to use mobile banking Supported
H6 Security and privacy of the system plays a major role in determining my intention to adopt mobile banking
Supported
H7I believe perceived risk will have a significant effect on my decision to adopt mobile baking
Not
Supported
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CHAPTER 5
DISCUSSIONS AND CONCLUSION
5.1 Introduction
The objective of this chapter is to an un-abridged discussion on the hypothesis
results from the previous chapter. Contribution of this study to research and study is also
discussed. Additionally, the limitations of this research to the results are also included in
this chapter. Suggestions for future research are also covered in this chapter. Finally, the
ending this chapter with the conclusion as the summary of the entire research.
5.2 Discussion on Hypotheses
H1: Perceived usefulness will have a positive effect on the behavioral intention to use
mobile banking.
Perceived usefulness was found to positively affect user acceptance of mobile
banking. This was in consistence with previous research findings, which found the
hypothesis to be supported (Luarn and Lin, 2005; Rao and Troshani, 2007). According to
Davis (1989), perceived usefulness is the degree to which a person believes that using a
particular system would enhance his or her job performance. The results were parallel
with previous researches that found it to have significant effect on information system
and usage. These studies prove the significant effect of perceived usefulness in
individual reactions to information technology. Hence, it is quite expected that the reason
why people use mobile banking is because they find it useful. Amin et al. (2008) stated
that perceived usefulness is strongly correlated with productivity. It suggests that using
computer in the workplace would improve job performance, increase user’s productivity,
enhance job effectiveness and be valuable in the job.
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H2: Perceived ease of use will have a positive effect on the behavioral intention to use
mobile banking.
Hypotheses 2 was not supported. From the results it was apparent that perceived
ease of use positively influences use of mobile banking among users in Malaysia.
Perceived ease of use refers to the degree to which a person believes that using a
particular system would be effortless (Davis, 1989). Respondents perceived the system
to be easy to use and did not require loads of knowledge. Luarn and Lin (2005) also
stated that there is a positive causality between perceived ease of use and the usage
intention. ). In the mobile setting, perceived ease of use corresponds to the degree to
which individuals relate freedom of difficulty with the use of mobile technology and
services in daily usage (Knutsen, Constantiou and Damsgaard. 2005).
H3: Compatibility will have a positive effect on the perceived ease of use of mobile
banking.
Perceived compatibility was supported based on the correlation analysis. This
meant that H3 was supported. According to Rogers (1995) perceived compatibility is
defined as “the degree to which an innovation is perceived as being consistent with the
existing values, past experiences and the needs of potential adopters”. Yu (2009) viewed
compatibility as a sign of how well the service or technology fits with the way the
customers manage and control their finances and how it ensembles their lifestyle.
Individuals are more likely to adopt an innovation when they find it compatible with
their past experience, beliefs and the way they are accustomed to work (Agarwal and
Prasad, 1998; Tornatzky and Klein, 1982). Rogers (1995) also added that compatibility
is demonstrated to capture the reliability between innovation and experience, values, in
addition to the needs of potential adopters.
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H4: Self – efficacy will have a positive effect on the perceived ease of use of mobile
banking.
Perceived self-efficacy or H5 was supported which was only a positive prove to
the previous researches that found it to positively influence mobile banking adoption.
Self-efficacy of mobile banking is defined as “a judgment of one’s ability to use a
mobile banking service” (Luarn and Lin, 2004). Self-efficacy could include knowledge,
skill and abilities needed to use the new IT.
H5: Subjective norm will positively influence intention to use Mobile baking.
Subjective norm or H5 was supported based on the correlation analysis. Prior
studies have discovered the importance of such construct in social science studies
including in banking studies (Amin et al., 2007; Nysveen et al., 2005; Kleijnen et al.,
2004). Amin et al., (2007) found that subjective norm was a key interpreter for mobile
banking use from a Malaysian point of view. The results were in line with previous
research that found it to have a significant effect on adoption of mobile banking.
Research also clarifies that the pressure from referent groups to adopt an innovation is
effective because it adds to reducing risk associated with adoption (Ishii, 2004; Lu et al.,
2003; Teo and Pok, 2003). Hartwick and Barki (1994) mentioned that the comparative
influence of subjective norm on intentions is anticipated to be stronger for potential users
with no pervious practice since they are more likely to rely on the reactions of others in
shaping their intention.
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H6: Perceived credibility will have a positive effect on the behavioral intention to use
mobile banking.
Perceived credibility was supported in this study. It mainly has two
elements: privacy and security. In this study, it was found that this variable has a positive
effect on the intention to use the system. By definition, perceived credibility is one's
judgment on the privacy and security issues of the mobile banking. As stated by Wang, et
al. (2003) security and privacy are the two important dimensions in perceived credibility.
The significance of security and privacy to the acceptance of banking technologies has
been illustrated in many banking studies (Howcroft, et al., 2002; Polatoglu and Ekin, 2001;
and Sathye, 1999). As mobile banking is considered relatively new, perceived credibility
has a higher ability to predict and analyze the uses’ intention to use mobile banking.
H7: Perceived risk will have a negative effect on behavioral intention to use mobile
banking.
Relating to prior studies and group discussions, it is obvious that users’ intention
to use new technology is affected by whether or not such risk does really exist. Perceived
risk will directly influence users’ intention to use mobile banking. Wong and Chang
(2005) considered that risk generally arises from the uncertainty that users face when
they cannot anticipate the consequences of their purchase decision. Perceived risk or H7
was not supported based on the correlation analysis.
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5.3 Contributions to research
Results from this research provide more evidence that certain factors still influence
adoption to mobile banking regardless of the change in times. Findings were also found
to support the TAM (Technology Acceptance Model) by Davis (1989) which provides
futher evidence of the appropriateness of the model.
The findings of this study also help future researchers. The findings will help
researchers identify gaps that need to be filled in order to conduct further research in this
area. Researchers can also benefit from the results of this study as they can use it as a
reference for their work. It will also assist them in choosing which variables to test and
which not to test in their research.
The findings of this of this study also helps to better understand the factors that
influence adoption of mobile banking in Malaysia, an area that has not been covered
widely.
5.4 Contributions to Practice
This study’s result can also be implemented to help banks better understand what
really influences adults in Malaysia to adopt mobile banking. By referring to these
findings, they can be able to formulate effective techniques to attract this group into
adopting to the system.
The campaigns can be used to educate more on the relative advantage of using the
system as well as how to handle and protect themselves from security and privacy issues.
Campaigns can also be used to enhance confidence among those with low self-efficacy
via manifestations at bank branches using a one-on-one consultancy system. For
instance, these campaigns can be located in universities (since most young adults are in
universities).
89
The government as well as other organizations should motivate their staff and
customers to use the system. Organizations can also influence use of the system by
encouraging their customers to make their payments or check their financial status by
using mobile banking system. They can also influence the use of this system by offering
free training for those interested.
5.5 Limitation of study
1. Most of the data was obtained from the internet, journal publications and library.
There was some lack of information due to unavailable funds to subscribe the articles.
2. Additionally, the study sample was from Multimedia university students who were
selected according to convenience. Additionally the respondents were only from one
certain location and therefore cannot be used to represent the entire population of
Malaysia
3. In terms of the questionnaires, some were not properly filled, which led to distorted
data. Originally the total amount of questionnaires distributed were 230, but due to
respondents not willing to fill up the questionnaires or might have filled in some parts
incorrectly, led to distorting 40 questionnaires.
5.6 Suggestions for future research
Future research should be conducted withholding the limitations of this study in
mind. Suggestions like conducting research in other universities could be useful, like
Hanudin (2007) have suggested. Results can be compared, and general and more
accurate conclusions can be drawn.
90
Research should also be conducted on non-mobile banking users to better know if
they intend to adopt the system in the near future or not. If not, researches could be
conducted to clarify that and find solutions.
Future research shouldn’t just be limited to universities only as there are young
adults who are not in universities but are rather working. If resources are available, this
perspective should be looked at.
5.7 Conclusion
The findings show that intention to use mobile banking can be predicted by
perceived usefulness, ease of use, compatibility, self-efficacy, subjective norm,
credibility and perceived risk. This result signified that the first research question was
answered (What are the key factors that influence the intention to use mobile banking
services in Malaysia?).
Perceived risk yielded a mean of 3.8947, which was higher than all the other variables
(perceived usefulness, 3.7316; perceived ease of use, 3.6421; perceived compatibility,
3.6895; perceived self-efficacy, 3.4211; subjective norms, 3.6000; perceived credibility,
3.8684).
In conclusion, banks could also include extra features on their mobile applications to
make the experience more memorable, fun and secure so that customers will gain the
confidence that will influence them to use this system. Transaction costs should also be
at a very minimal amount.
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APPENDICES
92
Dear respondent,
This questionnaire is done as part requisite to complete my final year project as part of
my Bachelors degree (Hons) on Banking and finance to get an overview on factors influencing
the intension to use Mobile banking services. The study is essential for the legitimate
compilation of information regarding the scope of study.
The questionnaire firstly obtains your information in order to understand the
respondent’s overall response to the questions that is the demographics of the respondents. It
will then on the second part encompass the core questions of the research. These are questions
on the factors influencing the intensions to use Mobile banking services.
The respondent is assured of the utmost confidentiality on all pieces of information provided.
Thank you.Yours faithfully,
………………………NEBIL ABDUREZAK AHMEDBachelor of Business Administration (HONS) Banking and FinanceFaculty of Business and LawMultimedia UniversityMalacca Campus
93
For further clarification or questions please contact:
Nebil abdurezak: E-mail: [email protected] or Phone: 010-2502570 OR
Dr. Uchenna: E-mail: [email protected]
PART I
Please tick the appropriate answer that is applicable to you
Personal information
1. Gender Male Female
2. Age group 15−20 21−25 26−30 31and Above
3. Nationality Malaysian Others (Please specify) ___________
4. Race Malay Chinese Indian Others
5. Marital Status Single Married
6. FacultyFBL FIST FET
7. Monthly income range RM0 -- RM500 RM501--RM1,000 RM1,001 – RM1,5000 RM1501 – RM2,000 RM2,001 – RM2,500 RM2,501 & Above
94
Understanding of Mobile Banking
Are you familiar with Mobile Banking services?
□ Yes
□ No
□ Not that much
Have you used Mobile-banking services before?
□ Yes
□ Never
□ Once before
□ A few times
□ Intending to use in future
How many years have you used mobile devices (such as cell phones and PDAs) do you have?
□ <1 year
□ 1- less than 3 years
□ 3 – less than 5 years
□ 5 or more years
Are you satisfied with your banking institution’s mobile application?
□ Yes
□ No
How likely are you to use Mobile banking?□ Very unlikely
□ Somewhat unlikely
□ Not Sure
□ Somewhat Likely
□ Very likely
Part II
Please answer the following questions by circling the one you feel most suitable with.
Perceived Usefulness Strongly Disagree
Disagree Neutral Agree Strongly Agree
Mobile banking would be useful in conducting my banking transactions
1 2 3 4 5
Using mobile banking enables me to conduct banking transactions more quickly
1 2 3 4 5
If I were to adopt mobile banking, it would be a more effective way to make transactions
1 2 3 4 5
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Mobile banking would give me greater control 1 2 3 4 5
Mobile banking would improve the quality of my decision making 1 2 3 4 5
Using m-banking will allow me to enjoy a variety of services regardless of my recent location
1 2 3 4 5
I am able to find mobile connectivity in the remotest places, including areas where Internet applications is weak 1 2 3 4 5
Perceived Ease of Use
I find banking transactions on mobile phones easy and simple 1 2 3 4 5
I find mobile banking clear and understandable proficient 1 2 3 4 5
It would be easy to do what I want while using mobile banking 1 2 3 4 5
I find mobile banking through cell phone very user friendly1 2 3 4 5
I find mobile banking less time consuming1 2 3 4 5
Using mobile banking can be frustrating (R)1 2 3 4 5
I find certain services on mobile phones very friendly, especially when browsing internet-like interfaces on mobile device 1 2 3 4 5
Perceived Compatibility
I find mobile banking compatible with my beliefs and the way they are accustomed to work
1 2 3 4 5
I find mobile banking compatible with my past experience 1 2 3 4 5
With mobile banking, I am able to combine services and technologies into my daily life
1 2 3 4 5
I believe mobile banking have filled all the gaps caused by internet banking
1 2 3 4 5
I find mobile banking the best way to manage and control my finances1 2 3 4 5
I believe mobile banking perfectly assembles my lifestyle1 2 3 4 5
Perceived Self-efficacy
I am familiar with my mobile device 1 2 3 4 5
I am familiar with checking my account balances through my mobile device
1 2 3 4 5
I am familiar with paying bills through my mobile device 1 2 3 4 5
I am of complete awareness and understanding of the benefits 1 2 3 4 5
96
provided by mobile banking
I am always willing to try new things 1 2 3 4 5
Subjective Norms
People who influence my behavior suggest that I use mobile banking 1 2 3 4 5
If I use mobile banking, most of the people who are important to me will regard is as useful
1 2 3 4 5
If I use mobile banking, most of the people who are important to me will regard is as valuable
1 2 3 4 5
The reason why I chose to use mobile banking is because of the environment I live in 1 2 3 4 5
I find it very critical that my surrounding have a positive perception about using mobile banking 1 2 3 4 5
The media is considered the strongest influence adopters may take into account when choosing mobile banking 1 2 3 4 5
Perceived Credibility
I believe that trust affects the demand for m-banking services. 1 2 3 4 5
I am comfortable with typing my credit/debit card detail in my mobile for a payment
1 2 3 4 5
I believe that my transactions with Mobile Banking providers are likely to be safe
1 2 3 4 5
I trust mobile banking providers because they keep my best interest in mind
1 2 3 4 5
I find banking via mobile devices a way to reduce the risk of fraud 1 2 3 4 5
I think that mobile banking providers do not sincerely consider security and privacy concerns
1 2 3 4 5
Considering security and privacy protection will make it less difficult to use mobile banking
1 2 3 4 5
Perceived Risk
I find using mobile banking in my transactions not risky 1 2 3 4 5
I do not experience any uncertainties or trust issues when making purchasing decisions.
1 2 3 4 5
I find it very risky to type in my personal details when using mobile banking
1 2 3 4 5
I believe mobile banking is not secure enough to keep passwords or codes safely
1 2 3 4 5
97
I believe mobile banking is more secure than internet banking 1 2 3 4 5
Dependent Variables
The usefulness of mobile banking will influence my intention to use it.
1 2 3 4 5
Perceived ease of use will influence my decision to adopt mobile banking.
1 2 3 4 5
Perceived compatibility will play a significant role in determining my intention to use mobile banking
1 2 3 4 5
I don’t need to be thought how to use mobile banking 1 2 3 4 5
Subjective norms will influence my decision to use mobile banking 1 2 3 4 5
Security and privacy of the system plays a major role in determining my intention to adopt mobile banking
1 2 3 4 5
I believe perceived risk will have a significant effect on my decision to adopt mobile baking
1 2 3 4 5
Please rank the following in order of most influential when choosing the type of banking
system to use. With “1” being the most important and “8” being the least important.
Perceived Usefulness
Perceived Ease of use
Perceived Compatibility
Perceived Self-efficacy
Subjective Norms
Perceived Credibility
Perceived Risk
Thank you for your time and dedication to respond to my questionnaire.
98
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