at the university of sheffield by reza...
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Factors leading to the adoption of Mobile-banking in the UK
A study submitted in partial fulfilment
Of the requirements for the degree of
Master of Information System and Management
At
THE UNIVERSITY OF SHEFFIELD
By
Reza Mojtahed
September 2010
1
Abstract:
Background:
The Mobile banking is a new service offered by British banks to their customer, with
large capital investment to start up and promote it. Since there is no study performed
in Britain, this research has been concentrated to identify the behavioural factors
effecting mobile banking.
Aims:
The objective of this research is to identify the factors having an impact on intention
to use of mobile banking by mobile phone users in the UK. The framework of the
research includes six main factors of perceived ease of use (PEOU), perceived
usefulness (PU), perceived enjoyment (PE), perceived risk (PR), Accessibility, and
demographic variables (age, gender, and education).
Method:
A Survey is selected as suitable methodology for doing this research, because of the
nature of this research is quantitative, probability sampling was selected as
appropriate method to gather data. Since conducting this survey in the entire UK is
not possible due to time and cost restrictions, students of Sheffield University chosen
as the sample. Of around 350 questionnaires printed or distributed through university
e-mail list, 140 valid questionnaires were collected in 3 weeks.
Results:
The factors identified to have positive influence on intention to use mobile banking
are perceived ease of use, perceived usefulness, and perceived enjoyment while two
factors of perceived risk and accessibility appear to have negative influence on
intention to use of mobile banking. In addition, the researcher identified that three
factors of perceived risk, perceived usefulness, and perceived enjoyment have direct
relationship with intention to use of mobile banking. Moreover, three factors of
perceived risk, perceived enjoyment, and perceived ease of use are identified as
having direct influence on perceived usefulness of mobile banking. Finally, the factor
2
of perceived ease of use is identified to have direct relationship with perceived
enjoyment of the mobile banking.
Conclusion:
In this research, seven out of thirteen hypotheses are approved. However, the
respondents were mostly post graduate students therefore they were not
representative of whole students of the university of Sheffield and perform study
again in this area could provide better result in term of understanding of student point
of view. In addition, the educated people are just part of whole population and study
of wider population could provide better result. The study of the factors such as
culture, trust, and politics are suggested for future research on adoption of mobile
banking.
3
Acknowledgements:
This dissertation is dedicated with love and appreciation to God and my family who
supported me through my life.
To my parents, Dr. Davoud Mojtahed and Dr. Fahimeh Abtahi, that without all of
their love and support, I could not reach to this point to write this dissertation. To my
brother Hamed that aspires to be an IT scientist to serve the world.
To my uncle and his wife, Morteza and Marzeyeh, for all of their help and support.
To my supervisor, Dr. Miguel Baptista Nunes at the University of Sheffield that
consistently helped me with encouragement and advice through all stages of this
work.
I thank God everyday for blessing me with such fortune.
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Table of Content:
Abstract: ................................................................................................................................... 1
Acknowledgement: .................................................................................................................. 3
Chapter One: Background ........................................................................................................ 9
1.1 Introduction: ................................................................................................................. 10
1.2 The Research Problem: ................................................................................................ 11
1.3 Scope of the research: .................................................................................................. 11
1.4 Research question, Objective, and Hypothesis: ........................................................... 11
1.4.1 Research question and Objectives:........................................................................ 11
1.4.2 Hypothesis: ........................................................................................................... 12
1.4.3 Research Model: ................................................................................................... 13
1.5 Organisation of the research: ....................................................................................... 13
Chapter two: Literature Review ............................................................................................. 15
2.1 M-commerce: ............................................................................................................... 16
2.1.1 Introduction: .......................................................................................................... 16
2.1.2 The Benefits of the Mobile Commerce: ................................................................ 18
2.1.2.1 Benefit for customers: ........................................................................ 18
2.1.2.2 Benefit for Organisations: .................................................................. 18
2.1.3 The shortcoming of Mobile-Commerce: ............................................................... 19
2.2 E-banking and movement toward applying m-commerce in banking sector: .............. 20
2.2.1 Introduction: .......................................................................................................... 20
2.2.2 Electronic banking in the UK: .............................................................................. 22
2.2.3 Benefit of mobile banking: ................................................................................... 24
2.2.4 Mobile banking Services offered through banks in the UK: ................................. 25
2.2.5 E-banking Customers: ........................................................................................... 25
2.3 Information System adoption models .......................................................................... 26
2.3.1 Introduction: .......................................................................................................... 26
2.3.2 Information Success Model: ................................................................................. 27
2.3.3 Innovation Diffusion Theory (IDT): ..................................................................... 28
2.3.4 Task Technology Fit (TTF): ................................................................................. 28
2.3.5 Theory of Reasoned Action (TRA): ...................................................................... 29
2.3.6 Theory of Planned Behaviour (TPB): ................................................................... 30
2.3.7 Technology acceptance model (TAM): ................................................................ 31
5
2.3.7.1 Perceived Ease of Use and Perceived Usefulness: ............................. 31
2.3.7.1.1 Perceived Usefulness (PU):......................................................... 32
2.3.7.1.2 Perceived Ease of Use (PEOU): .................................................. 32
2.3.8 TAM 2: .................................................................................................................. 33
2.3.9 UTAT: ................................................................................................................... 34
2.3.10 Comparison of theories: ...................................................................................... 35
2.4 Past studies in area of the adoption of mobile-commerce ............................................ 35
Chapter Three: Research Methodology: ................................................................................ 39
3.1 Research Approach: ..................................................................................................... 40
3.2 Research Method: ........................................................................................................ 40
3.2.1 Literature Review:................................................................................................. 41
3.2.2 Survey: .................................................................................................................. 42
3.2.3 Sampling: .............................................................................................................. 42
3.2.4 Data collection: ..................................................................................................... 42
3.2.4.1 Questionnaire: .................................................................................... 43
3.2.4.1.1 Questionnaire structure: .............................................................. 43
3.2.4.1.1.1Technology acceptance model: ............................................. 44
3.2.4.1.1.2 Perceived ease of use and Perceived Usefulness: ................ 45
3.2.4.1.1.3 Perceived risk: ...................................................................... 46
3.2.4.1.1.4 Perceived enjoyment: .......................................................... 47
3.2.4.1.1.5 Socio-demographic: ............................................................. 47
3.2.4.1.1.6 Accessibility: ........................................................................ 48
3.2.5 Data Analysis: ....................................................................................................... 48
3.3 Reliability:.................................................................................................................... 49
3.4 Ethical issue of the research: ........................................................................................ 50
Chapter 4: Findings ................................................................................................................ 51
4.1 Descriptive Analysis: ................................................................................................... 52
4.2 Frequency analysis: ...................................................................................................... 56
4.2.1 Frequency analysis of Accessibility: ..................................................................... 56
4.2.2 Frequency analysis of perceived ease of use questions: ....................................... 57
4.2.3 Frequency analysis of perceived usefulness: ........................................................ 61
4.2.4 Frequency analysis of perceived risk: ................................................................... 62
4.2.5 Frequency analysis of perceived enjoyment: ........................................................ 62
4.3 Mean Comparison: ....................................................................................................... 65
4.3.1 Accessibility: ......................................................................................................... 65
6
4.3.2 Perceived Ease of Use: .......................................................................................... 65
4.3.3 Perceived Usefulness: ........................................................................................... 66
4.3.4 Perceived risk (security and privacy): ................................................................... 68
4.3.5 Perceived Enjoyment: ........................................................................................... 68
4.4 Data Analysis: .............................................................................................................. 69
4.4.1 T-test: .................................................................................................................... 69
4.4.1.1 Perceived ease of use: ........................................................................ 69
4.4.1.2 Perceived usefulness: ......................................................................... 70
4.4.1.3 Perceived Risk:................................................................................... 70
4.4.1.4 Perceived Enjoyment: ........................................................................ 71
4.4.1.5 Accessibility: ...................................................................................... 72
4.4.2 Regression test: ..................................................................................................... 72
4.4.2.1 Regression test one:............................................................................ 72
4.4.2.2 Regression tests two: .......................................................................... 75
4.4.2.3 Regressions test three: ........................................................................ 76
4.4.3 Correlation test: ..................................................................................................... 77
4.5 Discussion: ................................................................................................................... 80
4.5.1 Findings: ............................................................................................................... 80
4.6 Managerial suggestion: ................................................................................................ 84
Chapter 5: Conclusion ............................................................................................................ 86
5.1 Conclusion: .................................................................................................................. 87
5.2 Lessons learned: ........................................................................................................... 88
5.3 Limitations: .................................................................................................................. 88
5.4 Further research: .......................................................................................................... 89
References: ............................................................................................................................. 90
Appendix 1 : ......................................................................................................................... 106
Appendix 2: .......................................................................................................................... 111
Appendix 3: .......................................................................................................................... 112
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Tables:
Table 1: Banks offered Mobile-banking services ...................................................... 24
Table 2: Mobile-banking services offered by banks .................................................. 25
Table 3: Relevant Situation for Different Research Strategies .................................. 41
Table 4: Cronbach's Alpha for each variable ............................................................. 50
Table 5: Demographic characteristics ........................................................................ 52
Table 6: Frequency of respondent answers about Q7 ................................................ 56
Table 7: Frequency of respondent answers about Q8 ................................................ 57
Table 8: Frequency of respondent answers about Q9 ................................................ 58
Table 9: Frequency of respondent answers about Q10 .............................................. 58
Table 10: Frequency of respondent answers about Q11 ............................................ 59
Table 11: Frequency of respondent answers about Q12 ............................................ 60
Table 12: Frequency of respondent answers of Q13 through Q17 ............................ 61
Table 13: Frequency of respondent answers of Q20 through Q22 ............................ 62
Table 14: Frequency of respondent answers about Q23 ............................................ 63
Table 15: Frequency of respondent answers about Q24 ............................................ 63
Table 16: One sample mean test of PEOU................................................................. 69
Table 17: One sample mean test of PU ...................................................................... 70
Table 18: One sample mean test of PR ...................................................................... 70
Table 19: One sample mean test for PE ..................................................................... 71
Table 20: One sample mean test of accessibility ....................................................... 72
Table 21: Model summery ......................................................................................... 73
Table 22: ANOVA ..................................................................................................... 73
Table 23: Coefficients a of Test One ......................................................................... 75
Table 24: Coefficients a of Test two.......................................................................... 76
Table 25: Coefficients a of Test three ....................................................................... 77
Table 26: Correlation ................................................................................................. 79
Table 27 : Result of Hypothesis Test ......................................................................... 83
8
Figures:
Figure 1: The research Model .................................................................................... 13
Figure 2: Information Success Model, DeLone and McLean (1992). ....................... 27
Figure 3: Basic model of TTF .................................................................................... 29
Figure 4. Theory of Reasoned Action ........................................................................ 30
Figure 5: Theory of planned behaviour ...................................................................... 30
Figure 6: Technology acceptante model (TAM) ........................................................ 32
Figure 7: Technology Acceptance Model 2 ............................................................... 33
Figure 8: Unified Theory of Acceptance and Use of Technology ............................. 34
Figure 9: Percentage of mobile banking services users prefer to use ........................ 53
Figure 10: Source of information of the respondent‘s about mobile banking services
.................................................................................................................................... 53
Figure 11: Type of mobile phone of respondents ...................................................... 54
Figure 12 : Access to mobile internet ........................................................................ 55
Figure 13: Mean of accessibility questions ................................................................ 65
Figure 14: Mean of perceived ease of use questions.................................................. 66
Figure 15: Mean of perceived usefulness questions .................................................. 67
Figure 16: Mean of perceived risk questions ............................................................. 68
Figure 17: Mean of perceived enjoyment questions .................................................. 68
Figure 18: Approved model ....................................................................................... 83
9
Chapter One: Background
Chapter 1 consists of five main parts: introduction; research problem; scope of the
research; research question, objectives, hypothesis; the research model; and finally
organisation of the research.
10
1.1 Introduction:
We live in an era in which information and communication technology has
penetrated in to all activities and businesses by changing the methods and ways of
performing tasks. In recent decades, the impact of Information and Communication
Technology is very well recognized in business and government segments. The
Information and communication technology facilitates and shapes the daily lives of
individuals in different forms by providing services such as e-commerce, e-
government, e- learning, e-health, and e-working (Dwivedi et al., 2008).
E-commerce has reshaped how businesses interact with their customers and operate
internally by changing the communication and exchanging information in digitalized
form, by using electronic based technology with aim of performing the task in virtual
area (Rayport and Jaworski, 2001).
E-commerce is recognized as a new medium for linking with customers and is an
essential tool for enhancing products and services; thereby adopting information
technology is essential for commercial transactions and activities such as banking,
trading, supplying, etc (Shaw et al., 2000).
The success of information technology in the banking industry transforms it as a rival
tool in the competing economies (Kannabiran and Narayan, 2005). Today, the
banking sectors are using information and communication technology for providing
better services to their customer by suggesting different services such as telephone
banking, automated teller machine, internet banking and mobile banking.
Mobile banking is a new service offered by banking sector to their customers and
because of its convenience, and time saving features: the customers value it
(Suoranta, 2003).
The main impact of using Information and communication technology in business
and government is the high volume use of internet and mobile network by
government and citizens (Erdmann and Behrendt, 2003). Therefore, the rapid
expansion of information and communication technology in our daily lives and
utilization of such technology by businesses and organizations emphasizes that the
adoption of information technology is highly needed not only for organizations but
also, for customers in order to reach high effectiveness and efficiency in a
competitive world.
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1.2 The Research Problem:
According to suggested statistics by the International Telecommunication Union
(ITU), by the end of 2012, the number of mobile cellular subscriptions would reach
to approximately 4.5 billion worldwide (ITU, 2008). Even though the number of
mobile phone subscriptions in UK has reached to more than 75 million (Cellular-
news, 2009), a very few number of these users are mobile banking customers in UK.
According to a 2009 statistics published by KPMG 67 percent of the population feels
uncomfortable using mobile phone for financial purposes. However, 77 percent of
this population stated that accessing online banking on their mobile phone is
important to them but would not wish to pay for such services.
The Mobile banking is a new service offered by British banks to their customer, with
large capital investment to start up and promote it. Because of the failure of U.S.
banks when they introduced mobile banking to their customers due to the lack of
interest by their customers and subsequently the loss of huge sums of assets and
investment (Mallat et al., 2004); British banks are more cautious and conservative in
their approach. Given, that only few studies have been conducted to identify the
factors influencing the adoption of mobile banking and especially since there is no
study performed in Britain, this research has been concentrated to first identify the
behavioural factors effecting mobile banking. In addition, find out the impact of
those identified factors on the intention to use mobile banking.
1.3 Scope of the research:
This research surveys and analyses the adoption of mobile banking among mobile
phone users in the UK. Since, the possibility of performing research in the whole UK
is not possible due to financial and time constraint this research focuses on
undergraduate, postgraduate, and PhD students at Sheffield University. The
questionnaire for this research was distributed in prints and also was available on
line.
1.4 Research question, Objective, and Hypothesis:
1.4.1 Research question and Objectives:
What are the factors having an impact on the behaviour of UK mobile phone
users when utilizing Mobile banking services?
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As result of the research question identified, five research objectives are suggested:
Identify mobile banking services users prefer to use when banking.
Identify from the literature review, the factors that have an impact on the
intention of users to engage with mobile banking service.
Establish theory on this issue.
Test and explore the impacts of the identified factors on mobile phone users
in the UK.
Establish the possible solutions and methods for increasing the use of mobile
banking.
1.4.2 Hypothesis:
This research has 13 hypothesises as follow:
𝐻1 : Perceived Ease of Use has direct relationship with the intention to use of mobile
banking.
𝐻2 : Perceived Usefulness has direct relationship with the intention to use of mobile
banking.
𝐻3 : Perceived Risk has direct relationship with the intention to use of mobile
banking.
𝐻4 : Perceived Enjoyment has direct relationship with the Perceived usefulness of
mobile banking.
𝐻5 : Gender has direct relationship with the intention to use of mobile banking.
𝐻6 : Age has direct relationship with the intention to use of mobile banking.
𝐻7 : Education has direct relationship with the intention to use of mobile banking.
𝐻8 : Accessibility to internet through mobile phone has direct relationship with the
intention to use of mobile banking.
𝐻9 : Perceived ease of use has direct relationship with the Perceived usefulness of
mobile banking.
𝐻10 : Perceived risk has direct relationship with the Perceived usefulness of mobile
banking.
13
𝐻11 : Perceived enjoyment has direct relationship with intention to use of mobile
banking.
𝐻12 : Accessibility to mobile and internet has direct relationship with the Perceived
usefulness of mobile banking.
𝐻13 : Perceived ease of use has direct relationship with the Perceived enjoyment of
mobile banking.
1.4.3 Research Model:
The research model was created based on a review of the literature, which is
explained in chapter 2. The research model consists of six main factors that have
been deduced from the literature review. The research model is a combination of
TAM (Davis, 1989), perceived risk (for example: Langendoerfer, 2002),
demographic variables (for example: Morris and Venkatesh, 2000; McKechnie et al.,
2006), perceived enjoyment (for example: Davis et al., 1989), and accessibility (for
example: Daniel, 1999). The research model is shown in Figure 1.
Figure 1: The research Model
1.5 Organisation of the research:
This research consists of five chapters. Chapter 1 includes the introduction, research
problem, research question and objective. Chapter 2 is a literature review which
discusses mobile commerce, electronic banking, information system adoption
theories and previous studies about adoption of mobile commerce. Chapter 3
explains research methodology. In chapter 4, the findings, through data gathered by
questionnaires, are analysed, described and explained; in addition, managerial
Perceived Risk
Perceived
Usefulness
Perceived
Ease of Use
Intention to
Use Mobile
Banking
Accessibility
Age
Education
Gender
Perceived
enjoyment
14
solutions are suggested. Chapter 5 offers a conclusion, limitations and suggestions
for further research.
15
Chapter two: Literature Review
This chapter consists of three parts; first of all, this chapter explains m-commerce; its
definition, benefits and shortcomings. In the second part, the research considers e-
banking services and the movement towards using the benefits of m-commerce and
offering mobile banking services. In third part, different information system adoption
models are explained and then comparisons between the models are performed.
16
2.1 M-commerce:
2.1.1 Introduction:
During the last two decades, the rapid growth of mobile phones across the world has
aspired organizations to offer their products and services through this medium
(Dholakia and Dholakia, 2004). Since the expectation of researchers and scholars in
the mid-1990s in relation to extensive growth and use of e-commerce by customers
was not realized, the researchers have aspired to achieve their goals through wireless
tools (Prabhaker, 2000; Ropers, 2001). The strategic advantages offered by mobile
technology in organizations include improving workflow, information sharing,
communication and marketing and as a result, more sales and market share (Sheng et
al., 2005).
Feng et al. (2006) defined m-commerce as something different from e-commerce
with its own functionality and characteristics of interaction styles such as mobility
and broad reach ability. Researchers predict a prosperous future and an increase in
the transaction of m-commerce will depend on the penetration rate of mobile phones
in the world ( Hampe et al., 2000; Kannan et al., 2001; May, 2001) and also having
the advantage of internet access through mobile phones (Carlsson, 2000; Delichte,
2001; Hampe et al., 2000; Müller-Versee, 2000; Kim et al., 2007) . An opportunity to
access internet by mobile devices becomes possible by using 3G, GPRS, and WAP
technology (Park et al., 2007).
M-commerce started in 1979 through the introduction of first generation analogue
mobile phone technology. The first generation (1G) of mobile phones evolved
gradually in 1990s, which lead to the second generation (2G) of mobile phones that
was based on digital radio technology and provided the option of sending text
messages. The third generation technology started in Japan and it has diffused
rapidly since 2001. However, another generation of mobile phone technology was
introduced which is referred to as 2.5 generation (2.5G) technology that is between
3G and 2G as temporary technology with the possibility of sending limited graphics
until suitable technology replaces it (Turban and King, 2003; Kim et al., 2007).
Today, the use of mobile phones is a necessary and inseparable part of human life
(Laukkanen, 2005) and the statistics published by Internet World in 2007 shows that
there are 1.24 billion internet users in 210 countries while the number of mobile
17
phone subscribers have reached 2.7 billion (Mobile World, 2007 cited in Dai and
Palvia, 2009). Therefore, it can be concluded that m-commerce can surpass e-
commerce in the future.
Tarasewich et al. (2002) defined mobile commerce as way of performing all
commercial activities through wireless communication medium. The internet access
through mobile phone provides the possibilities of doing commerce, communication,
and content (Kim et al., 2007). The applications that can be run through mobile
technology are mobile-banking, mobile entertainment, mobile advertising, and
mobile ticketing (Kupper and Gao, 2007). For example; mobile financial applications
such as mobile-banking, mobile money transfer and brokerage services are an
essential part of m-commerce, these services in the future could be an adequate
replacement for doing business and banking. Mobile advertising would be an
effective form of advertising in the future. The socio-demographic information of
users, which is provided by the users to telecommunication companies and
considering the location of users, provides a highly successful form of targeting
customers. In modern societies where the population is always on the go, mobile
entertainment offers soothing distraction and convenient entertainment for mobile
phone users. However, for providing such services suitable mobile phone, and high
bandwidth wireless technology are required (Varshney and Vetter, 2002).
Hampe et al. (2000) stated that the penetration rate of mobile phones is more than
PCs in most industrialized countries. According to statistics, the numbers of existing
mobile phones in the UK are nearly 76 million, while the population is about 61
million (Cellular-news, 2009). The statistic shows a high adoption rate of mobile
phones among British citizens which represents a high potential for performing
business through this technology. However, the number of people adapted in to the
mobile banking services is around one third of the mobile phone population
(Cellular-news, 2010). Furthermore, based on the Gartner Group (2009) study, only 1
percent of all mobile phone users used their mobile phone for payment purpose
services in 2008. The study of human behaviour is imperative in order to offer
effective consumer services and to diffuse m-commerce (Green et al., 2001).
According to Cellular magazine article, there needs to be more research on the
factors influencing the mobile banking usage and to dispute the fact that the
convenience of mobile banking would automatically attracts customers.
18
2.1.2 The Benefits of the Mobile Commerce:
2.1.2.1 Benefit for customers:
The obvious benefit m-commerce provides in comparison of e-commerce to its
customers are mobility (Sarker and Wells, 2003 ; Kim et al., 2007) and possibility of
communication at any time (Wei et al., 2009; Wong and Hiew, 2005; Kim et al. ,
2007 ; Varshney and Vetter, 2000 ; Davis, 2002). Mobility is defined as the ability to
access services in all locations (Wei et al., 2009; Wong and Hiew, 2005) at all times
through wireless devices such as mobile phone and PDA (Coursaris and Hassanein,
2002; Lyytinen and Yoo, 2002). Also, Yao et al. (2007) defines mobility as
flexibility consumers can achieve by eliminating location and time restriction. Mallat
et al. (2008) conducted a study on individuals who travel frequently, or who have
lives that are continually in transit to identify their habits for using services, banking
and shopping. He concluded that the mobility of users does not necessarily increase
by using mobile technology but movement is reduced while access to all services is
available through mobile phones. Therefore, it can be concluded that mobility
provides time and place independency (Mallat et al., 2008). The other benefit is
being wireless. However being wireless is different as mobility, the devices
considered as wireless do not necessarily support mobility (May, 2001). The
customers however might appreciate wireless capabilities since utilizing them
requires less skill and money and eliminates the need for wires and cables. However
wireless technology is not as flexible and offers only limited capabilities (Anckar and
Dincau, 2002). Therefore, the applications and services run through mobile phone
provide the advantage of time and place independency (Carlsson et al., 2006;
Constantiou et al., 2006; Mallat, 2007).
2.1.2.2 Benefit for Organisations:
Utilizing mobile technology has gained importance and popularity among
organisations (Gayeski, 2002; Andersen et al., 2003; Siau and Shen, 2003; Siau et al.,
2004). Today, use of information technology (IT) is defined as strategic tool for the
organisation (Buhalis, 2004). The advantages mobile technology could offer to
organisations are the same as any other form of IT. The main benefits of utilizing IT
by an organization is productivity improvement (Hitt and Brynjolfsson, 1996), cost
and labour reduction, and profit growth (Mukhopadhyay et al., 1995; Santhanam and
19
Hartono, 2003; Buhalis, 2004; Jarvenpaa and Ives, 1990; Brown et al., 1995; Ryan
and Harrison, 2000). Also, the banks who are pioneer in implementing new IT will
benefit from the exposure by having a more competitive brand and a bigger market
share (Salehi and Alipour, 2010).
The deployment of an information technology by an organisation would have an
influence on internal performance and competitive advantage of the organisations,
which leads to how they operate, by changing the product they offer and forms of
their competition (Porter and Millar, 1985). Increasing the quality of services offered
to customers (Anderson et al., 2003), and efficiency of transfer of information, along
with high standard products (Ryan and Harrison, 2000) are the advantages of
implementing IT in the organisation.
However, some researchers question the validity of impact IT might have on
productivity (Bharadwaj et al., 1999; Devaraj and Kohli, 2000; Bharadwaj, 2000;
Santhanam and Hartono, 2003; Melville et al., 2004; Ray et al., 2004). Even though
IT‘s financial impact is not proven; most researchers however agree on IT‘s impact
in offering better customer service and thereby increasing customers‘ satisfaction
(Kohli and Devaraj, 2004; Ray et al., 2004).
Furthermore, a study by Sheng et al. (2005) on how implementation of mobile
technology impacts organisational performance shows the use of mobile technology
by organisations leads to improve working process, increase communication and
knowledge sharing, and increase effective sale and marketing by the organisation.
2.1.3 The shortcoming of Mobile-Commerce:
Utilizing mobile phones for commercial purposes has advantages as well as
disadvantages. The main disadvantages are the focus of this paragraph.
The small screen size and keyboard of mobile devices (Kim et al., 2007; Hill and
Troshani, 2009; Hoehle and Huff, 2009; Laukkanen, 2005; Condos et al., 2002;
Green, 2000) have a negative impact on perception of ease of use of the m-commerce
applications which in turn deter users from using such applications. According to a
study on mobile banking the small screen size of mobile device is identified as
suitable for informative type of banking such as showing account balance but for
transaction forms of banking larger screen size is required (Laukkanen, 2007).
20
However, research indicates that the users‘ ability to read and interact with different
screens is the same regardless of the screen size (Dillon et al., 1990; Duchnicky and
Kolers, 1983; Resiel and Shneiderman, 1987; Shneiderman, 1987).
Furthermore, Teo and Pok (2003) study indicates mobile phone banking can be
boring and tedious for some users. While, Pura (2005) and Kim et al. (2007) study
shows banking transactions by mobile phone is quite joyful for the users. The
interface design of mobile phone devices is one of the elements impacting the users‘
satisfaction. However, the utility and the objective of the application in use have a
great influence on the interface design and navigation (Cyr et al., 2006). In addition,
users‘ concerns over security and privacy of their personal data while mobile
banking keeps many potential users away. The mobile phones users are concerned
about their personal information being tracked by mobile operators (Hill and
Troshani, 2009) or sold to a third party (Wu and Wang, 2005). In addition, Luarn and
Lin (2005) stated that the concern of mobile phone users about security of mobile
phone devices for performing monetary transaction is another issue deterring users
from utilizing mobile banking.
2.2 E-banking and movement toward applying m-commerce in banking
sector:
2.2.1 Introduction:
The benefits gained through information and communication technology for future
performance of financial sectors is obvious, especially in the banking industry
(Kannabiran and Narayan, 2005). Integrity, responsiveness, reliability, availability,
functionality and high speed of fulfilling the process of banking tasks and customer
requests are identified as factors, which lead to customer satisfaction and increase
their tendency to utilize e-banking services in comparison to traditional form of
banking (Johnston, 1995; 1997). The ICT provides self-service and electronic based
advancements to the banking sector that enables banks to provide electronic based
services to their customers such as telephone banking, Automated Teller Machines,
internet banking, and mobile banking ( Hoehle and Huff, 2009).
Automated Teller Machines (ATM) were introduced in 1970. It is known as the first
self-service technology in the banking industry. Moutinho et al. (1989) defined ATM
as a computerized telecommunication medium that provide secure communication
21
between customers and banks, providing direct access for customers to their money
and bank accounts. There have been different studies performed to identify the
factors that have an impact on the intention of users to use ATM. According to some
of the research findings elderly people are less likely to use ATM (Leblanc, 1990;
Marshall and Heslop, 1988) and also perceived ease of use, performance expectation,
and perceived enjoyment have direct influence on using ATM (Dabholkar and
Bagozzi, 2002).
Telephone banking was introduced a decade after the ATM machine. It is a service
offered by banks to customers for doing transactions over the telephone. Most of the
services offered by telephone banking are based on an automated answering machine
with an interactive voice response and a phone keypad response mechanism (Ahmad
and Buttle, 2002). However, telephone banking is known by customers to be a
difficult and tiresome method for banking ( for example: Van Birgelen et al., 2006).
The proliferation of the World Wide Web during the 90s made it possible for the
banking industry to offer new services to their customers: internet banking. The
internet banking application allows customers to access and perform their banking
activity through the use of the banks‘ websites (Tan et al., 2000). Internet banking at
the beginning of its first introduction was known as tool for informing customers
about bank activities and services offered and it was more informative rather than
transactional at that time. But, with new available technologies that guaranties safety
and privacy of on-line banking transactions, internet banking has shifted from only
informative transactions to actually performing a task on line (Tan and Teo, 2000).
Finally, the diffusion of mobile phones and the possibility of access to the internet
through mobile devices have simultaneously provided the movement to perform
banking by mobile devices in e-banking area (Pouttchi and Schuring, 2004). Mobile
banking has been available in European and Asian countries since 1999 (Suoranta
and Mattila, 2004). During the last decade, the banking sectors have offered a mobile
banking application, which allows customers to use their mobile phones, smart-
phones, and personal digital assistances (PDA) for fulfilling their financial
transactions (Barnes and Corbitt, 2003; Hoehle and Huff, 2009). The mobile phone
screen allows customers two forms of interactions; through text messaging or
internet access, with their banks (Hoehle and Huff, 2009). There are many services
22
offered to mobile banking customers such as checking balances, transacting on
accounts, paying invoices, transferring money between accounts, monitoring the use
of credit cards and activities on the accounts, selling and buying stocks, buying
credit for mobile phones and pricing information (Laukkanen and Pasanen, 2005).
This research focuses on mobile banking through internet access by mobile phones.
According to Laukkanen (2005), each type of e-banking service provides different
values for customers. The considerable difference or advantage of m-banking
services in comparison to other e-banking services is the possibility of immediate
action in m-banking while the other type of e-banking services such as internet
banking is still place dependent (Laukkanen, 2005). Simply stated, for internet
banking people are required to be at home or office while mobile-banking can take
place anywhere with a mobile phone that can access internet. Recently, because of
highly competitive nature of banking industry, some of the British banks are offering
mobile-banking package to their customers based on 3G mobile technologies. Since
M-Banking is a new tool for providing banking services to customers understanding
the factors influencing, the utilization of mobile banking by customers is highly
required.
2.2.2 Electronic banking in the UK:
The implementation of information and communication technology in the banking
sector raised the expectance of ending the brick and mortar banking and transformed
it in to a more convenient form of banking which is known as online banking (St
Germain, 2005). Because of the benefits offered by on line-banking such as,
convenience, lower cost ,and sales, customers behaviour for visiting actual branch
banks is shifting and less customers are walking through branch banks (Trethowan
and Silicone, 1997). Burnham (1996) estimated the cost of an opening a bank branch
is around $1.5 to $2 million with the annual operating cost of around $500.000.
These figures represent a decade ago and the initial investment and operating cost for
branch banks in today‘s market is estimated to be higher. The estimated cost of
offering and up keeping banking services through internet is 50 percent less than of
conventional banking, which makes mobile banking even more lucrative for the
banking industry ( Ivatury and Ignacio , 2008). As a result, IT utilization and
equipping banks with the necessary technology to offer on line banking is imperative
to the banks‘ bottom line and customers‘ satisfaction. The first committee of London
23
clearing bank was held in 1955 than can be considered as the first movement toward
automation of banking sector. In 1961, the first form of automation of banking in
England was introduced by using Power-Samas tablators to pay shareholders‘ profit.
The Barclays Bank and Martins Bank were pioneers in using computer technology
for banking activities. Barclays introduced ATM to its customers in mid-70 while
linking all the Barclays‘ branches together took from 1961 to 1974, or 13 years (B-
Lazo and Wardley, 2007). The first forms of e-banking services in the UK were
offered by the ―HomeLink‖ in the early 1980s (Tait and Davis, 1989). However, the
use of e-banking was discontinued due to lack of acceptance by the customers
(Vinson and McVandon , 1978). Nevertheless, the rapid growth of the internet and
the popularity of e-services among people, rehabilitated the interest to use e-banking
services (Booz and Hamilton, 1996; Daniel, 1998), for example based on the
statistics published by the UK payment administration in the first half of 2009, 22
million adults banked online, which is more than 50 percent of internet users in the
UK (UK payment administration, 2010). Daniel (1999) investigated the provision of
electronic banking in the UK and stated that based on the challenges that exist for
future competition in banking sectors, the electronic channels such as digital TV and
personal computers would be suitable means to satisfy the requirements. Recently,
due to high competition to attract more customers, some banks such as Lloyds,
NatWest, and Barclays are offering mobile-banking packages to their customers
based on 3G mobile technologies. The name of banks who provides mobile banking
services to their customers are presented in table 1:
24
Table 1: Banks offered Mobile-banking services
Banks offering Mobile banking services
BARCLAYS
LIoyds TSB
HSBC
RBS
NATWEST
Sources: Barclays, Lioyds, HSBC, RBS, Natwest websites 2010
2.2.3 Benefit of mobile banking:
Today mobile banking is known as the most cost saving form of doing online form of
transaction (CGAP, 2008). According to Suoranta (2005) factors such as
independency of m-banking services to time and place (Wei et al., 2009; Wong and
Hiew, 2005), connivance, time and effort saving and increased privacy are benefits
perceived by users that lead to adoption of mobile banking services. Also, mobile
banking offers time and place independency and efficiency which internet banking
lacks according to a study conducted by Laukkanen (2005) comparing mobile
banking with internet banking.
25
2.2.4 Mobile banking Services offered through banks in the UK:
The m-banking services are offered through text and internet. The main services
offered through mobile are check balance, transfer money, mini statement, and
payment. The detail of services offered by banks are provided in the table below.
Table 2: Mobile-banking services offered by banks
Banks Check
Balance
Transfer
Money
Mini
statement
Payment Request
Pin
Check
Book
Exchange
rate
Mobile
phone
top up
Service Through
Internet Text
BARCLAYS
LIoyds TSB
HSBC
RBS
NATWEST
Sources: Barclays, Lioyds, HSBC, RBS, Natwest websites 2010
2.2.5 E-banking Customers:
In recent decades, the high intention of the banks to move from branch banking
toward online form of banking is greatly obvious. This strategy helps banks save
their resources and use their human resource management in an effective way. In
addition, customers‘ loyalty to traditional forms of banking has declined and their
attitude toward online banking has shifted recently. Customers now are demanding
24/7 banking services and are more adapt in using the new technology to have access
to their accounts (Coelho and Easingwood, 2004). Despite the fact that the
customers‘ tendency for using electronic based financial services has increased, the
usage rate of electronic banking channels however shows a different reality (Hoehle
and Huff, 2009). According to DB Research (2006) in Europe 73 percent of bank,
customers used services offered by ATM machine while 24 percent used internet
banking. Research performed in North America and Australia in 2007 indicates that
26
only between 5 and 10 percent of customers used mobile banking and telephone
banking (Forrester Research, 2007). According to Oxford Internet Survey (OIS) in
2009, one out five internet users in Britain accessed internet through their mobile
phones or wireless devices. According to this statistic, men are more likely to use
mobile devices rather than women. Based on the statistic published by OIS students
are the highest ranking group to access internet on the move, 30 percent, while
employed and retired people are in second and third place by 22 and 7 percent
respectively. In addition, OIS survey in 2009 indicates that nine out of ten (89%)
British people have mobile phone (Dutton et al., 2009).
Therefore, based on the statistics published by OIS the population have the necessary
and required tools to utilize m-banking, nevertheless the given statistic does not
imply an increase in mobile banking. Therefore, attention must be given to both
better marketing and declining social psychological constraints effecting utilization
of m-banking. Therefore, this research aims to identify the factors influencing the
intention to use mobile banking by the users of mobile phone in the UK.
2.3 Information System adoption models
2.3.1 Introduction:
Since the last four decades, an implementation of Information system (IS) in
organisations has been known to be costly, frustrating and with a low success rate in
the management information system (MIS) literature review (Legris et al., 2003). An
organisation decides to invest in IS in order to improve its performance, maintain
customer satisfaction increase the quality of its services and decline cost (Legris et
al., 2003). Therefore, it is imperative to implement the most effective methods of IT
that can also be welcomed and accepted by customers. Identifying the reasons of
acceptance or rejection of IS has been one of the main challenges of IS research
(Swanson, 1988). Davis (1989) stated that one of the main indications of IS success
or failure is the level/degree of the acceptance of the system by the users. This
statement clearly represents the importance of user acceptance of the system. Since
IT usage has become one of the main determinants of organisation performance
(Devaraj and Kohli, 2003) and organisations continue to invest in IT advancement
allocating a large portion of their assets for IT investment even during financial
crises (Kanaracus, 2008). Identifying a suitable model for acceptance of IT has been
prioritised as the main goal in IS researches. The social psychological ( for example:
27
Technology Acceptance Model) and marketing theories ( For example: Expectation
Disconfirmation Theory) are widely used for identifying the reasons of IT usage by
the researchers. Swanson (1982) , and Bhattacherjee and Premkamar (2004) stated
that the social psychology theories have been identified and evolved as appropriate
theoretical backgrounds for identifying and explaining the reasons of user acceptance
or rejection of an IS .
There are different models for adoption of an IS among users. In this research eight
main models (Theory of Reasoned Action, Theory of Planned Behaviour,
Technology Acceptance Model, TAM2, Innovation Diffusion Theory, Task Fit
Technology, Information success model, and Unified Theory of Acceptance and Use
of Technology ) of IS adoption are first explained and finally compared in below.
2.3.2 Information Success Model:
The Information Success Model was developed by Delone and Mclean in 1992. The
Information Success Model is defined as consisting of six variables: system quality,
use, information quality, individual impact, organizational impact, and user
satisfaction. According to Delone and Mclean (1992) model a successful
implementation of IS in organization depends on the users interaction with IS. They
claimed that in order to provide acceptable interaction between an individual and
information system is the user satisfaction must increase. They mentioned that one
way to increase satisfaction of users regarding IT is to inform them of the qualities
and advantages provided by using IT.
Figure 2: Information Success Model, DeLone and McLean (1992).
However, an Information Success Model similarly to other theories, are full of
shortcomings ( for example: Pitt et al, 1995; Seddon and Kiew, 1996; Myers et al.,
1997; Seddon et al., 1999; Jiang et al., 2002). Delone and McLean (2002; 2003)
have reviewed this model after its publish in 1992 and have suggested modifications.
Use System
Quality
Information
Quality
User
Satisfaction
Individual
Impact
Organisational
Impact
28
They added the service quality variable and replaced the variable of individual and
organisational impacts with net benefits (Petter et al., 2008). Finally, they added the
variable of an intention to use as sub part due to the belief that the users satisfaction
will dictate and influence the intent of use, while positive experience of using the
system will lead to user satisfaction that results in high intention to use the system
(Delone and Mclean, 2003).
2.3.3 Innovation Diffusion Theory (IDT):
IDT was introduced by Rogers in 1995. Rogers (1995) theory provides the broad
structure about the factors that have an influence on individual choices for selecting
and using of an innovation. He suggested that the amount of information users
receive leads them to have greater trust in the system. In IDT, according to Rogers
(1995) diffusion is inseparable part of adoption. Rogers (1995) stated that adoption
process in IDT consist of five parts. Part one: awareness of individuals regarding
innovation. The awareness of individuals about innovation can be influenced by
personal characteristics, which means that particular characteristics of users can
produce specific type of behaviour (Wood and Swait, 2002). Furthermore, the socio-
economical situation and the mass media have influence on users‘ awareness
(Bandura, 2001). Part two is persuasion which is in relation to the condition when an
individual has received sufficient information about innovation thus enabling them to
reach a decision as to whether it is a favourable or unfavourable innovation. Stage
three is about an individual‘s decision to accept or reject of innovation. Stage four is
―implementation‖ which means that individuals act based on their decision. The final
stage is confirmation which refers to an individual‘s behaviour based on his or her
decision and also re-evaluation in order to decide to continue or stop the adoption of
an innovation. As mentioned before Rogers (1995) stated that diffusion is an
inseparable part of adoption. In addition, he defined diffusion as a particular type of
communication. The diffusion theory consists of four parts (communication
channels, social system, time, and innovation) that explain how individual adoption
leads to diffusion. However, the IDT model has raised some concerns amongst the
researchers who have study the theory (Straub, 2009).
2.3.4 Task Technology Fit (TTF):
Goodhue (1995) and Goodhue and Thompson (1995) developed and defined TTF as
the task, and way people make decisions to use IT which result in different
29
outcomes. This means that those individuals using information system with high
perception of TTF will have better performance than individual who perform the task
but with low TTF. They introduced this model in order to find out the relationship
between performance of an individual and IS. The TTF model consists of four main
variables: Task characteristic, technology characteristic, TTF, and performance or
utilization. According to Goodhue and Thompson (1995) model task and technology
characteristic combined together influence TTF, which TTF then influences
performance or utilisation. Goodhue and Thompson (1995) defined technology
characteristics as the technology selected by an individual in order to task. They also
defined task characteristics as the behaviour performed by an individual in order to
transfer input into output. Task Technology Fit is defined as the level of technology
used to help people to do their task (Goodhue and Thompson, 1995).
Figure 3: Basic model of TTF
2.3.5 Theory of Reasoned Action (TRA):
TRA was suggested by Fishbein and Ajzen in 1975. The main goals of Fishbein and
Ajzen is the understanding and predicting of human behaviour that finally leads to
TRA (Hartwick and Barki, 1994). TRA includes four common concepts; behavioural
attitude, subjective norms, plan to use, and actual usage. The element of subjective
norm is considered an important element of TRA. This element suggests that
Individual behaviour is greatly influenced by social influences that were founded in
the social explanation for using of the media (Shih and Fang, 2004). Based on
Fishbein and Ajzen (1975) people‘s subjective norms are directly or indirectly under
the influence of other people, which means that society‘s opinion greatly influences
individual behaviour and defines the social norm. The perception toward TRA is
structured in a way that is affected by beliefs that behaviour is outcome driven and is
measured based on the desirability of the outcome. Therefore, people attitude
towards behaviour is as a consequence of people‘s salient beliefs about the results of
Task
Characteristic
Technology
Characteristic
Task Technology
Fit
Performance
Utilisation
30
actual behaviour multiplied by the assessment of those consequences (Davis et al.,
1989). The subjective probabilities of individuals about doing a particular task will
lead to specific consequences defined as beliefs (Fishbein and Ajzen, 1975).
Figure 4. Theory of Reasoned Action
2.3.6 Theory of Planned Behaviour (TPB):
The TPB ( Ajzen , 1985;1991) is a developed version of TRA (Fishbein and Ajzen,
1975). Both theories, TRA and TPB, suggest that behavioural intention is based on
behaviour. The TPB indicates that behavioural intention is based on three factors;
attitude, subjective norms, and perceived behavioural control (PBC). The PBC was
added as a factor to suggest that individual behaviour is not completely under their
control in some situations (Ajzen, 1985:1991; Ajzen and Madden, 1986). PBC
suggests that individual behaviour is influenced by the perceived facilities which
exist for individuals (Shih and Fang, 2004). Therefore, according to Ajzen (1991),
the difficulties or the ease of the facilities and resources provided for users impact
people‘s behaviour.
Figure 5: Theory of planned behaviour
Attitudinal
Belief
Normative
Belief
Attitude
Subjective
Norm
Subjective
Norm
Attitudinal
Belief Behavioural
intention
Actual Usage
Normative
Belief
Attitude
Subjective
Norm
Attitudinal
Belief
Attitude Attitudinal
Belief
Normative
Belief
Perceived
Behavioural
Control
Control
belief
Subjective
Norm Behavioural
intention
Actual
Usage
Attitude
31
2.3.7 Technology acceptance model (TAM):
TAM was introduced by Davis in 1989. At that time the emphasise was on
achieving and identify the effective factors that have an impact on user acceptance of
information technology by both researchers and organisations. There was a lack of
the proper model for user adoption of IT since all of the suggested models in that
period were invalidated or their relationship to the usage were unverified
(Davis,1989). One decade after the entry of the TAM structure in to a group of
information system (IS) adoption models, TAM has been approved as strongest,
most pervasive and continuous model used in the area of measuring adoption of IT
(Venkatesh and Davis, 2000).
Davis (1989) and Davis et al. (1989) suggested TAM as a suitable model that can
address the reasons why users accept or reject IT. TAM was developed based on the
social psychology theory of reasoned action (Fishbein and Ajzen, 1975; Ajzen and
Fishbein, 1980) and the theory of planned behaviour, which is an evolved version of
TRA that was introduced by Ajzen in 1991. TRA is based on the assumption that
people consider the impacts of their possible actions and make decisions to do the
tasks based on their reasoning ( Ajzen and Fishbein, 1980). This means that in the
case of mobile banking services the mobile phone users will use mobile banking if
they believe this bank service would be beneficial to them. TAM consists of two
factors; perceived ease of use and perceived usefulness, which is explained in the
next page.
2.3.7.1 Perceived Ease of Use and Perceived Usefulness:
Davis identified two elements; perceived ease of use (PEOU) and perceived
usefulness (PU), as effective factors, influencing peoples‘ behaviour when using
information technology with reliability of 0.98 and 0.94 as measures of usefulness
and ease of use respectively. Davis (1989) found that both factors of PEOU and PU
had strong correlation with current and self-predicted future usage of information
technology. However, he concluded that the perceived usefulness has a stronger
relationship with usage of computer technology than perceived ease of use.
Furthermore, his findings indicated that; a system‘s ease of use has an impact on the
users‘ perception of a system‘s usefulness. The TAM structure is presented in Figure
6 .
32
Figure 6: Technology acceptance model (TAM)
2.3.7.1.1 Perceived Usefulness (PU):
PU defines the usefulness of a system as apparent by its users and states that users
will continue using the system until they no longer find the system useful. Davis
(1989) defined PU as ―the degree to which a person believes that using a particular
system would enhance his or her job performance‖. PU is identified as one of the
important elements, which has an impact on intention to use IT. This issue is greatly
emphasised by most of the researchers who have tried to identify the factors leading
to the adoption of IT ( for example: Agarwal and Prasad, 1999; Davis et al., 1989;
Hu et al., 1999; Jackson et al., 1997; Venkatesh, 1999; Mathieson et al., 2001; Yi and
Hwang, 2003; Venkatesh et al., 2003; Heijden, 2004; Wixom and Todd, 2005; Park
et al, 2009).
2.3.7.1.2 Perceived Ease of Use (PEOU):
PEOU is defined as ―the degree to which a person believes that using a particular
system would be free of effort‖. The difficulties of using a system somehow
overcome the benefits of the system and this issue reveals the influence of PEOU on
the PU of the system that since the system is easy to use it seems more useful and
vice versa (Davis,1989). According to Agarwal and Prasad (1999), Davis et al.
(1989), Jackson et al. (1997), Venkatesh (1999), Yi and Hwang (2003), Wixom and
Todd (2005) and Park et al. (2009), PEOU has a direct impact on intention to use IT
while indirectly effecting PU.
In conclusion, Adams et al. (1992), Hendrickson et al. (1993,1996), Segars and
Grovers (1993), Szajna (1994), Igbaria et al. (1995), Moon and Kim (2001) have
studied the impact of PEOU and PU in different environmental and organisational
Perceived
Usefulness
Perceived
ease of use
Behavioural
intention to use
Actual
system use
33
contexts and all of them have concluded that those elements are valid and reliable
and have an influence on the usage of IT.
TAM has been tested and approved as a useful and reliable model for acceptance and
adoption of IS by many authors (see, for example, Davis, 1989; Davis et al., 1989;
Mathieson, 1991; Adams et al., 1992; Davis, 1993; Segars and Grover, 1993; Taylor
and Todd, 1995; Davis and Venkatesh, 1996). Furthermore this model has evolved
with many changes added by many researcher (see, for example, Venkatesh and
Speier, 1999; Venkatesh and Davis, 2000; Venkatesh et al., 2002; Henderson and
Divett, 2003; Lu et al., 2003). For example, Venkatesh and Davis (2000) introduced
an extension of the TAM model, which explains how the elements of the cognitive
instrumental process and social influences have an impact on PU and the intention to
use IS.
2.3.8 TAM 2:
TAM2 is an extended form of TAM model with the social and organisational
variable added. TAM2 consists of two instrumental processes: Social influential and
cognitive instrumental. The variables such as subjective norms, image, job relevance,
output quality are variable of these processes added in to the TAM model (Venkatesh
and Davis, 2000). According to Venkatesh and Davis (2000), subjective norm has an
influence on perceived usefulness and intention of users to use technology. TAM2
model is presented in the table below:
Figure 7: Technology Acceptance Model 2
Subjective
norms
Image
Job
Relevanc
e
Output
Quality
Result
demonstrability
Perceived
Usefulness
Perceived
Ease of Use
Intention
to use
Usage
Behaviour
Technology Acceptance
Model
34
2.3.9 UTAT:
A Unified Theory of Acceptance and Use of Technology (UTAUT) was introduced
by Venkatesh et al. in 2003. UTAUT model suggests that performance expectancy,
effort expectancy, facilitating conditions, and social influences have an influence on
behavioural intention to use IT. Performance expectancy in UTAUT model is
defined as the degree an individual believes that using IT helps improve job
performance. Effort expectancy is explained as the level of ease provided by using
IT. Social influences is the perception of an individual about others‘ opinion on
whether or not IT shoud be employed. Finally facilitating condition is technical and
organisational infrastructures provided to users to support the use of IT (Venkatesh et
al., 2003). Furthermore, UTAUT model consist of some moderating factors for
overcoming the inconsistencies that exist in other IS adoption model. Moderating
factors are: gender, age, experience, and variance of use. Venkatesh et al. (2003)
stated that this model is not a complete model and requires modification for
application in different context. UTAUT model is presented in Figure 8.
Figure 8: Unified Theory of Acceptance and Use of Technology
Age Gend
er
Experience
Social
Influence
s
Effort
expectanc
y
Performance
Expectancy
Facilitating
Conditions Voluntariness of
use
Behavioural
intention
Use
Behaviour
35
2.3.10 Comparison of theories:
Each of the social psychology approaches mentioned above offer a different theory
about IT adoption by people. However, there are some similarities between these
methodologies. The four theories of TAM2, TAM, TRA, and TPB all state that
attitude, intention, and behaviour are related to each other. This means that these
theories believe that normative, cognitive, or individual perception and beliefs
influence people attitudes and attitude impacts behavioural intention to use
technology and finally leads to actual usage of technology. The information success
model (Delone and Mclean, 1992) theorised that intention to use IT is based on
quality of information and system and also users‘ satisfaction. On the other hand,
Information Diffusion Theory (Rogers, 1995) suggests that an individual knowledge
of the system , society, time and innovation lead individual to decide trusting the
system and adopt IT. Task technology fit (Goodhue and Thompson, 1995) is defined
as the task people intend to do and the characteristic of the technology to ease the
way of doing task. There are some similarities between UTAT and TAM model.
Performance expectancy is same as perceived usefulness and effort expectancy is
similar to perceived ease of use. Furthermore, TTF, IDT, TRA, TPB, PU, PEOU, and
Information success model all suggest that people decision making process which is
effected by their conscious attitude impacts the utilization of IT. The two theories;
Information success model and IDT, both suggest that the quality of information has
an impact on behavioural intention to use technology. In addition, persuasion of
individuals about salient of the factors and awareness of individuals about
innovations are closely similar to PEOU and PU.
2.4 Past studies in area of the adoption of mobile-commerce
The features of mobile services (for example: mobile banking) influence the factors
leading to adopt such technology (Hill and Troshani, 2009). In this section, the past
researches in the area of m-commerce which explores the factors influencing the
intention to use are explained and discussed.
Wu and Wang (2005) studied the factors impacting the adoption of mobile
commerce in Taiwan. Their study model is based on the combination of TAM and
IDT and they also used perceived risk and cost elements which was introduced in
TAM2 by Vanketash and Davis in 2000. They concluded that perceived risk,
36
compatibility, cost and perceived usefulness have direct impact on the intention to
use mobile commerce while perceived ease of use has an impact on perception of
usefulness of the system but its direct impact on intention to use was not supported.
Another study was performed by Laukkanen and Cruz (2009) in order to identify the
factors that influence resistance of customers when engaging in mobile banking in
two European countries, Finland and Portugal. Their findings indicate that
perception about mobile banking‘s risks has an influence on users‘ resistance in both
countries . However, the element of risk is emphasised as a more influential factor to
resist m-banking by Finnish rather than Portuguese customer. Hill and Troshani
(2009) studied the elements, which have an influence on adoption of mobile services
among young population and as the result of their studies; two elements of perceived
enjoyment and usefulness are identified as the strongest factors that lead to attract
young population to use and adopt mobile services. In addition, they suggested that
the adoption of services depends on type of services offered to users. Moreover, they
identified perceived risk as a factor with less impact than Perceived usefulness and
perceived enjoyment. Security and privacy are two important elements that have an
influence on intention of users to accept e-based system of transaction. Based on the
result of Park et al. (2007) security and privacy are identified as factors leading to
user dissatisfaction of e-banking services. In Australia, Wessels and Drennan (2009)
investigated the acceptance of mobile banking by Australian consumers, and studied
how the factors of perceived usefulness, compatibility, and perceived cost have a
direct relationship with intention to use mobile banking and concluded that the
elements such as risk, perceived usefulness, perceived cost, and compatibility are
influencing users‘ attitudes which can impact on the intention to use mobile
banking. Gu et al. (2009) examined the impact of PEOU, PU, and trust on intention
to use mobile banking and based on this study, these three factors have direct
influence on intention to use mobile banking. Furthermore, perceived ease of use and
trust increases the influence of perceived usefulness on intention to use of mobile
banking. Kim et al. (2010) studied the factors influencing the intention for using
mobile payment system. According to this study having knowledge and information
about mobile payment system empowers the perception of the users about ease of
using the mobile payment systems. In addition, factors such as convenience,
accessibility, and mobility are identified as the characteristics that can impact users‘
perceived usefulness of the system while convenience and reachability are
37
concluded to impact the perceived ease of use. Mallat (2007) researched factors
acting as barriers for adopting m-commerce and identified premium price of the
payment, complexity of payment procedures , lack of widespread merchanent
acceptance and perceived risk as main barriers. Hacking and un-authorized access to
mobile phone information and records are recognised as risks associated with mobile
commerce (Mallat, 2007). Dai and Palvia (2009) conducted a cross-cultural study to
find out factors impacting adoption of mobile commerce in two countries, China and
USA. They concluded innovativeness, perceived usefulness, perceived ease of use ,
perceived cost and subjective norms have impacts on the intention to use m-
commerce in China while in the USA compatibility, perceived enjoyment, perceived
usefulness, innovativeness, and privacy concerns were identified as influential
factors on intention to use mobile commerce. Liu et al. (2009) studied the role of
trust and TAM with the intention of Chinese users to use mobile banking and what
they identified as result of their study is PU and trust have a direct influence on
intention to use mobile banking. However, the direct impact of PEOU on intention to
use is not supported but, PEOU impacted usefulness of the mobile banking system.
The characteristics of an individual is identified as one of the elements which has
impact on IS success (Zmud, 1979; Nelson, 1990). Suoranta (2003) in her study
identified age and education as major factors impacting people intention to use
mobile phone for banking services. She identified the average age of mobile banking
users to be between 25 and 34 years. Also, Suoranta and Mattila (2004) stated that
the early adaptors of innovative services have better education, social position, and
occupation.
Amin et al. (2007) studied the factors leading to acceptance of mobile banking in
Malaysia, and concluded that PEOU, and PU of TAM model has an impact on the
adoption of mobile banking. Wang et al. (2006) studied factors influencing
Taiwanese mobile phone users using mobile services and as result of their studies
PEOU and PU have a considerable impact on Taiwanese population for using mobile
services. Laukkanen and Pasanen (2005) identified age and gender as effective
variables influencing the customers perception of using mobile banking. According
to their findings men are more likely to use mobile banking services rather than
women. In addition, they claimed that the middle age people intention to use mobile
banking is 1.9 times greater than those between the ages of 18 and 24.
38
Lee et al. (2007) studied elements leading to resistance to use mobile banking
services in Korea and Finland and they identified, perception about the risk and lack
of knowledge and information about mobile banking lead to resistance and rejection
of mobile banking. Yang (2005) studied the influence of TAM toward the adoption
of mobile commerce in Singapore and as the result of his studies, TAM is quite an
appropriate model for explaining the consumer decision making process to use m-
commerce. According to Lee et al. (2007) the current system of e-banking is one of
the barriers to adoption of mobile banking since internet banking customers are
quite satisfied with internet banking and resist the shift to mobile banking. Security
and privacy are identified by different researchers as factors impacting people‘s
decisions negatively about on-line banking (Singh, 2004; Kim et al., 2006; Luarn et
al., 2005; McKnight et al.,2002). According to Luarn and Lin (2005) security and
privacy are identified as an influential factor on perception of mobile banking users
about use of such technology to perform their banking activities. Security and
convenience of mobile banking are considered privileges of mobile banking in
comparison to other type of e-banking (Herzberg, 2003). Mattila (2003) identified
risk as a prominent factor on the adoption of m-banking. Heijden (2003) in his study
on influential factors impacting usage of websites found out that perceived ease of
use has an influence on perceived usefulness and enjoyment of the system.
According to Cyr et al. (2006) ease of using a system leads to enjoyment. Liao et al.
(2007) studying factors impacting the usage of 3G mobile services in Taiwan
observed that perceived usefulness, enjoyment, and ease of use have positive
influences on users‘ attitude and perceived ease of use has influence on perceived
enjoyment and also perceived enjoyment impacts perceived usefulness. In addition,
Gu et al. (2009 ) observed that perceived ease of use has an impact on perceived
usefulness of the mobile banking system. According to a study conducted by
Suoranta (2003), Anckar and D‘Incau (2002), Luarn and Lin (2005), Laukkanen
(2007) for adoption of mobile banking to be success access to the services at any
time and place is imperative. Thereby access to internet through a mobile phone with
such capability is the main component of successful m-banking.
39
Chapter Three: Research Methodology:
This chapter introduce the methodology of the dissertation. It starts by discussing the
research approach, explanation about methodology that was applied and methods and
tools used to perform this research. In addition, issues such as reliability and ethical
concerns of the research are discussed at the end of this chapter.
40
3.1 Research Approach:
There are two types of research approaches: inductive and deductive. The two
approaches differ in the methods utilized to draw conclusion. Saundars et al. (2000)
defined the inductive approach as collecting data and then developing theory from
the data. Deductive approach however draws conclusion based on theory and
hypothesis and evaluates and refines that conclusion against the real world data
afterward (Zikmund, 2000). This research is deductive. That means the research
begins with theory and then the researcher evaluates the theories against the real
world (De Vaus, 2002).
There are three main approaches in information system projects: quantitative,
qualitative, and design research. The quantitative approach is based on developing
figures that can be used to explain the area of study, while the qualitative approach is
usually about understanding the case by making interviews and observations and
attending to real situations (Pickard, 2007). The design research is about explaining,
understanding, and developing the behavioural aspect of information system by
analysing the use and design of artefact (Vaishnavi and Kuechler, 2009).
The aim of this study is to identify the degree of impact from factors deduced from
the literature review on usage of mobile-banking services. Due to the scope and aims
of this research, the quantitative approach, which involves numerical representation,
is deemed to be the best approach. In addition, this research is both descriptive and
explanatory. It is descriptive because it aims to identify and describe the factors,
which positively influence users of mobile phones to use mobile banking services.
Moreover, this research is categorized as explanatory because it then explains the
influence of these factors.
3.2 Research Method:
The research method may referred to as other names such as methodology or
research strategy; the research methods are about the researchers approach to the
investigation and the methods chosen will be affected by different factors (Pickard,
2007). There are five main methods in experimental data collection: Experiment,
Archival Analysis, Survey, History, and Case Study. According to Yin (1994), three
issues will shape the research methods: the type of question being asked, whether the
41
research studies human behaviour for the long term or short term, and whether the
study deals with the past or present will all affect the methods used.
Table 3: Relevant Situation for Different Research Strategies
Strategy Form of
Research
Question
Regular Control
of Behavioural
Event
Focus on
Contemporary
Event
Experiment How, Why? Yes Yes
Survey Who, What,
Where, How
many, How
much?
No Yes
Archival
Analysis
Who, What,
Where, How
many How
much?
No Yes / No
History How, Why? No No
Case Study How, Why? No Yes
Source: Yin, 1994, Page 5
Based on these considerations, the researcher aims to identify the factors which have
influences on intention to use mobile banking. The researcher selected survey as the
most suitable method, since, this research is a short-term study and focuses on a
contemporary event and furthermore the question type is ―What‖ (See table 3 above).
3.2.1 Literature Review:
A literature review can be described as searching for knowledge and information
available in the specific area of the study often from different disciplines and
bringing it together (Pickard, 2007). The literature review is usually performed by
using primary and secondary sources. Secondary sources usually provides a general
knowledge about the area of study and when a researcher has gained the required
knowledge about area of study and once the problem of the study is isolated then
primary sources such as journal articles are used, based on the research salient
(Burns, 2000).
42
Selecting the right keywords for searching literature is important in order to avoid
useless information and unnecessary repetition (Pickard, 2007). In term of this
research, keywords such as m-commerce, adoption, mobile banking, UK, and
technology acceptance model were searched. In addition, different search engines for
example, Library eResources of Sheffield University, Google Scholar, Science
Direct, and JSTOR were used .
3.2.2 Survey:
A survey consists of gathering and analyzing information by asking questions of
individuals who are part of the population or the whole population (Pickard, 2007).
This research is both a descriptive and an explanatory survey. It is descriptive
because it describes the environments of subjects of survey and its explanatory
because it aims to define the causes and effects of identified factors on usage of
mobile-banking services.
3.2.3 Sampling:
Due to time and financial constraints the researcher is forced to use sampling, which
means selecting part of the population in order to accomplish the research (Pickard,
2007). Since the nature of this research is quantitative, probability sampling was
selected as appropriate method to gather data. Adopting probability sampling as
suitable method for providing statistical bases when surveying the wider population
is not feasible aides in generalizing the findings to a wider population (Pickard,
2007). Since conducting this survey in the entire UK is not possible due to time and
cost restrictions, students of Sheffield University were chosen as the sample.
Students represent a good sample of the population for the purposes of this research
since they are active users of mobile phones (Office for National Statistics, 2007)
and are also available for participating in such research in short period.
3.2.4 Data collection:
According to Yin (1994) there are six ways of collecting data: interview,
documentation, archival records, direct observation, participant observation, and
physical artefact. For the aim of this study UK banks‘ websites and News agencies‘
websites are used for gathering preliminary information. Furthermore, after
identifying the suitable research method based on identified research aim, the best
data collecting tools for fulfilling the goal must be identified (Bell, 1991). According
to Burns (2000) questionnaires are usually used for data gathering purposes.
43
Therefore, questionnaire identified as appropriate tool and five points scale of Likert
to measure the strength of the respondents‘ attitude are methods utilized for the
purposes of this research (Pickard, 2007). More precisely electronic questionnaire
was selected for gathering sample data because university students have regular
access to internet. Furthermore, in order to broaden the sample population printed
questionnaires were distributed among students at Information Common library, the
most active library at University of Sheffield during the summer.
3.2.4.1 Questionnaire:
The questionnaire was constructed based on the review of literature. Eleven
questionnaires were distributed among the students of university for pilot study. As
the result of pilot study, the questionnaire was modified and then distributed among
students for real data collection.
The modified questionnaire consists of seven parts. In part one, the demographic
information such as age, and gender were gathered. Part two measures the scale of
accessibility and ease of access to internet through mobile devices. Parts three
through seven question and measure perceived ease of use, perceived usefulness,
intention to use mobile banking, security and privacy and perceived enjoyment
respectively.
The questionnaire consists of two types of questions: Close-ended and Open-ended
(Giddens, 2001). Close ended questions have fix range of responses available, while
in the open ended questions the respondent have an opportunity to express their
views. This study consists of twenty four close-ended questions. As mentioned
before five point Likert scale was used in this questionnaire. In this scale, scores
range from ―1‖ for Very Low or Strongly Disagree, ―2‖ for Low or disagree, ―3‖ for
No Opinion or Neither agree nor disagree, ―4‖ for High or agree, and ―5‖ for Very
High or strongly agree.
3.2.4.1.1 Questionnaire structure:
Since this research is deductive in approach. The research questions are constructed
based on reviewing the research literature. As mentioned in the questionnaire section
factors of accessibility, demographic variable, perceived ease of use, perceived
usefulness, perceived enjoyment, perceived risk are deduced from an accepted and
44
popular model in USA, called TAM. Explanation of the above factors presented in
below:
3.2.4.1.1.1Technology acceptance model:
As mentioned before TAM was introduced by Davis in 1989. Davis identified two
elements; perceived ease of use (PEOU) and perceived usefulness (PU), as effective
factors, impacting peoples‘ behaviour when using information technology (IT).
Perceived Usefulness (PU): Defines the usefulness of a system as perceived by its
users and states that users will continue using the system until they no longer find
the system useful. Davis (1989) defined PU as ―the degree to which a person believes
that using a particular system would enhance his or her job performance‖. And
Perceived Ease of Use (PEOU): The PEOU is defined as ―the degree to which a
person believes that using a particular system would be free of effort‖.
Davis (1989) concluded that the perceived usefulness has a stronger relationship
with usage of computer technology than perceived ease of use. Furthermore, his
findings indicated that; a system‘s ease of use has an impact on the users‘ perception
of system‘s usefulness. During the last two decades, TAM has been recognized as a
well-structured, dominant, and economical tool for predicting users‘ acceptance of
Information System among researchers (Venkatesh and Davis, 2000). Many studies
performed to identify the effective factors impacting adoption of e-banking among
users have recognized TAM as a powerful tool for identifying users‘ intentions (
Gerrard et al., 2006; Jahangir and Noorjahan, 2007; Amin, 2007). Many researcher
identified PU and PEOU as significant factors impacting adoption of mobile-banking
(Luarn and Lin, 2005; Gu et al., 2009; Deng et al., 2010). Also, researchers identified
TAM as an effective factor on adoption of mobile banking (Liu et al., 2009; Gu et
al., 2009; Luarn and lin, 2005). Ease of use is an important element impacting the
use of internet through mobile phone because of smaller screen size and limitation on
the programs‘ size executable on mobile phones (Kim et al, 2007). Wei et al. (2009)
studied the factors impacting the intention to use m-commerce in Malaysia found
that PU has an influence on intention to use m-commerce. The finding of this
research is highly supported by past researchers who tested TAM in area of m-
commerce (Luarn and Lin, 2005; Lin and Wang, 2006; Lu et al., 2003; Khalifa and
Shen, 2008). Accessibility and instantaneous nature of m- commerce positively
influences the perceived usefulness and ease of use (Wei et al., 2009).
45
Kim et al. (2010) identified that PEOU and PU are factors that have positive
influence on intention to use mobile payment services.
3.2.4.1.1.2 Perceived ease of use and Perceived Usefulness:
As mentioned previously in part of the literature review about advantages and
shortcomings of mobile commerce; In this part, the researcher discuss about how
those feature influences perceived ease of use and perceived usefulness of mobile
banking.
According to Teo and Pok (2003) that using specific services such as browsing
websites through mobile phone is boring and at times challenging. Also, small
screen sizes and compacted keyboards can have an inverse influence on using
mobile devices for accessing services offered through such devices (Hill and
Troshani, 2009) because it is looks difficult to use. In addition other factors such as
clear and visible steps , user friendliness, clear commands, symbols, and layout
influence perceived ease of use and subsequently adoption as well (Condos et al.,
2002). The small screen size and compacted keyboards on mobile phones makes data
entry more challenging and therefore deters users of mobile phones to engage in
mobile banking unless no other banking methods are available (Hohel and Huff,
2009). Laukkanen (2005) studied and compared m-banking and internet-banking
systems and concluded that the small screen size of mobile phones can only display
limited amount of information, which in turn makes mobile phones not the ideal
devices for fund transfer.
Utilizing m- commerce requires less expertise than e-commerce since access to
internet and engaging in banking transactions can be perceived as more user friendly
than engaging in the same tasks on personal computers ( Philippe and Navarro, 2000;
Ropers, 2001). However, Green (2000), argues that low internet bandwidth , small
screen size and simple functionality of mobile devices prevent the design of
effective user interface for m-commerce. According to Carlsson and Walden (2002)
study in Finland, slow speed of services offered through mobile phone in addition to
limited size of mobile phone screen are major barriers of m-commerce diffusion.
Furthermore, Vrechopoulos et al. (2002) identified the list of critical factors that
have positive influences on extending mobile commerce penetration in Europe. The
study identified: high bandwidth and network coverage, improved mobile devices,
user-friendly applications and increased transaction security as critical factors
46
leading to success in m-commerce adoption. Kim et al. (2010) stated that having
knowledge about m-commerce influences perception of people about ease of use,
also accessibility and mobility of m-commerce increases the perceived usefulness of
the system. Among studies performed to identify the factors impacting usage of m-
commerce, Wong and Hiew (2005) suggested that an increase in perceived
usefulness of m- commerce sheds a positive light on usefulness of mobile devices
and brings to attention the ubiquitous nature of mobile devices, which offers freedom
of time and place.
3.2.4.1.1.3 Perceived risk:
The definition of perceived risk has evolved over time. In the past, perceived risk
was associated with product quality and consumers‘ acceptance of that product, but
with emergence of new technology which offers new commerce outlets the definition
of perceived risk has evolved.
The perception of risk in technology is associated with the uncertainty about the
capability of technology in delivering the expected outcome (Im et al., 2008).
Perceived risk includes financial, product performance , social , psychological, and
physical risk users face when engaging in an online transaction (Ben-Ur and
Winfield, 2000; Forsythe and Shi, 2003).The perceived risk in e-commerce and m-
commerce has a negative impact on users‘ perceptions of using self-service banking
technology. There are different types of risk associated with using e-banking
services. The main risks include operational risks, and misuse of technology by
users. In addition, there are legal, reputational, credit, market and strategic risk
associated with use of e-banking services which threaten users of e-banking services
(Rahman, 2009). The perceived risk is expected to effect the attitude, and opinion of
users about the perceived ease of use and the perceived usefulness of services (Rose
and Fogarty, 2006). When engaging in mobile commerce, trust which includes
perceived risk and information privacy is a definitive factor impacting the usage of
such services (Ba and Pavlou, 2002). Retrospectively, high trust in the system
translates into lower perception of risk and vice versa. Meanwhile doubts about
security and privacy of personal information negatively impacts m-commerce
adoption (Hill and Troshani, 2009). Security and privacy is not a new concern in the
field of m-commerce and has been established by past researchers (Pikkarainen et
al., 2004, Fang et al., 2005). Langendoerfer (2002) suggested that the main barriers
47
of m-commerce adoption could be found in psychological aspect of human
behaviour and that is privacy concerns of users of m-commerce. Luarn and Lin
(2005) claim that customers concerns about their information transferred to third
parties without their permission is one of the main worries in term of using m-
banking. It means that the issue of security and privacy are important elements which
have an impact on using m-banking. Wu and Wang (2005) stated that concerns about
security and privacy exist in both e- commerce and m- commerce which negatively
impacts customers attitude toward these commercial channels. Therefore, in this
research two elements of security and privacy are suggested for further research.
3.2.4.1.1.4 Perceived enjoyment:
PE is categorised as an intrinsic motivation which means users‘ perceived and actual
enjoyment of using certain technology is independent of the actual benefits that
technology offers. These users in turn then are more likely to adopt new technology
(Davis et al., 1989).
Perceived enjoyment (PE) is applied by different researchers to evaluate its impact
on new technologies adoption and concluded that PE has a positive impact on
adoption of new technology (Davis et al., 1992 ; Teo et al, 1999). PE combined with
TAM is considered a good combination in predicting utilization of new technologies,
such as m-commerce (Dabholkar, 1996; Moon and Kim, 2001; Bruner and Kumar,
2005). Dabholkar (1996) discovered that perceived enjoyment is a prominent
antecedent of self-service technology. Also Dai and Palvia (2009) findings indicates
that perceived enjoyment is an important factor for mobile commerce adoption in
US. PE is identified as an important motivator aspiring users (Anckar and D'Incau,
2002) to utilize new technology offered through mobile devices (Pura, 2005; Kim et
al., 2007).
3.2.4.1.1.5 Socio-demographic:
The customers‘ socio-demographic profile and background determines the type of
information and banking packages they request from banks (McKechnie et al., 2006).
New innovations always have some early and late adaptors with women and elderly
recognized as reluctant groups to use new technology (Morris and Venkatesh,
2000).After researching mobile banking in China, Laforet and Li (2005) concluded
that males and highly educated users are dominant users of mobile and online
banking services. The young generation is more likely to use self-service
48
technologies in banking sector because they value its convenience and time saving
properties (Howcroft et al, 2002). Furthermore, Karjaluoto et al. (2002) identifies
and concludes demographic factors as a viable consideration impacting on-line
banking behaviours of customers in Finland. Koivumaki et al. (2008) identified male
users to be dominant users of mobile services, accounting for 68.7 percent of
customers and also that the users of mobile services were relatively young. The users
skills and familiarity with the system being used also had a direct correlation with
perceived ease of use and usefulness of the system (Koivumaki et al., 2008). This
means that higher skilled users have higher perception of ease and usefulness of the
system. Wei et al. (2009) concluded that PEOU does not impact intentions to use m-
commerce in young generation. According to his study of age group 18-24, the
young generation is more apt in learning new technology and is not influenced by
PEOU when engaging in m-commerce.
3.2.4.1.1.6 Accessibility:
Access s means ease of approach or enter. Access to the right tools to achieve a
certain task is imperative in m-banking. Utilizing mobile banking requires access to
appropriate mobile phone, which is capable of accessing the internet. According to
Daniel (1999) one of the main barriers of using e-banking in the UK is not having
access to appropriate medium for performing task.
3.2.5 Data Analysis:
The collected data was analysed by SPSS software version 16. Also, all calculations
and statistical tests and graphs were created by SPSS and Excel software‘s. Identified
statistical test for this research are:
Frequency Test: to identify the distribution of the response to the questions
Mean comparison: to identify the impact of identified factors on intention to
use mobile banking services.
T-test: The tests identify factors that deduced from review of literature have
an impact on the intention to use mobile banking in the UK.
Correlation test: to identify level of dependency between identified factors.
Regression test: to identify the direct impact of identified factors on intention
to use mobile banking.
49
3.3 Reliability:
Peter (1979; p6) defined reliability as the degree the measures are free from any
error and produce static result. Reliability dictates whether or not the research can be
repeated with the same predictions and is a measure applied to quantitative research.
Coefficient alpha is used for testing of the internal consistency of questionnaire.
Cronbach introduced coefficient alpha in 1951. It was introduced as generalised
measure for measuring the internal consistency of multi item scale. The formula for
calculating coefficient alpha is stated below:
𝛼 = 𝑘
𝑘 − 1 1 − 𝜎𝑖
2
𝑘
𝑖=1
÷ 𝜎𝑠2
According to Peterson (1994) the acceptable values for coefficient alpha can vary
between 0.5 and 0.9 based on the type of the research. For example, in clinical
research high efficiently is exceedingly important and coefficient alpha of 0.9 and
above is required while in basic research the reliability score between 0.7 and 0.8 is
sufficient (Kaplan and Saccuzzo, 2008, p. 125).
The pilot test was performed among 11 mobile phone users in order to test the
reliability of the questionnaire. The Cronbach alpha was calculated and presented in
the table 4. The result of pilot study indicates that the questionnaire is reliable since
cronbach alpha for all variables is greater than .7 and according to Kaplan and
Saccuzzo (2008) for basic research the alpha number between 0.7 and 0.8 is
sufficient. The reliable questionnaire then was distributed among the population of
study and 140 valid questionnaires were collected. The reliability test for each factor
was calculated and presented in table 4.
50
Table 4: Cronbach's Alpha for each variable
Cronbach's Alpha N of Items
Perceived Enjoyment 0.772 2
Accessibility 0.704 2
Perceived Ease of Use 0.833 4
Perceived Usefulness 0.948 5
Perceived Risk 0.723 2
3.4 Ethical issue of the research:
This is a research study involving human behavioural patterns and by definition
requires a questionnaire for gathering population data. Based on research categories
this research is identified as non-invasive and low risk.
The ethical issues concerning this research are:
Informed consent:
The first page of the research questionnaire is allocated to informed consent,
which involves the following:
o Explaining the aims of doing such research.
o Explaining the use of gathered data.
o Explaining the research agreement to the respondents.
The respondents to the questionnaire will remain anonymous to protect their
privacy.
There is no coercion to force the respondents to fill the questionnaire.
51
Chapter 4: Findings
In chapter 4, after collecting data through a survey a data is analyzed using SPSS
software. Chapter four consists of three main parts. Part one is a descriptive analysis,
part two is data analysis and parts three includes managerial suggestions.
52
4.1 Descriptive Analysis:
There were 140 questionnaires collected from University of Sheffield student‘s
respondents. Table 5 presents the demographic characteristics of respondents.
Table 5: Demographic characteristics
Variables Classification of Variables Frequency Percentage
Gender
Male 79 56.4%
Female 61 43.6%
Age
Less than 20 5 3.6%
20-35 130 92.8%
36-50 5 3.6%
51-65 0 .0%
Education
Diploma 2 1.4%
BSc 26 18.6%
MSc 104 74.3%
Doctorate 8 5.7%
The demographic characteristics of the respondents show that 56.4 percent of the
respondents were male, and 92.8 percent of the respondents were age between 20 and
35. The respondents‘ educational background indicated that 75.5 percent of the
respondents were studying for master degrees; 18.6 for bachelor degrees and 5.7
percent were studying for doctorates. According to table 5, gender distribution of the
respondent is quite close to each other therefore the researcher could have equal
opinion for both groups. In addition, majority of the respondents were young and
since age group between 20 and 35 which are major users of IT. This can provide
valuable information for organisation such as banks who are providing mobile
banking services to their customers.
Question four of the questionnaire asked which mobile banking services the
respondents prefer to use through their mobile phones. Answers are shown in Figure
9:
53
Figure 9: Percentage of mobile banking services users prefer to use
The results of the bar chart above indicates that checking the account balance was the
most utilized option by the students, while transferring funds was the least utilized
service. However, the difference between utilization of fund transfer and bill
payment services was minimal 42.1 and 44.3 percent respectively.
Question 5 asked whether the respondents had heard about mobile banking services
and if so where from. Answers are presented in Figure 10:
Figure 10: Source of information of the respondent’s about mobile banking
services
70.7
42.1 44.3
0
10
20
30
40
50
60
70
80
Check Balance Transfer Money Pay Bill
48
19
2 0.7
26
0
10
20
30
40
50
60
Bank Website Bank Pamphlet
Tv. Advertisment
Newspaper No
Percentage
54
As can be concluded from the chart above, bank websites were the most prominent
tool (48%) for informing about mobile banking services, while bank pamphlets, TV
advertisements, and newspapers were in second, third, and fourth place by 19, 2 and
0.7 percent respectively. In addition, 26 percent of the respondents stated that they
had not heard about mobile banking until they completed the questionnaire. This
finding indicates that students were using website and internet more than any other
multimedia communication tools such as TV or newspaper. Therefore, bank website
is best communication medium between students and bank.
Access to mobile internet:
Questions 6 through 8 refer to accessibility to mobile internet through mobile phone.
The results are comprised and presented in the charts below:
Figure 11: Type of mobile phone of respondents
Of all the respondents to the questionnaires, 67.9 percent claimed that they had third
generation mobile phones, while 12.9 and 16.4 percent of the respondents were using
2.5 generation and 2 generation mobile phones respectively. In addition, 2.9 percent
of the respondents did not use mobile phones. As result of figure 11, 97.1 percent of
2.9
67.9
12.9
16.4
Mobile Phone
No
3G
2.5G
2G
55
students have mobile phone, which present the infrastructure for using mobile phone
for banking activities among students are available.
Figure 12 : Access to mobile internet
The 76.4 percent of the respondents reported that they accessed the internet through
their mobile phones. However, 76.4 percent is a considerable percentage for using
internet of mobile phone for connecting mobile banking website but the policy
should be set to provide better and easier access to the internet.
76.4
23
Access to Mobile Internet
Yes
No
56
4.2 Frequency analysis:
In this part, the frequency and distribution of answers to each question are calculated
and explained in separate tables.
4.2.1 Frequency analysis of Accessibility:
The access to mobile internet consists of two questions. The frequency for Q7 and
Q8 are presented in the tables below.
The answers to Q7, which asks about the difficulties of respondents to access the
internet through their mobile phones, is displayed in table 6.
Table 6: Frequency of respondent answers about Q7
Frequency Percent Valid Percent
Cumulative
Percent
Very Low 24 17.1 17.1 17.1
Low 31 22.1 22.1 39.3
No opinion 12 8.6 8.6 47.9
High 26 18.6 18.6 66.4
Very High 47 33.6 33.6 100.0
Total 140 100.0 100.0
As illustrated in the table above, when accessing the internet through their mobile
phones, 31 respondents experienced very little difficulty while 26 and 47 respondents
had high or very high levels of difficulty respectively. As result of table 6, more than
50 percent of respondents had difficulty in term of accessing to mobile internet
which can result in delay for using mobile banking. Therefore, it should provide
facilities such as cheaper and faster internet access for mobile phone to persuade
users to use these banking activities.
57
Frequency table for the question 8, which asks ―Did you have difficulty accessing
the internet through your mobile phone during last week?‖ is displayed in the table
below.
Table 7: Frequency of respondent answers about Q8
Frequency Percent Valid Percent
Cumulative
Percent
Very Low 8 5.7 5.7 5.7
Low 31 22.1 22.1 27.9
No Opinion 37 26.4 26.4 54.3
High 25 17.9 17.9 72.1
Very High 39 27.9 27.9 100.0
Total 140 100.0 100.0
As shown in the table above 27.9 percent of the respondents strongly agreed to the
Q8 however, 22.1 and 5.7 percent of the respondents disagreed and strongly
disagreed to the Q8 respectively.
4.2.2 Frequency analysis of perceived ease of use questions:
Four questions were presented to the respondents in order to fully realize mobile
banking‘s perceived ease of use by the respondents. This section focuses on
displaying and describing those answers presented in separate tables. Each table
contains information about frequency, percentage, valid percent and cumulative
percent.
Frequency table for the question 9 which states limited amount of information that
can possibly be displayed on mobile phones does not impact the respondents
perceived ease of use while mobile banking is presented in table 8.
58
Table 8: Frequency of respondent answers about Q9
Frequency Percent Valid Percent
Cumulative
Percent
Strongly Disagree 7 5.0 5.0 5.0
Disagree 40 28.6 28.6 33.6
Neither Agree nor Disagree 52 37.1 37.1 70.7
Agree 31 22.1 22.1 92.9
Strongly Agree 10 7.1 7.1 100.0
Total 140 100.0 100.0
According to the table above, 28.6 percent of respondents disagreed about the
possibility of displaying limited information through mobile phone not having an
impact on their perception of ease of use of the system, while only 22.1 percent
agreed and 7.1 percent strongly agreed.
Frequency table for the question ten which states ―The small screen size and
keyboard of mobile phones facilitate and enhance mobile banking experience.‖ is
presented in the table below.
Table 9: Frequency of respondent answers about Q10
Frequency Percent Valid Percent
Cumulative
Percent
Strongly Disagree 22 15.7 15.7 15.7
Disagree 49 35.0 35.0 50.7
Neither Agree nor Disagree 29 20.7 20.7 71.4
Agree 31 22.1 22.1 93.6
Strongly Agree 9 6.4 6.4 100.0
Total 140 100.0 100.0
59
Among the respondents, 35 percent found the small size of mobile phone screen and
keyboard inappropriate for mobile banking. Also, 15.7 percent strongly disagreed.
However, 22.1 and 6.4 percent of the respondents agreed and strongly agreed that the
mobile phone physical characteristics are suitable for mobile banking. Therefore,
small size of screen and keyboard defied as problematic by respondents for using
mobile phone for banking in near future. This issue requires a bank study about what
better design for mobile phone could be done to make it easy for using it for banking
activities.
Frequency table for the question 11, which asks is learning to use mobile banking
easy? is displayed in below.
Table 10: Frequency of respondent answers about Q11
Frequency Percent Valid Percent
Cumulative
Percent
Strongly Disagree 6 4.3 4.3 4.3
Disagree 13 9.3 9.3 13.6
Neither Agree nor Disagree 32 22.9 22.9 36.4
Agree 64 45.7 45.7 82.1
Strongly Agree 25 17.9 17.9 100.0
Total 140 100.0 100.0
The table above indicates that 45.7 percent of the respondents agreed that they can
easily learn to use mobile banking and 4.3 percent of respondents claimed that they
would have major difficulties in learning to use mobile banking. As result, there is
no special need for providing training session for those who are studying or being
educated in terms of how to use mobile banking.
60
Frequency table for the question 12, which states, ―The interface design of mobile
banking application has an influence on my perception about ease of use of the
system.‖, is illustrated in table below.
Table 11: Frequency of respondent answers about Q12
Frequency Percent Valid Percent
Cumulative
Percent
Strongly Disagree 4 2.9 2.9 2.9
Disagree 20 14.3 14.3 17.1
Neither Agree nor Disagree 41 29.3 29.3 46.4
Agree 51 36.4 36.4 82.9
Strongly Agree 24 17.1 17.1 100.0
Total 140 100.0 100.0
As illustrated in table 11, 36.4 percent of the respondents agreed with this statement
that interface design of mobile banking impacts the perceived ease of use while,
29.3 percent neither agreed nor disagreed. In addition, 14.3 and 2.9 percent selected
disagree and strongly disagree options. This indicates that interface design of mobile
banking website is important for respondents and the how to interface is well
designed for the perception of mobile phone users about the ease of using mobile
banking would increase.
61
4.2.3 Frequency analysis of perceived usefulness:
The perceived usefulness section consists of five questions. Table 12 presents the
frequency and percentage of the respondents‘ answers.
Table 12: Frequency of respondent answers of Q13 through Q17
Strongly
Disagree
Disagree Neither Agree
nor Disagree
Agree Strongly Agree
Freq Percent Freq Percent Freq Percent Freq Percent Freq Percent
Q13 11 7.9 20 14.3 16 11.4 71 50.7 22 15.7
Q14 9 6.4 19 13.6 18 12.9 72 51.4 22 15.7
Q15 8 5.7 14 10 12 8.6 77 55 29 20.7
Q16 10 7.1 18 12.9 22 15.7 67 47.9 23 16.4
Q17 7 5.0 12 8.6 37 26.4 64 45.7 20 14.3
The table above shows that 15.7 percent of the respondents strongly agreed with
questions 13 and 14 which states ― Use of mobile banking services would make my
banking tasks easier ― and ―Using mobile banking services would accomplish my
banking tasks more quickly‖. In response to question 13, 66.4 percent of the
respondents agreed or strongly agreed that mobile banking eases their banking
tasks, while only 22.2 percent of the respondents disagreed or strongly disagreed
with the same statement. Question 15 asks about the usefulness of mobile banking
accessibility with 55 and 20.7 percent of the respondents agreeing or strongly
agreeing with usefulness of this feature. Furthermore, 47.9 and 16.4 percent of the
respondents agreed and strongly agreed with the usefulness of mobile banking for
transferring money and checking balances. Finally, 45.7 percent of the respondents
agreed with the question 17, ―My information about m-banking would lead me to
find the system useful.‖ while in total 13.6 percent of the respondents strongly
disagreed and disagreed. Therefore, usefulness of mobile banking is an obvious
advantage of mobile banking among students and banks in order to increase the
number of users which should emphasise on its advertisement.
62
4.2.4 Frequency analysis of perceived risk:
Perceived risk section is comprised of three questions and their frequency and
percentage figures are presented in table 13:
Table 13: Frequency of respondent answers of Q20 through Q22
Strongly
Disagree
Disagree Neither Agree
nor Disagree
Agree Strongly
Agree
Freq Percent Freq Percent Freq Percent Freq Percent Freq Percent
Q20 10 7.1 42 30 26 18.6 48 34.3 14 10
Q21 11 7.9 48 34.3 24 17.1 41 29.3 16 11.4
Q22 0 0 5 3.6 39 27.9 66 47.1 30 21.4
10 and 34.3 percents of respondents strongly agreed and agreed with the question 20
which states ―I do not have complete trust in my mobile operator for doing mobile
banking‖ while 30 and 7.1 percent disagreed and strongly disagreed. Question 21
asks the respondents if mobile banking is a secure method of banking. Among the
respondents 11.4 percent strongly agreed and 29.3 percent agreed with mobile
banking to be a secure method of banking while 42.2 percent of the respondent
chose to disagree or strongly disagree. 68.5 percent of the respondents agreed or
strongly agreed with question 22 which states, ― The risk of an unauthorized third
party overseeing the payment process in mobile banking is high‖ , while only 3.6
percent selected to disagree . In conclusion, the risk of performing mobile banking
perceived high by respondents of the questionnaire that would have a negative
impact on future usage of mobile banking by mobile phone users. In order to
overcome the fear about fraud and stealing money bank should provide information
and security package to potential users.
4.2.5 Frequency analysis of perceived enjoyment:
The last two questions on the questionnaire are about perceived enjoyment. The
result of frequency analysis is presented in the table below.
The frequency table of question 23 which states, ―I would enjoy using mobile
banking services.‖ is presented in table 14.
63
Table 14: Frequency of respondent answers about Q23
Frequency Percent Valid Percent
Cumulative
Percent
Strongly Disagree 17 12.1 12.1 12.1
Disagree 24 17.1 17.1 29.3
Neither Agree nor Disagree 29 20.7 20.7 50.0
Agree 60 42.9 42.9 92.9
Strongly Agree 10 7.1 7.1 100.0
Total 140 100.0 100.0
As shown in the table above, 42.9 percent of the respondents agreed that they would
enjoy using mobile banking services and 20.7 percent of the respondents neither
agreed nor disagreed.
Also, the frequency analysis for the question 24, ― I would have lots of fun by
accessing the mobile banking page through my mobile phone device‖ presented in
table 15:
Table 15: Frequency of respondent answers about Q24
Frequency Percent Valid Percent
Cumulative
Percent
Strongly Disagree 8 5.7 5.7 5.7
Disagree 27 19.3 19.3 25.0
Neither Agree nor Disagree 43 30.7 30.7 55.7
Agree 43 30.7 30.7 86.4
Strongly Agree 19 13.6 13.6 100.0
Total 140 100.0 100.0
64
According to table 15, 30.7 percent of the respondents agreed and 19 percent
strongly agreed that they would enjoy accessing the mobile banking page through
their mobile phones, On the other hand, 30.7 percent of the respondents neither
agreed nor disagreed . To conclude access and perform mobile banking would
provide joy and fun for the students.
65
4.3 Mean Comparison:
In this part, the mean of the variables are studied. As mentioned before, the response
rate is from ―1‖ strongly disagree or very low to ―5‖ strongly agree or very high. As
the result, if the calculated mean is close to 5 that variable has a higher impact on
adoption of mobile banking and vice versa.
4.3.1 Accessibility:
Figure 13: Mean of accessibility questions
As the figure above shows ― Do you have access to internet through your mobile
phone? If yes, how difficult, is your access to the internet through your mobile
phone?‖ (Q7) had a lower mean score of 3.29 compared to Q8 ―Did you have
difficulty accessing to the internet through your mobile phone during last week‖ with
the mean score of 3.4. Overall, figure 5 presents that the students‘ use of mobile
internet is not high.
4.3.2 Perceived Ease of Use:
The questions 9-12 relate to perceived ease of use. The mean of variables are
calculated and depicted in the charts below.
3.29
3.4
3.22
3.24
3.26
3.28
3.3
3.32
3.34
3.36
3.38
3.4
3.42
Q7 Q8
Mean
66
Figure 14: Mean of perceived ease of use questions
The above chart represents the mean calculation to the respondents‘ responses to
questions 9-12. Question 9 with the mean of 2.98 asks the respondents if the limited
amount of information that can possibly be displayed has any impact on the
respondents‘ perception of ease of use of m-banking. Question 10 with the mean of
2.69 however asks the respondents if the small screen size and keyboards are easy to
use while m-banking. Questions 9 and 10 have lower means compared to question
11 and 12. Question 11, which asks if learning to mobile bank is easy for the
respondents has the highest mean of 3.64. Question 12 which states, ―The interface
design of mobile banking application has an influence on my perception about the
ease of use of the system‖, was in second place by the mean score of 3.51.
4.3.3 Perceived Usefulness:
This part is comprised of questions 13 through 17, which determine usefulness of
mobile banking. Similar to previous section, the mean of perceived usefulness is
calculated and presented in Figure 15.
2.98
2.69
3.643.51
0
0.5
1
1.5
2
2.5
3
3.5
4
Q9 Q10 Q11 Q12
Mean
67
Figure 15: Mean of perceived usefulness questions
As the chart above illustrates ―use of mobile banking services would make my
banking task easy‖ (Q13) and ―using mobile banking would increase my
effectiveness when transferring money or checking my balance‖ (Q16) had the
lowest mean scores of 3.52 and 3.53 respectively. In addition, ―using mobile banking
services would make me accomplish my banking tasks more quickly‖ (Q14) and
―My knowledge of m-banking would lead me to find the system more useful‖ (Q17)
had the same mean of 3.56. Question 15 which asks the respondents about their
perceived usefulness of mobile banking since accounts can be accessed from any
place had the highest mean of 3.75 .
3.52
3.56
3.75
3.53
3.56
3.4
3.45
3.5
3.55
3.6
3.65
3.7
3.75
3.8
Q13 Q14 Q15 Q16 Q17
Mean
68
4.3.4 Perceived risk (security and privacy):
Questions 20-22 relate to perceived risk, which concerns security and privacy in
mobile banking. The mean scores are calculated and illustrated in Figure 16
Figure 16: Mean of perceived risk questions
According to the bar chart above the mean score for lack of trust in the mobile
operator when engaging in banking activities (Q20), is 3.1. The mean for the
perception of respondents about the security of transactions in mobile banking (Q21),
is 3.02. Finally, the mean for ―the risk of an unauthorized third party overseeing the
payment process in mobile banking‖ (Q22), is 3.86.
4.3.5 Perceived Enjoyment:
The perceived enjoyment questions are comprised of questions 23 and 24. The
results are summarised and presented in Figure 17.
Figure 17: Mean of perceived enjoyment questions
3.1 3.02
3.86
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Q20 Q21 Q22
Mean
3.16
3.27
3.1
3.12
3.14
3.16
3.18
3.2
3.22
3.24
3.26
3.28
Q23 Q24
Mean
69
Figure 17 indicates that the mean score for Q23 ―I would enjoy using mobile banking
services‖ and Q24 ―I would have lots of fun by accessing to mobile banking page
through my mobile phone device‖ were 3.16 and 3.27 respectively.
4.4 Data Analysis:
4.4.1 T-test:
The common sample t-test is used in order to identify the impacts of five factors;
perceived ease of use, perceived usefulness, perceived risk, perceived enjoyment and
accessibility. According to literature review, these factors have a detrimental and
beneficial impacts on the intention of using mobile banking. However, these factors
are not studied in the UK. Therefore, T-test performed in order to test this are how
they impact the usage of mobile banking in the UK. The results are shown in the
following tables:
4.4.1.1 Perceived ease of use:
Table 16: One sample mean test of PEOU
N
Mean Std.
Deviation
Std. Error
Mean
T D.F T with α
= 0.01
Perceived
ease of
use
140
3.20
.688
.058
3.472
139
2.326
𝐻0 : Perceived ease of use has no impact on intention to use mobile banking.
𝐻1 : Perceived ease of use has impact on intention to use mobile banking.
In Statistical terms:
𝐻0 : µ1<= µ0
𝐻1 : µ1> µ0
70
As presented in table above, T is greater than Tα by 3.20. Therefore, 𝐻0 is rejected
and 𝐻1is approved with 99 percent confidence level. Therefore, an impact of
perceived ease of use on intention to use of mobile banking is approved in the UK.
4.4.1.2 Perceived usefulness:
Table 17: One sample mean test of PU
N
Mean Std.
Deviation
Std. Error
Mean
T D.F T with α
= 0.01
Perceived
usefulness
140
3.58
.961
.0812
7.214
139
2.326
𝐻0 : Perceived usefulness has no impact on intention to use mobile banking.
𝐻1 : Perceived usefulness has impact on intention to use mobile banking.
In Statistical terms:
𝐻0 : µ1<= µ0
𝐻1 : µ1> µ0
As illustrated in table 17, T, perceived usefulness, is 7.214 while Tα is equal to 2.326.
Therefore, given T >Tα it is concluded that 𝐻0 is rejected and 𝐻1is approved.
Therefore, the researcher should expect about an impact of perceived usefulness on
intention to use of mobile banking in the UK.
4.4.1.3 Perceived Risk:
Table 18: One sample mean test of PR
N
Mean Std.
Deviation
Std. Error
Mean
T D.F T with α =
0.01
Perceived
Risk
140
3.33
.794
.067
4.89
139
2.326
71
𝐻0 : Perceived Risk has no impact on intention to use mobile banking.
𝐻1 : Perceived Risk has impact on intention to use mobile banking.
In Statistical terms:
𝐻0 : µ1<= µ0
𝐻1 : µ1> µ0
As shown in table 18, T (4.89) is greater than Tα (2.326). Therefore, 𝐻0 ―Perceived
Risk has no impact on intention to use mobile banking‖ is rejected and 𝐻1is
accepted. Therefore, an influence of perceived risk on intention of using mobile
banking in the UK is approved.
4.4.1.4 Perceived Enjoyment:
Table 19: One sample mean test for PE
N
Mean Std.
Deviation
Std. Error
Mean
T D.F T with α =
0.01
Perceived
Enjoyment
140
3.214
.893
.075
2.836
139
2.326
𝐻0 : Perceived enjoyment has no impact on intention to use mobile banking.
𝐻1 : Perceived enjoyment has impact on intention to use mobile banking.
In Statistical terms:
𝐻0 : µ1<= µ0
𝐻1 : µ1> µ0
As presented in the table above T, 2.836, is greater than Tα , 2.326, therefore 𝐻1 is
approved. To conclude, an impact of perceived enjoyment on intention to use of
mobile banking is accepted.
72
4.4.1.5 Accessibility:
Table 20: One sample mean test of accessibility
N
Mean Std.
Deviation
Std. Error
Mean
T D.F T with α
= 0.01
Accessibility
140
3.31
1.24
.0105
3.31
139
2.326
𝐻0 : Accessibility to mobile internet has no impact on intention to use mobile
banking.
𝐻1 : Accessibility to mobile internet has impact on intention to use mobile banking.
In Statistical terms:
𝐻0 : µ1<= µ0
𝐻1 : µ1> µ0
As illustrated in table 20, T, 3.31, is greater than Tα 2.326, therefore 𝐻1 is approved.
This result indicated that the researcher should expect the accessibility issue would
have an impact on intention to use of mobile banking in the UK.
4.4.2 Regression test:
The regression test is performed in order to identify the impacts of perceived ease of
use, perceived usefulness, perceived risk, perceived enjoyment, gender, age, and
education as independent variables on dependent variable (intention to use mobile
banking). And also, test the linear relationship between other factors identified in the
research model which have direct linear relationships with each other. The results of
regression test presented in the tables below:
4.4.2.1 Regression test one:
The first regression test is to identify the linear relationship between eight factors of
perceived ease of use, perceived usefulness, perceived risk, perceived enjoyment,
accessibility, age, gender, and education on intention to use mobile banking.
73
Table 21: Model summery
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
1 .808a .652 .631 .71887
a. Predictors: (Constant), Enjoyment, Education, Gender ,
Accessibility, Ease of Use, Age ,Risk, Usefulness
In order to identify how suitable the suggested model is , R square needs to be noted.
Since R square 0.652, which means that 65.2 percent of observed behaviour of the
respondent‘s intention to use mobile phone for banking activities is defined by eight
independent variable of perceived ease of use, perceived usefulness, perceived risk,
demographic variable (Age, gender, and education), perceived enjoyment, and
accessibility. In addition, coefficient R represents the strength of the relationship
observed between independent variable and the value predicted on the regression
line. The value of coefficient R is always between zero and one. A value close to one
indicates the precision and reliability with which the value of dependent variable
from the independent variables can be predicted. But, if the value of R coefficient is
equal to zero then it means that there is no linear relationship between dependent and
independent variables. Therefore since the value of coefficient R (0.808) in this
research is close to one the current regression model can be used for predicting the
dependent and independent variables.
Table 22: ANOVA
Model Sum of
Squares df
Mean
Square F Sig.
1 Regression 126.902 8 15.863 30.695 .000
a
Residual 67.698 131 .517
Total 194.600 139
a. Predictors: (Constant), Enjoyment, Education, Gender, Accessibility, Ease of Use, Age ,
Risk, Usefulness
b. Dependent Variable: Intention to Use
74
The ANOVA table, presented above, tests the null hypothesis. The null hypothesis
assumes, while testing the population of the study, that there are no linear
relationships between dependent and independent variables. Therefore, the
regression F test is utilized to establish the existence or absence of any linear
relationship between intention to use mobile banking (Dependent variable) and
perceived ease of use, perceived usefulness, perceived risk, accessibility, perceived
enjoyment, and demographic variables (Independent variable). The calculated F in
ANOVA test is 30.695 and the significant values is less than 0.0005. Therefore, the
null hypothesis which denies the existence of any linear relationships between
dependent and independent variables is rejected and the researcher should have
expectation to observe the linear relationship between identified independent
variables ( for example: perceived ease of use, perceived risk) and dependent
variable ( Intention to use mobile banking) on Coefficient table.
As the coefficient table 23 illustrates, the sigma value for factor of perceived
usefulness is less than 0.005 and equal to 0 and R is equal to 0.532. This represents
the existence of a relationship between perceived usefulness and intention to use
mobile banking where standard derivation error is equal to 0.089. Therefore, it can
be concluded that increase in the perception of respondents about usefulness of
mobile banking amounts to 0.532 growths on intention to use mobile banking. The
sigma value for perceived enjoyment factor is 0 which is less than 0.05and its
standard regression coefficient is 0.25. This represents that perceived enjoyment has
a positive influence on intention to use mobile banking. In addition, the sigma value
for perceived risk is 0.047, which is less than 0.05 and the standard coefficient is
-0.124. This represents that perceived risk has a negative impact on the intention to
use mobile banking. The linear relationship between the other variable is not
supported since calculated sigma value is equal or greater than 0.1.
75
Table 23: Coefficients a of Test One
Model Unstandardized
Coefficients
Standardized
Coefficients
t
Sig. B
Std.
Error
Beta
1 (Constant) .816 .764 1.068 .287
Gender .004 .128 .002 .031 .975
Age -.051 .247 -.012 -.208 .835
Education -.141 .123 -.063 -1.144 .255
Access -.008 .052 -.009 -.160 .873
Ease of Use .097 .102 .057 .958 .340
Usefulness .655 .089 .532 7.323 .000
Risk -.185 .092 -.124 -2.008 .047
Enjoyment .331 .085 .250 3.909 .000
a. Dependent Variable: intention to Use
4.4.2.2 Regression tests two:
The second regression is calculated in order to identify the existence or absence of
any linear relationship between four variables of perceived ease of use, accessibility,
perceived enjoyment, and perceived risk (independent variables) on perceived
usefulness (dependent variable) of mobile banking.
The R square value is 0.491, and the coefficient R is 0.701. The null hypothesis is
rejected in ANOVA test because the F value is 32.578 and also its significant is
0.000. Therefore, it proves the existence of relationships between dependent and
independent variables (Regression model summery and ANOVA tables presented in
Appendix 2).
As it is shown in table 24, the significant value for perceived ease of use is less than
0.05 and its standard coefficient is equal to .287, which means that perceived ease of
use has an influence on perceived usefulness of the mobile banking system. In
addition, the significant value for perceived enjoyment is equal to .000, proving it to
be significant and R is equal to .366, which means increase in perceived enjoyment
76
of the mobile banking system only 36.6 percent increases perceived usefulness of
mobile banking . The significant value for accessibility is equal to .429 which is
greater than 0.09 therefore it is not significant and R is equal to .051. Also, the
significant value of perceived risk is .000 and its standard coefficient -.328 show that
there is a linear relationship between perceived usefulness and perceived risk. In
conclusion, it is established that there is no linear relationship between accessibility
and perceived usefulness of mobile banking. Therefore, perceived risk has a negative
influence on perceived usefulness of mobile banking and if concern of mobile phone
users about security of mobile banking increase leads to decline of users perception
about usefulness of system while two factors of perceived ease of use and perceived
enjoyment have positive influence on perception of usefulness of mobile banking.
Table 24: Coefficients a of Test two
Model Unstandardized
Coefficients
Standardized
Coefficients
t
Sig. B
Std.
Error
Beta
1 (Constant) 2.228 .518 4.299 .000
Ease of Use .401 .091 .287 4.412 .000
Risk -.397 .080 -.328 -4.939 .000
Enjoyment .393 .074 .366 5.334 .000
Access .039 .049 .051 .793 .429
a. Dependent Variable: Usefulness
4.4.2.3 Regressions test three:
The R square for 3rd
regression test which establishes the existence or absence of
relationship between perceived enjoyment (dependent variable) and perceived ease
of use (independent variable) is equal to .093 and R is equal to .305. The calculated
R square (.093), represents that only 9.3 percent of observed behaviour in perceived
enjoyment of mobile banking is defined by variable of perceived usefulness. The
calculated F in ANOVA test is equal to 14.166 and the value of its significant is.000.
Therefore, null hypothesis is rejected and the linear relationship between dependent
77
and independent variable is established (Regression model summery and ANOVA
tables presented in Appendix 3).
Table 25: Coefficients a of Test three
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig. B Std. Error Beta
1 (Constant) 1.944 .345 5.636 .000
Ease of Use .397 .105 .305 3.764 .000
a. Dependent Variable: Enjoyment
The factor of perceived ease of use has Sigma value of .05< and standard regression
coefficient of .305 which determines that perceived ease of use has positive influence
on the Use of mobile Banking. Therefore, as long as use of mobile banking system
has been easy for users then users will enjoy using of the system.
4.4.3 Correlation test:
The correlation test is performed in order to identify any dependencies between
different variables. The relationships between variables are categorised as strong,
moderate, weak, and no relationship. The correlation value is between -1 and
+1.Calculated correlation figures close to +1 shows that there are positive and strong
correlations between two variables and vice versa. Also, if calculated correlation
figures are close to 0 it means that there is no significant correlation between two
variables. The level of significance is quite important in the correlation test, the
minimum acceptable level of significant for business and management studies is 0.05
(Maylor et al., 2005). Therefore, levels of significant greater than 0.05 mean that it
is not significant and there is no correlation between two variables.
The correlation test is done between the factors identified and suggested as
influential on intention to use mobile banking in the literature review and the result
of correlation test is presented in table 26. In the correlation table, the factors of
perceived ease of use, perceived usefulness, perceived risk, accessibility and
perceived enjoyment are identified as influential on intention to use mobile banking.
Furthermore, the correlation table illustrated that gender, accessibility, ease of use,
usefulness and perceived risk have an influence on perceived enjoyment. In addition,
age, accessibility, ease of use, and usefulness are identified as influential factors on
78
perceived risk. Also, the variables of accessibility and ease of use are identified as
having correlations with factors of ease of use and usefulness respectively.
79
Table 26: Correlation
Gender Age Education Accessibility Ease of Use Usefulness
Risk Enjoyment
Intention
to Use
Gender Pearson Correlation 1.000
Sig. (2-tailed)
N 140.0
Age Pearson Correlation .162 1.000
Sig. (2-tailed) .056
N 140 140.0
Education Pearson Correlation -.011 .306
** 1.000
Sig. (2-tailed) .894 .000
N 140 140 140.000
Accessibility Pearson Correlation .022 .022 -.114 1.000
Sig. (2-tailed) .798 .800 .178
N 140 140 140 140.000
Ease of Use Pearson Correlation -.154 -.049 -.051 -.180* 1.000
Sig. (2-tailed) .070 .567 .551 .034
N 140 140 140 140 140.000
Usefulness Pearson Correlation -.125 -.134 -.033 -.145 .451**
1.000
Sig. (2-tailed) .140 .114 .699 .087 .000
N 140 140 140 140 140 140.000
Risk Pearson Correlation .157 .192* .079 .199
* -.186
* -.501
** 1.000
Sig. (2-tailed) .064 .023 .356 .018 .028 .000
N 140 140 140 140 140 140 140.000
Enjoyment Pearson Correlation -.179* -.030 .003 -.215
* .305
** .559
** -.355
** 1.000
Sig. (2-tailed) .034 .725 .969 .011 .000 .000 .000
N 140 140 140 140 140 140 140 140.000
Intention to
Use
Pearson Correlation -.139 -.136 -.095 -.168* .401
** .764
** -.498
** .610
** 1.000
Sig. (2-tailed) .101 .109 .266 .048 .000 .000 .000 .000
N 140 140 140 140 140 140 140 140 140.000
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
80
4.5 Discussion:
The aim of this study is to identify the factors impacting the intention of mobile
phone users to adopt mobile banking services. Eight factors of perceived ease of use,
perceived usefulness, perceived enjoyment, perceived risk, accessibility and
demographic factors of education, age, and gender are studied in order to find out
their influences on intention to adopt mobile banking services. Since, there is no
study performed in the UK to identify what factors have an impact on adoption of
mobile banking, this study can be considered as a pioneering research in this area.
4.5.1 Findings:
In order to better analyse and establish the significance of respondents‘ answers the
values of strongly agree and agree are combined and considered as agree with similar
calculation for strongly disagree and disagree. More than 50 percent of the
respondents claimed that small size of screen and keyboard of mobile phones
negatively influences their ease of use of mobile phones for banking activities
which is supported by Kim et al. (2007), Hill and Troshani (2009) , Hohel and Huff
(2009) and Laukkanen (2005) research. 63.6 percent of the respondents answered
that learning to use mobile banking is easy for them which positively influences and
increases the perceived ease of use which supports studies of Philippe and Navarro
(2000) and Ropers (2001). According to 53.5 percent of the respondent, the interface
design of mobile banking application has an influence on perception of ease of use of
the system. This finding is supported by study of Kim et al. (2007), Hill and
Troshani (2009), Hohel and Huff (2009), Laukkanen (2005), Condos et al. (2002),
and Green (2000).
The usefulness of mobile banking which is emphasized by banks‘ advertisements and
marketing has the highest agreement percentage by the respondents in comparison to
other questions . The possibility of access to bank accounts at any place as a useful
characteristic of mobile banking has the highest agreement of 75.5. This finding is
similar to study of Wei et al. (2009) and Wong and Hiew (2005) about m-commerce
application because accessibility to services at any place seems as useful.
In addition, 68.5 percent of the respondents stated that they worry about their
transaction being overseen by an unauthorised third party.
81
Hill and Troshani (2009) also emphasized that concerns about overseen transactions
is one of factors acting as a barrier to adoption of mobile services among young
population in Australia.
44.3 percent of the respondent claimed that accessing mobile banking page through
mobile phone is enjoyable which support the statement of Pura (2005) and Kim et
al. (2007). While 25 percent of the respondent found mobile banking to be boring
and dull which supports Teo and Pok (2003) statement that claims access to m-
banking website and doing transactions through mobile phones are quite boring.
Furthermore, The findings of this study establishes that perceived ease of use,
perceived enjoyment, perceived usefulness, perceived risk, and accessibility have
influences on intention to use mobile banking which is supported by past studies
explained in literature review. According to the correlation test, perceived ease of use
(40.1 %), perceived usefulness (76.4%), perceived enjoyment (61.0 %), have positive
influences on intention of mobile phone users to use mobile banking services.
However, perceived Risk (-49.8%), and accessibility (-16.8 %) is identified as having
negative influences on intention to use mobile banking. Influences of the other
variables on intention to use mobile banking are not supported since their results are
not statistically significant. Also, the factors of perceived ease of use (45.1%),
perceived risk (-50.1%) and perceived enjoyment (55.9%) are identified as
influential on perceived usefulness of mobile banking. According to correlation
table, accessibility (-18%), perceived risk (-18. 6%), and perceived enjoyment
(30.5%) have impacts on perceived ease of use of mobile banking system. The
variables of perceived risk (-35.5%) and accessibility (-21.5%) have negative
influences on perceived enjoyment of mobile banking. Finally, accessibility (19.9%)
has an influence on perceived risks of mobile banking.
Moreover, the result of regression test were that perceived enjoyment (B=.250),
perceived usefulness (B=0.532) and perceived risk (B=-0.124) have linear
relationships with the intention to use mobile banking. These variables completely
explain 65.2% of the variance on the intention to uses mobile banking (𝑅2=65.2
coefficient of determination). This part of research finding is totally supported by
past researches that illustrates the direct influence of perceived risk (Wu and Wang,
2005; Laukkanen and Cruz, 2009; Wessels and Drennan, 2009; Dai and Palvia
82
,2009), perceived usefulness (Wu and Wang,2005; Hill and Troshani,2009; Wessels
and Drennan,2009; Dai and Palvia,2009), perceived enjoyment (Hill and
Troshani,2009; Dai and Palvia,2009) on intention to use mobile banking by a
customers. The result of regression test indicates that as the value of perceived risk
increases the intention to use mobile banking declines. In addition, it can be conclude
that as long as perceived usefulness and perceived enjoyment is emphasise and
marketed effectively by industry the level of intention to use mobile banking
increases. The regression table indicates that there is a linear relationship between
perceived risk and intention to use mobile banking, which means, if the levels of
security and privacy in mobile banking increases the intention of mobile phone users
to engage in mobile banking will increase. In addition, perceived ease of use
(B=.287), perceived risk (-.328) and perceived enjoyment with beta value of .355 and
significant value of 0 have influences on perceived usefulness of mobile banking.
However, the significant value calculated for accessibility was 0.429 which renders
this variable insignificant and does not support the relationship between accessibility
and perceived usefulness of mobile banking. This finding of the research approved
by other researchers study, suggest that perceived risk (Rose and Fogarty,2006; Gu et
al, 2009), perceived enjoyment (Liao et al., 2007) and perceived ease of use (Wu and
Wang, 2005; Gu et al.,2009; Liu et al.,2009) have a direct influence on perceived
usefulness of m-commerce. Finally, direct impact of perceived ease of use with a
Beta value of .305 on perceived enjoyment of mobile banking is supported as Cyr et
al. (2006) and Liao et al. (2007) indicated in their studies in Canada and Taiwan. The
direct relationship between perceived ease of use and intention to use mobile banking
is not supported as was concluded by Wei et al. (2009) research since the research
subjects were mainly young.
83
The result of hypothesis analysis is presented in the table below.
Table 27 : Result of Hypothesis Test
Hypothesis Effect Path
coefficient
T-statistic Remark
H1 PEOU→ Use MB .057 .958 Not Supported
H2 PU→ Use MB .532 7.323 Supported
H3 PR→ Use MB -.124 -2.008 Supported
H4 PE→ Use MB .250 3.909 Supported
H5 Gender→ Use MB .002 .031 Not Supported
H6 Age→ Use MB -.012 -.208 Not Supported
H7 Education→ Use IB -.063 -1.144 Not Supported
H8 Accessibility→ Use IB -.009 -.160 Not Supported
H9 PEOU→ PU .287 4.412 Supported
H10 PR→ PU -.328 -4.939 Supported
H11 PE→ PU .366 5.334 Supported
H12 Access→ PU .051 .793 Not Supported
H13 PEOU→ PE .305 3.764 Supported
Given the results of the above table, the model under study concludes which factors
have direct influence on intention to use mobile banking in the UK. This is also
presented in the Figure below:
Figure 18: Approved model
Intention to use
mobile banking
Perceived
Usefulness
Perceived
Enjoyment
Perceived Ease
of Use
Perceived Risk
84
Based on the demographic variables the distribution of gender of the respondents is
close to each other with 56.1 percent male and 43.9 percent female. The majority of
respondents were studying for Master degrees (75.5 %) and 92.8 percent of the
respondents were between the ages of 25 and 36.
Among the services banks offered through mobile banking, checking balance was the
most popular service among respondents with 70.7 percent while the rest of services:
transfer money, pay bill, had the percentage less than 50 with 42.1, 44.3 percent
respectively.
Among the respondents 80.8 percent had 3G and 2.5G mobile phones which can
access the internet. However, only 76.4 percent of respondents had access to the
internet through their mobile phones. Also, banks‘ websites were the most effective
informative tool in educating the customers about their mobile services with 48
percent followed by banks‘ pamphlet with 19 percent.
4.6 Managerial suggestion:
The result of study indicates that small size of screen and keyboard of mobile
phones has negative influence on perception of mobile phone users.
Therefore, it is suggested that banks provide loans for buying mobile phones
which has wider mobile screen for example iPhone mobile phones for its
customers since the screen of iPhone is bigger than ordinary mobile phones. .
It is also suggested for banks to in research and introduce more user friendly
interface design for mobile banking applications.
Since the possibility of accessing bank accounts at any place and time is the
main draw and attraction of mobile banking, compared to e-banking services,
it is suggested that bank should market and advertise this feature to their
advantage.
The study indicates that security of mobile banking has a negative impact on
perceived usefulness and intention to use of mobile banking. To overcome
this negative image, banks have to first educate their customers about the
safety of mobile banking transactions and also research and introduce
85
innovative software‘s to better combat inadequate security and privacy in
mobile banking.
Since, majority of respondents claimed that they had become aware of mobile
banking services through banks‘ websites, therefore it is suggested that banks
utilize their websites more effectively to educate and minimize the
customers‘ concerns about the security and safety of mobile banking.
86
Chapter 5: Conclusion
Chapter 5 consists of the research conclusion and discusses the research aims,
research findings, the limitation and suggestion for further research. In addition, the
lessons learned are discussed.
87
5.1 Conclusion:
Mobile banking is the newest service offered by British and worldwide banks to their
customers. Since there is no research performed on the factors influencing the
adoption of mobile banking among British customer, this study can be considered as
pioneering research uncovering these influential factors and their influences and aid
banks in attracting more mobile banking‘s customers. Based on reviewing the
literature six main factors of perceived ease of use, perceived usefulness, perceived
enjoyment, perceived risk, accessibility and demographic factors( age, education,
gender) are identified and their impacts on intention to use mobile banking are
studied by using survey methodology.
Since distributing the questionnaires to the whole population of UK was not possible
due cost and time constrain, the population sample was limited to the students of
university of Sheffield. The questionnaires, consisting of six factors under study,
were distributed among the students via e-mail and printed format. The researcher
answered to all of the research questions which defined in chapter 1. The research
result indicates that three out of six factors perceived risk, perceived usefulness, and
perceived enjoyment have direct impacts on intention to use mobile banking. Based
on the study‘s results, perceived risk, perceived enjoyment, and perceived ease of use
have direct impacts on perceived usefulness of mobile banking. In addition, direct
impact of perceived ease of use on perceived enjoyment is proven. Therefore,
according to research findings perceived risk has a negative influence on perceived
usefulness and intention to use mobile banking. This means that when perception of
mobile phone users regarding the security and privacy would increase and leads to
decline on perceived usefulness and the intention of mobile phone users. Therefore,
banks should put all their efforts to decline the perception about risk of mobile
banking which are; unauthorized access to customer information, invade privacy of
customer, and finally steeling money of mobile banking users. In addition, an
influence of perceived ease of use on perceived usefulness and perceived enjoyment
of mobile banking is approved. Therefore, finding a solution for declining a negative
influence of small size of mobile phone screen and keyboard which are identified as
problematic by respondents should be consider as first priority for all banks. In
addition, better interface design for mobile banking website must be researched by
all banks. Mobile banking interface is considered as only tools for communication
88
between banks and mobile phone users and if it is not well designed it leads to
difficulties for users which have negative impact on ease of use of mobile banking
services. Also, difficulty in using of mobile banking identified as having negative
impact on perception of mobile phone users in term of joy and fun for banking
activities.
Furthermore, according to research findings the joy and fun of using mobile banking
services has a positive influence on perceived usefulness and intention to use of
mobile banking. Moreover, bank website is identified as appropriate communication
medium between students and banks. Low usage and difficulties in term of accessing
to mobile internet is observed as another shortcoming that requires the banks to find
best solutions as soon as possible to provide required infrastructure for using m-
commerce services.
5.2 Lessons learned:
The way of effective searching for information and how to find relevant data
for a literature review.
The researcher learned how to design a research model.
The researcher learned how to design a well -structured questionnaire and
how to ask appropriate questions to receive better responses from the research
population.
The use of SPSS software and applying different statistical tests such as
regression and T-test are learned.
5.3 Limitations:
The limitations of this research are:
The sample population of study is limited to only the student of university of
the Sheffield.
89
The respondents to the questionnaire were mostly post graduate students
since post grads are the main available students during summer term.
Undoubtedly, if the sample population had included broader spectrum of
education levels the results would have better represented the general public.
The other limitation of this research is that all of the respondents to the
questionnaire are educated people, which do not represent the whole
population of the UK.
5.4 Further research:
In this research only TAM model is used to find out the factors impacting
adoption of mobile banking while, there are other models such as UTAT,
IDT that can be considered for further study in this area.
The study of the factors such as culture, trust, and politics are suggested for
future research on adoption of mobile banking.
Word Count: 20407
90
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Appendix 1 :
Dear Student
This research aims to find out the effective factors that have an impact on intention to
use mobile banking in the UK. Since your valuable opinion leads to a better banking
service, please fill this questionnaire with accuracy. All the information is
categorised as confidential, and it will only used in term of this research.
Thank you for taking your time to answer this questionnaire
Demographic Information
Q1. Gender:
Female Male
Q2. Age:
Less than
20
20-35 35-50 50-65 More than
65
Q3. In which degree you
are studying:
Diploma BSc MSc Doctorate
Q4. Which of the following Mobile Banking services do you prefer to use through your mobile
phone ?
Check Balance:
Yes No
Transfer
Money:
Yes No
Bill Pay:
Yes No
107
Q5. Have you heard about Mobile Banking Services? If yes, from where?
Yes No Newspaper TV
advertisement
Bank
website
Bank
pamphlet
Other
website
General Information about Use Mobile Phone and Accessibility
Q6. Do you have
Mobile? If yes,
which generation
of mobile phone
do you have?
Yes No 3G 2.5G 2G 1G
Q7. Do you have
access to internet
through your
mobile phone? If
yes, how difficult
is your access to
the internet
through your
mobile phone?
Yes No Very
Low
Low No
Opinion
High Very
High
Q8. Did you have
difficulty
accessing the
internet through
your mobile phone
during last week?
Very Low Low No
Opinion
High Very
High
108
Perceived Ease of Use
Q9. Although the amount of
information is possible to
display through mobile phone is
limited . It would have no
impact on my perception of ease
for using of the mobile banking
system.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Q10. The small screen size and
keyboard of mobile phones
facilitate and enhance mobile
banking experience.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Q11. Learning to use mobile
banking is easy for me.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Q12. The interface design of
mobile banking application has
an influence on my perception
about ease of use of the system.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Perceived Usefulness
Q13. Use of Mobile
Banking service would
make my banking tasks
easier.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
109
Q14. Using Mobile
banking services would
accomplish my
banking tasks more
quickly.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Q15. I would find
Mobile Banking useful
because I can have
access to my account at
any place.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Q16. Using Mobile
Banking would
increase my
effectiveness when
transferring money or
checking my balances.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Q17. My information about M-banking would lead me to find system as useful.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Intention to Use
Q18. If, I had access
to mobile banking
systems, I will use
them.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Q19. I intend to
increase my use of
mobile banking in the
future.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
110
Perceived Risk
Q20. I do not have
complete trust in my
mobile operator for
doing mobile banking.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Q21. I would not find
mobile banking
services secure in
conducting my
transactions.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Q22. The risk of an
unauthorized third
party overseeing the
payment process in
mobile banking is high
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Perceived Enjoyment
Q23. I would enjoy
using mobile banking
services.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
Q24. I would have lot
of fun by accessing to
mobile banking page
through my mobile
phone device.
Strongly
Disagree
Disagree Neither Agree nor
Disagree
Agree Strongly Agree
111
Appendix 2:
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
1 .632a .399 .386 .75281
a. Predictors: (Constant), Accessibility, Ease of Use,
Enjoyment
ANOVAb
Model
Sum of
Squares df Mean Square F Sig.
1 Regression 51.218 3 17.073 30.125 .000a
Residual 77.074 136 .567
Total 128.291 139
a. Predictors: (Constant), Accessibility, Ease of Use, Enjoyment
b. Dependent Variable: Usefulness
112
Appendix 3:
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
1 .305a .093 .087 .85436
a. Predictors: (Constant), Ease of Use
ANOVAb
Model
Sum of
Squares df Mean Square F Sig.
1 Regression 10.340 1 10.340 14.166 .000a
Residual 100.731 138 .730
Total 111.071 139
a. Predictors: (Constant), Ease of Use
b. Dependent Variable: Enjoyment