a comparison study of online shopping behaviours of nigerian
TRANSCRIPT
A COMPARISON STUDY OF ONLINE SHOPPING BEHAVIOURS
OF NIGERIAN STUDENTS IN SHEFFIELD AND NIGERIA
A Study submitted in partial fulfilment
of the requirements for the degree of
Master of Science in Information Systems Management
at
THE UNIVERSITY OF SHEFFIELD
by
ALLEY, VIVIAN M.
September 2010
2
ABSTRACT
Background. The literature reveals the different levels of e-commerce adoption and use
globally and in Nigeria. It also reveals online shopping trends in the UK and Nigeria.
Previous surveys have all indicated a low level of e-commerce adoption and use in
Nigeria in comparison with other countries like the UK.
Aims. The study aimed to compare online shopping behaviours of Nigerian PGT
students in Sheffield and Nigeria, and to examine if factors identified in previous
research were responsible for any changes that might exist.
Methods. A questionnaire was developed based on instruments used in previous
studies, and the research model developed in this study, and was distributed manually to
the target population of PGT Nigerian students in the University of Sheffield. There
was a response rate of 74% from the total number of Nigerian PGT students (99
students).
Results. A large percentage (79.2%) of respondents was familiar with e-commerce
while in Nigeria, however, only a fraction (34.7%) used it. While in Sheffield,
respondents reported 100% familiarity with e-commerce with over 80% being active e-
commerce users. In terms of online shopping, less than 10% of respondents shopped
online while in Nigeria, but over 80% shopped online in Sheffield. Statistical tests were
used to examine changes in online shopping behaviours and determine factors
responsible for these changes. Factors responsible for lack of use of e-commerce for
online shopping in Nigeria were identified as trust and personal constraints. Factors that
encouraged respondents to shop online in Sheffield were also identified as trust and
consumers‟ perceptions of technology. Accessibility to the Internet was also
emphasised as a key factor contributing to respondents‟ e-commerce and online
shopping in both countries.
Conclusions. It is concluded that online shopping behaviours of Nigerian PGT
students in the University of Sheffield have significantly improved in comparison with
when they were in Nigeria. However, a more extensive survey with a larger sample
group from different universities in the UK would be desirable and could involve a
more detailed analysis of results employing more statistical tests to identify factors
responsible for changes in online shopping behaviours due to change in environment.
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ACKNOWLEDGEMENT
I would first like to thank God Almighty for His guidance throughout the course of my
study.
Secondly, I would like to thank my supervisor, Angela Lin, for all the support she
provided during this research and for the consideration given me when I was ill.
I would also like to thank all the participants of this research who took time to complete
the questionnaire and assist in the dissertation.
Finally, I would like to acknowledge my parents, Emmanuel & Joan Alley; my siblings,
Steven, Josephine, Michael, and John; and Gennaro Avolio for their love and support
during the entire duration of my course, especially the research time.
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TABLE OF CONTENTS
ABSTRACT ...................................................................................................................... 2
ACKNOWLEDGEMENT ................................................................................................ 3
TABLE OF CONTENTS ................................................................................................. 4
CHAPTER 1: INTRODUCTION ..................................................................................... 8
1.1 INTRODUCTION ............................................................................................. 8
1.2 BACKGROUND AND MOTIVATION OF RESEARCH ............................. 8
1.2.1 E-commerce development globally ........................................................... 9
1.2.2 E-commerce development in Nigeria ...................................................... 10
1.3 GAP IN PREVIOUS RESEARCH ................................................................. 11
1.4 RESEARCH AIMS ......................................................................................... 12
1.5 RESEARCH OBJECTIVES............................................................................ 12
1.6 STRUCTURE OF THE DISSERTATION ..................................................... 13
1.7 SUMMARY ..................................................................................................... 14
CHAPTER 2: LITERATURE REVIEW ....................................................................... 15
2.1 INTRODUCTION ........................................................................................... 15
2.2 E-COMMERCE ............................................................................................... 15
2.2.1 Development of B2C e-commerce .......................................................... 15
2.3 ONLINE SHOPPING TRENDS ..................................................................... 17
2.3.1 Online Shopping Trends in the UK ......................................................... 18
2.3.2 Online Shopping Trends in Nigeria ......................................................... 18
2.4 TRUST IN ONLINE SHOPPING .................................................................. 21
2.4.1 Definition of trust in online shopping ...................................................... 22
2.5 SUMMARY ..................................................................................................... 23
CHAPTER 3: METHODOLOGY .................................................................................. 24
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3.1 INTRODUCTION ........................................................................................... 24
3.2 RESEARCH MODEL ..................................................................................... 24
3.2.1 Trust and Technology Acceptance Model (TAM) .................................. 24
3.2.1.1 TAM.................................................................................................. 24
3.2.1.2 The Modified TAM for e-commerce ............................................... 26
3.2.2 Research Model ........................................................................................ 26
3.3 RESEARCH METHODOLOGY .................................................................... 28
3.3.1 Inductive and Deductive Approaches ...................................................... 28
3.3.2 Qualitative and Quantitative Approaches ................................................ 28
3.4 RESEARCH APPROACH .............................................................................. 29
3.5 SAMPLING PROCESS .................................................................................. 30
3.6 QUESTIONNAIRE DESIGN ......................................................................... 31
3.7 ETHICAL ISSUES .......................................................................................... 34
3.8 SUMMARY ..................................................................................................... 34
CHAPTER 4: DATA PRESENTATION AND ANALYSIS ........................................ 36
4.1 INTRODUCTION ........................................................................................... 36
4.2 SECTION A: PERSONAL INFORMATION ................................................ 36
4.2.1 Gender Composition ................................................................................ 36
4.2.2 Duration of stay in Sheffield .................................................................... 37
4.2.3 Previous Work Experience ....................................................................... 37
4.3 SECTION B: RELATED QUESTIONS......................................................... 38
4.3.1 Internet Usage ........................................................................................... 38
4.3.2 E-commerce in Nigeria ............................................................................ 40
4.3.2.1 E-commerce Familiarity ................................................................... 40
4.3.2.2 E-commerce and Online Shopping Behaviours in Nigeria .............. 41
4.3.2 E-commerce in Sheffield .......................................................................... 46
4.3.2.1 E-commerce and Online Shopping Behaviours in Sheffield ........... 46
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4.4 SECTION C: EFFECT OF VARIABLES ON CONSUMERS‟ ACTUAL
USAGE OF ONLINE SHOPPING ............................................................................ 54
4.4.1 Perceived Usefulness................................................................................ 54
4.4.2 Perceived Ease of Use .............................................................................. 56
4.4.3 Intention to Use ........................................................................................ 58
4.4.4 Trust .......................................................................................................... 62
4.5 SUMMARY ..................................................................................................... 67
CHAPTER 5: DISCUSSION ..................................................................................... 69
5.1 INTRODUCTION ........................................................................................... 69
5.2 ONLINE SHOPPING BEHAVIOURS .......................................................... 69
5.2.1 Online Shopping Behaviours in Nigeria .................................................. 69
5.2.2 Online Shopping Behaviours in Sheffield ............................................... 70
5.3 FACTORS RESPONSIBLE FOR CHANGE................................................. 70
5.3.1 Trust Concerns of Consumers .................................................................. 70
5.3.1.1 Privacy and Confidentiality .............................................................. 70
5.3.1.2 Authenticity of Products ................................................................... 71
5.3.1.3 Data security and Credit card threat ................................................. 71
5.3.1.4 Trust in online vendors ..................................................................... 72
5.3.2 Consumers‟ Perceptions of Technology .................................................. 72
5.3.2.1 Perceived Usefulness and Perceived Ease of Use ............................ 73
5.3.2.2 Accessibility...................................................................................... 73
5.3.2.3 Network Reliability .......................................................................... 74
5.4 SUMMARY ..................................................................................................... 75
CHAPTER 6: CONCLUSION ................................................................................... 76
6.1 INTRODUCTION ........................................................................................... 76
6.2 AIM AND OBJECTIVES ............................................................................... 76
6.2 CONCLUSIONS ............................................................................................. 77
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6.2.1 Main Findings of Research ...................................................................... 77
6.2.2 Relationship of Research to the Literature ............................................... 78
6.3 LIMITATIONS ................................................................................................ 79
6.3.1 Sampling ................................................................................................... 79
6.3.2 Data Collection Process ........................................................................... 80
6.3.3 Data Analysis ........................................................................................... 80
6.4 RECOMMENDATIONS ................................................................................ 80
6.4.1 Suggestions for Further Research ............................................................ 81
6.5 SUMMARY ..................................................................................................... 81
BIBLIOGRAPHY ........................................................................................................... 83
APPENDIX I: QUESTIONNAIRE ................................................................................ 91
APPENDIX II: CORRELATION MATRIX 1…….…………………..……….…......97
APPENDIX III: TOTAL VARIANCE EXPLAINED 1………………………….......98
APPENDIX IV: CORRELATION MATRIX 2…….…………………………...........99
APPENDIX V: TOTAL VARIANCE EXPLAINED 2……….………………….....101
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CHAPTER 1: INTRODUCTION
1.1 INTRODUCTION
This chapter presents an overview of the research and gives details of issues addressed.
Firstly, the background and motivation for carrying out this research is introduced with
a brief description of e-commerce development globally and in Nigeria. Secondly, the
gap in previous research is explained. Thirdly, the research aims and objectives are
clearly stated and finally, the structure of the dissertation is presented.
1.2 BACKGROUND AND MOTIVATION OF RESEARCH
The exchange of goods and services between parties has existed in different forms for
centuries and has also evolved over time to meet the needs of individuals and
technological advancements. Electronic commerce (E-commerce) is one of the products
of these changes and developments and has changed the way in which business is
transacted. Ghosh (1997:1) states:
“E-commerce provides consumers the ability to bank, invest, purchase,
distribute, communicate, explore, and research from virtually anywhere an
Internet connection can be obtained”.
Previous literature show different approaches to defining Electronic commerce (e-
commerce) by researchers. Zwass (1996:3) defines e-commerce as “sharing business
information, maintaining business relationships, and conducting business transactions
by means of telecommunications networks”. Kalakota and Whinston (1997:3) define e-
commerce in four different perspectives:
From a communications perspective, e-commerce is the delivery of
information, products/services, or payments via telephone lines, computer
networks, or any other means.
From a business process perspective, e-commerce is the application of
technology toward the automation of business transactions and workflows
From a service perspective, e-commerce is a tool that addresses the desires of
firms, consumers, and management to cut service costs while improving the
quality of goods and increasing the speed of service delivery.
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From an online perspective, e-commerce provides the capability of buying
and selling products and information on the Internet and other online
services.
Laudon and Laudon (2006:9) define e-commerce as,
“a process of buying and selling goods electronically with computerized
business transactions using the Internet, networks, and other digital
technologies. It also encompasses activities supporting those market
transactions, such as advertising, marketing, customer support, deliver, and
payment”.
Barsauskas et al. (2008:72) define e-commerce within the aspect of business processes,
as “the use of electronic networks with the objective to simplify and fasten all phases of
business processes – from the production of goods to their sale and delivery”.
From definitions available in literature, it can be observed that e-commerce involves
different processes depending on the context of use (Applegate et al., 1996; Riggins and
Rhee, 1998). However for the purpose of this study, e-commerce is defined simply as
“the use of the global Internet for purchase and sale of goods and services, including
services and support after the sale” (Treese and Stewart, 1998:5). This definition
amongst others emphasizes its use in the context of online shopping (buying and/or
selling) in the form of Business to Customer (B2C) e-commerce, which refers to,
transactions between businesses and consumers. With continuous improvements in ICT
and more people adopting its usage globally, e-commerce has also experienced a surge
in growth and acceptance as a means of transacting business effectively. Studies show
that, although the Business to Business (B2B) e-commerce has witnessed the most
significant growth rate compared to other types, B2C e-commerce is growing and
gaining popularity among Internet users globally (Jackson et al., 2003).
1.2.1 E-commerce development globally
A survey carried out in 2008 by the National Statistics Office, reveals that Internet sales
in the UK rose to £222.9bn, indicating an increase of 36.6% from the 2007 figure of
£163.2bn. These statistics show the growth rate of e-commerce in the UK and is a
reflection of the global trend. According to The Nielsen Company (2008), more than
85% of the world's Internet users surveyed shop online. This popularity and global
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acceptance of E-commerce have been attributed to the many benefits associated with it.
Benefits to customers include; a vast array of products to choose from, convenient
means of shopping online, fast and effective delivery of banking services, price
comparison opportunities, and accessibility to large volumes of product information
amongst others (Tassabehji, 2003). Benefits to businesses also abound and include;
opportunities for businesses of different scales and sizes to transact at a reduced cost on
a common ground and without geographical boundaries (Barsauskas et al., 2008;
Laudon and Laudon, 2009). E-commerce also enables a convenient and quick means to
set up a business from the comfort of one‟s home with access to large numbers of
potential customers (i.e. internet users). These advantages and many more have
encouraged both businesses and customers to adopt the use of e-commerce globally.
1.2.2 E-commerce development in Nigeria
Despite the global popularity and growth of e-commerce, developing countries like
Nigeria, seem to be lagging behind. As a developing country, ICT is growing gradually
in Nigeria, with Internet users making up 16.1% of the total population (Internet World
Stats, 2009). This shows a considerable increase compared to users in 2006 (3.1% of
total population). With more people becoming computer literate and open to adopting
ICT usage, e-commerce is gradually gaining popularity among many Nigerians.
However, previous studies have shown that e-commerce has not been fully adopted in
the country. A study by Folorunso et al. (2006:2226) shows that 70% of the respondents
surveyed had heard about e-commerce before, but only 32% had used it. This shows
that, only a very small percentage of the sample surveyed actually used e-commerce
(about 22%) and is evident in most researches done on e-commerce adoption in
Nigeria. In order to understand reasons behind the low percentage of e-commerce users,
Ajayi et al. (2008:6) identify common e-commerce activities among users in Nigeria as
products browsing (74%), products selection (56%), online payment (15%), offline
payment (82%), checking results online (43%). From these percentages it is obvious
that though consumers were interested in shopping online (by browsing online and
selecting products), only a handful were actually making online payments (Ajayi et al.,
2008). This low level of adoption of e-commerce in Nigeria has been attributed to
various factors by previous researchers.
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Folorunso et al. (2006:2224) identifies factors affecting the adoption of e-commerce in
Nigeria as “establishing cost, accessibility, privacy and confidentiality, data security,
network reliability, credit card threat, authenticity, citizen‟s income and education”.
Data security and citizen‟s income were concluded to be the major factors impeding the
adoption of e-commerce in Nigeria. Ayo (2006:2) also identifies the issue of cyber-
crime as a major factor responsible for the low level of e-commerce implementation in
Nigeria. Ayo et al. (2008:2) state that “Internet penetration is still abysmally low and is
one of the major threats to e-commerce implementation” in the country. Other factors
identified in previous studies include substandard online payment methods, lack of trust
in web retailers, poor technological infrastructures, and fear of inadequate security in
online environments (Adeyeye, 2008; Ajayi et al. 2008; Ayo et al., 2008; Adeshina and
Ayo, 2010).
It is however, noteworthy to state that although these factors exist, one aspect of
e-commerce that has been widely accepted by the Nigerian population is the use of
e-banking and payment systems. Nigerians engage in online banking (money transfers
between accounts, obtaining bank statements, paying bills such as electricity, water, etc)
because it offers quicker and more convenient delivery of banking services to customers
as opposed to physical banking. However, these customers are exposed to various
forms of cyber crimes when transacting online (Egwali, 2009). In addition to
substandard payment methods and insecurity, the growth of e-commerce activities such
as Internet banking in Nigeria has been inhibited by insufficient telecommunication
facilities and erratic electric supply (Ayo et al., 2008:4).
All these factors mentioned, discourage most people from fully adopting and using e-
commerce, thereby hindering the development of e-commerce in Nigeria. These factors
can also be considered to be environmental factors that influence people studied in that
particular environment (Nigeria).
1.3 GAP IN PREVIOUS RESEARCH
Although there have been previous studies on the adoption and development of ICT and
e-commerce in Nigeria, little research has been done on the adoption of e-commerce in
Nigeria for online shopping purposes. Ayo (2006) carried out a study on the assessment
of the prospects of e-commerce implementation in Nigeria, and the level of
participation of major companies and citizens. Another study by Folorunso et al. (2006)
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investigating factors affecting the adoption of e-commerce in Nigeria, suggested that
data security and citizens‟ income were the two major factors. Ajayi et al (2008) carried
out a study on online shopping in Nigeria to analyse online shopping experiences of
consumers. These studies and others mentioned afore were carried out in Nigeria, and
the sample populations were randomly chosen within specific locations in the country
with emphasis on e-commerce generally.
It is expected that a change in environment will influence certain habits and behaviours
in people (Bandura‟s Social Cognitive Theory, 1989). Bandura (1989:2) stipulates:
“Social cognitive theory favours a model of causation involving triadic reciprocal
determinism. In this model of reciprocal causation, behaviour, cognition and other
personal factors, and environmental influences all operate as interacting determinants
that influence each other bidirectionally”.
These influences could either be positive or negative, and this study attempts to identify
those changes. With little or no previous study on e-commerce adoption by Nigerians
living abroad, the focus of this research is to determine if a change in environment will
lead to a change in online shopping patterns of Nigerian Post Graduate Taught (PGT)
students currently studying in Sheffield. This group has been selected because they
represent an educated workforce of the Nigerian population. The study builds on
previous research on Nigeria‟s e-commerce adoption, and the outcome of this study will
give a clear picture of what improvements need to done by all stakeholders to increase
e-commerce usage in Nigeria.
1.4 RESEARCH AIMS
This dissertation aims to compare online shopping behaviours of Nigerian PGT students
in Sheffield and Nigeria, and to examine if factors identified in previous research are
responsible for any changes that might exist.
1.5 RESEARCH OBJECTIVES
In order to satisfy the research aim, a series of explicit objectives has been developed as
follows:
To investigate if Nigerian PGT students are familiar with e-commerce and
what they use it for;
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To examine the extent to which they engage in online shopping while in
Sheffield compared with when they were in Nigeria;
To identify similarities and/or differences in their online shopping behaviours
in both countries;
To investigate why these similarities and/or differences exist;
To make recommendations based on the findings of the empirical research.
1.6 STRUCTURE OF THE DISSERTATION
This study is made up of six chapters as discussed below;
Chapter 1 (Introduction): This chapter introduces the background of the research and
the motivation for carrying out this research with a brief description of e-commerce
development globally and in Nigeria. Secondly, the gap in previous research is
explained to justify the need for carrying out this research. Thirdly, the research aims
and objectives are clearly stated and finally, the structure of the dissertation is
presented.
Chapter 2 (Literature Review): This chapter reviews literature on e-commerce, online
shopping trends, trust and the Technology Acceptance Model (TAM). This provides
background knowledge for the research and is drawn from books and recent journals on
e-commerce and online shopping trends.
The development of B2C e-commerce is discussed briefly. Online shopping trends
globally, in the UK, and Nigeria are analysed and inhibiting factors affecting online
shopping in Nigeria are identified. The chapter then addresses the issue of trust in
online shopping and explores existing literatures on TAM and the modified TAM
model for e-commerce.
Chapter 3 (Methodology): This chapter introduces the research model which is based
on previous literature. The research methodology and research approach are discussed
in detail to justify the choice of methods used in this study. The sampling process is also
presented in detail to support the sample size used. The chapter concludes with a design
of the questionnaire and ethical issues are finally addressed.
Chapter 4 (Data Presentation and Analysis): This chapter presents and analyses data
collected through questionnaires from the sample group. Statistical techniques are used
to analyse the data collected to determine changes in online shopping behaviours and
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factors responsible for these changes. The results are presented in the form of graphs
and charts and findings are explained to give a better understanding of the analysis.
Chapter 5 (Discussion): This chapter discusses findings and results obtained from the
data analyses carried out in the previous chapter. The discussions draw on the literature
reviewed in Chapter 2 to support the validity of findings.
Chapter 6 (Conclusion): This chapter presents and evaluates the level of achievement
of the aims and objectives of the study. The main findings of the research and
relationship of research to the literature are discussed. Limitations of the research are
also identified and, recommendations are proposed. Finally, suggestions for further
research are made.
1.7 SUMMARY
This chapter introduced the background and motivation for carrying out this research
with a brief description of e-commerce development globally and in Nigeria. The gap in
previous research was explained, and the research aims and objectives were clearly
stated. Finally, the structure of the dissertation was presented.
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CHAPTER 2: LITERATURE REVIEW
2.1 INTRODUCTION
This chapter reviews literature on e-commerce, online shopping trends, trust and the
Technology Acceptance Model (TAM).
The development of B2C e-commerce is discussed briefly. Online shopping trends
globally, in the UK and Nigeria are analysed and inhibiting factors affecting online
shopping in Nigeria are identified. The chapter then addresses the issue of trust in
online shopping..
2.2 E-COMMERCE
The advantages, changes and benefits associated with technological advancements are
innumerable and the advent of the Internet has brought about social, economic, political
changes, to say the least. One of the most notable changes associated with ICT
advancements is the way business is transacted. The Internet as a tool has bridged gaps
in the financial sector between customers and businesses today. Though traditional
commerce (face-to-face transactions) has not been completely phased out in many
settings, electronic commerce is gaining momentous popularity among internet users
globally as a convenient and quick way of transacting business. Hence, it is important to
understand the concept of e-commerce to appreciate its adoption.
2.2.1 Development of B2C e-commerce
E-commerce has evolved rapidly to meet the needs of today‟s highly competitive and
fast paced market and this can be attributed to improvements and advancements in
technology (Barsauskas et al., 2008). This rapid growth rate has been attributed to “the
unique nature of the Internet and the Web” (Laudon and Laudon, 2009:300). The Table
2.1 below shows the features of e-commerce technology that are responsible for this
growth.
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E-commerce Technology Dimension Business Significance
Ubiquity. Internet/Web technology is
available everywhere: at work, at home, and
elsewhere via mobile devices, anytime.
The marketplace is extended beyond
traditional boundaries and is removed from
a temporal and geographical location.
“Marketspace” created; shopping can take
place anywhere. Customer convenience is
enhanced, and shopping costs are reduced.
Global Reach. The technology reaches
across national boundaries, around the Earth.
Commerce is enabled across cultural and
national boundaries seamlessly and without
modification. The marketspace includes,
potentially, billions of consumers and
millions of business worldwide.
Universal Standards. There is one set of
technology standards, namely Internet
standards.
There is one set of technical standards
across the globe so that disparate computer
systems can easily communicate with each
other.
Richness. Video, audio, and text messages
are possible.
Video, audio, and text marketing messages
are integrated into a single marketing
message and consumer experience.
Interactivity. The technology works through
interaction with the user.
Consumers are engaged in a dialog that
dynamically adjusts the experience to the
individual, and makes the consumer a co-
participant in the process of delivering
goods to the market.
Information Density. The technology
reduces information costs and raises quality.
Information processing, storage, and
communication costs drop dramatically,
whereas currency, accuracy, and timeliness
improve greatly. Information becomes
plentiful, cheap, and more accurate.
Personalisation/Customisation. The
technology allows personalised messages to
be delivered to individuals as well as groups.
Personalisation of marketing messages and
customisation of products and services are
based on individual characteristics.
Social Technology. The technology
promotes user content generation and social
networking.
New Internet social and business models
enable user content creation and
distribution, and support social networks.
Table 2.1 Unique Features of E-commerce Technology (Laudon and Laudon,
2009:302)
Although B2B e-commerce has experienced the most significant growth rate compared
to other types (Jackson et al., 2003; Laudon and Laudon, 2007), B2C e-commerce has
grown in the past few years, gaining popularity among Internet users and with many
benefits to businesses and consumers. Tassabehji (2003) identifies some of the benefits
of B2C e-commerce to consumers to include; cheap product choices, price comparison
opportunities and improved delivery processes, amongst others. B2C e-commerce
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include activities such as banking, online shopping, marketing and online advertising,
stock brokerage (Zwass, 1996). For the purpose of this study, emphasis is placed on
B2C e-commerce online shopping behaviours of Nigerians outside their home country.
2.3 ONLINE SHOPPING TRENDS
Online shopping involves searching for products and service information and the actual
buying and selling of products and/or services online. The Internet has made online
shopping not only a possibility but also a huge success contributing to economies
around the globe. A survey carried out in 2009 on world internet usage and population
statistics reveals that 26.6% of the total world population are internet users, showing a
growth rate of 399.3% in the last decade (Internet World Stats, 2009). With the number
of internet users on the increase globally, it is little wonder that the number of online
shoppers have increased greatly over the past few years. A 2008 global survey
conducted by The Nielsen Company on trends in online shopping reveals that over 85%
of the world‟s internet users have ever made a purchase over the Internet. This
percentage shows an increase of 40% from the number of online shoppers two years
ago (2006), with more than half of internet users being regular online shoppers, making
online purchases at least once a month (Nielsen, 2008). It was also discovered that the
country with the highest number of online shoppers was South Korea (99% of Internet
users have shopped online), while Egypt had the least number of online shoppers (67%
of internet users have never made a purchase online). The most frequent online
shoppers in the world also come from South Korea (79% of internet users have shopped
online in a span of one month) and the least frequent online shoppers come from
Philippines (59% of online shoppers have not made a purchase in the span of 3 months)
(Nielsen, 2008).
These trends and figures show that although online shopping is gaining popularity and
growing exponentially across the globe, this growth is not uniform. Some countries are
quick to adopt and use the Internet for their commercial activities (e.g. South Korea,
UK, USA, France, Ireland, Germany, etc), while others are slow adopters and would
rather carry out business the traditional way (e.g. Egypt, Pakistan. Philippines,
Argentina, etc).
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2.3.1 Online Shopping Trends in the UK
Online shopping trends in the UK are quite similar to South Korea. The Nielsen
Company survey (2008) reveals that 97% of Internet users in the UK have made
purchases over the Internet with 82% of them being frequent online shoppers (i.e. have
shopped within a period of one month). A recent survey carried out in 2009 by the
National Statistics Office, reveals an increase in internet users in the UK by 10.3 % (3.5
million adults) from 2008. It was also discovered that 94% of internet users accessed
the Internet from their homes and 6% via a wireless hotspot. This increase in internet
users in the UK and ease of access has contributed to the increase in frequent online
shoppers (National Statistics Office, 2009). In addition to ease of access; structured
online payment systems through the use of debit cards, credit cards, and other means;
innumerable online vendors; have also contributed to the adoption of online shopping in
the UK.
2.3.2 Online Shopping Trends in Nigeria
With e-commerce being at an early stage in most third world countries of the world,
online shopping trend in Nigeria is not as advanced as it is in the UK and other
developed countries. Although, the people engage in online banking (e-banking), most
people are still not open to the idea of shopping online and prefer to carry out their
transactions traditionally, i.e. face-to-face. Previous researches on the slow adoption of
e-commerce and online shopping have identified various contributing factors
(Folorunso, 2006; Adeyeye, 2008; Ajayi, 2008; Ayo, 2008; Egwali, 2009; Adeshina
and Ayo, 2010). One of such factors is accessibility to the Internet. A recent study on
internet usage in the UK reveals that 82.5% of the total population (62,348,447 people)
are internet users and 29.4% (18,354,000 people) are broadband subscribers (Internet
World Stats, 2010). This ease of access to the Internet has been identified as one of the
factors encouraging the adoption and growth of e-commerce and online shopping in the
UK (Soopramanien and Robertson, 2007).
In contrast, majority of the Nigerian population do not have access to the Internet. A
recent study on internet usage in Nigeria reveals that about 16.1% of the total
population (149,229,090 people) are internet users and less than 1% of the populace
(i.e. 67,800 people) are broadband internet subscribers (Internet World Stats, 2009).
From these percentages, it is evident that only a fraction of the population uses the
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Internet and even those who access it do so through numerous cybercafés scattered all
over urban parts of the country (Ayo, 2006). “Cybercafés are places where Internet
public access services are provided by entrepreneurs for a fee” (Adomi et al. 2003:489)
and are quite popular among Nigerians because of the high cost of connectivity by
individuals. However, due to the public nature of these cybercafés, people are not
comfortable carrying out e-commerce activities there for privacy, security and network
reliability issues, and this negatively affects online shopping trends in the country
(Adeshina and Ayo, 2010).
Another factor affecting the use of e-commerce for online shopping in Nigeria “is the
lack of a nationally acceptable payment method for online goods and services” (Ajayi et
al. 2008). Ayo et al. (2008:4) suggest that the low level of e-Payment infrastructure in
the country, serves as a hindrance to public participation in e-commerce. From previous
researches carried out on e-payment in Nigeria, it is evident that the Automated Teller
Machine (ATM ) is the most prominent method of payment in Nigeria (Adekunle and
Tella, 2008; Adeyeye, 2008; Ayo et al. 2008; Adeshina and Ayo, 2010). Most
individuals have at least one bank ATM (cash) card because they find it to be a
convenient means of banking without having to queue up in banks for cash. However,
Ayo et al. (2008:2) states that though the use of the ATM is widely accepted
nationwide, “it is only a means for making local payments and not for e-commerce
services” such as online shopping and this has a negative effect on online shopping in
Nigeria.
Adeyeye (2008:1) also identifies another crucial factor affecting online shopping in
Nigeria to be the shortage of indigenous online vendors. Most people who shop online
do so from foreign online vendors like Amazon and EBay because there are very few
credible online vendors in Nigeria. However, shopping from these foreign vendors can
be discouraging due to high shipping costs and most orders not being processed.
Nigeria has had a negative reputation for years as one of the world‟s most corrupt
countries engaging in wide scale Internet fraud. A recent survey by the Internet Crime
Complaint Center (IC3) ranks Nigeria third in the world with 8.0% of perpetrators of
cyber crime living in Nigeria after the US (65.4%) and UK (9.9%) (Internet Crime
Complaint Center, 2009). This percentage when compared with the total population of
Nigerians (i.e. over 140 million people) poses a considerable threat to the Internet
20
world. Hence, most online vendors are wary when dealing with orders from Nigeria for
fear of fraud.
It was also observed that, the few online vendors that exist do not have a “structured
way of presenting information (product categories) to users and beside, they offered
little assistance in helping customers find appropriate products” (Ajayi, 2008:7). This
makes it difficult for customers to use their websites for online shopping purposes and
this could be the reason why most Nigerian companies with online presence had
minimal commercial activities taking place (Ayo et al., 2008:4).
It is therefore not surprising that only a fraction of the Nigerian populace engage in
online shopping. A recent study by Adeyeye shows that only 16% of the sample
surveyed shop online and the most popular payment methods used in Nigeria were the
prepaid card system and direct payment to vendors‟ accounts (Adeyeye, 2008:5).The
prepaid card system involves buying a card to use for online purposes like checking
examination results, buying airtime or renewing subscription to services; while some
online vendors require direct payment into their bank accounts for purchases made
online (confirmation of payment is also required before orders are fully processed).
However, this method can prove frustrating and slow as customers have to make
physical payments in banks. There were also a few people (about 25% of the sample
surveyed) who owned credit cards and mostly shopped online from foreign vendors as
discussed above (Adeyeye, 2008:5). Although these offline payment systems (prepaid
card system and direct payment) may not be entirely appropriate and convenient for
online shopping, most online shoppers in Nigeria are prepared to pay for products and
services purchased on the Internet and the prepaid card systems seems to be the most
accepted means of payment for purchases done online with 65% of sample surveyed
preferring it to other payment methods (Adeyeye, 2008:5). This is due to the perceived
minimal risk associated with buying the cards for online purposes.
However, due to poor internet access, lack of structured e-payment systems, few online
vendors often requiring offline payments, and other factors affecting online shopping in
Nigeria, only a fraction of the Nigerian populace engage in online shopping. Most
people would rather engage in face-to-face transactions than go through these troubles
associated with online shopping.
21
2.4 TRUST IN ONLINE SHOPPING
The importance of trust in human interactions cannot be overemphasised and there have
been numerous researches on the concept of trust. As a result, trust has varying
definitions depending on the context of use and fields of application. Mayer et al.
(1995:726) simply define trust as a “willingness to be vulnerable to another party”.
Gefen (2000:726) describes trust in a broader sense as “the confidence a person has in
his or her favourable expectations of what other people will do, based, in many cases,
on previous interactions”. Gefen et al. (2003:54) define trust as “one's belief that the
other party will behave in a dependable, ethical, and socially appropriate manner”.
Pavlou (2003: 106) also describes trust “as the belief that the other party will behave in
a socially responsible manner, and, by so doing, will fulfil the trusting party‟s
expectations without taking advantage of its vulnerabilities”. From these definitions of
trust (among others), it can be deduced that trust is vital for interaction and relationship
building between parties involved.
It has also been argued that some degree of trust is essential in environments perceived
to be risky, however minimal (McKnight and Chervany, 2002; Pavlou, 2003;
Schoorman et al. 2007; Hernandez et al. 2009). McKnight and Chervany (2002:36)
state that “trust is central to interpersonal and commercial relationships because it is
crucial wherever risk, uncertainty, or interdependence exist”. The Internet is one of such
environments due to its shifting and somewhat unpredictable nature. In face-to-face
transactions, customers build trust based on physical interactions and human
mannerisms of vendors. People are less likely to make purchases from individuals
perceived to be dubious, even on a first time basis. However, online customers do not
enjoy such benefits of human interaction and can only base their perceptions on
vendors‟ websites. Hence, the need for trust in online environments is as important (or
more important) as it is in physical interactions. To this effect, the significance of trust
as a contributing factor of consumer acceptance and use of onlineshopping has been
studied by many researchers (Jarvenpaa et al., 2000; McKnight et al., 2002; Gefen et
al., 2003b; Pavlou, 2003; Su et al., 2009 etc). McKnight et al. (2002:335) state that
“trust is important because it helps consumers overcome perceptions of uncertainty and
risk and engage in “trust-related behaviours” with Web-based vendors, such as sharing
personal information or making purchases”. Gefen et al. (2003b:307) also suggest that
“trust is crucial in an online environment because of the greater ease with which online
22
customers, compared with bricks-and-mortar store customers, can be taken advantage
of in an online environment, even without their knowledge”.
Previous studies have investigated the reasons why people engage in online shopping
and identified various contributing factors aside trust. A study by Monsuwe et al.
(2004:119), shows that “attitudes toward online shopping and intention to shop online
are not only affected by ease of use, usefulness, and enjoyment, but also by exogenous
factors like consumer traits, situational factors, product characteristics, previous online
shopping experiences, and trust in online shopping”. Dennis et al. (2008:1123) in a
recent study on e-consumer behaviour, also link image (in terms of product selection,
fulfilment, and customer service), emotional states, social factors and learning to
attitudes and intention to shop online. However, much emphasis has been placed on
trust in e-commerce and online shopping because of the reasons suggested earlier.
Pavlou (2003:102) states that “the importance of trust is elevated in e-commerce
because of the high degree of uncertainty and risk present in most on-line transactions”.
2.4.1 Definition of trust in online shopping
Pavlou (2003:106) defines trust in e-commerce as “the belief that allows consumers to
willingly become vulnerable to Web retailers after having taken the retailers‟
characteristics into consideration”. McKnight et al. (2002:335) identify “multiple,
interrelated dimensions of e-commerce trust” that inform consumer behaviour and trust
building and describes trust as “the willingness to depend on a vendor to deliver on
commitments; as a belief that the vendor uses consumer data ethically; or a perception
that the Internet is technologically secure”. It is therefore, possible to have trust based
on one or more dimensions but not necessarily all to engage in online shopping. Tan
and Thoen (2000) identify two (2) main elements of trust in online shopping as trust in
the vendors and trust in the technological infrastructure (the Internet), which are evident
from the above definitions. However, Pavlou (2003:107) argues that web retailers have
a significant role to play in encouraging trust in the infrastructure by creating safe and
secure online shopping environments. This implies that consumers‟ trust in the Internet
can be influenced by perceptions of the vendors. Therefore for the purpose of this study,
emphasis will be placed on consumers‟ trust in online vendors rather than trust in the
infrastructure. This study argues that since online vendors are the consumers‟ main
focus when transacting online, trust is built based on perceptions of the vendors.
23
2.5 SUMMARY
In this chapter, the development of B2C e-commerce was discussed. Statistics were
presented on online shopping trends globally, in the UK and Nigeria. Some
comparisons were made between these trends with the aim of identifying inhibiting
factors affecting online shopping in Nigeria. The issue of trust in online environments
was also explored based on existing literature as this was identified as one of the major
factors affecting e-commerce adoption in Nigeria.
24
CHAPTER 3: METHODOLOGY
3.1 INTRODUCTION
This chapter introduces the research model which is based on previous literature and
explores existing literatures on TAM and the modified TAM model for e-commerce.
The research methodology and research approach are discussed in detail to justify the
choice of methods used in this study. The sampling process was also presented in detail
to support the sample size used. The chapter concludes with a design of the
questionnaire and, ethical issues are finally addressed.
3.2 RESEARCH MODEL
3.2.1 Trust and Technology Acceptance Model (TAM)
Studies on trust and TAM abound with researchers proposing different theories (Gefen
et al. 2003a; Hans van der Heijden et al. 2003; Pavlou, 2003; Swilley and Goldsmith,
2007; Tang and Chi, 2008; Ha and Stoel, 2009). These studies have integrated trust
with the existing TAM use-antecedents, i.e. perceived ease of use and perceived
usefulness, in a bid to establish a relationship between these variables and attitude to
online shopping. These studies, amongst others, confirm a positive relationship between
consumer trust and attitude to shop online. They confirm that trust is vital for adoption
of online shopping.
3.2.1.1 TAM
There have been previous studies on understanding how and why people engage in e-
commerce, especially online shopping which involves searching for products and
service information and the actual buying of products and/or services (Gefen and
Straub, 2000; Chen et al., 2002; Vijayasarathy, 2004; Klopping and McKinney , 2004).
These studies have employed different theories and models such as the Technology
Acceptance Model (TAM), Theory of Planned Behaviour (TPB) and Theory of
Reasoned Action (TRA) in an attempt to understand user acceptance of computer
technology.
Davis (1989) developed TAM in a bid to explain and predict user acceptance of
information technology and is theoretically based on Fishbein and Ajzen‟s (1975) TRA
which states that “beliefs influence attitudes which lead to intentions, and finally to
25
behaviours” (Klopping and McKinney, 2004:36). The theory explains that peoples‟
behaviours are determined by their intentions, and these intentions are influenced by
attitudes and subjective norms with respect to the particular behaviour (Davis et al.
1989). TPB on the other hand is a modification of TRA and “refers to an individual‟s
perception of whether or not the requisite resources or opportunities are present to
perform a behaviour” (Klopping and McKinney, 2004:36).
Davis (1989) identifies two major variables from previous research, affecting the
acceptance and use of IT namely; Perceived Ease of Use and Perceived Usefulness.
Perceived Ease of Use (PEOU) is “the degree to which a person believes that using a
particular system would be free of effort” (Davis, 1989:320) and Perceived Usefulness
(PU) is “the degree to which a person believes that using a particular system would
enhance his or her job performance” (Davis, 1989:320). These variables explain that
people are more likely to adopt and use IT if they feel it is beneficial to them and easy
to use (i.e. involves minimal effort). The Figure 3.1 below shows TAM as an adaptation
of these theories into an IT acceptance model.
Figure 3.1: Technology Acceptance Model (TAM) (Davis et al. 1989: 985)
Later studies have identified PU as important in IT adoption (Taylor and Todd, 1995;
Igbaria et al., 1996; Gefen and Keil, 1998; Agarwal and Prasad, 1999; Dishaw and
Strong, 1999; Moon and Kim, 2000). However, there have been no concrete
correlations between PEOU and user‟s attitude or intention to use IT (Keil et al. 1995).
Most studies to date have applied the TAM to IT adoption in the workplace (Teo et al.,
1999; Lederer et al., 2000), but few studies related to consumer web adoption found
TAM appropriate for e-commerce (Klopping and McKinney, 2004).
Perceived
Usefulness
(U)
Perceived
Ease of Use
(E)
Behavioural
Intention to
Use (BI)
Actual
System
Use
External
Variables
Attitude
Toward
Using (A)
26
3.2.1.2 The Modified TAM for e-commerce
Klopping and McKinney (2004:37), propose “a modified TAM and a broader view of
the shopping task” to make TAM more suitable to online shopping environments. The
modification involves eliminating the link between PEOU and PU in the original TAM,
since it is argued that web tools are considerably easy to use (Childers et al., 2001;
Magal and Mirchandani, 2001). It also involves “further simplifying the original TAM
by dropping attitude and instead studying the relationship between PU and PEOU on
intention to use” (Gefen and Straub, 2000; Lederer et al., 2000; Teo et al., 1999).
Klopping and McKinney (2004) also introduce a direct effect of PU on actual use. It is
argued that consumers may increase their use of online shopping without necessarily
changing their intention to use. The Figure 2 below shows the modified TAM as
proposed by Klopping and McKinney (2004).
Figure 3.2: Modified TAM for E-Commerce (Klopping and McKinney, 2004:37)
3.2.2 Research Model
The research model used in this study was based on the above discussed modified TAM
for e-commerce. It also integrates trust as an external variable that affects behavioural
intention to shop online and actual purchases. The Figure 3.3 below shows the research
model.
Perceived
Usefulness
(PU)
Perceived Ease
of Use
(PEOU)
Behavioural
Intention to Use
Actual
Usage
27
Fig. 3.3 Research model
In order to satisfy the aims and objectives of this study, the following hypotheses were
proposed from the research model;
H1: “a consumer’s perceived usefulness has a positive effect on his/her actual usage
of online shopping”.
H2: “a consumer’s perceived usefulness has a positive effect on his/her intention
towards online shopping”.
H3: “a consumer’s perceived ease of use has a positive effect on his/her intention to
use online shopping”.
H4: “a consumer’s trust towards online shopping has a positive effect on his/her
intention to use online shopping”.
H5: “a consumer’s trust has a positive effect on his/her actual usage of online
shopping”.
H6: “a consumer’s intention to shop online has a positive effect on his/her actual
usage of online shopping”.
These hypotheses were proposed to prove if the variables affected actual usage of
online shopping by respondents and identify changes in previous use in Nigeria.
Perceived
Usefulness (PU)
Perceived Ease
of Use (PEOU)
Behavioural
Intention to Use
Actual
Usage
H1 H2
H4
H5
H3
H6
Trust
28
3.3 RESEARCH METHODOLOGY
Strauss and Corbin (1990:3) define a methodology as “a way of thinking about and
studying social reality” and methods as “a set of techniques for gathering and analysing
data”. The type of research methodology to be used in a research depends on the aims
and objectives of that research. A clear comprehension of these aims and objectives is
essential in selecting suitable research techniques (methods) for carrying out the study
(Oppenheim, 1998).
3.3.1 Inductive and Deductive Approaches
Two broad methods applied in studying social reality and reasoning are the deductive
and inductive approaches. An inductive approach employs an induction process
“through which observations are made (possibly casually at first), data are collected,
general patterns are recognised and relationships are proposed” (Black, 1999:8).
Thomas (2003:2) defines inductive approach as “a systematic procedure for analysing
qualitative data where the analysis is guided by specific objectives”. Inductive approach
is empirically driven using already existing facts to draw new conclusions and is
commonly called a bottom up approach.
While a deductive approach is theoretically driven, testing results with ideas or
hypotheses. A deductive approach employs a deduction process which “assumes that
one can explain, or deduce an explanation, by matching a specific situation to a more
general one” (Black, 1999:9). Deductive reasoning works from the more general to the
more specific and is termed a "top-down" approach (Trochim, 2006).
3.3.2 Qualitative and Quantitative Approaches
Research methods could either be of a qualitative, quantitative or mixed approach.
Strauss and Corbin (1990:10) describe qualitative research as “any type of research that
produces findings not arrived at by statistical procedures or other means of
quantification” but rather involves collecting, analysing and interpreting data by
observing what people say or do (Burns, 2000). Gorman and Clayton (2005:3) state:
“Qualitative research is a process of enquiry that draws data from the context in which
events occur, in an attempt to describe these occurrences, as means of determining the
process in which events are embedded and the perspectives of those participating in the
events, using induction to derive possible explanations based on observed phenomena”.
29
Morse and Field (1995: 1) also state that “qualitative research enables us to make sense
of reality, to describe and explain the social world, and to develop explanatory models
and theories”. Therefore, qualitative research is quite effective in providing in-depth
understanding on why something is happening and techniques or methods of gathering
qualitative data include interviews (face-to-face and/or telephone) and observations.
Quantitative research on the other hand, uses statistical procedures to analyse data to
produce results. “Quantitative research is based on the collection of considerable data
from representative samples of a larger population for a few variables” (Black, 1999:9).
Bryman, (1988:12) describes quantitative research as:
“a genre which uses a special language which appears to exhibit some
similarity to the ways in which scientists talk about how they investigate the
natural order, variable ,control, measurement [and] experiment”.
Quantitative research provides analysis on what is happening to a group of people
through the use of questionnaires which contain sets of structured questions.
“Quantitative research involves the use of structured questions in which response
options have been predetermined and a large number of respondents involved” (Burns
and Bush, 2004:3).
Johnson and Onwuegbuzie (2004:17) define a mixed approach as “the class of research
where the researcher mixes or combines quantitative and qualitative research
techniques, methods, approaches, concepts or language into a single study”.
3.4 RESEARCH APPROACH
In order to achieve the objectives of this research, the quantitative approach was used to
identify changes in online shopping behaviours of Nigerian PGT students in the
University of Sheffield and factors responsible for these changes (if existent). The use
of structured questions and predetermined responses were employed in the form of
questionnaires. Several advantages of using questionnaires as instruments for collecting
data were carefully considered in this research before adopting it. In terms of cost, they
are relatively cheap to produce and distribute. Large numbers of respondents can also
be surveyed in a considerably short period, thereby saving time (Bath, 2005). In terms
of quality of data collected, respondents answer questions at their own convenience and
time, and participate visually rather than verbally (as in the case of qualitative data)
30
hence there is little room for misunderstood words or statements (Bryman, 2001. In
terms of anonymity, respondents enjoy privacy in responding and are protected from the
expectations of the interviewer, therefore the responses are strictly personal and
unbiased (Mangione, 1995:6).
Despite these advantages, Oppenheim (1998:102) identifies disadvantages of using
questionnaires for collecting data. These include, low response rates of respondents and
fewer questionnaires returned than expected due to loss or damage; no chance of
making corrections, probing further or offering explanations. There is also no way of
checking and/or correcting incomplete responses, questionnaires, or wrongly filled
questionnaires.
After taking all these merits and demerits into account, the questionnaire was
considered to be the best instrument for collecting reliable statistical data on online
shopping behaviours of Nigerian PGT students in Sheffield in comparison with Nigeria.
Statistical analysis was carried out on the data collected to determine what factors were
mainly responsible for any change in behaviours regarding online shopping and to what
degree these factors influenced the respondents. Benefits in terms of cost and time were
also taken into consideration to ensure this research was achievable.
As stated earlier, depending on the aims and objectives of the research, an inductive or
deductive approach could be applied. However, to satisfy the aims of this research, i.e.
to compare online shopping behaviours of Nigerian PGT students in Sheffield and
Nigeria, and to examine if factors identified in previous research were responsible for
any changes that might exist, an deductive approach was used to draw conclusions from
the data collected through the quantitative approach discussed above. This approach
was adopted to identify changes in online shopping behaviours due to change in
environment.
3.5 SAMPLING PROCESS
With little or no previous study on e-commerce adoption by Nigerians living abroad
(outside their home country), this research focused on Nigerian Post Graduate Taught
(PGT) students currently studying in the University of Sheffield to determine if a
change in environment will lead to a change in online shopping patterns. Yearly,
thousands of Nigerian students come to the UK for both undergraduate and
postgraduate studies. A 2008 survey on the number of Nigerian students studying in the
31
UK revealed that were about 15,000 postgraduate (PG) students from Nigeria studying
in UK higher education institutions (BUSINESSDAY, 2009). There are presently 166
institutions of higher education in the UK (Universities UK, 2010), giving an average of
approximately 100 PG Nigerian students in each institution yearly. Knowledge on the
approximate number of Nigerian PG students was important as this study focused on
these students in a particular institution (i.e. University of Sheffield).
Upon thorough enquiry, it was discovered that there were 99 Nigerian PGT students in
the University of Sheffield domiciled in Nigeria (Source: University of Sheffield
Marketing Department) as at the time of study. This group was selected because they
represent an educated workforce of the Nigerian population.
Since the objective of this study was to identify a generalised change pattern in the
target population rather than individuals, a non probability sampling method was used.
Time and cost constraints, as well as access to the participants were also of great
importance when choosing sampling method. After taking all these factors and the
target population size (99 students) into account, snowball sampling was used to select
participants in the survey. Contact was made with a small group of Nigerian PGT
student personally known to the researcher and through them, contact was established
with others. Although it was impossible to reach everyone in the target population, a
sample size of at least two thirds (i.e. 66 students) of the total number was aimed at.
As discussed earlier, sampling was restricted to Nigerian PGT students in the
University of Sheffield for a number of reasons; firstly, they were new to Sheffield and
had only lived in the UK for less than a year; secondly, they were easily accessible, and
they represent an educated workforce of the Nigerian population. This research was
also limited to Sheffield to eliminate complexities due to long distance surveys and
travelling time and cost.
3.6 QUESTIONNAIRE DESIGN
As mentioned before, questionnaires were used to collect data from the sample of
students. Questionnaires are very important instruments of research and contain sets of
structured questions and predetermined responses that can ease data collection. Hence,
the need to design a suitable questionnaire that covered all aspects of the research was
vital in providing reliable and useful data. The questionnaire design was based on the
research model shown in Figure 3.3 and on the objectives of the study, which are;
32
To investigate if Nigerian PGT students are familiar with e-commerce and
what they use it for;
To examine the extent to which they engage in online shopping while in
Sheffield compared with when they were in Nigeria;
To identify similarities and/or differences in their online shopping behaviours
in both countries;
To investigate why these similarities and/or differences exist;
To make recommendations based on the findings of the empirical research.
The questionnaire comprised of closed questions and few open ended questions.
Closed questions were used because they enable quick processing of responses and
less ambiguity in responses, thereby making the data easy to analyse. It was also
easy for respondents to fill the questionnaires in short periods of time. However, the
limitation with using closed questions was the inability of respondents to give
responses based on their individual perspectives. It is possible for respondents to
have different views with regard to the same question, and these views could also
differ from the predetermined response options given in the questionnaire. In order
to limit the possibility of getting unreliable responses, open ended questions were
also included. The Table 3.1 below gives a detailed structure of the questionnaire
used in this study.
Question
Number
Question Types Information Format
1
Personal Factual Questions
Gender Checklist (choose
only one option)
2 Duration of stay in
Sheffield
Open ended question
3 Previous Work
Experience
Checklist (choose
only one option)
4
Questions on Internet use
Frequency of use in
Nigeria
Checklist (choose
only one option)
5 Frequency of use in
Sheffield
6 Purpose of use in
Nigeria
Checklist (tick
relevant answers).
Open question
included 7 Purpose of use in
Sheffield
8
Questions on E-commerce
Familiarity before
coming to Sheffield
Checklist (choose
only one option)
9 Usage before coming
to Sheffield
Checklist (choose
only one option).
Only for those who
33
had heard about e-
commerce before.
10 Question on E-commerce Purpose of use in
Nigeria
Checklist (tick
relevant answers).
Only for those who
had used e-commerce
before. Open question
included.
11 Question on online shopping Frequency of use in
Nigeria
Checklist (choose
only one option).
Only for those who
had used e-commerce
before.
12
Questions on E-commerce
Familiarity in
Sheffield
Checklist (choose
only one option).
Only for those who
had not heard about
e-commerce before.
13 Factors that affected
use in Nigeria
Checklist (tick
relevant answers).
Only for those who
had no prior use.
14 Purpose of use in
Sheffield
Checklist (tick
relevant answers).
Open question
included
15 Frequency of use in
Sheffield
Checklist (choose
only one option).
16
Questions on online shopping
Number of retail
websites visited in a
month
17 Duration of visits per
week
18
Questions on online shopping
Products shopped for Checklist (tick
relevant answers).
Open question
included
19 Change in use in both
countries
Scaled checklist
(choose only one
option)
20 Factors that have
encouraged use in
Sheffield
Checklist (choose
only two options).
Open question
included
21 Question on e-commerce Change in use in both
countries
Checklist (choose
only one option)
PU1
Questions on perceived
usefulness
Internet access
concerns
Scaled Matrix
Scaled Matrix
PU2 Internet usefulness for
shopping
PU3
Questions on perceived
usefulness
Online shopping
usefulness
PEU4
Questions on perceived ease of
Internet usage
concerns
Scaled Matrix
PEU5 Internet usage
concerns
PEU6 Information seeking
34
use on websites
PEU7 Internet usage
concerns
IU8
Questions on intention to use
Internet use for online
shopping in Nigeria
Scaled Matrix
IU9 Trust concerns
IU10 Online shopping
usefulness
IU11 Ease of use of website
IU12 Internet usage
concerns
T13
Questions on trust
Trust concerns
Scaled Matrix
T14 Trust concerns of
Nigerian retailers
T15 Trust in Internet use in
Sheffield
T16 Safety concerns
T17 Product authenticity
concerns
T18 Payment concerns
T19 Data security concerns
T20 Shopping experience
in Sheffield
T21 Trust concerns
Table 3.1 Questionnaire Structure
Since the target population in this study was restricted to the University of Sheffield,
distribution of questionnaires was done manually and 73 questionnaires were received
back which was about 74% of the total number of Nigerian PGT students.
3.7 ETHICAL ISSUES
Anonymity of participants in this research was highly respected by keeping all
responses unidentifiable and untraceable to the respondents involved. This was done in
conformance with the University of Sheffield research guidelines and the Data
Protection Act 1998.
3.8 SUMMARY
In this chapter, existing literatures on TAM and the modified TAM model for e-
commerce were explored and the research model based on the modified TAM was
presented. The research methodology and research approach were discussed in detail to
justify the choice of methods used in this study. A deductive approach was adopted as
the suitable research method to identify changes in online shopping behaviours of
Nigerian PGT students in Sheffield in comparison with Nigeria and factors responsible
for these changes. A quantitative approach was also considered effective for collecting
data in line with the objectives of this study. The sampling process involved in the
35
survey was discussed to justify the sample size used in this study and the survey was
carried out using questionnaires. The use of questionnaires was considered most
appropriate in comparison with other methods of investigation with regards to time and
cost constraints. Finally, ethical issues were addressed with emphasis on anonymity of
participants in the study.
36
CHAPTER 4: DATA PRESENTATION AND
ANALYSIS
4.1 INTRODUCTION
This chapter presents and analyses data collected through questionnaires from the
sample group.
Presentation and analysis of data are carried out following the format of questions asked
in the questionnaire. The first section presents the respondents‟ personal information
and analyses the data based on gender composition, duration of stay in Sheffield, and
previous work experience. The second section presents and analyses data on
respondents‟ internet usage in Nigeria and Sheffield, and on respondents‟ e-commerce
and online shopping behaviours in both countries and uses statistical tests to determine
factors responsible for changes in behaviour. The final section examines effects of
variables on respondents‟ actual usage of online shopping.
4.2 SECTION A: PERSONAL INFORMATION
4.2.1 Gender Composition
Figure 4.1 Gender Composition
From the pie chart above (Figure 4.1), it can be deduced that the sample group consisted
of more males (53.4%) than females (46.6%). The number of Nigerian PGT students in
the University of Sheffield was 99 and 52.5% were males, while 47.5% were females
(Source: University of Sheffield Marketing Department). According to a 2010 survey,
51% of the working populations (i.e. 15–64 years) in Nigeria were males and 49% were
37
females (CIA-The World Factbook). These percentages show little disparity in gender
composition between the national level and the sample group.
4.2.2 Duration of stay in Sheffield
Figure 4.2 Duration of stay in Sheffield
The Figure 4.2 above shows that 86.3% of respondents had been in Sheffield for less
than one year. This shows that most of them were new to that environment and
whatever change they experienced, had occurred within this short period of time.
4.2.3 Previous Work Experience
Figure 4.3 Previous Work Experience
The Figure 4.3 above shows that 93.2% of respondents had previous employments
before coming to study and only 6.8% had no jobs. Although the working population in
Nigeria is about 55%, this sample shows a small group of people who were well
educated and employed.
38
4.3 SECTION B: RELATED QUESTIONS
4.3.1 Internet Usage
Respondents were asked questions on how often they used the Internet while in Nigeria
and in Sheffield. This was done to measure any change in internet use due to change in
environment.
Figure 4.4 Internet usage in Nigeria
Figure 4.4 shows that 49.3% of respondents used the Internet every day, while 38.4%
used it 3 or 4 times a week, 6.8% used it twice a week and less than 6% used it once a
week and very rarely while in Nigeria. However from the Figure 4.5 below, it can be
observed that 97.3% of respondents now used the Internet everyday and only a fraction
of the sample (i.e. 2.7%) used it 3 or 4 times a week in Sheffield. This shows an
increase of about 48% in every day users of the Internet in Sheffield compared with
Nigeria.
Figure 4.5 Internet usage in Sheffield
39
Questions on internet activities carried out were also asked to check for changes in use
by respondents. The Figure 4.6 below shows internet activities carried out in Nigeria
with information seeking (Yahoo, Google, etc) ranking highest with a percentage of
98.6% and E-mailing ranking second (83.3%). Social networking also ranked high with
73.6% of respondents using the Internet for that purpose. However, only 25.0%, 11.1%,
and 1.4% of respondents reported using the Internet for online (internet) banking,
shopping, and selling respectively. These activities are all e-commerce activities and
these percentages show minimal use of the Internet for these purposes by respondents
while in Nigeria.
Figure 4.6 Purpose of internet use in Nigeria
Although Information seeking, E-mailing, and Social networking still ranked highest
(98.6%, 95.8%, and 94.4% respectively), it can be observed in the Figure 4.7 below that
the percentage of respondents using the Internet for e-commerce purposes in Sheffield
increased greatly. Internet banking increased to 81.9%, Shopping (86.1%), and Selling
(8.3%) as opposed to 25.0%, 11.1%, and 1.4% respectively previously. This shows that
more respondents used the Internet for e-commerce purposes while in Sheffield
compared with when in Nigeria.
98.6%
73.6%65.3%
55.6%
22.2% 27.8% 25.0%
83.3%
11.1%1.4%
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
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Internet activities
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Figure 4.7 Purpose of internet use in Sheffield
4.3.2 E-commerce in Nigeria
4.3.2.1 E-commerce Familiarity
In order to measure any changes in online shopping behaviours, it was necessary to
know how familiar respondents were with e-commerce. Hence, respondents were asked
questions on familiarity of e-commerce while in Nigeria. The Figure 4.8 below shows
that 79.2% of respondents had heard about e-commerce before coming to Sheffield
while only 20.8% had not. However, when asked if they had used e-commerce before
coming to Sheffield, only 34.7% of respondents reported using it in Nigeria (Figure
4.9).
Figure 4.8 E-commerce familiarity in Nigeria
98.6% 94.4% 93.1%
69.4%
87.5%
68.1%
81.9%
95.8%86.1%
8.3%
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
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Internet activities
41
Figure 4.9 E-commerce usage in Nigeria
Figure 4.9 also shows that 65.3% of respondents had never used e-commerce before
coming to Sheffield. These percentages indicate common knowledge on e-commerce
by a majority of respondents but fewer users of e-commerce in Nigeria.
4.3.2.2 E-commerce and Online Shopping Behaviours in Nigeria
Since it was established above that only 34.7% of respondents used e-commerce in
Nigeria, it was necessary to identify what activities they used it for. This was to
determine what percentage of respondents used e-commerce for online shopping while
in Nigeria. The Figure 4.10 below shows common activities respondents used e-
commerce for. It can be observed from the figure that the most popular activity carried
out was searching for product information (58.3%), followed by money transfers
(50%). Online shopping and paying bills each had a percentage of 25%, indicating
fewer respondents (about 8% of the sample) shopped online while in Nigeria.
Figure 4.10 Purpose of e-commerce use in Nigeria
50.0%
25.0%
58.3%
25.0%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%
Money Transfers Online shopping Searching for product
information
Paying bills
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E-commerce activities
42
With few respondents actually shopping online while in Nigeria, the frequency of
online shopping among respondents who were e-commerce users (i.e. 34.7% of
respondents) was measured. This was done to identify reasons for the low percentage of
online shopping (25%). The Figure 4.11 below shows that 48% of respondents who
reported to be e-commerce users while in Nigeria had never shopped online. 20% of
these respondents reported shopping online two or three times a year and 16% shopped
online once a year. These high percentages of non-shoppers and infrequent shoppers as
opposed to monthly shoppers (16% of respondents) could be responsible for the low
percentage of respondents who shopped online while in Nigeria.
Figure 4.11 Online shopping in Nigeria
From these charts, it is obvious that the percentage of respondents who did not use e-
commerce while in Nigeria (i.e. 65.7%) was much greater than those who used it (i.e.
34.3%, as can be seen in Figure 4.9) and even fewer online shoppers. It was therefore,
essential to know which factors best affected their use in Nigeria. These factors were
determined using factor analysis.
FACTOR ANALYSIS 1:
Preliminary Analysis
Multicollinearity: Field (2006:738) defines multicollinearity as a “situation in which
two or more variables are very closely linearly related”. Since the determinant of the
correlation matrix (see Appendix II) was 1.30 which was bigger than 0.00001,
multicollinearity was not a problem in these data.
43
Sample size: In the Table 4.1 below, the KMO statistic is 0.699 and is greater than 0.5,
which is the minimum KMO measure of sampling adequacy (Kaiser, 1974). From the
table it is also evident that the Bartlett‟s test of sphericity is significant, since Sig. is
0.000 which is less than 0.05. Bartlett (1954) suggests that the value of Sig. should be
less than 0.05 for factor analysis to be considered appropriate. From these values, it is
evident that the sample size was adequate to produce reliable factors.
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy. .699
Bartlett‟s Test of
Sphericity
Approx. Chi-Square 80.634
df 28.000
Sig. .000
Table 4.1 KMO and Bartlett‟s Test
Factor Extraction
From the table of Total Variance Explained (see Appendix III), it can be observed that
SPSS extracted 3 factors with eigenvalues greater than 1 based on Kaiser‟s criterion.
However, Kaiser‟s criterion is “accurate when there are less than 30 variables and the
communalities after extraction are greater than 0.7, or when the sample size exceeds
250 and the average communality is greater than 0.6” (Field, 2006:655). From this data,
there were 8 variables but there were factors with less than 0.7 in the „extraction‟
column in the communalities table. Therefore, it was necessary to use the scree plot to
extract factors. The scree plot in the Figure 4.12 shows a significant inflexion at 2
factors, hence retaining 2 factors is justifiable.
44
Figure 4.12 Scree Plot
Factor Rotation and Interpretation
Factor rotation was carried out using orthogonal rotation (varimax). A rotated
component matrix of factor loadings (based on loadings greater than 0.4) for each
variable is shown in the Table 4.2 below.
Component
1 2
Which of these factors BEST
affected your use in Nigeria?
privacy and confidentiality
.820
Which of these factors BEST
affected your use in Nigeria?
data security
.815
Which of these factors BEST
affected your use in Nigeria?
authenticity of products
.666
Which of these factors BEST
affected your use in Nigeria?
credit card threat
.647 -.544
Which of these factors BEST
affected your use in Nigeria?
computer literacy
.777
Which of these factors BEST
affected your use in Nigeria?
income
.693
Which of these factors BEST
affected your use in Nigeria?
accessibility
.570
Which of these factors BEST
affected your use in Nigeria?
few online vendors
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.
Table 4.2 Rotated Component Matrix
From the matrix above, the following pattern can be observed:
Factor 1:
45
Variable 1: Data security
Variable 2: Privacy and confidentiality
Variable 3: Authenticity of products
Variable 4: Credit card threat
These variables indicate trust concerns of consumers. As discussed in the literature
review, there were two elements trust in online shopping, trust in the vendors and trust
in the technological infrastructure (the Internet), however for the purpose of this study,
factor 1 relates to trust in web vendors since they can affect consumers‟ trust in
technology by providing adequate and effective safety measures.
In the questionnaire, questions were asked on factors affecting online shopping in
Nigeria and only those who had not used e-commerce before coming to Sheffield
responded to it. From the Figure 4.13 below, it is evident that Privacy and
Confidentiality ranked the highest factor chosen by respondents with a percentage of
61.4%, followed by Accessibility (60%), Data security (59.1%), Credit card threat
(47.7%), and Authenticity of products (40.9%). Apart from accessibility, all other
factors mentioned above were related to factor 1 in the factor analysis carried out. This
shows that trust was a major factor for Nigerian PGT students in Sheffield not using e-
commerce in Nigeria.
Figure 4.13 Factors affecting online shopping in Nigeria
Factor 2:
60.0% 61.4%
18.2%
40.9%
59.1%47.7%
6.8%
38.6%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%
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Factors
46
Variable 1: Computer Literacy
Variable 2: Income
Variable 3: Accessibility
These variables reflect consumers‟ personal constraints and are all interrelated. Low
income will impede the purchase and/or use of computers, thereby resulting in low
levels of computer literacy. Low income also affects the use of cybercafés for accessing
the Internet, since they charge fees for services provided (as discussed in the literature
review). Low levels of computer literacy invariably discourages accessing and using the
Internet for various activities especially e-commerce.
From the Figure 4.13 above, 18.2% and 6.8% of respondents also chose Income and
Computer literacy respectively as factors that affected their use in Nigeria. These
factors and accessibility have been termed as personal constraints that hinder the use of
e-commerce in Nigeria (factor 2).
From these analyses, it is evident that trust concerns and personal constraints were the 2
main factors that affected e-commerce usage in Nigeria.
No factor:
Variable 1: Few online vendors
38.6% of respondents chose few online vendors as a factor that affected their use of e-
commerce. Although from the factor analysis, this variable belonged to no factor; it is
however worth nothing that this was one of the factors identified from past studies
carried out in Nigeria as discussed in the literature review.
4.3.2 E-commerce in Sheffield
4.3.2.1 E-commerce and Online Shopping Behaviours in Sheffield
Respondents were asked questions on familiarity with e-commerce in Sheffield and
100% reported positively. It was then necessary to identify what e-commerce activities
they engaged in to check for changes in online shopping behaviours. From the Figure
4.14 below, 86.1% of respondents reported shopping online in Sheffield, 80.3% made
money transfers (online banking), 59.7% searched for product information, and 48.6%
paid bills online. Although this percentage included previous non-users and users of e-
47
commerce, this shows an increase in online shopping from 8% (in Nigeria) to 86.1% of
respondents in Sheffield.
Figure 4.14 Purpose of e-commerce use in Sheffield
The frequency of e-commerce use in Sheffield was also investigated to check the level
of participation of respondents. The Figure 4.15 shows that 64.8% of respondents
reported using e-commerce monthly, 23.9% reported using it daily, and 11.3% reported
using it two or three times a year. This reveals that majority of respondents (about 89%)
used e-commerce on monthly and daily bases in Sheffield, making them active e-
commerce users.
Figure 4.15 Frequency of e-commerce use in Sheffield
To determine how active respondents were in shopping online in Sheffield, the average
number of online retail websites visited in a given month and time spent on online
shopping activities per week were measured. From the Figure 4.16 below, it was
80.3%86.1%
59.7%
48.6%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%80.0%90.0%
100.0%
Money Transfers Online shopping Searching for product
information
Paying bills
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E-commerce activities
48
observed that 31.9% of respondents visited between 6 to 20 online retail websites in a
given month. 30.6% visited 1-2 websites, 29.2% visited 3-5 websites, and 8.3% of
respondents visited over 20 websites in a given month. This shows that about 40% of
respondents visited over 6 websites on an average monthly.
Figure 4.16 Average number of online retail websites visited in a given month
Figure 4.17 shows time spent on online shopping activities per week. 36.1% of
respondents spent 16-60 minutes per week on online shopping activities, 26.4% spent 6-
15 minutes, 20.8% spent over 20 minutes, and 16.7% spent 0-5 minutes per week on
online shopping. From these percentages, it is evident that about 83% of respondents
spent over 6 minutes per week on online shopping activities while in Sheffield.
Figure 4.17 Time spent on online shopping per week
It was also necessary to investigate shopping patterns of respondents by identifying
products mostly shopped online. The Figure 4.18 shows types of products shopped
online and the percentage of respondents who shopped for these products. It was
observed that 67.1% of respondents made reservations (travel tickets, take outs, hotels,
etc) online. 63% shopped for wears (clothes, shoes, accessories, etc), 39.7% shopped
49
for books, 23.3% shopped for entertainment (music, movies, games, etc), 21.9%
shopped for electronics, 11% shopped for others (call cards, licenses, subscriptions,
etc), and only 2.7% shopped for groceries online. This shows that the most popular
products shopped online by the respondents were reservations and wears.
Figure 4.18 Products shopped online
Based on previous responses given, respondents were asked to compare their online
shopping behaviours in Sheffield with when they where in Nigeria. The Figure 4.19
below shows the result for this comparison and it was observed that 70.8% of
respondents strongly agreed that they did more online shopping in Sheffield. 23.6%
agreed and only 5.6% were neutral about shopping online more frequently in Sheffield
compared with when they were in Nigeria. It is therefore evident that over 94% of
respondents agreed that they shopped online more in Sheffield than they did in Nigeria
and this shows an improvement in online shopping behaviours amongst respondents.
39.7%
2.7%
63.0% 67.1%
23.3% 21.9%
11.0%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%80.0%
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Types of product
50
Figure 4.19 Comparison of online shopping behaviours in Sheffield with Nigeria
It was therefore, important to know which factors encouraged respondents to engage in
online shopping in Sheffield. These factors were determined using factor analysis.
FACTOR ANALYSIS 2:
Preliminary Analysis
Multicollinearity: Since the determinant of the correlation matrix (see Appendix IV)
was 0.323 which was bigger than 0.00001, multicollinearity was not a problem in these
data.
Sample size: In the Table 4.3 below, the KMO statistic is 0.719 and is greater than 0.5
and from the table it is also evident that the Bartlett‟s test of sphericity is significant,
since Sig. is 0.000 which is less than 0.05. From these values, it is evident that the
sample size was adequate to produce reliable factors and factor analysis was
appropriate.
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy. .719
Bartlett's Test of
Sphericity
Approx. Chi-Square 77.404
df 28.000
Sig. .000
Table 4.3 KMO and Bartlett‟s Test
51
Factor Extraction
From the table of Total Variance Explained (see Appendix V), it can be observed that
SPSS extracted 2 factors with eigenvalues greater than 1. However, based on the
Kaiser‟s criterion discussed above, and data available, the scree plot was used to extract
factors. The scree plot (Figure 4.20) shows a significant inflexion at 2 factors, hence
retaining 2 factors was justifiable.
Figure 4.20 Scree Plot
Factor Rotation and Interpretation:
Factor rotation was carried out using orthogonal rotation (varimax). A rotated
component matrix of factor loadings for each variable is shown in the table below.
From this matrix, the following pattern can be observed:
Factor 1:
Variable 1: Privacy and confidentiality
Variable 2: Trust in online vendors
Variable 3: Authenticity of products
Variable 4: Data security and Credit card threat
These variables indicate trust concerns of consumers, therefore, factor 1 relates to trust
in web retailers as discussed above.
52
Component
1 2
Which of these factors have
encouraged you to engage in
online shopping now in
Sheffield? privacy and
confidentiality
.726
Which of these factors have
encouraged you to engage in
online shopping now in
Sheffield? trust in online
vendors
.705
Which of these factors have
encouraged you to engage in
online shopping now in
Sheffield? authenticity
.656
Which of these factors have
encouraged you to engage in
online shopping now in
Sheffield? data security and
credit card threat
.549
Which of these factors have
encouraged you to engage in
online shopping now in
Sheffield? perceived ease of
use
.789
Which of these factors have
encouraged you to engage in
online shopping now in
Sheffield? accessibility
.659
Which of these factors have
encouraged you to engage in
online shopping now in
Sheffield? perceived
usefulness
.622
Which of these factors have
encouraged you to engage in
online shopping now in
Sheffield? network
reliability
.415
a. Rotation converged in 3 iterations.
Extraction Method: Principal Component Analysis.
Table 4.4 Rotated Component Matrix
53
In the questionnaire, questions were asked on factors encouraging online shopping in
Sheffield and were applicable to all respondents. From the figure below, it is evident
that Accessibility ranked the highest factor chosen by respondents with a percentage of
64.4%, followed by Trust in online vendors (56.2%), Privacy and confidentiality
(50.7%), Perceived ease of use (41.1%), Network reliability (41.1%), Data security and
Credit card threat (38.4%), Authenticity of products (30.1%), and Perceived usefulness
(27.4%). Although accessibility ranked highest, it is evident that variables relating to
trusts concerns (i.e. factor 1) carry more loadings (though minimal) than other variables.
This shows that trust was a major factor for Nigerian PGT students in Sheffield
shopping online in Sheffield.
Figure 4.21 Factors encouraging online shopping in Sheffield
Factor 2:
Variable 1: Perceived ease of use
Variable 2: Accessibility
Variable 3: Perceived usefulness
Variable 4: Network reliability
These variables have been termed as consumers‟ perceptions of technology that could
encourage online shopping in Sheffield (factor 2).
64.4%
50.7%56.2%
38.4%30.1%
41.1% 41.1%
27.4%
0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%
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Factors
54
From these analyses, it is evident that trust concerns and consumers‟ perceptions of
technology were the 2 main factors that encouraged online shopping in Sheffield.
4.4 SECTION C: EFFECT OF VARIABLES ON
CONSUMERS’ ACTUAL USAGE OF ONLINE SHOPPING
4.4.1 Perceived Usefulness
Respondents were asked questions on perceived usefulness as follows;
Q1: Having more access to the Internet enables me to shop online more often than
previously.
From the Figure 4.22 below, 43.1% and 27.8% of respondents strongly agreed and
agreed respectively, that having more access to the Internet enabled them to shop more
often than previously, while 18.1% and 11.1% of respondents were neutral and
disagreed respectively. This shows that over 70% of respondents agreed with this
statement.
Figure 4.22 Internet access and shopping
Q2: Using the Internet makes it easier and quicker for me to shop.
The Figure 4.23 shows that 37.5% and 48.6% of respondents strongly agreed and
agreed respectively, that using the Internet made it easier and quicker to shop, while
12.5% and 1.4% were neutral and disagreed respectively with this statement. From
55
these percentages, it is evident that over 86% of respondents agreed the Internet was
useful for shopping.
Figure 4.23 Perceived usefulness of the Internet for shopping
Q3: I find shopping online convenient for meeting my needs.
The Figure 4.24 shows that 31% and 43.7% strongly agreed and agreed respectively,
that shopping online was convenient for meeting their needs, while 22.5% and 2.8%
were neutral and disagreed respectively with the statement. These percentages imply
that over 74% of respondents found online shopping useful for meeting their needs.
Figure 4.24 Perceived usefulness of online shopping
The responses obtained from the analyses above show that majority of respondents
believe that having more access to the Internet enabled them to shop more often than
previously and was useful for shopping. This also shows that majority of respondents
56
agreed that online shopping was useful for meeting their needs. This supports the
hypothesis (H2) proposed earlier which states that:
“A consumer’s perceived usefulness has a positive effect on his/her actual usage of
online shopping”.
4.4.2 Perceived Ease of Use
Respondents were asked questions on perceived ease of use as follows;
Q4: I found it difficult to learn how to use the Internet to do my shopping activities.
From the Figure 4.25 below, 43.1% strongly disagreed and 51.4% disagreed with this
statement, while 5.6% of respondents were neutral. This shows that majority (over
94%) of respondents did not find it difficult to use the Internet for shopping.
Figure 4.25 Perceived ease of use of the Internet for shopping (Learning difficulty)
Q5: I took a long time to learn to use the Internet to do my shopping activities.
In response to this question (Figure 4.26), 48.6% of respondents strongly disagreed and
43.1% disagreed, while 4.2% were neutral and 4.2% agreed that it took a long time for
them to learn to use the Internet for shopping. From these percentages, it is evident that
over 90% of respondents did not spend much time learning to use the Internet for
shopping.
57
Figure 4.26 Perceived ease of use of the Internet for shopping (Learning time)
Q6: I find it easy to locate the information that I need in a retailer‟s Web site.
Figure 4.27 shows responses to this question and it can be observed that 19.7% of
respondents strongly agreed, while 52.1% agreed that they found it easy to locate
information on retailers‟ websites. 22.5% were neutral, 4.2% disagreed and 1.4%
strongly disagreed. These percentages indicate over 70% of respondents did not have
difficulties in finding necessary information on retailer‟s websites.
Figure 4.27 Information seeking on retailer‟s website
Q7: I shop online more frequently in Sheffield because I find the Internet easier to
use now.
58
Respondents responded to this question with mixed reviews. While 18.1% strongly
agreed and 26.4% agreed that they shopped online more frequently in Sheffield because
they found the Internet easier to use, 26.4% and 6.9% disagreed and strongly disagreed
with this statement. Compared to these percentages, a significant number of
respondents reported being neutral (22.2% of respondents). Although, it can be
observed that majority of respondents (over 44%) agreed that their increase in online
shopping in Sheffield could be attributed to perceived ease of use of the Internet, over
36% of respondents disagreed. Due to the significant percentage of respondents who
were neutral, it was difficult to make a valid conclusion based on these responses.
Figure 4.28 Perceived ease of use and increase in online shopping in Sheffield
The responses obtained from the analyses above show that majority of respondents did
not experience difficulties in learning to use the Internet for shopping, they also did not
spend much time learning to use the Internet for shopping, and they found it easy to
locate information on retailers‟ websites. However, the analysis on perceived ease of
use and increase in online shopping in Sheffield failed to reach a valid conclusion as
discussed above.
4.4.3 Intention to Use
Respondents were asked questions on intention to use as follows;
Q8: I have always wanted to use the Internet for my shopping activities in addition
to traditional methods in Nigeria.
59
Figure 4.29 shows that 11.3% and 36.6% of respondents strongly agreed and agreed
respectively, that they had always wanted to shop online in addition to traditional
methods while in Nigeria. 21.1% and 7.0% of respondents disagreed and strongly
disagreed with this statement. However, 23.9% of respondents reported being neutral to
the idea. Although over 28% of respondents did not indicate intentions to use online
shopping in Nigeria, over 47% agreed that they had always had the intention to use
online shopping in Nigeria. It can therefore be deduced that majority of respondents had
intentions to shop online in Nigeria.
Figure 4.29 Intention to use the Internet for online shopping in Nigeria
Q9: I would use the Internet for my shopping activities in addition to traditional
methods in Nigeria if I trust a retailer‟s website.
From the Figure 4.30 below, it is evident that respondents related trust to their intention
to shop online in Nigeria. 14.1% and 52.1% of respondents strongly agreed and agreed
that they would shop online in Nigeria if they trusted a retailer‟s website. 23.9% of
respondents reported being neutral, while 8.5% and 1.4% of respondents disagreed and
strongly disagreed with this statement. It is therefore, evident that over 66% of
respondents would shop online in Nigeria if they had trust in web retailers.
60
Figure 4.30 Intention to shop online in Nigeria and trust in web retailers
Q10: I would use the Internet for my shopping activities because I find online
shopping very useful.
When asked if they would shop online because they found it useful, 15.7% and 55.7%
of respondents strongly agreed and agreed respectively that they would shop online
because they found online shopping useful, while 20% reported being neutral (Figure
4.31). 7.1% disagreed and 1.4% strongly disagreed with this statement. From these
percentages, it is clear that majority of respondents (over 70%) intended to shop online
because they found online shopping useful.
Figure 4.31 Intention to shop and perceived usefulness of online shopping
Q11: I would use a retailer‟s website for my shopping activities because I find it easy
to use.
61
From the Figure 4.32 below, 18.6% strongly agreed and 44.3% of respondents agreed
that they would use a retailer‟s website for shopping online if they found it easy to use,
30.0% of respondents were neutral. 4.3% disagreed and 2.9% of respondents strongly
disagreed with the statement and failed to see any connection between intention to shop
online and perceived ease of use of a retailer‟s website. However, since majority of
respondents (over 62%) agreed that they had intention to shop online if they found
retailer‟s website easy to use, it is evident that there is a link between intention to shop
and perceived ease of use.
Figure 4.32 Intention to shop and perceived ease of use of retailer‟s website
Q12: Overall, I like using the Internet for my shopping activities.
When asked if they liked using the Internet for shopping, 21.4% of respondents strongly
agreed and 38.6% agreed, while 25.7% reported being neutral (Figure 4.33). 12.9% of
respondents disagreed and 1.4% strongly disagreed that they liked shopping online.
This shows that majority (about 60%) of respondents liked shopping online.
Figure 4.33 Intention to shop and actual online shopping
62
The above analyses shows that majority of respondents had intentions to shop online
while in Nigeria, and would shop online in Nigeria if they had trust in web retailers. It is
also evident that majority of respondents intended to shop online because they found
online shopping useful and retailer‟s website easy to use. The analyses confirm that
majority of respondents liked shopping online and support the following hypotheses
proposed previously;
H4: “a consumer’s trust towards online shopping has a positive effect on his/her
intention to use online shopping”.
H1: “a consumer’s perceived usefulness has a positive effect on his/her intention
towards online shopping”.
H3: “a consumer’s perceived ease of use has a positive effect on his/her intention to
use online shopping”.
H6: “a consumer’s intention to shop online has a positive effect on his/her actual
usage of online shopping”.
4.4.4 Trust
Respondents were asked questions on trust as follows;
Q13: Trust is a major factor when shopping online.
When respondents were asked if trust was a major factor when shopping online, 73.6%
strongly agreed, 23.6% agreed, and 2.8% reported being neutral (Figure 4.44). This
shows that over 97% of respondents believe that trust is important in online shopping.
Figure 4.44: Trust as a major factor for online shopping
63
Q14: The main reason I did not use the Internet for online shopping in Nigeria was
lack of trust in retailers.
Figure 4.45 shows that 26.1% of respondents strongly agreed, 30.4% agreed that lack of
trust in retailers hindered them from shopping online in Nigeria, while 17.4% reported
being neutral. 21.7% disagreed and 4.3% strongly disagreed. This reveals that about
56% of respondents did not shop online in Nigeria due to lack of trust in retailers.
Figure 4.45 Lack of trust and actual shopping in Nigeria
Q15: I have more trust in using the Internet for online shopping in Sheffield.
Figure 4.46 below shows that more respondents had more trust in using the Internet for
online shopping in Sheffield. 24.3% of respondents strongly agreed, 44.3% agreed,
while 24.3% reported being neutral. 5.7% of respondents disagreed and 1.4% strongly
disagreed that they had more trust shopping online in Sheffield. It is therefore evident
that over 68% of respondents had more trust shopping online in Sheffield than they did
while in Nigeria.
Figure 4.46 Trust in using the Internet in Sheffield
64
Q16: I feel unsafe about providing personal details when shopping online.
It was observed from the Figure 4.47 that 22.5% and 43.7% of respondents strongly
agreed and agreed respectively that they felt unsafe about providing personal details
when shopping online, while 22.5% of respondents reported being neutral. Only 7.0%
and 4.2% of respondents disagreed and strongly disagreed respectively with the
statement. This shows that most respondents (over 66%) were concerned about the
safety of their personal details when shopping online.
Figure 4.47 Safety of personal details online
Q17: I trust the authenticity of products displayed on retailers‟ websites.
Figure 4.48 below shows that 12.9% and 31.4% of respondents strongly agreed and
agreed respectively that they trusted the authenticity of products displayed on retailers‟
websites, while 45.7% of respondents reported being neutral. Only 5.7% and 4.3% of
respondents disagreed and strongly disagreed respectively with this statement. This
shows that most respondents were not certain that goods and services shopped online
will meet previous expectations.
65
Figure 4.48 Trust and authenticity of products
Q18: I feel uncomfortable providing card details when making payments in online
environments.
Figure 4.49 shows that over 25.7% and 38.6% of respondents strongly agree and agree
respectively expressed concerns about providing credit/debit card details when making
payments online, while 21.4% reported being neutral. About 11.4% disagreed and 2.9%
of respondents strongly disagreed that they felt uncomfortable when making payments.
It is therefore evident that though respondents were willing to shop online, most of them
(over 64%) were uncomfortable making payments online.
Figure 4.49 Credit card security concerns
Q19: A breach in data security will put me off online shopping completely.
It is evident from the Figure 4.50 below that 47.2% of respondents strongly agreed and
33.3% of respondents agreed that a breach in data security will stop their actual usage of
66
online shopping, while 6.9% reported being neutral. Less than 14% of respondents
disagreed (9.7%) and strongly disagreed (2.8%). This shows that majority of
respondents (over 80%) believed that safety of data in online environments is vital for
online shopping.
Figure 4.50 Effect of breach in data security
Q20: From online shopping experiences in Sheffield, I have complete trust in
retailers.
It can be observed from the Figure 4.51 below that 43.1% of respondents reported being
neutral when asked if they had complete trust in retailers based on online shopping
experiences in Sheffield. About 41% of respondents strongly agreed (8.3%) and agreed
(33.3%) while 15.3% disagreed with this statement. This shows that most respondents
did not have complete trust in online retailers while in Sheffield.
Figure 4.51 Online shopping experiences in Sheffield and trust
67
Q21: Trust will lead to repurchasing from a particular vendor (retailer).
When asked if trust would lead to repurchasing from a particular retailer, over 90% of
respondents strongly agreed (40.8%) and agreed (49.3%), while 8.5 % of respondents
reported being neutral and 1.4% disagreed with the statement (Figure 4.52). This shows
that trust was indeed important for the continuous use of online shopping by
respondents.
Figure 4.52: Trust as a factor for repurchasing
These analyses shows trust as an important factor for respondents when shopping online
and support the hypothesis H5, which states that:
“A consumer’s trust has a positive effect on his/her actual usage of online shopping”.
4.5 SUMMARY
This chapter presented and analysed data collected through questionnaires from the
sample group.
From the presentation and analyses of data relating to respondents‟ personal
information, it was observed that male to female ratio in the sample was similar to that
obtainable in Nigeria. Most respondents were also new to their environment and had
experienced changes in a short duration (less than one year).
Presentation and analyses of data on respondents‟ internet usage showed significant
increase in Sheffield compared with usage in Nigeria. It was also evident that less than
10% of respondents shopped online while in Nigeria, but over 80% shopped online in
Sheffield. This confirmed that e-commerce and online shopping behaviours of
68
respondents had improved significantly since coming to Sheffield. Statistical tests were
used to determine factors responsible for lack of use of e-commerce for online shopping
in Nigeria, which were identified as trust and personal constraints using factor analysis.
Factors that encouraged respondents to shop online in Sheffield were also identified
using factor analysis as trust and consumers‟ perceptions of technology. The analyses
also emphasised accessibility as a major factor contributing to respondents‟ e-
commerce and online shopping in both countries.
Finally, effects of variables on respondents‟ actual usage of online shopping were
examined. These variables included perceived ease of use, perceived usefulness,
intention to use, and trust. The results of the analyses carried out supported the
hypotheses proposed and derived from the research model in the previous chapter.
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CHAPTER 5: DISCUSSION
5.1 INTRODUCTION
This chapter discusses findings and results obtained from the data analyses carried out
in the previous chapter.
Respondents‟ levels of familiarity with e-commerce and usage in Nigeria and Sheffield
are discussed. Online shopping behaviours of respondents in both countries are also
compared to identify similarities and/ or differences. Finally, factors responsible for
changes in online shopping behaviours identified previously, are elucidated to give a
better understanding of why these changes exist.
5.2 ONLINE SHOPPING BEHAVIOURS
The research findings analysed in the previous chapter indicate a change in the use of
the Internet for e-commerce activities with emphasis on online shopping by respondents
in Sheffield compared with when they were in Nigeria. In terms of previous e-
commerce use by respondents, it was evident from the analysis that a large percentage
(79.2%) of respondents was familiar with e-commerce while in Nigeria, however, only
a fraction (34.7%) actually used it. These figures show that although the target
population in this study was considerably small in comparison with the Nigerian
populace, it was a valid representation of the level of e-commerce adoption in Nigeria
as suggested by previous studies (Folorunso et al., 2006; Adeyeye, 2008; Ayo, 2008).
Although most respondents reported using the Internet frequently while in Nigeria,
fewer respondents used the Internet for e-commerce activities as can be deduced from
Figure 4.6, which showed e-commerce activities ranking lowest amongst common
internet activities carried out with online shopping (and selling) being very minimal.
On the other hand, respondents reported 100% familiarity with e-commerce in Sheffield
with over 80% being active e-commerce users (see Figure 4.15). An increase in the use
of the Internet in Sheffield was also evident and more respondents engaging in e-
commerce activities, especially online shopping (see Figure 4.7).
5.2.1 Online Shopping Behaviours in Nigeria
The analyses showed that less than 10% of the total sample group shopped online while
in Nigeria even though a larger percentage searched for product information without
70
actual purchases (see Figure 4.10). This supports the findings from previous research
that Nigerians were willing to engage in online shopping but do not for different
reasons (Ajayi et al., 2008). The analyses also showed that most online shoppers were
infrequent shoppers who shopped less than three (3) times a year (see Figure 4.11). It is
therefore evident that majority of respondents were non-online shoppers while in
Nigeria and those who shopped online did so very rarely.
5.2.2 Online Shopping Behaviours in Sheffield
The analyses showed that majority (86.1%) of respondents shopped online in Sheffield
as opposed to the low percentage of online shoppers in Nigeria reported earlier. It could
also be deduced from the average number of online retail websites visited in a month
and time spent on online shopping activities per week that most respondents were
frequent online shoppers in Sheffield.
5.3 FACTORS RESPONSIBLE FOR CHANGE
From the analysis and discussion above, it is obvious that online shopping behaviours
of respondents had changed positively from non-shoppers and infrequent shoppers in
Nigeria to active and frequent shoppers in Sheffield. This change in behaviour had been
attributed to two (2) broad factors identified as; trust concerns and consumers‟
perceptions of technology.
5.3.1 Trust Concerns of Consumers
Trust concerns of consumers identified in this study relate to trust in web retailers and
include the following variables;
5.3.1.1 Privacy and Confidentiality
This refers to the belief consumers have that web retailers will keep information
(personal and/or transaction histories) private and confidential from third parties
(Hoffman et al., 1999). Although it is impossible to guarantee 100% privacy and
confidentiality in online environments, consumers expect web retailers to respect their
privacy and not misuse information given on their websites. This belief and expectation
fosters trust in web retailers and promote online shopping amongst consumers. From
the analyses, it was deduced that 61.4% of respondents considered privacy and
confidentiality as factors which hindered online shopping in Nigeria (see Figure 4.13).
This was as a result of the high level of cyber crime in Nigeria as discussed earlier.
71
Consumers are afraid to divulge information on the Internet because they cannot
ascertain the safety and privacy of their information. While in Sheffield, 50.7% of
respondents believed that information given in online environments was considerably
secure (though not completely) from third parties, and encouraged them to shop online
more in Sheffield (see Figure 4.21).
5.3.1.2 Authenticity of Products
This is the ability of the quality of goods and services displayed to be met the way it is
displayed on the Internet (Folorunso et al., 2006:2226). When consumers receive
products or services shopped online in the condition described on a retailer‟s website,
they tend to perceive the retailer as being credible which in turn leads to trust in the
retailer. The analyses showed that respondents did not trust the web retailers to deliver
products in the same state as displayed online while in Nigeria and still did not
completely have complete trust in Sheffield. This lack of trust could be due to biases
already formed before shopping online in Sheffield and showed that although
respondents were willing to shop online more frequently than they did in the past, they
still had reservations about getting the „expected‟ value for their money spent.
5.3.1.3 Data security and Credit card threat
Adeshina and Ayo (2010:6) define security as “the protection of information or systems
from unauthorised intrusions”. Perpetrators of such unauthorised intrusions include
hackers out to steal caches of credit card numbers which pose threats to consumers. The
more secure consumers feel about their payment details, the more they trust a web
retailer. On the other hand, if consumers believe their credit cards details are exposed to
unapproved access and/or use by web retailers, they could desist from shopping online
due to lack of trust (see Figure 4.50). The analyses supported this statement as majority
of respondents reported that data security and credit card threat were important factors
which hindered them from shopping online in Nigeria (see Figure 4.13). The issue of
cyber crime in Nigeria cannot be over emphasised when it comes to consumer trust in
online environments. With the alarming rate of cyber crime in the country and Nigeria
ranking third in the world, consumers are afraid of losing money to fraudsters who can
have access to their card details online. It is also important to note that respondents‟
views of data security and credit card threat while in Sheffield were not too different
from those previously formed while in Nigeria. Respondents were still wary about
providing card details when making payments online (see Figure 4.49) due to the nature
72
of their former environment (Nigeria) and the existence of cyber crime even in the UK
as discussed earlier.
5.3.1.4 Trust in online vendors
Trust as discussed earlier in this study, is the willingness of a consumer to be vulnerable
to web retailers (Pavlou, 2003). It has also been argued that the more trust consumers
have in web retailers, the more likely they are to shop online. These variables discussed
above all relate to trust in online vendors and from the analyses, it was deduced that
respondents regarded trust as a major factor when shopping online (see Figure 4.44). It
was also deduced that majority of respondents did not shop online while in Nigeria due
to lack of trust in online vendors (see Figure 4.45). This lack of trust could be due to
afore mentioned factors and although most respondents reported still not having
complete trust in online retailers while in Sheffield (see 4.51), majority of respondents
reported having more trust in using the Internet for online shopping in Sheffield
compared with when they were in Nigeria (see Figure 4.46).
It is therefore evident from the analyses, that respondents‟ trust in online shopping
which was previously nonexistent or minimal while in Nigeria, was growing gradually
leading to repurchases and continuous use in Sheffield. It is also important to note that
though respondents had not attained a level of total trust when shopping online, it was
obvious that they were willing to build the trust required to engage frequently in online
shopping and this is evident in the percentage increase in online shoppers in Sheffield
(86.1%) compared with Nigeria (less than 10%) . Hence the hypotheses H4 and H5
which state that “a consumer‟s trust towards online shopping has a positive effect on
his/her intention to use online shopping” and “a consumer‟s trust has a positive effect
on his/her actual usage of online shopping” respectively, were duly justified by the
analyses.
5.3.2 Consumers’ Perceptions of Technology
Perceptions of technology use, usefulness, accessibility, and reliability differ from
person to person and can be subjective to an extent. Therefore, the following variables
have been grouped together as consumers‟ perceptions of technology as they relate to
individuals;
73
5.3.2.1 Perceived Usefulness and Perceived Ease of Use
As discussed earlier, these variables explain that people are more likely to adopt and use
IT if they feel it is beneficial to them and easy to use (i.e. involves minimal effort).
Previous studies suggest that these variables are not necessarily interrelated (Childers et
al., 2001; Magal and Mirchandani, 2001). This implies that consumers could shop
online if they perceived it as being useful to them regardless of the efforts involved.
From the analyses, it was deduced that majority (74%) of respondents found online
shopping convenient for meeting their needs (see Figure 4.24) and this increased their
intention to shop online in Sheffield (see Figure 4.31). On the other hand, although
majority (62%) of respondents reported they would use a retailer‟s website for shopping
activities if they found it easy to use (see Figure 4.32), it was difficult reaching a valid
conclusion on the importance of perceived ease of use and actual usage by respondents
(see Figure 4.28).
It is therefore evident that respondents considered online shopping useful and found the
Internet easy to use for online shopping purposes, and these factors increased intention
to shop. Actual shopping also increased as a result of respondents‟ perceived usefulness
of online shopping, hence and the following hypotheses were justified by the analyses:
H1: “a consumer‟s perceived usefulness has a positive effect on his/her actual usage
of online shopping”
H2: “a consumer‟s perceived usefulness has a positive effect on his/her intention
towards online shopping”
H3: “a consumer‟s perceived ease of use has a positive effect on his/her intention to
use online shopping”.
5.3.2.2 Accessibility
Folorunso et al. (2006:2225) define accessibility as “the extent to which the needed
technologies for e-commerce are available for individuals to use”. One major factor
identified from the analyses in this study was accessibility to the Internet. Accessibility
to the Internet in Nigeria is very poor due to the cost of owning personal computers and
acquiring individual connectivity as explained earlier in this study, with a majority of
the population using cybercafés which are not convenient and secure for transacting
online. It is also common for people who work in large organisations to have access to
74
the Internet during working hours, but that only affords them about 8 hours of restricted
accessibility everyday and it is considered inappropriate to shop online while at work.
These restrictions and limitations in accessing the Internet affected respondents‟ online
shopping in Nigeria. In contrast, it is obvious that respondents had more access to the
Internet in Sheffield compared with when they were in Nigeria as the percentage of
everyday users increased from 49.3% (in Nigeria) to 97.3% (in Sheffield), thereby
increasing the number of online shoppers and frequency of online shopping.
Therefore, accessibility to the Internet was identified as one of the factors that affected
respondents‟ e-commerce use while in Nigeria and encouraged online shopping in
Sheffield (see Figure 4.22).
5.3.2.3 Network Reliability
This refers to the ability of communication networks to transfer data (confidential and
otherwise) consistently and safely over the Internet. Network reliability can be
compromised as a result of obsolete infrastructures (e.g. web servers, PCs), limited
bandwidth between consumers and Internet Service Providers (ISPs), poorly installed
applications, low speed networks such as dial up and frame relay, and many more
(Folorunso, 2006; Ajayi, 2008). As discussed earlier, most Nigerians use cybercafés to
access the Internet and most of these public businesses do not invest in first-class
communication networks due to cost and few excellent ISPs in the country.
Consequently, internet users do not get value for their money as they spend much time
achieving little online. However, in Sheffield most respondents had better connectivity
through wireless and broadband internet connections, hence increasing network
reliability which encouraged them to shop online (see Figure 4.21) more often.
These variables reflect consumers‟ perceptions of technology. Accessibility affects
perceived ease of use and perceived usefulness of the Internet to shop. Network
reliability also affects perceived ease of use. This study also suggests that the more
reliable consumers perceive a network to be, the more willing they are to transact on it.
This will in turn increase their perceived usefulness of online shopping and intention to
shop online thereby encouraging actual purchases. Hence the hypothesis H6 which
states that “a consumer‟s intention to shop online has a positive effect on his/her actual
usage of online shopping” was justified by the analyses.
75
On the other hand if a network is unreliable, consumers are discouraged from using it
and will not form regular online shopping habits.
5.4 SUMMARY
This chapter discussed findings and results obtained from the data analyses carried out
in the previous chapter.
Respondents‟ levels of familiarity with e-commerce and usage in Nigeria and Sheffield
were discussed and similar e-commerce trends identified in previous literatures were
observed. Online shopping behaviours of respondents in both countries were also
compared and differences based on frequency of use were identified. It was evident that
online shopping behaviours of respondents had improved significantly in Sheffield
compared with when they were in Nigeria.
Finally, factors responsible for changes in online shopping behaviours were identified
as trust concerns and consumer perceptions of technology. It was observed that
respondents had more trust using the Internet for online shopping in Sheffield and also
had more access to the Internet which increased their perceived usefulness of online
shopping. Network reliability also increased their intention to shop online and actual
purchases. These factors encouraged respondents to shop online more frequently in
Sheffield than they did while in Nigeria.
76
CHAPTER 6: CONCLUSION
6.1 INTRODUCTION
This chapter presents and evaluates the level of achievement of the aim and objectives
of the study. The main findings of the research and relationship of research to the
literature are discussed. Limitations of the research are also identified and
recommendations are proposed. Finally, suggestions for further research are made.
6.2 AIM AND OBJECTIVES
The aim of this study was to compare online shopping behaviours of Nigerian PGT
students in the University of Sheffield and their use in Nigeria, and to examine if factors
identified in previous research were responsible for any changes that might exist.
This involved studying online shopping behaviours of the target population in both
countries to identify similarities and/or differences in behaviour due to a change in
environment. To achieve this aim, the following objectives were developed and met;
To investigate if Nigerian students are familiar with e-commerce and what
they use it for;
To examine the extent to which they engage in online shopping while in
Sheffield compared with when they were in Nigeria;
To identify similarities and/or differences in their online shopping behaviours
in both countries;
To investigate why these similarities and/or differences exist;
To make recommendations based on the findings of the research.
These objectives were met by firstly carrying out an extensive literature review on e-
commerce in the UK and Nigeria. This served as the background for the study and is
reflective in Chapters 1 and 2. Factors hindering the full adoption and use of e-
commerce (with emphasis on online shopping) in Nigeria as identified in previous
literatures were examined and discussed to give a better understanding of online
shopping trends in Nigeria. Previous literatures on trust in online shopping were also
reviewed as trust was identified to be a major factor affecting online shopping in
Nigeria.
77
Secondly, a survey was carried out using questionnaires to investigate the extent of use
of e-commerce and online shopping by respondents while in Nigeria and Sheffield.
Several hypotheses were also proposed from the research model to satisfy the aim of
this study (Chapter 3).
In order to identify similarities and/or differences in respondents‟ online shopping
behaviours in both countries, the data obtained from the survey was presented and
analysed in Chapter 4. Factors identified in previous chapters were analysed through
quantitative analysis and hypotheses proposed were justified accordingly.
The analysis carried out in the previous chapter revealed vast differences in
respondents‟ online shopping behaviours in both countries and these differences were
discussed to give an in-depth understanding of why these differences existed (Chapter
5).
Recommendations based on findings are discussed in this chapter which focuses on
trust building, amongst other issues to encourage online shopping in Nigeria.
6.2 CONCLUSIONS
Having met the objectives set out to satisfy the aim of this study, it is necessary to
identify the main findings of the research and discuss how it relates to the literature.
6.2.1 Main Findings of Research
The findings of this study revealed that although majority of Nigerian PGT students in
the University of Sheffield were familiar with the concept of e-commerce while in
Nigeria, only a handful of them actually used e-commerce and fewer shopped online
while in Nigeria. However, a significant increase in number of e-commerce users and
online shoppers in Sheffield showed a change in behaviour amongst respondents.
The study also revealed that within a period of less than 12 months, these students who
were previously non-online shoppers while in Nigeria had become frequent and active
online shoppers in Sheffield using the Internet for meeting basic needs such as books,
wears, reservations, etc.
Factors responsible for lack of use by respondents while in Nigeria were identified as
trust concerns and personal constraints. Trust concerns identified included; Data
security, Privacy and confidentiality, Authenticity of products, and Credit card threat.
78
From the literature review it was evident that consumers in Nigeria lacked trust in using
the Internet for e-commerce activities especially online shopping due to the high rate of
cyber crime in the country. Personal constraints such as Computer Literacy, Income,
and Accessibility were also identified as factors responsible for the low level of e-
commerce adoption in Nigeria. The analysis showed that most respondents believed
they lacked adequate accessibility to the Internet to transact online, hence this was a key
factor impeding their use of the internet for online shopping purposes.
With clear distinctions in online shopping behaviours of respondents in both countries
identified, further findings revealed factors which fostered frequent online shopping in
Sheffield. These factors were identified as trust concerns and consumers‟ perceptions of
technology. The findings revealed that respondents had more trust using the Internet for
online shopping purposes in Sheffield compared with when they were in Nigeria and
this encouraged them to form shopping behaviours that were nonexistent or minimal
previously while in Nigeria. The findings also revealed that having more access to the
Internet encouraged respondents to shop online in Sheffield, which they found useful
for meeting their needs.
6.2.2 Relationship of Research to the Literature
Previous literature on e-commerce adoption and use in Nigeria discussed in the
literature review showed that the level of adoption in Nigeria is very low compared to
countries like the UK. This low level of adoption was attributed to several factors such
as establishing cost, substandard online payment methods, accessibility to the Internet,
lack of trust in web retailers, privacy and confidentiality, data security, network
reliability, poor technological infrastructures, credit card threat, authenticity of products,
citizen‟s income, cyber-crime, insufficient telecommunication facilities, and erratic
electric supply amongst others (Folorunso, 2006; Adeyeye, 2008; Ajayi et al. 2008;
Ayo et al., 2008; Egwali, 2009; Adeshina and Ayo, 2010).
This study produced results which were comparable with these previous literatures in
the following ways;
The low level of e-commerce reported amongst respondents in this study
was comparable to that observed in Nigeria by previous researchers. This
shows that although the target population in this research was a fraction of
79
the Nigerian population, the results obtained were true reflections of the
state of e-commerce use in Nigeria.
This study also showed similar trends in online shopping behaviours with
those suggested in previous literatures. It was discovered that previously
identified factors such as trust and consumer constraints (accessibility,
income, and computer literacy) were also responsible for these trends
amongst respondents.
Previous studies on e-commerce adoption and online shopping in Nigeria
examined trends within the country and the sample populations were
randomly chosen within specific locations in the country with emphasis on
e-commerce generally. However, this study took a step further by examining
e-commerce adoption by Nigerians living abroad (Sheffield).
The study revealed that a change in environment led to a change in online
shopping patterns of Nigerian Post Graduate Taught (PGT) students
currently studying in the University of Sheffield. This change in online
shopping behaviours was attributed to factors such as trust and accessibility
amongst others. It was also deduced that respondents were willing to shop
online in Nigeria if impeding factors discussed earlier were eliminated.
It is therefore evident that this study builds on previous research to
determine past online shopping behaviours of respondents in their home
country (Nigeria) which was minimal or inexistent and further shows
significant improvement in their behaviours due to a change in environment
(Sheffield).
6.3 LIMITATIONS
This research had several limitations which could have indirectly affected the quality of
results obtained.
6.3.1 Sampling
The sample size could be considered small compared to the Nigerian population.
Although the results obtained were similar to those reported in previous studies, a larger
sample size would have given a better basis for comparison. This would have required
sampling PGT students from other universities across the UK to obtain more data for
80
investigation. However due to time and cost constraints, it was only possible to sample
PGT students in the University of Sheffield.
6.3.2 Data Collection Process
A survey was used to collect data from respondents through questionnaires. There were
99 PGT students in the University of Sheffield but only 73 questionnaires were received
back. The questionnaires were distributed manually since the sample size was small and
to ensure prompt feedback. However, some respondents failed to return their
questionnaires and some students could not be reached due to their busy schedule. A
more effective distribution method could have been employed by using the University‟s
intranet in addition to manual distribution. In this way, more students would have been
reached (even though it is impossible to ascertain prompt responses) and the stress
involved in meeting each respondent would have been minimised.
Interviews could also have been conducted to give respondents the opportunity to
express themselves, thereby providing more in-depth knowledge on what they thought
was responsible for any change in their online shopping behaviours. However as
discussed earlier, it was easier and faster to collect data through questionnaires due to
time constraints.
6.3.3 Data Analysis
Using SPSS for data analysis was the best option in this study but some results could
have been flawed due to the researchers‟ inexperience in using the application.
Although functions such as Factor Analysis, Correlation Analysis, Bar charts and Pie
Charts were used to present and analyse data, other functions could have been
employed to carry out more tests and analysis.
6.4 RECOMMENDATIONS
The outcome of this study shows that Nigerians have different views about e-commerce
and online shopping when they experience a change in environment and are willing to
shop online if their environment encourages such activities. Hence, the following
recommendations have been proposed to improve online shopping behaviours in
Nigeria;
Accessibility to the Internet was identified as a major factor and this can be
improved if the ISPs in Nigeria provide cheaper internet services. This will
81
provide more individuals with affordable private connections at home and
reduce the current high dependency on cybercafés in the country.
It is also important for these ISPs to improve the quality of services provided
to customers by investing in recent technologies and equipments to ensure
network reliability.
Another major factor identified in this study was the issue of trust. The high
rate of cyber crime in Nigeria needs to be curbed and decreased significantly
by the government and people of the country. Effective policies and
legislations should be put in place to ensure safety in online environments
and cyber crime perpetrators should be prosecuted appropriately to serve as a
deterrent to others.
Finally, web retailers should make their websites safe and secure from
unwanted intrusions by putting efficient security measures in place to protect
consumers‟ data (personal, financial, and otherwise).
It is believed that if these recommendations are taken into consideration, the level of
online shopping and e-commerce adoption in Nigeria will increase significantly.
6.4.1 Suggestions for Further Research
This study compared online shopping behaviours of Nigerian PGT students in Sheffield
and their use in Nigeria, and examined if factors identified in previous research were
responsible for any changes that might exist. However, the study was limited to the
University of Sheffield, thereby limiting the scope of comparison. It would be more
comprehensive for further research to be carried out involving a larger sample size from
universities across the UK to determine if the results obtained in this study apply. The
method of data collection also needs to be broadened to include interviews to give a
better understanding of changes in online shopping behaviours due to change in
environment and what can be done to improve the situation in Nigeria.
6.5 SUMMARY
This chapter presented the levels of achievement of the aim and objectives of the study.
The conclusion of the study was made which included the main findings of the research
and relationship of research to the literature. Limitations of the research were also
identified and recommendations based on results obtained in the study were proposed.
Finally, suggestions for further research were made.
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APPENDIX I: QUESTIONNAIRE
I understand that my participation is voluntary and I am free to withdraw at any time
without giving any reason.
I understand that my responses will be anonymous during the whole research project
and after that.
I agree to take part in this research project and partake in any related interview if
necessary.
Please note, all questions marked (*) are common to every participant.
==============================================================
SECTION A: PERSONAL INFORMATION
*1. Sex
(a) Male (b) Female
*2. For how long have you been in Sheffield?
*3. Did you have any previous work experience before coming to Sheffield (NYSC
inclusive)?
(a) Yes (b) No
SECTION B: RELATED QUESTIONS
E-commerce (Electronic commerce) is the buying and selling of products,
information and/or services on the Internet and other online services (Kalakota and
Whinston (1996:3).
*4. How often did you use the internet while in Nigeria?
(a) Everyday
(b) 3 or 4 times a week
(c) Twice a week
(d) Once a week
(e) Very rarely
*5. How often do you use the internet now in Sheffield?
(a) Everyday
(b) 3 or 4 times a week
(c) Twice a week
(d) Once a week
(e) Very rarely
92
*6. What did you use the internet for while in Nigeria? Please tick relevant
answer(s).
(a) Information (Yahoo, Google, etc)
(b) Social Networking (Facebook, Bebo, etc)
(c) Communication (Skype, Yahoo messenger, etc)
(d) Transfer of files
(e) Entertainment (Youtube, downloading movies, etc)
(f) Online education
(g) Internet Banking (Money transfers, checking bank statement, etc)
(h) e-mail (Yahoomail, Hotmail, AOL, etc)
(i) Shopping (buying online)
(j) Selling (selling things online)
(k) Others, please specify
*7. What do you use the internet for now in Sheffield? Please tick relevant
answer(s).
(a) Information (Yahoo, Google, etc)
(b) Social Networking (Facebook, Bebo, etc)
(c) Communication (Skype, Yahoo messenger, etc)
(d) Transfer of files
(e) Entertainment (Youtube, downloading movies, etc)
(f) Online education
(g) Internet Banking (Money transfers, checking bank statement, etc)
(h) e-mail (Yahoomail, Hotmail, AOL, etc)
(i) Shopping (buying online)
(j) Selling (selling things online)
(k) Others, please specify
*8. Have you heard about E-commerce before coming to Sheffield?
Yes (please go to Question 9) No (please got to question 12)
9. Have you used E-commerce before coming to Sheffield?
Yes (please go to Question 10 & 11) No (please got to question
13)
93
10. What did you use E-commerce for while in Nigeria? Please tick relevant
answer(s)
(a) Money transfers (i.e. online banking)
(b) Online shopping
(c) Searching for product information
(d) Paying bills
(e) Others, please specify
11. How frequently did you shop online while in Nigeria?
(a) Once a year
(b) Two or three times a year
(c) Monthly
(d) Daily
(e) Never
12. Are you familiar with E-commerce now since you come to Sheffield?
Yes (Please go to Question 14) No
*13. Which of these factors BEST affected your use in Nigeria? Please tick relevant
answer(s)
(a) Accessibility to the internet
(b) Privacy and Confidentiality of personal information
(c) Level of Income
(d) Authenticity of products displayed
(e) Data Security
(f) Internet Usage Proficiency
(g) Network Reliability
(h) Credit Card Threat
(i) Computer Literacy
(j) Few online vendors (retailers)
(k) Others, please specify
*14. What do you use E-commerce for now in Sheffield? Please tick relevant
answer(s)
(a) Money transfers (i.e. online banking)
(b) Online shopping
(c) Searching for product information
94
(d) Paying bills
(e) Others, please specify
*15. How frequently do you use E-commerce now in Sheffield?
(a) Once a year
(b) Two or three times a year
(c) Monthly
(d) Daily
(e) Never
*16. On average, how many different online retail websites do you visit in a given
month (Choose only one)?
(a) None
(b) 1-2
(c) 3-5
(d) 6-20
(e) over 20
*17. In general, how much time do you spend doing online shopping activities per
week (Choose only one)?
(a) 0-5 minutes
(b) 6-15 minutes
(c) 16-60 minutes
(d) over 60 minutes
*18. What products do you MOSTLY shop online for?
(a) Books
(b) Grocery
(c) Wears (clothes, shoes, accessories etc)
(d) Reservations (Travel tickets, Take outs, Hotels, etc)
(e) Entertainment (Music, Movies, Games, etc)
(f) Electronics
(g) Others, please specify
*19. Would you say you do more online shopping now in Sheffield compared with
when you were in Nigeria?
(a) Strongly agree (b) Agree (c) Neutral (d) Disagree (e)
Strongly disagree
*20. Which of these factors have encouraged you to engage in online shopping now
in Sheffield (Choose only two)?
(a) Accessibility to the internet
(b) Privacy and Confidentiality of personal information
(c) Trust in online vendors (retailers)
95
(d) Authenticity of products displayed
(e) Data Security and Credit Card Threat
(f) Perceived eased of use
(g) Network Reliability
(h) Perceived usefulness
(i) Others, please specify
SECTION C:
*21. Would you say you use E-commerce more since coming to Sheffield compared
with when you were in Nigeria?
(a) Yes (b) No
96
If you feel there are other factors not covered above, please provide further details of
reasons why your online shopping behaviour has changed in Sheffield in comparison
with when you were in Nigeria.
Strongly
Agree
Agree Neutral Disagree Strongly
Disagree
Perceived Usefulness
1. Having more access to the Internet enables me
to shop more often than previously.
2. Using the Internet makes it easier and quicker
for me to shop.
3. I find shopping online convenient for meeting
my needs.
Perceived Ease of Use
4. I found it difficult to learn how to use the
Internet to do my shopping activities.
5. I took a long time to learn to use the Internet to
do my shopping activities.
6. I find it easy to locate the information that I
need in this retailer‟s Web site.
7. I shop online more frequently in Sheffield
because I find the Internet easier to use now.
Intention to Use
8. I have always wanted to use the Internet for
my shopping activities in addition to traditional
methods in Nigeria.
9. I would use the Internet for my shopping
activities in addition to traditional methods in
Nigeria if I trust a retailer‟s website.
10. I would use the Internet for my shopping
activities because I find online shopping very
useful.
11. I would use a retailer‟s website for my
shopping activities because I find it easy to use.
12. Overall, I like using the Internet for my
shopping activities.
Trust
13. Trust is a major factor when shopping online.
14. The main reason I did not use the Internet for
online shopping in Nigeria was lack of trust in
retailers.
15. I have more trust in using the Internet for
online shopping in Sheffield.
16. I feel unsafe about providing personal details
when shopping online.
17. I trust the authenticity of products displayed
on retailers‟ websites.
18. I feel uncomfortable providing card details
when making payments in online environments.
19. A breach in data security will put me off
online shopping completely.
20. From online shopping experiences in
Sheffield, I have complete trust in retailers.
21. Trust will lead to repurchasing from a
particular vendor (retailer)
APPENDIX II: CORRELATION MATRIX 1
98
APPENDIX III: TOTAL VARIANCE EXPLAINED 1
99
APPENDIX IV: CORRELATION MATRIX 2
100
CORRELATION MATRIX 2 (Cont’d)
101
APPENDIX V: TOTAL VARIANCE EXPLAINED 2