Ict in Banking in Uganda
-
Upload
james-baguma -
Category
Documents
-
view
63 -
download
2
Transcript of Ict in Banking in Uganda
INFLUENCE OF ICT ON THE BANKING INDUSTRY: THE CASE OF KAMPALA
BY
A Dissertation Submitted to the School of Graduate Studies in Partial Fulfillment for the Award of Master of Science
in Computer Science Degree of Makerere University
Option: Management Information Systems
August, 2007
Declaration
published and/or submitted for any other degree award to any other University before.
Signature...................................... Date:..........................................
Department of Information Systems
Faculty of Computing and Information Technology
Makerere University
Approval This dissertation has been submitted for Examination with the approval of the following
supervisor.
Signature........................................ Date:............................................
Dr. Patrick Ogao, PhD
Department of Information Systems
Faculty of Computing and Information Technology
Makerere University
i
I james baguma, do hereby declare that this dissertation is original and has not been
JAMES BAGUMA
Dedication To God (The Father, The Son and The Holy Spirit).
ii
Acknowledgements
The completion of this dissertation would have been a myth if assistance was not
rendered. Therefore, I would like to thank the Lord God Almighty who gave me the
wisdom and everything that I needed throughout the period of my course.
I would like to extend my heartfelt gratitude to Dr. Patrick Ogao, Dr. Bakkabulindi
F.E.K. (East African Institute of Higher Education and Development) and Mr. Bissaso
Ronald (East African Institute of Higher Education and Development) who put in endless
time and effort to ensure that I finish successfully.
I would like to appreciate the entire staff of Faculty of Computing and Information
Technology for their resourceful guidance and encouragement during my course of study.
Special thanks go to the following students Mrs. Mwangye Joyce Besigye, Mr. Tibaijuka
Tom, Mr. Moini Fred, Ms. Nakakawa Agnes and Mr. Semalulu Paul who have been very
supportive to me.
iii
Contents Declaration ………………………………………………………………………………..i
Approval………………………………………………………………………………..….i
Dedication………………………………………………………………………………....ii
Acknowledgement………………………………………………………………………..iii
Table of contents………………………………………………………………………….iv
List of tables……………………………………………………………………………..vii
List of figures……………………………………………………………………………viii
Acronyms…………………………………………………………………………………ix
Abstract …………………………………………………………………………………..x
Chapter One
1. Introduction 1
1.0 Introduction…………………………………………………………………………....1 1.1 Background……………………………………………………………………………1 1.1.1 Theoretical background…………………………………………………………...1 1.1.2 Conceptual background…………………………………………………………...2
1.1.3 Contextual background……………………………………………………………3
1.2 Problem Statement…………………………………………………………………….4
1.3 Purpose………………………………………………………………………………...5
1.3.1 Specific Objectives of the Study…………………………………………………….5
1.3.2 Hypotheses…………………………………………………………………………..5
1.4 Scope…………………………………………………………………………………..6
1.5 Justification……………………………………………………………………………6
1.6 Outline of the dissertation…………………………………………………………......6
1.7 Contribution of the dissertation…………………………………………………...…..7
1.8 Chapter summary…………………………………………………………………….7
iv
Chapter Two
2. Literature Review 8
2.0 Introduction ………………………………………………………………………......8
2.1 Theoretical review………………………………………………………………….....8
2.2 Conceptual framework………………………………………………………………..9
2.3 Review of related literature………………………………………………………......11
2.3.1 E-funds transfer technology and its influence on the banking industry………......11
2.3.2 Telephone banking technology and its influence on the banking industry……….15
2.3.3 Internet banking technology and its influence on users in the banking industry…17
2.4 Chapter summary…………………………………………………………………….21
Chapter Three
3 Methodology 22
3.0 Introduction………………………………………………………………………......22
3.1. Research design…………………………………………………………………......22
3.2 Study population…………………………………………………………………......22
3.3 Sampling procedure………………………………………………………………….23
3.4 Data collection method and tool…………………………………………………….23
3.4.1 Questionnaire method……………………………………………………………24
3.4.2 Self-administered questionnaire………………………………………………….24
3.5 Quality of research tool………………………………………………………………24
3.51 Validity of the SAQ………………………………………………………………25
3.5.2 Reliability of SAQ……………………………………………………………….26
3.6 Data processing and analysis………………………………………………………...26
3.7 Chapter summary…………………………………………………………………….27
Chapter Four
4. Data presentation, analysis and interpretation 28
4.0 Introduction………………………………………………………………………......28
v
4.1 Description of background variables………………………………………………...28 4.1.1 Employment status by sex……………………………………………………......29
4.1.2 Bank of respondent by account……………………………………………………30
4.1.3 Salary level by age Table 4: Salary level by age………………………………….32
4.2 How the dependent variable varies according to the background variables…………33
4.2.1 Banking industry and employment status………………………………………...34
4.2.2 Banking industry and sex………………………………………………………….35
4.2.3 Testing for variations between banking industry and age………………………...36
4.2.4 Testing for variations between banking industry and type of account…………….38
4.2.5 Testing for variations between banking industry and salary level…………………40 4.3 Verification of hypotheses…………………………………………………………...42
4.3.1 Factor analysis……………………………………………………………………42
4.3.2 Relationship between constructs……………………………………………….....47
4.3.3 Influence of e-funds transfer technology on the banking industry in Kampala…...48
4.3.4 Influence of telephone banking technology on the banking industry in
Kampala………………………………………………………………………………….49
4.3.5 Influence of Internet banking technology on the banking industry in Kampala…..
……………………………………………………………………………………………50
4.3.6 ICT and the banking industry in Kampala…………………………………….......51 4.4 Chapter summary…………………………………………………………………….52
Chapter Five
5 Discussions, conclusions, recommendations, limitations and further work 53
5.0 Introduction………………………………………………………………………......53
5.1 Discussion……………………………………………………………………………53
5.2 Conclusions………………………………………………………………………......54 5.3 Recommendations……………………………………………………………………55
5.4 Limitations…………………………………………………………………………...57
5.5 Further work…………………………………………………………………………57
5.6 Chapter summary.........................................................................................................57
5.7 References 58
vi
Appendices
5.8 Appendix A 68
5.8.1 Questionnaire for individual bank customers
5.9 Appendix B 73
5.10.1 Letter to research expert
6.0 Appendix C 74
6. 1 Codebook for individual bank customers in Kampala
7.0 Appendix D 80
7.1 Data entry form………………………………………………………………….80
vii
List of tables Table 1: Simulations of Cronbach's alpha……………………………………………….26
Table 2: Employment status by sex……………………………………………………...29
Table 3: Bank of respondent by account………………………………………………... 30
Table 4: Salary level by age …………………………………………………………......32
Table 5: Independent t-test: employment status and banking industry…………………. 34
Table 6: Independent t-test: sex and banking industry………………………………......35
Table 7: One-way ANOVA: variations of age according to banking industry…………. 36
Table 8: Duncan multiple range test-Post hoc test for cash withdrawal…………………37
Table 9: One-way ANOVA: variations of type of account according banking industry
……………………………………………………………………………………………38
Table 10: Duncan multiple range test-Post hoc test for cash deposit……………………39
Table 11: One-way ANOVA: variations of salary level according to banking
industry………………………………………………………………………………......40
Table 12: Duncan multiple range test-Post hoc test for cash withdrawal………………..41
Table 13: Rotated component matrix: E-funds transfer technology……………………. 43
Table 14: Rotated component matrix: Telephone banking technology………………….44
Table 15: Rotated component matrix: Internet banking technology…………………… 45
Table 16: Correlation matrix: ICT constructs-banking industry…………………………47
Table 17: Model 1-E-funds transfer technology and the banking industry………….......48
Table 18: Model 2-Telephone banking technology and the banking industry…………..49
Table 19: Model 3-Internet banking technology and the banking industry……………...50
Table 20: Model 4-ICT and the banking industry……………………………………….51
viii
List of figures Figure 1 Conceptual framework…………………………………………………………10
Figure 2 New model of ICT and the banking industry in Kampala……………………...56
ix
Acronyms ATM -Automatic Teller Machine or Automated Teller Machine
E-banking -Electronic Banking
E-commerce -Electronic Commerce
E-funds transfer -Electronic Funds Transfer
ICT -Information Communication Technology
IT - Information Technology
M-banking -Mobile Banking
SMS - Short Message Services
x
Abstract The research aimed at establishing the influence of ICT on the banking industry because
there was an empirical desire to investigate how ICT is related to the banking industry in
Kampala. The research was carried out using quantitative, qualitative, correlational and
case study research structure. Findings revealed that telephone banking had a high
predictive potential compared to e-funds transfer and Internet banking technologies. It
was concluded that the predictive potential of ICTs on the banking industry in Kampala is
still low 54%. This therefore implies that there is less integration of ICTs in the banking
industry in Kampala. It was recommended that there is need for bank managers to
embark on user awareness, implementation and monitoring and evaluation of what is
implemented bearing in mind that it requires high financial investment and a critical plan.
In a nutshell, this research is an empirical model that specifically dealt with e-banking
technologies thus a paramount contribution in the field of e-commerce.
xi
CHAPTER 1
INTRODUCTION
1.0 Introduction This chapter is the introductory part of the study and covers the background, problem
statement, purpose, specific objectives, hypotheses, scope, justification and outline of
the dissertation. This chapter is basically the preamble of the study and is very
significant in highlighting the theoretical issue or problem and provides a platform for
understanding it.
1.1 Background The background is subdivided into the theoretical background, conceptual and
contextual background. The theoretical background gives the importance of ICT to the
banking industry hence linking the two variables; the theoretical background also gives
a highlight on the theory underpinning the research. The conceptual background
explains the operational terms that is ICT and the banking industry and the contextual
background explains the situation of ICT in relation to the banking industry,
highlighting the problem.
1.1.1 Theoretical background Before the emergence of ICT, brick and mortar banks were the key to banking.
However, technological innovations have influenced the banking sector in one way or
another. Kassim (2005) [42], explains that the technological revolution has produced
new developments in the banking industry. It is no doubt that ICT is now a very
strategic issue in the banking realms (Kobrin, 2001) as reported by Vij (2003) [77].
Significant development in ICT has paved way for banking applications such as
1
electronic funds transfer and telephone banking. The development in the banking
industry also incorporates the use of the global network (Internet), which can be
accessed by anyone at any time (Basel Committee on Banking Supervision, 2001) [10].
According to Quirós (2002) [66] and Ayadi (2003) [6], the use of electronic payment
means and increase in customer connection to the Internet eliminates geographical
constraints and customers may not need to access banks physically, implying that
customers can have access to banking services in any area at any time. Further more,
Harris and Spence (2002) [27] argue that new ICT has created new commercial
opportunities. The theory underpinning this research is Rogers' (2003) Diffusion of
Innovations Theory. This theory suggests that whenever there is a new innovation there
is a social change depending on the level of adoption. Rogers (2003) argues that several
studies have explained the causes or failures of ICT innovations. This is why the study
seeks to investigate the influence of ICT on the banking industry in Kampala.
1.1.2 Conceptual background Rogers conceptualises an innovation as a social change (Rogers, 2003). ICT is seen as
an innovation adopted by the banking industry. According to Gottschalk and Andersen
(2001) [25], ICT is an umbrella term that covers computer hardware, software,
communication and network systems. In this study the term ICT signifies the provision
of banking products and services electronically in form of e-funds transfer technology,
telephone banking technology and Internet banking technology, in other-words e-
banking. E-funds transfer technology focussed on ATMs, credit and debit cards and e-
cheques, telephone banking technology focussed on Interactive Voice Response (could
be wired or wireless in nature) and Internet banking focussed on the Internet and its
applications such as websites and e-mail.
United States Department of Labor (2005) [76], posits that the banking industry is an
entity that constitutes banks which safeguard the money and valuables and provide
loans, credit, and payment services, such as chequing accounts, money orders, and
cashier's cheques. Banks may also offer investment and insurance products. United
States Department of Labor (2005), further explains that banks are primarily meant to
2
accept deposits and lend funds from the deposits made by users. In respect to this
research the banking industry is viewed in terms of the cash deposits, cash withdrawals
and account balance inquiry.
1.1.3 Contextual background In 1993, Bank of Uganda designed a website intended to disseminate banking
information (Kasita, 2004 September 21) [41]. In 1997, Standard Chartered Bank
introduced the first ATMs in Uganda and other banks followed (Monitor Reporter,
2004 August 16) [51]. By 2001, there was continued progress being made in Uganda in
the use of ATMs in Kampala City due to ATM establishments. It was hoped that the
risk of money transfer from location to location would be reduced. There was growing
optimism in the banking industry that VISA credit cards would also be introduced to
ease clients' access to cash from their accounts (Kakembo, 2001 December 6) [34]. In
2004, Bankom a local electronic financial transaction services company in Uganda
switched to the use of ICT in which mobile phones could also be used to pay bills
(Kanyegirire, 2004 January 8) [37]. According to Mwebya, as reported by Ssettumba
(2004 November 30) [70], a payment system in which the transfer of funds is done
electronically was introduced in Bank of Uganda in 2004. The installed Electronic Fund
Transfer Direct Debit System enabled known customers from utility companies to
instruct their companies to deduct cash from their accounts and transfer it to the bank
account of the utility company. This was done as a means to aid non-cash transactions
through the banking system with an aim of making cash transfers efficient, fast and
secure which may sort of improve the system.
In 2005, credit cards were on the increase and came with several advantages such as
avoiding to carry cash physically. However, if the user of the credit card is not
conscious about security, then chances that unauthorized withdrawal of cash from a
user's account might be carried out by a malicious person (Kahyana, 2005 February 19)
[32]. According to Musoke., the head of Corporate Affairs (Standard Chartered Bank)
as reported by Ministry of Tourism and Industry (2005 September 2) [50], Standard
Chartered Bank was probing a multi-million unsecured loan scam involving fraudsters
3
masquerading as Mulago Hospital employees. Between July 11th and September 8th
2005; the fraudsters had secured loans that were intended for Mulago Hospital
employees. The amount in the fraud case was $135,000, about 250 Ugandan million
shillings. Stanbic Bank introduced pre-fabricated ATMs to reduce the queues at their
access points (Nabayunga, 2006 April 18) [56]. Today ICT has diffused according to
indicators such as the use of ATMs, debit and credit cards, telephones, mobile phones
and web sites. However no body has quantified it to explain its influence on the
banking industry particularly in Kampala, hence suggesting a need to establish the
influence of ICT on the banking industry in Kampala.
1.2 Problem Statement The emergent ICT in Kampala is characterised by the use of technologies such as
ATMs, telephones, mobile phones and websites. ICT is an innovation that has left a
query within the banking industry; much as it carries some benefits in some banking
institutions, on the other hand it seems to create some threats. For example, as observed
in the contextual background, the scenario in Standard Chartered Bank case in which
$135,000 about 250 Ugandan million shillings was embezzled. Coupled to this is the
fact that some people assert that ICT has led to increased queuing at ATM machines
which wastes a lot of time and seems no different from the former way of withdrawing
funds from the banks (Tabaza, 2006 April 2) [73]. Therefore one wonders how ICT has
influenced the banking industry in Kampala. It is therefore imperative for the researcher
to establish the influence of ICT on the banking industry in Kampala.
4
1.3 Purpose The study aimed at establishing the influence of ICT on the banking industry in
Kampala.
1.3.1 Specific Objectives of the Study The specific objectives of the study were:
i. To identify the influence of e-funds transfer technology on the banking industry in
Kampala.
ii.To identify the influence of telephone banking technology on the banking industry in
Kampala.
iii.To identify the influence of Internet banking technology on the banking industry in
Kampala.
1.3.2 Hypotheses The study hypothesised the following statements:
i. The influence of e-funds transfer technology on the banking industry in Kampala has
been positive (H1).
ii. The influence of telephone banking technology on the banking industry in Kampala
has been positive (H2).
iii. The influence of Internet banking technology on the banking industry in Kampala
has been positive (H3).
5
1.4 Scope Geographically the study took place in Kampala because it is where majority of the
banking institutions are located. Conceptually the study assessed the influence of ICT
(conceptualised as e-funds transfer, telephone banking and Internet banking
technologies) on the banking industry (conceptualised as cash deposit, cash withdrawal
and account balance inquiry). The sample space included individual customers in
Kampala.
1.5 Justification The research enlightens the banking institutions on how ICT has influenced its
individual customers in Kampala. The study is potends to policy makers such as the
Government of Uganda for implementation of policies geared towards the influence of
ICT on the banking industry. The study is provides knowledge that may be adopted by
society, especially researchers interested in ICT application within the banking
industry.
1.6 Outline of the dissertation This dissertation comprises five chapters. Chapter one covers an introduction,
background, problem statement, purpose, objectives, research questions, hypotheses,
scope, justification and the outline of the dissertation. Chapter two covers an
introduction, the theoretical review conceptual framework and review of literature.
Chapter three covers an introduction, research design, study population, sampling
procedure, data collection method and tool, quality of research tool, research procedure
and data processing and analysis. Chapter four covers an introduction, presentation,
analysis and interpretation of data and chapter five covers an introduction, discussions,
conclusions, recommendations, limitations and further work. Every chapter is crowned
with a summary.
6
1.7 Research contribution The study has put forward a new model that explains the predictive potential of ICT on
the banking industry with focus on ATM services and telephone services. The
conceptualisation of ICT and the banking industry is also a unique contribution of the
research.
1.8 Chapter summary This chapter is rather the preamble of the research. It basically gives the background,
purpose, objectives, scope and justification and finally crowned by the dissertation
outline, which indicates the chapters in the report. Without this chapter the research
cannot precede hence the gateway to the other chapters of the research.
7
Chapter 2 Literature Review 2.0 Introduction This section entails the theoretical review, conceptual framework and the review of
literature. This section expands on the theory used in the research as explained in the
theoretical background. It also expands on the concepts given in the conceptual
background to build the conceptual model and finally explains views of different
researchers, which are related to the study. Basically this chapter is based on views of
different researchers, which are conceptualised by the researcher to get a directed path
for this research.
2.1 Theoretical review In this study Rogers' Diffusion of Innovations Theory (DOI) has been adopted. An
influence can be termed as weight to something which can be interpreted as positive or
negative. According to Rogers (2003), in his Diffusion of Innovations Theory,
consequences are changes that appear in an individual or social system as a result of the
adoption or rejection of an innovation. In this case one of the variables can be used to
predict another. Rogers (2003) argues that in order for one to understand consequences,
a three dimensional approach is very important which includes: desirable versus
undesirable, direct versus indirect and anticipated versus unanticipated outcomes.
This study focused on the desirable and undesirable dimension implying a negative or
positive effect. It should be noted that Rogers (2003) discusses consequences of
innovations, which are also important in explaining the influence of ICT on the banking
industry. Other researchers who have used this Theory include: Surry and Farquhar
(1997) [72] in their study entitled Diffusion Theory and Instructional Technology;
8
conclude that diffusion theories are of great benefit to instructional technology and
Singh et al (2003) [69] who in their study entitled the Dynamics of Innovations in E-
banking found out that the diffusion of network systems and distributed systems
resulted in radical innovations such as ATMs and Internet banking. Unlike Surry and
Farquhar (1997) and Singh et al (2003) and other authors who have used Roger's DOI
theory, this study specifically focused on the influence of ICT on the banking industry
in Kampala.
2.2 Conceptual framework/model Basing on Rogers' (2003) and Bakkabulindi (2006), ICT in this research is
conceptualised as an innovation adopted by the banking industry. The desirable and
undesirable dimensions signify the positive and negative dimensions of the influence of
ICT on the banking industry basing on the data collected from the field. It is presumed
that if ICT influences the banking industry the dimension (direction) of influence may
be positive or negative.
9
Conceptual framework/model relating ICT to the banking industry
Independent variables (ICT)
E-funds transfer technology (ATM, credit, debit card and e-cheques services
Dependent variable (Banking industry)
Figure 1: Source: Adopted from Rogers, 2003, Diffusion of innovations. New York:
Free Press and Bakkabulindi, F. E. K. 2006. Social correlates of innovation
diffusion/adoption in organizations: the case of Makerere University. Unpublished
PhD. (Educational planning, management and administration) thesis, Makerere
University, Kampala, Uganda.
Independent variable
From the conceptual framework/model, the independent variable is conceptualised as
ICT and subdivided into e-funds transfer, telephone banking and Internet banking
-Availability -Accessibility -Use
Telephone banking technology (Wired and wireless services) -Availability -Accessibility -Use
Cash deposit -Convenience -Speed -Security Cash withdrawal -Convenience -Speed -Security Account balance inquiry -Convenience
Internet banking technology (e-mail and website services)
-Speed -Security
-Availability -Accessibility -Use
10
technologies. Each of the three technologies (E-funds transfer, telephone banking and
Internet banking technologies) has the following indicators: availability, accessibility
and use.
Dependent variable
From the conceptual framework/model, the banking industry is conceptualised as the
dependent variable because it is the one affected by ICT (e-funds transfer, telephone
banking and Internet banking technologies). The banking industry is conceptualised as
cash deposit, cash withdrawal and account balance inquiry. Each of these three
components was appraised on convenience, speed and security. Hence the influence of
ICT on the banking industry was assessed in terms of whether it has positively affected
the convenience, speed and security on the banking industry or otherwise.
2.3 Review of related literature
This section entails literature related to the three objectives of the study so that the
information gathered is relevant to the study and to create consistency and uniformity
hence giving readers a clear picture of what is being researched on. The section
includes empirical or past studies revealing the gaps that were left in the given studies.
The section also explains opinions of past researchers that are appropriate in
understanding the problem.
2.3.1 E-funds transfer technology and its influence on the banking industry ATMs have extended banking services to the remote areas depositing and withrawal of
funds can be carried out in rural areas in Ghana, (Morris-Cotterill, 2002) [52]. This has
enabled loading and unloading of cash in small communities or in widespread
communities where people gather, however real cash ATMs for general use and deposit
would require more servicing and more security (Morris-Cotterill, 2002). Cracknell
(2004) [19], opined that Malawi Central Bank established a smart card infrastructure
with biometric enabled ATMs with an aim of reducing insecurity with in the banking
11
industry, with the use of such developments on the ATMs, withdrawal and depositing
of cash is now done safely thus yielding positive results. According to the Glossary of
Terms Used in Payment Settlement Systems as reported by Anguelov et al (2004) [4] e-
funds transfer is defined as the movement of money or credits from one account to
another through an electronic medium. According to a Survey of Consumer finances
(2001) as reported by Anguelov (2004) e-funds transfer has features such as direct
deposit, an ATM or debit card among the rest. In this study e-funds transfer technology
means the availability, accessibility and usage of ATM cards, debit cards, credit cards
and e-cheques with reference to cash deposit, cash withdrawal and account balance
inquiry.
Several researchers indicate that the use of e-funds transfer technologies such as ATMs
and e-cheques have shown positive response. For example (Wucker, 2004) [80],
explained that in Latin America, migrant workers use ATMs to send money home in
which members of their families can easily withdraw funds. This therefore makes it
easier for the migrant workers to send cash easily to their families at cheaper costs
through the use of banking services. In this way customers are able to withdraw and
deposit cash easily as compared to the former days when the use of such services was
not available. Gourlay and Pentecost (2005) [26] explain that funds are transferred
electronically using ATMs to provide retail banking services allowing 24, hours a day
cash withdrawal, balance verification and bill payment at branches and remote
locations away from branches. ATMs in the UK are seen as a substitute capital for
labour particularly in routine human teller operations. Transaction costs associated with
need to withdraw cash unexpectantly are lowered, (Ingham and Thompson, 1993;
Hamphrey, 1994; Haynes and Thompson, 2000 as reported by (Gourlay and Pentecost,
2005).
ATMs are widely used in transfer of cash. They are mainly located at shopping stations
to help customers in carrying out shopping easily (Organisation for Economic
Corporation and Development, 2003) [62]. For example in Japan, Ito -Yokado Stores is
planned to provide banking services through its stores. It is worth noting that electronic
12
transactions can be carried out using e-cheques and e-cash for large amounts of money.
There are positive results noted in the use of e-funds transfer with increased use of
ATMs and e-cards. According to the Australian Bankers Association (2002) as reported
by Arch and Burmeister (2003) [5], in Australia emphasis is placed on e-banking
technologies. It was also noted that Australians with visual impairment were introduced
to audio-enabled ATMs, through an initiative jointly supported by the National
Australian Bank's
ATM supplier (Diebold) and Blind Citizens Australia. The first of these was installed at
the Royal Victorian Institute for the Blind premises. This implies that use of e-funds
transfer technology in Australia has enabled the banking industry to provide services to
its clients because even the blind can deposit and withdraw their money from the
banking institutions hence indicating a desirable dimension. While the above authors
give their views on ICTs their concentration is on ATMs rather than technologies such
as credit cards and debit cards. Berger (2002) [13], studied Technological Progress and
its Effects on the Banking Industry in the US. It was noted that IT-based delivery
systems like ATMs led to improvements in the bank performance and consolidation of
the industry during the deployment of technologies (Berger, 2002). Berger, (2002)
further posited that, to establish links between technological progress and the
productivity growth of the banking industry and industry structure multivariate analysis
should be used. Despite the contribution of the above study, the influence of ICT on
users in the banking industry in Kampala can be established by an empirical approach
that the study seeks to use.
In Uganda, while ATMs are found to have some set backs such as limited amount of
functionality, queuing and shutting down when they are empty, they have caused an
aggressive competition among banks, which has been claimed to have strengthened the
banking culture in Uganda (Batanda, 2001 April 11) [12]. The information given by
(Batanda, 2001 April 11) is not quantified and the approach followed is not elaborated,
hence motivating the current study to take place and establish the influence of ICT on
the banking industry in Kampala. Coupled to this is the fact that ATMs are not the only
13
technologies of e-funds transfer other technologies such as credit and debit cards need
to be studied to establish true influence of e-funds transfer on the banking industry in
Kampala.
Karin et al (2005) [38] studied Evaluating the Efficacy of Credit Card Regulation in
USA and used the elaboration likelihood model to explore how consumers might
respond to the revised credit card disclosure requirements, focusing specifically on
college students. Random selection approach was used and it was noted that college
students possessed a fairly low level of knowledge of credit cards thus are not very well
equipped to make educated choices concerning such cards. While Karin et al (2005)'s
sample of interest was limited to college students, the sample of interest in this research
was open to any individual customer in Kampala and the technologies studied did not
only include credit cards but also included ATM and debit cards among other
technologies. Rugimbana (1995) [68] studied Predicting Automated Teller Machine
Usage, the Relative Importance of Perceptual and Demographic factors in Australia.
The main purpose of his study was to discriminate users from non-users, using the
demographic variables of respondents and their perceptions of ATM attributes in order
to assess the relative importance of these predictor variables. The study, which was
based on a survey of 430 retail banking consumers, found that perceptual variables
were far more successful as predictors of ATM service usage than respondent
demographic variables. While Rugimbana (1995) used ATMs as a criterion variable,
ATMs are used as a predictor variable of the banking industry in this study.
Inyaga (2002) [31] carried out a study on the Utilisation of Information and
Communication Technology in the management of Uganda Martyrs University Nkozi.
Inyaga (2002), used a correlational research design to compare the relationship between
the Management and the Utilisation of ICT, it was noted that the utilisation of ICTs
correlated significantly with the library, research and students' academic records
management. Egesa (2006) [21] studied Computer Utilisation in the Management of
Students' Information in Uganda and revealed that limited number of computers was
one of the major obstacles, which hinders effective utilisation of computers in the
14
management of students' data. Although the above studies correlated ICT with Usage
and Management review of these empirical studies does not show any relationship
between ICT and the banking industry thus leaving a clear path for this research to take
place.
2.3.2 Telephone banking technology and its influence on the
banking industry
Bohm et al 2000 [14] asserts that some banks have always accepted instructions by
telephone from trusted customers well known to them, as part of their ordinary branch
banking service. Telephone banking requires a customer and bank to agree at the outset
of the relationship a small category of 'security information' to be used to verify the
customer's authority to give telephone instructions and usually include a password
chosen by the customer (Bohm et al, 2000). Bohm et al (2000) defines telephone
banking as a service, which the customer can use to give instructions and get
information by speaking to bank staff by telephone. In respect to this research
telephone banking technology means availability, accessibility and usage of telephones
(wired or wireless telephones) to engage in cash deposit, withdrawal and account
balance inquiry by users in the banking industry.
Al Ashban and Burney (2001) [2] studied Customer Adoption of Tele-banking
Technology in Saudi Arabia and found that customers increasingly extend their use of
tele-banking as their experience grows with the system and that education played a vital
role in the adoption and usage of tele-banking technology. While Al Ashban and
Burney indicated that education played an important role in the adoption and usage of
tele-banking, Howcroft et al (2002) [28] indicated that educational levels of
respondents did not affect the usage of telephone banking. Findings of these two studies
reveal conflicting results.
15
In Uganda telephone banking is strengthened through Bankom, a local electronic
financial transaction services company in Uganda and a representative of Euro net used
in Europe (Kanyegirire, 2004 January 8). There is mobile phone banking in which air
time can be fixed on the mobile phone electronically from the customer's account hence
enabling customers to enjoy banking services without necessarily having to appear at
the bank. Inter-bank communication is trying to connect Crane Bank, Standard
Chartered Bank, Centenary Rural Development Bank, Stanbic Bank, Allied bank, Bank
of Baroda and Nile bank in Uganda (Kanyegirire, 2004 January 8); Nafula, 2006 March
31 [57]). Idowa et al (2002) [30], studied The Effect of Information Technology on the
growth of the Banking Industry in Nigeria. This study concentrated on the use of
technologies such as telephone banking technology. It was noted that the use of ICT
ensured a quick and improved services delivery to customers in Nigeria, thus an
indicating desirable outcomes. While the above study showed positive correlates in
Nigeria it does not point to the context in Kampala thus leaving a gap that the study
seeks to fill. Knowing the existence of telephone banking technology in Kampala may
not be enough, there is need to investigate its influence in order for the business
enterprises to benefit from it.
Constanzo et al (2003) [17] studied Strategic Approach to the Study of Innovation in the
Financial Services Industry about Telephone Banking in the UK and described the
strategic approach applied and revealed that differentiation in the financial market place
is not achieved with the implementation of distribution channels or just technology, but
bringing to the market 'unprecedented value'. Wendy et al (2005) [78] studied
Customers' Adoption of Banking Channels in Hong Kong and investigated factors that
influenced Hong Kong bank customers' adoption of four major banking channels, that
is to say branch banking, ATM, telephone banking, and internet banking. In their study
emphasis was placed on the influence of demographic variables and psychological
beliefs about the positive attributes possessed by the channels.
Wendy et al (2005) used interviews on 10 bank managers and questionnaires on 314
customers to solicit data. It was further revealed that telephone banking was the least
16
frequently adopted channel. Psychological beliefs about the extent to which a channel
possessed certain positive attributes were more predictive of adoptions of ATM and
Internet banking than adoptions of branch banking and telephone banking. Muhasa
(2005) [54], studied Technological Innovation, Employee Attitudes, Job design, User-
adoption and Perceived Organisational Performance in Uganda Revenue Authority; a
cross-sectional survey was used and the study revealed that user-adoption has the
individuals' predictive strength on the dependent variable perceived performance as
regards the magnitude of Standardised Beta Coefficients in the regression model. A
conceptual model which relates technological innovaions, job design, employee
attitudes, user-adoption and perceived performance in Uganda Revenue Authority was
developed by Muhasa (2005). Although this study took place in Kampala it does not
correlate ICT to the banking industry.
2.3.3 Internet banking technology and its influence on users
in the banking industry
Ayadi (2003) explains that access to electronic means of payment and the high number
of customers connected to the Internet has changed the perception of banks toward
market and increased the development of Internet Banking. Hutchinson and Warren
(2003) [29] argue that Internet banking requires a sound security procedure that
involves designing effective methods via which users can be authenticated in a remote
environment such that transactions being conducted are secured within their respective
environments. Internet banking technology has made remarkable changes in the
banking industry, which include: cost reduction due to electronic processing carried out
on the Internet. For example the US while the average transaction cost at a full service
bank is about $1.07, it reduces to $0.27 at an ATM and falls to about a penny if the
same transaction is conducted on the web (Nath et al, 2001) [58].
In the Australian banking industry sophisticated functionality is routinely offered to
customers to make download of account history in various formats and preview history
17
of their banking details (Li and Andrew, 2004) [47]. Purcell and Toland (2003) [65]
opine that the use of the Internet in the banking institutions can give cost advantage by
reducing financial transaction costs; middleman-ship; emerge into new products in the
financial industry and the construction of expensive websites that can secure financial
transactions. According to Mathias and Sahut (1999) as reported by Ayadi (2003),
Internet banking can be defined as a set of systems that enable bank customers to access
accounts and general information on bank products and services through a personal
computer among other intelligent devices or any other activity held on the Internet. In
this research Internet banking technology means the availability, accessibility and usage
of websites and e-mail services in cash deposit, cash withdrawal and account balance
inquiry by users in the banking industry.
In Malaysia, Internet banking technology is mainly grounded in three banks which
include: the Malayan Banking Berhad which conducts banking through its web site,
Hong leong Bank Berhad through e-commerce banking and the Southern Bank Berhad.
Despite the services of these financial institutions, there is fear that unauthorized
account users inside and outside the bank can get access to customer accounts through
the use of the Internet in any place and at any time which scares away bank customers
to withdraw or use online banking facilities and instead resort to using other means thus
an indication of a negative out come (NST, 2001) [59]. According to Kerem (2003)
[43], Internet banking technology has led to the incorporation of new features for
security transactions, international payments; viewing credit card statements, deposits
and account history, customers can now send e-mails from the bank's home page. This
implies that banks can use websites as means to provide services to customers.
According to Goldstuck (2004) as reported by Buys and Brown (2004) [16], Internet
banking accounts in South Africa recently surpassed one million and continued to rise
rapidly. There is no wide spread dissatisfaction about the security concern on the use of
Internet banking in South Africa instead Internet banking has led to increased customer
support and quickens transactions and payments of customers (Buys and Brown, 2004).
18
Ezeoha (2005) [23] studied Regulating Internet Banking in Nigeria and noted that there
are security concerns in Internet banking where fraud has become a daily business to
some individuals; Internet banking has remained insignificant due to fraud and forgery,
e-banking services are offered in Naira only and that in Nigeria Internet banking may
take a long time to fully become one of the economic relevance in the country banking
practice because of fraud which has made it complex hence causing few customers to
transact their businesses through the Internet. Coupled to that is that the development of
bank websites does not go beyond information purposes. Poor government measures
have also affected the right environment for Internet banking (Ezeoha, 2005). Given the
state of Internet banking in Nigeria one can argue that its influence is an indicator of an
undesirable dimension. In Uganda, Internet banking is limited to banks with in
Kampala. Nile Bank in Uganda avails information to its customers online through the
use of the bank web site. Other services offered include utility payments for electricity
and water, and 3rd party payments like post paid telephone bills and much more which
has enabled customers to effect their bills without physical appearance to the bank
hence avoiding time wastage. SMS can also be provided through True African online to
get any inquiries from the bank as compared to before when one had to get to the bank
physically (True African, 2006) [75].
Waite and Harrison (2005) studied An Analysis of Website Evolution in the Pensions
Sector and found that pension websites support new business transactions rather than
existing account management and provide more information on company strength and
market position than detail on product and services and proposed a model of financial
services website evolution and applies it to a longitudinal content analysis of 30
pension provider websites, spanning eight years of web development from 1996 to
2003. Eriksson et al (2004) [22] studied the Customer Acceptance of Internet Banking
in Estonia and used the Technology Acceptance Model. They found out that bank use
increases in so far as customers perceive it as useful. It was also noted that perceived
usefulness of Internet banking for banks is a key construct for promoting customer use.
Laforet and Li (2005) [45] studied Consumers' Attitudes Towards Online and Mobile
banking in China and found out that the issue of security was found to be the most
19
important factor that motivated Chinese consumer adoption of online banking; main
barriers to online banking were the perception of risks, computer and technological
skills and Chinese traditional cash-carry banking culture.
Yeap and Chach (2005) [82] carried out a study in Malaysia about Internet banking and
found that Internet banking concentrated in foreign banks. Saloner and Shepard, R.
(1995), studied Adoption of Automated Teller Machines in US. Banks; Furst, Lang and
Nolle (2000) studied the adoption of transactional web sites among US, nationally
chartered banks; Masciandaro, J. (2000) studied Introduction of E-banking in the first
110 Italian banks up to May 2000 as reported by (Courchane et al, 2002) [18].
Courchane et al in their study about the application Internet banking in Financial
Matters developed a model of the probability of adoption basing on the findings.
Similarly to Courachane et al the influence of ICT on the banking industry is expressed
in form of an empirical model basing on the findings after data collection. Bradley and
Steward (2002) [15] studied A Delphi study of the Drivers and Inhibitors of Internet
Banking in the United Kingdom and investigated factors driving and inhibiting Internet
banking using the delphi method. As opposed to Bradley and Laura (2002) this study
aimed at establishing the influence of ICT on the banking industry using self-
administered questionnaires to solicit data from the respondents.
Tan and Teo (2000) [74] studied Factors Influencing the Adoption of Internet Banking
in Singapore basing their study on the Theory of Planned Behaviour. Unlike Tan and
Teo (2000), this study incorporated Rogers' (2003) Diffusion of Innovations Theory
while establishing the influence of ICT on the banking industry in Kampala. Despite
the existence of Internet banking technology in Uganda, its magnitude has not been
established hence giving room for the study to take place. Polatoglu and Ekin (2001)
[63] studied An empirical investigation of the Turkish Consumers' Acceptance of
Internet Banking Services and found that cost and time saving dimensions are
perceived as a major benefits when customers use Internet banking more often and for
larger transactions.
20
2.4 Chapter summary
This chapter demarcated the boundary of the study by expanding on Rogers' Diffusion
of Innovations Theory and formulating the conceptual framework/model basing on
other researchers. Emphasis was placed on the concept of ICT and its influence on the
banking industry while conceptualising past studies. Attempts on ICTs in relation to the
banking industry have been inconclusive and it has been noted that e-banking
technology is an important aspect that has received little attention. This area mainly
focused on identifying the research gaps that were existent in other past studies that
were reviewed. The focal point of the literature review was based on the e- funds
transfer, telephone banking and Internet banking technologies and their influence on the
banking industry as shown in the objectives.
21
Chapter 3
Methodology
3.0 Introduction This chapter entails research design, study population, sampling procedure, data
collection method and tool, quality of research tool, research procedure and data
processing and analysis. This chapter generally contains the approach used to achieve
the objectives of the study.
3.1 Research design The research design was quantitative, qualitative, correlational and case study in nature.
(Baskerville and Myers (2004) [11]; Davidson et al (2004) [20]; Markus et al (2002)
[48]; Kakinda-Mbaaga (2000) [35] and (Yin, 1984) [81]). For example data collection
was largely quantitative basing on use of a questionnaire with limited qualitative
approach in explaining the results where possible. Correlations were used in explaining
how ICT has influenced the banking industry in Kampala. Kampala was the unit of
study (case study).
3.2 Study population Targeted population included individual bank customers who held accounts within
Kampala from the following banking institutions: Barclays, Baroda, Cairo
International, Centenary Rural Development, Citi, Crane, DFCU, Diamond Trust,
National Bank of Commerce, Nile, Orient, Post, Stanbic, Standard Chartered and
22
Tropical Africa. The population size was difficult to establish because none of the
bank-managing directors was willing to release the number of individual customer
since it was against the corporate law.
3.3 Sampling procedure Unsystematic random sampling was used in the selection of respondents given the fact
that the population of interest was difficult to establish. Determination of the sample
size was done using the following formula.
n=(z2α/2pq)/e
2
Where n is the sample size
z is the abscissa of the normal curve and was got from statistical tables
p is the estimated proportion of an attribute that is present in the population
q is 1-p
e is the desired level of precision/estimated error
Since N (population) is unknown then p is 0.5
Desired precision is normally 0.05/2=0.025
Substitution of formula
n=zp(1-p)/e
n=1.96*1.96*0.5*0.5/0.05*0.05
n=0.9604/0.0025
n=384.16
The minimum sample size was expected to be 384 however the researcher managed to
obtain a sample of 419 individual customers.
3.4 Data collection method and tool This section entails the method and the tool used in the research. The section clearly
elaborates the purpose of the method in achieving the objectives and the structure of the
tool as a means of data collection.
23
3.4.1 Questionnaire method The questionnaire method was used as a means of data collection given the fact that the
target population was large. The researcher used a pre-designed set of questions to
identify the influence of e-funds transfer, telephone banking and Internet banking
technologies on the banking industry in Kampala.
3.4.2 Self-administered questionnaire The self-administered questionnaire (SAQ) was used as a tool for data collection
because it is quicker in getting data from the respondents (Bakkabulindi, 2004) [7]. The
questionnaire was structured into: the background information, dependent variable and
independent variable respectively (Oppenheim, 1992) [61]. The researcher developed
the questionnaire by identification of the dependent and independent variables. There
after operationalisation of the dependent and independent variables took shape. The
banking industry was operationalised basing on the three main activities that take place
in the bank: cash deposit, cash withdrawal and account balance inquiry. On the other
hand ICT had three independent variables: e-funds transfer technology which was
operationalised as ATM card, credit card, debit card and e-cheque services, telephone
banking technology which was operationalised as wired and wireless telephone services
and Internet banking technology which was operationalised as e-mail and website
services. All the questions were directly linked to the indicators in the conceptual
framework/model. Using the indicators the researcher therefore developed the
questions basing on the operationalisation of the variables. For the SAQ see Appendix
A.
3.5 Quality of research tool The quality of research tool entailed the following: Reliability of the SAQ and validity
of the SAQ. Validity and reliability of the research instruments are very important
aspects of a research instrument and should be put into consideration by researchers if
they are to obtain substantial results from a research instrument (Oppenheim, 1992).
24
3.5.1 Validity of the SAQ The SAQ was developed by the help of the research experts who were conversant with
research method practices to see whether the questions in context can get the data
needed to support the research hence achieving content validity. See Appendix B that
shows the letter to one of the research experts). The researcher used the following
delimiters similarly used in Likert's scale: very appropriate, appropriate, inappropriate
and very inappropriate in rating the experts' views. Each expert was given the title, the
purpose, objectives, the conceptual framework and the methodology to tarry with the
questions in the SAQ. At first the questionnaire had 51 components and 12 components
were later dropped. 3 questions were dropped from the background information and 6
questions were dropped from the independent variable of Internet banking, 3 questions
were dropped from the dependent variable (banking industry) leaving the questionnaire
with 39 questions. In some cases the questions were adjusted.
This was because the experts thought that some had technical terms, which some
respondents may not have been exposed to. For example one of the experts said that he
was very conversant with ICTs but still if some one expected an answer from a
statement, 'Satellite connection is accessible in the Bank in which I hold an account' it
would be hard to get their response. Adjustments were made on questions. For
example, concerning the salary level of the respondent, the researcher was advised to be
specific and mention monthly salary because the respondents could not understand
whether the salary was monthly, yearly and the like. To achieve predictive validity of
the SAQ, measures were used in relating ICT and the banking industry that is how far
the items measured distinct variables that were previously developed. This was carried
out using factor analysis using varimax rotation simulated via SPSS correlating ICT
subscales with the banking industry. ICT subscales were then correlated with the
banking industry final scores. In this case some of the components that were
insignificant were dropped and those that had zero variance were removed completely
from further analysis: for example qn. (question) 23, qn.19 and qn.27 on e-cheque
25
technologies were removed because none of the services existed in the given banks.
This therefore meant that the variables with a high predictive potential were left, thus
ensuring validity of the research instrument. For the predictive validity, see factor
analysis in chapter four where the sufficient items were extracted.
3.5.2 Reliability of the SAQ The SAQ was tested for reliability. Cronbach's alpha was used to establish the
reliability of the research instrument simulated via SPSS (Software Package for Social
Scientists). The banking industry had a 9 item scale with Cronbach's alpha reliability
scale of 0.92, e-funds transfer had a 12 item scale and produced an alpha of 0.79 while
telephone banking and Internet banking technology had 6 item scales and produced
alphas of 0.89 and 0.91 respectively. It was noted that all the above items had
acceptable Cronbach alpha coefficients above 0.78 as explained by (Cronbach 1951;
Nunnaly 1978) and reported by (Mpeera, 2005) [55]. Cronbach alpha simulations are
shown below in Table 1.
Table 1: Simulations of Cronbach’s alpha
Variables Number of items Alpha
Banking industry 9 0.92
E-funds transfer technology 12 0.79
Telephone banking technology 6 0.89
Internet banking technology 6 0.91
3.6 Data processing and analysis After data collection data processing took place: data were edited by eliminating
questionnaires with inconsistencies, and remaining data were coded through the
development of a coding scheme. For the coding scheme see Appendix C. Data was
26
entered using Epi data (Epidemiological data) software in which the researcher
designed a data entry form. For the data entry form see Appendix D. The designed form
was subjected to validation to check whether it could accept the data values. After
validation of the data entry form the researcher entered the data. Data was then
exported to excel from Epi data and then imported to SPSS and summarised as table,
graphical or text format. Data analysis was done using factor analysis, cross tabulations
for explaining background variables, independent t-tests and ANOVA (one-way) for
finding out how the dependent variable varied with the background variables. The
relationship between the ICT and the banking industry was shown using Pearson's
correlation coefficient and to test the significance of the correlation the coefficient of
determination was used using regression analysis tool aided by SPSS version 12.
3.7 Chapter summary This chapter shows the approach the researcher used to achieve the objectives.
Quantitative data collection method was mainly used for data collection given, the fact
that the entire population of study was too large. Qualitative approach was used in the
interpretation of the research findings. A sample size of 419 respondents was taken as
representative of the entire individual customer population in Kampala within the
banking industry.
27
Chapter 4
Data presentation, analysis and interpretation
4.0 Introduction This chapter has three main sections: Description of background variables; how the
dependent variable varies with the background variable and verification of hypotheses.
This chapter basically reports what the researcher found in the field and it is geared
towards the achievement of the study objectives.
4.1 Description of background variables The background information was coded to understand the nature of the respondents. It
is very important to understand the nature of the respondents because it gives a deeper
understanding of any given research and such information may be useful for future use.
Cross-tabulations were used in this section to explain the nature of respondents, as
shown below.
28
4.1.1 Employment status by sex
Table 2: Employment status by sex
Status Sex of the respondents Total Male Female Employed Count 240 150 390 % within employment status of
the respondent 61.5% 38.5% 100.0%
% within Sex of the Respondents
93.4% 92.6% 93.1%
% of Total 57.3% 35.8% 93.1% Un-employed Count 17 12 29 % within employment status of
the respondent 58.6% 41.4% 100.0%
% within Sex of the respondents 6.6% 7.4% 6.9% % of Total 4.1% 2.9% 6.9% Total Count 257 162 419 % within employment status of
the respondent 61.3% 38.7% 100.0%
% within sex of the respondents 100.0% 100.0% 100.0% % of Total 61.3% 38.7% 100.0%
As shown in the table above, results indicate that majority of the individual bank
customers were male, accounting for 61.3%. Male individual customers accounted for
employment and unemployment status of 61.5% and 58.6% respectively. Results also
indicate that the majority of the individual bank customers were employed, accounting
for 93.1%. Results are consistent with Ayadi (2006); Ongkasuwan (2002) [60] who
revealed that majority of the respondents were male and employed.
29
4.1.2 Bank of respondent by account
Table 3: Bank of respondent by account
Bank of the Respondent Type of account mainly operated Total Current
Account Savings Account
Fixed Account
Salary Account
Future account
Barclays Bank Count 23 9 7 1 3 43 % within Bank 53.5% 20.9% 16.3% 2.3% 7.0% 100.0% Bank of Baroda Count 8 19 6 33 % within Bank 24.2% 57.6% 18.2% 100.0% Cairo International Bank Count 3 1 4 % within Bank 75.0% 25.0% 100.0% CERUDEB Count 5 20 1 1 27 % within Bank 18.5% 74.1% 3.7% 3.7% 100.0% Citi Bank Count 3 3 6 % within Bank 50.0% 50.0% 100.0% Crane Bank Count 12 20 3 35 % within Bank 34.3% 57.1% 8.6% 100.0% DFCU Count 13 22 8 43 % within Bank 30.2% 51.2% 18.6% 100.0% Diamond Trust Bank Count 1 1 % within Bank 100.0% 100.0% National Bank of Commerce Count 1 4 5 % within Bank 20.0% 80.0% 100.0% Nile Bank Count 22 8 6 2 38 % within Bank 57.9% 21.1% 15.8% 5.3% 100.0% Orient Bank Count 2 2 1 1 6 % within Bank 33.3% 33.3% 16.7% 16.7% 100.0% Post Bank Count 1 2 3 6 % within Bank 16.7% 33.3% 50.0% 100.0% Stanbic Bank Count 36 58 10 2 106 % within Bank 34.0% 54.7% 9.4% 1.9% 100.0% Standard Chartered Bank Count 17 23 16 3 1 60 % within Bank 28.3% 38.3% 26.7% 5.0% 1.7% 100.0% Tropical Africa Bank Count 1 5 6 % within Bank 16.7% 83.3% 100.0% Total Count 144 198 63 9 5 419 % within Bank 34.4% 47.3% 15.0% 2.1% 1.2% 100.0%
As shown in the table above, results reveal that majority of the individual customers
were savings account holders, accounting for 47.3%. Minority of the account holders
were future account holders accounting for 1.2%. This could be true because few
people in developing countries have a tendency to save for the future. Results
30
revealed that majority of the account holders were from Stanbic bank, accounting for
25.3%.
31
4.1.3 Salary level by age
Table 4: Salary level by age
Level of monthly salary Age of respondent Total Less than 19
years 20-29 years 30-39
years 40-49 years Above 50
years
No salary Count 2 27 29 % within level of monthly
salary 6.9% 93.1% 100.0%
% within age group of the respondents
66.7% 16.9% 6.9%
% of Total .5% 6.4% 6.9% Less than 90,000/= Count 7 7 14 % within level of monthly
salary 50.0% 50.0% 100.0%
% within age group of the respondents
4.4% 4.5% 3.3%
total 1.7% 1.7% 3.3% 100,000-490,000/= Count 69 51 12 1 133 % within level of monthly
salary 51.9% 38.3% 9.0% .8% 100.0%
% within age group of the respondents
43.1% 33.1% 14.8% 4.8% 31.7%
% of Total 16.5% 12.2% 2.9% .2% 31.7% 500,000-990,000/= Count 44 51 17 5 117 % within level of monthly
salary 37.6% 43.6% 14.5% 4.3% 100.0%
% within age group of the respondents
27.5% 33.1% 21.0% 23.8% 27.9%
% of Total 10.5% 12.2% 4.1% 1.2% 27.9% 1,000,000-1,490,000/= Count 11 26 24 5 66 % within level of monthly
salary 16.7% 39.4% 36.4% 7.6% 100.0%
% within age group of the Respondents
6.9% 16.9% 29.6% 23.8% 15.8%
% of Total 2.6% 6.2% 5.7% 1.2% 15.8% Above 1,500,000/= Count 1 2 19 28 10 60 % within level of monthly
salary 1.7% 3.3% 31.7% 46.7% 16.7% 100.0%
% within age group of the respondents
33.3% 1.3% 12.3% 34.6% 47.6% 14.3%
% of Total .2% .5% 4.5% 6.7% 2.4% 14.3% Total Count 3 160 154 81 21 419 % within level of monthly
salary .7% 38.2% 36.8% 19.3% 5.0% 100.0%
% within age group of the respondents
100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
% of Total .7% 38.2% 36.8% 19.3% 5.0% 100.0%
32
As shown in the table above, results indicate that majority of the individual bank
customers were aged between 20 to 29 years of age, accounting for 38.2%. Individual
customers aged between 20 to 29 mainly earned between 100,000/= to 490,000/=
(accounting for 43.1%). Findings are partially consistent with Tan and Teo (2000) in
which most of the respondents were aged between 20 to 29 years accounting for 64.1%.
It was also noted that 6.9\% earned no salary because they were unemployed. Results
also indicate that respondents aged between 40 to 49 years mainly earned above
1,500,000/= accounting for 46.7%.
4.2 How the dependent variable varies according to the
background variables This analysis was done with an aim of knowing how the dependent variable varies with
the background variables since it is the most important variable. This analysis gave the
means and the significance of their differences using t-tests and one-way ANOVA as
shown below.
33
4.2.1 Banking industry and employment status
Table 5: Independent t-test: employment and banking industry
Employment
status of individual bank customers
N Mean SD t df Sig. (2 tailed)
As shown in the table above, results indicate that there was a significant difference
between employed and unemployed individual customers when it came to cash deposit
and account balance inquiry. Employed individual customers engaged more in cash
deposit than their unemployed counterparts (t=1.93, p<0.02). It was also noted that
account balance inquiry activity was also significantly higher with the employed
individual bank customers (t=2.02, p<0.04) than with the unemployed.
Employed 390 4.16 .84 30.45 Cash deposit 1.93 .02* Un employed 229 3.76 1.10
417 Employed 390 3.88 1.12 31.02 Cash
withdrawal 1.34 .31
Un employed 29 3.22 1.12 417 Employed 390 4.31 .82 30.44 Account
balance inquiry
2.02 .04*
Un employed 29 4.02 1.08 417
34
4.2.2 Banking industry and sex
Table 6: Independent t-test: sex and banking industry
Sex N Mean SD t df Sig. (2 tailed)
As shown in the table above, results indicate that there was significant difference
between males and female individual customers on cash deposit. The analysis shows
that male individual bank customers engage more in cash deposit than their female
counterparts (t=-1.14, p<0.02) at 0.05 level.
Male 257 4.11 .98 417 Cash deposit -1.14 .02* Female 162 4.17 .95 353.18 Male 257 3.79 1.12 417 Cash
withdrawal -1.03 .31
Female 162 3.91 1.12 342.15 Male 257 4.29 .84 417 Account
balance inquiry
-.61 .73
Female 162 4.37 .85 338.28
35
4.2.3 Testing for variations between banking industry and age
Table 7: One-way ANOVA: variations of age according to banking industry
Sum of square
Sum of squares
df Mean square
F Sig.
As shown in the above, results indicate that cash withdrawal rating varied significantly
by age group, F (4, 415)= 2.75, p<0.03 at 0.05 level. After carrying out post-hoc tests it
was noted that those in the age group of 40-49 years rated cash withdrawal higher on
average (4.16) compared to other age groups as shown below.
Between groups
5.740 5 1.435 Cash deposit 1.95 .10
Within groups
304.797 413 .736
Total 310.537 418 Between groups
13.637 5 3.409
Within groups
514.001 413 1.242
Cash withdrawal
2.75 .03*
Total 527.638 418 Between groups
2.002 5 .500
Within groups
296.319 413 .716
Account balance inquiry
.70 .59
Total 298.320 418
36
Table 8: Duncan multiple range test-Post hoc test for cash withdrawal
Age of individual bank
customers N Subset for alpha=. 05
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size=12.314.
b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type 1
error levels are not guaranteed.
c. Type 1/Type 2 Error seriousness Ratio=100.
Less than 19 years 3 3.33 20-29 years 160 3.72
Duncana,b
30-39 years 154 3.76 Above 50 years 21 4.06 40-49 years 81 4.16 Sig. .01 Less than 19 years 3 3.33 20-29 years 160 3.72
Waller-Duncana,1
30-39 years 154 3.76 Above 50 years 21 4.06 40-49 years 81 4.16
37
4.2.4 Testing for variations between banking industry and type of
account
Table 9: One-way ANOVA: variations of type of account according to banking
industry
Sum of
square Sum of squares
df Mean square
F Sig.
As shown from the table above, results indicate that cash deposit rating varied
significantly by type of account, F (4, 415)= 2.63, p<0.04. After carrying out post-hoc
tests it was noted that the fixed account holders rated cash deposit higher on average
(4.87) compared to other account holders as shown below.
Between groups
7.413 4 1.853 Cash deposit 2.63 .04*
Within groups
303.124 414 .732
Total 310.537 418 Between groups
9.493 4 2.373
Within groups
518.146 414 1.252
Cash withdrawal
1.90 .110
Total 527.638 418 Between groups
7.381 4 .1.845
Within groups
290.940 414 .703
Account balance inquiry
2.53 .03
Total 298.320 418
38
Table 10: Duncan multiple range test-Post hoc test for cash deposit
Account of individual bank
customers N Subset for alpha=. 05
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size=14.750.
b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type 1
error levels are not guaranteed.
c. Type 1/Type 2 Error seriousness Ratio=100.
1 2 Future account 9 4.02
Duncana,b
Salary account 5 4.13 Current account 144 4.32 4.32 Savings account 198 4.33 4.33 Fixed account 63 4.87 Sig. .37 .11 Future account 9 4.02 Salary account 5 4.13
Waller-Duncana,1
Current account 144 4.32 4.32 Savings account 198 4.33 4.33 Fixed account 63 4.87
39
4.2.5 Testing for variations between banking industry and salary level
Table 11: One-way ANOVA: variations of salary level according to banking
industry
Sum of square
Sum of squares
df Mean square
F
Sig.
As shown in the table above, results indicate that cash withdrawal rating varied
significantly by salary level, F (4, 415)= 16.94, p<0.01. After carrying out post-hoc
tests it was noted that individual customers who earned above 1,500,000 rated cash
withdrawal higher on average (4.45) compared to individual customers at different
salary levels as shown below.
Between groups
39.765 5 7.953 Cash deposit 12.13 .000
Within groups
270.772 413 .656
Total 310.537 418 Between groups
89.799 5 17.960
Within groups
437.839 413 1.060
Cash withdrawal
16.94 .01*
Total 527.638 418 Between groups
14.420 5 .1.845
Within groups
283.901 413 .703
Account balance inquiry
4.20 .001
Total 298.320 418
40
Table 12: Duncan multiple range test-Post hoc test for cash withdrawal
Salary level of individual bank customers
N Subset for alpha=. 05
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size=39.013.
b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type 1
error levels are not guaranteed.
c. Type 1/Type 2 Error seriousness Ratio=100.
1 2 3 No salary 29 3.22
Duncana,b
Less than 90,000/= 133 3.34 100,000/=-490,000/= 14 3.45 500,000/=-990,000/= 117 3.97 1,000,000/=-1,490,000/= 66 4.38 4.38 Above 1,500,000/= 60 4.45 Sig. .35 0.73 .78 No salary 29 3.22 Less than 90,000/= 133 3.34
Waller-Duncana,1
100,000/=-490,000/= 14 3.45 500,000/=-990,000/= 117 3.97 1,000,000/=-1,490,000/= 66 4.38 Above 1,500,000/= 60 4.45
41
4.3 Verification of hypotheses The study focused on achieving the following objectives: To identify the influence of e-
funds transfer technology on the banking industry in Kampala, to identify the influence
of telephone banking technology on the banking industry in Kampala and to identify
the influence of Internet banking technology on the banking industry in Kampala. To
achieve the given objectives, there were tentative statements; referred to as hypotheses
(H1, H2 and H3) on page 5 and 6. Before the verification of the hypotheses, validity of
the predictive variables had to be ensured using factor analysis. This section involves
factor analysis, discussion of the relationship between constructs and fulfilment of the
objectives.
4.3.1 Factor analysis Varimax rotated component matrix was used to identify the items that could best
predict the banking industry. For each technology two factors were extracted as shown
below thus a total of six factors were extracted from the global construct of ICT. The
extracted factors were later used in the regression model for prediction. According to
Oppenheim (1992) factor analysis is important in explaining underlying dimensions or
patterns in data.
42
Table 13: Rotated matrix: E-funds transfer technology
Extraction method: Principle component analysis.
Rotation method: Varimax with Kaiser normalisation.
A rotation converged into 3 iterations.
As shown in the table above, the construct of e-funds transfer loaded on two factors
namely: Credit-debit card services and ATM services accounting for a cumulative
percentage of 68% and eigen values of 4.4 and 1.7 respectively. The first factor
explained availability and accessibility of credit and debit card services to individual
customers hence the label credit-debit services. The values from the loadings presented
acceptable results. The first factor had the items 17, 18, 21 and 22 with values 0.91,
0.94, 0.91 and 0.96 respectively. The second factor explained availability, accessibility
and use of ATM card services hence the label ATM services. The loadings on this
1 2 Credit-debit card services
Atm card services
16. ATM services are available in the Bank where I own an account
.84
17. Credit card services are available in the Bank where I hold an account
.91
18. Debit card services available in the Bank where I hold an account
.94
20. ATM services are accessible in the bank where I hold an account
.79
21. Credit card services are accessible in the Bank where I hold an account
.91
22. Debit card services are accessible in the Bank where I hold an account
.96
24. I use ATM services in the Bank where I hold an account
.51
Eigen values 4.4 1.7 Cumulative percentage 68%
43
factor also indicated acceptable results. The factor had the following items 16, 20 and
24 with values of .84, .79 and .51 respectively.
Table 14: Rotated component matrix: Telephone banking technology
1 2 Wired-wireless availability- accessibility services
Wired-wireless use services
28. Wired telephone services are available in the Bank where I hold an account
.88
29. Wireless telephone services are available in the Bank where I hold an account
.91
30. Wired telephone services are accessible in the Bank where I hold an account
.93
31. Wireless telephone services are accessible in the Bank where I hold an account
.92
32. I use wired telephone services in the Bank where I hold an account
.68
33. I use wireless telephone services in the Bank where I hold an account
.75
Eigen values 3.9 1.2 Cumulative percentage 86%
Extraction method: Principle component analysis.
Rotation method: Varimax with Kaiser normalisation.
A rotation converged into 3 iterations.
As shown in the table above, the construct of telephone banking technology loaded on
two factors namely: Wired-wireless availability-accessibility services and wired-
wireless services for a cumulative percentage of 86% and eigen values of 3.9 and 1.2
respectively. The first factor explained availability and accessibility of wired and
wireless services to individual customers hence the label wired-wireless availability-
accessibility services. The values from the loadings presented acceptable results. The
44
first factor had the items 28, 29, 30 and 31 with values 0.88, 0.91, 0.93 and 0.92
respectively. The second factor explained use of wired and wireless telephone use
services hence the label wired-wireless use services. The loadings on this factor also
indicated acceptable results. The factor had the following items 32 and 33 with values
of .68 and .75 respectively
Table 15: Rotated component matrix: Internet banking technology
Extraction method: Principle component analysis.
Rotation method: Varimax with Kaiser normalisation.
A rotation converged into 3 iterations.
As shown in the table above, the construct of Internet banking technology loaded on
two factors namely: E-mail-website availability-accessibility services and e-mail-
website use services accounting for a cumulative percentage of 93% and eigen values
of 4.3 and 1.3 respectively. The first factor explained availability and accessibility of e-
1 2 E-mail-website availability-accessibility services
E-mail-website use services
34. E-mail services are available in the Bank where I own an account
.91
35. Website services are available in the Bank where I own an account
.88
36. E-mail services are accessible in the Bank where I own an account
.95
37. Website services are accessible in the Bank where I hold an account
.95
38. I use e-mail services in the Bank where I hold an account
.73
39. I use website telephone services in the Bank where I hold an account
.69
Eigen value
4.3 1.3
Cumulative percentage 93%
45
mail and website services to individual customers hence the label e-mail-website
availability-accessibility services. The values from the loadings presented acceptable
results. The first factor had items 34, 35, 36 and 37 with values 0.91, 0.88, 0.95 and
0.95 respectively. The second factor explained e-mail and website use services hence
the label wired-wireless use services. The loadings on this factor also indicated
acceptable results. The factor had the following items 38 and 39 with values .73 and .69
respectively. It was noted that six factors in total were extracted with acceptable values.
Kaiser (1974) [33] recommends accepting values greater than 0.5 and further explains
that values between 0.5 and 0.7 are mediocre, 0.7 and 0.8 are good values between 0.8
and 0.9 are great values and those above .9 are superb.
46
4.3.2 Relationship between constructs
Table 16: Correlation matrix: ICT constructs-banking industry
Bank 1a 1b 2a 2b 3a 3b
Bank Pearson Correlation
1
Credit-debit card services (1a)
Pearson Correlation
.403** 1
1 ATM card services (1b)
Pearson Correlation .530** .000
Wired-wireless availability-accessibility services (2a)
Pearson Correlation
1
.791** .486** .121*
Wired-wireless use services (2b)
Pearson Correlation
1 .602** .330** -.018 .000
Internet availability and accessibility services (3a)
Pearson Correlation
1
.401** .853** .044 .484** .371**
Internet use services (3b)
Pearson Correlation
1 .027 .181** .036 .066 .307** .000
** Correlation is significant at the 0.01 level (2-tailed).
*Correlation is significant at the 0.05 level (2-tailed).
Relationship between ICT constructs
As shown in the correlation matrix above credit-debit card service significantly
positively correlated with wired-wireless availability-accessibility services (r=0.486**,
p<0.01). A significant relationship was also noted between credit-debit services and
wired-wireless use services (r=0.330**, p<0.01). This therefore signifies that an
increase in either service may lead to increase in another service. There were significant
correlations between Internet availability-accessibility services with credit-debit card
services (r=0.853**, p<0.01). Internet use services and credit-debit card services were
also correlated (r=0.181**, p<0.01) although not highly related as compared to the
availability and accessibility of Internet services. This therefore implies that an increase
47
in credit-debit card services may probably increase Internet services with change in
Internet availability and accessibility. There was a significant positive relationship
between ATM services and wired-wireless (r=0.121*, p<0.05)
4.3.3 Influence of e-funds transfer technology on the banking industry
in Kampala Pearson's correlation coefficient results reported in Table 16 indicated significant
positive correlations between e-funds transfer technologies and the banking industry.
Credit-debit card services and ATM services were positively correlated with the
banking industry, (r=0.403**, p<0.01 and r=0.530**, p<0.01) respectively at 0.01
level.
Table 17: Model 1-E-funds transfer technology and the banking industry Model 1 Standardised beta
coefficients T Sig.
a Predictors: (Constant), Credit-debit card services, ATM services b Dependent Variable: banking industry
Constant 9.639 .000
Credit-debit card services
. 403 6.404 .000
ATM card services
. 530 3.656 .000
R . 529 R square . 280 Adjusted R Square . 269 Std. Error of the Estimate .20444 From the above table credit-debit cards and ATM services were used as the predictor of
the banking industry separately. As already noted e-funds transfer was reported to have
a low predictive potential the regression model explained 27% of the total variation in
the banking industry. Implying that the level of incorporation of e-funds transfer
technologies is low in the banking industry.
48
4.3.4 Influence of telephone banking technology on the banking
industry in Kampala Pearson's correlation coefficient results reported in Table 16 revealed significantly
positive correlations between the banking industry and telephone banking technologies.
Wired-wireless availability-accessibility and wired-wireless use services, (r=0.791**,
p<0.01, r=0.602**, p<0.01,) respectively.
Table 18: Model 2-Telephone banking technology and the banking industry Model 2 Standardised beta
coefficients T Sig.
a Predictors: (Constant), wired-wireless availability-accessibility, wired-wireless use services b Dependent Variable: banking industry
Constant 3.993 .000
Wired-wireless availability-accessibility services
. 791 3.932 .000
Wired-wireless use services
. 602 2.246 .000
R .731 R square . 534 Adjusted R Square . 528 Std. Error of the Estimate . 55455 With reference to the above table telephone banking technology was used as the
predictor of the banking industry separately and it was noted that it had a predictive
potential of 53% although much higher compared to both e-funds transfer technologies
and Internet banking technologies. Findings are not consistent with Wendy et al (2005)
who argue that telephone banking is the least frequently adopted channel in Hong
Kong.
49
4.3.5 Influence of Internet banking technology on the banking industry
in Kampala Pearson's correlation coefficient results reported in Table 16 revealed significantly
positive correlations between Internet banking technologies. E-mail-website
availability-accessibility services and the banking industry, (r=0.401**, p<0.01). Never
the less, e-mail-website use services did not significantly correlate with the banking
industry. Table 19: Model 3-Internet banking technology and the banking industry
Model 3 Standardised beta
coefficients T Sig.
a Predictors: (Constant), internet use, internet availability and access b Dependent Variable: banking industry
Constant 24.224 .000
Internet availability and access
.401 5.937 .000
Internet use .027 .563 .003 R .340 R square .116 Adjusted R Square .111 Std. Error of the Estimate .07908
The regression model above shows that Internet banking technology has predictive
potential of 11% of the total variation of the banking industry, which is very low. This
implies that Internet banking is least supported with in the banking industry Kampala.
50
4.3.6 ICT and the banking industry in Kampala The aim of the study was to establish the influence of ICT on the banking industry in
Kampala. As shown in Table 16 results indicate that ICT constructs were uncorrelated
with in their sets. It was therefore inevitable to achieve the aim of the study with such a
pattern in the independent constructs.
Table 20: Model 4-ICT and the banking industry
Model 4 Standardised beta coefficients
T Sig. a Predictors: (Constant), ATM card services, credit-debit card services, wired-wireless availability-access, wired-wireless use, internet-use, internet availability-accessibility a Dependent Variable: banking industry Constant 19.639 .000
Credit-debit card services
.136 1.564 .119
ATM card services
.501 2.828 .005*
Wired-wireless availability-access
.690 9.633 .001*
Wire-wireless use service
.330 2.384 .002*
Internet use service
-.120 -1.333 .183
Internet availability and access service
-.070 -1.474 .141
R . 740
R square . 550
Adjusted R Square . 541
Std. Error of the Estimate .51220
51
The regression model above shows that a combination of e-funds transfer, telephone
banking and Internet banking technologies has a predictive potential of 54% on the
banking industry which is low although better than single predictions based on either
predictor variable. The approach is supported by Gay and Airasian (2003) [24] who
argued that using a combination of correlations below 0.50 might yield better
predictions. This therefore implies that the level of ICTs incorporation is still low with
in the banking industry as perceived by the response of the individual customers.
Findings reveal that ATM, wired-wireless availability-accessibility and wired-wireless
use services are significant predictors of the banking industry because their significant t
values are less or equal to 0.05 as opposed to the other services.
4.4 Chapter summary This chapter has generally put forward what the researcher entirely found in the field.
The study was set out to establish the influence of ICT on the banking industry. The
chapter has explained the nature of the background variables and also shown the
variation of the background variables with the dependent variable. Lastly the chapter is
crowned with models fulfilling the objectives of the study, explaining the relationship
between ICT constructs (e-funds transfer, telephone banking and Internet banking
technologies) and the banking industry.
52
Chapter 5
DISCUSSIONS, CONCLUSIONS,
RECOMMENDATIONS, LIMITATIONS AND
FURTHER WORK
5.0 Introduction This is section is the final part of the dissertation and includes: Discussions,
conclusions, recommendations, limitations and further work. Discussions are explained
with an attempt to relate research findings with theory. Conclusions are the researcher's
opinions depending on the outcome from the data analysed as per the objectives of the
study. Recommendations are the way forward resulting from conclusions and are very
vital for policy making. Limitations are set to explain the restrictions of the study.
Further work gives an area of importance that the researcher left unexplored in relation
to the on going study.
5.1 Discussion The first hypothesis stated that the influence of e-funds transfer on the banking industry
in Kampala has been positive, findings from the study indicated that e-funds transfer.
These findings are consistent with findings of several researchers such as Wucker,
(2004), Arch and Burmeister, (2003) who claimed that the e-funds transfer technologies
have positively influenced the customers in the banking industry. The second
hypothesis stated that the influence of telephone banking on the banking industry in
Kampala has been positive; findings are consistent with Idowa et al, (2002) who
showed positive correlates between telephone banking and the banking industry. The
third hypothesis stated that the influence of Internet banking on the banking industry in
Kampala has been positive; findings have revealed that Internet banking technology has
a positive relationship with the banking industry. These findings are not consistent with
53
NST, (2001) and Ezeoha (2005) who explained that insecurity (fear of fraud) has
frightened away would be users of Internet banking. The results indicated stand as they
are probably because unlike the previous years the banking industry has started
incorporating the use of ICTs such as ATMs as away of improving services to their
customers.
5.2 Conclusions The first objective of the study was to identify the influence of e-funds transfer on the
banking industry in Kampala, findings from the study indicated that e-funds transfer
has a low predictive potential of 27% on the banking industry this could be true because
(Kaliisa and Oostdijk, 2006) [36] argued that very few individuals own credit cards in
the developing world which implies that few individual customers in Kampala could be
in position of holding e-funds transfer technologies such as credit cards. This supports
findings in that the beta coefficients for credit-debit card services are insignificant.
The second objective of the study was to identify the influence of telephone banking on
the banking industry in Kampala. Findings have revealed that telephone banking has a
better predictive potential (53%) as compared to e-funds transfer and Internet banking
technologies. The third objective was to identify the influence of Internet banking on
the banking industry in Kampala and it was found that Internet banking has the least
influence on the banking industry (11%) among the three technologies. This could be
attributed to the slow speed of the Internet in developing countries, hence limiting
Internet connection as a result impacting on the usability and functionality of its
application (Kaliisa and Oostdijk, 2006). In general influence of ICT on the banking
industry is still low (54%) in Uganda and is consistent with Kasigwa et al, (2006) [40]
who argued that despite the emphasis placed on ICTs, many ICT initiatives have stalled
in developing countries. According to Pfitzmann et al, (2003) as reported by Kalisa and
Oostdijk, (2006) there is lack of ICT capable financial institutions in developing
countries.
54
5.3 Recommendations The above presentation explains the importance of using ICT to predict the banking
industry, which embeds implications for IT bank managers for helping the banking
industry to improve its services. The results have indicated that there is a positive
relation between ICT and the banking industry, which is an indication that ICT
contributes to improvement in the banking industry services. However it has been noted
that the incorporation of ICTs is still low in the banking industry in Kampala. This
suggests a need to adopt an IT strategy by IT bank managers, placing more emphasis
on the awareness of ICTs while educating individual customers on their existence and
benefits. If technologies such as telephone banking are perceived by customers as
improving service, IT bank managers should support them. User awareness of
telephone banking, e-funds transfer and Internet banking services can be increased
through putting in place community based workshops before introduction of new
technology funded by management of the banking industry. This is recommended
because few people in Uganda are ICT-literate therefore introducing these technologies
without any education about their use might be a loss to the banking industry.
After user awareness then implementation can take place so that what the users have
been taught is put into practice. In the process of implementation emphasis should be
put much more on technologies such as ATM and wired/wireless services because
findings have revealed that these technologies are very significant for the banking
industry. Security should be one of the vital issues to consider, that is to say the
development of e-funds-transfer, telephone banking and Internet banking security
strategies as part of the IT strategy should be put in place since the banking industry is a
risky venture which holds people's finances.
Thereafter IT bank managers can monitor and evaluate the usage of the implemented
technologies, this can be done by identifying the number of customers using a given
technology and how often it is used, with such a measure in place. IT bank managers
can therefore get feed back on which technology that should be improved and then later
plan for their business without wastage of resources. The process of user awareness,
55
implementation and monitoring and evaluation for feedback should be continuous if the
banking industry is to get better results. The above framework however requires heavy
financial investment and critical planning. Basing on the findings the relationship
between ICT and the banking industry can be expressed in form of a model as shown
below.
New model of ICT and the banking industry in Kampala
Figure 2: Source: Namirembe, E. (2007). Influence of ICT on the banking industry:
the case of Kampala. Unpublished Masters’ Makerere University (Management
Information Systems) dissertation, Makerere University, Kampala, Uganda.
As shown in the model above, it has been noted that ATM and telephone services are
significant predictors of the banking industry and the direction of influence is positive
(+).
56
5.4 Limitations Although results of the study have indicated the relationship between ICT and the
banking industry, they cannot explain a casual link between ICT and the banking
industry. According to (Gay and Airasian, 2003), when interpreting any correlation
coefficient, it is important for one to keep in mind that what is being explained is a
relationship not a cause-effect relationship. The sample is limited to individual
customers only. The study is also restricted to the banking industry therefore the results
cannot be subjected to generalisation for other industries.
5.5 Further work While the study has related ICT and the banking industry, the unit of study was
individual customers leaving behind corporate customers. It would be better to
incorporate perceptions of corporate customers to provide integrated perceptions of
customers. The study can be extended to cover other financial services and products
such as insurance and on-line brokerage. While the study related ICT and the banking
industry it did not asses the process through which ICT influences the banking industry,
and this aspect requires further research.
5.6 Chapter summary This chapter is crowned with the discussion, conclusions, limitations and further work
and has noted that ICT is related to the banking industry and with low prediction
potential. This therefore implies that ICTs can be incorporated in the banking industry
but caution has to be taken by IT managers in the banking industry on commonly used
ICTs such as ATMs and telephone technologies. IT bank managers are therefore
advised to create awareness, implement and carry out monitoring and evaluation
measures for feed back to obtain better results.
57
5.7 References
1. Abor, .J. (2005). Technological innovations and banking in Ghana: an evaluation of
customers' perceptions. Journal of Ife psychologIA, 13 (1): 170-187.
2. Al Ashban, A. & Burney, M.A. (2001). Customer adoption of tele-banking
technology: the case of Saudi Arabia. International Journal of Bank Marketing, 19 (5):
191-201.
3. American Bankers Association. (2000). ABA deposit account fraud survey report.
Washington, D.C.: American Bankers Association.
4. Anguelov, C. E., Higert, M.A. and Hogarth, J. M. (2004). US consumers and
electronic bank, 1995-2003.} USA: Federal Reserve Bulletin.
5. Arch, A. M. J. and Burmeister, O. K. (2003). E-banking technologies. ITD Journal,
9 (2): 7-8.
6. Ayadi, A. (2003). Technological and organisational preconditions to Internet banking
implementation: case of Tunisia Bank. Journal of Internet Banking and Commerce,
11(11): 1-15.
7. Bakkabulindi, F. E. K. (2004). Research methods by example. Unpublished
manuscript. Makerere Univesity, Kampala, Uganda.
8. Bakkabulindi, F. E. K. (2006). Social correlates of the diffusion of ICT in
organizations: the case of Makerere University. Unpublished PhD. (Educational
planning, management and administration) thesis, Makerere University, Kampala,
Uganda.
58
9. Barnes, S. J. & Corbitt, B. (2003). Mobile Banking: Concept and Potential.
International Journal of mobile communications, 1 (3): 273-288.
10. Basel Committee on Banking Supervision. (2001). Risk management principles for
electronic banking. Basel: New Basel Committee Publication.
11. Baskerville, R. & Myers, M. D. (2004). Special issue on action research in
information systems: Making IS Research Relevant to Practice-Foreword. MIS
Quarterly, 28 (3): 329-335.
12. Batanda, B.J (2001 April 11). To love, hate the bank ATM. Daily Monitor, p.11.
13. Berger, A.N. (2002). Economic effects of technological progress: evidence from the
banking industry. Journal of Money, Credit and Banking, 35 (2): 141-176.
14. Bohm, N., Brown, I. & Gladman, B. (2000). Electronic Commerce: who carries the
risk of fraud? Journal of Information, Law and Technology, 3 (1), 1.
15. Bradley, L. and Steward, K. (2002). A delphi study of the drivers and inhibitors of
Internet banking. International Journal of Bank Marketing, 20 (6): 250-260.
16. Buys, M. & Brown, I. (2004). Customer satisfaction with Internet banking
websites: an empirical test and validation of a measuring instrument. Proceedings of
the 2004 annual research conference of the South African Institute of Computer
Scientists and Information Technologists on IT research in developing countries.
Hosted by of the South African Institute of Computer Scientists and Information
Technologists and held October 4-6, 2004 at Stellenbosch, Western Cape, South Africa.
17. Constanzo, L. A., Keasey, K. & Short, H. (2003). Strategic approach to the study of
innovation in the financial services industry: the case of telephone banking. Journal of
Marketing Management, 9 (3-4): 259-281.
59
18. Courchane, M., Nickerson, D. & Sullivan, R. (2002). Financial innovation,
strategic real options and endogenous competition: theory and an application to
Internet banking. Conference on innovation and financial services and payment.
Organized by Federal Reserve Bank of Philadelphia May 17, 2002 at Kansas City.
19. Cracknell, D. (2004). Which e-banking initiatives have been successful and why}.
Virtual conference on electronic banking for the poor. Hosted by MicroSave and held
February 16-27, 2004 at Nairobi, Kenya.
20. Davison, R. M., Martinsons, M. G., & Kock, N. (2004). Principles of canonical
action research. Information Systems Journal, 1 (14): 65-86.
21. Egesa, A. (2006). Computer utilisation in the management of the students’
information in Tororo municipal secondary schools. Unpublished bachelors' (of
Quantitative Economics) dissertation, Makerere University, Kampala, Uganda.
22. Eriksson, K., Kerem, K. & Nilsson, D. (2004). Customer acceptance of Internet
banking in Estonia. International Journal of Bank Marketing, 23 (2): 200-216.
23. Ezeoha, A. E. (2005). Regulating Internet banking in Nigeria: problems and
challenges. Journal of Internet Banking and Commerce, 10 (3): 1-5.
24. Gay, L. R. & Airasian, P. (2003). Educational research: competencies for analysis
and applications. 7th. Ed. Upper Saddle River: Merrill Prentice Hall.
25. Gottschalk, P. & Andersen, E. S. (2001). Information technology management.
Oslo: Scandinavian University Press.
60
26. Gourlay, A.R. & Pentecost, E. J. (2002). Impact of network effects on technology
adoption: evidence from the adoption of automated teller machine, Journal of
Manchester school, 70 (2): 185-203.
27. Harris, L. & Spence, L. J. (2002). The ethics of e-banking. Journal of Electronic
Commerce Research, 3 (2): 59-60.
28. Howcroft, B., Hamilton, R. & Hewer, P. (2002). Consumer attitude and the usage
and adoption of home-based banking in the United Kingdom. International Journal of
Bank Marketing, 20 (3), 111-121.
29. Hutchinson, D. & Warren, M. (2003). Security for Internet banking: a framework.
Journal of Logistics Information Management, 16 (1): 64-73.
30. Idowa, P.A.M., Alu, A.O. & Adagunodo, E.R. (2002). Effect of information
technology on the growth of the banking industry in Nigeria. Electronic Journal on
Information Systems in Developing Countries, 10 (2), 1-8.
31. Inyaga, A. (2002). The utilisation of information and communication technology in
the management of Uganda Martyr’s University Nkozi. Unpublished masters (of
Education Managemnet) dissertation, Makerere University, Kampala, Uganda.
32. Kahyana, D. (2005 February 19). Money talk: credit cards are in vogue, but... Daily
Monitor, p.12.
33. Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, (39): 31–36.
34. Kakembo, T. W. (2001 December 6). ATMs/Credit cards improve service quality.
New Vision, p.1.
61
35. Kakinda-Mbaaga, F. (2000). Introduction to social research. Unpublished
manuscript, Makerere University, Kampala, Uganda.
36. Kaliisa, I. & Oostdijk, M. (2006). Towards excellence in Internet security research
for developing countries. Journal of Measuring Computing Research Excellence and
Vitality..., 1 (1): 222-229.
37. Kanyegirire, A. (2004 January 8). Bankom switches on electronic banking. New
Vision, p.19.
38. Karin, B., Laurie, L. A. & Dave, R. (2005). Evaluating the efficacy of credit card
regulation. International Journal of Bank Marketing, 23 (3): 237-254.
39. Karjaluoto, H., Mattilla, M. & Pento, L. (2002). Electronic banking in Finland:
consumer beliefs and reactions to a new delivery channel. Journal of Financial
Services Marketing, 6 (4): 346-361.
40. Kasigwa, J. Williams, D. & Baryamureeba, V. (2006). Sustainable information and
communication technologies development. Journal of Measuring Computing Research
Excellence and Vitality..., 1 (1): 78-88.
41. Kasita, I. (2004 September 21). BOU to upgrade web site. Daily Monitor, p. 16.
42. Kassim, N. M. (2005). Quatar: E-banking service quality: gaps in the Qatari
industry. Journal Internet Banking and Commerce, 10 (2): 5.
43. Kerem, K. (2003). Internet banking in Estonia. Tallinn: TTU Press.
44. Khisa, E. (2003). Information Technology and Organisational Performance in
Uganda’s Insurance Sector. Unpublished masters (of Bussiness Administration)
dissertation, Makerere University, Kampala, Uganda.
62
45. Laforet, S. & Li, X. (2005). Consumers’ attitudes towards online and mobile
banking in China. International Journal of Bank Marketing, 23 (5): 362-380.
46. Lewis, W. (2005). Delivering on the promise to change the banking experience.
The 28th annual Bank Administration Institute (BAI) retail delivery conference &
Expo, a banking industry gathering held November 15-18, at Orlando.
47. Li, S. & Andrew, C. (2004). The relationship between the adoption of Internet
banking and electronic connectivity: an international comparison. International Journal
of Bank Marketing, 19 (4): 156-165.
48. Markus, M. L., Majchrzak, A. & Gasser, L. (2002). A design theory for systems
that support emergent knowledge processes. MIS guarterly, 26 (3): 179-212.
49. Mattila, M. (2003). Factors affecting the adoption of mobile banking services.
Journal of Internet Banking and Commerce, 8 (1).
50. Ministry of Tourism and Industry. (2005 September 2). Standard Chattered
probbing loan fraud : Press review from 1 to 30 September 2005. New Vision, p.9.
51. Monitor Reporter. (2004, August, 16). ATMs revolutionalize banking in Uganda.
Daily Monitor, p.26.
52. Morris-Cotterill, N. (2004). Which e-banking initiatives have been successful and
why. Virtual conference on electronic banking for the poor. Hosted by MicroSave and
held February 16-27, 2004 at Nairobi, Kenya.
53. My Web Times.com (2006, April, 12 ). Illinois taxpayers can get help online.
Ottawa News. p.1.
63
54. Muhasa, C. (2005). Technological innovation, employee attitudes, job design use-
adoption and perceived organisation performance in Uganda. Unpublished masters (of
Business Administration) dissertation, Makerere University, Kampala, Uganda.
55. Mpeera, J. N. (2005). Career resilience and sales force performance. Un published
PhD. thesis, Makerere University, Kampala, Uganda.
56. Nabayunga, H. (2006, April, 3). Stanbic gets mobile ATMs. Daily Monitor}, p.18.
57. Nafula, J. (2006, March, 31). Business. Daily Monitor, p.19.
58. Nath, R., Schrick, P. & Parzinger, M. (2001). Bankers' perspectives on Internet
banking. E-Service Journal, 1 (1): 21-36.
59. NST. (2001). E-commerce, e-trading and Internet money transaction. 11th
Malaysian law conference. Hosted by NST and held November 8-10, 2001 at Kuala
Lumpar.
60. Ongkasuwan, M. (2002). A comparative study of Internet banking in Thailand. Un
published manuscript. Asian University of Science and technology, Chonburi,
Thailand.
61. Oppenheim, A.N (1992). Questionnaire design and interviewing and attitude
measurement. New. ed. Continnum: London.
62. Organisation for Economic Corperation and Development. (2003). Banking
Competition in Latin America. First meeting of Latin American Forum. Hosted by
Latin American Forum and held April 7-8, 2003 at Paris.
64
63. Polatoglu, V. N. & Ekin, S. (2001). An empirical investigation of the Turkish
consumers' acceptance of Internet banking services. International Journal of Bank
Marketing, 19 (4): 192-222.
64. Potter, E. J. (2002). Customer authentication: the evolution of signature verification
in financial institutions. Journal of Economic Crime Management, 1 (1): 1-19.
65. Purcell, F. & Toland, J. (2003). E-finance for development: Global trends, nation
experience and SMEs. Journal on Information Systems in Developing Countries, 11
(6): 1-4.
66. Quirós, G. (2002). The new challenges for the European banking system. Speech at
a seminar. Organized by Ambrosetti and Getronics, April 12, 2002 at Vienna.
67. Rogers E. M. (2003). Diffusion of innovations. New York: Free Press.
68. Rugimbana R. (1995). Predicting automated teller machine usage:the relative
importance of perceptual and demographic factors. International Journal of Bank
Marketing, 13 (4): 26-32.
69. Singh, S., Chhatwal, S. S., Yahyabhay, T.M. & Heng, Y. C. (2001). Dynamics of
innovation in e-banking. 10th European conference on information systems. Organized
by School of computing, University of Singapore and held June 6-8, 2002 at Gdansk,
Poland.
70. Ssettumba, S. (2004 November 30). Payment system heads for better days. Daily
Monitor, p.20.
71. Suganthi, S. Balachandher, K.G. & Balachandran. (2001). E-banking patronage: an
empirical investigation of Malaysia. Journal of International Banking and Commerce,
6 (1).
65
72. Surry, D. W. & Farquhar, J. D. (1997). Diffusion theory and instructional
technology. Journal of Instructional Science and Technology, 2 (1): 1-14.
73. Tabaza, M. (2006 April 2). ATMs are worse than barmen. Daily Monitor, p.6.
74. Tan, M & Teo, T. S. H. (2000). Factors influencing the adoption of Internet
banking. Journal of Association of Information Systems, 15 (3): 168-185.
75. True African. (2006). SMS/Internet Banking. Retrieved May 3, 2006 from
http://www.trueafrican.com/internetBanking.php
76. United States Department of Labor. (2005). Nature of the industry. New Orleans:
Bureau of labor Statistics.
77. Vij, M. (2003). E-banking: An emerging perspective of the regulatory and taxation.
Unpublished manuscript: University of New Delhi, India.
78. Wendy W. N. W, Cheng-Leung L. & Cheris, W. C. C. (2005). Customers' adoption
of banking channels in Hong Kong. International Journal of Bank Marketing, 23 (3):
255-272.
79. Williams, K. (2003). Extending customer choice through prepaid cards: how banks
can profit from the potential of the pay before model, p.13. Retrieved April 29, 2006
from
http://66.249.93.104/search?q=cache:mDktam\_4QNUJ:www.efunds.com/web/pdf/exte
nding\_customer\_choice.pdf+Impact+of+e-
funds+transfer+on+the+banking+industry+in+USA\&hl=en\&gl=ug\&ct=clnk\&cd=5
80. Wucker, M. (2004). Remittances: the perpetual migration machine. World Policy
Journal, 21 (2): 2.
66
81. Yin, R.K. (1984). Case study research: design and methods. London: Sage
Publications.
82. Yeap, B. H. & Chach, K. G. (2005). Do foreign banks lead in Internet banking
services. Journal of Internet Banking and Commerce, 10 (2): 5.
67
5.8 Appendix A
5.8.1 Questionnaire for individual bank customers
SAQ I.D
QUESTIONNAIRE FOR INDIVIDUAL CUSTOMERS ONLY
Dear Sir/Madam,
I am a student from the Faculty of Computing and Information Technology in Makerere
University. You are kindly requested to participate in answering the following
questions, which will be used in establishing the influence of Information
Communication Technology (ICT) on the banking industry in Kampala. The intended
respondents will involve: individual customers only. Any information provided will be
used for academic purposes only. Please feel free to express your thoughts.
Thank you in advance,
Yours faithfully,
68
JAMES BAGUMA
SECTION A: BACKGROUND INFORMATION
This section is meant to provide the researcher background information for statistical
groupings. Please place a tick against any option of your choice in the boxes
corresponding to the questions where possible.
Qn. no Question Coding category 1. Which of the following categories do you belong to? 1. Employed
2. Un employed
2. What is your sex? 1. Male 2. Female
3. What is your age range? 1. Less than 19 years 2. 20-29 years 3. 30-39 years 4. 40-49 years 5. Above 50 years
4. Which Bank (name of the Bank) are you a customer to? ----------------------------------------------------- 5. What type of account do you mainly operate? 1. Current account
2. Savings account 3. Fixed account 4.Mention any other if any----------------------------------------------------------------------
6. What is the level of your monthly salary if any? 1. Less than 90,000/= 2. 100,000-490,000/= 3. 500,000-990,000/= 4. 1,000,000-1,490,000/= 5. Above 1,500,000/=
69
SECTION B: INFLUENCE ON USERS IN THE BANKING INDUSTRY
Please indicate the extent to which the following questions apply to you by placing a
tick against the answer of your choice. In this case 1=Not at all, 2=Little, 3=Fair,
4=Much, 5=Very much
Rating 1 2 3 4 5 Qn. No.
Cash deposit
7. I find cash deposit convenient in the Bank where I hold an account 8. I find cash deposit quick in the Bank where I hold an account 9. I find cash deposit secure in the Bank where I hold an account
Cash withdrawal 10. I find cash withdrawal convenient in the Bank where I hold an account 11. I find cash withdrawal quick in the Bank where I hold an account 12. I find cash withdrawal secure in the Bank where I hold an account
Account balance inquiry 13. I find account balance inquiry convenient in the Bank where I hold an
account
14. I find account balance inquiry quick in the Bank where I hold an account 15. I find account balance inquiry secure in the Bank where I hold an account
70
SECTION C: AVAILABILITY, ACCESSIBILITY AND USE OF ICT
Please indicate the extent to which the following questions apply to you by placing a
tick against the answer of your choice. In this case 1=Not at all, 2=Little, 3=Fair,
4=Much, 5=Very much
Rating 1 2 3 4 5 Qn. No.
E-funds transfer technology
16. ATM services are available in the Bank where I own an account 17. Credit card services are available in the Bank I you hold an account 18. Debit cards services available in the Bank where I hold an account 19. Electronic cheques services are available in the Bank where I hold an
account
20. ATM services are accessible in the Bank where I own an account 21. Credit card services are accessible in the Bank where I hold an account 22. Debit card services are accessible in the Bank where I hold an account 23. Electronic cheques services are accessible in the Bank where I hold an
account
24. I use ATM services in the Bank where I own an account 25. I use credit card services in the Bank where you hold an account 26. I use debit card services in the Bank where I hold an account 27. I use electronic cheque services in the Bank where I hold an account
71
Please indicate the extent to which the following questions apply to you by placing a
tick against the answer of your choice. In this case 1=Not at all, 2=Little, 3=Fair,
4=Much, 5=Very much
Rating 1 2 3 4 5 Qn. no
Telephone banking technology
28. Wired telephone services are available in the Bank where I hold an account 29. Wireless telephone services are available in the Bank where I hold an
account
30. Wired telephone services are accessible in the Bank where I hold an account 31. Wireless telephone services are accessible in the Bank where I hold an
account
32. I use wired telephone services in the Bank where I hold an account 33. I use wireless telephone services in the Bank where I hold an account Internet banking technology 34. E-mail services are available in the Bank where I hold an account 35. Website services are available in the Bank where I hold an account 36. E-mail services are accessible in the Bank where I hold an account 37. Website services are accessible in the Bank where I hold an account 38. I use e-mail services in the Bank where I hold an account 39. I use website services in the Bank where I hold an account
72
5.9 Appendix B
5.9.1 Letter to research expert
Request for expert vetting of the interview guide
FCIT Makerere University, P.O. BOX 7062, Kampala-Uganda,
1/09/2006.
Prof. M.E Amin, Dept of higher education, Makerere University, P.O.BOX 7062, Kampala-Uganda.
Thru,
Dr. Patrick Ogao,
Dear Dr.,
RE: Request for validation of my questionnaire I am undertaking a master’s degree in the faculty of Computing and Information Technology particularly majoring in Management Information Systems. I am requesting you to please check and see if the questions in the interview guide are credible in view of the problem, objectives, research questions and the literature review. The following codes below may please be used for rating of the interview guide: VA=Very appropriate, A=Appropriate, I=Inappropriate and VI=Very inappropriate
I will be very grateful if I can receive the response with in one week in which case I will collect the outcome from your office secretary.
Thank you in advance, Yours faithfully,
73
James Baguma,
James baguma,
6.0 Appendix C 6. 1 CODE BOOK FOR INDIVIDUAL BANK CUSTOMERS IN KAMPALA
Question number
Variable name Variable description Codes
- SAQ ID Questionnaire identification number
001
1. eplyt Category of respondent 1. Employed 2. Unemployed
2. sex Sex of respondent 1. Male 2. Female
3. age Age range of respondent 1. Less than 19 years 2. 20-29 years 3. 30-39 years 4. 40-49 years 5. Above 50 years
4. bank Bank of respondent 1. Barclays 2. Baroda 3. Cairo International 4. Centenary Rural
Development 5. Citi 6. Crane 7. DFCU 8. Diamond Trust 9. National Bank of Commerce 10. Nile 11. Orient 12. Post 13. Stanbic 14. Standard Chartered 15. Tropical Africa
5. typeacc Type of Bank account 1. Current 2. Savings 3. Fixed account 4. Salary account
6. salary Level of monthly salary 1. Less than 90,000/= 2. 100,000-490,000/= 3. 500,000-990.000/= 4. 1,000,000-1,490,000/= 5. Above 1,500,000/=
74
Question number Variable name Variable description Codes 7. convdep Convenience of cash
deposit 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 8. speeddep Speed of cash deposit 1. Not at all
2. Little 3. Fair 4. Much
5. Very much 9. secdep Security of cash deposit 1. Not at all
2. Little 3. Fair 4. Much
5. Very much 10. convwith Convenience of cash
withdrawal 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 11. speedwith Speed of cash
withdrawal 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 12. secwith Security of cash
withdrawal 1. Not at all 2. Little 3. Fair 4. Much
5. Very much
75
Question number Variable name Variable description Codes 13. convbal Convenience of account
balance inquiry 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 14. speedbal Speed of account
balance inquiry deposit 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 15. secbal Security of account
balance inquiry 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 16. avatm Availability of ATM
cards 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 17. avcc Availability of credit
cards 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 18. avdb Availability of debit
cards 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 19. avec Availability of
electronic cheques 1. Not at all 2. Little 3. Fair 4. Much
5. Very much
76
Question number Variable name Variable description Codes 20. acatm Accessibility of ATM cards 1. Not at all
2. Little 3. Fair 4. Much
5. Very much 21. accc Accessibility of credit cards 1. Not at all
2. Little 3. Fair 4. Much
5. Very much 22. acdb Accessibility of debit cards 1. Not at all
2. Little 3. Fair 4. Much
5. Very much 23. acec Accessibility of electronic
cheques 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 24. useatm Use of ATM cards 1. Not at all
2. Little 3. Fair 4. Much
5. Very much 25. usecc Use of credit cards 1. Not at all
2. Little 3. Fair 4. Much
5. Very much 26. usedb Use of debit cards 1. Not at all
2. Little 3. Fair 4. Much
5. Very much 27. useec Use of electronic cheques 1. Not at all
2. Little 3. Fair 4. Much
5. Very much
77
Question number Variable name Variable description Codes 28. avwdtel Availability of wired
telephones 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 29. avwltel Availability of
wireless telephones 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 30. acwdtel Accessibility of wired
telephones 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 31. acwltel Accessibility of
wireless telephones 1. Not at all 2. Little 3. Fair 4. Much
5. Very much
32. usewdtel Use of wired telephones
1. Not at all 2. Little 3. Fair 4. Much
5. Very much 33. usewltel Use of wireless
telephones 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 34. avemail Availability of e-mail
services 1. Not at all 2. Little 3. Fair 4. Much
5. Very much 35. avweb Availability of
website services 1. Not at all 2. Little 3. Fair 4. Much
5. Very much
78
Question number Variable name Variable description Codes 36. acemail Accessibility of e-
mail services 1. Not at all 2. Little
3. Fair 4. Much 5. Very much 37. acweb Accessibility of
website services 1. Not at all
2. Little 3. Fair 4. Much
5. Very much 38. useemail Use of e-mail
services 1. Not at all 2. Little
3. Fair
4. Much 5. Very much
39. useweb Use of website services
1. Not at all 2. Little 3. Fair 4. Much
5. Very much
79
7.0 Appendix D 7.1 Data entry form 1
80
Data entry form 2
81
Data entry form 3
82