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

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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

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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

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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%


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%


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%


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%


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%


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*


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


9.493 4 2.373

Within groups

518.146 414 1.252

Cash withdrawal

1.90 .110


7.381 4 .1.845

Within groups

290.940 414 .703


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






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


89.799 5 17.960

Within groups

437.839 413 1.060

Cash withdrawal

16.94 .01*


14.420 5 .1.845

Within groups

283.901 413 .703


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






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%




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




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

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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



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



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


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


5. Very much 12. secwith Security of cash


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


5. Very much 18. avdb Availability of debit


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


5. Very much 21. accc Accessibility of credit cards 1. Not at all


5. Very much 22. acdb Accessibility of debit cards 1. Not at all


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


5. Very much 25. usecc Use of credit cards 1. Not at all


5. Very much 26. usedb Use of debit cards 1. Not at all


5. Very much 27. useec Use of electronic cheques 1. Not at all


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


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


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


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

Documents

Ict in Banking in Uganda