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Factors affecting the adoption of mobile money services in the banking and financial industries of Botswana
Pako Maradung
Mini dissertation in partial fulfilment of the requirements for Master in Business
Administration
Supervisor: Prof N. Mavetera
Due date: October 2013
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ACKNOWLEDGEMENTS
I am grateful to my many friends, colleagues at Gaborone Technical College, and fellow
MBA students at North West University.
I also owe special thanks to my supervisor, Prof. N. Mavetera, who has guided and
encouraged me throughout the research process. I appreciate his many helpful comments.
Final editing and assembly of the research has been greatly influenced by the efforts ofLyn
Voigt.
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ABSTRACT
This study set out to investigate factors affecting the adoption of mobile money services in
the banking and financial industries of Botswana in the light of the Technology Acceptance
Model (TAM) and demographic variables (that is, age of individuals, income, education
level, bank account) from mobile money service adoption literature.
To do this, a likert-like closed-ended questionnaire was administered to a total of 190
respondents from a targeted sample of 200 users and non-users of mobile banking services
from four regions in Gaborone-Botswana. To ensure diversity in terms of demographic
characteristics, stratified random sampling was done.
The analysis of the results revealed that gross income and ownership of bank accounts
appeared to be insignificant in determining the use of mobile money services in Botswana.
However, the age of individuals did seem to be significant in determining whether an
individuai used mobile money services or not, with more young people preferring to use
mobile money services than older people.
The education of individuals generally did not show any influence on the preference to use
mobile money services to access banking and financial services. Sex/gender was shown to be
significant with more males than females using mobile money services. Employment status
was also significant with more employed individuals preferring to use mobile money services
to access banking and financial services than unemployed.
This study has therefore shown that, despite the lower penetration and absorption of mobile
banking services in Botswana, indicators are that mobile banking is increasingly being
adopted in Botswana especially by males, employed individuals and the youth. This is
encouraging since mobile banking has the potential to improve access to financial and
banking services in Botswana.
Key words: TAM, mobile money services, banking, impact
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TABLE OF CONTENTS
ACKNOWLEDGEMENTS ........................................................................................................................... ii
ABSTRACT ............................................................................................................................................... iii
TABLE OF CONTENTS .............................................................................................................................. iv
CHAPTER ONE: INTRODUCTION TO THE STUDY ................................................................... 1
1.1 Background of Study ..................................................................................................................... 1
1.2 Statement of Problem .............................................................................................................. 2
1.3 Aim of Study ........................................................................................................................... 3
1.5 Research Objectives ................................................................................................................ 4
1.6 Significance ofthe Study ........................................................................................................ 4
1.7 Chapter Summary .................................................................................................................... 4
1. 8 Definition of Terms ....................................................................................................................... 4
CHAPTER TWO: LITERATURE REVIEW ........................................................................................ 5
2.1 Introduction ................................................................................................................................... 6
2.2 Overview ofMobile Money Services ........................................................................................... 6
2.3 Overview of Mobile Money Services in Botswana ................................. .,, .................................. 8
2.7 Merits ofMobile Money Services ............................................................................................... 16
2. 8 Empirical Review ........................................................................................................................ 18
2.8 Technology Acceptance Model ................................................................................................... 20
2.10 Factors Affecting the Adoption of Mobile Money Services ................................................... 23
2.11 Chapter Sumtnary ...................................................................................................................... 26
CHAPTER THREE: RESEARCH DESIGN AND METHODOLOGY .............................................. 27
3.1 Introduction ........................................................................................................................... 27
3.2 Research Design- Quantitative Approach ............................................................................ 27
3.3 Population ............................................................................................................................. 28
3.4 Questionnaire and Sample ..................................................................................................... 28
3.4.1Motivational reasons for selection of stratified sampling method ........................................ 29
3.4.2Motivational reasons for selection of questionnaire .............................................................. 29
3.5 Research Philosophical Perspective ...................................................................................... 30
3.6 Hypotheses and Empirical Sstrategy ..................................................................................... 30
3. 7 Hypotheses ............................................................................................................................ 31
3.9 Chapter Summary .................................................................................................................. 32
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CHAPTER FOUR: DATA ANALYSIS ............................................................................................... 33
4.1 Introduction ................................................................................................................................. 33
4.2 Hypothesis Testing ...................................................................................................................... 33
4.2.2 Gross Income Level ............................................................................................................. 35
4.2.3 Sex/Gender oflndividuals .................................................................................................... 37
4.2.4 Employment Status of Individuals ....................................................................................... 40
4.2.5 Age ofindividuals ............................................................................................................... 41
4.2.6 Ownership of Bank Account ................................................................................................ 43
4.3 Most Popular Mobile Money Services used in Botswana ........................................................... 45
4.4 Most Popular Mobile Money Service Transactions in Botswana ............................................. 46
4.5 Chapter Summary ........................................................................................................................ 47
CHAPTER FIVE: CONCLUSION AND DISCUSSION ..................................................................... 48
5.1 Conclusion .................................................................................................................................. 48
5.3 Limitations ofthe Study .............................................................................................................. 49
BIBLIOGRAPHY ................................................................................................................................. 51
APPENDICES ...................................................................................................................................... 61
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CHAPTER ONE: INTRODUCTION TO THE STUDY
1.1 Background of the Study Access to finance refers to the availability of a supply of reasonable quality financial services
at reasonable cost, where reasonable quality and reasonable cost have to define some
objective standard, with costs reflecting all pecuniary costs. Lack of access to financial
services could be a major constraint on the capacity of the financial system in Africa to drive
growth and reduce poverty (Ikhide, 2008: 15).
Access to financial services has remained a major problem in Botswana. According to
Jefferies (2008: 14), financial access is highly topical in Botswana, reflecting a number of
widespread concerns about the lack of comprehensive coverage of the population by the
financial sector. The importance of access to banking and financial services is reflected in
widespread discussions and policy debates the world over. An estimated 41% of Batswana
have a bank account (FinScope Botswana, 2009) and there have been exponential increases in
the number of people with mobile phones.
The term "mobile money services" in the context of this research refers to the wide range of
mobile banking services. These services include products such as performing balance checks,
account transactions, payments, credit applications and other banking transactions through a
mobile device such as a mobile phone.
A number of commercial banks already offer mobile services to their clients. These include
Barclays, Standard Bank and First National Bank Botswana. However, in this research the
focus will be on both banked and non-banked mobile phone operators. These are Orange
Money, MyZaka Mascom Money and Be Mobile Money.
Non-bank mobile money services offer an opportunity to bridge the gap between the banked
and unbanked population. They play an important role in the access of financial services and
the development of financial services. Mobile banking offers an opportunity to
"revolutionise" access to finance. According to Ondiege (20 1 0:20), a mobile phone can serve
as a virtual bank terminal point of sale.
The use of mobile money services has the potential to enhance access to finance and banking
services because conventional dedicated full service banks with "bricks and mortar" branches
have high costs and staffing requirements and are not viable routes for expanding access to
finance in Botswana. The charges for recovering the costs for establishing branches make the
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banking services unaffordable to many. This, notwithstanding the fact that already banking
charges in Botswana are said to be among the highest in Africa.
Hence, this research project presents a framework that can be used by policy makers in
dealing with the use of mobile money services in accessing banking and financial services in
Botswana.
1.2 Statement of Problem
The issue of factors that influence the adoption of mobile money services in Botswana is not
very clear. Mobile money services providers, policy makers, regulators and related stakeholders
in the banking sector find it difficult to understand the significant factors that influence the
adoption of mobile money services in Botswana leading to low adoption compared to other
countries such as Kenya, Philippines and South Africa. Due to this, it is of vital importance
that Botswana has to address this problem as mobile money services can help bridge the gap
between the banked and unbanked and also lead to financial inclusion.
During the past decade, technological development has reshaped the banking and financial
industry, which has become one of the leading sectors in utilizing new technology in
consumer markets. Today, mobile communication technologies offer a vast additional value
for consumers including banking transactions that are functional and the option to access
banks at any time and anywhere. The terms m-banking, m-payments, m-transfers and m
finance refer collectively to a set of applications that enable people to use their mobile
telephones to manipulate their bank accounts, store value in an account linked to their hand
sets, transfer funds, or even access credit or insurance products (Donner & Tellez, 2008:22-
25). Mobile money offers a new and innovative system that allows customers to carry out
simple banking operations and transactions in total security.
This research hopes to determine the factors affecting the adoption of mobile money services
and evaluate these services in Botswana in the light of the Technology Acceptance Model
(TAM), which is a relatively new technology (Davis, Bagozzi & Warshaw, 1989a;
Mathieson, 1991; Davis & Venkatesh, 1996a). Davis, 1989a, Venkatesh and Davis, 1996b
note that user attitude towards and acceptance of a new information system have a critical
impact on successful information adoption. Aderonke and A yo (20 1 0) argue that the quality
and effectiveness of a system can only be evaluated with its level of user acceptance.
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Adoption of mobile money services delivery is fast gaining ground in Botswana. Different
mobile money services such as My-Zaka Mobile Money, Orange Money, Tobetsa Mobile
Money, Barclays Money, EWallet, B-Mobile Money have been introduced in Botswana.
This study will further examine the attitude of the unbanked that own mobile phones but do
not have bank accounts to mobile money services to determine whether mobile money
services have been really transformational and if they can "revolutionise" the banking and
financial services in Botswana as in countries like Kenya and South Africa, where according
to William and Tavneet (20 11: 17), they have been successful.
Mobile services may enhance access to finance by delivering low cost (and hence low
charge) banking services. The services mostly provided by mobile money services in
Botswana include airtime top-up, bill payments and money transfer (mobile payments).
Mobile money services may transform financial and banking access by extending to the
unbanked. For most, mobile money services may narrow the gap between the banked and
unbanked and help to grow the economy of Botswana.
1.3 Aim of Study
The aim of this study was to look at the factors that currently impact the adoption of mobile
money services in the banking and financial industries of Botswana. This study could be of
significance and value to policy makers, regulators in the banking sector and other related
financial services related to banking. The findings and recommendations for the banking and
financial industry could help to analyse and reform strategies in order to attract customers.
The banking industry can attract potential customers to mobile banking by taking into
account the factors influencing user decisions or preferences.
1.4 Research Questions
1. What are the most popular transactions offered by mobile money service operators in
Botswana?
2. What are the most widely used mobile money services in Botswana?
3. What are the different factors that determine the adoption of mobile money services in
Botswana?
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1.5 Research Objectives
The purpose of this study was to
1. determine the most widely used mobile money services in Botswana
2. evaluate the most popular transactions offered by mobile money service operators in
Botswana
3. To find out factors that determines the adoption of mobile money services in
Botswana.
1.6 Significance of the Study
The results of study may be used to
1. increase awareness of the role played by mobile money services in improving access to banking and financial services
2. enhance the use of mobile money service for banking through the implementation of a marketing strategy
3. highlight areas where possible amendment of current policies may be implemented to enhance the use of mobile money in the banking industries ofBots\vana.
1. 7 Chapter Summary
The chapter provided the aims of the study, objectives, problem statement and research focus.
From the information given in the chapter, it is clear that the concept of mobile money
services in Botswana is a relatively new technology. Money mobile services offer an
opportunity to bridge the gap between the banked and unbanked population of Botswana by
enhancing the access to finance. The main research objective was to investigate to what
extent the population in Botswana has adopted the use of this new technology.
1.8 Definition of Terms
Mobile money services: a facility that allows people to use their cell phones and other hand
held devices to handle financial transactions (Q Finance)
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1.9 Structure of Dissertation
The purpose of this paper is to present empirical insights into the impact of mobile money
services in the banking and financial services of Botswana. Chapter 2 considers the literature
review relating to the use of mobile money services and their impact on banking and financial
services. The methodology of the study is set out in chapter 3. Chapter 4 is based on the
analysis and presentation of results. Finally, chapter 5 presents conclusions and
recommendations.
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CHAPTER TWO: LITERATURE REVIEW
2.1 Introduction
Mobile financial services are among the most promising mobile operations in the developing
world. Mobile money services could become a general platform that transforms entire
economies, as it is adopted across commerce, health care, agriculture, and other sectors
(Donovan, 2012:61). Barnes and Corbitt (2003) suggest that recent innovations in
telecommunications have enabled the launch of new access methods for banking services.
One of these is mobile money services whereby a customer interacts with a bank via a mobile
device such as a mobile phone or personal digital assistant. Mobile money services are
especially useful in developing countries. Some countries like Kenya and South Africa, just
to name a few, are very successful in the use of mobile money services. These services give
users many of whom are poor and have no access to banks a way to save small amounts of
money (Jack & Suri, 2010:6).This chapter reviews international experience on the use,
factors affecting adoption and the success of mobile money services with the hope of
establishing the optimal way to implement the system in Botswana.
2.2 Overview of Mobile Money Services
The informal system of money transfer such as individuals carrying money or sending drivers
and conductors is susceptible to highway robbery and theft (Kim, Mirsobit & Lee, 2010;
Hughes & Louie, 2007). Sander (2003) also notes that money sent through friends and
relatives is sometimes misused and at times does not reach its destination while money sent
via letters and parcels by courier companies may be stolen and is expensive. Other challenges
associated with the formal and semi-formal systems include delays and long queues, network
limitations, insolvency of branches, unreliable communication and misdirected parcels (Au &
Kauffman, 2008).
The situation has changed dramatically in the past few years with the introduction of mobile
phone-based money transfer services. The introduction of prepaid cards of low
denominations and the falling prices of mobile handsets have resulted in a rapid spread of
mobile phones in developing countries (International Telecommunications Union, 2010) (.
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But the real potential of mobile money services may be to make basic financial services more
accessible to millions of poor people across the world. The mobile phone became the first
communications technology to have more users in developing countries than in developed
ones. More than 800 million mobile phones were sold in developing countries in the past
three years (GSM Association, 2006). As mobile phone usage expands, so do the many
opportunities for the unbanked. With mobile banking, low-income people no longer need to
use scarce time and financial resources to travel to distant bank branches. Mas and Radcliffe
(2010) argues that mobile operators in developing countries unlike banks have developed a
usage-based revenue model, selling prepaid airtime to poor customers in small increments,
such that each transaction is profitable on a stand-alone basis. Mobile money services are
already reaching the unbanked poor in countries like South Africa, Kenya and Botswana just
to name a few. One third of people who do not have bank accounts and those that are low
income customers do own mobile phones or have access to one (FinMark Trust, 2004;
FinMark Trust, 2005a). Cobert , Helms and Parker, (2012) state that more than a billion
people in emerging and developing markets have cell phones but no bank accounts. Many
low-income people store and transfer money using informal networks but these have high
transaction costs and are prone to theft. Mobile money is beginning to fill this gap by offering
financial services over mobile phones trom simple person-to-person transfers to more
complex banking services. Kendall and Sonnenschein (2012) note that one of the key
advantages of mobile technology is that it can extend access to banking services for those
who do not live in close proximity to brick and mortar bank branches. Mobile money services
have brought competition and efficiency to the banking and financial services in sub-Saharan
African countries. According to Kendall et al, as a result of their survey conducted in 2011,
mobile money services are popular in Kenya, Tanzania and Uganda. The results of this
survey are detailed in the table below:
Table 1.1: 2011 Gallup study on channels used to send domestic remittances in 2011
Mobile Transfer Money Cash (sent Exclusively
phone from bank transfer by bus or brought
money (%) service(%) through money in
transfer (%) someone person(%)
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else)(%)
Kenya 66 2 1 5 27
Uganda 43 1 0 18 38
Tanzania 32 3 3 16 46
Zambia 4 17 17 33 29
Botswana 4 22 8 13 53
Nigeria 3 29 0 34 34
Rwanda 2 8 2 60 28
South 2 33 13 17 35
Africa
Sierra 0 6 5 58 29
Leone
I Congo ,..,
Source: 2011 Gallup study on channels used to send domestic remittances in 2011
2.3 Overview of Mobile Money Services in Botswana
In Botswana, traditional branch-based banking remains the most widely adopted method of
conducting banking transactions. At the same time, commercial banks are undergoing a
rapid change, the majority of them driven by information and telecommunication
technology. The introduction of mobile money payment services, which has been successful
in other African countries, is a welcome development in Botswana as it will enhance
financial inclusion, that is, including access to financial services by the unbanked
population, especially in rural areas (Bank of Botswana, 2011:1 0). Among commercial
banks, First National Bank Botswana was first to introduce mobile banking services (FNBB,
2012 :12). Today many commercial banks like Barclays Bank Botswana Limited, Standard
Chartered Bank Botswana Limited, Stanbic Botswana Limited and Bank Gaborone
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Botswana have also launched mobile banking services using information and
telecommunication technology, and now they can reach out to the majority of their
customers. These banks also provide customers with not only general information about
their services but also the opportunity of performing interactive retail banking transactions
like depositing and withdrawal of funds anytime, anywhere. Jefferies (2008) maintains that
with regard to geographical access, commercial banks and financial services access are
highly topical in Botswana reflecting a number of widespread concerns about the lack of
comprehensive coverage of the population by the financial sector. Jefferies (2008) concludes
that Botswana's financial sector is dominated by commercial banks, whose main focus is
waged urban employees resulting in banks depriving the rural population of their products,
services and facilities. However, there are risks associated with this service delivery channel,
such as the potential to compromise customer privacy and security, as well as identity theft
and other forms of fraud. The Bank of Botswana (BoB) in the Banking Supervision Annual
Report (20 11) states that banks have given assurance on all the necessary mitigation
strategies that they have put in place. The bank further mentions that as a financial
institution, its supervisors would closely monitor the uptake and the management of these
products.
First National Bank Botswana (FNBB) launched a unique eWallet send money service in
2010. The service is used for transferring money to people with cell phones. The receivers
do not need to have a bank account or a bank card to access the money. They can simply
withdraw their money from one of the ATMs. Recipients who are not FNB customers are
provided with temporary pin numbers that they can use to access the A TMs (FNBB
newsletter 2010). FNB's eWallet send money service offers money senders an instant and
secure money transfer service, as well as offering receivers various electronic transactions
options. FNB customers can send money instantly at any time of the day or night, without
having to wait for the branches to open the next day. The eWallet send money service allows
receivers immediate access to all the money sent to them. Withdrawals can be made in full,
or receivers may choose to withdraw part of the money and keep the rest in an e Wallet for
future use (www.fnb.co.za/cellphone-services/ewallet.html).
Three companies provide mobile phone services in Botswana. These are Mascom Wireless,
Be Mobile and Orange Botswana in partnership with the commercial banks and other micro
finance companies.
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Orange Money is an innovative, mobile phone-based payment system like MyZaka Mascom
Money that allows customers to call security without the requirement of a bank account.
Customers can deposit and withdraw money from an Orange Money account. Customers can
also transfer money from person to person within the country, pay for goods and services
from utility companies and service providers like Orange. Orange Money has been developed
in partnership with Standard Chartered Bank of Botswana Limited to ensure controls and
adherent transactions and compliance to Bank of Botswana regulations. Orange Mobile
payment services have the potential to bring cost-effective and secure access to banking
services to low income people who often live in rural or remote areas. These services also
provide customers with the means to save money and not only reinforce customer loyalty but
also enable customers to play an active role in the economic development of the country
(www.orange.co.bw/services).
MyZaka Mascom Money is a revolutionary service that allows Mascom Prepaid and Postpaid
subscribers to send money to anyone anywhere in Botswana by means of their cell phone,
pay bills and purchase Mascom airtime. Another benefit of the service is that even those
without ceil phones can still receive money through the service, For you to register for the
service you have to follow the normal know your customer (KYC) procedure. The deposits
and withdrawals are only done at MyZaka Mascom Money agents. The sender has to give an
unregistered user the secret code token number and amount sent to enable claiming of the
funds.
Figure 1: The use of Mobile Money Services Source: www.mascom.bw
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2.4 Explanation of Mobile Money Services
Even though mobile money services have not been well defined in literature, it can be said to
include a variety of activities regarding long-distance remittance, micro-payments, and
informal air-time bartering schemes that bring financial services to the unbanked using
mobile technology. Jenkins (2008) defines mobile money services simply as money that can
be accessed and used via a mobile phone. According to Tiwari and Buse (2007), mobile
money services refer to the provision and availability of banking and financial services with
the help of mobile telecommunication devices. Other authors like Pousttchi and Schurig
(2004) add to the definition by saying that in the broader sense mobile money services form
that type of execution of financial services in the course of which, within an electronic
procedure, the customer uses mobile communication techniques in conjunction with mobile
devices.
Figure 2: Source: The Economist 2012
As mobile network operators around the world are discovering, money is a
complicated business (Davidson & Leishman, 2009a) and far more complex than
traditional mobile value added services. Mobile money platforms require that
operators tackle a host of difficult strategic issues and operational challenges. One of
the most difficult of these is the need to put together an agent network (Davidson &
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Leishman, 2009b). Most people think that mobile money services offer users a bank
in their pocket. However, this is not a good metaphor. Customers generally conduct
some transactions, like initiating a peer-to-peer payment using their mobile phones
but it is only when physically present with an agent that customers can convert cash to
electronic money and convert electronic money to cash. In these early days of mobile
money deployment, these services are in high demand (Davidson & Leishman,
2009c). Less tangibly, but equally important, agents are the front-line, human faces
for an operator's mobile money service. When users have questions, they are as likely
to pose them to their local agents as to a call centre; and customers will always have
questions given that mobile money is unlike any services they have used before.
Typically agents are the ones who teach users how to perform transactions using a
mobile phone but some transactions can be performed without the participation of an
agent (Davidson & Leishman, 2009d).
Mas and Morawczynski (2009a) posit that the M-PESA user interface is driven by an
application that runs from the user's mobile phone. M-PESA is a mobile money
service in Kenya which is very successful. This service can be launched right from
the phone's menu; hence it is easy for users to find. The menu loads quickly because
it resides on the phone and does not need to be downloaded from the network each
time it is called. The menu prompts the user to provide all the necessary information,
one piece at a time, based on the type of transaction requested. Once all the
information is gathered, it is sent for processing through the air interface in a single
text message. The figure below shows schematically the structure of the M-PESA
user menu (Mas & Morawczynski, 2009b ).
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Call up main ~ From main phone ---;ill" menu, select ~
phone menu Apph'callons
From Applications menu, select
Safaricom
From Safaricom menu, select:
M-PESA
FromM-PESA menu, select
/~--,-·-------,,
Confirm OK ~ Enter PIN -E-- Enter amount -cE-- Enter phone #
Confirm OK ~ Enter PIN -E-- Enter amount -E-Conflrm OK -cE-- Enter PIN -E-- Enter amount
Confirm OK -E-- Enter PIN -E-- Enter amount -E-- Enter phone #
Enter agent #
tv't; phone l _Other p_hone _,
Confirm OK -E-- Enter PIN -E-- Enter amount -E-- Enter acct # -E-- Enter business #
Enter PIN -E-- Enter agent #
From My Account menu, select
Enter PIN
~ Confirm call OK
Repeat new PIN -E-- Enter new PIN -E-- Enter old PIN
Confirm OK ~ Enter PIN -E-- Enter new secret word
Enter PIN
EnterPIN -E-- From Language menu,select Engh'shor Kiswahili
Show balance
Call support
Change PIN
Secret word
Update menu
Language '-------/
Figure 3: Source: Ignacio Mas and Olga Morawczynski (Lessons from M-PESA)
Send f'fl)lfey
Withdraw cash
Buy airtime
Pay goods
Pay bill
ATMwilhdrawal
tv't; account
Wizzit Payments (Pty) Ltd is the South African mobile banking service for the unbanked
and under-banked, meaning people or enterprises that have no or only limited access to
banking services. Its services are based on the use of mobile phones for accessing bank
accounts and conducting transactions, in addition to a Maestro debit card that is issued to
all customers upon registration. Wizzit is a branchless banking business, meaning that its
services are designed so that customers can generally conduct transactions without the
need to visit bank branches. It has partnered with Absa Group and the South African Post
Office. Ivatury and Pickens (2006) state that Wizzit is for low-income customers and they
give mobile banking high marks for its convenience, accessibility and affordability. They
continue that a Wizzit account is as much as one third cheaper than an account at one of
South Africa's big retail banks for the same basket of services. Customers can use their
mobile phones to make person to person payments, transfer money, purchase prepaid
electricity, and buy airtime for a prepaid mobile phone subscription. Customers can also
make cash deposits at any Absa Bank or Post Office branch.
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Figure 4: Source: (http://www.sapo.co.za)
2.5 Current Situation of Mobile Money Services in Botswana
Botswana has a potential to expand mobile money services because of the high ownership of
mobile phones. The total number of mobile phone subscribers is approximately 144 mobile
phone subscriptions per 100 people (World Bank, 2011: 1 0). The use of mobile money
services worldwide is almost 30 million active users (Penicaud, 2012:30). This is besides the
availability of alternative methods of payments such as credit cards. The significantly high
percentage of unbanked population, with only 20% of the population holding bank accounts,
highlights the role of mobile money services in Botswana. According to Bangens and
SOderberg (2008:4), the unbanked are predominantly rural poor people who live in a highly
informal, cash-based economy. Bangen et al (2008:4) further maintain that unbanked people
are willing to adopt new technologies when they have real needs; that is, a problem that can
be solved by technology.
There are currently ten commercial banks in Botswana. (Banking Supervision Annual Report,
2011:8). Yet internet banking has not taken off in Botswana because of the low rates of
internet penetration.
2.6 Risk and Security of Mobile Money Services
The security and the trustworthiness of a service have been identified as the most important
factors within every target customer segment when the use of a service delivery channel is
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decided (Githui, 2011). Mattila (2002) maintains that there is trustworthiness in the usage of
mobile phones in transferring money. Davidson and Leishman (2009d) also talk about
trustworthiness; they mention that customers will never use mobile financial services if they
do not believe that their money will be safe. They conclude that fraudulent financial services,
although usually on a small scale, do emerge in developing markets from time to time,
leading to customers being sceptical about trusting someone else with their money. The word
"risk" as defined by Fain and Roberts (1997) is a perception of consumers, not characteristics
of a product. Other authors like Sharma and Singh (2009) note that Indian mobile banking
service users - especially illiterate people - are especially concerned about security issues.
These involve financial fraud, account misuse and user friendliness issues like difficulty in
remembering the different codes for different types of transactions, application software
installation and updating because of lack of standardisation. Solin and Zerzan (20 1 0) believe
that every payment system has some vulnerability that could facilitate a money laundering
and terrorist financing (ML/TF) risk. However, in markets with the highest demand for and
success of mobile money services, cash transactions are the predominant transaction type.
Solin and Zerzan conclude by comparing the generic vulnerability of cash and mobile
transactions based on the World Bank's risk factors ifthere are no anti-money laundering and
combating financial terrorist controls in place as shown in the table below.
Table 2: Comparison of risk factors involved in cash and mobile transactions
General risk factors Cash Mobile money
Anonymity Indicates risk is highly Indicates risk is somewhat
prevalent prevalent
Untraceable transactions Indicates risk is highly Indicates risk is somewhat
prevalent prevalent
Rapidity Indicates risk is low Indicates risk is highly
prevalent
Lack of oversight Indicates risk is highly Indicates risk is low
prevalent
Source: www.worldbank.org
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2.7 Merits of Mobile Money
Mobile money services have the potential to extend services beyond the reach of the formal
financial sector. Besides helping to organise domestic money transfers, mobile money can
improve the national payments system by providing innovative ways to meet the transaction
needs of ordinary people. Success of this calls for a better understanding of people's needs,
current adoption and usage patterns of mobile money along with accompanying motivations
and perceptions (Drake, John, Doreen & Muyingi, 2008:9).
Williams and Torma (2007) provide additional theoretical and anecdotal evidence of the
impact of mobile financial services. They argue that access to banking has a two-fold impact
on low-income households. First, the benefits of access to finance are exclusively
improvements in the quality of people's lives, such as saving time, reducing the threat of
crime and making transactions easier. The second merit introduces additional benefits which
flow from establishing financial track records.
Financial records reduce informational asymmetries, allowing beneficial financial
instruments that include debt financing (such as mortgages) and long-term savings products
(such as pensions). Although researchers have yet to be able to systematically document the
relationship between mobile money and more sophisticated financial products, anecdotally,
there is an improvement in the quality of life arising from the use of mobile money services.
Heyer & Mas (2009:4) give an example of South African farm workers who previously had
to travel for hours, spending considerable sums, to purchase airtime, but can now do so "for
less than one rand and eliminate all the travel time". Mobile money is useful as a retail
payment platform because it has extensive reach into large segments of the population.
The mobile money operational overview maintains that mobile money has created
commercial opportunities for entrepreneurial customers to derive a supplementary source of
income (Jenkins, 2008).
Kleine (2010:8) identifies user control as a key feature of interactive technologies. It is also
frequently mentioned as a benefit of mobile transaction services (Aderonke & Ayo, 2009:20).
User control is defined as the extent to which consumers can determine the timing, content,
and sequence of a transaction. Pickens, Mark, David and Sarah (2009: 12) highlight that
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people's perceptions of control over situations increase the likelihood of their positive
feelings toward the experience.
Furthermore, user control leads consumers to believe they can influence their goal attainment
process and thereby increase their confidence about the outcome (Kleijen et al., 2004:15).
Money mobile services, by providing consumers with real-time, on-demand access to
services, provide benefits that will enhance their perceived value.
Figure 5: A typology of mobile money from Colombant (20lla)
One of the reasons mobile money has attracted considerable attention is the expectation that it
can provide affordable financial services to previously excluded populations. Literature on
financial inclusion emphasises that "banking the unbanked" can lead to better
decision-making, more efficient markets, and various other development goals (Lyman,
Pickens & Pretorius, 2008). Throughout the developing world, mobile phones have emerged
as one of the most widely diffused technologies imaginable to replace traditional brick-and
mortar infrastructure, such as bank branches.
Ivatury and Mas (2008) provide additional evidence about the early uses of mobile phones as
financial service platforms. Cost reduction, which can be passed on to the user, is a major
benefit. In the Philippines, a typical transaction through a bank branch costs the bank
US$2.50; this would cost only US$0.50 if it were automated by using a mobile phone. In
Pakistan, Tameer Bank estimated that opening a bank branch in a Karachi slum would cost
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thirty times what a retail agent would cost, and monthly operating costs would be US$28,000,
compared with US$300 for an agent.
Mobile banking has the potential of offering these higher quality services. In contrast to
traditional branch banks, mobile networks are generally widespread in developing countries
making it possible for low income and rural segments of the population to access the service
and reduce transaction costs. Informal financial services electronic transactions are made in
real time, are supervised and are thus reliable.
2.8 Empirical Review
In a research carried out by the Department for International Development's (DFID), (2008)
it is noted that policy makers and regulators in developing and emerging economies are
embracing the use of information and communication technologies (ICTs) and non-bank
retail channels to reduce costs of delivering financial services to clients beyond the reach of
traditional banking. The DFID (2008) research was carried out in seven countries, targeting
the unbanked poor in South Africa, Kenya, Philippines, India, Pakistan, Russia and Brazil.
High dissimilarities were evident in the various countries depending on the continent.
However, the policy makers and regulators in these countries studied have a common feature:
the unbanked are people without formal bank accounts who operate in a cash economy; they
are limited in their ability to take out loans, maintain savings or make remote payments, and
these constraints can inhibit their economic opportunities.
Challenge: how to formulate proportionate regulatory policy that gives space for innovation
and permits branchless banking to scale up safely.
Ivatury, Gautum, Mas and Ignacioa (2008: 12) focus on smaller banks and micro institutions
(MFis) that face a much higher cost-of-delivery because of the smaller transaction values
they handle and the likely more remote and dispersed location of at least some of their
customers. Their discussion highlights that the banks and MFis have adequate back office
and transaction switching capability and sufficient internal controls, whether managed in
house or outsourced. Without that, mobile banking is not possible because it is fundamentally
a front end to a financial institution's information technology system.
Mas & Ignacio (2008: 16) have developed a broad vision for financial inclusion, by which
payments can be made easily through an electronic network. What makes visioning such a
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payments utility possible is the technology available today, which can be used to bridge
distances, close information gaps, contain settlement risks and generally reduce transaction
costs. Mas et al (2008) outlines the main challenges for the mass deployment of branchless
banking.
Mas & Ignacio (2008:17) highlight that even when there are agency networks with third
parties to serve as their retail channels, banking regulations require banks to retain legal and
financial responsibility for the actions of all their retailers. Banks can outsource their
operations, but cannot delegate responsibilities. This naturally diminishes the banks'
"appetite for entering into such arrangements and fragments the universe of retailers into
exclusive retail bank franchises. Banks may achieve lower costs, but these retail
arrangements do not transform the nature of the problem. It remains difficult and costly for
banks to go after business when the volume of deposits is relatively low, either because of
low population density or low income levels.
Morawczynski and Pickens (2009:18) conducted ethnographic research on M-PESA studying
how people belonging to two places, Kibera and Bukura, supported mobile banking services.
The research offers insight into how poor people use M-PESA, its impact on their lives, and
some unexpected consequences. Rapid adoption and frequent use ofM-PESA engendered a
variety of positive outcomes, as well as unintended consequences. By partnering with
financial service providers and mobile operators, banks can play a significant role in
mobilising savings using mobiles as a tool of financial inclusion.
Puhazhendi (20 1 0:22) in his study of the microcredit programme of the nationalised
commercial banks in India, concludes that the intermediation of non-governmental
organisations (NGOs) and self-help groups (SHGs) in the credit delivery system reduces the
transaction costs of both banks and borrowers.
Tankha (2002:30) concludes that group formation costs are impacted by the number of
groups handled by one field worker, transport costs, training costs and regional differences in
average staff salaries owing to differentials in local wage structures.
Sarah, Mas & Ignacio (2008:14) reviewed some of the bigger failures and some ofthe more
promising experiences in the use of smartcards and mobile phones as payment platforms in
developed countries. The objective of the study was to extract some lessons from the failures
and the successes, although these developed country experiences may not directly translate
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into lessons that can be used in developing countries. Their study informs about what may or
may not be possible and may or may not be different in the developing world context.
In South Africa, mobile money pioneers, Ivatury and Pickens (2006), surveyed 515 low
income individuals, 215 of whom used Wizzit, a mobile banking service, and 300 of whom
did not. The authors note that the sampling methodology had a number of weaknesses, but as
an exploratory study, the results can be considered indicative. Customers lauded Wizzit for
its convenience, accessibility, and affordability. A Wizzit account was found to be as much as
one-third cheaper than an account at one of South Africa's big retail banks for the same
basket of services. However, the very poor were not using mobile money because of the
expense, lack of awareness, the complexities of the technology and a belief that the service
was not appropriate for them. Therefore, users tended to be wealthier than non-users, and
more employed, disproportionately male and better educated.
Ivatury and Pickens (2009) assessed 62 banks and microfinance institutions (MFis) using ICT
(information computer technology) to deliver financial services to poor people. Of these, only
ten were using mobile phones, as opposed to A TMs or point-of-sale terminals. Providers
were motivated to use ICT by a desire to improve customer convenience, lower processing
costs and increase coverage, revenue and holdings. The available data gave empirical
evidence that the poor and remote populations were benefiting, especially the unbanked
population.
More recent analysis of pricing of mobile money corroborates the reduced costs. In an
international comparison of the cost of 16 branchless banking operations (including Mobile
Money) against 10 traditional banks in a recent review, Ardic, Heimann and Mylenko (20 11)
targeting the poor, found that branchless banking was 19% cheaper on average. At low
transaction amounts, the difference is even higher, at 38%. It is also 54% cheaper than
informal money transfer options. In Kenya, low-income households spend 0.04% of their
GDP share on branchless banking compared to 0.07% on average, and M-PESA is routinely
one-third to one-half cheaper than even these alternatives.
2.9 Theoretical Foundation of Mobile Money Services Adoption
The Technology Acceptance Model (TAM) is one of the most utilised models in studying
information system acceptance (Davis ., 1989; Mathieson, 1991; Davis & Venkatesh, 1996).
Adesina (20 1 0) defines TAM as an information system theory that models how users come to
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accept and use a technology. Davis (1989: 14) proposes an adaptation of the Theory of
Reasoned Action (TRA) which is a theoretical model for explaining users' acceptance of a
new information technology (IT). Development of TRA started in the 1950s and the first
research concerning TRA was published in 1967 (Ajzen and Fishbein, 1980). According to
TRA, an individual's behavioural intention, which results in actual behaviour, is influenced
by his/her subject norm and attitude, and the attitude is influenced by individual beliefs
(Ajzen & Fishbein, 1980:13). Based on the causality ofTRA, TAM uses perceived usefulness
and perceived ease-of-use as key determinants to explain users' acceptance of IT (Davis,
1989a:28). Perceived usefulness is defined by Davis (1989b) as "the prospective user's
subjective probability that using a specific application system will increase his or her job
performance within an organizational context" and perceived ease-of-use is defined as ''the
degree to which the prospective user expects the target system to be free of effort".
Perceived usefulness is related to productivity but perceived ease-of-use is related to effort
(Venkatesh, 1999:30). These two beliefs influence an individual's attitude that results in
his/her behavioural intention, which finally influences his/her actual usage of IT (Davis,
1989c:28). In addition, perceived ease-of-use affects perceived usefulness because the easier
IT is to be used the more useful it will be.
In the context of e-commerce, trust is considered a key construct of behaviour, because e
commerce transactions are conducted through the internet without face-to-face meetings
(Grazioli & Jarvenpaa, 2000:13).Trust refers to "an individual's belief that others will
behave based on an individual's expectation" (Grazioli & Jarvenpaa, 2000:7). The latter
proposes determinants of trust as satisfaction with past transactions and reputation (Pavlou,
2003:13), social presence (Gefen, Karahanna & Straub, 2003:10), familiarity and disposition
(Gefenet al., 2003: 12).
According to Mathieson, (1991) and Davis and Venkatesh (1996), TAM has been tested
widely with different samples in different situations and proposed to be a valid and reliable
model explaining information system acceptance and use. Many extensions to the original
TAM have been proposed (Venkatesh & Speier, 1999; Venkatesh et al., 2003 etc). Venkatesh
and Davis (2000) and Morris and Venkatesh (2000) introduced the second version ofT AM,
labelled T AM2 to explain how subjective norms and cognitive instrumental processes affect
perceived usefulness and intentions.
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Several studies have been conducted to replicate and extend TAM to determine factors
affecting technology adoption in organisations. Venkatesh et al (2000) applied TAM in a
longitudinal study to include social influence processes and cognitive instrument processes.
TAM was also tested by Grandon and Pearson (2004) in the small business context in the
USA. They identified four factors that influence electronic commerce adoption:
organisational readiness, external pressure, perceived ease of use, and perceived usefulness.
2.10 The Model
Based on the literature review, a model indicating the adoption of mobile money services was
developed (figure 2). The model consists of six factors that are considered to have an effect
on adoption of mobile money services.
Level of education
I PVPI nf inrnmP
I Age of individuals ~ H3
L__ H4 Employment status !
H2
HS
Hl
H6
Ownership of a bank account ~
Adoption of mobile
money services in the
banking and financial
services of Botswana
Figure 6: Adapted extended TAM model of factors affecting the adoption ofMMS
2.11 Research Model and Hypothesis
Extended TAM is a widely used and proven model of investigating users' adoption of
information technology. The extension refers to the introduction of external variables and the
measurement of their impact on the acceptance of use of information technology. Extended
TAM is adopted as the theoretical framework in this research. Extended TAM in the study
includes variables such as age, gender or sex, income, educational level and bank account.
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2.12 Factors Affecting the Adoption of Mobile Money Services
2.12.1 Apparent cost of mobile money services
Perceived financial cost has been added to the original TAMconstructs and was found to be
positively associated with consumer intentions to use mobile banking services (Kleijnen,
Wetzels, & Ruyter, 2004:20-25). The higher the usage cost, the less willing is the consumer
to adopt mobile money services. The better the affordability, the more consumers are willing
to adopt mobile money services.
2.12.2 Demographics
The impact of demographics on electronic services adoption has been extensively studied in
the past (Cruz, Laukkanen, Muftoz-Gallego, 2009; Nysveen, Pedersen, Thorbjornsen, 2005;
Laukkanen, Sinkkonen, Kivijarvi, 2007; Laukkanen & Pasanen, 2008). Studies focusing on
the adoption of new technologies refer to a predominance of male, younger, more educated
and higher income persons, when compared to those who do not adopt innovations (Sim &
Koi, 2002)
2.12.3 Education
Household income and education have been shown to have a significant impact on the
adoption of internet banking services (Mattila, Karjaluoto & Penta, 2003). Padachi et al.
(2007:566) argue that the higher the education level achieved, the greater the probability of
the customer adopting internet banking; the higher the income ladder, that is, the more
affluent people are, the more likely they are to possess cell phones, thus more likely to use
internet banking. A greater level of education could lead to a greater understanding and
ability regarding self-service technologies (Meuter, Ostrom, Bitner &Brown, 2005) and lower
perceptions of complexity of innovations. A higher household income could also represent,
simultaneously, greater time-saving motivations to use mobile services, as well as utilising
opportunities for accessing updated devices, such as mobile ones (Meuter et al., 2005: 12).
Hypothesis 1: Other things being equal, the use of mobile money services to access banking and financial services is not significantly determined by levels of education.
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2.12.4 Income
Income has been established to be significant in determining the adoption of mobile money
services. According to Madden and Savage (2000), individuals who tended to use the internet
early in Australia were young males, with high levels of income and education. Furthermore,
Rogers (2003) shows that demographic attributes play an important role in predicting adoption
and that economic status/income is highly correlated to initial adoption.
Hypothesis 2: Other things being equal, the use of mobile money services to access banking and financial services is not significantly determined by income level.
2.12.5 Age
Previous research shows that older people have a lower tendency to adopt new technology
based services (Oumlil and Williams, 2000:21). According to Rogers (2003a) the adopter of a
new technology is typically younger, has a good income and appropriate level of education
and more reactive to new innovation than a non-adopter. Padachi, Rajid, Seetanah,
(2007:566) maintain that the younger the generation the more they are used to new
technological advancements as compared to the older generation; thus they are more likely to
adopt internet banking. Earlier studies (Laukkanen et al.; 2007) show that mature customers
have more resistance to internet and mobile banking services than younger bank customers.
Laukkanen and Pasanen (2008) argue that a typical Finnish mobile banking user is more
likely to be middle-aged (30 - 49 years old) and the same pattern could be found for China
(Laforet & Xiaoyan, 2005) and Japan (Flinders, 2008).
Hypothesis 3: Other things being equal, the use of mobile money services to access banking and financial services is not significantly determined by the age of individuals.
2.12.6 Employment status
The employment status of individuals is a significant factor in whether an individual uses or
adopts mobile money services. According to Medhi, Ratan andToyama (2010:489), the
uptake ofm-banking services in a location seemed to depend on whether adoption was forced
or optimal depending on the kind of employment of the household's wage earners.
Hypothesis 4: Other things being equal, the use of mobile money services to access banking and financial services is not significantly determined by the employment status of individuals.
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2.12.7 Gender
Gender or sex is among the most researched demographic determinant in mobile and
electronic services. Chen and Wellman (2004) in a study which focuses on internet usage in
China, Germany, Korea, Italy, Japan, Mexico, UK and the USA find that men are more likely
than women to use the internet and the rate of adoption is high for young people who
understand English and live in urbanised environments. When compared to women, males
perceive less risk in online business activities (Garbarino and Strahilevitz, 2004; Nysveen, et
al, 2005). Males tend to evaluate mobile commerce more positively than women (Yang,
2005:8). Some studies evidence a male preponderance among users of mobile banking
services (Flinders, 2008; Laforet & Xiaoyan, 2005; Laukkanen & Pasanen, 2008).
Hypothesis 5: Other things being equal, the use of mobile money services to access banking and financial services is determined by the sex/gender of individuals.
2.12.8 Bank account
Mobile money services have enabled easy access of the unbanked to financial and banking
services. Heyer and Mas (2009) argue that access to forma! bank accounts may be very
limited in emerging markets, as banks are often not able to compete directly with non-bank
providers owing to higher fixed and operating costs and much more limited physical
presence. The first group of factors for M-PESA's success points to failure by the existing
financial institutions to meet the needs of the unbanked (Ngugi & Pelowski, 2010:7a).
According to Ngugi and Pelowski (2010:7b), only 19% of the Kenyan population had access
to banking services by the time M-PESA was launched in 2007.
Hypothesis 6: Other things being equal, the use of mobile money services to access banking and financial services is not significantly determined by the ownership of a bank account.
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2.13 Chapter Summary
The chapter provided the literature covering critical issues of the use of mobile money
services in Botswana and its current adoption in other countries in and outside Africa. The
various theoretical concepts by various authors about definitions, measurements, factors
affecting the adoption of new technology as well as conceptual issues surrounding money
mobile services brought the focus closer to the research domain. The chapter also gave an
account of a variety of empirical studies undertaken by various researchers, and their findings
on the adoption of information technology related products.
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CHAPTER THREE: RESEARCH DESIGN AND METHODOLOGY
3.1 Introduction
This chapter deals with the research methodology used in this dissertation to test the factors
affecting the adoption of mobile money services in the banking and financial services
industry of Botswana. On the basis of previous studies on computer technology and
information systems acceptance, the use of the information system was chosen to be the
indicator for success (Davis , 1989c; Davis, 2003 Al-Gahtani, 2001). The adoption of mobile
money services was chosen as the dependent variable in the model. This is in line with other
studies, in which actual usage has been selected as the measure of the use (Legris, Ingham &
Collerette, 2003).
Selecting specific research strategies and methods for a particular study is undoubtedly a
challenging task. However, in this study a survey strategy through self-administered
questionnaires to answer the research questions was employed. The methodology referred to
here comprises a set of techniques that researchers use to conduct an enquiry. Miller and
Brewer (2003) maintain that methodology constitutes a set of rules and procedures to guide
research against which its claims can be evaluated, Saunders; I ,ewis and Thornhill (2007)
posit that a survey strategy is perceived as authoritative by people in general, because it is
easily understood. This strategy also allows for the collection of a large amount of data from
a sizeable population in a highly economic way. However, this method is regarded as time
consuming when it comes to designing and piloting questionnaires. This chapter covers the
research design, population of the study, sampling procedure, data collection methods, data
analysis, reliability and validity of the study and ethics. The study justifies the main reasons
for using primary data and argues that the reason for choosing the Gaborone region was that
Gaborone is a fast growing city in Botswana. Moreover, time and financial constraints led to
the adoption of a study in Gaborone as opposed to other regions. Furthermore, a justification
of data collection methods that were used in the research is also provided and finally, the data
sample and the data collection procedures are briefly discussed.
The research design of this study involves a quantitative consumer survey. It is conducted in
the form of a questionnaire to identify the factors affecting the adoption of mobile money
services in the banking and financial services of Botswana.
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3.2 Population
A population can be defined as including all people or items with the characteristics one
wishes to understand (Kerlinger, 1986). The target population of this study consisted of users
of both bank based mobile money services and non-bank based mobile money services, in
Gaborone the capital city of Botswana.
3.3 Questionnaire and Sample
The data was collected via stratified sampling distribution. The stratified random sampling
method was adopted. Cooper and Schindler (20 11) define stratified sampling as the process
by which the sample is constrained to include elements from each of the segments, while
Saunders,et al.(2007) define stratified random sampling as a modification of a random
sampling in which the population is divided into two or more relevant and significant strata
based on one or a number of attributes through a self-administered questionnaire. The
questionnaire for this study was distributed among Gaborone individuals who use mobile
money services, but did not use the services in Gaborone during July 2012. The reason for the
choice of the city was that it has a large population and many banks and technology
companies offering these services and as such provides a very good unprejudiced sample of
the mobile money services in Botswana. In this study, individuals who used mobile money
services as well as those who did not use mobile money services filled in the questionnaires
because they had the relevant information about the issues relating to mobile money services.
To ensure that the questionnaires had a good measure of reliability and validity, the "Likert
style" rating and "list questions" methods were used to design the questionnaire.
Furthermore, pilot testing was undertaken on questionnaires through classmates and friends
with the approval ofthe supervisor.
Initially the sample of 200 questionnaires was distributed physically in four regions of
Gaborone, and 50 individuals were randomly selected. This was the best method to choose
because it can cover a large and geographically dispersed population. However, the problem
of a very low response was encountered, being only 60% after two weeks. To overcome this
problem, 80 more questionnaires were printed and distributed, resulting in a response rate of
90% (190 out of200 questionnaires were filled in, returned and were usable). The advantage
of using stratified sampling distribution over other sampling methods is that it focuses on
important subpopulations but ignores irrelevant ones; it improves the accuracy of estimation
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and is efficient. Sampling equal numbers from strata varies widely in size and may also be
used to equate the statistical power of tests of differences among strata. However, the
limitations are that it can be difficult to select relevant stratification variables; it is not useful
when there are no homogeneous subgroups; it can be expensive; and requires accurate
information about the population, or it introduces bias. It also looks randomly within specific
sub-headings. The population of he city of Gaborone was stratified into four regions:
Gaborone North, Gaborone Central, Gaborone West and Gaborone East
3.4.1Motivational Reasons for Selection of the Stratified Sampling Method
According to Cooper and Schindler (20 11 ), there are three reasons for a researcher to choose
a stratified random sample:
1. To increase a sample's statistical efficiency
2. To provide adequate data for analysing the various subpopulations or strata
3. To enable different research methods and procedures to be used in different strata
3.4.2 Motivational Reasons for Selection of Questionnaire
Questionnaires: Questionnaires were used to gather information about the users such as
information on their educational and income levels. The choice of questionnaire as the data
collection technique was based on its advantages over other competing data collection
methods such as face-to-face interviews, observations, and focus group discussions (FGDs).
A questionnaire gives the respondents the freedom to answer questions without undue
influence and is also inexpensive. Also when properly structured, a questionnaire ensures that
every respondent is asked the questions in exactly the same way. Extensive secondary
material such as journals within mobile phones, ICT and banking/finance contexts, reports
from the bank of Botswana, the Ministry of Finance and statistics Botswana was also
assessed and deductively applied.
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3.4 Research Philosophical Perspective
According to Myers (2008), all research can be classified into three philosophical categories:
positivist, interpretive and critical philosophical perspectives. The philosophical perspective
that was adopted by this study was the positivist approach because it allowed the researcher
to collect and analyse the data before arriving at any conclusions.
3.5 Hypotheses and Empirical Strategy
As discussed in chapter 2, literature on mobile money services was obtained from different
theories and indicated that mobile money services users prefer using mobile cell phones for
transactions to the bricks and mortar banking and financial services. According to this theory,
a broad number of financial transactions can be done through a cell phone. According to Jack
and Suri (20 11 :30), early on in the banking revolution using mobile phones, cell phone users
realised that they could effectively transfer money across vast distances. Phone companies
have long allowed individuals to purchase "air-time" (that is, pre-paid cell phone credit that
can be used for voice or SMS communication) and send this credit to other users. It was a
small step for the recipient user to on-seii the received air-time to a local broker in return for
cash, or indeed for goods and services, thus effecting a transfer of purchasing power from the
initial sender to the recipient. Mobile money services are especially useful in developing
countries like Botswana. Workers in towns can send money to their families in the villages
without wasting a day travelling by bus. People can also pay their household bills directly
from their phones. As noted by Mas & Ignacio (2008:27), a broad vision for financial
inclusion, involving easy payments through an electronic network, would cut down on the
cost of transactions, both business and personal, significantly. What makes visioning such a
payments utility possible is the technology available today; this can be used to bridge
distances, close information gaps, contain settlement risks, and generally reduce transaction
costs. One of the reasons mobile money has attracted considerable attention is the expectation
that it can provide affordable financial services to previously excluded populations (Lyman,
Pickens & Porteous, 2008:8). Moreover, mobile money services are safer too- nobody wants
to carry a lot of cash on public transport.
A number of studies have explored the factors that influence the adoption of mobile
technology, specifically mobile phones, from a business perspective. Apart from the
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technology and mobility attributes already mentioned, the usage costs emerge as an important
influence (Zhang & Yuan 2002:16). Regarding the evidence on the adoption of mobile
money services as far as banking and access to financial services are concerned, Dass and Pal
(2012:30) believe that financial institutions, which have had difficulty providing profitable
services through traditional channels to poor clients, see mobile financial services as a form
of "branchless banking". However, there has been lack of research in Botswana on
determining the factors that affect the use of mobile money services in the country. Because
ofthe vital role played by mobile money services, the hypothesis drawn from the literature in
this study is: The use of mobile money services is not significantly determined by the
education of the user, the level of income, the age, the employment status, sex or gender and
by the ownership of a bank account.
3.6 Hypotheses
Hypothesis 1: Other things being equal, the use of mobile money services to access banking
andfinancial services is not significantly determined by the level of education.
Hypothesis 2: Other things being equal, the use of mobile money services to access banking
and financial services is not significantly determined by income levels.
Hypothesis 3: Other things being equal, the use of mobile money services to access banking
and financial services is not significantly determined by the age of individuals.
Hypothesis 4: Other things being equal, the use of mobile money services to access banking
and financial services is not significantly determined by the employment status of individuals.
Hypothesis 5: Other things being equal, the use of mobile money services to access banking
and financial services is not determined by the sex/gender of individuals.
Hypothesis 6: Other things being equal, the use of mobile money services to access banking
and financial services is not significantly determined by the ownership of a bank account.
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3.8 Ethical Considerations
Research requires not only expertise and diligence, but also honesty and integrity. According
to Cooper and Schindler (20 11 :34), ethics are norms or standards of behaviour that guide
moral choices about individuals' behaviour and our relationships with others. Weiman,
Kruger and Mitchell (2005: 182) explain that ethical considerations and ethical behaviour are
as important in research as they are in any other field of human activity. The goal of ethics in
research is to ensure that no one is harmed or suffers adverse consequences from research
activities. Ethical consideration in research means adhering to good codes of conduct.
3.9 Chapter Summary
The chapter provided the research methodology that was used in investigating the impact of
mobile money services in the banking and financial services industries of Botswana. The
impact was assessed in terms of educational level, income level, age of individuals,
employment status of individuals, sex/gender of individuals, and ownership of a bank
account. The methodology referred to comprised of a set of techniques that researchers use to
conduct an enquiry. This is supported by Babbie and Mouton (2001:74) who maintain that
research methodology refers to systematic methodological and accurate execution of design.
This chapter covered research design, population, and data collection methods.
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university qualifications of the respondents regarding their level of ability to use mobile
money services to access banking and financial services. However, a greater level of
education could lead to a greater understanding and ability regarding self-service
technologies (Meuter, Ostrom, Bitner & Roundtree, 2005) and lower perceptions on
complexity of innovations.
Table 3: Descriptive statistics of level of education
Table 3.1:Use ofMobile Money Services
95% Confidence Interval for Mean
Std Lower Upper
N Mean Deviation Std Error Bound Bound Minimum Maximum
Primary Certificate 2 1.00 .000
Junior/Middle 10 1.10 .316 School Certificate
Senior School 69 1.29 .457 Certificate
Vocational/College 60 1.28 .454 Certificate
University Degree 48 1.25 .438
Other 1 1.00
Total 190 1.26 .442
Source; Primary data
Table 3.2: ANOV A
Use of Mobile Money Services
Sum of
.000
.100
.055
.059
.063
.032
Squares df Mean Square
Between Groups .556 5 .111
Within Groups 36.286 184 .197
Total 36.842 189
Source; Primary data
1.00 1.00 1 1
.87 1.33 1 2
1.18 1.40 1 2
1.17 1.40 1 2
1.12 1.38 1 2
1 1
1.20 1.33 1 2
F Sig.
.564 .728
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Table 3.3: Test of Homogeneity of Variances
Use ofMobile Money Services
Levene Statistic dfl df2 Sig.
4.811a 4 184 .001
a. Groups with only one case are ignored in computing the test of homogeneity of variance for use of mobile money services.
Source; Primary data
4.2.2 Gross income level
Testing Hypothesis 2
One way ANOV A results present the compared mean level of the use of mobile money
services to access banking and jinanciai services is not significantly determined by gross
income. The income level is categorised as lower income earners (<P500, P500 - PIOOO ,
P1000- P2000), medium income earners P2000- P5000, P5000- PlO 000 and large income
earners with more than Pl 0 000. The mean level of the use of mobile money services is the
dependent variable and the income level is the independent variable. Table 2 shows that
P2000 - P5000 has the highest mean of 1.39 while P5000- Pl 0 000 has the least mean score
of 1.15. The assumption of approximately equal variances is met with the F value of 1.001
and (sig.) .419 > 0.05. Therefore, it can be concluded that there is an insignificant difference
between income levels. The Levene's test for equality of variance is 3.194 > 0.05 so the null
hypothesis (Ho) that variances are equal is rejected. Hence, the p-value of 0.002 < 0.05 is
used. Therefore the hypothesis Other things being equal, the use of mobile money services to
access banking and financial services is significantly determined by income level is rejected.
Williams and Torma (2007) provide additional theoretical and anecdotal evidence of the
impact of mobile financial services. They argue that access to banking has a two-fold impact
on low-income households. In the first step, the benefits of access to finance are
improvements in the quality of people's lives, such as saving time, reducing the threat of
crime, and simplifying transactions. Household income has been pointed to have significant
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impact on the adoption of internet banking services (Mattila, Karjaluoto & Penta, 2003 :30).
A greater level of income could lead to higher levels of adoption of mobile money services.
Table 4: Descriptive statistics of gross income
Table 4.1:Descriptives
Use ofMobile Money Services
95% Confidence
Interval for Mean
Std. Std. Lower Upper
N Mean Deviation Error Bound Bound Minimum Maximum
<P500 62 1.29 .458 .058
P500-P1000 12 1.33 .492 .142
Pl000-P2000 61 1.21 .413 .053
P2000-P5000 23 1.39 .499 .104
P5000-Pl0000 26 1.15 .368 .072
+P10000 6 1.33 .516 .211
Total 190 1.26 .442 .032
Source; Primary data
Table 4.2:ANOV A
Use ofMobile Money Services
Sum of
Squares df Mean Square
Between Groups .976 5 .195
Within Groups 35.867 184 .195
Total 36.842 189
1.17 1.41 1 2
1.02 1.65 1 2
1.11 1.32 1 2
1.18 1.61 1 2
1.01 1.30 1 2
.79 1.88 1 2
1.20 1.33 1 2
F Sig.
1.001 .419
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Source; Primary data
Table 4.3:Test of Homogeneity of Variances
Use of Mobile Money Services
Levene Statistic dfl df2 Sig.
3.914 5 184 .002
Source; Primary data
4.2.3 Sex/Gender of individuals
Testing hypothesis 3
One way ANOV A results present the compared mean level of The use of mobile money
services to access banking and financial services is not significantly determined by the
sex/gender of individuals. The sex/gender of individuals is categorised as male or female. The
mean level of the use of mobile money services is the dependent variable and sex/gender is
the independent variable. Table 3 shows that females have the highest mean of 1.28 while
males have the lowest mean score of 1.24. The assumption of approximately equal variances
is met with the F value of 0.580 and (sig.) 0.447 > 0.05. Therefore, it can be concluded that
there is a significant difference between the sex/gender of individuals regarding mobile
banking services. Levene's test for equality of variance is 2.297 > 0.05 so the null hypothesis
(Ho) that variances are equal is rejected. Hence, the p-value of 0.131 > 0.05 is used.
Therefore the hypothesis, Other things being equal, the use of mobile money services to
access banking and financial services is not significantly determined by sex/gender of
individuals. is rejected. These findings are consistent with empirical studies in that males use
mobile money services more than females. When compared to women, males perceive less
risk in online business activities (Garbarino & Strahilevitz, 2004; Nysveen et al., 2005).
Males tend to evaluate mobile commerce more positively than women (Yang, 2005). Some
studies evidence a male preponderance among users of mobile banking services (Flinders,
2008; Laforet & Xiaoyan, 2005; Laukkanen & Pasanen, 2008).
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Table 5.0: Descriptive statistics for sex/gender of individuals
Table S.l:Use of Mobile Money Services
95% Confidence Interval for
Mean
Std. Std. Upper
N Mean Deviation Error Lower Bound Bound Minimum Maximum
Male 100 1.24 .429 .043 1.15 1.33 1 2
Female 90 1.29 .456 .048 1.19 1.38 1 2
Total 190 1.26 .442 .032 1.20 1.33 1 2
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Test ofHomogeneity of Variances
Table 5.2:Use of Mobile Money Services
Levene
Statistic dfl df2 Sig.
2.297 1 188 .131
Source; Primary data
Table 5.3:ANOV A
Use of Mobile Money Services
Sum of
Squares df Mean Square
Between Groups .113 1 .113
Within Groups 36.729 188 .195
Total 36.842 189
Source; Primary data
F
.580
a e . : n epen en T bl 54 I d d tS amp1es es I T t Levene's Test for
Equality of
Sig.
.447
Variances t-test for Equality_ of Means
Std. Mean Error
Sig. (2- Differen Differenc F Sig. T df tailed) ce e
Use Equal 6.940 .010 1.297 75 .199 .120 .093 of varianc mobil es e assume mone d y Equal 1.286 69.078 .203 .120 .094 servic varianc es es not
assume d
Source; Primary data
95% Confidence Interval of the
Difference
Lower Upper -.064 .305
-.066 .307
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4.2.4 Employment status of individuals
Testing hypothesis 4
One way ANOV A results present the compared mean level of The use of mobile money
services to access banking and financial services is not significantly determined by the
employment status of individuals. The employment status is categorised as yes or no. The
mean level of the use of mobile money services is the dependent variable and employment
status is the independent variable. Table 4 shows that those who are employed have the
highest mean of 1.28 while those unemployed have the lowest mean score of 1.27. The
assumption of approximately equal variances is met with the F value of0.448 and (sig.) 0.640
> 0.05. Therefore, it can be concluded that there is an insignificant difference between the
employment status of individuals. Levene's test for equality ofvariance is 2.656 > 0.05 so the
null hypothesis (Ho) that variances are equal is rejected. Hence, the p-value of0.73 > 0.05 is
used. Therefore, the hypothesis: Other things being equal, the use of mobile money services
to access banking and financial services is not significantly determined by the employment
status of individuals is accepted.
Table 6.0: Descriptive statistics for employment status of individuals
Use ofMobile Money Services
95% Confidence
Interval for Mean
Std. Std. Lower Upper Minimu
N Mean Deviation Error Bound Bound m
Yes 112 1.28 .449 .042 1.19 1.36 1
No 64 1.27 .445 .056 1.15 1.38 1
Other 13 1.15 .376 .104 .93 1.38 1
Total 189 1.26 .442 .032 1.20 1.33 1
Maximum
2
2
2
2
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Source; Primary data
Table 6.1:Test ofHomogeneity ofV ariances
Use of Mobile Money Services
Levene Statistic dfl df2 Sig .
2.656 2 186 . 073
Source; Primary data
Table 6.2:ANOVA
Use of Mobile Money Services
Sum of Mean Squares df Square
Between .176 2 .088 Groups
Within 36.596 186 .197 Groups
Total 36.772 188
Source; Primary data
4.2.5 Age of individuals
Testing hypothesis 5
F Sig.
.448 .640
To test hypothesis 5: Other things being equal, the use of mobile money services to access
banking and financial services is not significantly determined by the age of individuals, the
independent t-test statistic was employed. The ages of individuals were categorised into 6
groups: 1 =<16; 2 = 16- 19; 3 = 20- 29; 4 = 30- 39; 5 = 40-49 and 6 =50+. From Table 3,
the mean of age group 50+ years is seen as high at 1.67 while the mean of 20 - 29 years and
40- 49 years is low at 1.20. However, the Levene test is 3.604 > 0.05; therefore the "equal
variances are assumed" row is used. As the p-value in that row is 0.04 < 0.05, the hypothesis
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is rejected. This implies that the use of mobile money services to access banking and
financial services is ~o~ determined by the age of an individual. This is drawn from the
assumption that younger people use technology more than older people. Previous findings
show that older individuals have a lower propensity for adopting new technology-based
services (Oumlil & Williams, 2000). Indeed, earlier studies (Laukkanen et al., 2007) show
that mature customers have more resistance to the internet and mobile banking services than
younger bank customers. This indicates that banks prefer lower risk exposure to higher risk
exposure, all things being equal. This outcome is consistent with the expectation that younger
people are more receptive to mobile money services than older ones.
Table 7.0: Descriptive statistics of age of individuals
Descriptives
Use of Mobile Money Services
<16
16-19
20-29
30-39
40-49
50+
Total
95% Confidence
Interval for Mean
Std. Std. Lower
N Mean Deviation Error Bound Upper Bound
7 1.43 .535 .202 .93 1.92
12 1.33 .492 .142 1.02 1.65
135 1.21 .407 .035 1.14 1.28
28 1.43 .504 .095 1.23 1.62
5 1.20 .447 .200 .64 1.76
3 1.67 .577 .333 .23 3.10
190 1.26 .442 .032 1.20 1.33
Source; Primary data
Table 7.1:Test of Homogeneity of Variances
Use ofMobile Money Services
Levene
Statistic dfl df2 Sig.
3.604 5 184 .004
Source; Primary data
Minimum Maximum
1 2
1 2
1 2
1 2
1 2
1 2
1 2
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Table 7.2:ANOVA
Use ofMobile Money Services
Sum of
Squares Df
Between Groups 1.945 5
Within Groups 34.897 184
Total 36.842 189
Source; Primary data
Mean Square F Sig.
.389 2.051 .074
.190
Table 7.3:Independent Samples Test
Levene's Test
for Equality of
Variances t-test for Equality of Means
95% Confidence
Interval of the
Difference
Mean
Sig. (2- Differen Std. Error
F Sig. t df tailed) ce Difference Lower
Age Group Equal variances 4.844 .029 1.297 187 .196 .174 .134 -.091
assumed
Equal variances 1.477 85.846 .143 .174 .118 -.060
not assumed
Source; Primary data
4.2.6 Ownership of bank account
Testing hypothesis 6
Independent sample t-test shows the results of the hypothesis that states that other things
being equal, the use ofmobile money services to access banking and financial services is not
significantly determined by ownership of a bank account". Table 6 reveals that the
ownership of bank accounts is divided into two categories of "yes" and "no". The individuals
who do not have a bank account have a high mean score of 1.27 while those who have a bank
account have a relatively low mean score of 1.23. As the Levene test of equality variance is
1.276 > 0.05, the p-value in the first row is 0.260 > 0.05. Therefore null hypothesis is not
43
Upper
.438
.408
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rejected since there is not sufficient evidence at 5% level that the ownership of a bank
account determines the use of mobile money services to access banking and financial
services. However, contrary to these results, other studies indicate a very low percentage of
banked individuals in most developing countries including Botswana; however, the unbanked
do have access to mobile phones. Empirical studies show that the solution for the poor is to
rely on informal financial services which are more expensive than formal financial and are
often unsafe (Coyle, 2007; Donner, 2007a; Porteous & Wishart, 2006). By filling a financial
vacuum for the poor it offers the possibility of gaining access to savings, micro-credits and
receiving remittances.
Table 8.0: Descriptive statistics of ownership of a bank account
Use ofMobile Money Services
95% Confidence Interval for Mean
Std. Lower
N Mean Deviation Std Error Bound
Yes 146 1.27 .448 .037 1.20
No 43 1.23 .427 .065 1.10
Total 189 1.26 .442 .032 1.20
Source; Primary data
Table 8.1:Test of Homogeneity of Variances
Use of Mobile Money Services
Levene Statistic dfl df2 Sig.
1.276 1 187
Source; Primary data
Table 8.2:ANOVA
Use ofMobile Money Services
Sum of
Upper Bound
1.35
1.36
1.33
.260
Squares df Mean Square
Between Groups .057 1 .057
Within Groups 36.716 187 .196
Total 36.772 188
Source; Primary data
Minimum
1
1
1
F
.290
Maximum
2
2
2
Sig.
.591
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Table 8.3:Independent Samples Test
Levene's
Test for
Equality of
Variances t-test for Equality of Means
95% Confidence
Interval of the
Difference
Std Error
Sig. (2- Mean Differenc
F Sig. t df tailed) Difference e Lower Upper
Use of Equal 1.276 .260 .539 187 .591 .041 .077 -.110 .193 Mobile varianc
Money es Services assume
d
Equal .552 71.341 .582 .041 .075 -.108 .191
varianc
es not
assume
d
Source; Primary data
4.3 Most popular mobile money services used in Botswana
Table 9: Types of mobile money services used by respondents
Mobile money service Frequencies Percentages Mascom MyZaka 19 15% Orange Money 28 22% e-Wallet 55 42% Barclays 13 10% Tobetsa Mobile Money 0 0% Missing values 15 11% Totals 130 100%
Source; Primary data
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Mobile Money Services mostly used by Respondents
60
~ 40 ·o c ~ 30 cr Q)
~ 20
10
0
Mascom Orange myzaka money
Figure 7: Source; Primary data
E-wallet Barclays Tobetsa
Mobile Money Services
mobile money
missing values
Table 7 above presents the type of mobile money services used by the respondents: 55 usee
Wallet for transactions which are mainly money transfers; 19 use Mascom MyZaka for
airtime top-up and money transfer; 28 use Orange Money for transactions; Barclays Mobile
Money is used by for 13 users; 15 surveyed respondents do not use mobile money services.
This means that the majority of respondents use e-Wallet for their transactions.
4.4 Most Popular Mobile Money Service Transactions in Botswana
Table 10: Mobile money services transactions
Transactions Frequencies Percentages (%) Aitiime top-up
58 32% Bill payments
14 7% Balance enquiries
50 27% Money transfer (money payments)
62 34% Others
0 0% Total 115 100% Source; Primary data
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Mobile Money Transactions
• Airtime top-up
Balance enquiries
Others
Figure 8; Source; primary data
IIIII Bill payments
IIIII Money transfer(money payments)
0%
Table 8 above shows that 32% of people use the airtime top-up services for mobile money
services transactions; 34% transfer money (mobile payments); 27% inquire about their
balances and finally only 7% do bill payment transactions. According to Heyer and Mas
(2009), bill payments constitute an important and easily reachable niche application for
mobile money, especially in countries where basic infi·astructure is reasonably well
developed.
4.5 Chapter Summary
The chapter provided the data analysis covering critical issues of the use of mobile money
services in Botswana and its current adoption in other countries in Africa and outside Africa.
Collected data from questionnaires was analysed using the Statistical Package for Social
Science research. SPSS has the capability of performing a variety of data analysis tests and
presentation functions. Specifically, it offered descriptive statistics, which were used for
displaying frequencies for variables and for exploring factors that influence mobile money
services.
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CHAPTER FIVE: CONCLUSION AND DISCUSSION
5.1 Conclusion
This chapter concludes and provides recommendations which can be used for further
research. The aim of the research was to evaluate mobile money service transactions in
Botswana. It also set out to discover the most popular mobile money services in Botswana.
Furthermore, the research, determined, by means of a number of variables, whether there was
a significant difference between the use of brick and mortar financial services and the
adoption of mobile money services in the banking and financial services. This research
employed quantitative analysis of results that were obtained from a total of 190 out of the
targeted sample of 200 respondents from the study regions. The analysis of the results
revealed that gross income appeared to be insignificant in determining the use of mobile
money services in Botswana. Williams and Torma (2007) provide additional theoretical and
anecdotal evidence of the impact of mobile financial services. They argue that access to
banking has a two-fold impact on low-income households. In the first instance, the benefits of
access to finance are improvements in the quality of people's lives, such as saving time,
reducing the threat of crime, and simplifying transactions.
The education of the individuals generally did not show any influence on the preference to
use mobile money services to access banking and financial services. However, a greater level
of education could lead to a greater understanding of and ability regarding self-service
technologies (Meuter al., 2005) and lower perceptions of the complexity of innovations.
The sex/gender of an individual was significant in determining whether an individual used
mobile money service or not to access banking or financial services. The analysis revealed
that more males chose to use mobile money services than females. Males tend to evaluate
mobile commerce more positively than women (Yang, 2005:8).
Empirical studies show that the solution for the poor is to rely on informal financial services
which are more expensive than formal financial services and are often unsafe (Coyle, 2007;
Donner, 2007a; Porteous & Wishart, 2006). By filling a financial vacuum for the poor,
mobile money services offer the possibility of gaining access to savings, micro-credits and
receiving remittances.
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Employment status was also significant in determining whether an individual used mobile
money services or not. More employed individuals preferred to use mobile money services to
access banking and financial services than unemployed. From the study it was evident that
52.4% used e-Wallet for transactions (mostly money transfer); 33.3% used Mascom MyZaka
for airtime top-up and money transfer; 9.5% used Orange Money; lastly Barclays Mobile
Money accounted for 4.8%. This means that the majority of respondents used e-Wallet for
their transactions.
The body of the research concluded that this study supported some hypotheses while
rejecting others. For instance, there was a lack of support for ownership of a bank account
and gross income for the adoption of mobile money services in the banking and financial
services of Botswana. This, however, does not necessarily completely eliminate the role of
these factors in the adoption of mobile money services. Their influences may be extrinsically
linked to variants that did not emerge in the current study. For example, the sample may have
predominantly included young people who did not have jobs and had not yet opened bank
accounts. Future research could examine the impact of these additional factors.
5.2 Theoretical contributions
From a theoretical standpoint, the results presented contributed to the existing literature in a
number of ways. First, the research made a contribution to mobile money services literature
by providing insights into the factors that seem to affect the adoption of mobile money
services. The results hint that the age of individuals, educational background, gender/sex,
employment status are significant factors influencing adoption. Gross income and ownership
of bank accounts were found to be insignificant. This is consistent with mobile money
services/m-banking studies conducted during the past years.
5.3 Limitations of the study
The main limitations of this study were threefold:
First, the absence of published baseline research data on the adoption of mobile banking
services for financial and banking services in Botswana meant that no comparisons could be
made.
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Second, although the sample size of 200 was large compared with sample sizes of other TAM
studies, it consisted of users of mobile money services in Gaborone only. This has an effect
on the generalisation ofthe findings.
Third, the model might also suffer from the fact that other possible factors influencing the
adoption of mobile money services were not included in the model.
These limitations pave the way for future studies.
5.4 Potential Areas of Future Research
Political, economic and infrastructural environmental factors are likely to play a major role in
the growth of mobile banking (Kleijnen et al., 2004). It would be interesting to research the
extent of these environmental factors in the growth of mobile money services. There could be
links in the level of development of the technology infrastructure, related financial services,
political environment and regulatory frameworks, and the related growth of mobile money
services. A comparative study of the environments and different levels of development of
mobile money services in Botswana and neighbouring countries, such as Kenya, Uganda,
Tanzania, Zimbabwe would be significant and interesting.
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Websites
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http://www.nber.org/w16721. Retrieved on 3 April2011.
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www .orange.co. bw /services
www.mascom.bw
http://www.sapo.co.za
http://www.qfinance.com >Home> QFINANCE Dictionary
www. theeconomist
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Gaborone Technical College
Private Bag 00358
Gaborone, Botswana
Cell phone; 71354104
Email: [email protected]
APPENDICES
Questionnaire for Academic Research
(In partial fulfilment of the requirements of Master in Business Administration)
by
Pako Maradung
This questionnaire is for gathering information to be used in addressing the topic:
Investigating the impact of mobile money services in the banking and financial industries of Botswana (a case study of users in Gaborone)
Dear Respondent
I would like to thank you very much for your anticipated cooperation in this research work. Please note that this is purely an academic work and information provided will not be used in any way detrimental to you, the respondent. Therefore your response is anonymous.
Please answer all the questions by ticking the category that best reflects your view [ "]
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SECTION A: Demographics
1.
2.
3.
4.
5.
6.
Instructions
1. All the information you provide will be treated in the strictest confidence. 2. Questions should be answered in a fair and consistent manner.
Sex
Male Female
Language
English Setswana Both English and Setswana Other
Age group
<16 16-19 20-29 30-39 40-49 50+
Your educational background
Primary certificate Junior/middle school certificate Senior school certificate Vocational/college certificate University degree Other
Are you employed?
Yes No Other
Gross income
<P500 P500 -Pl 000
D D
D D D
D D D D D D
D D D D D
D D
D D
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P1 000- P2 000 P2 000 - P5 000 P5 000- P10 000 + P10 000
7. Do you have a bank account?
Yes No
8. Do you have access to a cell phone handset?
Yes No
9. If yes, have you used mobile money services?
Yes No
D D D D
D D
D D
D D
10. If yes, please answer questions 10.1 to 10.7; otherwise proceed to Qll
10.1 How did you register for the mobile money service?
Through authorised mobile agents (retailers) 0 Through the cell phone D Other __ _
10.2 What mobile money services are you using or have you used?
Mascom MyZaka Orange Money e-Wallet Barclays Mobile Money Tobetsa Mobile Money Other ------
D D D D D
10.3 How often do you make use of mobile money services
.Very often Occasionally Do not use it Do not know about it
D D D D
10.4 When last did you make use of mobile money services?
Between 1 - 2 weeks 2 -4weeks 4-8 weeks
D CJ D
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8 -10weeks
10 weeks and more
D D
10.5 How long have you been using mobile money services?
Fewer than 3 months Between 3 - 6 months Between 6 -12 months More than 1 year
D D D D
10.6 What transactions have you done using mobile money services?
Airtime top-up Bill payments Balance enquiries
Money transfer (mobile payments) Other: -----
D D D D
10.7 Has the use of money mobile service reduced the frequency with which you used to visit your bank?
Yes
No D D
11. In your assessment, to what extent has the use of mobile money banking services reduced the time and stress involved in carrying out your banking services?
No effect Slightly Considerably
D D D
12. In your view, to what extent have mobile money services contributed to the development and growth ofTHE Botswana financial sector industry?
No effect Slightly Moderately Highly Not sure
D D D D D
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Section B
12.
13.
14.
15.
18.
19.
20.
21.1.1
21.1.2
21.1.3
21.1.4
22.
23.
Mobile money services are for people who do not have bank accounts.
It is difficult to register for mobile money services
It is easy to use mobile money services.
The cost of using mobile money services is affordable.
The security features of using mobile money services are trustworthy.
Mobile money services provide one of the most efficient and effective for out services. Mobile money services can expand banks' reach in rural areas. Mobile money services can be used to achieve financial inclusion and enable basic banking and financial services to reach the of
High banking charges
Long queues at the banks and ATMs
Unfavourable operational hours of banks
Personnel
There have been remarkable changes in my banking transactions since I got to know about mobile money
services Service delivery in the use of mobile money service is
and efficient.
Thank you very much for filling in this questionnaire
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Descriptives
Use of Mobile Money Services
95% Confidence Interval for
Mean
N Mean Std Deviation Std Error Lower Bound Upper Bound Mi
Primary Certificate 2 1.00 .000 .000 1.00 1.00
Junior/Middle School Certificate 10 1.10 .316 .100 .87 1.33
Senior School Certificate 69 1.29 .457 .055 1.18 1.40
Vocational/College Certificate 60 1.28 .454 .059 1.17 1.40
University Degree 48 1.25 .438 .063 1.12 1.38
Other 1 1.00
Total 190 1.26 .442 .032 1.20 1.33
ANOVA
Use ofMobile Money Services
Sum of Squares df Mean Square F Sig.
Between groups .556 5 1 1 1 ,111 .564 .728
Within groups 36.286 184 .197
Total 36.842 189
Descriptives
Use ofMobile Money Services
95% Confidence Interval for
Mean
N Mean Std Deviation Std Error Lower Bound Upper Bound Minim
<P500 62 1.29 .458 .058 1.17 1.41
P500-P1000 12 1.33 .492 .142 1.02 1.65
P1000-P2000 61 1.21 .413 .053 1.11 1.32
P2000-P5000 23 1.39 .499 .104 1.18 1.61
P5000-P10000 26 1.15 .368 .072 1.01 1.30
+P10000 6 1.33 .516 .211 .79 1.88
Total 190 1.26 .442 .032 1.20 1.33
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Use ofMobile Money Services
Sum of Squares
Between groups .976
Within groups 35.867
Total 36.842
Test ofHomogeneity of Variances
Use ofMobile Money Services
Levene
Statistic dfl dfl Sig.
3.914 5 184 .002
ANOVA
df Mean Square F
5 .195
184 .195
189
Independent Samples Test I
Levene's I
Test for Equality of Variances t-test for Equality of Means
Sig. (2- Mean Std. Error F Sig. T df tailed) Difference Difference
Use of Equal 6.940 .010 1.297 75 .199 .120 .093 mobile variances money assumed services Equal 1.286 69.078 .203 .120 .094
variances not assumed
Sig.
1.001 .419
I
95% Confidence
Interval of the Difference
Lower Upper -.064 .305
-.066 .307
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