ROLE OF MOBILE MONEY SERVICES ON FINANCIAL INCLUSION
AMONG SMES IN MAVOKO SUB COUNTY
BY
VICTOR MUTUKU NZYOKA
D63/8245/2017
A RESEARCH PROPOSAL PRESENTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF THE DEGREE OF MASTER OF SCIENCE IN FINANCE, SCHOOL OF BUSINESS, UNIVERSITY OF NAIROBI
SEPTEMBER 2019
DECLARATION
This research proposal is my original work and has not been submitted to any other college, institution or university
Signature: …………………………… Date: …………………………….
Victor Nzyoka Mutuku
D63/8245/2017
This research proposal has been submitted for examination with my approval as the University supervisor
Signature: ……………………………… Date: ……………………………
Dr. Kennedy Okiro
Senior Lecturer, Department of Finance and Accounting
School of Business
University of Nairobi
Table of Contents
ABBREVIATIONS AND ACRONYMS. iv
1.1 Background of the study. 1
1.1.1 Mobile Money Services. 1
1.1.3 Small and Medium Enterprises in Mavoko Sub County. 5
1.1.4 Mobile Money Services and Financial Inclusion of SMEs. 6
1.2 Statement of the Problem.. 7
1.4 Significance of the Study. 10
CHAPTER TWO: LITERATURE REVIEW… 12
2.21 Innovation Diffusion Theory (IDT) 12
2.2.2Technology Acceptance Model (TAM) 13
2.3.1 Global Empirical Evidence. 14
2.3.2 Local Empirical Evidence. 15
2.5 Summary of the Literature Review.. 17
CHAPTER THREE: RESEARCH METHODOLOGY.. 19
3.6 Validity and Reliability of the Instrument 20
3.7.2 Variable definition and Measurement 22
ABBREVIATIONS AND ACRONYMS
ATM Automatic Teller Machine
CBK Central Bank of Kenya
CA Communication Authority
GSM Global System for Mobile Communications
ICT Information Communication Technology
MFI Micro Finance Institutions
MMT Mobile Money Transfer
MNO Mobile Network Operators
M-PESA Mobile Money service by Safaricom
M-SWARI Mobile money service by Safaricom and CBA bank
CBA Commercial Bank of Africa
CHAPTER ONE: INTRODUCTION
1.1 Background of the study
It is widely recognized that technology is invaluable for improving efficiency, accuracy, increasing outreach and reducing costs. One of the recently emerging technologies in the microfinance industry is the use of mobile phone technology for both banking and remittance. According to Gartner (2012) the global volume of mobile transactions grew from USD 37.4 billion in 2011 to over USD 1.13 trillion in 2014, while the number of users of mobile money services worldwide surpassed 141 million in 2014 and the number of mobile phones rose to 7 billion, greater than the total population in the globe. Mobile money services have been defined as the electronic money accounts accessed via mobile phone (Zutt, 2010). They offer secure and convenient means for banked and unbanked people to send and receive money with mobile phones at home and abroad anywhere at any time. The services permit members of a mobile telephony company to register and store monetary value in a phone and allow them to share the value with others in the same system network.
According to the word bank, financial inclusion involves access to money related products and services that meet their needs at fair and reasonable considerations. The services include savings and withdrawal of cash, payments and transfer of funds, insurance and credit facilities. It is expected access to these services would generally enable individuals and businesses to achieve their planned goals and hence improve their standards of living. Evasion from the formal money related structure has dynamically been perceived as one of the hindrances to a world without financial exclusion. In many developing countries, most of families don’t have a record with a money related association, while little firms sometimes allude to inconvenience in getting to and overseeing financing as a key constraint on their improvement (Kunt, 2011).
1.1.1 Mobile Money Services
By 2012, there were 25 mobile money services operated by different Mobile Network Operators (MNOs) across Africa, 15 of these are in East Africa (GSMA, 2012). Among the five East African countries as at the year 2012, Kenya had the leading number of users of mobile money services with over 30,800,000 registered users, which represents 71.3% of the total number of mobile phone users in the country. Tanzania is the second with 9,200,000 users of mobile money which represents 43.4% of the total number of mobile phone subscribers in the country (GSMA, 2012). Uganda had the third largest number of mobile money users in the East African region with 2,100,000 users representing 8.1% of the total number of mobile phone subscribers. Rwanda and Burundi had 309,127 and 29,000 users of mobile money services representing 8.3% and 2.7% of the total number of mobile phone users in those countries respectively (GSMA, 2012). In Kenya the number of people with mobile subscription by December 2017 stood at 42.8 Million representing 94.3% penetration rates (CCK Sector Statistics report, 2017).
Must and Ludewig (2010) trace the rise of mobile money servcies to the rapid and worldwide penetration of mobile phones back to 1999. However, mobile phone enabled commerce (m-commerce) or services may have started as early as 1997 when mobile phone enabled Coco Cola vending machines and mobile phone banking services were introduced in Finland. Earlier documented mobile commercial services include a Philippine mobile operator’s launch of SMART money in 1999. By the year 2000, mobile money technology had started to spread to include several other countries. Later GLOBE Telecom launched G-cash in 2004 (Wishart, 2006). Bharti Airtel launched their mobile money transfer pilot project in India in 2007 (Bosi, Celly and Joshi, 2011).
Mobile money can be broadly categorized into three groups; M-transfer, M-payment and M-financial services. M-transfer involves money transfer from one user to another, normally without any accompanying exchange of goods and services, it may be domestic or international (Chale and Mbamba, 2014). According to Jenkins (2008) M- payment involves money exchange between users with an accompanying exchange of goods and services. It includes persons to a person (P2P), government to a person (G2P) and person to business (P2B). M-financial services are mobile money services in which mobile money is linked to a bank account to provide the user with transactions that they would access at a bank branch. It includes credit, insurance and saving, bills payment and money transfer.
In Kenya, the first mobile money service was launched by the now defunct KenCell and was called Sokotele. The service was poorly marketed and did not get significant traction. In March 2007 M-Pesa was launched by the biggest mobile operator, Safaricom and soon took over the market. In the initial stages of mobile money in Kenya, the service enabled subscribers to send or receive money to and from other mobile phone users. Over time more features have been added while other mobile phone operators have included mobile money as a service. Since the broad acceptance of mobile money in Kenya through Safaricom’s M-Pesa platform, the service has been rolled out by other mobile operators. As outlined by World Bank (2012), mobile money services are often linked to financial inclusion and therefore applications extend financial services to the unbanked or those preferring cheaper financial services.
1.1.2 Financial Inclusion
According to Demirguc (2008) financial inclusion or broad access to financial services is defined as an absence of price and non price barriers in the use of financial services. In order for a country to attain full inclusion the following are of great importance. First financial services should be accessible to all often seen as the goal of financial inclusion. Secondly financial services provided should also be of quality which includes traits such as affordability, convenience, product-fit, safety, dignity of treatment and client protection. Financial inclusion involves provision of the full suite of basic financial services such as basic credit, savings, insurance and payment services.
Financial exclusion has also been defined in the context of a larger issue of social exclusion of certain groups of people from the mainstream of the society. Leyshon and Thrift (1995) define financial exclusion as referring to those processes that serve to prevent certain social groups and individuals from gaining access to the formal financial system. According to Conroy (2005), financial exclusion is a process that prevents poor and disadvantaged social groups from gaining access to the formal financial systems of their countries. It signifies the lack of access by certain segments of the society to appropriate, low-cost, fair and safe financial products and services from mainstream providers.
Millions of people across the developing world do not have access to banking services. Faced with barriers related to cost, geography and education these individuals have no way of securely transferring funds, saving money, insurance or accessing credit (BASA, 2003). These four services serve different needs that each household encounters and ensuring access to this product range is an important goal of financial inclusion. Credit allows households to use future income to manage current vulnerabilities or to capitalize on investment opportunities. Savings provide a safe and value-retaining place where households can store funds, allowing them to tap into past income as needed. Insurance, protects against vulnerability to shocks (e.g. death, illness, or disability in the family). Payments services allow people to carry out financial transactions without having to be face-to-face.
Access has many dimensions such as services need to be available when desired and products need to be tailored to specific needs; the prices for these services need to be affordable including all non price costs such as having to travel a long distance to a bank branch and most important it should also make business sense, translate into profits for the providers of these services and therefore be available on a continuous basis. Access is difficult to measure. Usage is often used as a proxy, although it can underestimate the number of households that have access because it fails to capture those who currently have access to a financial service but are not using it (Demirguc, Levine and Ross 2009).
Kenya has succeeded in significantly expanding the reach of financial services over the past several years. If mobile money transfer services, savings and credit cooperatives (SACCOs) and micro finance institutions (MFIs) are included, formal financial inclusion increased from 26.4 percent in 2006 to 40.5 percent in 2009. (CBK annual report, 2012). There are several factors that have contributed to greater level of inclusion; the expanding reach of three major types of financial service providers, the identification of financial inclusion as a national priority (as stated in the Kenya vision 2030 national planning document) and the accessibility brought about by innovative electronic payment systems. Currently, Kenya has got only forty three commercial banks, eight Deposit Taking Microfinance Institutions of which both have only a total of four million with bank accounts (CBK annual report, 2012). Even with increased agency banking; the numbers did not grow due to the systemic perception and experience most unbanked have with the reached if the banks remained complacent (Maina, 2009). In Kenya, the upper rift, parts of Eastern and North eastern provide a vast population of financially excluded population which provides mobile service providers with the opportunity to get more footage and offer these services at low cost and minimal paperwork. They also partner with banks in order to offer fully financial products to the population and transform lives.
1.1.3 Small and Medium Enterprises in Mavoko Sub County
Although the definition of SME seems to differ significantly across countries or publications, in most cases the definition commonly uses the number of employees, value of assets, value of sales and size of initial capital and turnover. SMEs are therefore defined as businesses with six to 50 employees or with annual revenues less than 50 million Kenyan shillings (FSD Kenya, 2008). In the USA and EU countries, it is estimated that SMEs contribute over 60 percent in employment, 40-60 percent to Gross Domestic Product (GDP) and 30-60 percent to exports. The Asian Tigers such as India, Indonesia, China, Malaysia, Japan and South Korea also have thriving SMEs sectors contributing between 70-90 percent in employment and an estimated 40 percent contribution to their respective GDPs. In Africa, economic powerhouses such as South Africa, Egypt, Nigeria and Kenya, the SME sector is estimated to contribute over 70 percent in employment and 30-40 percent contribution to GDP but contribute less than four percent to export earnings (United Nations, 2005).
Small and Medium Enterprises (SMEs) have economic significance in Kenya and requires attention from policy makers. According to the economic survey of 2006, the sector contributed to over 50% of new jobs created in the year 2005. In 2011, the informal sector created approximately 80.6% of the total jobs during this period according to the economic survey (KNBS, 2011). SMEs constitute a significant portion of the private sector in that they participate in overall investment, production of goods and services, taking risks, perceiving and utilizing new economic opportunities and developing business in the economy (Renny, 2011). SMEs in Kenya are faced with various challenges among them: lack of credit facilities, working capital and other financial services (Bowen, Morara & Mureithi 2009). Factors that contribute to the success of SMEs could help entrepreneurs in ensuring they employ the right mix of such factors from the onset of the enterprise and these need to be looked into.
Mavoko is situated approximately 25 kilometers south west of Nairobi. Though part of Machakos County, it borders Kajiado County. The region is a growing residential area due to its proximity to the capital city of Nairobi, has a railway station and is one of the fastest growing metropolitan areas in Kenya. The Mavoko town has an urban population of 22,000 (according to the 1999 census), and is relatively industrialized. Among its key industries are large manufacturing firms such as Devki Steel. The small and medium size enterprises in Athi River Town include hardware’s, salons, fast food restaurants, wholesales shops, construction firms and transport businesses (Daily Nation 2006, various editions).
It is therefore imperative to study the region because of the strategic importance of SME business in the outskirts of Nairobi. Athi River town which is the main town of the Sub County has been growing at a high rate if the number of businesses set up in the area in the last 2 years is anything to go by. A study carried out by Mwongera (2014) in Mavoko Sub-county in Machakos County found that most enterprises are owner-managed or largely controlled and run as a family business and mostly have limited capital base and the technical skills and capacity of those running the business is also limited. In the absence of research on how to increase financial inclusion the economy stands to lose a lot since its economic contribution to Kenya’s GDP will be severely affected.
1.1.4 Mobile Money Services and Financial Inclusion of SMEs
The transformation seen in mobile phones technology in making money related transactions has been developing across the world at an extraordinary phase. The continued acceptance of the mobile money services has added impetus towards financial inclusion .The achievements and advancement in technology specifically mobile devices have completely changed delivery of financial services and facilitated innovative ways of providing services to the deprived. To realize monetary presence for the underprivileged population, the development of mobile money technology has been mentioned as a turning point in the financial industry. (IFC Mobile money report 2011).In Africa, the adoption rate of mobile money is high. Initially the focus on determinants to use mobile money aroused concern on the social and economic variables .More interest on the economic impact and performance triggered a number of studies conducted on microenterprises indicating positive benefits for those who use it to carry business (Kwakwa 2012).
Variables that make mobile money services very attractive to SMEs include low transactional cost compared to alternatives (Zutt, 2010 and Omwansa, 2009), increased accessibility following increasing number of agents and subscribers countrywide has provided the services reliably over time and has the potential to provide financial services to SME (Must &Ludewig, 2010).Mobile phones has built in features to provide financial services instantaneously making it a possible tool for real time transactions (Zutt, 2010), adding to the efficient and reliability of mobile money service including the messaging system that allows the sender and receiver to obtain transaction information immediately after the transaction with only few errors reported during transactions mostly arising from the customer as they input transaction information .This features are crucial to the wellbeing of SMEs.
Small and medium enterprises in Kenya have adopted the use of the mobile payments as a way of transacting their business because of the relative affordability of mobile phones and the mobile banking services they offer (Mbogo, 2010). The vision 2030 proposes intensified application of science, technology and innovation to raise productivity and efficiency across its three pillars (economic, social and political) on which it is based. Mobile Money Transfer Service (MMTS) is one of the innovations in the ICT sector that may enhance the efficiency of businesses if properly used. Following the launch of mobile money transfer service M-Pesa by Safaricom, in March 2007, there was a quick adoption of the service by many Kenyans through subscription to M-Pesa. Leading to a rapid growth over the years, within eight months of its launch, M-pesa had 900, 000 subscribers (Omwansa, 2009) and by September 2009 over 8.5 million Kenyans were registered users (Safaricom, 2009).
In 2012, Safaricom Ltd, a leading mobile service provider in Kenya in partnership with Commercial Bank of Africa, one of the Kenya registered commercial bank, launched a service dubbed M-SHWARI that automatically opens a bank account for M-PESA registered customers and operates fully like a bank account. With such partnership, the society will also gain with more population included in the formal financial sector ( Kabbucho and Coetzee, 2010)
1.2 Statement of the Problem
Mobile money service, designed to help institutions streamline their operations has received overwhelming uptake in Kenya since its introduction in 2007 (Omwansa 2009). This success is attributed to the service being affordable and accessible to including low income earners (Mbogo 2010). The technological invention is considered easy to use yet efficient and reliable with the potential to extend financial services to the unbanked or those preferring cheaper financial services. It is an appropriate technological invention for SMEs that continue to face challenges related to limited affordable and accessible financial services to support business operations. Therefore it is important to explore usage rates of mobile money services, the nature of transactions and their contribution to the SME industry in Kenya. SMEs are responsible for approximately 80% of employment according to the Economic Survey (2011). The need to focus on affordable financial inclusion methods that contribute positively to SMEs business performance in areas like increased sales, increased use of mobile money services to purchase business products and supplies and savings and loan accessibility is very significant.
Financial inclusion as previously iterated includes all initiatives to make formal financial services available, accessible and affordable to all segments of the population (African Development Bank, 2013). In the absence of inclusive financial systems, the poor will have to be heavily reliant on their limited savings (if they have at all) to invest in their education and health among other needs and this could further widen the income inequality gap (Thorat, 2010). He further argues that financial inclusion calls for a higher level of penetration of access to bank accounts and easy access to credit at an affordable cost. Though this position stands valid the global and most importantly the scene on the developing continent tells a different story. Financial inclusion therefore calls for a higher level of penetration of innovative means such as the mobile money platform that has a wider reach than traditional brick and mortar bank branches.
The majority of the SMEs in Kenya operate in the informal sector with most of them being sole proprietorships or family businesses usually employing less than five persons. They are involved in small semi-organized and sometimes unregulated activities that are mainly concentrated in urban as well as in some parts of the rural areas. The business functions are usually conducted by the owner/manager in market stalls, open-yards and residential houses and on undeveloped open grounds. Many of these micro business operators do not have bank accounts while those who do, find the bank accounts cumbersome to operate as they have to leave their businesses unattended in order to conduct transactions in a bank. As a result the mobile money services have become popular both for the unbanked and the banked.
Literature reveals that the mobile money is faster, cheaper, more reliable and safer (Jack & Suri 2011). The benefits of cashless transaction including less opportunity for fraudulent and criminal activities and mobile money technology have increased adoption rates among SMEs in the capital city (Mbogo 2010). The main literature gaps exist in revealing whether mobile money technology has contributed to SMEs performance through increased sales, increased profits, loans accessibility and savings and if there is it’s limited in geography. The gaps exist in systematic assessment of the impact of mobile money especially on SMEs in Kenya. Even though current research suggests that mobile phone coverage and adoption has a positive impact on risk reduction, market improvement, coordination amongst firms and labour market ,empirical evidence is still limited (Jenny and Mbiti, 2010),.
Several studies have been done on mobile phone banking and financial inclusion concepts. Kigen (2011) studied the impact of mobile banking on transaction costs of microfinance institutions using a survey of microfinance institutions in Nairobi. In his findings, mobile banking drastically reduced the transaction costs of microfinance institutions (MFI) thereby increasing the penetration level of the MFIs. Otieno (2008) studied challenges in the implementation of mobile banking information systems in commercial banks in Kenya and established that the key challenges included high levels of online insecurities, fraud and low acceptance by the market. Wambari (2009) studied mobile banking in developing countries using a case study on Kenya where he established that m-banking has a positive impact on transfers, payments, deposits and withdrawals in financial transactions of small businesses.
Prior studies carried out elsewhere confirm the positive impact of mobile money service on micro enterprises. Most of these studies were conducted in other countries and in Kenya, studies have been mainly in Nairobi – the capital city, thus they may not reflect the impact on the success and growth of different business environments and in particular the SMEs in Mavoko Sub County. In fact, it has been observed that, studies investigating the impact of mobile telephones on the performance of firms are very limited, particularly in developing countries (Donner & Escobari, 2010). In light of the foregoing, this study seek to fill this gap by establishing the role of mobile money services on the financial inclusion of SMEs in Mavoko Sub County. The study aims to fill the identified gap in knowledge concerning the relationship between mobile money services and financial inclusion in Mavoko. Hence, the study sought to answer one research question: what is the role of mobile money services and financial inclusion in Mavoko Sub County?
1.3 Research objectives
1.3.1 General Objectives
The general objective of this study is to examine the role of mobile money services on financial inclusion among SMEs in Mavoko Sub County
1.3.2 Specific Objectives
- To examine the effect of mobile money transfer on financial inclusion amongst SMEs in Mavoko Sub County.
- To assess the relationship between mobile payment for goods and services and financial inclusion among SMEs in Mavoko Sub County.
- To determine whether mobile account management affects the degree of financial inclusion among the SMEs in Mavoko Sub County
- To establish the effect of mobile credit facilitation on financial inclusion on SMEs in Mavoko Sub County
1.4 Significance of the Study
The study seeks to determine the role the mobile money services play in the financial inclusion of SMEs in Mavoko. This study will help technology providers, government agencies and development partners to understand the contribution of mobile money service technology on the growth of SMEs with regard to financial inclusion. This will help them provide better technical support and advice to their clients as well as providing new innovations. The government will further provide the required regulations and other interventions that are necessary to ensure smooth operations for all concerned parties. Further the study will assist the SMEs operators to fully understand the entrepreneurial impact of this technology on their business so as to cope with the increasing developments in the mobile services on one hand and the challenges of the micro business operating environment on the other hand.
The results of this study will present valuable information to mobile phone companies that could develop or augment available products with special focus on SMEs. The SMEs operators or owners will benefit from knowledge of financial services available through mobile money and how they can use them to positively impact their business. Appropriate regulatory bodies could use the findings to enhance service delivery and ensure that the SME sector continues to benefit from innovations such as mobile money technology. The study adds value to the existing literature and establishes the gaps for future research on the same or similar topic by suggesting areas that need further studies to be conducted.
For the policy makers and agencies like the Central bank of Kenya (CBK), the findings of this study would be important in informing the policy formulation especially with regard to regulating the mobile banking services. The research findings add dimension that may help improve policy direction with regard to regulation of M-banking as well as factors that spur financial inclusion. The study will be of value to the general public by informing them about the benefits of mobile money services on financial inclusion. This follows the maxim that information is power and hence empowers the users as well as providers of the service gearing towards improved services.
CHAPTER TWO: LITERATURE REVIEW
2.1 Introduction
This chapter explores literature related to the study as guided by the objectives .It also discusses the concept of mobile money services and the financial inclusion of SMEs. The chapter looks at the conceptual frame work, the theoretical perspective and the summary of gaps in the literature.
2.2 Theoretical Review
This section explores theories that can be used to explain the variables of study and how they relate. The theories place the variables in a theoretical context to give an understanding on their relationship. This study relies on the following theories:
2.2.1 Innovation Diffusion Theory (IDT)
Innovation Diffusion Theory by Rogers (1983) states that an Innovation is any idea, object or practice that is perceived as new by members of the social system (Ahlstrom,2010). Diffusion of innovation on the other hand is the process by which the innovation is communicated through certain channels over time among members of social systems. This theory has received similar attention by scholars in explaining consumer behavior towards new technology. It is suggested that innovation diffusion is achieved by how a social system accepts and begins to use (adopt) an idea or technology (Ahlstrom,2010). The theory proposes that there are four key elements in adoption. These are: innovation, communication channels, time and social system.
According to Rogers (2003) an innovation is an idea, practice or project that is perceived as new by an individual or other unit of adoption irrespective of when it was invented. Communication is a process through which parties produce and exchange facts to reach a common agreement. Communication occurs through conduits between terminals. A channel is the means by which a message gets from the generator of the message to the receiver. Time is another element in the theory .The innovation-diffusion process and rate of adoptions have a time element within which it occurs. The social system refers to the set of connected units engaged in common problem resolution to accomplish a similar aim. Further the theory states that there are five stages involved in the innovation diffusion process which include; the knowledge stage, the persuasion stage, the decision stage, the implementation stage and the confirmation stage.
This theory is important to this research since it lays out the manner in which new innovations spread. An innovation is therefore spread if people got to know about it and are persuaded that it is good, if they decided to adopt and implement it and if others confirmed it as a good choice. Failure at any stage hindered the spread of the innovation.
2.2.2Technology Acceptance Model (TAM)
TAM is one of the most frequently used models formulated as an information systems theory that models how users come to accept and use a technology. The TAM states that a user’s adoption of a new information system is determined by that users’ intention to use the system, which in turn is determined by that users’ beliefs’ about the system. The TAM further suggests that two beliefs are instrumental in explaining the variance in users’ intentions. These two attitudes labeled most important for accepting a technology are Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). PU explains how useful the consumer finds a new technology whereas PEOU indicates how easy to use he/she finds it. The perceived element of the words is simply recognizing the facts that the actual usefulness or ease of use is a subjective element and in asking consumers we can only know how they perceive something filtered through their perception of reality. In some ways this is similar to the perceived behavior control in assessing subjective attitudes though it lacks the analysis of the subjects. In other words fears and other emotions or feelings limiting the perception of how the consumer will interact with reality are not taken into account as much. However Davis (1989) noted, future technology acceptance research must address how other variables affect usefulness, ease of use and user acceptance. Therefore the perceived ease of use and perceived usefulness may not fully explain behavioral intentions towards the use of mobile money services, necessitating a search for additional factors that can better predict the acceptance of mobile money services among SMEs.
TAM has been generally used to anticipate client acknowledgment and utilize in view of perceived value and usability (Ndubisi and Richardson, 2002). Thus TAM was picked as the suitable model to incorporate different factors, for example, perceived simplicity of availability of the portable installment administrations, perceived minimal effort of the versatile installment administrations, perceived accommodation, perceived security, perceived support from the flexible service provider.
2.3 Empirical Studies
2.3.1 Global Empirical Evidence
Agboola (2006) in his study on Information and Communication Technology (ICT) in Banking operations in Nigeria using the nature and degree of adoption of innovative technologies; degree of utilization of the identified technologies and the impact of the adoption of ICT devices on banks, found out that technology was the main driving force of competition in the banking industry. During his study he witnessed increase in the adoption of ATMs, EFT, smart cards, electronic home and office banking and telephone banking. He indicates that adoption of ICT improves the banks‘ image and leads to a wider, faster and more efficient market. He asserts that it is imperative for bank management to intensify investment in ICT products to facilitate speed, convenience and accurate services or otherwise lose out to their competitors.
Laha (2011) sort to identify the broad determinants of financial inclusion in some selected districts of west Bengal, India. Empirical results using Bivariate Probit model showed that asset level of the household, as determined by the operated land holding, significantly enhances the probability of becoming a bank customers and the existence of information asymmetry in financial services acts as an obstacle to the process of financial inclusion .Sharma (2008), through cross country empirical study examined a close relationship between financial inclusion and development in Pakistan. The study found a positive relation between financial inclusion and different socio-economic variables like income, inequality, literacy, physical infrastructures.
Kathuria, Uppal and Mamta (2009) assess the impact of mobile penetration on economic growth across Indian states. They estimated a structural model with three equations for 19 Indian states from 2000 to 2008. They specifically examined the links through which mobile phones affect growth and the constraints, if any, that limit their impact. They found that Indian states with higher mobile penetration rates can be expected to grow faster and that there is a critical mass at a penetration rate of 25 percent, beyond which the impact of mobile phones on growth is amplified by network effects. Telecom networks, more than any other infrastructure are subject to network effects: the growth impact is larger when a significant threshold network size is achieved.
Singh and Kodan (2012) analyzed the relationship between financial inclusion and development to identify factors associated with financial inclusion. With the help of Regression he found that per capita NSDP and urbanization were significant explorers of financial inclusion while the literacy, employment and sex-ratio were not statistically significant explorers/predictors of the financial inclusion.
2.3.2 Local Empirical Evidence
A study by Mutsune in (2014) investigates financial inclusion through mobile banking in Kenya. The study examines Kenya‘s highly successful money transfer model, Mpesa, in an effort to explore the nature and role of financial inclusiveness in stimulating economic activity. The study focused on exploring a framework that can be used to estimate how financial inclusion in Kenya through mobile banking has impacted economic dynamism. The ideas presented are an innovative exploration that blends economic thinking and with aspects of natural science with the aim of developing a framework that can be applied to appropriate data. The study recommends flexibility in this new form of technology application by policy makers. Due to increasing velocity of transactions in Kenya and the increasing assumption of banking services by mobile service providers, the monetary authorities should go back to the drawing board to recalibrate rules on money supply and banking services respectively. The study suggests a close attention to policy concerns in future studies.
Musau (2002) researched the impact of financial liberalization on selected financial sector development indicators in Kenya. Musau established that financial liberalization increased the penetration level of financial services in Kenya. Of the selected financial sector developments, Microfinance institutions played a major role in promoting financial sector development.
The work of Ngugi (2015) sought to investigate the contribution of mobile money, an example of such innovative means, to the promotion of financial inclusion. His study used secondary data that span across eight years (2006 to 2014). By using multiple regression analysis to test the relationship between mobile money transfer and financial inclusion, the study concluded that mobile money had a significant contribution to promoting financial inclusion. One facet of mobile money, mobile banking, was also observed to have contributed significantly to deepening financial markets.
Achieng (2011) studied the strategic responses of Kenya Commercial Bank to mobile money transfer in Kenya and found out that the money transfer service industry could be described as emerging, rapidly growing or a high velocity market in Kenya and any developing country. The study indicated that with the strategic positioning of the mobile telecommunications providers and the need for banking institutions to partner and integrate with the Mobile money transfer provides in order to remain relevant and share in the huge potential offered to mobile subscribers.
Waihenya (2012) conducted a study of the effect of agency banking on financial inclusion in Kenya. Secondary data was used for this study since it is easily accessible, cheaper and accurate for this case due to the regulations around submissions by Central Bank of Kenya. Secondary data from existing theories and researchers done on mobile money transfer and financial inclusion from finance books, journals, periodicals and internet was also relied upon. The study concluded that agency banking has the effect of increased financial inclusion in the country significantly. The research found that the levels of financial inclusion are low and that there is notable gap not bridged by formal banking framework. It further notes that agency banking is facing a lot of challenges from the increasing mobile penetration in the country and mobile money transactions increasing at the same rate.
Nyasetia (2012) set out to establish the implications of financial deepening on savings and investments in Kenya. He adopted a causal research design in investigating the relationship between financial deepening and savings and investments in Kenya. He used secondary data on financial deepening indicators, savings and investments from 2006-2011. He conducted regression analysis to establish the relationship and found a strong positive correlation between savings and investments. The study established that when there is proper financial deepening, the level of savings and investments in Kenya also improve. If interest rates are not favorable, if the stock market is not doing well, if deposits in banking institutions are not growing then there will be slow growth and improvement in savings and investments.
2.4 Conceptual Framework
Independent variable Dependent variable
Source: Author (2018)
2.5 Summary of the Literature Review
Variables that make mobile money services very attractive leading to increased uptake include low transactional cost compared to alternatives (Zutt, 2010 and Omwansa, 2009), increased accessibility following increasing number of agents and subscribers countrywide (Zutt, 2010), has provided the services reliably over time and has the potential to provide financial services to SME (Must &Ludewig, 2010). It has built in features to provide financial services instantaneously making it a possible tool for real time transactions adding to the efficient and reliability of mobile money service including the messaging system that allows the sender and receiver to obtain (Zutt, 2010) . Aside from extending financial access to the marginalized, mobile money seeks to improve productivity by increasing efficiency, lowering the cost of transaction, creating employment opportunities and serving as building blocks on which other businesses can grow (Donovan, 2012).
Literature has shown that mobile money may overcome the challenge of long distance payments and storage of money but still pose challenges related to withdrawal charges and possibility that money is not invested in projects and businesses. The main gaps exist in systematic assessment of the impact of mobile money especially on SMEs in Kenya. Even though current research suggests that mobile phone coverage and adoption has a positive impact on risk reduction, market improvement, coordination amongst firms and labour market (Jenny and Mbiti, 2010), empirical evidence is still limited.
From the above discussion of the theoretical and empirical literature, limited research has been conducted on the relationship between mobile money services and financial inclusion in Kenya .It is expected that there should be a positive relationship between mobile money services and financial inclusion, however no known study has been conducted to establish the relationship between the two in Mavoko hence the research gap. The existing studies have been done in other economies which have different operating environment from that in Kenya. This study therefore seeks to fill this research gap.
CHAPTER THREE: RESEARCH METHODOLOGY
3.1 Introduction
This chapter provides the methodology of the study. It gives the specific procedures that will be followed through in undertaking the study. The research design, population, sampling frame, data collection methods & data analysis are also defined & described in this chapter.
3.2 Research Design
Research design refers to how data collection and analysis are structured in order to meet the research objectives through empirical evidence (Cooper and Schindler, 2006). This study will adopt a descriptive research design. Mugenda and Mugenda (2003) describes descriptive research design as a systematic, empirical inquiring into which the researcher does not have a direct control of independent variable as their manifestation has already occurred or because the inherently cannot be manipulated. Descriptive research design is more appropriate because the study seeks to build a profile about the relationship between mobile money services and financial inclusion in Kenya. Gay (1981) defines descriptive research as a process of collecting data in order to test hypotheses or to answer questions concerning the current status of the subjects in the study.
3.3 Target Population
Mugenda & Mugenda (2003) defined population of study as the group of individuals, objects or events with some common researchable characteristics. The total number of individuals that the researcher is interested in studying about. It can also be said to be the population whose characteristics the researcher will attempt to describe. The target population in this study is the SMEs in Mavoko Sub County who use mobile money services. The respondents will be the business owners .The target sectors are retail, transport, hospitality, entertainment and health services . From the Machakos licensing department estimate there are about 380 SMEs in the target sectors in the area of study as at December 2017.
3.4 Sampling Design
Sampling is defined as the selecting of a number of individuals form the larger group for a study while a sample is defined as a representative part of the population whose characteristics will be studied to gain information about the whole (Kobo & Tromp 2006).This study will use stratified sampling method. Kothari (2009) said this method is appropriate if the population under study is not homogeneous. The target SMEs will be stratified on the basis of nature of business and then samples will be selected form the strata using simple random ,method to get a representative unit.
3.5 Data Collection
Data collection is the most crucial part in gathering the required information with a view of achieving the research objectives stated. The researcher acknowledges the various options available as data collection methods or research instruments, each with its advantages and disadvantages. In order to identify and determine the relationship between Mobile money services and financial inclusion in Kenya, this study will use both primary and secondary data. The secondary data on the number of mobile subscribers registered on mobile money services and number of mobile money subscribers in Mavoko will be gotten from Communication Authority of Kenya .This will make it easier to obtain adequate and accurate information necessary for the research.
Primary data will be collected using questionnaires. According to Gray (1981), the questionnaire is the typical method through which descriptive data can be collected. Allan and Randy (2005) further asserts that the suitability of a questionnaire lies in its ability to; cover large population within a short time, personnel and cost, hide the identity of the respondent which may trigger honest responses, avoid biases due to characteristics of probing and allow respondents enough time to answer questions. The questionnaire for this study will be divided into sections .Section A will capture the demographic data while B will cover the research objectives.
3.6 Validity and Reliability of the Instrument
Defined as how well a test measures what it’s supposed to measure ,validity is the accuracy, soundness or effectiveness of an instrument with regard to what it’s supposed to measure. To achieve validity in this study, the instruments will be reviewed with the supervisor and other field experts to ensure that they measure what they are intended to measure as recommended by Kumar (2005).
Reliability on the other hand is the degree to which a tool is able to produce stable and consistence results Moskal & Leydens 2000). A test retest method of measuring reliability will be adopted in this study. In this method the instrument is administered at two different times and a correlation between the scores computed (Shuttle worth 2009).The researcher will randomly select ten respondents and isolate their filled questionnaire. A similar test will be done to the group and a comparison done for reliability. This will be done in a span for a one week difference. A chi square test will be done to determine how the responses significantly differ and if the findings will be at 95% significance level and the tests are not different then reliability of the instruments will have been confirmed.
3.7 Data Analysis
After successful data collection exercise, the obtained data will be cleaned and edited for completeness and consistency. Data cleaning involves identifying any incomplete or inaccurate responses and undertaking the necessary corrections. After this the data will be coded and keyed into computer program Statistical package for social sciences (SPSS) version 20 for analysis which will involve both quantitive and qualitative data. Inferential statistics will also be generated and the results will be presented using frequency tables and models. Inferential statistics regression will be applied to establish the relationship between Mobile money services and financial inclusion in Kenya.
3.7.1Analytical model
The regression model used in this study is;
Y= α +β1X1 +β2X2+β3X3 +e
Where,
Y=financial inclusion
α = constant term
X1- Mobile money Transfer
X2- Payment for goods and services
X3- Account management
X4- Credit facilitation
Β1, β2, β3 = Beta coefficients indicating various levels of importance (weight of each factor)
3.7.2 Variable definition and Measurement
- Mobile money Transfer measured by the volume of funds transferred through cell phones
- Payment for goods and services measured by the number of payments made using mobile money
- Account management measured by the number of bank accounts opened using cell phones
- Credit facilitation measured by the volume of loans disbursed using cell phones
REFERENCES
African Development Bank. (2013). Financial inclusion in Africa. Tunisia: African Development
Bank Group
Agbola, N. (2006). Making Money Work for the Poor in India, Dhanraj Mahal, Mumbai-
.CMS Marg.
Ahlstrom, D., (2010). Innovations and growth: How businesses contribute to society. Academy of
Management Perspectives, 24(3), pp. 11-24.
Bosi, I., Celly, N., & Joshi H. (2011). The Indian Tiger Prowls in Africa: Bharti Airtel’s
Acquisition of Zain Africa. Asian Case Research Center, University of Hong Kong.
Bowen, M., Morara, M., & Mureithi, S. (2009). Management of Business Challenges Among
Small and Micro Enterprises in Nairobi –Kenya. KCA Journal of Business Management.
2(1) 16-31.
Central Bank of Kenya (CBK), 2009, Financial sector development, central bank of Kenya.
Communications Commission of Kenya (CCK). (2017). Annual Report 2012-2013, Retrieved
September 4, 2014
Cooper, D.R., & Schindler P.S. (2008). Business Research Methods. (10th ed). Singapore:
McGraw-Hill
Conroy,J,2005.APECandfinancialexclusion:Missedopportunitiesforcollectiveaction?Asia-
PacificDevelopmentJournal12(1),53–79.
Davis, F., D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of
Information Technology. MIS Quarterly, 13(3): 319 – 340
Demirguç-Kunt, Aslı, and Ross Levine. 2008. “Finance, Financial Sector Policies, and Long Run
Growth.” M.Spence Growth Commission Background Paper, No. 11. Washington
Donner, J., & Escobari, M., (2010). A Review of Evidence on Mobile use by Small and Micro
Enterprises in Developing Countries. Journal of International Development, 22, 641-658.
FSD 2008: Linking mobile banking and mobile payment platforms to credit bureaus, April, USA
GSMA (2012) “Mobile Financial Services for Unbanked”.
Jack, W. & Suri, T. (2010). The Economics of M-PESA.
Jenkins, B. (2008). Developing Mobile Money Ecosystems. Washington, DC: IFC and the
Harvard Kennedy School
Jenny, C.A. & Isaac, M. (2010). “Mobile Phones and Economic Development in Africa”,
Journal of Economic Perspectives, 24(3), 207-232.
Kigen, K. P. (2010). The impact of mobile banking on transaction costs of microfinance
institutions, Unpublished MBA project, University of Nairobi
Kothari, C.R. (2007). Research Methods and Techniques. New Delhi: New Age International Publishers
Laha, A. (2011). Determinants of financial inclusion: A study of some selected districts of West
Bengal, India. Indian journal of finance 98:60-65.
Leyshon, A, Thrift, N, 1995, “Geographies of financial exclusion: Financial abandonment in
Britain and the United States” Transactions of the Institute of British Geographers,
New Series 20 312–341
Mbogo, M., (2010). The Impact of Mobile Payments on the Success and Growth of Micro-
Business: The Case of M-Pesa in Kenya. The Journal of Language, Technology &
Entrepreneurship in Africa, 2(1). 2010, ISSN 1998-1279.
Mugenda, O. & Mugenda, A. (2003). Quantitative and qualitative approaches. Nairobi Africa
Centre for Technical Studies.
Musau, G. (2002). The impact of financial liberalization on selected financial sector
development indicators in Kenya. Unpublished MBA project, University of Nairobi.
Must, B., & Ludewig, K. (2010). Mobile Money: Cell Phone Banking In Developing Countries.
Policy Matters Journal, Spring 2010, 27-33.
Mutsune, T. (2014). No Kenyan left behind: The case of financial inclusion through mobile
banking. Global Conference on Business and Finance Proceedings, Iowa Wesleyan
College.
Ngugi, D. (2015). Relationship between mobile banking and financial inclusion in Kenya.
Retrieved, February 20 2017
Nyasetia, L.(2012).Financialdeepeningand its implications on savings and investments in
Kenya(Unpublished Master‘s project).University of Nairobi,Kenya.
Omwansa, T., (2009), M-PESA: Progress and Prospects. innovations / Mobile World Congress
- Retrieved March 20, 2014
Otieno, M. (2008).Challenges in the implementation of mobile banking information Paper
Presented at ―Portland International Conference on Management of Engineering
Renny, M. (2011).Micro and Small Enterprise Sector and Existing Support System with
emphasis on High-Tech oriented Entrepreneurship in Kenya: Journal of Language,
Technology & Entrepreneurship in Africa, 3(1), 99-1108.
Rogers, E.M. (2003). Diffusion of Innovations (5th ed.). New York: Free Press
Safaricom, (2009). Financial Year 2008/2009; Annual Results Presentation and Investor update.
Thorat, U. (2008). Financial inclusion and Sustainable Development: Role of IT and I
intermediaries, Address to Annual Bankers Conference, Hydrabad.
United Nations. (2005). Economic and Social Commission for Asia and the Pacific: Trade
Finance Infrastructure Development Handbook for Economies in Transition,. Thailand:
United Nations Publications.
Waihenya, H. (2012) The effect of Agent Banking on Financial Inclusion in Kenya, an
unpublished MBA dissertation. UON
Wambari, A. & Mwaura, P (2009), mobile banking in developing countries, Vaassan
Ammattikkor Keakoulu University of applied science
Wishart, N. (2006). Micro-Payment Systems and Their Application to Mobile Networks.
Washington, DC: infoDev / World Bank.
World Bank. (2012). Information and Communications for Development 2012: Maximizing
Mobile. hington, DC: World Bank. DOI: 10.1596/978-0-8213-8991-1. Retrieved June
18, 2014
Zutt, J., (2010). Kenya Economic Update: Poverty Reduction and Economic Management Unit
Africa Region Edition 3. World Bank