Mobile Banking Research Paper Example

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A Better Measurement Model for Post Adoption User Perception of Mobile Banking Services with a Keen Interest in the Key Driving Factors for Mobile Banking Services Adoption and Continued Use

Abstract

With liberalization and internalization in the financial market and progress in information technology, banks and other service industry players face dual competitive pressures to provide service quality and administrative efficiency. Mobile Commerce is gaining increasing acceptance amongst various sections of the society as a service channel of choice. Mobile Banking, the offering of bank-related financial services via mobile devices, builds a cornerstone of Mobile Commerce. Kenya has in the recent years witnessed tremendous growth in the use of mobile money transfer services. This rise can be partly traced back to technological and demographic changes which have affected important socio-cultural behavioral aspects in today’s world. Mobility needs / wishes seem to usually be the driving force behind mobile commerce. However, taking it that these recent developments are fueled by technology alone might misleadingly suggest that the adoption of mobile banking is largely based on technological criteria. This study therefore seeks to establish a better measurement model for post adoption user perception of mobile banking services with a keen interest in the key driving factors for mobile banking services adoption and continued use. The study will make use of a descriptive research design where a sample of m-banking services users and potential users will be used as the population for the study. The study will be carried out in two geographical locations; Nairobi and Busia representing urban and rural population respectively.

Table of Contents

ABSTRACT

TABLE OF CONTENTS

LIST OF ABBREVIATIONS

CHAPTER ONE

  • 1.0         INTRODUCTION
  • 1.1         Background of the Problem
  • 1.2         Statement of the Problem
  • 1.3         General Objective
  • 1.4         Specific Objectives
  • 1.5         Importance of the study
    • 1.5.1       To Businesses, Investors and Individuals
    • 1.5.2       To the Banks
  • 1.6         Scope of the study
  • 1.7         Definition of Terms
  • 1.8         Chapter summary

CHAPTER TWO

  • 2.0        LITERATURE REVIEW
  • 2.1         Introduction
  • 2.2        Mobile Banking Awareness
    • 2.2.1      Employment of Mobile Technologies in the Banking Sector
      • 2.2.1.1   Mobile Accounting
      • 2.2.1.2   Mobile Brokerage
      • 2.2.1.3   Mobile financial information
    • 2.2.2      Mobile banking Business models
      • 2.2.2.1   Bank-focused Model
      • 2.2.2.2  Bank-led model
      • 2.2.2.3  Non-Bank-led model
    • 2.2.3     Mobile Banking Regulations
    • 2.2.4     Effect of awareness on Mobile banking usage
  • 2.3         Perceived Security of mobile banking Services
    • 2.3.1      General Security features of mobile banking products

Figure 2.1 GSM components

    • 2.3.2      General Security Concern in GSM
    • 2.3.3      The risk barrier to m-banking usage in Kenya
  • 2.4          Perceived Usefulness of M-banking products
    • 2.4.1       Match between offerings and need
    • 2.4.2      Pricing vis-à-vis alternate channels
    • 2.4.3      Reliability with respect to informal channels
  • 2.5          Ease of use
    • 2.5.1       Technology Discomfort
    • 2.5.2       Self-efficacy
    • 2.5.3       Ease-of-use as a barrier to M-Banking usage
  • 2.6          Chapter Summary

CHAPTER THREE

  • 3.0          Research methodology
  • 3.1           Introduction
  • 3.2           Research Design
  • 3.3           Population and Sampling Design
    • 3.3.1        Population
    • 3.3.2        Sampling Design
      • 3.3.2.1      Sampling Frame
      • 3.3.2.2      Sampling Technique
      • 3.3.2.3      Sample Size
  • 3.4             Data Collection Methods
  • 3.5             Research Procedures
  • 3.6             Data Analysis Methods
  • 3.7             Chapter Summary

REFERENCES

APPENDICES

  • Appendix 1: COVER LETTER
  • Appendix 2: QUESTIONNAIRE
  • Appendix 3: RESEARCH BUDGET
  • Appendix 4: WORK PLAN

List of Abbreviations

ATM:              Automated Teller Machines

CBK:               Central Bank of Kenya

Et al:                (et alia): and others

FIs:                  Financial Institutions

G.o.K:             Government of Kenya

ICT:                 Information Communication and Technology

Ksh:                 Kenyan Shilling

PC:                  Perceived cost

PEOU:             Perceived Ease of Use

PR:                  Perceived risk

PU:                  Perceived usefulness

RAs:                Research Assistants

SE:                  Self efficacy

SMS:               Short message service

SPSS:              Statistical Package for Social Scientists

TAM:              Technology Acceptance Model

Chapter One

1.0  Introduction

1.1    Background of the Problem

While mobile services and mobile service consumption have lately become a hot topic among information systems and marketing scholars, service providers are putting great efforts to take advantage of the business opportunities offered by wireless technology. This may be due to the fact that value-adding mobile services are becoming increasingly important in gaining a competitive edge in the marketplace (Wang, Guriting, Ndubisi, 2006).

For some occasions, mobile banking represents an additional service in the financial services sector which adds the element of true mobility to the Internet banking used over fixed networks. Some bank customers, for example, find mobile banking valuable when being out of home on a country cottage, on the road or in case of acute need for money transfer (Laukkanen and Lauronen, 2005). Indeed, while Internet banking services provide economic benefits for the banks, mobile services serve rather as a way to offer customers value added (Laukkanen et al., 2005). In Finland, already two thirds of the population pays their bills primarily over the Internet (Federation of Finnish Financial Services, 2007) but the adoption rates of mobile phones for banking are in their infancy.

Kenya’s financial system is among the largest and more developed in Sub-Saharan Africa, with a fairly large banking sector. The sector is a cutthroat business arena, with over 44 players including multinationals all scrambling for a slice of the pie. According to World Bank estimates, the banking sector accounts for up to about 40% of the country’s GDP.  Notable however is the fact that much of the Kenyan banking sector’s activity is concentrated among the richest 20% of the population (World Bank, 2008).

According to Financial Sector Deepening Kenya (2008), the latest available data shows that only 19% of adult Kenyans have access to a formal, regulated financial institution over time A third (38 percent) did not indicate access to even the most basic form of informal financial service. This leaves more than 80% outside the bracket of the reach of mainstream banking. The population is massively under-banked, largely because more than half of the people in Kenya live in rural areas where banking services are non existent and their earnings are paltry.

Recent indication of growth in incomes and rapid urbanization in Kenya however is already pushing up demand for banking services. Financial services growth, which was muted in the recent past, is clearly poised for a take-off in Kenya, on the back of a strengthening economy, advent of technology and systematic reforms of the sector.

A suitable banking climate is regarded as both a central component and an enabler of economic growth (Koivu, 2002). Initially, banks in Kenya responded to the growing demand for banking services by opening up new bank branches at the grass roots closer to their potential customers. Nevertheless, with the constantly evolving wave of knowledge driven economy, Kenya’s banking industry has increasingly found itself unable to avoid technical indulgence to meet customer requirements. Koivu argues that there has been a persistent expansion and transformation of banking trends due to the need for convenient ways of accessing financial resources outside conventional standards. Given the huge demand for finance oriented services, even institutions beside the historical banks such as the mobile phone service providers have joined the fray in an attempt to take a piece of the expected chance cake in the banking sector.

The demanding business process in financial services has pressurized banks to develop new distribution mechanisms to draw customers and boost the understanding of clients. Electronic Banking or simply e-banking due to its flexibility and perceived convenience has increasingly become the distribution channel of choice for most retail banks. E-banking is a paragliding term for the mechanism by which a customer can execute electronic banking transactions without visiting a brick-and-mortar institution (FinCen 2000). E-banking encompasses the use banking services delivery channels such as ATMs, telephone, use of plastic money, mobile phone banking and electronic funds transfers.

According to the GSM Association and Ovum, over the last few years, the mobile and wireless market has been one of the fastest growing markets in the world with over 2.4 billion cell phone users and it is still growing at a rapid pace. In Kenya, there are more than 20 million mobile phone users slightly over half the population of the country (KNBS, 2009).

The unprecedented uptake of mobile phones in Kenya and rapid absorption of mobile-based banking services is of vital significance. This pattern of continued reliance on mobile devices for the execution of monetary transactions is growing steadily. Mobile Banking or simply M-banking is one of the newest approaches to the provision of financial services through ICT, made possible by the widespread adoption of mobile phones even in low income regions of Kenya.

Mobile banking takes several dimensions of execution all representing a new channel of distribution that allows financial institutions and other commercial players to offer financial services outside traditional bank premises. M-banking services in Kenya started with the creation of mobile phone sms services by banks. These services included Top-up of mobile phone air time, Minimum/Maximum Threshold Balance Notification, Bills payment, Overdraft notification, Fraud alerts and notification, Daily transaction limit notification, Monthly transaction limit notification, Daily balance notification, Account debit notification, Account withdraw, Transaction status updates for non real time transactions, Loan process status updates, Loan transaction summary, Monthly interest summary etc. These facilities were aimed at enabling customers’ access information relating to their accounts.

Subsequent innovations have seen the mobile banking phenomena continue to grow steadily in Kenya. M-PESA, a mobile money transfer service for instance is one such land mark innovation. M-PESA was first piloted in 2005 where the service was used to disburse loans from a Faulu Kenya to its clients and then to collect repayments via designated Safaricom airtime agents. The commercial version of M-PESA was launched in early 2007 and its success paved the way for numerous mobile banking schemes. Today, different institutions and business are offering m-banking services in Kenya. Some are provided solely by banks, others entirely by providers of telecommunications, and yet others include a relationship between a bank and a provider of telecommunication. Regulatory factors play a strong role in determining which services can be delivered via which institutional arrangements (Mortimer-Schutts, 2007).

The mobile banking services are available to mobile phone users of the three main mobile service providers namely Safaricom, Zain and Econet wireless. Safaricom’s service is branded “Mpesa”, Zains service goes by the “Zap” brand name whereas Econet’s services is called U-Cash. The other mobile service provider Telkom wireless/Orange is also expected to roll out its mobile banking service in the course of time. Partnership between Banks and these telecommunication firms to develop mobile applications is in top gear. Products such as M-Kesho of Equity bank’s, Family Bank’s Pesa Pap, and Standard Chartered Bank’s mBanking are just but a few m-banking applications arising out of these partnerships.

While mobile banking applications are rapidly gaining popularity within the banking sector in Kenya, there is not enough evidence of its acceptance amongst consumers. Robinson (2000) reported that half of the people that have tried e- banking services would not become active users. Another author claims that e-banking is not living up to the hype (Weeldreyer 2002). According to Njenga (2009), the effects of usage associated with mobile phone banking in Kenya are yet to be consolidated or quantified in a well-documented fashion.

Lee and Lin (2005) emphasized the need for further studies to assess the impact of e-service on the efficiency and satisfaction of customer-perceived business (Ibrahim et al, 2006). The perception is formed as a result of interpreting the customer’s experience with the services. (Hiltunen et al., 2002) notes that there is a growing interest in understanding the users’ experience since it has been observed to be a larger concept than user satisfaction. This study seeks to ascertain the users’ perception of M-banking in Kenya by considering four factors; perceived usefulness, perceived ease of use, consumer awareness about m-banking and perceived risks associated with mobile banking. The study aims at examining the impact of these four factors in the move to embrace m-banking in Kenya.

1.2    Statement of the Problem

The pervasiveness of the mobile phone in developing countries has recently instigated the development of applications, which are designed to enhance customer service One of the new is m-banking-a forum for mobile phone distribution of financial services. The main concern within the m-banking literature however is related to its adoption. Many studies pose the question of whether or not these applications have the potential to be appropriated by a large segment of the population. Mols et al., (1999) stated that the diffusion of any form of e-banking is more determined by customer acceptance than by seller offerings. According to Bauer et al (2005), Customer satisfaction and customer retention are increasingly developing into key success factors in e-banking. Any form of e-banking requires perhaps the most consumer involvement, as it requires the consumer to maintain and regularly interact with additional technology. Consumers who use e-banking use it on a continuous basis and need to acquire a certain level of comfort with the technology to continue to use it (Servon and Kaestner, 2008) hence the need for regular feedback about their experiences.

Research on consumer attitude and e-bank adoption has shown that there are several factors that predetermine the consumer’s attitude towards e-banks, such as demography of the individual, perceived danger, ease of use the service and ones behavior towards technology. It has also been found that consumer’s attitudes toward e-banking are influenced by the prior experience of computer and new technology (Laforet and Li, 2005.

Though customer acceptance is a key driver determining the rate of change in the financial sector, empirical studies on what may be hindering total embrace of e-banking by customers have been few (Sathye, 1999). To date, there is very little empirical work examining the customer experience and adoption of m-banking applications in Kenya and discussing the numerous barriers to this process. This survey therefore seeks to bridge that gap by establishing what the users’ perception of the mobile banking products is and what are the main driving factors towards/against the use of the mobile banking products in Kenya. Besides, this study is founded on the knowledge that assessing user experience is an essential part of any new technology product and services particularly in a highly risky and competitive industry such as banking.

1.3   General Objective

The general objective of this study is to determine customers’ perception of the various mobile-banking services in Kenya.

1.4    Specific Objectives

  • To assess the customers’ level of awareness and their knowledge about m-banking services.
  • To establish the customer’s perceived ease of use of the m-banking services.
  • To establish customers perceived usefulness of the mobile banking services/products in Kenya.
  • To determine customer say regarding the risk associated with use the m-banking services.

1.5    Importance of the Study

1.5.1   To Businesses, Investors and Individuals

The survey will also provide a platform through which users and non-users of mobile banking services will voice their concerns and complements. So far, there are no clear channels through which consumers of potential consumers of m-banking services can voice their concerns and therefore this study will present them with that much needed platform.

1.5.2   To the Banks

This research may help banks to better strategize and better see the future opportunities relating to m-banking. The findings of this study will help decision makers in the banking sector to identify gaps between their expectations of the mobile banking services and the actual customers’ experience. This will go a long way in assisting banks understand better their customer needs and in designing other mobile products and services hence offering better services to their customer, an important ingredient of strategic advantage.

1.5.3 To the Government

Through the Central Bank of Kenya, the Government could greatly benefit from this study. The findings and recommendations could help the Government to better tap and fully explore the opportunities of the mobile Banking models and assist in establishing any missing regulatory needs necessary for the smooth running of these services.

1.5.4 To Academicians and Researchers

For this group, the outcome of this research will inspire further research in the area. It can constitute a starting point of reference and a source for secondary data for further scrutiny in the area. More importantly, the study will at least fill a knowledge gap in that the findings and conclusions will identify some important factors that would affect the adoption of mobile banking in Kenya. As for students of finance and banking and Marketing, this study will be of great help as it will assist them to clearly understand the concept of mobile banking and its applicability.

1.6    Scope of the Study

The key intention of this study is to evaluate those factors that determine the perception of retail banking customers towards mobile-banking products in Kenya. The study will focus on the m-banking customers around Nairobi area and the survey will be conducted between the month of June 2011 and July 2011.

1.7    Definition of Terms

  • E-Banking -The process by which a customer may perform banking transactions electronically without visiting a brick-and-mortar institution (FinCen, 2000)
  • M-Banking -The use of a mobile phone or another mobile device to undertake financial transactions linked to a client’s account (Anderson, 2009)
  • Mpesa – Mobile money transfer service provided by the leading mobile phone service provider Safaricom (Indrani M. et al, (2009).
  • Mkesho– Equity banks’ m-banking product that link customer account Mpesa service. (Indrani M. et al, (2009)
  • Customers– Consumers and potential consumers of Mobile Banking products

1.8  Chapter Summary

This study seeks to offer an insight into the customer experience with the mobile banking services in Kenya that has not previously been investigated. It focuses on customers’ perception of the various mobile-banking services in relation to usefulness, ease of use, risks and customer awareness of m-banking. The study recognizes the prior research efforts to establish the status of mobile banking usage in Kenya but builds on these findings by seeking the customers’ feedback on the usage of the services. A survey based on the objectives of the study will be conducted between the month of February 2011 and March 2011 in Nairobi.

The subsequent chapter reviews the existing literature on the concept of mobile banking and consumer adoption of m-banking products and Chapter three is a narrative of the research methodology.

Chapter Two

2.0 Literature Review

2.1  Introduction

This chapter presents a review of the literature related to the purpose of the study; “Towards Mobile Banking in Kenya- a customer perspective”. The chapter is organized according to the four specific objectives developed in the previous chapter which include assessing customers’ level of awareness and knowledge about m-banking services and establishing customers’ perceived usefulness and ease of use of the m-banking services/products in Kenya. Finally, chapter discusses customers view regarding the risk associated with use the m-banking services. At the end of the chapter, a chapter summary is provided to give an overview of the related literature review and a description of what the next chapter will cover.

2.2  Mobile Banking Awareness

2.2.1   Employment of Mobile Technologies in the Banking Sector

According to Tiwari, Buse and Herstatt (2006), a cornerstone of Mobile Commerce is built on Mobile Banking which is the provision of bank-related financial services via mobile devices. This covers accounting, brokering and financial information services. He further states that many banks around the world are increasingly employing mobile banking to generate additional revenue, reduce costs or increase customer satisfaction, often with greater success.

Unlike in the past, when banks providing mobile services suffered a severe setback due to lack of consumer interest and unrepeatable technology, the time now seems ripe for (re-)launching mobile services (Tiwari R., et al 2006) Generally mobile banking is described as doing banking business with the aid of mobile devices such as mobile phones or PDAs. The services offered may include transaction facilities as well as other related services specifically addressing information needs that revolve around financial activities.

2.2.1.1 Mobile Accounting

Often Mobile Accounting is defined as transaction-based banking services that revolve around a bank account and use mobile devices (Georgi and Pinkl 2005). Nevertheless, not all programs related to mobile accounting are inherently transaction-based. Hence, a more accurate definition of Mobile Accounting would describe it as “availability of non-informational account-specific banking services (Tiwari et al). Mobile Accounting Services may be divided into two groups to distinguish between services vital to the management of an account and those related to the administration of an account.

Table 2.1: Services in Mobile Accounting

Mobile Accounting
Account Operation Account Administration
Money remittances & transfersAccess administration
Standing orders for bill paymentsChanging operative accounts
Money transfer to sub-accountsBlocking lost cards
Subscribing insurance policiesCheque book requests

Source: Tiwari R.,et al (2006)

2.2.1.2 Mobile Brokerage

In the context of banking- and financial services, the Brokerage applies to bourse-related intermediary services, e.g. Mobile Brokerage can thus be described as non-informative, transaction-based mobile financial services revolving around a securities account (Georgi and Pinkl, 2005). Mobile Brokerage, too, may be split into two groups to differentiate between services essential to the management of a securities account and services essential to the administration of that account. (Georgi and Pinkl, 2005).

Table 2.2: Services in Mobile Brokerage

Mobile Brokerage
Account OperationAccount Administration
Selling & purchasing financial instruments (e.g. securities)Access administration
Order book administration

Source: Tiwari et al (2006)

2.2.1.3 Mobile Financial Information

Mobile Financial Information refers to non-transaction based banking- and financial services of informational nature (Tiwari, R. and S. Buse). Mobile Financial Information services include subsets from both banking and financial services and are meant to provide the customer with anytime, anywhere access to information (Georgi, F. and J.Pinkl 2005). The information may either involve the customer’s bank and securities accounts, or it may be important for that individual customer in relation to market developments.

According to Georgi and Pinkl (2005), this information may be customized on the basis of preferences given by the customer and sent with a frequency decided by him. Ideally, the information should be given both on pull and push basis. Information services are an integral part of Mobile Accounting and Mobile Brokerage but can also be provided as a separate, stand-alone module, i.e. It is possible to offer mobile financial information without providing Mobile Accounting or Mobile Brokerage but vice versa is not feasible.

Table 2.3: Services in Mobile Financial Information

Mobile Financial Information
Account InformationMarket Information
Balance inquiries / Latest transactionsForeign exchange rates
Statement requestsMarket and bank-specific interest rates
Threshold alertsCommodity prices
Returned cheques / cheque statusStock market quotes and reports
Credit card informationProduct information & offers
Branches and ATM locations
Helpline and emergency contact
Information on the completion status

Source: Tiwari et al. (2006)

2.2.2   Mobile Banking Business Models

A broad spectrum of mobile / branchless banking models is undergoing development. Whatever business model, however, if mobile banking is used to attract low-income populations in often rural locations, the business model will depend on bank agents, i.e. retail or postal outlets that process financial transactions on behalf telecoms or banks (Wambari, 2009). The banking agent is an important part of the business model of mobile banking since it will rely on them for customer care, service quality and cash management. A lot of telecoms are going to work with their local airtime resellers. In Colombia, Brazil, Peru, and other markets however, the use of pharmacies, bakeries, etc as agents is common. Such models vary mainly on the issue of who will create the connection to the end customer, the bank or the non-bank / telecommunications company (Telco) (account opening, deposit taking, lending etc.) Another difference lies in the nature of agency agreement between bank and the Non-Bank (Infogile, 2007). The branchless banking models can be categorized into three broad categories: Bank Focused, Bank-Led, and Nonbank-Led.

2.2.2.1 Bank-Focused Model

The Bank-focused model emerges when a mainstream bank uses non-traditional low-cost distribution platforms to provide its existing customers with banking services (Infogile, 2007).  In this model the technological/physical infrastructure of a mobile operator / retailer is used to provide some basic banking services like balance enquiry, A/c to A/c fund transfer, payments for merchant goods / services using a bank account (via ATM / Debit Card / Telephone SMS). Most of these services are already offered by banks and fall under existing regulations. Thus this model raises few specific regulatory issues (Infogile, 2007).

2.2.2.2 Bank-Led Model

According to Ratha., Sanket and Vijayalakshmi, (2009), The bank-led model provides a distinct alternative to traditional branch-based banking in that customer performs financial transactions at a network of retail agents (or by mobile phone) instead of at bank branches or through bank employees. This model promises the potential to substantially increase the financial services outreach by using a different delivery channel (retailers/ mobile phones), a different trade partner (Telco / chain store) Getting expertise and target audience distinct from traditional banks, and could be considerably cheaper than bank-based alternatives.

The bank-led model can be applied either through reciprocal agreements or through the establishment of a relationship between Bank and Telco / non-bank (Infogile, 2007). In this model the relationship with the bank lies with the customer account. This model is, therefore, prone to agent-related risks. Nonetheless, these agent-related risks can be mitigated by holding banks fully accountable for their agents ‘ actions and by giving regulators the power to inspect the record of bank-related transactions by agents.

2.2.2.3 Non-Bank-Led Model

Customers do not negotiate with a bank in this model nor do they hold a bank account. Instead, customers deal with a Non-Bank firm—either a mobile network operator or prepaid card issuer—and retail agents serve as the point of customer contact (Infogile, 2007). The bank does not get into the picture here (except perhaps as a surplus fund safe-keeper) and the non-bank (e.g. Telco) performs all the functions.

Customers exchange their cash for e-money stored in a virtual e-money account on the non-bank’s server, which is not linked to a bank account in the individual’s name.

This model is riskier as the regulatory environment in which these non-banks operate in Kenya does not give adequate importance to issues related to customer identification, which may lead to significant risks. Further the non-banks are not much regulated in areas of transparent documentation and record keeping which is a prerequisite for a safe financial system.

2.2.3     Mobile Banking Regulations

2.2.3.1 Existing Regulatory Framework for Financial Sector in Kenya

Understanding the legal framework governing the mobile banking activities in Kenya require a deep look at the development of M-pesa, a pioneer mobile banking service in Kenya. Until M-PESA services were introduced in Kenya, Safaricom sought permission from the Central Bank of Kenya (CBK) to conduct the money transfer operation. In evaluating the proposal, the CBK considered the request on the basis of safety, reliability and efficiency of the service (Sirken, 2009). Two CBK departments had been involved in this effort. The Department of Financial Institutions Supervision (FISD) is responsible for the prudential regulation of banks and MFIs that take out deposits. His main concern regarding M-PESA was whether the operator (Safaricom) stretches or even breaks the rules for the banking business.

By contrast, the National Payment System (NPS) Division of the Banking (which focuses on the integrity, effectiveness, efficiency, and security of the payment system) viewed M-PESA as a payment service provider. The NPSD were more willing than the FISD to permit experimentation with the non bank based model of m-banking (CGAP, 2007). Interestingly, in Kenya telecommunications regulations require that a mobile network operator offer only the telecommunication services listed in its license and m-banking falls under the definition of telecommunication service in the law. Hence, Safaricom stand was therefore that service should be listed in the license agreement. The primary regulator over the m-banking operations of a mobile network operator, however, will be the banking regulator. (CGAP, 2007)

Precautionary measures were however put in place to ensure that the services did not infringe upon the banking services regulatory framework as provided for under section 2(1) of the Banking Act. In particular, M-PESA Trust Company Limited holds the proceeds from issuing e-money in trust for the clients in a pooled account with the Commercial Bank of Africa. Any interest earned on this pooled account can not benefit Safaricom (without triggering the “banking business” definition); the use of interest proceeds is currently being considered. Consumer allegations against M-PESA Trust Company resulting from the trust company’s or Safaricom’s negligence or deliberate misconduct shall be protected by Safaricom Additionally, maximum account balance limits (around US$ 750) and maximum transaction size (around US$ 530) offer additional support to CBK as they restrict the risks of Money laundering and the amount any single customer may lose in the event of insolvency. (CGAP, 2007)

Table 2.4 Legal and Regulatory Mobile Banking Related Issues in Kenya

Legal /regulatory issuesNon-bank based
KYCAccount opening (both on site and remotely) while maintaining adequate “know your customer” (KYC) standards. Domestic and international transfers of funds are not subject to specific KYC rules.
Maximum limit of

transactions

KES 50,000 per M-PESA account per day and a transaction limit of KES 35,000 per day in order to mitigate against settlement risk
AML/CFTAML bill 2007
E-money issuanceKenya has no laws, regulations or policies dealing directly with e-money
Payment systemThere is no law in Kenya expressly governing the payment system.

Source:  Ratha. Et al. (2009)

2.2.4   Effect of Awareness on Mobile Banking Usage

For the adoption of e-banking in general, it is necessary that banks make their customers aware of the availability of such a service and explain how it adds value relative to other ways of conducting banking services (Sathye, 1999). In their study Kuisma et al. (2007) found that some Internet banking non-users suffered from a lack of information and felt that they had not received enough information or help from the bank concerning Internet banking services resulting uncertainty toward the service.

Jayawardhena and Foley (2000) noted that the information about the services provided should be detailed enough and easily available on the web pages. Indeed, in order to enable customers to perform transactions individually it has been found to be important that the information is available before but also during the usage of the service (Filotto et al., 1997).

Acording to Indrani M. et al, (2009), the level of awareness about availability and features of m-banking services affects the way in which potential users adopt (or not adopt) these services. In the Philippines, 21 out of 30 subjects, 11 out of 23 in South Africa and 22 out of 26 in India had never heard of m-banking networks. Among the subjects who were aware, the perception was that the service would be expensive because it involves the use of technology (Indrani M. et al, 2009).

2.3   Perceived Security of Mobile Banking Services

2.3.1  General Security Features of Mobile Banking Products

Security features of mobile banking apps are based on the GSM (Global System for Mobile Communication) technology via which mobile phones communicate (Ananda F. and Kiptum J. , 2008). GSM is a cellular network which means that mobile phones link to the network by searching for cells nearby.

Figure 2.1 GSM components

Mobile Banking Research Paper Example

Source: Ananda F. and Kiptum J., (2008)

2.3.2  General Security Concern in GSM

Despite the elaborate technological structure of the GSM network and the security measures put in place, there are various security concerns with this technology. According to Michael W. (2000), GSM networks only provide access security and do not address active attacks. He further asserts that the technology lacks user Visibility and poses a challenge in upgrading the cryptographic mechanisms.

2.3.3   The Risk Barrier to M-Banking Usage in Kenya

The obstacle to risk applies to the threats that customers face or perceive in technologies. Fain and Roberts (1997) point out that marketers should keep in mind that risk is rather a perception of a consumer than a characteristic of a product. Some customers, for example, are afraid that they may make mistakes when conducting their bank affairs using a mobile phone (Laukkanen and Lauronen, 2005). In mobile banking especially the data input and output mechanisms are argued to impede the banking process creating feelings of insecurity (Laukkanen and Lauronen, 2005).

Mobile phones may also be limited in computational power, memory capacity and battery life limiting the usage of mobile services in complicated business environments (Siau and Shen, 2003). Other aspects of perceived Risk in mobile banking may further be broadly classified into Agent-Related and E-Money Risks.

According to Siau and Shen (2003), agents Related Risks arise from substantial outsourcing of customer contact to retail agents. From the viewpoint of a traditional banking regulator, entrusting retail customer interaction to the types of retail agents used in both bank-led and non-bank-led models in the hands of bank tellers in a conventional bank branch would seem to be more dangerous than these same roles. Such retail agents can work in areas that are difficult to reach or hazardous, and lack physical security measures and specially trained staff. The lack of expert training may seem a particular concern if the roles of retail agents extend beyond traditional bank tellers ‘ cash-in / cash-out transactions to include a role in credit decision making.

E-Money Risks means accepting non-bank companies that are not subject to prudential regulation and control of repayable funds from retail customers. Risk is that an unlicensed, unsupervised Non-Bank will collect repayable funds from the public in exchange for e-money and will either steal these funds or will use them imprudently, it results in insolvency and failure to meet the demands of the customers.

2.4  Perceived Usefulness of M-Banking Products

Perceived utility is characterized as the degree to which a person believes his or her job performance will be improved by using a particular technology. People tend to use an application or not to use it to the degree they assume it will help them do their job better-( Davis et al., 1989). Phillips and colleagues defined perceived usefulness as; the prospective adopter’s subjective probability that applying the new technology from foreign sources will be beneficial to his personal and/or the adopting company’s well-being”. (Phillips et al., 1994). Perceived utility describes the understanding of the user in so far as the technology improves the efficiency of the workplace of the consumer (Davis et al. 1989). It ensures that the consumer has a sense of how helpful the device is in carrying out their work tasks. It involves reducing the time, more reliability and more precision to do the job.

A significant number of studies have shown that perceived usefulness is an important antecedent of computer utilization (Davis et al., 1989; Davis et al., 1992; Igbaria & Iivari, 1995; Keil et al., 1995; Satzinger & Olfman,1995; Igbaria et al., 1996). In these studies, perceived usefulness has proven to be the stronger of the two TAM variables (perceived usefulness & perceived ease). Taylor & Todd (1995) tested a decomposed TPB model, in which they found that for business environments, perceived usefulness had a strong direct effect on an individual’s intention to utilize an IT product. The researchers provided support for Davis et al. (1989) argument that in a real work environment, behavioural intentions are based primarily on performance-related elements, rather than on the individual’s attitude towards the behaviour (Taylor & Todd, 1995a).

Since behavioral intent depends on cognitive choice, a potential mobile banking user for instance can either respond favorably or unfavorably towards engaging in m-banking. Meaning, the “like/dislike nuance” would be based on whether the tradeoff is beneficial to the potential mobile banking user as opposed to other banking service channels. Partly, this study believes that the power to attract mobile banking user lies in the technology’s usability and usefulness. This is in line with Davis (1989) who describes the latter as perceived utility (PU), i.e. assuming that using the application would increase one’s efficiency. In this context, the performance would be centered in the benefits of obtaining banking services via mobile phone minus the trade off of a physical banking practice.

In the past, researchers have validated the construct of PU and they were found to influence the intention of potential user of e-commerce such as internet shoppers. Research on internet retailing, however, from the TAM perspective is limited; however, many other technical applications also gained tremendous support from the PU build. (2002) reiterated the presence in Intranet media of a positive influence of PU on the purpose. Additionally, Agarwal and Prasad (1999); Chau and Hu (2002); Davis, et al.(1989); Hu et al. (1999); Igbaria et al. (1995); Igbaria (1993); Mathieson (1991); Mathiesonet al. (2001); Moon and Kim (2001); Ramayah et al. (2002); Venkatesh and Davis (2000) have stated that PU is important and has a positive influence on the purpose of actions. Hence, it is expected that:

Empirical support for the relationship between usefulness and attitude has been provided by a number of studies (Adams, Nelson & Todd, 1992; Mathieson, 1991). Although these studies have been limited to job-related contexts where few information system alternatives are available, perceived usefulness attributes, such as convenience, intuitively apply to the competitive e- service context. This view has been supported by the marketing literature findings that convenience, saving time and money, being in control and avoiding interpersonal interaction are some of the benefits that customers seek in self-service technology (Reardon & McCorckle, 2002; Meuter, Ostrom, Roundtree & Bitner, 2000; Dabholkar, 1996; Bolton & Drew, 1991; Zeithaml, 1988). This relationship has also been recently observed in the context of e-service use (Gefen, Karahana & Straub, 2003; Chen, Gillenson & Sherrell, 2002; Bhattacherjee, 2001a; Bhattacherjee, 2001b; Karahana, Straub & Chervany, 1999; Kenney, 1999).

Some studies found strong support for perceived usefulness during post-acceptance stages (Gefen et al., 2003; Karahana, et al., 1999) other studies offered only mild support (Bhattacherjee, 2001a; Bhattacherjee, 2001b). This paper expects a positive association between the user beliefs about the usefulness of M-banking services and their continuance intentions. Aspects of m-banking services that influence customers’ perception of the usefulness of the m-banking product include the matching between the m-banking product and the customer need, pricing and reliability of the product with respect to informal channels (Indrani M. et al., 2009)

2.4.1   Match Between Offerings and Need

According to Indrani M. et al, (2009) there were often issues of the mismatch between the m-banking product offer and the user need. In South Africa, for instance, According to Indrani M. et al, (2009) found out that there was no strong a need for domestic remittance, instead 5 out of 7 Wizzit users, were migrant workers from Zimbabwe, who expressed a strong need for international remittances yet  WIZZIT in South Africa was only offering domestic remittances. In Kenya, while airtime purchases were offered via M-PESA, none of our respondents had started buying airtime via the m-payment, even those who actively used M-PESA for money transfers channel .When asked why, they said the ‘bamba’ prepaid talktime cards were so easy to get and use. For them, that was “enough” (Indrani M. et al, 2009).

2.4.2   Pricing Vis-à-Vis Alternate Channels

The m-banking service’s pricing of other formal and informal remittance channels available at a location was a determinant of how our subjects embraced and used the In Kenya, one of the reasons some users switched to M-PESA for remittance transfers was because it was half the price of the formal alternative, i.e. the postal money order they used at the moment. Compared to the nearest centralized, safe alternatives, M-PESA was lower cost for transacting with or between the unbanked, though it remains more costly than using informal networks such as family or friends. On the other hand in the Philippines, 9 out of 30 subjects mentioned that they would prefer to use the local bus line because it costs less (Indrani M. et al, (2009). They must simply hand over cash in an envelope to the driver who moves in the direction of the location of the receiver. In the case of seven out of nine subjects, this transfer did not have an explicit cost since the driver was a friend or family member of the sender or the recipient.

2.4.3   Reliability with Respect to Informal Channels

In their studyMobile-BanRing Adoption and Usage by Low-Literate, Low-Income Users in the Developing World”, Indrani M. et al, (2009 established that subjects in South Africa and Kenya would use WIZZIT and M-PESA respectively because of the reliability these m-banking services provided compared to informal channels. 8 Of the 34 subjects mentioned sending money via friends and relatives, there were no specific costs, but sometimes the money never reached the recipient expected. Instead, with m-banking, doing the transfer directly to the recipient’s phone and receiving confirmation for the same did not leave any uncertainty on whether the money had reached the intended recipient or not.

2.5  Ease of Use

It refers to the degree to which a person thinks easily using a particular technology. Perceived ease of- use closely parallels with the concept of complexity (Davis, 1989; Teo and Pok, 2003), defined as the degree to which an innovation is perceived as difficult to understand and use (Rogers, 2003). Users may believe that a given application is useful, but they may, at the same time, believe that the technology is too hard to use and that the performance usage advantages are outweighed by the implementation commitment (Davis and Arbour, 1989). Phillips and his colleagues have identified ease of use as ‘ the degree to which the prospective adopter expects free use of new technology adopted by a foreign company of effort regarding its transfer and utilization’. (Phillips et al., 1994, p. 18,). Perceived ease of use explains the user’s perception of the amount of effort required to utilize the system or the extent to which a user believes that using a particular technology will be effortless. (Davis et al.,1989).

Similar to PU, Perceived ease of Use (PEU) plays a major role in e-commerce. Many previous research has shown that perceived user-friendliness is an important factor influencing user acceptance and IT behaviour. According to the Ram and Sheth’s (1989) consumer resistance framework, ease of- use as barrier to adoption of technological innovation comes into operation when the innovation is not well-suited with existing workflows, practices or habits. Laukkanen et al. (2007) suggest that in the case of technology intensive services the ease of- use barrier could be connected to the usability of the service and the changes it requires from the consumers. Internet shopping for instance is surmised to have beneficial outcomes, yet the hassle of engaging in the interaction medium (i.e. Website) may prove overwhelming to certain consumers. In short, the PEU is associated with the “user-friendliness” of the website. If the hassle continues to outweigh the advantage of buying over the web, then future Internet shoppers will prefer to buy through traditional channels.

Long download times are one of the factors which contribute to the unfriendliness of some internet retailers websites. Furthermore, poorly designed forms may result in potential e-shoppers losing focus from their carts and purchases. In other words, these obstacles minimize the understanding of Internet shopping’s ease of use, thus causing Internet users to develop a negative attitude. This in turn leads to the reluctance of the online shopper to engage in Internet shopping.

Similarly, this study anticipates that potential mobile banking users who find the products difficult to use are likely to shun the products.

Mobile services are getting increasingly complex and enhanced with new characteristics such as personalisation and context-awareness, new usability challenges are being raised. Indrani M. et al, (2009) notes that there is significant variation in users’ ability to conduct the m-banking transaction on their mobile phones themselves. Despite having their own M-PESA accounts, for instance, 3 of 8 M-PESA users transacted on their account only through peers or their local agents (Indrani M. et al, 2009). Instead of handing over their money and sometimes their phone to a friend or agent, they did not access the application on their own computer, and had them do the transaction.

The two main factors effecting perceived ease of use in the usage of mobile banking are Technology discomfort and self efficacy.

2.5.1   Technology Discomfort

Technology discomfort (TD) is the tendency of an individual to be uneasy, apprehensive, stressed or have anxious feelings about the use of a technological product; Is a similar construct factor found to have a negative effect on perceived ease of use in computer anxiety (Venkatesh, 2000). The expanded model suggests a similar link between technological discomfort and perceived user-friendliness and also a link between technological discomfort.

2.5.2   Self-Ffficacy

Self- efficacy is defined as a person’s belief about their ability to organize and execute courses of action necessary to achieve a goal (Bandura A., 1977). Recent studies have provided empirical support for the relationship between self-efficacy and technology usage. Hill et al. (1987) showed that computer self-efficacy is an important determinant of an individual’s decision to use computer technology. In a different study, Compeau & Higgins (1995) found self-efficacy to play an important role in determining computer usage, both directly and through outcome expectations.

Igbaria & Iivari (1995) found self-efficacy to have a strong direct effect on perceived ease of use. In another study, computer self-efficacy was found to have a positive effect on both perceived ease of use and perceived usefulness (Venkatesh, 2000; Wang et al., 2003). It was hypothesised that perceived self-efficacy regarding confidence in one’s ability to use Self Service Banking technologies (SSBTs) would have a positive effect on an individual’s judgment about the usability of an SSBT.

2.5.3   Ease-of-Use as a Barrier to M-Banking Usage

The ease-of-use is related to the usability of the service and the changes it requires on the part of the consumers. Siau and Shen (2003) note that whilst mobile devices demonstrate a greater extent of mobility and flexibility compared to personal computers and laptops, the small screens of mobile terminals and tiny multifunction keypads are cumbersome to use further inhibiting data input and output.

Earlier literature on mobile banking shows that smaller screens are adequate in information-based services but services requiring transactions call for bigger screen size (Laukkanen, 2007). For example, bill payment via mobile phone is perceived to be quite difficult and time-consuming by some consumers as the device enables only a limited amount of information processing and therefore the entire bill is not visible on the screen (Laukkanen and Lauronen, 2005).

Moreover, in their qualitative study Laukkanen and Lauronen (2005) report that those mobile banking services that do not require PIN and TAN codes, such as request for account balance service, creates comfort, ease of use and reliability for the delivery of services.

2.6  Chapter Summary

The chapter presented the literature and recent studies in the areas of Mobile Banking and user perception. Starting with a brief introduction to the chapter, this chapter explored literature on M-banking models and classification of m-banking services. The chapter then discussed the four main aspects of M-banking that affect the customer perception of M-banking products as a whole with reference to recent studies in this area.

Having reviewed the relevant literature in the area of m-banking and customer perception, the chapter that follows will capture the research methodology and describe in details the methods and procedures that will be used to carry out this study.

Chapter Three

3.0 Research Methodology

3.1 Introduction

This chapter outlines the method that will be used for the study and adopts the following structure: research design, population and sample, population description and data collection methods. Described also in this chapter is the research instrument used as well as the data analysis techniques.

3.2 Research Design

The research design to be used in this study is a descriptive design. The cross-sectional survey design will be used. This approach involves collecting data from more than one case and at a single point in time to gather a body of qualitative or quantifiable data in connection with multiple variables which are then analyzed to identify association patterns (Bryman 2001). According to Burns and Bush (2010), a descriptive research design is a set of methods and procedures that describe variables.

Churchill and Brown (2007) consider a descriptive research design as typically concerned with determining the frequency with which something occurs or the relationship between variables. Descriptive study investigates these variables by answering who, what, where, when and how questions (Cooper and Schindler, 2001). Further, Cooper and Schindler (2001) consider descriptive research as versatile and popular in business research. Descriptive research is carried out to describe the characteristics of relevant groups, such as customers, organizations or market areas; to estimate the percentage of units displayed in a specified population exhibiting a certain behavior; to determine the perceptions of products or services characteristics; to determine the degree to which variables are associated and to make specific predictions

The survey research design is the most appropriate for this study, as it allows for the description, interpretation, of existing relationships and comparison of variables under study. Bias is also less common in studies when participants are randomly assigned to procedures, and when subjects and respondents are blind to the treatment identification.

3.3 Population and Sampling Design

3.3.1 Population

A population is an entire group of individuals, events, or objects having in common observable characteristic (Mugenda and Mugenda (2003). Cooper and Schindler (2008) on the other hand define a population as the total of the elements upon which inferences can be made. From a population, a sample which is usually a representative sub-set or microcosm of the population is drawn.

In this study, the population will comprise users and potential-users of the mobile banking services drawn from Nairobi, Kenya.  Generally, the respondents will be individuals who have been exposed to mobile phone usage. Thietart, et al. (2001), define a target population as one for which the study results will be generalized through statistical inference while the study population is one that is operationalized in order to have clear criteria to determine the elements included or excluded.

3.3.2 Sampling Design

Sampling involves selecting individual units to measure from a larger population. Sampling presents several benefits to the researcher. The three main advantages of sampling are that the cost is lower, data collection is quicker, and since the data set is smaller, homogeneity can be maintained and data accuracy and consistency increased. According to Adèr, Mellenbergh, & Hand (2008), researchers rarely survey the entire population for two reasons; the cost is too high, and the population is dynamic in that the those who make up the population can change over time.

3.3.2.1 Sampling Frame

A sample frame is a list of elements from which the sample is actually drawn and is closely related to the population (Cooper and Schindler, 2008). According to   Saunders, Lewis, and Thornhill (2007), a sample frame is a complete list of all the cases in the population from which the sample is drawn. The list could of geographical areas, institutions, individuals, or other units (Churchill and Brown, 2007).

In this study the sample frame will comprise one representative mobile money transfer product; Mpesa, and account related m-banking services offered by two major banks in Kenya (equity and Family bank). In cases of account related services, the participating banks will help identify the service consumers and potential customers whereas in the case of the money transfer service, respective dealers will help identify the users of the services.

3.3.2.2 Sampling Technique

A sample is a population group which will be representative of the population (Coopers & Schindler, 2008). Sampling is the method of choosing elements that will reflect the population from the sample (Collins and Hussey, 2006).

A stratified random sampling (probability sample) technique will be engaged to identify sample elements in this study. Stratified random sampling is the probability of selection in which units are randomly sampled from a population that has been divided into categories or strata (Bryman, 2008).

Stratified sampling has several potential benefits; firstly, the division of the population into separate, independent strata can allow researchers to draw inferences about specific subgroups that may be lost in A more generic random sample; the use of a stratified sampling method will lead to more efficient statistical estimates (provided that the selection of strata is based on the appropriate criterion; instead of availability of the samples and finally, since each stratum is treated as an independent population, different sampling approaches can be applied to different strata, potentially enabling researchers to use the approach best suited for each identified subgroup within the population.

The researcher must randomly select the individual respondents after receiving the sample respondents from the various sources as outlined above. The respondents will be stratified according whether they are consumers of the m-banking services or whether they are non-consumers, services consumed/likely to be consumed and then within these strata, individual elements will be randomly selected in order to ensure that each respondent has an equal chance of being chosen.

3.3.2.3 Sample Size

A statistical sample size is the number of observations that make up it. A cording to Thietart, et al (2001) a sample size is the set of elements from which data is collected. The sample size enables the researcher to have adequate time and resources in piloting and designing the means of collecting data. The sample size ensures that the information is detailed and comprehensive.

A sample size of 170 respondents will be used because of some resource constraints particularly associated with time and finances. The sample distribution will be as follows:

Sample Distrebution
 M-Banking ServiceNo. of respondents% of the sample Size
Mkesho(Equity Bank)4018
Pesa-pap! (Family Bank)3014
SMS Banking4018
Mpesa5023
Non-Users6027
TOTAL220100

3.4 Data Collection Methods

Data will be collected using a structured questionnaire written in English and which will be developed and organized on the basis of the research’s specific objectives. The organized approach has been chosen to ensure that the responses achieve uniformity. The respondents will be served the questionnaire through drop and pick methods. The method was chosen because of the limited time and financial constraints.

3.5 Research Procedures

First a pilot test will be performed on 5 per cent of the sample size. The pilot test adhere to the fundamentals attested by Cooper and Schindler (2008), who define a pilot test as a tool that should be administered so as to detect weaknesses in the research design and the instruments. Kumar (2005) describes a pilot study in the same optics as a study that is performed to assess its feasibility. It is also referred to as feasibility study. A defined time period of three days will be offered for the pilot test. The questionnaire will be redesigned on the basis of the feedback that the researcher will receive. Respondents in the pilot test will be requested to highlight any ambiguous or duplicated questions, to point out if wording is clear, if all questions could be interpreted in similarly by respondents or if any study bias occurs. The final version of the questionnaire (which will be part of the appendices of the project) will be administered to the respondents selected in the sample size excluding the respondents who participated earlier in the pilot test. At the end the final questionnaire will also comprise a cover letter clarifying the purpose of the research.

The researcher will get some assistance from his undergraduate colleagues (Research Assistants) who have a business background and all between junior and senior year of study. Research assistants (RA) must initially be instructed on the different aspects of the research instruments. Time span will be six months to complete the entire analysis. The first four months will be used for drafting the plan, the fifth month for data collection and the last month for data analysis, debate, conclusions, recommendations and finalization of the entire report.

3.6 Data Analysis Methods

The collected data will be statistically analyzed using the Microsoft Excel spread sheet program and the Statistical Program for Social Scientists (SPSS). Editing of the data will be undertaken before data analysis. Using the cited statistical tools, frequency tables, cross tabulations, percentages, variance, standard deviations, and regressions will be generated to analyze the respondents’ measure to the various aspects elaborated in the questionnaires. Tables, pie charts and bar graphs will be used to present the data to enable ease in the understand ability, analysis and interpretation of the results.

3.7 Chapter Summary

This chapter essentially described the research methodology that will be used to carry out this study. The population is defined and the sampling technique, and sample size have been described. The chapter also addressed how the work will be done. Also discussed in this chapter are data collection methods and the instruments to be used. The chapter also highlighted the research procedures. The chapter concluded with the data analysis methods which the researcher will use to analyze the collected data, and make conclusive remarks on the study.

Having discussed the approach to be used in this research, the following chapter describes the study’s findings.

References
  • Ahmad, S. 2002. ‘Service failures and customer defection: A closer look at online shopping experiences’, Managing Service Quality, 23(3): 19-29.
  • Aiken, L.S. & West, S.G. 1991. Multiple regression: Testing and interpreting interactions. New York: Sage Publications.
  • Arbuckle, J.L., Amos User’s Guide Version 3.6, SaltWaters Corporation, Chicago, IL, 1997.
  • Aron, M. (2007). Kenya: trend-setting M-Pesa goes international. Business Daily.Nairobi.
  • Banduras, A. , Self-efficacy: Toward a Unifying Theory of Behavioral Change, Psychological Review 1977, Vol. 84, No. 2, 191-215.
  • Baveja, S.S., Rastogi, S. & Zook, C. 2000. The value of online customer loyalty. Atlanta: Mainspring, Bain & Company.
  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238-246.
  • Bhattacherjee, A. 2001a. ‘An empirical analysis of the antecedents of electronic commerce service continuance’, Decision Support Systems, 32: 201-214.
  • Bobbitt, L. M., & Dabholkar, P. A. (2001). Integrating attitudinal theories to understand and predict use of technology-based self-service: the Internet as an illustration. International Journal of Service Industry Management, 12(5), 423-450.
  • Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K.A. Bollen & J. S. Long (Eds.), Testing Structural Equation Models (pp. 136-162).Newbury Park, CA: Sage.
  • Byrne, B. M. (2001). Structural equation modeling with AMOS: basic concepts, applications, and programming. Mahwah, New Jersey: Lawrence Erlbaum Associates.
  • Charness, N., Park, D. C., & Sabel, B. A. (2001). Communication, technology and aging: opportunities and challenges for the future. New York: Springer Publishing Company, Inc.
  • Comninos, A., Esselaar, S., Ndiwalana, A. & Stork, C., (2008).Towards evidence-based ICT policy and regulation m-banking the unbanked, (Policy Paper 4)
  • Compeau, D.R. and C.A. Higgins, Computer self-efficacy: development of measure and initial test, MIS Quarterly, 19(2): 189–211, June 1995.
  • Curran, J. M., Meuter, M. L., & Surprenant, C. F. (2003). Intentions to use selfservice technologies: a confluence of multiple attitude. Journal of Service Research,5(3), 209-224.
  • Dabholkar, P. A. (2000). Technology in service delivery: implications for self-service and service support. In T.A. Swartz & D Iacobucci (Eds.), Handbook of Services
  • Davis, F.D., A technology acceptance model for empirically testing new end-user information systems: theory and results, Doctoral dissertation, MIT Sloan School of Management, Cambridge, MA, 1986.
  • Davis, F.D, Bagozzi, R.P. & Warshaw, P, R. 1989. ‘User acceptance of computer technology: A comparison of two theoretical models’, Management Science, 35(8): 982-1003.
  • Davis, F.D. and V. Venkatesh, A critical assessment of potential measurement biases in the technology acceptance model: three experiments, International Journal of Human–Computer Studies, 45: 19–45, 1996.
  • Davis, F.D., Bagozzi, R.P. & Warshaw, P.R. 1992.‘Extrinsic and intrinsic motivation to use computers in the workplace’, Journal of Applied Social Psychology, 22(4):1111-1132.
  • Davis, F.D., User acceptance of information technology: system characteristics, user perceptions and behavioral impacts, International Journal of Man-Machine Studies, 38: 475–487, 1993.
  • Devraj, S., Fan, M. & Kohli, R. 2002. ‘Antecedents of B2C channel and preference: Validating e-commerce metrics’,Information Systems Research, 13(3): 316-333.
  • Delone, W.H. & McLean, E.R. 1992. ‘Information systems success: The quest for the dependant variable’, Information Systems Research, 3(1): 60-95.
  • Dowling, G.R. & Uncles, M. 1997. ‘Do customer loyalty programs really work’, Sloan Management Review, summer: 71-82.
  • D. R. Cooper and P. S. Schindler, 2008, Business Research Methods, 10th Edition, Chicago.
  • Federation of Finnish Financial Services, 2007. Saving and borrowing in Finland. Survey Report, May 2007. Available online at www.fkl.fi
  • Financial Sector Deepening (Kenya) Annual report, 2007
  • Forsythe, S.M., Shi, B., 2003. Consumer patronage and risk perceptions in Internet shopping.Journal of Business Research 56, 867–875.
  • Georgi, F. and J.Pinkl; “Mobile Banking in Deutschland – Der zweite Anlauf”, in Die Bank,Berlin, Issue 3/2005, p. 57-61.
  • Hartwick, J. and H. Barki, Explaining the role of user participation in information system use, Management Science, 40(4): 440–465, April, 1994.
  • Hubona, G.S. and E. Kennick, The impact of external variables on information technology usage behavior, in: Proc. of the 29th Annual Hawaii International Conference on System Science 1995}, January 1996.
  • Hubona, G.S. and S. Geitz, External Variables, beliefs, attitudes and information technology usage behavior, in: Proc. of the 30th Annual Hawaii International Conference on System Sciences. IEEE Computer Society Press, Los Almitos, CA, 1997.
  • Indrani Medhi, Aishwarya Ratan, Kentaro Toyama (2009): Mobile-Banking Adoption and Usage by Low-Literate, Low-Income Users in the Developing World. Sadashivnagar, Bangalore-560080- India
  • Johnson, P. O. (1959). “Development of the sample survey as a scientific methodology”. Journal of Experiential Education, 27, 167-176.
  • Karsch, W.; “Mobile Banking: Vor dem Durchbruch in Deutschland”, in Die Bank, Berlin, Issue: 09/2004, pp. 70-72.
  • Koivu T 2002 Do efficient banking sectors accelerate economic growth in transition countries? Bank of Finland Institute for Economies in Transition
  • Kumar, R. 2005. Research methodology: A step-by-step guide for beginners. London: Sage Publications Ltd
  • Lyman T, Porteous D, and Pickens M, 2008, Regulating Transformational Branchless Banking:Mobile Phones and Other Technology to Increase Access to Finance.” Focus Note 43.Washington, D.C.: CGAP.
  • Lyman,T., Ivatury & Staschen (2006). Use of agents in branchless Banking for the Poor: rewards, risks, and regulation. CGAPWebsite
  • Marketing & Management (pp. 103-110), California: Thousand Oakes. Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self service: moderating effects of consumer traits and situational factors. Journal of the Academy of Marketing Science, 30(3), 184-201.
  • Mugenda, O., & Mugenda, A. (2003). Research Methods: Quantitative & Qualitative Approaches. Nairobi: African Centre for Technology Studies.
  • Njenga A, 2009, “Mobile phone banking: Usage and experience in Kenya” Catholic university of East Africa.
  • On the security of 3GPP networks, Michael Walker, Vodafone Airtouch & Royal Holloway, University of London
  • Owens, John and Anna Bantug-Herrera (2006): Catching the Technology Wave: Mobile Phone Banking and Text-A-Payment in the Philippines
  • Porteous D, 2006, “The Enabling Environment for Mobile Banking in Africa”, London: DFID.
  • Ratan, A. L. (2008) ‘Using technology to deliver financial services to low-income households: a preliminary study of Equity Bank and M-PESA customers in Kenya’, Microsoft Research Technical Report, June 2008.
  • Ratha., Sanket & Vijayalakshmi( 2009): Mobile banking: Overview of Regulatory framework in emerging markets, Grameenphone Ltd, Bangladesh
  • Raymond Alain Thietart, N/a, Thietart (2001). Doing Management Research. London: Sage Publications Ltd
  • Sarker S and Wells J D, 2003, Understanding mobile handheld device use and adoption.Communication of the ACM V 46 n 12
  • Saunders, M., Lewis, P., & Thornhill, A. (2007). Research Methods For Business Students (4th Edtiion). (F. T. Press, Ed.) Harlow, England: Pearson Education Inc.
  • Sirken. (2009). Ministry of finance audit findings on M-Pesa money transfer services. Retrieved September 25, 2009, from the Kenya political blog.
  • Tiwari, R., S. Buse, and C. Herstatt (2006): “Mobile Banking as Business Strategy: Impact of Mobile Technologies on Customer Behaviour and its Implications for Banks”, in: Technology Management for the Global Future – Proceedings of PICMET ’06, July 8 – 13, 2006, Istanbul, pp. 1935 – 1946.
  • Tiwari, R., S. Buse, and C. Herstatt (2007): “Mobile Services in Banking Sector: The Role of Innovative Business Solutions in Generating Competitive Advantage”, in: Proceedings of the International Research Conference on Quality, Innovation and Knowledge Management, New Delhi, pp. 886-894.
  • Tiwari, R. and S. Buse, The Mobile Commerce Prospects: A Strategic Analysis of Opportunities in the Banking Sector, unpublished.
  • Tiwari, Rajnish and Buse, Stephan (2007): The Mobile Commerce Prospects: A Strategic Analysis of Opportunities in the Banking Sector, Hamburg University Press
  • Tiwari, Rajnish; Buse, Stephan and Herstatt, Cornelius (2006): Customer on the Move: Strategic Implications of Mobile Banking for Banks and Financial Enterprises, in: CEC/EEE 2006, Proceedings of The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services (CEC/EEE’06), San Francisco, pp. 522–529.
  • Tiwari, Rajnish; Buse, Stephan and Herstatt, Cornelius (2006): Mobile Banking as Business Strategy: Impact of Mobile Technologies on Customer Behaviour and its Implications for Banks, in: Technology Management for the Global Future – Proceedings of PICMET ’06.
  • Vaughan, P. (2007). Early lessons from the deployment of M-PESA, Vodafone’s own mobile transactions service. In D. Coyle (Ed.), The Transformational Potential of MTransactions (Vol. 6, pp. 6-9). London: Vodafone Group.
  • Venkatesh V. and R. Agarwal,Turning Visitors into Customers: A Usability-Centric Perspective on Purchase Behavior in Electronic Channels, Management Science, March 1, 2006; 52(3): 367 – 382.
  • Wambari Andrew(2009): Mobile Banking in Developing Countries (a case study on Kenya)
  • Wessels, L. & Drennan, J. (2010). An Investigation of Consumer Acceptance of  M-Banking. International Journal of Bank Marketing, 28/7, 547-568.
  • Yi, M.Y. and V. Venkatesh, Role of computer self-efficacy in predicting user acceptance and use of information technology, in: Proc. Conference for the Association of Information Systems (AIS), July 1996.

Appendices

Appendix 1: Cover Letter

United States International University

Friday, 7th 2011.

Dear Respondent,

RE: M-Banking Services Customer Perception Survey-2011

In partial fulfillment of the requirement for the degree of Masters of Business Administration (MBA) at USIU, I am carrying out a research to establish the level of user satisfaction/perception of the mobile banking services in the Kenyan market.

Sir/Madam, I would be very grateful if you kindly completed the enclosed questionnaire which will be used to collect the data relevant to the study. That would go a long way in helping me successfully conduct this study. You have been randomly selected among many to participate in this study and it is estimated that it will take less than ten (10) minutes of your time to complete the questionnaire. If you have any questions or concerns about completing the enclosed questionnaire, please do not hesitate to contact me any time through my contact provided below.

I assure you of the highest level of confidentiality in your participation in this exercise. Your views, comments and expectations will be treated with confidentiality and as such will not be used for any other purpose other than for which they were sought.

Thank you for your continued cooperation and support.

Yours Sincerely,

Student (Researcher)

Appendix 2: Questionnare

 

Appendix 3: Research Budget

 

ACTIVITIESCOST (Ksh)
PROPOSAL DEVELOPMENT

Materials (Outlining & Drafting papers)

Typing and Printing

Stationary, Photocopying

 

3,000

2,500

5,000

 

FIELD WORK (DATA COLLECTION)

Questionnaires printing/photocopying (450 copies @Ksh 20 each)

Telephone

Travelling Expenses

 

 

9,000

6,000

10,000

 

DATA ANALYSIS AND COMPILATION

Coding entry and analysis

Editing fee

 Printing of Final Project Drafts

 

7,000

3,000

5,000

PRINTING & BINDING OF FINAL PROJECT

Printing 5 copies(100 pages each) @ 1500 per copy

Binding @ 500 per copy

 

7,500

2,500

 

Others   3,000

 

TOTAL BUDGET (TENTATIVE)

 

  63,500

Appendix 4: Work Plan

ActivityTime Frame
StartFinishDuration
1Development of Draft ProposalSeptember 1st , 2011Dec ember 1st, 201113 weeks
2Pilot TestingJanuary  17th, 2011January 21th, 20115 days
3Data CollectionJanuary 24th, 2011February 11th , 20113 weeks
4Data entry and editingFebruary 15th , 2011February 17th, 20113 days
4Data AnalysisFebruary 18th , 2011February 25th, 20111 weeks
5Writing of Discussions, Recommendations, and ConclusionFebruary 26th, 2011March 5th  20111 week
6Finalizing the Entire ProjectMarch 7th , 2011March 8th  , 20112 day
7Binding of the ProjectMarch 9th , 2011March 9th , 20111 day

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