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 recent years witnessed tremendous growth in the use of mobile money transfer services. This growth can be partly traced back to technological and demographical developments that have been influencing important aspects of the socio-cultural behavior in today’s world. The need/wish for mobility seems to be the driving force behind Mobile Commerce in general. 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
1.1 Background of the Problem.. 5
1.2 Statement of the Problem.. 9
1.5 Importance of the study. 11
1.5.1 To Businesses, Investors and Individuals. 11
2.2 Mobile Banking Awareness. 14
2.2.1 Employment of Mobile Technologies in the Banking Sector 14
2.2.1.3 Mobile financial information. 16
2.2.2 Mobile banking Business models. 18
2.2.3 Mobile Banking Regulations. 20
2.2.4 Effect of awareness on Mobile banking usage. 22
2.3 Perceived Security of mobile banking Services. 22
2.3.1 General Security features of mobile banking products. 22
2.3.2 General Security Concern in GSM.. 23
2.3.3 The risk barrier to m-banking usage in Kenya. 23
2.4 Perceived Usefulness of M-banking products. 24
2.4.1 Match between offerings and need. 27
2.4.2 Pricing vis-à-vis alternate channels. 27
2.4.3 Reliability with respect to informal channels. 28
2.5.1 Technology Discomfort 30
2.5.3 Ease-of-use as a barrier to M-Banking usage. 31
3.3 Population and Sampling Design. 33
3.3.2.2 Sampling Technique. 34
3.4 Data Collection Methods. 35
Appendix 3: RESEARCH BUDGET. 51
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).
In the financial services sector, mobile banking represents an additional service for certain occasions adding the element of true mobility to Internet banking used over fixed networks. Some bank customers, for example, find mobile banking valuable when being out of a home on a country cottage, on the road or in case of the 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 most recent data available indicates that only 19% of adult Kenyans reported having access to a formal, regulated financial institution while over a third (38%) indicated no access to even the most rudimentary 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.
A 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 take-off in Kenya, on the back of a strengthening economy, the advent of technology and systematic reforms of the sector.
An appropriate banking environment is considered a key pillar as well as 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 grassroots closer to their potential customers. However, with the continuously emerging wave of information-driven economy, the banking industry in Kenya has inevitably found itself unable to resist technological indulgence in order to meet customer needs. Koivu asserts that the need for convenient ways of accessing financial resources beyond the conventional norms has seen the recurrent expansion and modernization of banking patterns. Given the huge demand for finance-oriented services, even institutions besides the historical banks such as the mobile phone service providers have joined the fray in an attempt to grab a piece of the perceived cake of opportunity within the banking industry.
The challenging business process in the financial services pressurized banks to introduce alternate delivery channel to attract customers and improve customers’ perception. 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 an umbrella term for the process by which a customer may perform banking transactions electronically without visiting a brick-and-mortar institution (FinCen, 2000). E-banking encompasses the use of 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 trend of continued reliance on mobile devices to execute monetary transactions is steadily gaining momentum. 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 distribution channel that allows financial institutions and other commercial actors 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 to 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 landmark 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 offered entirely by banks, others entirely by telecommunications providers, and still others involve a partnership between a bank and a telecommunications provider. 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. The 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) highlighted the need for further research to measure the influence of e-service on customer-perceived service quality and satisfaction (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 most recent is m-banking—a platform for the delivery of financial services via the mobile phone. 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 an ongoing basis and need to acquire a certain comfort level with the technology to keep using it (Servon and Kaestner, 2008) hence the need for regular feedback about their experiences.
Research on consumer attitude and adoption of e-banking showed that there are several factors predetermining the consumer’s attitude towards e-banking such as person’s demography, perceived risk, ease of use of the service and one’s 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 compliments. 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 to 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 the Nairobi area and the survey will be conducted between the month of June 2011 and July 2011.
1.7 Definition of Terms
- 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, the 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. It comprises of services in the field of accounting, brokerage, and financial information. He further notes that Mobile Banking is increasingly being employed by many banks around the world to generate additional revenues, reduce costs or to increase customer satisfaction, often with greater success.
Unlike in the past, when banks offering mobile services suffered a severe setback due to lack of customer interest and unripe technologies, the time seems to be now ripe for (re-)launching mobile services(Tiwari R., et al 2006). Mobile Banking is usually defined as carrying out banking business with the help of mobile devices such as mobile phones or PDAs. The offered services may include transaction facilities as well as other related services that cater primarily to informational needs revolving around financial activities.
2.2.1.1 Mobile Accounting
Mobile Accounting is sometimes characterized as transaction-based banking services that revolve around a bank account and are availed using mobile devices (Georgi and Pinkl 2005). Not all Mobile Accounting services are however necessarily transaction-based. A more precise definition of Mobile Accounting would therefore characterize it as “availment of account-specific banking services of non-informational nature (Tiwari et al). Mobile Accounting services may be divided in two categories to differentiate between services that are essential to operate an account and services that are essential to administer an account.
Table 2.1: Services in Mobile Accounting
| Mobile Accounting | |
| Account Operation | Account Administration |
| Money remittances & transfers | Access administration |
| Standing orders for bill payments | Changing operative accounts |
| Money transfer to sub-accounts | Blocking lost cards |
| Subscribing insurance policies | Cheque book requests |
Source: Tiwari R., et al (2006)
2.2.1.2 Mobile Brokerage
Brokerage, in the context of banking- and financial services refers to intermediary services related to the bourse, e.g. selling and purchasing of stocks. Mobile Brokerage can be thus defined as transaction-based mobile financial services of non-informational nature that revolve around a securities account (Georgi and Pinkl, 2005). Mobile Brokerage, too, may be divided into two categories to differentiate between services that are essential to operate a securities account and services that are essential to administer that account. (Georgi and Pinkl, 2005).
Table 2.2: Services in Mobile Brokerage
| Mobile Brokerage | |
| Account Operation | Account 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 any time, anywhere access to information (Georgi, F. and J.Pinkl 2005). The information may either concern the bank and securities accounts of the customer or it may be regarding market developments with relevance for that individual customer.
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. The information should be provided, ideally, on both, pull and push basis. Information services are an integral part of Mobile Accounting and Mobile Brokerage but they may also be offered as a stand-alone, independent module, i.e. Mobile Financial Information can be offered without offering Mobile Accounting or Mobile brokerage but vice versa is not feasible.
Table 2.3: Services in Mobile Financial Information
| Mobile Financial Information | |
| Account Information | Market Information |
| Balance inquiries / Latest transactions | Foreign exchange rates |
| Statement requests | Market and bank-specific interest rates |
| Threshold alerts | Commodity prices |
| Returned cheques / cheque status | Stock market quotes and reports |
| Credit card information | Product 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 wide spectrum of Mobile/branchless banking models is evolving. However, no matter what business model, if mobile banking is being used to attract low-income populations in often rural locations, the business model will depend on banking 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 mobile banking business model since customer care, service quality, and cash management will depend on them. Many telecoms will work through their local airtime resellers. In Colombia, Brazil, Peru, and other markets however, the use of pharmacies, bakeries, etc as agents is common. These models differ primarily on the question that who will establish the relationship (account opening, deposit-taking, lending, etc.) to the end customer, the Bank or the Non-Bank/Telecommunication Company (Telco). Another difference lies in the nature of agency agreement between the bank and the Non-Bank (Infogile, 2007). Models of branchless banking can be classified 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 traditional bank uses non-traditional low-cost delivery channels to provide banking services to its existing customers (Infogile, 2007). In this model the technological/physical infrastructure of a mobile operator/retailer is used to provide some basic banking services like balance inquiry, A/c to A/c fund transfer, payments for goods/services at merchant outlets using bank account (through ATM/ Debit card / Phone SMS ). Most of these services are already being provided by banks and are covered under existing regulations. So this model poses little specific regulatory issues (Infogile, 2007).
2.2.2.2 Bank-led model
According to Ratha., Sanket and Vijayalakshmi, (2009), The bank-led model offers a distinct alternative to conventional branch-based banking in that customer conducts financial transactions at a whole range of retail agents (or through 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) having experience and target market distinct from traditional banks, and maybe significantly cheaper than the bank-based alternatives.
The bank-led model may be implemented by either using correspondent arrangements or by creating a partnership between Bank and Telco/non-bank (Infogile, 2007). In this model, customer account relationship rests with the bank. This model is, therefore, prone to agent-related risks. These agent-related risks can, however, be mitigated by making banks fully liable for actions of their agents and by giving regulators the power to review agents’ record of bank-related transactions
2.2.2.3 Non-Bank-led model
In this model, customers do not deal with a bank, nor do they maintain 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). Here, the bank does not come into the picture (except possibly as a safe-keeper of surplus funds) 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 nonbank’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 mobile banking activities in Kenya require a deep look at the development of M-pesa, a pioneer mobile banking service in Kenya. Prior to the launch of M-PESA services in Kenya, Safaricom sought authorization from the Central Bank of Kenya (CBK) to undertake the money transfer service. 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 Financial Institutions Supervision Department (FISD) is responsible for the prudential regulation of banks and deposit-taking MFIs. Its primary concern regarding M-PESA was whether the operator (Safaricom) is stretching or even breaking the rules for the business of banking.
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. However, the primary regulator with respect to a mobile network operator’s m-banking activities 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. Specifically, the proceeds from issuing e-money are held by M-PESA Trust Company Limited in trust for the clients in a pooled account with the Commercial Bank of Africa. Any interest earned on this pooled account cannot benefit Safaricom (without triggering the definition of “banking business”); use of interest proceeds is currently under consideration. Customer claims against M-PESA Trust Company arising from negligence or intentional wrongdoing by the trust company or by Safaricom shall be covered by Safaricom. In addition, caps on the maximum account balance (about US$ 750) and maximum transaction size (about US$ 530) provides CBK with additional comfort because they limit the risks of money laundering and the amount any individual customer could lose in case of insolvency. (CGAP, 2007)
Table 2.4 Legal and regulatory mobile banking related issues in Kenya
| Legal /regulatory issues | Non-bank based |
| KYC | Account 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/CFT | AML bill 2007 |
| E-money issuance | Kenya has no laws, regulations or policies dealing directly with e-money |
| Payment system | There 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).
According 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. 21 out of 30 subjects in the Philippines, 11 out of 23 in South Africa and 22 out of 26 in India had never heard of m-banking channels. 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 connect to it by searching for cells in the immediate vicinity.
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 risk barrier refers to the risks consumers encounter or perceive in innovations. 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 a typical banking regulator’s perspective, entrusting retail customer contact to the types of retail agents used in both the bank-led and nonbank-led models would seem riskier than these same functions in the hands of bank tellers in a conventional bank branch. These retail agents may operate in hard-to-reach or dangerous areas & they lack physical security systems and specially trained personnel. The lack of expert training may seem a particular problem if retail agents’ functions range beyond the cash-in/cash-out transactions of typical bank tellers to include a role in credit decisions.
E-Money Risks relates to acceptance of repayable funds from retail customers by Non-Bank entities that are not subjected to prudential regulation and supervision. 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, resulting in insolvency and the inability to honor customers’ claims.
2.4 Perceived Usefulness of M-banking products
Perceived usefulness is defined as the degree to which a person believes that using a particular technology will enhance his or her job performance. People tend to use or not to use an application to the extent they believe it will help them perform 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 usefulness explains the user’s perception to the extent that the technology will improve the user’s workplace performance (Davis et al. 1989). This means the user has a perception of how useful the technology is in performing his job tasks. This includes decreasing the time for doing the job, more efficiency and accuracy.
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, behavioral intentions are based primarily on performance-related elements, rather than on the individual’s attitude towards the behavior (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 defines the latter as perceived usefulness (PU), i.e. the belief that using the application would increase one’s performance. In this context, the performance would be centered in the benefits of obtaining banking services via mobile phone minus the trade-off of physical banking practice.
In the past, researchers have validated the construct of PU and they were found to influence the intention of a potential user of e-commerce such as internet shoppers. However, the study on Internet retailing from the TAM perspective is limited; nevertheless, the PU construct still garnered tremendous support from many other technological applications. For example, Horton et al. (2002) asserted the existence of a positive influence of PU on intention in Intranet media. 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); Mathieson et al. (2001); Moon and Kim (2001); Ramayah et al. (2002); Venkatesh and Davis (2000)also reported that PU is Significant and positively influences the behavioral intent. 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 purchase was offered via M-PESA, none of our respondents, even those who actively used M-PESA for money transfers had begun buying airtime through the m-payment 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 pricing of the m-banking service with respect to other formal and informal remittance channels available in a location was a determinant of how our subjects adopted and used the m-banking service (Indrani M. et al, (2009). In Kenya, one of the reasons for some users to shift to M-PESA for remittance transfers was because it was half the price of the formal alternative, i.e. the postal money order that they were currently using. For transacting with or between the unbanked, compared to the nearest formal, secure alternatives, M-PESA was lower cost, though it remains more expensive than using informal channels like 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 could simply hand over cash in an envelope to the driver traveling in the direction of the recipient’s location. In the case of 7 out of the 9 subjects, this transfer had no explicit cost given that the driver was a friend or a family member of the sender or the recipient.
2.4.3 Reliability with respect to informal channels
In their study “Mobile-Banking 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 out of 34 subjects described sending money through friends and relatives had no explicit cost, but sometimes the money never reached the intended recipient. Instead, with m-banking, doing the transfer directly to the recipient’s phone and receiving a 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
This refers to the degree to which a person believes that using a particular technology will be free of effort. 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 benefits of usage are outweighed by the effort of using the application (Davis and Arbor, 1989). Phillips and his colleagues defined perceived ease of use as ‘the degree to which the prospective adopter expects the new technology adopted from a foreign company to be free 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. Much of previous researches have established that perceived ease of use is an important factor influencing user acceptance and usage behaviour of information technologies. According to the Ram and Sheth’s (1989) consumer resistance framework, ease of- use as a 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) could prove to be daunting for some consumers. In short, the PEU is associated with the “user-friendliness” of the website. If the hassle proves to outweigh the benefit of purchasing through the net, then potential Internet shoppers would prefer to purchase through conventional channels.
One of the factors that contribute towards the unfriendliness of some websites of Internet retailers is long download times. Additionally, poorly designed forms might cause potential e-shoppers to lose focus of their carts and purchases. In other words, these barriers reduce the perception on the ease of use of Internet shopping, therein, allowing Internet user’s to develop a negative attitude. In turn, this leads to Internet shopper’s unwillingness 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 personalization 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). They did not access the application on their own device, instead of handing over their money and sometimes their phone to a peer or agent, and having them perform the transaction.
The two main factors affecting 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 to computer anxiety, a variable that has been found to have a negative effect on perceived ease of use (Venkatesh, 2000). The extended model proposes a similar link between technology discomfort and perceived ease of use and also a link between technology discomfort.
2.5.2 Self-efficacy
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 hence the whole bill is not visible on the display (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 a request for account balance service, creates convenience, ease of use and efficiency to the service consumption.
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 the 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
3.1 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 descriptive design. The cross-sectional survey design will be used. This design entails the collection of data of more than one case and at a single point in time in order to collect a body of qualitative or quantifiable data in connection with several variables which are then examined to detect the patterns of association (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 conducted to describe the features of relevant groups, such as customers, organizations, or market areas; to estimate the percentage of units 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. In surveys, bias is also less likely if subjects are randomly assigned to treatments, and if subjects and researchers are blind to the identity of the treatments.
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 faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. 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 individuals making up the population may 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 group from the population that will be representative of the population (Coopers and Schindler, 2008). Sampling is the technique of selecting elements from the population that will represent the population (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).
There are several potential benefits to stratified sampling; first, dividing the population into distinct, independent strata can enable researchers to draw inferences about specific subgroups that may be lost in a more generalized random sample; utilizing a stratified sampling method can lead to more efficient statistical estimates (provided that strata are selected based upon relevance to the criterion in question, 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.
On receiving the sample respondents from the various sources as outlined above, the researcher will randomly select the actual respondents. The respondents will be stratified according to 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
The sample size of a statistical sample is the number of observations that constitute it. A cording to Thietart, et al (2001) 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.
Due to some resource constraints especially associated with time and finances, a sample size of 170 respondents will be used. The sample distribution will be as follows:
| SAMPLE DISTRIBUTION | ||
| M-Banking Service | No. of respondents | % of the sample Size |
| Mkesho(Equity Bank) | 40 | 18 |
| Pesa-pap! (Family Bank) | 30 | 14 |
| SMS Banking | 40 | 18 |
| Mpesa | 50 | 23 |
| Non-Users | 60 | 27 |
| TOTAL | 220 | 100 |
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 structured approach has been preferred so as to ensure uniformity is achieved in the responses. 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
A pilot test on 5 percent of the sample size will be first conducted. 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. In the same optic, Kumar (2005) defines a pilot study as a study which is carried out to determine 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 the same way by respondents or if there is any research bias. 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. The research assistants (RA) will first be trained on the various aspects of the research instruments. The time span to carry out the entire study will be six months. The first four months will be used to develop the proposal, the fifth month will be for data collection, and the last one will be used for data analysis, discussions, conclusions, recommendations and finalization of the entire report.
3.6 Data Analysis Methods
The collected data will be statistically analyzed using the Microsoft Excel spreadsheet 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 understandability, 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 further discussed the method that will be used to conduct the research. 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 methodology to be used in this study, the chapter that follows will present the findings of the study.
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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,
Mr. Onyango Polycap Okumu,
Student-ISIU(Researcher),
Tel : 0721827107
Appendix 2: QUESTIONNAIRE
Appendix 3: RESEARCH BUDGET
| ACTIVITIES | COST (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
| Activity | Time Frame | |||
| Start | Finish | Duration | ||
| 1 | Development of Draft Proposal | September 1st, 2011 | Dec ember 1st, 2011 | 13 weeks |
| 2 | Pilot Testing | January 17th, 2011 | January 21th, 2011 | 5 days |
| 3 | Data Collection | January 24th, 2011 | February 11th, 2011 | 3 weeks |
| 4 | Data entry and editing | February 15th, 2011 | February 17th, 2011 | 3 days |
| 4 | Data Analysis | February 18th, 2011 | February 25th, 2011 | 1 week |
| 5 | Writing of Discussions, Recommendations, and Conclusion | February 26th, 2011 | March 5th, 2011 | 1 week |
| 6 | Finalizing the Entire Project | March 7th, 2011 | March 8th, 2011 | 2 day |
| 7 | Binding of the Project | March 9th, 2011 | March 9th, 2011 | 1 day |
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