Factors Influencing the Adoption of Mobile Credit System in Kenya

A Project Report Submitted to the Chandaria School of Business in Partial Fulfillment of the Requirement for the Degree of Executive Masters of Organizational Development (EMOD)The purpose of this study was to identify factors influencing the adoption of mobile credit system in Kenya and the specific research questions of the study were: to establish the influence of acceptability factors on the adoption of mobile credit system in Kenya; to establish the influence of affordability factors on the adoption of mobile credit system in Kenya; and to establish the influence of accessibility factors on the adoption of mobile credit system in Kenya. The research design was descriptive in nature. The research was conducted among Airtel Kenya employees – Mombasa Road Headquarters’ Office. The sampling frame from this study was selected from a population of 350 employees as provided by the Human Resources office electronic mails. A sample of 78 employees was targeted to represent the population of interest. The data gathered was edited and transformed into a quantitative form through coding. It was then entered into a computer. Univariate analysis like frequency distribution was adopted in the study. The analyzed data was presented inform of tables. Statistical Package for the Social Science (SPPS) was used to aid in data analysis. In regards to acceptability factors and adoption of mobile credit system in Kenya, the first major findings of the study was that the questions which were asked included amongst others on marketing exposure, demographic characteristics, and security concerns. On marketing exposure, respondents agreed that promotional efforts can create awareness of mobile credit system in establishing the influence of acceptability factors; on demographic characteristics, respondents strongly agreed that age, education and wealth characteristics are predictor of adoption decision in establishing the influence of acceptability factors; and on security concerns, out of respondents agreed that mobile provider should generate trust among uneducated rural subscribers in establishing the influence of acceptability factors. Thus, the researcher concluded that perceived security concerns has the higher ability to predict and explain the intention of users to adopt mobile credit system in Kenya. With respect to affordability factors and adoption of mobile credit system in Kenya the second major findings of this study indicated that the questions which were asked included amongst others on online transaction, credit availability, and transaction cost. On online transaction, respondents agreed that credibility was everything if it comes to mobile credit system in establishing the affordability; on credit availability, respondents agreed that out of stock lead the subscribers not to adopt the credit system in establishing the affordability factors; and on transaction cost, respondents strongly agreed that the cost of transaction to be lowered to attract rural population in establishing affordability factors. Thus, the researcher concluded that transaction cost has the higher ability to predict and explain the intention of users to adopt mobile credit system in Kenya. In relation to accessibility factors and adoption of mobile credit system in Kenya, the third and last major findings of this study indicated that the questions which were asked included amongst others on service convenience, technical issues, and network efficiency. On service convenience, respondents strongly agreed that credit system should be reasonably priced in establishing accessibility factors; on technical issues, respondents strongly agreed that limitation increases complexities thus reduces the possibility of adoption in establishing accessibility factors; and on network efficiency, respondents were neutral on the speed of mobile web connections in establishing accessibility factors. Thus, the researcher concluded that service convenience has the higher ability to predict and explain the intention of users to adopt mobile credit system in Kenya. The study made several conclusions among them that firstly, with respect to the influence of acceptability factors on mobile credit system adoption, this study concluded that perceived security risk was all about the extent to which technology-enabled services were perceived to be secure, sufficiently safe and reliable to use. Secondly, in regards to the influence of affordability factors on mobile credit system adoption, this study concluded that, users would agree to pay a reasonable fee to use a service depending on the credit cost and service provider. Thus, value for money barrier may be another factor influencing the adoption of mobile credit system. Thirdly and final, in relations to accessibility factors on mobile credit system adoption, this study concluded that, price of a technology was an important factor that influenced the adoption of the technology. This was because in times of increased competition, a distribution channel organized business processes efficiently so as to reduce distribution costs. The study also made a recommendation that the location of this study is only confined to Airtel Kenya employees at Kenya Headquarter in Nairobi. Thus, the sample and its responses may not be a representation of the beliefs and intention of Kenya towards using mobile credit system. Future research can improve on this limitation by increasing the sample size and performing future research across different respondents