MBA Theses and Dissertations (2024)

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Browsing MBA Theses and Dissertations (2024) by Author "Anwar, F. S."

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    Determinants of electric vehicle adoption by public transport companies in Nairobi City County, Kenya
    (Strathmore University, 2024) Anwar, F. S.
    Even though several studies on the adoption of Electric Vehicles (EVs) have been conducted globally and regionally, there exist significant conceptual, methodological, and contextual inconsistencies identified, necessitating the present study to investigate and bridge these knowledge gaps. A literature search revealed limited studies conducted in Kenya on the factors influencing public transport companies' adoption of EVs in Nairobi City County. Using Kenya's Nairobi County as a case, this study sought to answer the question, "Which factors influence the electric vehicle adoption by public transport companies in Nairobi City County?" The study’s specific objectives are to establish the influence of perceived barriers, perceived benefits, and fleet managers' characteristics on electric vehicle adoption (EVA) by public transport companies in Nairobi City County. The study is grounded on three theoretical underpinnings: the unified theory of acceptance and tech use, automobility theory, and actor-network theory. This study adopted the positivism philosophy for quantitative research to fulfill the purpose of the study and inform the descriptive research design. The public transport companies that had not adopted EVs were selected through simple random sampling while the census approach selected the EVs-adopted firms for this study. As such, a sample size of 174 respondents was selected. Self-administered drop-and-pick questionnaires were used to collect data to minimize non-responsiveness. The pilot study included 18 respondents purposively sampled from Kisumu County public transport companies. In this regard, the unit of observation includes the fleet managers and operational staff members of public transport companies. The researcher tested the instruments to meet the reliability and validity threshold. The study used descriptive and inferential statistics. Descriptive statistics analyzed data quantitatively using percentages, means, and standard deviation, while inferential statistics estimated the relationship between the variables. Pearson correlation and multiple regression explained the relationship between the variables. Data was then presented in the form of frequency distribution tables. The study established that perceived barriers, perceived benefits, and fleet managers’ personal characteristics were significant predictors of electric vehicle adoption. Particularly, the study findings were that perceived barriers had a strong negative relationship with electric vehicle adoption. Perceived benefits and fleet managers’ personal characteristics had a positive relationship and were statistically significant with electric vehicle adoption. Therefore, there is a need to acknowledge the perceived barriers to EV adoption and leverage on the perceived benefits and fleet managers’ personal characteristics to enhance the rate at which public transport companies accept and use EVs in developing nations such as Kenya. The research focused on the determinants of EV adoption by public transport companies in Kenya’s Nairobi County. Therefore, this study cannot be generalized to private transport firms in Kenya. To address this limitation, a similar study may be undertaken on private transport companies.