RISK FACTORS AND PERFORMANCE OF APP-BASED TAXI OPERATORS IN NAIROBI COUNTY, KENYA

Triza Karimi Njue, Dr. Richard Keroti

Abstract


The frequency of strikes among app-based taxi operators in Kenya has escalated significantly in recent years, with at least four actual and threatened strikes occurring within a year, primarily originating in Nairobi County. These strikes, some lasting over a day, pose a direct threat to the daily household income of drivers, with reports indicating that on strike days, drivers lose income averaging up to KSh. 3000 a day in Nairobi. Additionally, strikes in Nairobi have broader implications, causing traffic delays, reduced mobility, and, in extreme cases, resulting in damage to public and private property, as well as loss of life. The general objective of this study was to identify the risk factors faced by app-based taxi operators (drivers) in Nairobi County, and how these risk factors affect their performance. The study was guided by the following specific objectives; To identify the technological risks and financial risks experienced by app-based taxi operators in Nairobi County and their effects on performance. This study was guided by protection motivation theory and prospect theory. This study used descriptive research design. The unit of analysis for this study was Uber, Bolt, and Little while the unit of observation was the operators. Yamane’s formula was used to determine the study sample size. From the formula, the appropriate sample size for the study was 340 operators. The study sample was selected using stratified random sampling technique. This study used primary data collected using close-ended questionnaires. In the pilot study 34 participants were invited to participate in filling the questionnaires. The Statistical Package for Social Scientists (SPSS) version 28 was used for analysis. Quantitative data collected was analyzed using descriptive statistics techniques. Pearson R correlation will be used to measure the strength and direction of linear relationship between variables. Multiple regression models will be fitted to the data in order to determine how the independent variables influence the dependent variable. The findings were presented in tables and figures. The pilot study, involving 34 participants (10% of the study sample), demonstrated strong validity and reliability of the research instrument. The findings revealed that technological risks (Beta = 0.351, p = .000) positively influence performance, highlighting the importance of reliable technological infrastructure and effective training. Financial risks (Beta = 0.315, p = .000) were found to affect performance, underscoring the importance of robust financial management practices. The study concludes that effective management of these risks is crucial for enhancing the performance of app-based taxi operators. Recommendations include prioritizing advanced technologies, implementing financial risk management strategies.

Key Words: Risk Factors, App-Based Taxi Operators, Performance, Technological Risks, Financial Risks 


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