LEVERAGING AI-ENHANCED PAYMENT AND FINANCIAL SYSTEMS TO ENHANCE PERFORMANCE OF TAXI BUSINESS IN NAIROBI COUNTY, KENYA
Abstract
Statement of the Problem: Use of AI-Enhanced Payment and Financial Systems is crucial in transforming taxi business operations by optimizing routes, improving customer experiences, predicting demand, and effectively lowering operational costs. However, the scenario is quite different for taxi businesses in Nairobi County, where performance remains low.
Purpose of the Study: To leverage AI-Enhanced Payment and Financial Systems to enhance performance of taxi business in Nairobi County, Kenya.
Methodology: The study employed a mixed-method approach with concurrent triangulation, targeting 37,838 respondents (17,045 taxi operators and 20,793 taxi drivers) in Nairobi County. Using Yamane's Formula, a sample of 391 respondents was selected through a combination of stratified sampling across 17 sub-counties, purposive sampling for taxi operators (170), and simple random sampling for taxi drivers (221). Data analysis combined thematic analysis for qualitative data and both descriptive and inferential statistics (using SPSS Version 25) for quantitative data.
Findings: The study established that performance of taxi business has been on a downward trend. This is attributed to the inability to taxi operators to effectively use AI-Enhanced Payment and Financial Systems as a form of AI application.
Recommendations: Taxi operators and owners should consider investing in AI-Enhanced Payment and Financial Systems-driven price optimization and data privacy tools to improve operational efficiency and customer satisfaction. This would allow taxi operators to leverage AI-Enhanced Payment and Financial Systems to predict areas of high demand, optimize prices in real-time based on traffic conditions, and reduce idle times.
Keywords: Leveraging, AI-Enhanced Payment, Financial Systems, Performance, Taxi Business
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