Browsing by Author "Alirach Victor"

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    Consumer Adoption, Repayment Mechanisms and Performance of Online Lending Platforms in Kampala.
    (Makerere University Business School, 2025-10-14) Alirach Victor
    The performance of online lending platforms in Kampala District, consumer adoption, and repayment methods were all examined in this study, addressing growing concerns about low customer retention, operational inefficiencies, and slow technological adoption among digital lenders. The study's goal was to evaluate how consumer-centric elements like mobile accessibility, customer support, and transparency, along with repayment systems including credit scoring models, loan restructuring, and real-time payment tracking, influence platform performance. This research adopted a quantitative methodology with a cross-sectional design, following the principles of the Technology Acceptance Model (TAM). 44 out of 50 samples of online lending platforms operating in Kampala were selected. Data were collected using self-administered structured questionnaires distributed to 132 employees, with 107 valid responses obtained, reflecting an 81.6% response rate. Data analysis was performed utilizing SPSS software, combining correlation, regression, and descriptive statistics. Analysis of Corrections revealed a positive association between consumer adoption and platform performance (r = 0.703**, p < 0.01), and between repayment mechanisms and performance (r = 0.744**, p < 0.01). Among the dimensions of consumer adoption, mobile accessibility is positively associated with performance more than repayment mechanisms. Regression analysis demonstrated that consumer adoption and repayment mechanisms significantly predicted platform performance, accounting for 58.3% of its variance (Adjusted R² = 0.583). Repayment mechanisms emerged as the stronger predictor (Beta = 0.501), compared to consumer adoption (Beta = 0.311), indicating the critical role of structured repayment systems in sustaining platform growth. The study recommends integrating adaptive repayment tools tailored to local conditions and investing in digital literacy and customer support, along with further research using longitudinal and qualitative methods to explore platform performance dynamics.