Browsing by Author "Jumba John"

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    Financial Literacy, Loan Terms and Loan Repayment in Uganda: A Case of Smallholder Farmers in Gulu.
    (Makerere University Business School, 2025-12-05) Jumba John
    This study investigated the relationship between financial literacy, loan terms, and loan repayment among smallholder farmers. Specifically, the study was guided by the following objectives: to examine the relationship between financial literacy and loan repayment; to examine the relationship between loan terms on loan repayment; and to determine the combined effect of financial literacy and loan terms on loan repayment behavior. A cross-sectional research design was adopted, and data was collected using a structured questionnaire administered to smallholder farmers. A total of 278 questionnaires were received, yielding a response rate of 72.3%. Data analysis was conducted using the Statistical Package for Social Sciences (SPSS). The reliability of the instrument was confirmed with Cronbach's Alpha values exceeding 0.6, thus validating the use of correlation and regression analyses. Correlation results revealed a weak and statistically non-significant relationship between financial literacy and loan repayment, although financial knowledge a subcomponent showed a moderate and significant correlation. In contrast, loan terms demonstrated a moderate and statistically significant relationship with loan repayment, with collateral requirements, interest rate, and repayment period all contributing significantly. Regression analysis indicated that financial literacy and loan terms jointly accounted for 14.7% of the variation in loan repayment (R² = 0.147), with loan terms emerging as the strongest predictor. The study concludes that loan repayment is more strongly influenced by the structure and fairness of loan terms than by financial literacy alone. Limitations included the use of a cross-sectional design and a structured questionnaire, which restricted deeper exploration of individual experiences. The study recommends future research employing a longitudinal design to capture the dynamic influence of these variables over time.