Effect of business finance model on performance of small and medium enterprises (SMEs): A study of selected SMEs in Bungoma municipality, Kenya

Resumo

This study examined the effect of business finance models on the performance of small and medium enterprises (SMEs) in Bungoma Municipality, Kenya, with specific attention to the influence of traditional bank financing, digital/mobile lending platforms, microfinance institutions, and informal finance models on SME performance metrics. The study drew on the pecking order theory and financial intermediation theory. A descriptive cross-sectional design was adopted. The target population comprised 2,450 registered SMEs across six strata in Bungoma Municipality. A sample of 331 SME owner/managers was drawn using stratified random sampling, ensuring proportional representation. Structured questionnaires were the primary data collection instrument, with reliability confirmed (Cronbach's α = 0.87). Descriptive statistics, Pearson correlation, and multiple regression analysis were applied using SPSS version 29. Digital/mobile lending platforms were the most utilised finance model (68.3%), followed by microfinance institutions (45.2%), informal finance (42.1%), and traditional bank financing (28.4%). Digital lending showed the strongest positive correlation with composite SME performance (r = 0.62, p < 0.001), particularly sales growth (r = 0.58) and business expansion (r = 0.54). The regression model explained 47% of variance in SME performance (R² = 0.47, F = 28.6, p < 0.001), with digital lending (β = 0.34, p < 0.001) and microfinance (β = 0.28, p < 0.01) the strongest predictors. Traditional bank financing's most distinctive contribution was its correlation with asset acquisition (r = 0.51), reflecting the longer loan tenors and larger loan sizes that banks offer. SMEs utilising multiple financing models simultaneously outperformed single-model users across all performance dimensions. High interest rates on digital loans (71.3%), stringent collateral requirements (58.7%), and limited financial literacy (52.4%) were the most frequently cited challenges. Qualitative findings further documented aggressive debt-recovery practices by digital lenders, including unsolicited contact with borrowers' social networks, reported as widespread despite regulatory prohibition. The study concludes that digital lending has become the structural backbone of SME financing in Bungoma Municipality, not because it is optimal, but because collateral requirements exclude the majority of SMEs from formal bank financing. Its dominance is a symptom of a financing gap rather than evidence of an efficient market outcome. Microfinance institutions represent a comparatively underutilised but high-impact intermediary, particularly for firms in the small enterprise band. The superior absolute performance of bank financing users reflects selection bias rather than product quality, since banks approve credit primarily for already-established firms. The multi-model utilisation pattern among 42.3% of respondents confirms that combining complementary financing instruments produces superior outcomes to dependence on any single model. The study recommends that the Bungoma County Government establish a Business Finance Information Hub providing SME owners with transparent, regularly updated comparisons of all finance models operating in the county.