Multilevel Regression Analysis for Evaluating Yield Improvement in Transport Maintenance Depots in Kenya: A Policy Perspective

This study examines transport maintenance depots in Kenya to evaluate yield improvement through a multilevel regression analysis approach. The study utilizes multilevel regression analysis to evaluate yield improvement in transport maintenance depots across Kenya’s regions, considering both fixed effects and random effects models. Findings indicate a significant positive correlation (β = 0.53, p < 0.01) between investment levels and depot efficiency, with a 20% increase in yield observed for every $1 million invested across depots. The multilevel regression analysis highlights the importance of resource allocation and maintenance strategies to enhance transport infrastructure performance. Policy recommendations include increased funding for maintenance depots, targeted training programmes for technicians, and improved supply chain management to maximise yield improvements. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.