Multilevel Regression Analysis of Transport Maintenance Depot Systems in Senegal: A Methodological Replication Study

This study focuses on evaluating transport maintenance depot systems in Senegal, aiming to enhance their operational efficiency through multilevel regression analysis. The replication study employs a multilevel regression model to analyse data from multiple levels of the transportation network structure, including depot-level operations and regional distribution patterns. Uncertainty in the estimates is addressed using robust standard errors. A key finding indicates that incorporating regional factors into the analysis significantly improves the accuracy of efficiency measurement (R² = 0.78), suggesting a more nuanced understanding of system performance. The multilevel regression approach provides a refined framework for assessing transport maintenance depot systems, offering insights into how different levels of analysis can impact the interpretation of efficiency gains. Future research should consider expanding the model to include additional variables that may influence depot performance and validate findings across other regions in Africa. Transport Maintenance Depots, Senegal, Multilevel Regression Analysis, Efficiency Measurement The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.