This study aims to evaluate transport maintenance depots in Senegal, focusing on their efficiency and potential for improvement. A Bayesian hierarchical model will be used to analyse data from multiple depots, incorporating spatial and temporal variability to estimate yield improvements with uncertainty quantification. The analysis revealed significant variation in maintenance efficiency across different depots, indicating the need for targeted interventions. The application of a Bayesian hierarchical model offers a robust framework for evaluating transport maintenance systems, enhancing their operational performance. Deploying tailored improvement strategies based on regional and depot-specific data could lead to substantial yield improvements in Senegalese depots. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Ndiaye et al. (Sun,) studied this question.