The study examines transport maintenance depots in Ethiopia to evaluate their cost-effectiveness. Bayesian hierarchical modelling is applied to analyse data from Ethiopian depots. The model accounts for variability between depots and incorporates prior knowledge about depot performance. A significant proportion (35%) of the variance in depot costs was explained by the model, indicating its effectiveness in predicting cost differences among depots. The Bayesian hierarchical model provides a robust framework to evaluate and improve the efficiency of transport maintenance depots in Ethiopia. Based on findings, it is recommended that Ethiopian transportation authorities implement targeted interventions in depots with high costs relative to their peers. Bayesian Hierarchical Model, Cost-effectiveness, Transport Maintenance Depots, Ethiopia The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Gebreab et al. (Sat,) studied this question.
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