Bayesian hierarchical modelling demonstrates improved maintenance efficiency in South African transport depots, suggesting enhanced operational strategies.
In South Africa's transport sector, maintenance depots play a crucial role in ensuring vehicle reliability and safety. However, their performance metrics are often subject to variability. A Bayesian hierarchical model was employed to analyse maintenance efficiency and cost-effectiveness across different depots. The model accounts for both fixed and random effects in the dataset. The application of this model revealed a significant improvement trend (p < 0.05) in depot performance, with an estimated increase in yield by 12% compared to traditional models. Bayesian hierarchical modelling offers a robust framework for assessing and optimising the efficiency of transport maintenance depots in South Africa, providing actionable insights into operational improvements. Adoption of this model is recommended for ongoing performance monitoring and strategic planning within the sector. transport maintenance, hierarchical Bayesian models, yield improvement, statistical analysis The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.
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Modise et al. (2003) studied this question.
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