Time-Series Forecasting Model Evaluation of Transport Maintenance Depot Systems in South Africa,

This study focuses on evaluating the cost-effectiveness of transport maintenance depots in South Africa by applying time-series forecasting models. A hybrid ARIMA-GARCH model was employed to forecast future maintenance costs based on historical data from to . Robust standard errors were used to account for uncertainty in the forecasting process. The analysis revealed a significant upward trend in maintenance costs over the study period, with an estimated annual growth rate of 5% (95% CI: 4-6%). The hybrid ARIMA-GARCH model provided reliable cost forecasts for future planning and resource allocation. Based on the findings, it is recommended that maintenance depots implement proactive cost management strategies to mitigate potential financial risks. The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.