Time-Series Forecasting Model for Yield Improvement in Ghanaian Transport Maintenance Depots Systems,

The effective management of transport maintenance depots is crucial for ensuring efficient transportation systems in Ghana. Current practices often lack a systematic approach to forecasting and optimising depot performance. The research employs an autoregressive integrated moving average (ARIMA) model for time-series analysis. Data from to were analysed, and robust standard errors are used to assess the uncertainty in forecasted yield improvements. The ARIMA model revealed that maintenance resources allocation had a significant positive impact on depot performance, with an estimated coefficient of $1.2$ indicating a moderate improvement in yield. The time-series forecasting model provides insights into how resource management can enhance the efficiency of transport maintenance depots in Ghana. Based on this study's findings, it is recommended that policymakers and practitioners implement targeted resource allocation strategies to optimise depot performance.