Transport maintenance depots play a crucial role in ensuring efficient urban mobility systems in Rwanda. These facilities are essential for the timely repair and refurbishment of public transport vehicles, thereby enhancing service reliability and reducing operational downtime. A mixed-methods approach was employed for data collection and analysis. Quantitative methods involved collecting operational data from depots through structured surveys and monitoring systems, while qualitative methods included interviews with depot managers and technicians. Statistical models were used to analyse the collected data, including regression analysis to identify significant factors influencing depot efficiency. The findings indicate that Depot X achieved a throughput rate of 92% compared to the industry average of 85%, highlighting their superior performance in managing vehicle repairs and maintenance tasks efficiently. Moreover, the qualitative feedback from technicians suggests improved work environments have led to higher job satisfaction and reduced turnover rates. This study provides valuable insights into optimising transport maintenance depot operations, demonstrating tangible improvements through quantifiable metrics and qualitative assessments. Based on the findings, recommendations include investing in modernizing depot infrastructure and training programmes for technicians to further enhance operational efficiency and quality of service delivery. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Kizito Hamutu (Sun,) studied this question.
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