A Difference-in-Differences Model for the Cost-Effectiveness Evaluation of Transport Maintenance Depot Systems in South Africa

{ "background": "The cost-effectiveness of transport maintenance depot systems is a critical concern for infrastructure asset management, yet robust quantitative evaluation methods tailored to the operational and data constraints of emerging economies are lacking.", "purpose and objectives": "This case study develops and applies a novel quasi-experimental econometric model to evaluate the causal impact of a centralised depot management system on maintenance expenditure, compared to a decentralised model.", "methodology": "A difference-in-differences (DiD) model is employed, using panel data from two comparable provincial road networks. The centralised system's implementation in one network serves as the treatment. The core model is $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\delta (\\text{Treat}i \\times \\text{Post}t) + \\epsilon_{it}$, where $\\delta$ captures the causal effect. Inference is based on cluster-robust standard errors.", "findings": "The analysis finds a statistically significant reduction in average monthly maintenance expenditure per vehicle of approximately 18% attributable to the centralised system. The DiD estimator, $\\delta = -0.198$, is significant at the 5% level (95% CI: -0.376, -0.020), indicating the intervention's cost-saving effect.", "conclusion": "The centralised depot system demonstrated a measurable, positive impact on cost-effectiveness within the studied context. The DiD model proved a viable methodological tool for infrastructure investment appraisal where randomised controlled trials are impractical.", "recommendations": "Transport authorities should consider adopting quasi-experimental evaluation frameworks for major system changes. Further research should apply the model to a wider set of depots and incorporate additional performance metrics, such as vehicle availability.", "key words": "infrastructure management, econometric evaluation, quasi-experimental design, asset maintenance, causal inference", "contribution statement": "This study provides the first