"background": "Transport infrastructure maintenance in sub-Saharan Africa is often hampered by inefficient depot systems, leading to unreliable service and accelerated asset degradation. Current policy evaluations typically rely on observational data, which lack the rigour to establish causal effects of systemic interventions on operational reliability. ", "purpose and objectives": "This policy analysis evaluates a novel methodological approach for diagnosing reliability in transport maintenance depots. Its primary objective is to assess the efficacy of a randomised field trial (RFT) in generating robust, causal evidence to inform maintenance policy. ", "methodology": "A stratified randomised field trial was implemented across a network of regional depots. Depots were randomly assigned to a diagnostic intervention featuring structured reliability-centred maintenance protocols or to a control group continuing standard practice. System reliability was measured via mean time between failures (MTBF) for a fleet of heavy goods vehicles. The impact was estimated using a difference-in-differences model: Y{it = \0 + \1 (Treatmenti \ Postt) + \ + \ +, where robust standard errors were clustered at the depot level. ", "findings": "The intervention group exhibited a statistically significant increase in MTBF. Point estimates indicate a 22% improvement in reliability metrics compared to the control group (95% CI: 15% to 29%). The trial also revealed that procedural standardisation was the most frequently cited mechanism for this improvement by depot managers. ", "conclusion": "Randomised field trials are a viable and powerful tool for engineering policy analysis in infrastructure maintenance contexts, providing high-quality evidence for causal inference. ", "recommendations": "National transport authorities should integrate randomised pilot studies into the policy formulation cycle for maintenance system upgrades. Funding should be allocated to build local capacity in experimental design and causal analysis for infrastructure management. ", "key words": "randomised field trial, maintenance policy, reliability engineering, causal inference, infrastructure management", "contribution statement": "This article provides the first application of a randomised
Okello et al. (Mon,) studied this question.
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