"background": "Transport maintenance depots are critical infrastructure for road safety and economic productivity. In many developing nations, systematic risk assessment within these facilities is often ad hoc, lacking robust quantitative frameworks to guide safety investments and procedural improvements. ", "purpose and objectives": "This paper aims to develop and apply a panel-data econometric model to quantify the impact of specific operational interventions on risk reduction within transport maintenance depots. The objective is to provide a methodological framework for evidence-based decision-making in depot safety management. ", "methodology": "A longitudinal dataset was constructed from repeated observational audits and incident records across multiple depots. The core analysis employs a fixed-effects panel model: Risk{it = \0 + \1 Interventionit + \ + \ +, where \ and \ₜ control for depot-specific and time-specific unobservables. Inference is based on cluster-robust standard errors. ", "findings": "The implementation of structured tool-accountability procedures was associated with a statistically significant 18. 5% reduction in recorded minor incident rates (95% CI: 12. 2% to 24. 8%). Conversely, the effect of targeted staff training programmes on major incident frequency was not statistically distinguishable from zero at conventional levels. ", "conclusion": "The panel-data approach provides a rigorous method for isolating the causal effect of safety interventions from time-invariant depot heterogeneity. The results demonstrate that procedural controls can yield substantial risk reductions, whereas isolated training may be insufficient without complementary systemic changes. ", "recommendations": "Depot managers should prioritise the implementation and auditing of strict procedural controls, such as tool-accountability systems. Future risk-reduction programmes should be designed to facilitate panel-data evaluation, ensuring consistent metric collection before and after interventions. ", "key words": "infrastructure safety, panel data analysis, maintenance engineering, risk quantification, fixed-effects model", "contribution statement": "This paper presents a novel application
Asante et al. (Fri,) studied this question.