Abstract
{ "background": "The operational efficiency of transport maintenance depots is critical for infrastructure sustainability, yet robust empirical methodologies for its measurement in developing contexts are lacking. Prevailing assessments often rely on cross-sectional data, failing to capture dynamic efficiency gains over time.", "purpose and objectives": "This study aims to methodologically evaluate the performance measurement of depot systems and to empirically estimate longitudinal efficiency gains using a panel-data framework. The objective is to quantify the impact of systematic interventions on depot productivity.", "methodology": "A panel dataset was constructed from operational records of multiple depots. Efficiency was modelled using a fixed-effects regression: $Y{it} = \\alphai + \\beta X{it} + \\delta Tt + \\epsilon{it}$, where $Y{it}$ is the output metric for depot $i$ in period $t$, $X{it}$ is a vector of inputs, and $Tt$ is a time trend. Robust standard errors were clustered at the depot level to account for heteroskedasticity and autocorrelation.", "findings": "The analysis identified a statistically significant positive time trend, indicating an average annual efficiency gain of 7.3% across the depots studied (95% CI: 5.1% to 9.5%). This gain was strongly associated with the phased implementation of standardised procurement and workshop scheduling systems.", "conclusion": "The application of panel-data methods provides a superior, dynamic assessment of depot efficiency compared to static analyses. The results confirm that structured operational interventions can yield substantial and measurable improvements in maintenance output over time.", "recommendations": "Depot managers and policymakers should adopt panel-data methodologies for performance monitoring. Investment should prioritise standardising procurement and workflow scheduling, as these drivers yielded the most significant efficiency returns.", "key words": "infrastructure maintenance, efficiency analysis, panel data, fixed effects, operational research, asset management", "contribution statement": "This paper provides a novel application of econometric panel-data estimation to engineering