Journal Design Engineering Masthead
African Civil Engineering Journal | 16 August 2006

A Comparative Methodological Evaluation of Transport Depot Maintenance Systems in Ethiopia

A Difference-in-Differences Analysis of Adoption Rates (2000–2026)
A, b, e, b, e, H, a, i, l, u, ,, T, e, w, o, d, r, o, s, A, s, s, e, f, a, ,, S, e, l, a, m, a, w, i, t, T, e, s, f, a, y, e, ,, M, e, k, l, i, t, G, e, b, r, e, m, e, d, h, i, n
Infrastructure ManagementDifference-in-DifferencesAdoption RatesDecentralised Systems
Decentralised systems show 18-percentage-point higher adoption than centralised models.
Difference-in-differences provides rigorous causal inference in non-experimental settings.
Enhanced local resource utilisation emerges as a key driver of adoption success.
Findings support policy shifts toward decentralised maintenance frameworks.

Abstract

{ "background": "Transport depot maintenance systems are critical for infrastructure longevity and operational efficiency in developing economies. However, robust methodological frameworks for evaluating the adoption and impact of different maintenance regimes are lacking in the literature, particularly in sub-Saharan contexts.", "purpose and objectives": "This study provides a methodological evaluation of competing maintenance systems. Its primary objective is to apply a quasi-experimental difference-in-differences (DiD) model to quantify and compare the adoption rates of centralised versus decentralised maintenance frameworks.", "methodology": "A comparative longitudinal analysis was conducted using panel data from a national sample of transport depots. The core econometric model is specified as $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\delta (\\text{Treat}i \\cdot \\text{Post}t) + \\epsilon_{it}$, where $\\delta$ is the DiD estimator for adoption. Inference is based on cluster-robust standard errors at the depot level.", "findings": "The analysis indicates a statistically significant positive effect of the decentralised system on adoption rates. The DiD coefficient ($\\delta$) was 0.18 (95% CI: 0.12, 0.24), suggesting an 18-percentage-point increase in adoption probability attributable to the decentralised model. Key themes from supplementary analysis highlighted enhanced local resource utilisation as a driver.", "conclusion": "The decentralised maintenance system demonstrates a substantially higher rate of adoption compared to the centralised model. The DiD approach proved a rigorous method for isolating the causal effect of system type in a non-experimental setting.", "recommendations": "Policy should prioritise decentralised maintenance frameworks, supported by targeted capacity-building at local depot level. Future engineering management research should employ quasi-experimental designs like DiD for more credible impact evaluation.", "key words": "infrastructure management, maintenance systems, difference-in-differences, adoption