
Transport maintenance depots play a critical role in ensuring the reliability of transport infrastructure in Uganda's road network. A multilevel regression model was employed to analyse data collected from multiple depots across different regions, accounting for both fixed effects (system-level variables) and random effects (local variations). The analysis revealed significant improvements in depot efficiency, with a mean efficiency gain of 15% across all depots after implementing the recommended interventions. This study underscores the importance of systematic improvements to optimise transport maintenance operations in Uganda's road infrastructure. Policy makers should prioritise investments and regulatory measures that support consistent performance monitoring and system updates within depot networks. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Geographic, Sub-Saharan, African, Systems, Depots, Evaluation, Multilevel, Districts, Regression
Geographic, Sub-Saharan, African, Systems, Depots, Evaluation, Multilevel, Districts, Regression
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
