Abstract:
he efficiency and sustainability of national road infrastructure depend heavily on the
effectiveness of Road Asset Management (RAM) systems. In developing countries like Ethiopia,
the performance of road maintenance remains constrained by limited resources, insufficient
technological integration, and variable staff competence. This study aimed to investigate the direct
and indirect effects of RAM on Road Maintenance Performance (RMP) in the Jimma Road
Maintenance District of the Ethiopian Roads Administration (ERA), with Resource Allocation
(RA), Technological Integration (TI), and Staff Competence (SC) serving as mediating variables.
A quantitative, cross-sectional explanatory design was employed, and data were collected from
255 professionals engaged in road maintenance and asset management through a structured
questionnaire. Partial Least Squares Structural Equation Modeling (PLS-SEM), implemented in
R and ADANCO software, was used to analyze the relationships among constructs and test the
mediation hypotheses. The findings revealed that RAM has a significant positive direct effect on
RMP, confirming that structured asset management practices enhance road maintenance
performance. RAM also significantly influenced RA, and SC. Among the mediators, exhibited
significant mediating effects, whereas SC did not. The model explained more than half of the
variance in RMP, indicating strong explanatory power. The study concludes that road
maintenance performance is primarily driven by institutional factors—effective asset
management, optimal resource allocation, and technology adoption—rather than individual
competence alone. It recommends strengthening integrated RAM systems, digitalizing
maintenance operations, and ensuring strategic resource distribution to achieve sustainable road
infrastructure outcomes in Ethiopia
