Development of Cost Minimisation Model for Improvement of Road Maintenance Management

This study aimed to develop a maintenance cost minimisation model for the improvement of road maintenance management under TARURA in Songea District, Tanzania. Recognising road maintenance as a cornerstone of socio-economic development in urbanising regions, the research identifies key cost drivers and proposes a data-driven framework for financial sustainability and operational improvement. A quantitative approach was employed, using structured questionnaires administered to 82 respondents from TARURA and civil contracting firms. Descriptive statistics and the Relative Importance Index (RII) ranked critical cost factors, while multiple linear regression analysis was used to construct and validate the model. Five major cost determinants were identified: project management, resource availability, material usage, institutional frameworks, and environmental conditions—with project management emerging as the most influential. The model demonstrated strong explanatory power (R² = 0.766) and high predictive accuracy (97.83%), further optimised through a linear programming objective function. The study recommends structured project management, technological investment, institutional strengthening, and local sourcing strategies to reduce maintenance costs. These findings offer an actionable roadmap for policy reform and operational planning in road infrastructure management