Development of Maintenance Fund Allocation Prioritisation Model for District Road: A Case of Makete District – Njombe Region (TARURA)

Road infrastructure is critical for socio-economic development in rural Tanzania, yet the Tanzania Rural and Urban Roads Agency (TARURA) faces severe funding constraints, with annual budgets covering only 30% of required maintenance needs. In Makete District, TARURA manages 700km of district roads with funding of 1.2-2.8 billion Tanzanian Shillings, far below the 5.5 billion required for optimal maintenance. The current allocation system lacks systematic prioritisation, relying on subjective decisions that fail to optimise limited resources in this challenging mountainous terrain. This study developed a maintenance fund allocation prioritisation model for district roads in Makete District. Using a mixed-methods approach, data were collected from 80 stakeholders through structured questionnaires and field observations. Relative Importance Index (RII) analysis identified seven critical factors: Traffic Volume (0.913), Road Physical Condition (0.905), Connectivity to Essential Services (0.905), Maintenance Cost-Effectiveness (0.903), Geographical Challenges (0.903), Economic Importance (0.900), and Rainfall and Drainage Requirements (0.898). A multiple linear regression model was developed with strong statistical validity (R² = 0.782, p < 0.001): Y = 0.11 + 0.12(RC) + 0.21(TV) + 0.12(CES) + 0.13(MCE) + 0.14(GC) + 0.24(EI) + 0.13(RDR). Model validation across six road segments demonstrated consistent, rational prioritisation rankings aligned with infrastructure needs. The study successfully transformed subjective maintenance fund allocation into an objective, data-driven process that balances technical, economic, social, and environmental considerations. This research provides TARURA with a practical decision-support tool for efficient resource allocation and offers a methodology adaptable to other rural districts facing similar infrastructure management challenges