The National Housing Corporation (NHC) in Tanzania faces significant challenges in efficiently allocating scarce maintenance resources across 167 buildings within the Arusha Region, leading to reactive maintenance decisions that reduce building availability and increase operational costs. This study developed a comprehensive maintenance prioritisation system to address optimal resource distribution and enhance building availability performance through evidence-based decision-making frameworks. The research employed a mixed-methods design utilising stratified random sampling of 118 buildings across four operational zones. Comprehensive data collection involved questionnaires, structured interviews, technical measurements, and detailed building condition assessments focusing on eight critical parameters: waterproofing, fire safety systems, HVAC systems, electrical systems, roof conditions, structural integrity, water supply, and windows and doors. Relative Importance Index (RII) analysis revealed waterproofing as the most significant factor (RII = 0.952), followed by fire safety systems (RII = 0.944) and HVAC systems (RII = 0.932). Multiple regression analysis generated a robust predictive model with exceptional statistical performance (R² = 0.980), indicating that the eight technical factors explain 98% of building availability performance variance. The resulting regression equation: Building Availability Performance = 0.010 + 0.020(Waterproofing) + 0.010(Fire Safety) - 0.020(HVAC) + 0.005(Electrical) + 0.040(Roof Condition) + 0.040(Structural Integrity) + 0.040(Water Supply) + 0.040(Windows & Doors) provides a quantitative framework for maintenance decision-making. The developed NHC Buildings Maintenance Prioritisation System (NHCMPS) represents a computerised application featuring building inventory management, inspection protocols, maintenance team coordination, and performance monitoring capabilities. System validation across four zones demonstrated effective priority differentiation with Buildings Prioritisation Index (BPI) scores ranging from 0.19 to 0.91, confirming the system's practical applicability. This research contributes a context-specific, resource-constraint-aware prioritisation framework that enables evidence-based maintenance decisions, facilitating the transition from reactive to proactive maintenance practices while enhancing building availability, extending asset life, and providing a replicable model for similar organisations in developing countries
Kuya et al. (Wed,) studied this question.