Year: 2025
Type: article
Abstract: This study focuses on modelling the factors affecting NSSF building maintenance management practices in order to facilitate asset performance and financial sustainability. Through RII and multiple regression analysis, the study pinpointed the key determinants as being the choice of materials, water and waste management, monitoring of structural integrity, design for maintenance, energy system efficiency, quality of contractor, and age of building. The model that was built showed a strong correlation between these aspects and Return on Investment (ROI) with a high coefficient of determination (R² = 0.923). The results of validation indicated that the actual ROI (2.77%) and the predicted ROI (3.01%) were very close, and a very low Mean Absolute Percentage Error (MAPE = 0.17%) was given as evidence of great accuracy and reliability by the predictive framework. The results suggest that the commitment made to preventive and condition-based maintenance rather than the execution of only reactive strategies will lead to the enhancement of the building's durability, efficiency of operation, and financial returns over time. The suggested model is an excellent NSSF decision-support tool for maintenance planning based on evidence, resource allocation at the most efficient level, and maintenance of property value in the investment portfolio.
Authors: Benard Geofrey, Joseph Mkilania
Institution: Dar es Salaam Institute of Technology
Language: English
Topic: Life Cycle Costing Analysis
Subfield: Accounting
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4415217953
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