A Hybrid Prioritization Model for Funding School Maintenance and Rehabilitation Projects Using Data Envelopment Analysis and Linear Programming Algorithms

Abstract

Public school buildings often require regular inspections and effective maintenance strategies to ensure their proper functional performance and safety. Because of budget constraints, school buildings always did not receive full attention to inspection and maintenance. This study aimed at developing a priority-rating model to evaluate the budget for maintenance and rehabilitation of school buildings. The model was developed based on data envelopment analysis (DEA) and linear programming (LP) techniques. A list of 35 school building elements was extracted from maintenance records. Five main factors affecting budget allocation for maintenance were identified. A total of 38 experts were selected to evaluate the relative importance of these five factors. A case study related to the rehabilitation of 20 schools was conducted to illustrate and verify the model. Results showed that some building components have more influence on the five factors than others. For example, wall exterior and sanitary waste strongly influence building user satisfaction. Merging DEA and LP overcame prioritization modeling issues by unifying factors with different units of measurement into a mathematical relationship and extracting weight ratios between these factors from the data instead of preselection. This study contributes to the body of knowledge by proposing a DEA-LP model to prioritize maintenance and funding allocation for school buildings. The findings from this study may be beneficial to practitioners by guiding adopting effective strategies to optimize school inspection activities and maintenance operations.