Zafar, M. B. and Mehmood, U. (2026) Understanding maintenance cost drivers in higher education: A multi-model econometric study. Built Environment Project and Asset Management, 16(3), pp. 520-541. ISSN 2044-124X
Abstract
Purpose – This study aims to identify and quantify the principal determinants of maintenance costs in higher education buildings using a multi-model econometric approach. It integrates operational, structural and climatic variables to provide generalizable insights for cost-effective and climate-responsive facility management (FM) across institutions. Design/methodology/approach – The analysis draws on 1.9 million maintenance work orders from 25 North American universities (2002–2021). A combination of mixed-effects modeling, quantile regression and panel data analysis is employed to examine how institutional, operational and environmental factors jointly influence maintenance expenditure. This multi-method econometric framework captures cost heterogeneity, handles nested data structures and distinguishes between cross-sectional and longitudinal effects. Findings – Planned Preventive Maintenance significantly reduces costs by up to 57% in high-expenditure cases (75th percentile) compared with unplanned maintenance. Labor remains the largest cost driver, while better building conditions consistently lower expenses. Climatic variables show mixed impacts: precipitation amplifies costs during prolonged maintenance tasks, whereas temperature variability, humidity and wind chill often exert weak or negative effects. Originality/value – The study extends the existing literature by applying a comprehensive econometric framework to a large, multi-institutional dataset, one of the most extensive of its kind in the higher education sector. By bridging quantitative modeling with FM practice, it offers empirical evidence to support predictive budgeting, resource optimization and climate-adaptive maintenance planning.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | facility management; higher education; maintenance cost; maintenance management; planned maintenance; preventive maintenance |
| Index terms: | precipitation, preventive maintenance, determinant, resource optimization, methodology, maintenance management, data structure, evidence, environmental factor, higher education, dataset, variability, humidity, modelling, budgeting, building condition, maintenance cost, data analysis, econometric |
| Subjects: | economic analysis, financial management, data management, asset management, educational institutions, control systems, maintenance engineering, research methods, environmental science, analytical methods, statistical analysis, data analysis and analytics, data science, climate science, risk assessment, evaluation and assessment methods |
| Topics: | Digital Applications, Sustainability, Engineering Principles, Risk Management, Research Practice, Business Strategy, Education, Project Management |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here