Cogent Engineering (Dec 2024)

Critical factors that influence the effectiveness of facility maintenance management practice in public university buildings in Ethiopia: an exploratory factor analysis

  • Muluken Tilahun Desbalo,
  • Asregedew Kassa Woldesenbet,
  • Hans-Joachim Bargstädt,
  • Mitiku Damtie Yehualaw

DOI
https://doi.org/10.1080/23311916.2024.2307150
Journal volume & issue
Vol. 11, no. 1

Abstract

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AbstractFacility maintenance management (FMM) is essential for ensuring long-term values and to sustain project goals throughout the life cycle delivery process. However, in underdeveloped nations such as Ethiopia, facility maintenance management is an immature and underutilised process that requires a holistic intervention for practical improvement. The main aim of this study was to identify and prioritise critical factors that affect the effectiveness of FMM, with a focus on public universities in Ethiopia. Initially, a total of thirty-three (33) crucial variables were identified with a systematic literature review and desk study. To collect primary data, a survey research design approach was utilised using questionnaires and informant interviews. A total of seventy-five (75) data sets were obtained from 180 online surveys for conducting exploratory factor analysis (EFA). The outcome of the study revealed thirteen (13) critical attributes grouped into four factors that affect the effectiveness of facility maintenance management practises. The final four-factor model includes F1, internal processes and organisation; F2, community culture, learning, and growth; F3, impacts of design and construction quality; and F4, facility maintenance approach and management. This study indicated that facility maintenance management practises in public universities in Ethiopia are immature and require extensive enhancement. The identified influencing factors highlight the need for a comprehensive intervention to promote improved facility maintenance management practises and applications in Ethiopia. Further research is needed to analyse a wider range of attributes and data using confirmatory factor analysis.

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