Rights statement: © Emerald Publishing Limited DOI 10.1108/JFM-08-2020-0055
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Integrating Building Information Modeling for Improving Facility Management Operations: A Fuzzy Synthetic Evaluation of the Critical Success Factors
AU - Oluleye, Ifeoluwa Benjamin
AU - Oyetunji, Abiodun Kolawole
AU - Olukolajo, Michael Ayodele
AU - Chan, Daniel W M
PY - 2023/3/27
Y1 - 2023/3/27
N2 - Purpose: Building information modelling (BIM) is a novel technological advancement in the built environment. Despite the potentials of BIM, its adoption and implementation are undermined in facility management (FM) operations. This might be because of limited information on the critical success factors (CSFs) that can enhance its adoption. The study aims to integrate building information modelling to improve facility management operation by adopting fuzzy synthetic approach for evaluating the critical success factors. Design/methodology/approach: Data for the study were sourced from practising and registered facility managers within Lagos metropolis, Nigeria. The data collected were analysed using a combination of methods which include mean item score, factor analysis and fuzzy synthetic evaluation (FSE). Findings: The factor analysis results showed that six underlying groups of CSFs would enhance the effective adoption of BIM in facility operations. The FSE results showed that out of the six groups, the three topmost important CSF grouping (CSFG) in the decision rule would enhance the effectiveness of BIM adoption for FM operations. Practical implications: The result of this study provides a credible road map for facility managers, policymakers and other stakeholders in FM operations on the CSFs and CSFG required for the adoption of BIM. Originality/value: Previous studies that aimed at integrating BIM into FM are limited. Hence, this study provides a broad perspective on the CSF required for BIM adoption and implementation in FM operations using the FSE approach.
AB - Purpose: Building information modelling (BIM) is a novel technological advancement in the built environment. Despite the potentials of BIM, its adoption and implementation are undermined in facility management (FM) operations. This might be because of limited information on the critical success factors (CSFs) that can enhance its adoption. The study aims to integrate building information modelling to improve facility management operation by adopting fuzzy synthetic approach for evaluating the critical success factors. Design/methodology/approach: Data for the study were sourced from practising and registered facility managers within Lagos metropolis, Nigeria. The data collected were analysed using a combination of methods which include mean item score, factor analysis and fuzzy synthetic evaluation (FSE). Findings: The factor analysis results showed that six underlying groups of CSFs would enhance the effective adoption of BIM in facility operations. The FSE results showed that out of the six groups, the three topmost important CSF grouping (CSFG) in the decision rule would enhance the effectiveness of BIM adoption for FM operations. Practical implications: The result of this study provides a credible road map for facility managers, policymakers and other stakeholders in FM operations on the CSFs and CSFG required for the adoption of BIM. Originality/value: Previous studies that aimed at integrating BIM into FM are limited. Hence, this study provides a broad perspective on the CSF required for BIM adoption and implementation in FM operations using the FSE approach.
KW - Building Information Modelling
KW - Implementation
KW - Success Factors
KW - Facility Management
KW - Operations
KW - Nigeria
KW - Critical success factors
U2 - 10.1108/JFM-06-2021-0066
DO - 10.1108/JFM-06-2021-0066
M3 - Journal article
VL - 21
SP - 201
EP - 220
JO - Journal of Facilities Management
JF - Journal of Facilities Management
SN - 1472-5967
IS - 2
ER -