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dc.contributor.authorEgwim, Christian
dc.contributor.authorAlaka, Hafiz
dc.contributor.authorDemir, Eren
dc.contributor.authorBalogun, Habeeb
dc.contributor.authorAjayi, Saheed O.
dc.date.accessioned2023-09-18T12:00:02Z
dc.date.available2023-09-18T12:00:02Z
dc.date.issued2022-10-13
dc.identifier.citationEgwim , C , Alaka , H , Demir , E , Balogun , H & Ajayi , S O 2022 , ' Systematic review of critical drivers for delay risk prediction: towards a conceptual framework for BIM-based construction projects ' , Frontiers in Engineering and Built Environment (FEBE) , vol. 3 , no. 1 , pp. 16-31 . https://doi.org/10.1108/FEBE-05-2022-0017
dc.identifier.issn2634-2502
dc.identifier.otherBibtex: egwim2022systematic
dc.identifier.otherBibtex: egwim2022systematic
dc.identifier.otherORCID: /0000-0003-2965-8749/work/166985575
dc.identifier.urihttp://hdl.handle.net/2299/26681
dc.description© 2022 The Author(s). Published by Emerald Publishing Limited. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/
dc.description.abstractPurpose – This study aims to develop a comprehensive conceptual framework that serves as a foundation for identifying most critical delay risk drivers for Building Information Modeling (BIM)-based construction projects. Design/methodology/approach – A systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to identify key delay risk drivers in BIM-based construction projects that have significant impact on the performance of delay risk predictive modelling techniques. Findings – The results show that contractor related driver and external related driver are the most important delay driver categories to be considered when developing delay risk predictive models for BIM-based construction projects. Originality/value – This study contributes to the body of knowledge by filling the gap in lack of a conceptual framework for selecting key delay risk drivers for BIM-based construction projects, which has hampered scientific progress toward development of extremely effective delay risk predictive models for BIM-based construction projects. Furthermore, this study’s analyses further confirmed a positive effect of BIM on construction project delay.en
dc.format.extent16
dc.format.extent1658105
dc.language.isoeng
dc.relation.ispartofFrontiers in Engineering and Built Environment (FEBE)
dc.titleSystematic review of critical drivers for delay risk prediction: towards a conceptual framework for BIM-based construction projectsen
dc.contributor.institutionHertfordshire Business School
dc.contributor.institutionCentre for Climate Change Research (C3R)
dc.contributor.institutionCentre for Future Societies Research
dc.contributor.institutionStatistical Services Consulting Unit
dc.description.statusPeer reviewed
rioxxterms.versionofrecord10.1108/FEBE-05-2022-0017
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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