Systematic review of critical drivers for delay risk prediction: towards a conceptual framework for BIM-based construction projects

Christian Egwim; Hafiz Alaka; Eren Demir; Habeeb Balogun; Saheed O. Ajayi

doi:10.1108/FEBE-05-2022-0017

Systematic review of critical drivers for delay risk prediction: towards a conceptual framework for BIM-based construction projects

Christian Egwim, Hafiz Alaka, Eren Demir, Habeeb Balogun, Saheed O. Ajayi

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Abstract

Purpose – 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.

Original language	English
Pages (from-to)	16-31
Number of pages	16
Journal	Frontiers in Engineering and Built Environment (FEBE)
Volume	3
Issue number	1
DOIs	https://doi.org/10.1108/FEBE-05-2022-0017
Publication status	Published - 13 Oct 2022

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© 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/
Final published version, 1.58 MBLicence: CC BY

Cite this

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title = "Systematic review of critical drivers for delay risk prediction: towards a conceptual framework for BIM-based construction projects",

abstract = "Purpose – 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{\textquoteright}s analyses further confirmed a positive effect of BIM on construction project delay.",

author = "Christian Egwim and Hafiz Alaka and Eren Demir and Habeeb Balogun and Ajayi, {Saheed O.}",

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AU - Ajayi, Saheed O.

N1 - © 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/

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N2 - Purpose – 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.

AB - Purpose – 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.

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Systematic review of critical drivers for delay risk prediction: towards a conceptual framework for BIM-based construction projects

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