Staff View: Intelligent risk management in construction projects: Systematic literature review

Intelligent risk management in construction projects: Systematic literature review

As digitalization leads to the development of the global economy and artificial intelligence stimulates technological innovation, integrating smart management methods into project management is becoming more and more critical to the development of the construction industry. As an influential branch...

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Main Authors:	Chenya, Liao, Aminudin, Eeydzah, Mohd., Suzila, Yap, Loh Seng
Format:	Article
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:	TH Building construction
Online Access:	http://eprints.utm.my/104415/1/EeydzahAminudin2022_IntelligentRiskManagementinConstructionProjects.pdf http://eprints.utm.my/104415/ http://dx.doi.org/10.1109/ACCESS.2022.3189157
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spelling	my.utm.1044152024-02-04T09:55:53Z http://eprints.utm.my/104415/ Intelligent risk management in construction projects: Systematic literature review Chenya, Liao Aminudin, Eeydzah Mohd., Suzila Yap, Loh Seng TH Building construction As digitalization leads to the development of the global economy and artificial intelligence stimulates technological innovation, integrating smart management methods into project management is becoming more and more critical to the development of the construction industry. As an influential branch of engineering management, intelligent risk management in the construction field will be a future research direction. Hence, the aim of this study is to find the gaps and future research trends in intelligent risk management field by Systematic Literature Review. In order to achieve these objectives, 436 articles were selected from the WOS and Scopus databases to be analyzed by CiteSpace scientometric software, and the results were classified into collaborative network analysis, co-citation analysis, and public network analysis. From the analysis, China had the highest number of publications, while the United States was the most influential country in this field. The researchers at different institutions in this field have formed research teams despite the lack of collaboration between the authors and their institutions. In co-cited references, the emphasis was on traditional methods and applications of risk analysis, with fewer citations of novel methods. According to the keywords, the clusters of keywords, and the temporal evolution of the keywords, and combining the conceptual model, 5 research gaps areas were discovered. In order to fulfill these challenges and barriers, this study found the future research trends, including: developing digital management platform for intelligent construction management and risk management, building a decision-making system for risk management to find an optimum solution, refining building digital models which would be the basis of digital management platform, identifying and category the characteristic construction risk factors by using machine learning techniques, just like text mining or knowledge graph, building an API to embed decision making system into digital management platform, and the intelligent risk management system in real-time projects to verify its possibility. Institute of Electrical and Electronics Engineers Inc. 2022 Article PeerReviewed application/pdf en http://eprints.utm.my/104415/1/EeydzahAminudin2022_IntelligentRiskManagementinConstructionProjects.pdf Chenya, Liao and Aminudin, Eeydzah and Mohd., Suzila and Yap, Loh Seng (2022) Intelligent risk management in construction projects: Systematic literature review. IEEE Access, 10 (NA). pp. 72936-72954. ISSN 2169-3536 http://dx.doi.org/10.1109/ACCESS.2022.3189157 DOI : 10.1109/ACCESS.2022.3189157
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	TH Building construction
spellingShingle	TH Building construction Chenya, Liao Aminudin, Eeydzah Mohd., Suzila Yap, Loh Seng Intelligent risk management in construction projects: Systematic literature review
description	As digitalization leads to the development of the global economy and artificial intelligence stimulates technological innovation, integrating smart management methods into project management is becoming more and more critical to the development of the construction industry. As an influential branch of engineering management, intelligent risk management in the construction field will be a future research direction. Hence, the aim of this study is to find the gaps and future research trends in intelligent risk management field by Systematic Literature Review. In order to achieve these objectives, 436 articles were selected from the WOS and Scopus databases to be analyzed by CiteSpace scientometric software, and the results were classified into collaborative network analysis, co-citation analysis, and public network analysis. From the analysis, China had the highest number of publications, while the United States was the most influential country in this field. The researchers at different institutions in this field have formed research teams despite the lack of collaboration between the authors and their institutions. In co-cited references, the emphasis was on traditional methods and applications of risk analysis, with fewer citations of novel methods. According to the keywords, the clusters of keywords, and the temporal evolution of the keywords, and combining the conceptual model, 5 research gaps areas were discovered. In order to fulfill these challenges and barriers, this study found the future research trends, including: developing digital management platform for intelligent construction management and risk management, building a decision-making system for risk management to find an optimum solution, refining building digital models which would be the basis of digital management platform, identifying and category the characteristic construction risk factors by using machine learning techniques, just like text mining or knowledge graph, building an API to embed decision making system into digital management platform, and the intelligent risk management system in real-time projects to verify its possibility.
format	Article
author	Chenya, Liao Aminudin, Eeydzah Mohd., Suzila Yap, Loh Seng
author_facet	Chenya, Liao Aminudin, Eeydzah Mohd., Suzila Yap, Loh Seng
author_sort	Chenya, Liao
title	Intelligent risk management in construction projects: Systematic literature review
title_short	Intelligent risk management in construction projects: Systematic literature review
title_full	Intelligent risk management in construction projects: Systematic literature review
title_fullStr	Intelligent risk management in construction projects: Systematic literature review
title_full_unstemmed	Intelligent risk management in construction projects: Systematic literature review
title_sort	intelligent risk management in construction projects: systematic literature review
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2022
url	http://eprints.utm.my/104415/1/EeydzahAminudin2022_IntelligentRiskManagementinConstructionProjects.pdf http://eprints.utm.my/104415/ http://dx.doi.org/10.1109/ACCESS.2022.3189157
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score	13.211869

Intelligent risk management in construction projects: Systematic literature review

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