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Barriers and Risks in BIM-Embedded Design Collaboration: A Two-Mode Social Network Analysis Read chapter Read first chapter

2022 | OriginalPaper | Chapter

BBN-Based Approach for Identifying the Governance Factors of Megaprojects

Authors : Lan Luo, Fenghao Gu, Yue Yang, Qiushi Bo

Published in: Proceedings of the 26th International Symposium on Advancement of Construction Management and Real Estate

Publisher: Springer Nature Singapore

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Abstract

The governance factors explored in previous studies are static, sticking to fixed scenes and factors. In the context of the increasingly complex environment of contemporary megaprojects, the results of static research show inadaptability, failing to accurately grasp the key factors of governance. This research proposes an approach to identify the factors affecting the governance of megaprojects in China based on the Bayesian belief network (BBN). Firstly, the governance factors of megaprojects are determined based on the literature review including a total of 33 factors. Secondly, the BBN-based model of megaprojects is constructed in line with 235 samples effectively collected. Finally, further analysis is conducted on the basis of the obtained model, including predictive, diagnostic, sensitivity, and influence chain analysis. The results indicate that cultural development and government decisions should be placed with more attention in the practices of megaprojects. The research contributes to (a) the state of knowledge by exploring the dynamic causal relationship of influencing factors and (b) the state of practice by proposing a megaprojects governance model by combining machine learning and expert advice.

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Metadata
Title
BBN-Based Approach for Identifying the Governance Factors of Megaprojects
Authors
Lan Luo
Fenghao Gu
Yue Yang
Qiushi Bo
Copyright Year
2022
Publisher
Springer Nature Singapore
Book
Proceedings of the 26th International Symposium on Advancement of Construction Management and Real Estate

Print ISBN: 978-981-19-5255-5

Electronic ISBN: 978-981-19-5256-2

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-981-19-5256-2_60