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Title: Schedule risks in prefabrication housing production in Hong Kong : a social network analysis
Authors: Li, CZD 
Hong, JK 
Xue, F 
Shen, GQ 
Xu, XX
Mok, MKY 
Keywords: Building information modeling
Prefabrication housing production
Schedule risk
Social network analysis
Issue Date: Oct-2016
Publisher: Elsevier
Source: Journal of cleaner production, 15 Oct. 2016, v. 134, pt. B, p. 482-494 How to cite?
Journal: Journal of cleaner production 
Abstract: Various schedule risks beset prefabrication housing production (PHP) in Hong Kong throughout the prefabrication supply chain, from design, manufacturing, logistics, to on-site assembly. Previous research on the risks in prefabrication construction projects has mainly focused on the construction stage and has been confined to issues of completeness and accuracy without consideration of stakeholder-related risks and their cause-and-effect relationships. However, in reality, the supply chain is inseparable as precast components should be manufactured and transported to sites to fit in with the schedule of on-site assembly in seamless connection manner, and most risks are interrelated and associated with various stakeholders. This study applies social network analysis (SNA) to recognize and investigate the underlying network of stakeholder-associated risk factors in prefabrication housing construction projects. Critical risks and relationships that have important roles in structuring the entire network of PHP are identified and analyzed. BIM (Building Information Modeling)-centered strategies are proposed to facilitate stakeholder communication and mitigate critical schedule risks and interactions underlying the risk network. This study not only provides an effective method to analyze stakeholder-associated risk factors and to evaluate the effect of these risk factors from a network perspective, but also offers a new visual perspective in the promotion of the use of the Internet of things (IoT) and helps identify housing construction problems in Hong Kong.
ISSN: 0959-6526
DOI: 10.1016/j.jclepro.2016.02.123
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