Modeling and Likelihood Prediction of Prefabrication Feasibility for Electrical Construction Firms
Publication: Journal of Construction Engineering and Management
Volume 142, Issue 2
Abstract
Electrical contracting firms have consistently pursued industrializing their business through the implementation of prefabrication, lean production, and supply chain integration. Despite the pioneering prefabrication efforts of electrical contractors, there is still no clear understanding of the determinants of electrical prefabrication feasibility in terms of supply chain collaboration and surrounding industry requirements. Accordingly, this paper presents the development of prediction models of prefabrication feasibility for electrical contractors. The research tasks of this study were performed in three main phases. The first phase included various data collection tasks, including conducting semistructured interviews, providing an online questionnaire, and obtaining relevant local economic data of the respondents’ metropolitan areas. The second phase involved the utilization of the collected questionnaire responses and economic data to develop logistic regression models that relate the prefabrication feasibility to its statistically significant determinants. The third phase involved validating the developed models by assessing their prediction accuracy and performing extensive sensitivity analysis of their determinants. The findings of this study should prove useful to electrical contractors who need to obtain data-driven assessment of prefabrication feasibility considering their business attributes and surrounding industry parameters. This study presents the two main contributions to the study field of construction prefabrication. First, prefabrication feasibility was found to be significantly dependent on four industry-related determinants: regional economic growth, industry competition, labor cost rate, and worker union resistance. Second, prefabrication feasibility was found to be significantly dependent on two main internal firm-related determinants: building information modeling capability and supply coordination with vendors.
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Published In
Journal of Construction Engineering and Management
Volume 142 • Issue 2 • February 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Feb 11, 2015
Accepted: Jun 29, 2015
Published online: Aug 31, 2015
Discussion open until: Jan 31, 2016
Published in print: Feb 1, 2016
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