Modeling Dynamics of Project-Based Collaborative Networks for BIM Implementation in the Construction Industry: Empirical Study in Hong Kong
Publication: Journal of Construction Engineering and Management
Volume 145, Issue 12
Abstract
Using the method of stochastic actor-oriented models (SAOM) and longitudinal data on building information modeling (BIM)-based construction projects undertaken in Hong Kong during 2008–2017, this study empirically modeled how the industry-level network of project-based collaborative relationships for BIM implementation evolves over time and how this evolution is influenced by a set of micromechanisms. The results of descriptive network analysis revealed that the collaborative network became increasingly dense over time but was persistently characterized by a relatively short average path length among network nodes, a high clustering coefficient, and a core–periphery structure. The results of SAOM analysis further provide evidence that the evolution of the macronetwork structure significantly relates to the structure-based preferential attachment effect and the experience-based similarity effect operating at the microlevel. The results also suggest that the individual covariate effects related to organizational ownership type and organizational BIM experience significantly influence the dynamics of the project-based collaborative network. This study not only provides a network view of how industry organizations interact with each other in BIM implementation practices across projects, but also contributes to a deepened understanding of how the networks of project-based collaborative relationships evolve as complex adaptive systems whose dynamics are driven by a set of structure- and attribute-based effects operating at the microlevel.
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Data Availability Statement
Data generated or analyzed during the study are available from the corresponding author by request.
Acknowledgments
This research has been financially supported by the Public Policy Research Funding Scheme from the Hong Kong Special Administrative Region Government (Grant No. 2016.A6.075.17A), the National Natural Science Foundation of China (Grant No. 71802150), the Fundamental Research Funds for the Central Universities (Grant No. 22120180008) and the Shanghai Pujiang Program (Grant No. 18PJC110).
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Journal of Construction Engineering and Management
Volume 145 • Issue 12 • December 2019
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©2019 American Society of Civil Engineers.
History
Received: Nov 3, 2018
Accepted: Apr 24, 2019
Published online: Oct 9, 2019
Published in print: Dec 1, 2019
Discussion open until: Mar 9, 2020
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