Toward an Efficient Construction Process: What Drives BIM Professionals to Collaborate in BIM-Enabled Projects

Kaiyang Wang, Cheng Zhang, Fangyu Guo*, Shuting Guo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

As one of the emerging digital technologies, building information modeling (BIM) has been increasingly used in the architecture, engineering, and construction (AEC) industry of many countries. One of the core benefits associated with BIM is facilitating collaboration among project teams, thereby improving information sharing and project performance by providing BIM-based construction networks (BbCNs). Nevertheless, it is still challenging to ensure an effective collaboration process in BIM-enabled projects. Several studies have investigated the factors that influence collaboration in BIM-enabled projects; however, most of these studies focus on technical matters of BIM, while the perspectives of socio-organization and processes have received less attention and are still in the conceptual stage, especially for the role of people management. Thus, an exploratory study was proposed to explore how key factors influence the professionals' willingness to collaborate in BIM-enabled projects. A total of 10 hypotheses were established based on literature review and expert verification. Following that, a questionnaire survey was administered in China to solicit the opinions of 273 BIM professionals for data collection. The hypotheses were then examined on the basis of the predictive capacity of regression analysis (binary logistic regression), with the findings validated using neural network analysis (multilayer perceptron). It was found that seven independent variables have a statistically significant influence on professionals' willingness to collaborate in BIM-enabled projects, namely, professional knowledge, skill, training, investment, BIM tools, BIM ownership, and standards and regulations. Among them, the variable of professional knowledge was ranked as the most influential factor. While extending the existing knowledge of literature, the findings of this study also deliver insights for stakeholders by enhancing their understanding of the BIM collaboration process and its influence factors.

Original languageEnglish
Article number04022033
JournalJournal of Management in Engineering
Volume38
Issue number4
DOIs
Publication statusPublished - Jul 2022

Keywords

  • Artificial neural network
  • Building information modeling (BIM)
  • Collaboration
  • Factors
  • Logistic regression

Fingerprint

Dive into the research topics of 'Toward an Efficient Construction Process: What Drives BIM Professionals to Collaborate in BIM-Enabled Projects'. Together they form a unique fingerprint.

Cite this