BIM-supported knowledge management: Potentials and expectations

Hao Wang, Xianhai Meng*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)
165 Downloads (Pure)

Abstract

Building information modeling (BIM) is currently a prevalent term for a new way of managing the design, construction, operation, and maintenance (O&M) of a project. It is regarded as an accumulation of information about a building anchored to a model. Consequently, BIM has been widely applied to manage information in construction projects. On the other hand, knowledge integrates context, experience, rules, and capability, which is at a higher level than information. Knowledge has also been widely recognized as one of the most important factors in construction projects. Therefore, close attention should be paid to knowledge management (KM) in construction projects. Compared to traditional information technology (IT) systems, BIM is characterized by object-oriented and parameter-driven modeling. How these characteristics can improve KM is a matter that has not been fully explored. To bridge the knowledge gap, this study first explores the existing tools used for KM in construction projects. Following this, the potentials of BIM for the improvement of KM are identified and the expectations for BIM-supported KM are outlined. A total of 30 industrial experts in the UK and Ireland were interviewed as the main research method in this study. Based on the analysis of interview results, a conceptual model is developed for BIM-supported KM. The conceptual model presents the features of BIM, such as three-dimensional (3D) visualization, lifecycle management, collaborative environment, and proactive mechanism, which can improve various KM activities. This study not only reveals the role of BIM for KM, but also gives insights into an innovative way of managing knowledge in construction projects.
Original languageEnglish
Pages (from-to)04021032-1 - 04021032-13
JournalJournal of Management in Engineering
Volume37
Issue number4
Early online date22 Apr 2021
DOIs
Publication statusPublished - 01 Jul 2021

Keywords

  • General Engineering
  • Industrial relations
  • Management Science and Operations Research
  • Strategy and Management

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