ITcon Vol. 24, pg. 273-298, http://www.itcon.org/2019/15

Analyzing BIM topics and clusters through ten years of scientific publications

submitted:August 2018
revised:February 2019
published:June 2019
editor(s):Turk Ž.
authors:Clément Lemaire
ETS Montréal, Canada

Louis Rivest
ETS Montréal, Canada
E-mail: louis.rivest@etsmtl.ca

Conrad Boton
ETS Montréal, Canada
E-mail: conrad.boton@etsmtl.ca

Christophe Danjou
Polytechnique Montréal, Canada
E-mail: christophe.danjou@polymtl.ca

Christian Braesch
Université Savoie Mont-Blanc – SYMME, Annecy, France
E-mail : christian.braesch@univ-smb.fr

Felix Nyffenegger
HSR, Rapperswil, Switzerland
E-mail: felix.nyffenegger@hsr.ch
summary:There has been considerable interest in Building Information Modeling (BIM) research and development during the last decade. BIM has established itself as a field of research in (and beyond) scientific communities interested in information technologies in construction. Interestingly, the contours of BIM as a scientific field are still not clearly identified. Several studies have recently tried to analyze different aspects of this issue, without providing a systematic and comprehensive methodological approach to accurately define the major themes and clusters of the BIM domain. This paper uses a systematic literature review approach to map the BIM research themes and clusters over ten years of scientific publications. 1244 articles published in peer-reviewed journals between 2007 and 2016 were selected and the associated metadata analyzed in order to highlight co-occurrences in author’s keywords. It appears that a few “big players” dominate the keywords, while most of the keywords used by authors are much less cited. Seven core clusters are identified using modularity optimization techniques: industry foundation classes, information technology, facility management, building, collaboration, computer aided design, and laser scanning.
keywords:BIM, Building information modeling, Systematic literature review, Mapping study, Bibliometric analysis, Scientometry, Research topics, Research themes, Research communities
full text: (PDF file, 2.305 MB)
citation:Lemaire C, Rivest L, Boton C, Danjou, C, Braesch C, Nyffenegger F (2019). Analyzing BIM topics and clusters through ten years of scientific publications, ITcon Vol. 24, pg. 273-298, https://www.itcon.org/2019/15