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Title: Knowledge, skills and functionalities requirements for quantity surveyors in building information modelling (BIM) work environment : an international Delphi study
Authors: Saka, AB 
Chan, DWM 
Keywords: Quantity surveyors
Building information modelling (BIM)
Issue Date: 2019
Publisher: Taylor & Francis
Source: Architectural engineering and design management, 2019, p.1-20, How to cite?
Journal: Architectural engineering and design management 
Abstract: Previous research studies have identified a lack of skilled personnel and a lack of Building Information Modelling (BIM) knowledge and training as one of the major challenges hindering the adoption of BIM in the Architecture, Engineering, and Construction (AEC) industry. Despite the significance of these challenges, there is a dearth of research studies to identify the necessary skills and knowledge to overcome these challenges. A few extant studies in this area focused on general domain skills and knowledge which may not sufficiently suit each domain. This study aims to identify a series of knowledge domains, domain-specific skills, and domain-specific functionalities needed for quantity surveyors to function in a BIM environment and for maintaining sustainable quantity surveying practice in the AEC industry. Delphi survey technique was adopted to aggregate the consensus of experts on knowledge, skills, and functionalities identified from the literature review coupled with experts' collective reviews and opinions. The survey findings underscored the need for quantity surveyors to be BIM compliant and identified 8 knowledge areas, 7 domain-specific skills, and 9 domain-specific BIM functionalities for the quantity surveyors along with the industry required level of expertise using the cognitive domain of Bloom's taxonomy. The survey findings will help mitigate possible fears of quantity surveyors as regards BIM adoption in practice and will be useful in the training and assessment of quantity surveyors to efficiently work in a BIM environment.
ISSN: 1745-2007
EISSN: 1752-7589
DOI: 10.1080/17452007.2019.1651247
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