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Macro-BIM adoption: Conceptual structures

Lookup NU author(s): Professor Mohamad Kassem


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© 2015 Elsevier B.V. All rights reserved. Building Information Modelling (BIM) concepts and workflows continue to proliferate within organisations, through project teams, and across the whole construction industry. However, both BIM implementation and BIM diffusion are yet to be reliably assessed at market scale. Insufficient research has been conducted to date towards identifying the conceptual structures that would explain and encourage large-scale BIM adoption. This paper introduces a number of macro-adoption models, matrices and charts (Fig. 1). These models can be used to systematically assess BIM adoption across markets, and inform the structured development of country-specific BIM adoption policies. This research is published in two complementary papers combining conceptual structures with data collected from experts across a number of countries. The first paper "Macro-BIM adoption: conceptual structures" delimits the terms used, reviews applicable diffusion models, and clarifies the research methodology. It then introduces five new conceptual constructs for assessing macro-BIM adoption and informing the development of market-scale BIM diffusion policies. The second paper "Macro-BIM adoption: comparative market analysis" employs these concepts and tools to evaluate BIM adoption and analyse BIM diffusion policies across a number of countries. Using online questionnaires and structured interviews, it applies the models, refines the conceptual tools and develops additional assessment metrics. The two papers are complementary and primarily intended to assist policy makers and domain researchers to analyse, develop and improve BIM diffusion policies.

Publication metadata

Author(s): Succar B, Kassem M

Publication type: Article

Publication status: Published

Journal: Automation in Construction

Year: 2015

Volume: 57

Pages: 64-79

Print publication date: 01/09/2015

Online publication date: 14/05/2015

Acceptance date: 25/04/2015

ISSN (print): 0926-5805

ISSN (electronic): 1872-7891

Publisher: Elsevier BV


DOI: 10.1016/j.autcon.2015.04.018


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