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Amuda-Yusuf, G (2018) Critical Success Factors for Building Information Modelling Implementation . Construction Economics and Building, 18(03), 55-73.

Livesey, P, V and Runeson, G (2018) Autoethnography and Theory Testing . Construction Economics and Building, 18(03), 40-54.

Loganathan, S, Forsythe, P and Kalidindi, s, N (2018) Work practices of onsite construction crews and their influence on productivity . Construction Economics and Building, 18(03), 18-39.

Mba,M, F, BG and Agumba, J , N (2018) Critical success factors influencing performance outcome of joint venture construction projects in South Africa: Comparison of first and second order models . Construction Economics and Building, 18(03), 74-94.

Yusof, N, A, Ishak, S, S, M and Doheim, R (2018) Identifying factors for incorporating spatial data into BIM using the Delphi method . Construction Economics and Building, 18(03), 1-17.

  • Type: Journal Article
  • Keywords: Spatial data, Building information modeling, Preconstruction planning, Delphi method, Construction industry
  • ISBN/ISSN: 2204-9029
  • URL: https://doi.org/10.5130/AJCEB.v18i3.6031
  • Abstract:
    Construction industry players are now realising the need to implement Building Information Modeling (BIM) at the preconstruction planning stage to allow spatial data of the site to be incorporated into the BIM. Incorporating spatial data in BIM as early as possible in the building lifecycle poses a new challenge to industry players, particularly to the consultants who collect and provide these data. The aim of this study is to identify important factors for incorporating spatial data into the BIM at the preconstruction planning stage. Three rounds of the Delphi method were employed to obtain a consensus among twenty construction industry experts, selected through purposeful sampling. The findings revealed seven consolidated factors, with Technology, Client Demand, and Added Value as the top three, followed by Regulations, Skilled Staff, Management Commitment and Data Management. Experts were significantly in agreement with each other, as indicated by the Kendall’s W Coefficient = 0.6505 significant at < 0.005. The findings highlight the requirements for utilizing spatial data in the BIM at the preconstruction planning stage and help the respective professional bodies to identify the prerequisites for BIM application and subsequently, improve the existing training for the professional development of their members.