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Readiness Assessment For Bim-based Building Permit Processes Using Fuzzy-Copras

Autor(en):




Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Journal of Civil Engineering and Management, , n. 8, v. 28
Seite(n): 620-633
DOI: 10.3846/jcem.2022.17274
Abstrakt:

With the recent technological advancement in the Architecture, Engineering, and Construction (AEC) industry, building control authorities in a number of countries are trying to integrate BIM into their building permit processes. Nevertheless, considering the involvement of multiple stakeholders and contexts, adopting BIM in any organization is challenging. The aim of this research is to assess readiness for BIM-based building permit processes using Fuzzy-COPRAS, a multiple criteria decision making (MCDM) method. In this research, three municipalities were selected as alternatives and twenty-five criteria (categorized into technology, people, process, and policies) related to BIM-based building permit processes were identified from a literature review. Then, as part of the COPRAS method, the weights of the criteria were determined based on their importance level through expert evaluation. The results of the study revealed the most important criteria for BIM-based building permit processes, i.e., supporting open standards, compatibility with existing building regulations and codes, willingness of employees, support from top management, and comprehensiveness of code compliance checks. Finally, the readiness assessment results demonstrated the most prepared alternative in the selected municipalities for the BIM-based building permit process based on the status of the considered criteria. The findings of this research have practical implications for municipalities considering and/or developing their BIM-based building permit processes in terms of where to focus their efforts with respect to the criteria associated with BIM-based building permits.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.3846/jcem.2022.17274.
  • Über diese
    Datenseite
  • Reference-ID
    10700606
  • Veröffentlicht am:
    11.12.2022
  • Geändert am:
    11.12.2022
 
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