Factors Influencing the Development of Cloud-Based Building Information Modelling (Cloud-BIM): A Hybrid FDelphi-FANP-TOPSIS-CEA Approach

The adoption of cloud-based building information modelling (Cloud-BIM) presents a complex landscape of potential benefits and challenges for architectural design enterprises in China. While similar opportunities and obstacles exist globally, the unique economic, technical, and regulatory landscape of China necessitates a focused analysis. This study addresses the research gap by investigating the factors influencing Cloud-BIM development in China, utilizing a novel hybrid FDelphi-FANP-TOPSIS-CEA approach. Following a systematic literature review, the interval-valued fuzzy Delphi method (FDelphi) was used to identify 4 primary and 14 secondary factors influencing Cloud-BIM adoption. A fuzzy analytic network process (FANP) was then used to prioritize these factors, revealing technology factors to be the most impactful, with interoperability holding the top position among the secondary factors. The technique for order preference by similarity to ideal solution (TOPSIS) method was further used to identify Cloud-BIM, with objects metasearch being the most favorable alternative among the four potential approaches. Finally, a causal effect analysis (CEA) was used to explore the cause-and-effect relationships between the identified factors, providing a deeper understanding of the underlying dynamics. This research offers valuable insights for architectural design enterprises in China considering Cloud-BIM implementation. By highlighting the key influencing factors, prioritizing their impact, and identifying the most suitable approach, this study equips practitioners with actionable knowledge to navigate the complex decision-making process. Additionally, the novel methodology contributes to the advancement of research in Cloud-BIM adoption, providing a robust framework for future studies in similar contexts.

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