Identification and prioritization of applications of building information modelling using an integrated BWM-VIKOR approach under rough set theory: A study of construction projects

Recently, Building Information Modelling has emerged as a new technology worldwide. However, a literature review indicates a large and significant gap in identifying and prioritizing BIM applications in construction project and their impacts. Also, many studies have been conducted on the issue of investigating BIM applications, and for this purpose, various models and methods have been proposed in fuzzy and deterministic environments. In this study, a new hybrid approach based on the best-worst and VIKOR methods, improved with rough set theory, is presented to identify and prioritize BIM applications. One of the advantages of the proposed method is modelling the uncertainty related to personal assessments and zeroing the decision maker's subjective judgment error, using the decision table approach. In the following, the new hybrid approach combines the research method and uses a four-stage approach. In the first stage, key performance indicators (KPIs) and BIM applications were identified through a literature review and expert validation. Then, the findings were adjusted using a two-round Delphi study tailored to the Iranian context, and key performance indicators and their applications were extracted. Next, using the best-worst concept in rough sets, the importance of the criteria (key performance indicators (KPIs)) is calculated and the selection of the best and worst indicators as well as pairwise comparisons in the best-worst method are performed accordingly in the second stage. Then, in the third stage, the VIKOR method was developed to prioritize BIM applications. Finally, validation and sensitivity analyses were performed in the fourth stage and the results showed that this approach provides valuable insights for increasing BIM implementation in Iranian construction projects. The results of the present study were also compared with the results of other studies and it was found that the results of the new hybrid approach are reliable and more consistent in real conditions.