This research aims to develop a comprehensive risk assessment model that refines and evaluates significant risks (both opportunities and threats) in the practice of Digital Twin (DT) within the construction industry.
An innovative approach is employed, integrating the Fuzzy Delphi Method and the General Cybernetic Best–Worst Method (G-CY-BWM). Data are collected from 30 experts in the initial phase, with 22 continuing through the complete assessment process. Sensitivity and comparative analyses are performed to validate the findings.
A novel risk assessment model is developed, identifying and assessing 32 critical risk factors. The top two opportunities are “enhancement in key digital enablers” and “higher productivity,” while the two most significant threats are “increase in cost of human resources” and “inadequate collaboration among stakeholders.” Sensitivity and comparative analyses were performed to validate the findings, confirming the importance of considering risk interdependencies in the analysis.
This research presents a comprehensive risk assessment model and introduces a novel, replicable methodology for digital twin implementation in construction projects, which informs the development of similar models in other fields. The use of purposive sampling limits the generalizability of the findings.
The developed model enables practitioners and decision-makers to conduct accurate risk analysis for successful digital twin implementation by effectively leveraging key opportunities and mitigating the most influential threats.
This study developed a risk assessment model capable of assessing the risks (opportunities and threats) associated with DT implementation in construction projects, considering their relationships. To this end, the research developed a novel and replicable methodology integrating the Fuzzy Delphi Method, the cybernetic pairwise comparison concept and the general best-worst method to ensure higher accuracy and consistency while reducing the cognitive data-collection load.
