Abstract:
Digital twin (DT) is increasingly recognized as a valuable instrument for improving water infrastructure efficiency. However, current research has yet to identify drivers and barriers impacting the use of DT in water infrastructure practices. Preliminary work has been undertaken regarding drivers and barriers of DT in the manufacturing, processing, and construction industries, but not in water. Therefore, this study engages two questions. First, what are the drivers and barriers to DT adoption in water infrastructure projects? Second, which of these drivers and barriers are critical? A literature review targeting an Environmental, Social, Governance, and Financial (ESG-Financial) framework was undertaken to identify candidate drivers and barriers. Text mining not only supplements but also validates and refines the list of driving and barrier factors obtained from literature reviews. Next, a fuzzy decision-making trial and evaluation laboratory (DEMATEL) method was utilized to find those most critical. Subsequently, a questionnaire survey provided cross-validation of the fuzzy DEMATEL results. Finally, 11 critical drivers and 8 critical barriers were identified. Based on these findings, some policy implications are proposed, including developing the potential of DT in water environment monitoring, strengthening collaboration, improving DT model reuse, promoting DT value capture, enhancing publicity, and increasing DT education investment. Β© 2024 ERP Environment and John Wiley & Sons Ltd.
