A Risk Assessment Model For The Implementation Of Digital Twin Technology In China’s Construction Industry Wang
The Chinese construction industry has been criticized for its slow adoption of digitization, while Digital Twin (DT) technology is recognized as a potential solution. However, the implementation of DT comes with various risks, encompassing both opportunities and threats. Moreover, there is a notable...
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2024
|
| Subjects: | |
| Online Access: | http://eprints.usm.my/62862/ http://eprints.usm.my/62862/1/WANG%20MAOYING%20-%20TESIS24.pdf |
| Summary: | The Chinese construction industry has been criticized for its slow adoption of digitization, while Digital Twin (DT) technology is recognized as a potential solution. However, the implementation of DT comes with various risks, encompassing both opportunities and threats. Moreover, there is a notable gap in risk assessment specific to DT implementation within the Chinese construction sector. To fill this gap, this research is aiming at developing an effective risk assessment model (RAM) for evaluating associated risks, with the goal of enhancing the successful implementation of DT in construction. First, this research conducted a comprehensive literature review to identify potential risks associated with the practice of DT in the construction industry. Second, semi-structured interviews and the Fuzzy Delphi Method are carried out to refine the risks. Third, to better evaluate these risks, this research develops a General Cybernetic Best-Worst Method (G-Cy-BWM) RAM to identify and assess the significant risk factors (RFs) associated with the practice of DT within the construction sector. The multicriteria decision-making (MCDM) methods are adopted and a total of 36 qualified experts are involved in different phases of this research. As a result, a total of 32 critical RFs, including 23 opportunities and 9 threats, are identified and prioritized based on their interdependent weights calculated using the developed RAM. |
|---|