Risk Measurement of Industry Chain Based on Set Pair Analysis -Variable Fuzzy Set with Improved Binary Semantics
Keywords: Risk Measurement; Industry Chain; Set Pair Analysis-Variable Fuzzy Set; Binary Semantics
Abstract: Under the current complex and severe new situation, China’s industry chain is facing huge risks caused by the superposition of multiple factors, such as the shortage of supply of “neck-breaking” technologies and the “decoupling and chain breakage” caused by anti-globalization, which urgently needs to strengthen the risk control of the industry chain fundamentally. Implementing industry chain risk measurement is a necessary precondition for risk control. In this study, based on the construction of the industry chain risk measurement indicator system, the comprehensive weights of the indicators are determined by the BWM-CRITIC method. Then, the industry chain risk is measured by binary semantics improved set pair analysis -variable fuzzy set model. Finally, an empirical study is conducted on the example of China’s integrated circuit industry to verify the scientificity and effectiveness of the model. The results of the empirical study show that the model can effectively reflect the risk level of the industry chain by analyzing the relationship between the sample data and the level of each indicator; at the same time, it can better solve the problem of information loss, comprehensively reveal the risk status of the industry chain, and provide a decision-making reference for effectively resisting the risk of the industry chain and realizing the sustainable development of the industry chain.
Submission Number: 11
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