Affiliations: Business School, Shandong University of Technology, Zibo, China
Correspondence:
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Corresponding author. Q. Sun, Business School, Shandong University of Technology, Zibo, China. E-mail: [email protected].
Abstract: In recent years, supply chain risk management has been followed with interest due to the short life cycle of products. How to identify risk indicators can help evaluate risks on supply chains. Commonly adopted methods such as Fuzzy to determine the level of risks have limitations. In this paper, a framework of supply chain risk evaluation is first proposed and risk indicators are identified by theoretical surveys from 35 keywords and empirical analysis from 448 questionnaires. Moreover, both linguistic risk assessment model and Cloud model are used to evaluate risks of supply chain. The Cloud model evaluation results are between general risk and high risk but closer to high risk. In addition, Cloud expected value of risk is 6.54 which is within the high-risk range, and evaluation results are also high risk. It is shown that when the weights are the same, the cloud model can determine the priority of risk indicators, and reflect volatility and randomness comparing with other evaluation methods.
