Abstract
This paper presents an integrated framework for supply chain risk assessment. The framework consists of some main components: risk identification, D-S calculation, fuzzy inference, risk analysis and risk evaluation. The risk identification comprises three parts, literature review, expert opinion interview, and questionnaire there are all used to identify the risk categories and their reasons and hazards. D-S calculation utilizes Dempster-Shafer Evidence Theory to fuse the potential risk’s information which are identified by the experts’ knowledge, historical data, literature review and questionnaire. The fuzzy inference part aims to solve how to identify the risk’s impact when there are no explicit data. The risk analysis part use the data from D-S calculation and fuzzy inference to define the main bodies of risk, it’s total probability, impact, and the final score of this risk-event. The risk evaluation component integrates all resources from the risk analysis part and gets a final supply chain score based on the assignment weight which are decided by the experts. A case study from a computer manufacturing environment is considered. Through the analysis of the supply chain, integrating the probability, hazard, and weight of the risk events and calculating a final score, managers can have a comprehensive understanding of the risks in the supply chain, and make some reasonable adjustment to avoid risks and reduce error rate for the purpose of maximizing their profits.
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This work was one of the “Cyberspace Security” key projects in People’s Republic of China.
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Shi, Y., Zhang, Z., Wang, K. (2017). A Dempster Shafer Theory and Fuzzy-Based Integrated Framework for Supply Chain Risk Assessment. In: Uden, L., Lu, W., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2017. Communications in Computer and Information Science, vol 731. Springer, Cham. https://doi.org/10.1007/978-3-319-62698-7_29
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DOI: https://doi.org/10.1007/978-3-319-62698-7_29
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