Journal of the Korean Society for Industrial and Applied Mathematics

Korean Society for Industrial and Applied Mathematics (한국산업응용수학회)
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IMPROVING GLOBAL SUPPLY CHAIN RISK IDENTIFICATION USING RCF

  • MYUNGHYUN, JUNG (DEPARTMENT OF INNOVATION CENTER FOR INDUSTRIAL MATHEMATICS, NATIONAL INSTITUTE FOR MATHEMATICAL SCIENCES) ;
  • SEYEON, LEE (DEPARTMENT OF INNOVATION CENTER FOR INDUSTRIAL MATHEMATICS, NATIONAL INSTITUTE FOR MATHEMATICAL SCIENCES) ;
  • MINJUNG, GIM (DEPARTMENT OF INNOVATION CENTER FOR INDUSTRIAL MATHEMATICS, NATIONAL INSTITUTE FOR MATHEMATICAL SCIENCES) ;
  • HYUNGJO, KIM (GVC CENTER, INDUSTRIAL POLICY DIVISION, KOREA ASSOCIATION OF MACHINERY INDUSTRY) ;
  • JAEHO, LEE (GVC CENTER, INDUSTRIAL POLICY DIVISION, KOREA ASSOCIATION OF MACHINERY INDUSTRY)
  • Received : 2022.12.02
  • Accepted : 2022.12.15
  • Published : 2022.12.25
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Abstract

This paper contains an introduction to industrial problems, solutions, and results conducted with the Korea Association of Machinery Industry. The client company commissioned the problem of upgrading the method of identifying global supply risky items. Accordingly, the factors affecting the supply and demand of imported items in the global supply chain were identified and the method of selecting risky items was studied and delivered. Through research and discussions with the client companies, it is confirmed that the most suitable factors for identifying global supply risky items are 'import size', 'import dependence', and 'trend abnormality'. The meaning of each indicator is introduced, and risky items are selected using export/import data until October 2022. Through this paper, it is expected that countries and companies will be able to identify global supply risky items in advance and prepare for risks in the new normal situation: the economic situation caused by infectious diseases such as the COVID-19 pandemic; and the export/import regulation due to geopolitical problems. The client company will include in his report, the method presented in this paper and the risky items selected by the method.

Keywords

Acknowledgement

This work was supported by National Institute for Mathematical Sciences(NIMS) grant funded by the Korean government(MSIT) (No.NIMS-B22810000). This work was supported by the Technology Innovation Program (20020724, Building Statistics DB of Material-Parts-Equipment Industry And Global Value Chain Analysis) funded By the Ministry of Trade, Industry & Energy MOTIE, Korea).

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