Optimal Risk Control of Complex Supply Chain Networks under Public Emergencies
DOI:
https://doi.org/10.54097/7r1th320Keywords:
Public Emergencies, Supply Chain Risk, Infectious Disease Model, Optimal ControlAbstract
Public emergency is an event that occurs suddenly, has a wide range of influence, and brings great impact to the society. It has the characteristics of suddenness, publicity, urgency and uncertainty. Frequent public emergencies pose a great threat to supply chain security, causing serious economic losses and social impacts. In order to improve the ability of supply chain network to cope with public emergencies, it is of great significance to study the law of supply chain risk transmission and risk control measures. Through the review of the relevant theories of supply chain sudden risk and infectious disease model, the existing problems and research prospects are pointed out. Then, based on the SEIR model, a complex supply chain network risk control model under government intervention is constructed to explore the transmission mechanism of supply chain risk and the optimal control rate of the government. Finally, the simulation verifies that by controlling the basic reproduction number, the government can effectively curb the further spread and diffusion of risks, and achieve the goal of controlling risks and balancing cost control.
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[1] P R Kleindorfer, G H Saad. Managing disruption risks in supply chains [J]. Production and Operations Management, 2005, 14(1): 53-68.
[2] H Yu, J Chen, G Yu. Managing Wholesale Price Contract in the Supply Chain under Disruptions [J]. Systems Engineering — Theory & Practice, 2006(08):33-41.
[3] Q H Pang. Research on coordination of three-level supply chain response to emergencies under benefit-sharing contract [J]. Chinese Journal of Management Science, 2010, 18(04):101-106.
[4] B C Giri, B R Sarker. Improving performance by coordinating a supply chain with third party logistics outsourcing under production disruption [J]. Computers & Industrial Engineering, 2017, 103: 168-177.
[5] D Ivanov, A Dolgui. Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak [J/OL]. International Journal of Production Research, 2020, 58(10): 2904-2915.
[6] S Hosseini, D Ivanov, A Dolgui. Ripple effect modelling of supplier disruption: integrated Markov chain and dynamic Bayesian network approach [J]. International Journal of Production Research, 2020, 58(11): 3284-3303.
[7] M O Kermark, A C Mokendrick, W G Thomas. Contirbutions to the mathematical theory of epidemics [J]. Proceedings of the Royal Society A, 1927, 115772:700-721.
[8] Z Y Wang, Y J Li. Propagation law and coping strategies for public opinions in emergency with the consideration of the government intervention [J]. Journal of Management Science and Engineering, 2017, 20(2):43-52..
[9] H M Zhu, S T Zhang, Z Jin, et al. Knowledge transmission model on the coupled network formed by WeChat group and offline communication [J]. Systems Engineering—Theory & Practice, 2019, 39(7): 1796-1806.
[10] X J Ding, L X Li. The spreading dynamics of rumors in social media under the anti-silence spiral effect [J]. Systems Engineering - Theory & Practice, 2020, 40 (12): 3149-3163.
[11] R May, S Levin, G Sugihara . Complex systems: Ecology for bankers [J]. Nature, 2008, 451 (7181): 893-895.
[12] A Garas, P Argyrakis, C Rozenblat, et al. Worldwide spreading of economic crisis [J]. New journal of Physics, 2010, 12(11): 113043.
[13] K Yang, Z Y Zhang. Research on Risk propagation mechanism of supply chain network based on Complex Network Theory [J]. Journal of Systems Science and Mathematical Sciences, 2013,33(10):1224-1232.
[14] D Liang, R Bhamra, Z Liu, et al. Risk Propagation and Supply Chain Health Control Based on the SIR Epidemic Model [J]. Mathematics 2022, 10, 3008.
[15] R F Zhang, X Q Li. Research on credit risk contagion measure of supply chain finance based on SWN-SEIRS model [J]. The Theory and Practice of Financial and Economics, 2021, 42(02):20-26.
[16] H Wang, X Zhang. Research on Supply Chain Risk Transmission Mechanism Based on Improved SIRS Model [J]. Mathematical Problems in Engineering, 2022, 2022.
[17] N Berger, S Schulze-Schwering, E Long, et al. Risk management of supply chain disruptions: An epidemic modeling approach [J]. European Journal of Operational Research, 2023, 304(3):1036-1051.
[18] P Driessche, J Watmough. Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease trans.
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