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Risk Diffusion and Control under Uncertain Information Based on Hypernetwork

Author

Listed:
  • Ping Yu

    (School of Science, Dalian Maritime University, Dalian 116026, China)

  • Zhiping Wang

    (School of Science, Dalian Maritime University, Dalian 116026, China)

  • Yanan Sun

    (School of Science, Dalian Maritime University, Dalian 116026, China)

  • Peiwen Wang

    (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

Abstract

During the height of the COVID-19 epidemic, production lagged and enterprises could not deliver goods on time, which will bring considerable risks to the supply chain system. Modeling risk diffusion in supply chain networks is important for prediction and control. To study the influence of uncertain information on risk diffusion in a dynamic network, this paper constructs a dynamic evolution model based on a hypernetwork to study risk diffusion and control under uncertain information. First, a dynamic evolution model is constructed to represent the network topology, which includes the addition of links, rewiring of links, entry of nodes, and the exit of outdated nodes that obey the aging principle. Then, the risk diffusion scale is discussed with the Microscopic Markovian Chain Approach (MMCA), and the risk threshold is analyzed. Finally, the consistency of Monte Carlo (MC) simulation and MMCA is verified by MATLAB, and the influence of each parameter on the risk diffusion scale and risk threshold is tested. The results show that reducing the cooperation and production during the risk period, declining the attenuation factor, enhancing the work efficiency of the official media, and increasing the probability of the exit of outdated nodes in the supply chain networks will increase the risk threshold and restrain the risk diffusion.

Suggested Citation

  • Ping Yu & Zhiping Wang & Yanan Sun & Peiwen Wang, 2022. "Risk Diffusion and Control under Uncertain Information Based on Hypernetwork," Mathematics, MDPI, vol. 10(22), pages 1-17, November.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:22:p:4344-:d:977625
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    References listed on IDEAS

    as
    1. Ran, Maojie & Chen, Jiancu, 2021. "An information dissemination model based on positive and negative interference in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    2. Hu, Ping & Geng, Dongqing & Lin, Tao & Ding, Li, 2021. "Coupled propagation dynamics on multiplex activity-driven networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    3. Huo, Liang’an & Guo, Hongyuan & Cheng, Yingying & Xie, Xiaoxiao, 2020. "A new model for supply chain risk propagation considering herd mentality and risk preference under warning information on multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    4. Ma, Weicai & Zhang, Peng & Zhao, Xin & Xue, Leyang, 2022. "The coupled dynamics of information dissemination and SEIR-based epidemic spreading in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    5. Meixell, Mary J. & Gargeya, Vidyaranya B., 2005. "Global supply chain design: A literature review and critique," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 41(6), pages 531-550, November.
    6. Suo, Qi & Guo, Jin-Li & Sun, Shiwei & Liu, Han, 2018. "Exploring the evolutionary mechanism of complex supply chain systems using evolving hypergraphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 141-148.
    7. Qian, Qian & Feng, Hairong & Gu, Jing, 2021. "The influence of risk attitude on credit risk contagion—Perspective of information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    8. Liu, Hui & Yang, Naiding & Yang, Zhao & Lin, Jianhong & Zhang, Yanlu, 2020. "The impact of firm heterogeneity and awareness in modeling risk propagation on multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    9. Jiang, Xin & Wang, Zhiping & Liu, Wei, 2019. "Information dissemination in dynamic hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    10. Wang, Zhiping & Yin, Haofei & Jiang, Xin, 2020. "Exploring the dynamic growth mechanism of social networks using evolutionary hypergraph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    11. Wang, Jiepeng & Zhou, Hong & Jin, Xiaodan, 2021. "Risk transmission in complex supply chain network with multi-drivers," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    12. Estrada, Ernesto & Rodríguez-Velázquez, Juan A., 2006. "Subgraph centrality and clustering in complex hyper-networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 581-594.
    13. Zhang, Mingli & Qin, Simeng & Zhu, Xiaoxia, 2021. "Information diffusion under public crisis in BA scale-free network based on SEIR model — Taking COVID-19 as an example," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
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