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The impact of firm heterogeneity and awareness in modeling risk propagation on multiplex networks

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  • Liu, Hui
  • Yang, Naiding
  • Yang, Zhao
  • Lin, Jianhong
  • Zhang, Yanlu

Abstract

Growing interest has emerged to understand the coupled awareness-epidemic dynamics in multiplex network. However, most previous studies usually assume that all the infected nodes have the same influence on the susceptible neighbors, without considering node’s heterogeneity. In this paper, with the similarity between epidemic spreading and risk propagation, we apply the UAU-SIS model to investigate the interplay between awareness and risk propagation in R&D networks considering firms’ heterogeneity. Here, the risk triggering probabilities are heterogeneous and depend on two factors: cooperation intensity and local risk prevalence. The results reveal that the cooperation intensity can increase the risk propagation prevalence and decrease the risk propagation threshold, while the local risk prevalence can only increase the risk propagation prevalence. Moreover, we find that the risk propagation threshold undergoes an abrupt transition with a certain point of the local awareness ratio (the global awareness ratio) ignoring the global awareness (the local awareness ratio), which includes two-stage effects on risk propagation threshold. Furthermore, threshold lies in three different areas when considering both the global and local awareness. These results could provide a basis for managerial professionals to improve the robustness of interdependent R&D networks under risk propagation by taking effective measures.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:539:y:2020:i:c:s0378437119316553
    DOI: 10.1016/j.physa.2019.122919
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    References listed on IDEAS

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    1. Mario V. Tomasello & Mauro Napoletano & Antonios Garas & Frank Schweitzer, 2017. "The rise and fall of R&D networks," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(4), pages 617-646.
    2. Nie, Xiaoyu & Tang, Ming & Zou, Yong & Guan, Shuguang & Zhou, Jie, 2017. "The impact of heterogeneous response on coupled spreading dynamics in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 225-232.
    3. Mattia Montagna & Thomas Lux, 2017. "Contagion risk in the interbank market: a probabilistic approach to cope with incomplete structural information," Quantitative Finance, Taylor & Francis Journals, vol. 17(1), pages 101-120, January.
    4. Zhang, Yanlu & Yang, Naiding, 2013. "Research on robustness of R&D network under cascading propagation of risk with gray attack information," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 1-8.
    5. Franck Marle, 2014. "A structured process to managing complex interactions between project risks," International Journal of Project Organisation and Management, Inderscience Enterprises Ltd, vol. 6(1/2), pages 4-32.
    6. Zhang, Yanlu & Yang, Naiding, 2018. "Vulnerability analysis of interdependent R&D networks under risk cascading propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1056-1068.
    7. Gnyawali, Devi R. & Park, Byung-Jin (Robert), 2011. "Co-opetition between giants: Collaboration with competitors for technological innovation," Research Policy, Elsevier, vol. 40(5), pages 650-663, June.
    8. Wang, Jingbei & Yang, Naiding & Zhang, Yanlu & Song, Yue, 2018. "Development of the mitigation strategy against the schedule risks of the R&D project through controlling the cascading failure of the R&D network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 390-401.
    9. Fan, Chong-jun & Jin, Yang & Huo, Liang-an & Liu, Chen & Yang, Yun-peng & Wang, Ya-qiong, 2016. "Effect of individual behavior on the interplay between awareness and disease spreading in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 523-530.
    10. Qazi, Abroon & Quigley, John & Dickson, Alex & Ekici, Şule Önsel, 2017. "Exploring dependency based probabilistic supply chain risk measures for prioritising interdependent risks and strategies," European Journal of Operational Research, Elsevier, vol. 259(1), pages 189-204.
    11. Ricarda Bouncken & Boris Plüschke & Robin Pesch & Sascha Kraus, 2016. "Entrepreneurial orientation in vertical alliances: joint product innovation and learning from allies," Review of Managerial Science, Springer, vol. 10(2), pages 381-409, March.
    12. Zang, Haijuan, 2018. "The effects of global awareness on the spreading of epidemics in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1495-1506.
    13. Das, T. K. & Teng, Bing-Sheng, 2001. "A risk perception model of alliance structuring," Journal of International Management, Elsevier, vol. 7(1), pages 1-29.
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    2. 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.
    3. Yang, Qing & Zou, Xingqi & Ye, Yunting & Yao, Tao, 2022. "Evaluating the criticality of the product development project portfolio network from the perspective of risk propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    4. Li, Ruimeng & Yang, Naiding & Zhang, Yanlu & Liu, Hui & Zhang, Mingzhen, 2021. "Impacts of module–module aligned patterns on risk cascading propagation in complex product development (CPD) interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    5. Li, Ruimeng & Yang, Naiding & Yi, Hao & Jin, Na, 2023. "The robustness of complex product development projects under design change risk propagation with gray attack information," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    6. Ping Yu & Peiwen Wang & Zhiping Wang & Jia Wang, 2022. "Supply Chain Risk Diffusion Model Considering Multi-Factor Influences under Hypernetwork Vision," Sustainability, MDPI, vol. 14(14), pages 1-15, July.

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