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A supply chain network game theory model of cybersecurity investments with nonlinear budget constraints

Author

Listed:
  • Anna Nagurney

    (University of Massachusetts)

  • Patrizia Daniele

    (University of Catania)

  • Shivani Shukla

    (University of Massachusetts)

Abstract

In this paper, we develop a supply chain network game theory model consisting of retailers and demand markets with retailers competing noncooperatively in order to maximize their expected profits by determining their optimal product transactions as well as cybersecurity investments subject to nonlinear budget constraints that include the cybersecurity investment cost functions. The consumers at the demand markets reflect their preferences through the demand price functions, which depend on the product demands and on the average level of cybersecurity in the supply chain network. We identify the supply chain network vulnerability to cyberattacks as well as that of the individual retailers. We demonstrate that the governing Nash equilibrium conditions can be formulated as a variational inequality problem and we provide a novel alternative formulation, along with the accompanying theory. We also propose an algorithm for the alternative formulation, which yields, at each iteration, closed form expressions in product transactions, security levels, and Lagrange multipliers associated with the budget constraints. We then apply the algorithm to compute solutions to a spectrum of numerical supply chain network cybersecurity investment examples. The examples broaden our understanding of the impacts of the addition of retailers, changes in budgets, demand price functions, and financial damages, on equilibrium product transactions and cybersecurity investments, as well as on the supply chain network vulnerability and retailer vulnerability under budget constraints.

Suggested Citation

  • Anna Nagurney & Patrizia Daniele & Shivani Shukla, 2017. "A supply chain network game theory model of cybersecurity investments with nonlinear budget constraints," Annals of Operations Research, Springer, vol. 248(1), pages 405-427, January.
  • Handle: RePEc:spr:annopr:v:248:y:2017:i:1:d:10.1007_s10479-016-2209-1
    DOI: 10.1007/s10479-016-2209-1
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    References listed on IDEAS

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    1. Toyasaki, Fuminori & Daniele, Patrizia & Wakolbinger, Tina, 2014. "A variational inequality formulation of equilibrium models for end-of-life products with nonlinear constraints," European Journal of Operational Research, Elsevier, vol. 236(1), pages 340-350.
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    3. George A. Akerlof, 1970. "The Market for "Lemons": Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 84(3), pages 488-500.
    4. Patrizia Daniele, 2006. "Dynamic Networks and Evolutionary Variational Inequalities," Books, Edward Elgar Publishing, number 3516.
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    Cited by:

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    3. E. Allevi & A. Gnudi & I. V. Konnov & G. Oggioni, 2018. "Evaluating the effects of environmental regulations on a closed-loop supply chain network: a variational inequality approach," Annals of Operations Research, Springer, vol. 261(1), pages 1-43, February.
    4. Adithya Thaduri & Mustafa Aljumaili & Ravdeep Kour & Ramin Karim, 2019. "Cybersecurity for eMaintenance in railway infrastructure: risks and consequences," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(2), pages 149-159, April.
    5. Yu, Min & Cruz, Jose M. & Li, Dong Michelle, 2019. "The sustainable supply chain network competition with environmental tax policies," International Journal of Production Economics, Elsevier, vol. 217(C), pages 218-231.
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    7. Nagurney, Anna, 2022. "Attracting international migrant labor: Investment optimization to alleviate supply chain labor shortages," Operations Research Perspectives, Elsevier, vol. 9(C).
    8. Nagurney, Anna & Shukla, Shivani & Nagurney, Ladimer S. & Saberi, Sara, 2018. "A game theory model for freight service provision security investments for high-value cargo," Economics of Transportation, Elsevier, vol. 16(C), pages 21-28.
    9. Longfei He & Qinxu Gu & Junsong Bian & Kin Keung Lai & Xiao Zhang, 2023. "To Pool or Not to Pool in Carbon Quotas: Analyses of Emission Regulation and Operations in Supply Chain Supernetwork under Cap-and-Trade Policy," Annals of Operations Research, Springer, vol. 324(1), pages 311-353, May.
    10. Yongtao Peng & Bohai Chen & Eleonora Veglianti, 2022. "Platform Service Supply Chain Network Equilibrium Model with Data Empowerment," Sustainability, MDPI, vol. 14(9), pages 1-21, April.
    11. Isa Feyzian-Tary & Jafar Razmi & Mohamad Sadegh Sangari, 2018. "A variational inequality formulation for designing a multi-echelon, multi-product supply chain network in a competitive environment," Annals of Operations Research, Springer, vol. 264(1), pages 89-121, May.
    12. Xing Gao & Siyu Gong, 2022. "An economic analysis of information security outsourcing with competitive firms," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 2748-2758, October.
    13. Lu Xu & Yanhui Li & Qi Yao, 2022. "Information security investment and purchase decision for personalized products," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 2619-2635, September.
    14. Wen Jiang & Zeyu Ma & Xinyang Deng, 2019. "An attack-defense game based reliability analysis approach for wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(4), pages 15501477198, April.
    15. Yaoguang Zhong & Fangfang Guo & Zhiqiang Wang & Huajun Tang, 2019. "Coordination Analysis of Revenue Sharing in E-Commerce Logistics Service Supply Chain With Cooperative Distribution," SAGE Open, , vol. 9(3), pages 21582440198, August.
    16. Dacorogna, Michel & Debbabi, Nehla & Kratz, Marie, 2023. "Building up cyber resilience by better grasping cyber risk via a new algorithm for modelling heavy-tailed data," European Journal of Operational Research, Elsevier, vol. 311(2), pages 708-729.
    17. Yong Long & Chengrong Pan & Yu Wang, 2018. "Research on a Microgrid Subsidy Strategy Based on Operational Efficiency of the Industry Chain," Sustainability, MDPI, vol. 10(5), pages 1-26, May.
    18. Cheung, Kam-Fung & Bell, Michael G.H. & Bhattacharjya, Jyotirmoyee, 2021. "Cybersecurity in logistics and supply chain management: An overview and future research directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    19. Wei Liu & Chan He, 2018. "Equilibrium Conditions of a Logistics Service Supply Chain with a New Smoothing Algorithm," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(02), pages 1-22, April.
    20. Fenling Feng & Tianzuo Zhang & Chengguang Liu & Lifeng Fan, 2020. "China Railway Express Subsidy Model Based on Game Theory under “the Belt and Road” Initiative," Sustainability, MDPI, vol. 12(5), pages 1-16, March.
    21. Peiyue Cheng & Guitao Zhang & Hao Sun, 2022. "The Sustainable Supply Chain Network Competition Based on Non-Cooperative Equilibrium under Carbon Emission Permits," Mathematics, MDPI, vol. 10(9), pages 1-31, April.
    22. Gabriella Colajanni & Patrizia Daniele, 2022. "A Mathematical Network Model and a Solution Algorithm for IaaS Cloud Computing," Networks and Spatial Economics, Springer, vol. 22(2), pages 267-287, June.
    23. Michel Dacorogna & Marie Kratz, 2022. "Special Issue “Cyber Risk and Security”," Risks, MDPI, vol. 10(6), pages 1-4, May.

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