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Regulation Games Between Government and Competing Companies: Oil Spills and Other Disasters

Author

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  • May Cheung

    (Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, New York 14260)

  • Jun Zhuang

    (Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, New York 14260)

Abstract

Oil spills are a characteristic risk of oil drilling and production. There are safety regulations set to reduce the risk of technological failures and human error. It is the oil company's decision to follow such laws and the government's decision to enforce them. Companies are balancing between safety efforts and production competition with other companies. To our knowledge, no previous research has considered the impact of competition in a government--company regulatory game. This paper fills the gap by modeling and comparing two games: a one-company game without competition and a two-company game with competition, both with the government as a regulator. The objectives of all players are to maximize their expected revenue and minimize their losses. Our results indicate that competition increases a company's threshold for risk and therefore requires stricter government regulation. These results could be generalized and applied to other industries including airline, nuclear power, and coal mining.

Suggested Citation

  • May Cheung & Jun Zhuang, 2012. "Regulation Games Between Government and Competing Companies: Oil Spills and Other Disasters," Decision Analysis, INFORMS, vol. 9(2), pages 156-164, June.
    • Handle: RePEc:inm:ordeca:v:9:y:2012:i:2:p:156-164
    DOI: 10.1287/deca.1120.0233
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Kjell Hausken & Jun Zhuang, 2016. "The strategic interaction between a company and the government surrounding disasters," Annals of Operations Research, Springer, vol. 237(1), pages 27-40, February.
    2. Jason R. W. Merrick & Fabrizio Ruggeri & Refik Soyer & L. Robin Keller, 2012. "From the Editors---Games and Decisions in Reliability and Risk," Decision Analysis, INFORMS, vol. 9(2), pages 81-85, June.
    3. Shitao Gong & Xin Gao & Zhou Li & Linyan Chen, 2021. "Developing a Dynamic Supervision Mechanism to Improve Construction Safety Investment Supervision Efficiency in China: Theoretical Simulation of Evolutionary Game Process," IJERPH, MDPI, vol. 18(7), pages 1-29, March.
    4. Cameron A. MacKenzie & Hiba Baroud & Kash Barker, 2016. "Static and dynamic resource allocation models for recovery of interdependent systems: application to the Deepwater Horizon oil spill," Annals of Operations Research, Springer, vol. 236(1), pages 103-129, January.
    5. Kumar, Sourabh & Kumar Barua, Mukesh, 2022. "Modeling and investigating the interaction among risk factors of the sustainable petroleum supply chain," Resources Policy, Elsevier, vol. 79(C).
    6. Cameron MacKenzie & Hiba Baroud & Kash Barker, 2016. "Static and dynamic resource allocation models for recovery of interdependent systems: application to the Deepwater Horizon oil spill," Annals of Operations Research, Springer, vol. 236(1), pages 103-129, January.
    7. Hausken, Kjell & Zhuang, Jun, 2013. "The impact of disaster on the strategic interaction between company and government," European Journal of Operational Research, Elsevier, vol. 225(2), pages 363-376.
    8. Agarwal, Puneet & Aziz, Ridwan Al & Zhuang, Jun, 2022. "Interplay of rumor propagation and clarification on social media during crisis events - A game-theoretic approach," European Journal of Operational Research, Elsevier, vol. 298(2), pages 714-733.
    9. Shandong Mou & Kexin Zhong & Yamin Ma, 2023. "Regulating the Big Data-Based Discriminatory Pricing in Platform Retailing: A Tripartite Evolutionary Game Theory Analysis," Mathematics, MDPI, vol. 11(11), pages 1-21, June.
    10. Peiqiu Guan & Jun Zhuang, 2015. "Modeling Public–Private Partnerships in Disaster Management via Centralized and Decentralized Models," Decision Analysis, INFORMS, vol. 12(4), pages 173-189, December.
    11. Puneet Agarwal & Kyle Hunt & Shivasubramanian Srinivasan & Jun Zhuang, 2020. "Fire Code Inspection and Compliance: A Game-Theoretic Model Between Fire Inspection Agencies and Building Owners," Decision Analysis, INFORMS, vol. 17(3), pages 208-226, September.
    12. Huijie Li & Deqing Tan, 2024. "How to Control Waste Incineration Pollution? Cost-Sharing or Penalty Mechanism—Based on Two Differential Game Models," Decision Analysis, INFORMS, vol. 21(2), pages 91-109, June.
    13. Daniel Seaberg & Laura Devine & Jun Zhuang, 2017. "A review of game theory applications in natural disaster management research," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(3), pages 1461-1483, December.
    14. Vicki M. Bier & Yuqun Zhou & Hongru Du, 2020. "Game-theoretic modeling of pre-disaster relocation," The Engineering Economist, Taylor & Francis Journals, vol. 65(2), pages 89-113, April.
    15. Cen Song & Jun Zhuang, 2018. "Modeling Precheck Parallel Screening Process in the Face of Strategic Applicants with Incomplete Information and Screening Errors," Risk Analysis, John Wiley & Sons, vol. 38(1), pages 118-133, January.
    16. Kjell Hausken & Jun Zhuang, 2016. "How companies and governments react to disasters," Journal of Risk and Reliability, , vol. 230(4), pages 417-426, August.

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