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The impact of disaster on the strategic interaction between company and government

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  • Hausken, Kjell
  • Zhuang, Jun

Abstract

A company allocates a resource between safety effort and production. The government earns taxes on production. The disaster probability is modeled as a contest between the disaster magnitude and the two players’ safety efforts. The model illustrates that safety efforts are strategic substitutes and inverse U shaped in the disaster magnitude. The company’s safety effort increases, and the government’s safety effort decreases, in taxation. Taxation can ameliorate companies’ free riding on governments’ safety efforts. With sufficiently large production, the government prefers, and the company does not prefer, raising taxation above 0%. For the government, an upper limit usually exists above which taxation cannot be profitably increased. The model shows how both or no players exert safety efforts when the disaster magnitude is small and large respectively, and how they free ride on each other’s safety efforts when the disaster magnitude is intermediate. The company free rides when the unit production cost is low so that the large profits outweigh the negative impact of the disaster. With endogenized taxation determined by the government, the tax rate decreases in the disaster magnitude, the unit production cost, the government’s unit cost of safety effort, and how the company is negatively affected by the disaster. The tax rate increases in the company’s resource and how the government is negatively affected by the disaster. The tax rate is weakly U shaped in the company’s unit safety effort. The model is illustrated with numerical examples and with the oil spill disasters by BP in 2010 and by Exxon Valdez in 1989.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ejores:v:225:y:2013:i:2:p:363-376
    DOI: 10.1016/j.ejor.2012.09.047
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    Cited by:

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    2. 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.
    3. Chunlin Xin & Jianwen Zhang & Chia-Huei Wu & Sang-Bing Tsai, 2020. "Safety Investment Decision Problem without Probability Distribution: A Robust Optimization Approach," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-10, November.
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    5. 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.
    6. Wenxin Su & Xin Gao & Yukun Jiang & Jinrong Li, 2021. "Developing a Construction Safety Standard System to Enhance Safety Supervision Efficiency in China: A Theoretical Simulation of the Evolutionary Game Process," Sustainability, MDPI, vol. 13(23), pages 1-22, December.
    7. Peiqiu Guan & Meilin He & Jun Zhuang & Stephen C. Hora, 2017. "Modeling a Multitarget Attacker–Defender Game with Budget Constraints," Decision Analysis, INFORMS, vol. 14(2), pages 87-107, June.
    8. Kjell Hausken & Jun Zhuang, 2016. "How companies and governments react to disasters," Journal of Risk and Reliability, , vol. 230(4), pages 417-426, August.
    9. Talarico, Luca & Reniers, Genserik & Sörensen, Kenneth & Springael, Johan, 2015. "MISTRAL: A game-theoretical model to allocate security measures in a multi-modal chemical transportation network with adaptive adversaries," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 105-114.
    10. Simon, Jay & Omar, Ayman, 2020. "Cybersecurity investments in the supply chain: Coordination and a strategic attacker," European Journal of Operational Research, Elsevier, vol. 282(1), pages 161-171.
    11. Yisha Xiang & Jun Zhuang, 2016. "A medical resource allocation model for serving emergency victims with deteriorating health conditions," Annals of Operations Research, Springer, vol. 236(1), pages 177-196, January.
    12. 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.
    13. 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.
    14. Mathews, Timothy & Paul, Jomon A., 2022. "Natural disasters and their impact on cooperation against a common enemy," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1417-1428.
    15. Liu, Yang & Cui, Na & Zhang, Jianghua, 2019. "Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 1-16.
    16. Zongjie Pi & Xin Gao & Linyan Chen & Jinghua Liu, 2019. "The New Path to Improve Construction Safety Performance in China: An Evolutionary Game Theoretic Approach," IJERPH, MDPI, vol. 16(13), pages 1-24, July.
    17. Liangdong Lu & Hong Huang & Jiuchang Wei & Jia Xu, 2020. "Safety Regulations and the Uncertainty of Work‐Related Road Accident Loss: The Triple Identity of Chinese Local Governments Under Principal–Agent Framework," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1168-1182, June.
    18. Shan, Xiaojun & Zhuang, Jun, 2013. "Hybrid defensive resource allocations in the face of partially strategic attackers in a sequential defender–attacker game," European Journal of Operational Research, Elsevier, vol. 228(1), pages 262-272.
    19. 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.
    20. Konrad, Renata A. & Trapp, Andrew C. & Palmbach, Timothy M. & Blom, Jeffrey S., 2017. "Overcoming human trafficking via operations research and analytics: Opportunities for methods, models, and applications," European Journal of Operational Research, Elsevier, vol. 259(2), pages 733-745.
    21. Sushil Gupta & Martin K. Starr & Reza Zanjirani Farahani & Niki Matinrad, 2016. "Disaster Management from a POM Perspective: Mapping a New Domain," Production and Operations Management, Production and Operations Management Society, vol. 25(10), pages 1611-1637, October.

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