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Risk, production and conflict when utilities are as if certain

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  • Kjell Hausken

Abstract

The article analyses a production and conflict model of risk, supplementing the common rent seeking analysis. Agents differ in attitudes toward risk, productive efficiencies, fighting efficiencies and resources for production versus fighting. A fighting decisiveness parameter determines distribution of utilities. Skaperdas' (1991) analysis of conflict and risk attitudes is generalised from a symmetric to an asymmetric risk function, from two agents to many agents of two kinds, and the fraction of risk seekers is endogenised. Specific functional forms of the utility function and production function are used. The amount of fighting increases in the amount of risk aversion, contrary to received rent seeking theory, but consistently with much experience. Surprisingly, higher production costs or lower fighting costs for risk seekers cause higher utility for risk seekers, contrary to the received theory of higher utility to risk avoiders. We show how the first agent taking on risk benefits, given that the other agents remain risk averse, whereas risk seeking by all agents is the worst scenario.

Suggested Citation

  • Kjell Hausken, 2010. "Risk, production and conflict when utilities are as if certain," International Journal of Decision Sciences, Risk and Management, Inderscience Enterprises Ltd, vol. 2(3/4), pages 228-251.
    • Handle: RePEc:ids:ijdsrm:v:2:y:2010:i:3/4:p:228-251
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    Citations

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    Cited by:

    1. Yong Wu & Gengzhong Feng & Richard Y. K. Fung, 2018. "Comparison of information security decisions under different security and business environments," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(5), pages 747-761, May.
    2. Wu, Di & Yan, Xiangbin & Peng, Rui & Wu, Shaomin, 2020. "Risk-attitude-based defense strategy considering proactive strike, preventive strike and imperfect false targets," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    3. Zhang, Jing & Wang, Yan & Zhuang, Jun, 2021. "Modeling multi-target defender-attacker games with quantal response attack strategies," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    4. Szidarovszky, Ferenc & Luo, Yi, 2014. "Incorporating risk seeking attitude into defense strategy," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 104-109.
    5. Zhang, Jing & Zhuang, Jun & Jose, Victor Richmond R., 2018. "The role of risk preferences in a multi-target defender-attacker resource allocation game," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 95-104.
    6. Hunt, Kyle & Agarwal, Puneet & Zhuang, Jun, 2022. "On the adoption of new technology to enhance counterterrorism measures: An attacker–defender game with risk preferences," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    7. Lin, Chen & Xiao, Hui & Peng, Rui & Xiang, Yisha, 2021. "Optimal defense-attack strategies between M defenders and N attackers: A method based on cumulative prospect theory," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    8. Kjell Hausken & Mthuli Ncube, 2016. "How Elections are Impacted by Production, Economic Growth and Conflict," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 1-29, March.
    9. Hausken, Kjell & Ncube, Mthuli, 2012. "Production and Conflict in Risky Elections," UiS Working Papers in Economics and Finance 2012/14, University of Stavanger.

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