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An Evolutionary Game Theory Approach To Market Competition And Cooperation

Author

Listed:
  • ADRIAN VASILE

    (The Bucharest University of Economic Studies, Piata Romana Number 6, Sector 1, Bucharest, Code 010374, Romania)

  • CARMEN EUGENIA COSTEA

    (The Bucharest University of Economic Studies, Piata Romana Number 6, Sector 1, Bucharest, Code 010374, Romania)

  • TANIA GEORGIA VICIU

    (The Bucharest University of Economic Studies, Piata Romana Number 6, Sector 1, Bucharest, Code 010374, Romania)

Abstract

Evolutionary game theory can be attested as a practical apparatus in providing additional information on the workings of the open market and on the blueprint for dynamics in economic phenomena. Through an interdisciplinary approach to different game scenarios, the dependencies among market forces are observed, thus, being capable of offering insight on the incentives for adopting different behaviors. This paper takes use of the different factors that form the payoff of certain strategies which can be adopted by companies, and determines the prerequisites for cooperation or competition while all together constructing settings and predictions on the evolution of the phenomena. Determining the evolutionary stable strategy for different scenarios and looking at the way in which the probability of encountering a certain behavior is constructed, provide the possibility to determine the outcome of an ongoing evolutionary process. By studying the monotony of the probability function in respect to each of the factors that contribute to the payoffs, the study indicates that there is a positive relation between the percentage of population playing competitive strategies and market potential, costs, and risks of penalty for cooperation and a negative relation between this percentage and the disputed market share and supplementary winnings from arrangements.

Suggested Citation

  • Adrian Vasile & Carmen Eugenia Costea & Tania Georgia Viciu, 2012. "An Evolutionary Game Theory Approach To Market Competition And Cooperation," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(supp0), pages 1-15.
    • Handle: RePEc:wsi:acsxxx:v:15:y:2012:i:supp0:n:s0219525912500440
    DOI: 10.1142/S0219525912500440
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    References listed on IDEAS

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    1. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, December.
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    Cited by:

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    2. Vazirani, Ashish & Sarkar, Subhro & Bhattacharjee, Titas & Dwivedi, Yogesh K & Jack, Sarah, 2023. "Information signals and bias in investment decisions: A meta-analytic comparison of prediction and actual performance of new ventures," Journal of Business Research, Elsevier, vol. 155(PB).
    3. A-Ru-Han Bao & Yao Liu & Jun Dong & Zheng-Peng Chen & Zhen-Jie Chen & Chen Wu, 2022. "Evolutionary Game Analysis of Co-Opetition Strategy in Energy Big Data Ecosystem under Government Intervention," Energies, MDPI, vol. 15(6), pages 1-24, March.
    4. Lipovetsky, Stan & Conklin, Michael, 2014. "Finding items cannibalization and synergy by BWS data," Journal of choice modelling, Elsevier, vol. 12(C), pages 1-9.
    5. Hsi Tse Wang, 2020. "Discussion of the Competitive Strategies of Telecom Operators and Over-the-Top Service Providers from the Perspective of Evolutionary Game Theory," Decision Analysis, INFORMS, vol. 17(3), pages 260-275, September.

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