IDEAS home Printed from
   My bibliography  Save this article

Dynamics of business games with management of fuzzy rules for decision making


  • Oderanti, Festus Oluseyi
  • De Wilde, Philippe


Effective and efficient strategic decision making is the backbone for the success of a business organization. These decision making processes, used among its competitors in a particular industry, determine whether the business will continue to survive or not. In this research, fuzzy logic (FL) concept and game theory are being used to model strategic decision making processes by business organizations. Competition between business organizations is viewed as a game with each business organization as a player. A player formulates his own decisions by making his strategic moves based on uncertain information. This is the information he has about the opponents with respect to prevailing or anticipated market demand, cost of production, marketing, consolidation efforts and some other business variables. This uncertain information is being modelled using the concept of fuzzy logic. The game is played between a fuzzy agent and human agents in a resource allocation game between two players with uncertain information. Moreover, fuzzy rules are constructed that symbolize various rules and strategic variables that a firm takes into consideration before taking a decision. Our model also includes a learning procedure that enables the agent to optimize the fuzzy rules and his decision processes. Matlab software was used for the design and implementation of the fuzzy decision making system and this procedure and methodology can be easily implemented by business managers and can assist them in their strategic policy formulation.

Suggested Citation

  • Oderanti, Festus Oluseyi & De Wilde, Philippe, 2010. "Dynamics of business games with management of fuzzy rules for decision making," International Journal of Production Economics, Elsevier, vol. 128(1), pages 96-109, November.
  • Handle: RePEc:eee:proeco:v:128:y:2010:i:1:p:96-109

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Bogataj, Marija & Usenik, Janez, 2005. "Fuzzy approach to the spatial games in the total market area," International Journal of Production Economics, Elsevier, vol. 93(1), pages 493-503, January.
    2. Famuyiwa, Oluwafemi & Monplaisir, Leslie & Nepal, Bimal, 2008. "An integrated fuzzy-goal-programming-based framework for selecting suppliers in strategic alliance formation," International Journal of Production Economics, Elsevier, vol. 113(2), pages 862-875, June.
    3. Martin Shubik, 1952. "Information, Theories of Competition, and the Theory of Games," Journal of Political Economy, University of Chicago Press, vol. 60, pages 145-145.
    4. Bottani, Eleonora, 2009. "A fuzzy QFD approach to achieve agility," International Journal of Production Economics, Elsevier, vol. 119(2), pages 380-391, June.
    5. Karatzas, Ioannis & Shubik, Martin & Sudderth, William D., 1997. "A strategic market game with secured lending," Journal of Mathematical Economics, Elsevier, vol. 28(2), pages 207-247, September.
    6. Martin Shubik, 1972. "On the Scope of Gaming," Management Science, INFORMS, vol. 18(5-Part-2), pages 20-36, January.
    7. Isabelle Huault & V. Perret & S. Charreire-Petit, 2007. "Management," Post-Print halshs-00337676, HAL.
    8. Martin Shubik, 1955. "The Uses of Game Theory in Management Science," Management Science, INFORMS, vol. 2(1), pages 40-54, October.
    9. Chen, Shun-Hsing & Yang, Ching-Chow & Lin, Wen-Tsann & Yeh, Tsu-Ming, 2008. "Performance evaluation for introducing statistical process control to the liquid crystal display industry," International Journal of Production Economics, Elsevier, vol. 111(1), pages 80-92, January.
    10. Ertugrul Karsak, E. & Tolga, Ethem, 2001. "Fuzzy multi-criteria decision-making procedure for evaluating advanced manufacturing system investments," International Journal of Production Economics, Elsevier, vol. 69(1), pages 49-64, January.
    11. Martin Shubik, 1972. "On Gaming and Game Theory," Management Science, INFORMS, vol. 18(5-Part-2), pages 37-53, January.
    12. Franklin M. Fisher, 1989. "Games Economists Play: A Noncooperative View," RAND Journal of Economics, The RAND Corporation, vol. 20(1), pages 113-124, Spring.
    13. Wu, Y. & Zhang, D.Z., 2007. "Demand fluctuation and chaotic behaviour by interaction between customers and suppliers," International Journal of Production Economics, Elsevier, vol. 107(1), pages 250-259, May.
    14. Gungor, Zulal & Arikan, Feyzan, 2000. "Application of fuzzy decision making in part-machine grouping," International Journal of Production Economics, Elsevier, vol. 63(2), pages 181-193, January.
    15. Kahraman, Cengiz & Cebeci, Ufuk & Ruan, Da, 2004. "Multi-attribute comparison of catering service companies using fuzzy AHP: The case of Turkey," International Journal of Production Economics, Elsevier, vol. 87(2), pages 171-184, January.
    16. Lewis, Michael A. & Maylor, Harvey R., 2007. "Game playing and operations management education," International Journal of Production Economics, Elsevier, vol. 105(1), pages 134-149, January.
    17. Abreu, Dilip & Rubinstein, Ariel, 1988. "The Structure of Nash Equilibrium in Repeated Games with Finite Automata," Econometrica, Econometric Society, vol. 56(6), pages 1259-1281, November.
    18. Irani, Zahir & Sharif, Amir & Love, Peter E. D. & Kahraman, Cengiz, 2002. "Applying concepts of fuzzy cognitive mapping to model: The IT/IS investment evaluation process," International Journal of Production Economics, Elsevier, vol. 75(1-2), pages 199-211, January.
    19. M. Shubik, 1960. "Games Decisions and Industrial Organization," Management Science, INFORMS, vol. 6(4), pages 455-474, July.
    Full references (including those not matched with items on IDEAS)


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:128:y:2010:i:1:p:96-109. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.