INFORMS Open Forum

  • 1.  A New Approach to Strategic Analysis for a Changing World

    Posted 11 days ago

    Changing global conditions bring new challenges for corporate boards and strategists. Deglobalization, economic instability, political and military crises as well as the rapid development of information technologies, especially artificial intelligence, are creating problems that managers have not faced in such an intense and complex form for decades. The situation is deteriorating rapidly and decision-makers must respond without delay.

    The first step toward making sound strategic decisions consistent with the OODA loop framework is to observe key factors and orient ourselves to the changing environment. However, traditional tools of strategic analysis long relied upon for this purpose may no longer be sufficient. Their limitations stem primarily from their static nature and inability to leverage the full potential of modern information technologies, especially AI.

    In response to these challenges, our team is developing scientific solutions grounded in game theory to help corporate boards and strategists make more informed decisions in turbulent times. Our ambition is not only to provide fresh insights for decision-makers but also to lay the logical foundation for AI-driven decision support systems.

    We are particularly focused on the phenomenon of co-opetition, which is the simultaneous cooperation and competition between entities. As our main methodological approach, we employ game theory with a special emphasis on biform games, which are well suited to modeling dynamic transitions between competitive and cooperative behaviors.

    Similar approaches have also been discussed in the literature, reflecting a growing academic interest in dynamic models of strategic interaction:

    • Alparslan Gök, S. Z., and Özcan, I. (2023). On big boss fuzzy interval games. European Journal of Operational Research, 306(3), 1040–1046.

    • Özcan, İ., Śledziński, J. D., Gök, S. Z. A., Butlewski, M., and Weber, G. W. (2023). Mathematical encouragement of companies to cooperate by using cooperative games with fuzzy approach. Journal of Industrial and Management Optimization, 19(10), 7180–7195.

    • Özcan, İ., Śledziński, J. D., Gök, S. Z. A., Meca, A., Weber, G. W., Butlewski, M., and Kocadag, E. (2025). A game theory perspective on strategic profit distribution in complex IT projects. Journal of Industrial and Management Optimization, 21(2), 1503–1517.

    With warm regards,

    Jacek Dominik Śledziński
    Faculty of Engineering Management, Poznan University of Technology
    📧 jacek.dominic@gmail.com

    İsmail Özcan   (Contact person)
    PhD
    📧 ismailozcanmath@gmail.com

    Gerhard-Wilhelm Weber
    Faculty of Engineering Management, Poznan University of Technology
    📧 gerhard.weber@put.poznan.pl



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    Gerhard-Wilhelm Weber
    Professor
    Poznan University of Technology
    Poznan
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  • 2.  RE: A New Approach to Strategic Analysis for a Changing World

    Posted 10 days ago

    Re: "traditional tools of strategic analysis long relied upon for this purpose may no longer be sufficient. Their limitations stem primarily from their static nature and inability to leverage the full potential of modern information technologies, especially AI."

    A methodology for sequential decision-making in OR/MS was developed a while ago that reflects how develop/update a new decision based on the previous one to model the evolution of the system over time, i.e. dynamic decision-making.

    See, e.g. Warren Powell, "Reinforcement Learning and Stochastic Optimization", Wiley, 2022.

    What can AI-driven support system add to this methodology? And how do you define what is AI in this context?

    Cooperative and competitive/uncooperative game theory was known for a long time. It is based on assumption of rationality of the players. In real life problems, this assumption has been refuted. So, what is the advantage of game theory vs. sequential dynamic decision-making?

    Thanks



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    Alexander Kolker
    ge healthcare
    MILWAUKEE WI
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  • 3.  RE: A New Approach to Strategic Analysis for a Changing World

    Posted 10 days ago
    Edited by Gerhard-Wilhelm Weber 10 days ago

    Dear Alexander Kolker,

    Classical game theory assumes fully rational agents, a premise often challenged by real-world bounded rationality and behavioral complexity. Despite this, it remains unique in formally modeling complex strategic interdependencies among multiple decision-makers. Sequential dynamic decision-making, by contrast, focuses on optimizing individual agents' decisions over time but lacks comprehensive treatment of multi-agent interactions.

    Artificial intelligence enhances this framework by enabling adaptive, data-driven learning that supports real-time adjustment, continual updating, and effective uncertainty management. Methods such as multi-agent reinforcement learning allow game-theoretic models to dynamically incorporate evolving behaviors and incomplete information.

    This synergy enables analysis of emergent phenomena including spontaneous cooperation, shifting alliances, and nuanced signaling in uncertain, co-opetitive contexts. While sequential models optimize individual strategies, AI-augmented game theory uniquely captures adaptive, collective dynamics, offering richer insights and more robust decision support for complex strategic environments, such as the incorporation of uncertainty sets-including polyhedral, fuzzy, ellipsoidal, and stochastic models-demonstrated in robust decision-making frameworks:

    • Alparslan Gök S.Z., Ergün, S., Kırlar, B. B., Özcan, İ., & Tayman, A. (2023). Fuzzy perspective of online games by using cryptography and cooperative game theory. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems31(06), 891-915.
    • Özmen, A., & Weber, G. W. (2014). RMARS: robustification of multivariate adaptive regression spline under polyhedral uncertainty. Journal of Computational and Applied Mathematics259, 914-924.
    • Savku, E., & Weber, G. W. (2022). Stochastic differential games for optimal investment problems in a Markov regime-switching jump-diffusion market. Annals of Operations Research312(2), 1171-1196.

    With warm regards,

    Jacek Dominik Śledziński
    Faculty of Engineering Management, Poznan University of Technology
    📧 jacek.dominic@gmail.com

    İsmail Özcan   (Contact person)
    PhD
    📧 ismailozcanmath@gmail.com

    Gerhard-Wilhelm Weber
    Faculty of Engineering Management, Poznan University of Technology
    📧 gerhard.weber@put.poznan.pl



    ------------------------------
    Gerhard-Wilhelm Weber
    Professor
    Poznan University of Technology
    Poznan
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  • 4.  RE: A New Approach to Strategic Analysis for a Changing World

    Posted 9 days ago

    Gerhard, I see you mentioned biform games.  I thought they were deprecated now.  Dror and Summerfield showed they were just a form of stochastic decision making.  I was around at the time Nichalin and Moshe wrote the paper.  It's interesting, given Alexander's comment.



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    Bruce Hartman
    Professor
    University of St. Francis
    Tucson, AZ United States
    bruce@ahartman.net
    website: https://sites.google.com/ahartman.net/drbrucehartman/Home
    blog:http://supplychainandlogistics.org
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  • 5.  RE: A New Approach to Strategic Analysis for a Changing World

    Posted 9 days ago

    Bruce, I agree with you. On top of that, my concern was how AI and its role was defined in the discussed context.

    So far, I saw only some  slogans/buzzwords like "AI enhances this framework....". It was not large language model (LLM), but what was it? In what way it enhances...data-driven learning..

    ?



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    Alexander Kolker
    ge healthcare
    MILWAUKEE WI
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  • 6.  RE: A New Approach to Strategic Analysis for a Changing World

    Posted 9 days ago

    Dear Professors,

    First of all, thank you very much for your responses.  The theoretical and methodological advancements we have made in extending biform games beyond their traditional boundaries offer a significant contribution to existing strategic decision modeling approaches. Our approach transcends static and outdated formulations by integrating biform structures into a dynamic, AI-augmented decision-making framework capable of modeling real-time transitions between cooperation and competition. Such dynamics are indispensable for capturing the complexity of contemporary strategic interactions.

    Our contribution goes beyond a mere refinement; it presents a mathematically rigorous and conceptually coherent framework explicitly designed for robust application under conditions of uncertainty. The geometric formalization of uncertainty sets facilitates both intuitive interpretability and analytical precision, thereby enhancing the framework's theoretical soundness and practical viability. This methodology synthesizes classical, fuzzy, and stochastic paradigms into a unified and flexible modeling architecture. Within this context, some key studies that could serve as the theoretical foundation for our proposed biform game modeling are as follows:

    • Kropat, E., Weber, G. W., & Tirkolaee, E. B. (2020). Foundations of semialgebraic gene-environment networks. Journal of Dynamics & Games7(4), 253-268.
    • Savku, E., & Weber, G. W. (2018). A stochastic maximum principle for a markov regime-switching jump-diffusion model with delay and an application to finance. Journal of optimization theory and applications179(2), 696-721.
    • Weber, G. W., Defterli, O., Gök, S. Z. A., & Kropat, E. (2011). Modeling, inference and optimization of regulatory networks based on time series data. European Journal of Operational Research211(1), 1-14.

    Consequently, assessments that rely solely on the limitations of earlier biform game models may inadvertently overlook the potential of this renewed formulation. By employing advanced mathematical tools and integrating them within AI-driven systems, our contribution represents not a reiteration of existing models, but a substantial reconfiguration-one that advances the theoretical foundations and broadens the practical scope of strategic decision modeling.

    With warm regards,

    Jacek Dominik Śledziński
    Faculty of Engineering Management, Poznan University of Technology
    📧 jacek.dominic@gmail.com

    İsmail Özcan   (Corresponding Author)
    PhD
    📧 ismailozcanmath@gmail.com

    Gerhard-Wilhelm Weber
    Faculty of Engineering Management, Poznan University of Technology
    📧 gerhard.weber@put.poznan.pl



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    Gerhard-Wilhelm Weber
    Professor
    Poznan University of Technology
    Poznan
    ------------------------------