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A Subgame Perfect Approach to a Multi-Period Stackelberg Game with Dynamic, Price-Dependent, Distributional-Robust Demand

Author

Listed:
  • Fakhrabadi, Mahnaz

    (Dept. of Business and Management Science, Norwegian School of Economics)

  • Sandal, Leif K.

    (Dept. of Business and Management Science, Norwegian School of Economics)

Abstract

This paper investigates a multi-periodic channel optimization facing uncertain, price dependent, and dynamic demand. The picture of the market uncertainty is incomplete, and only the price and time-dependent mean and standard deviation are known and may depend on the price history. The actual demand distribution itself is unknown as is typically the case in real world problems. An algorithm finding the optimized decentralized channel equilibrium is developed when the downstream member optimizes her expected profit stream by a distributional-robust approach, and the upstream member (leader) considers it as the follower’s reaction function. The algorithm allows for strategic decisions whereby the current demand is scaled by the previous price setting.

Suggested Citation

  • Fakhrabadi, Mahnaz & Sandal, Leif K., 2023. "A Subgame Perfect Approach to a Multi-Period Stackelberg Game with Dynamic, Price-Dependent, Distributional-Robust Demand," Discussion Papers 2023/4, Norwegian School of Economics, Department of Business and Management Science.
    • Handle: RePEc:hhs:nhhfms:2023_004
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    File URL: https://hdl.handle.net/11250/3059803
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    References listed on IDEAS

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    1. Brojeswar Pal & Shib Sankar Sana & Kripasindhu Chaudhuri, 2015. "A distribution-free newsvendor problem with nonlinear holding cost," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(7), pages 1269-1277, May.
    2. Mostard, Julien & de Koster, Rene & Teunter, Ruud, 2005. "The distribution-free newsboy problem with resalable returns," International Journal of Production Economics, Elsevier, vol. 97(3), pages 329-342, September.
    3. Biswajit Sarkar & Chong Zhang & Arunava Majumder & Mitali Sarkar & Yong Won Seo, 2018. "A distribution free newsvendor model with consignment policy and retailer’s royalty reduction," International Journal of Production Research, Taylor & Francis Journals, vol. 56(15), pages 5025-5044, August.
    4. Irfanullah Khan & Biswajit Sarkar, 2021. "Transfer of Risk in Supply Chain Management with Joint Pricing and Inventory Decision Considering Shortages," Mathematics, MDPI, vol. 9(6), pages 1-20, March.
    5. Gregory A. Godfrey & Warren B. Powell, 2001. "An Adaptive, Distribution-Free Algorithm for the Newsvendor Problem with Censored Demands, with Applications to Inventory and Distribution," Management Science, INFORMS, vol. 47(8), pages 1101-1112, August.
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    More about this item

    Keywords

    Multi-Periodic problem; Stochasticity; Stackelberg Game; Subgame Perfect Distributional-Robust Approach; Supply Chain Management; Price-History Dependent Dynamic Demand;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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