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Competitive and Cooperative Assortment Games under Markov Chain Choice Model

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  • Kameng Nip
  • Changjun Wang
  • Zizhuo Wang

Abstract

In this work, we study the assortment planning games in which multiple retailers interact in the market. Each retailer owns some of the products and their goal is to select a subset of products, that is, an assortment to offer to the customers so as to maximize their expected revenue. The purchase behavior of the customer is assumed to follow the Markov chain choice model. We consider two types of assortment games under the Markov chain choice model—a competitive game and a cooperative game. In the assortment competition game, we show that there always exists a pure‐strategy Nash equilibrium and such equilibrium can be found in polynomial time. We also identify an easy‐to‐check condition for the uniqueness of the Nash equilibrium. Then we analyze the equilibrium outcome of this competition game, and compare the outcome with that in a monopolistic setting and a central planner setting. We show that under the assortment competition game, each retailer will offer a broader assortment in the equilibrium, which could include products that are not profitable in the monopolistic or the central planner setting, and it will eventually lead to a decrease in revenue for each player. Furthermore, we show that the price‐of‐anarchy and the price‐of‐stability of the game can be arbitrarily large. Motivated by these results, we further consider the assortment cooperation game under the Markov chain choice model, in which retailers are allowed to form coalitions. We consider two settings of cooperative games distinguished by the way we assume other players’ behaviors outside a coalition. Interestingly, we find that when the players are assumed to be intrinsically competitive (meaning that players outside a coalition are assumed to be a collection of competing players), then there is incentive for all the players to form a grand coalition and there exists an allocation of the total revenue that makes the coalition stable (exists a core to the game). However, when the players are assumed to be intrinsically collaborative (meaning that players outside a coalition are assumed to form another coalition), then a stable coalition may not exist.

Suggested Citation

  • Kameng Nip & Changjun Wang & Zizhuo Wang, 2022. "Competitive and Cooperative Assortment Games under Markov Chain Choice Model," Production and Operations Management, Production and Operations Management Society, vol. 31(3), pages 1033-1051, March.
  • Handle: RePEc:bla:popmgt:v:31:y:2022:i:3:p:1033-1051
    DOI: 10.1111/poms.13593
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    as
    1. Bloch, Francis & van den Nouweland, Anne, 2014. "Expectation formation rules and the core of partition function games," Games and Economic Behavior, Elsevier, vol. 88(C), pages 339-353.
    2. Parkash Chander & Henry Tulkens, 2006. "The Core of an Economy with Multilateral Environmental Externalities," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 153-175, Springer.
    3. A. Gürhan Kök & Yi Xu, 2011. "Optimal and Competitive Assortments with Endogenous Pricing Under Hierarchical Consumer Choice Models," Management Science, INFORMS, vol. 57(9), pages 1546-1563, February.
    4. Antoine Désir & Vineet Goyal & Danny Segev & Chun Ye, 2020. "Constrained Assortment Optimization Under the Markov Chain–based Choice Model," Management Science, INFORMS, vol. 66(2), pages 698-721, February.
    5. Wallace J. Hopp & Xiaowei Xu, 2008. "A Static Approximation for Dynamic Demand Substitution with Applications in a Competitive Market," Operations Research, INFORMS, vol. 56(3), pages 630-645, June.
    6. Hongmin Li & Woonghee Tim Huh, 2011. "Pricing Multiple Products with the Multinomial Logit and Nested Logit Models: Concavity and Implications," Manufacturing & Service Operations Management, INFORMS, vol. 13(4), pages 549-563, October.
    7. Jacob B. Feldman & Huseyin Topaloglu, 2017. "Revenue Management Under the Markov Chain Choice Model," Operations Research, INFORMS, vol. 65(5), pages 1322-1342, October.
    8. Csercsik, Dávid & Hubert, Franz & Sziklai, Balázs R. & Kóczy, László Á., 2019. "Modeling transfer profits as externalities in a cooperative game-theoretic model of natural gas networks," Energy Economics, Elsevier, vol. 80(C), pages 355-365.
    9. Xiaotie Deng & Qizhi Fang, 2008. "Algorithmic Cooperative Game Theory," Springer Optimization and Its Applications, in: Altannar Chinchuluun & Panos M. Pardalos & Athanasios Migdalas & Leonidas Pitsoulis (ed.), Pareto Optimality, Game Theory And Equilibria, pages 159-185, Springer.
    10. Guillermo Gallego & Richard Ratliff & Sergey Shebalov, 2015. "A General Attraction Model and Sales-Based Linear Program for Network Revenue Management Under Customer Choice," Operations Research, INFORMS, vol. 63(1), pages 212-232, February.
    11. Jose Blanchet & Guillermo Gallego & Vineet Goyal, 2016. "A Markov Chain Approximation to Choice Modeling," Operations Research, INFORMS, vol. 64(4), pages 886-905, August.
    12. Yang, Guangjing & Sun, Hao & Hou, Dongshuang & Xu, Genjiu, 2019. "Games in sequencing situations with externalities," European Journal of Operational Research, Elsevier, vol. 278(2), pages 699-708.
    13. Guillermo Gallego & Woonghee Tim Huh & Wanmo Kang & Robert Phillips, 2006. "Price Competition with the Attraction Demand Model: Existence of Unique Equilibrium and Its Stability," Manufacturing & Service Operations Management, INFORMS, vol. 8(4), pages 359-375, June.
    14. Margaret Aksoy-Pierson & Gad Allon & Awi Federgruen, 2013. "Price Competition Under Mixed Multinomial Logit Demand Functions," Management Science, INFORMS, vol. 59(8), pages 1817-1835, August.
    15. Guillermo Gallego & Huseyin Topaloglu, 2019. "Revenue Management and Pricing Analytics," International Series in Operations Research and Management Science, Springer, number 978-1-4939-9606-3, December.
    16. Alper Nakkas & Yasin Alan & Mümin Kurtuluş, 2020. "Category Captainship in the Presence of Retail Competition," Production and Operations Management, Production and Operations Management Society, vol. 29(2), pages 263-280, February.
    17. Xin Fang & Soo-Haeng Cho, 2020. "Cooperative Approaches to Managing Social Responsibility in a Market with Externalities," Manufacturing & Service Operations Management, INFORMS, vol. 22(6), pages 1215-1233, November.
    18. Haoying Sun & Stephen M. Gilbert, 2019. "Retail Price Competition with Product Fit Uncertainty and Assortment Selection," Production and Operations Management, Production and Operations Management Society, vol. 28(7), pages 1658-1673, July.
    19. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    20. Dan Zhang & William L. Cooper, 2005. "Revenue Management for Parallel Flights with Customer-Choice Behavior," Operations Research, INFORMS, vol. 53(3), pages 415-431, June.
    21. Imma Curiel, 2008. "Cooperative Combinatorial Games," Springer Optimization and Its Applications, in: Altannar Chinchuluun & Panos M. Pardalos & Athanasios Migdalas & Leonidas Pitsoulis (ed.), Pareto Optimality, Game Theory And Equilibria, pages 131-157, Springer.
    22. Omar Besbes & Denis Sauré, 2016. "Product Assortment and Price Competition under Multinomial Logit Demand," Production and Operations Management, Production and Operations Management Society, vol. 25(1), pages 114-127, January.
    23. James Dong & A. Serdar Simsek & Huseyin Topaloglu, 2019. "Pricing Problems under the Markov Chain Choice Model," Production and Operations Management, Production and Operations Management Society, vol. 28(1), pages 157-175, January.
    24. Marshall Fisher & Santiago Gallino & Jun Li, 2018. "Competition-Based Dynamic Pricing in Online Retailing: A Methodology Validated with Field Experiments," Management Science, INFORMS, vol. 64(6), pages 2496-2514, June.
    25. Guillermo Gallego & Ruxian Wang, 2014. "Multiproduct Price Optimization and Competition Under the Nested Logit Model with Product-Differentiated Price Sensitivities," Operations Research, INFORMS, vol. 62(2), pages 450-461, April.
    26. H. Sebastian Heese & Victor Martínez-de-Albéniz, 2018. "Effects of Assortment Breadth Announcements on Manufacturer Competition," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 302-316, May.
    27. Hafalir, Isa E., 2007. "Efficiency in coalition games with externalities," Games and Economic Behavior, Elsevier, vol. 61(2), pages 242-258, November.
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    2. Doug J. Chung & Kyoungwon Seo & Reo Song, 2023. "Efficient computation of discrete games: Estimating the effect of Apple on market structure," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2245-2263, July.

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