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Centralizing Inventory in Supply Chains by Using Shapley Value to Allocate the Profits

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  • Eda Kemahl{i}ou{g}lu-Ziya

    (Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-3490)

  • John J. Bartholdi, III

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

How should the excess profit because of inventory pooling be shared amongst firms at different levels along the supply chain? Suppose each of several retailers observes local demand for a common item and places an order at the supplier, which is immediately filled if the supplier has the item in stock. The supplier can fill retailer orders either from their reserved inventories or from a shareable pool of inventory. Using terminology from cooperative game theory, we say that the supplier and the retailers whose orders are filled from the common pool have formed an inventory-pooling coalition and study the use of Shapley value to allocate the expected excess profit because of pooling. We find that under Shapley value allocations the retailers have incentive to join the inventory-pooling coalition, and the supplier carries the level of inventory that is optimal for the coalition. Shapley value allocations might not lie within the core of the game, but the grand coalition of all players is stable in the farsighted sense. And, although the supplier's share of the expected excess profit is largest when all the retailers participate in the inventory-pooling coalition, the allocations to the retailers may diminish as the coalition grows. Colluding against the supplier (by merging and forming larger retailers) may seem like an appealing strategy for the retailers to increase their share of the total supply chain profit, but we find that the total expected after-pooling profits of retailers may instead go down because of collusion.

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  • Eda Kemahl{i}ou{g}lu-Ziya & John J. Bartholdi, III, 2011. "Centralizing Inventory in Supply Chains by Using Shapley Value to Allocate the Profits," Manufacturing & Service Operations Management, INFORMS, vol. 13(2), pages 146-162, September.
  • Handle: RePEc:inm:ormsom:v:13:y:2011:i:2:p:146-162
    DOI: 10.1287/msom.1100.0310
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    Cited by:

    1. Jiahua Zhang & Shu-Cherng Fang & Yifan Xu, 2018. "Inventory centralization with risk-averse newsvendors," Annals of Operations Research, Springer, vol. 268(1), pages 215-237, September.
    2. J. Zambujal-Oliveira, 2021. "Supply Chain Innovation Research: A Conceptual Approach of Information Management with Game Theory," Group Decision and Negotiation, Springer, vol. 30(2), pages 377-394, April.
    3. Fang Tian & Greys Sošić & Laurens Debo, 2019. "Manufacturers’ Competition and Cooperation in Sustainability: Stable Recycling Alliances," Management Science, INFORMS, vol. 65(10), pages 4733-4753, October.
    4. Xin Fang & Soo-Haeng Cho, 2014. "Stability and Endogenous Formation of Inventory Transshipment Networks," Operations Research, INFORMS, vol. 62(6), pages 1316-1334, December.
    5. Tian, Fang & Sošić, Greys & Debo, Laurens, 2020. "Stable recycling networks under the Extended Producer Responsibility," European Journal of Operational Research, Elsevier, vol. 287(3), pages 989-1002.
    6. Florian Kellner & Andreas Otto, 2012. "Allocating CO 2 emissions to shipments in road freight transportation," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 22(4), pages 451-479, January.
    7. Karsten, Frank & Basten, Rob J.I., 2014. "Pooling of spare parts between multiple users: How to share the benefits?," European Journal of Operational Research, Elsevier, vol. 233(1), pages 94-104.
    8. Konur, Dinçer, 2021. "Keep your enemy close? Competitive online brands’ expansion with individual and shared showrooms," Omega, Elsevier, vol. 99(C).
    9. Wang, Xinyu & Sethi, Suresh P. & Chang, Shuhua, 2022. "Pollution abatement using cap-and-trade in a dynamic supply chain and its coordination," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    10. Li, Jun & Feng, Hairong & Zeng, Yinlian, 2014. "Inventory games with permissible delay in payments," European Journal of Operational Research, Elsevier, vol. 234(3), pages 694-700.
    11. Fang Fang & Harihara Prasad Natarajan, 2020. "Sourcing and Procurement Cost Allocation in Multi‐Division Firms," Production and Operations Management, Production and Operations Management Society, vol. 29(3), pages 767-787, March.
    12. Lin, Jing & Ma, Xin & Talluri, Srinivas & Yang, Cheng-Hu, 2021. "Retail channel management decisions under collusion," European Journal of Operational Research, Elsevier, vol. 294(2), pages 700-710.
    13. Eirini Spiliotopoulou & Karen Donohue & Mustafa Çagri Gürbüz, 2022. "Ordering Behavior and the Impact of Allocation Mechanisms in an Integrated Distribution System," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 422-441, February.
    14. Jun Wang & Song Yao & Xinman Lu & Yu Li, 2019. "Organic Food Labeling and Advertising: A Tripartite Game Model between One Supplier and Two Heterogeneous Manufacturers," Complexity, Hindawi, vol. 2019, pages 1-14, November.
    15. Soo-Haeng Cho & Xin Wang, 2017. "Newsvendor Mergers," Management Science, INFORMS, vol. 63(2), pages 298-316, February.
    16. Feess, Eberhard & Thun, Jörn-Henrik, 2014. "Surplus division and investment incentives in supply chains: A biform-game analysis," European Journal of Operational Research, Elsevier, vol. 234(3), pages 763-773.
    17. Hezarkhani, Behzad & Slikker, Marco & Van Woensel, Tom, 2018. "Collaborative replenishment in the presence of intermediaries," European Journal of Operational Research, Elsevier, vol. 266(1), pages 135-146.

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