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Nash game model for optimizing market strategies, configuration of platform products in a Vendor Managed Inventory (VMI) supply chain for a product family

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  • Yu, Yugang
  • Huang, George Q.

Abstract

This paper discusses how a manufacturer and its retailers interact with each other to optimize their product marketing strategies, platform product configuration and inventory policies in a VMI (Vendor Managed Inventory) supply chain. The manufacturer procures raw materials from multiple suppliers to produce a family of products sold to multiple retailers. Multiple types of products are substitutable each other to end customers. The manufacturer makes its decision on raw materials' procurement, platform product configuration, product replenishment policies to retailers with VMI, price discount rate, and advertising investment to maximize its profit. Retailers in turn consider the optimal local advertising investments and retail prices to maximize their profits. This problem is modeled as a dual simultaneous non-cooperative game (as a dual Nash game) model with two sub-games. One is between the retailers serving in competing retail markets and the other is between the manufacturer and the retailers. This paper combines analytical, iterative and GA (genetic algorithm) methods to develop a game solution algorithm to find the Nash equilibrium. A numerical example is conducted to test the proposed model and algorithm, and gain managerial implications.

Suggested Citation

  • Yu, Yugang & Huang, George Q., 2010. "Nash game model for optimizing market strategies, configuration of platform products in a Vendor Managed Inventory (VMI) supply chain for a product family," European Journal of Operational Research, Elsevier, vol. 206(2), pages 361-373, October.
  • Handle: RePEc:eee:ejores:v:206:y:2010:i:2:p:361-373
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Pibernik, Richard & Zhang, Yingying & Kerschbaum, Florian & Schröpfer, Axel, 2011. "Secure collaborative supply chain planning and inverse optimization - The JELS model," European Journal of Operational Research, Elsevier, vol. 208(1), pages 75-85, January.
    2. Yu, Yugang & Wang, Zheng & Liang, Liang, 2012. "A vendor managed inventory supply chain with deteriorating raw materials and products," International Journal of Production Economics, Elsevier, vol. 136(2), pages 266-274.
    3. Aust, Gerhard & Buscher, Udo, 2012. "Vertical cooperative advertising and pricing decisions in a manufacturer–retailer supply chain: A game-theoretic approach," European Journal of Operational Research, Elsevier, vol. 223(2), pages 473-482.
    4. Aust, Gerhard & Buscher, Udo, 2014. "Cooperative advertising models in supply chain management: A review," European Journal of Operational Research, Elsevier, vol. 234(1), pages 1-14.
    5. Rezapour, Shabnam & Hassani, Ashkan & Farahani, Reza Zanjirani, 2015. "Concurrent design of product family and supply chain network considering quality and price," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 18-35.
    6. Egri, Péter & Váncza, József, 2013. "A distributed coordination mechanism for supply networks with asymmetric information," European Journal of Operational Research, Elsevier, vol. 226(3), pages 452-460.
    7. Huynh, Candice H. & Pan, Wenting, 2015. "Operational strategies for supplier and retailer with risk preference under VMI contract," International Journal of Production Economics, Elsevier, vol. 169(C), pages 413-421.
    8. Cai, Jianhu & Zhong, Man & Shang, Jennifer & Huang, Weilai, 2017. "Coordinating VMI supply chain under yield uncertainty: Option contract, subsidy contract, and replenishment tactic," International Journal of Production Economics, Elsevier, vol. 185(C), pages 196-210.
    9. Gerhard Aust & Udo Buscher, 2016. "Game theoretic analysis of pricing and vertical cooperative advertising of a retailer-duopoly with a common manufacturer," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(1), pages 127-147, March.
    10. Du, Gang & Jiao, Roger J. & Chen, Mo, 2014. "Joint optimization of product family configuration and scaling design by Stackelberg game," European Journal of Operational Research, Elsevier, vol. 232(2), pages 330-341.

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