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Optimal decisions for fixed-price group-buying business originated in China: a game theoretic perspective

Author

Listed:
  • Guanqun Ni
  • Yinfeng Xu
  • Jiuping Xu
  • Yucheng Dong

Abstract

In this paper, we study a new group-buying mechanism originated in China where the new mechanism adopts a fixed group price rather than a dynamic pricing mechanism. We employ a sensitive parameter α$ \alpha $, reflecting the initial customer’s seeking and communication cost and formulate this new group-buying business as a game model. First, we formulate the basic model as a Stackelberg game where the website is the leader and the seller is the follower. Our result shows that the group-buying mechanism is more efficient when the value of α$ \alpha $ is smaller, and there is also an upper bound for α$ \alpha $ to adopt group-buying mechanism. Second, we establish three other group-buying game structures by considering different market power between the website and the seller. By comparing the maximum revenues and optimal decisions obtained under different market structures, some interesting and valuable managerial insights are established such that when to adopt a group-buying mechanism or a non-group-buying mechanism and how to make a decision optimally based on adopted mechanism.

Suggested Citation

  • Guanqun Ni & Yinfeng Xu & Jiuping Xu & Yucheng Dong, 2015. "Optimal decisions for fixed-price group-buying business originated in China: a game theoretic perspective," International Journal of Production Research, Taylor & Francis Journals, vol. 53(10), pages 2995-3005, May.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:10:p:2995-3005
    DOI: 10.1080/00207543.2014.965350
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    Cited by:

    1. Huang, Yeu-Shiang & Ho, Jyh-Wen & Lee, Chang-Lin, 2024. "Group buying in multiple channels with consideration of heterogeneous customers," International Journal of Production Economics, Elsevier, vol. 270(C).
    2. Shen-Tsu Wang & Meng-Hua Li & Chun-Chi Lien, 2019. "Optimal Multiple Attribute Decision Model for Key Parameters of Online Group Buying Product," Mathematics, MDPI, vol. 7(10), pages 1-21, September.
    3. Guanqun Ni, 2019. "A pricing model for group buying based on network effects," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-18, January.

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