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A group-buying mechanism for considering strategic consumer behavior

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  • Chenxu Ke

    (South China University of Technology)

  • Bo Yan

    (South China University of Technology)

  • Ruofan Xu

    (South China University of Technology)

Abstract

This study investigates a group-buying mechanism that considers strategic consumer behavior. In a market that consists of three types of consumers, the seller offers a product via two channels—spot purchasing and group buying—and maximizes his/her profit by setting the optimal group-buying threshold (G). Strategic consumers then choose one channel and enroll in the group based on the group-buying success rate and utility. Results show that consumer surplus decreases with increasing G and that two equilibria occur between the seller and strategic consumers. The behavior of the strategic consumers influences the group-buying success rate and the seller’s profit. We also discuss the optimization of G and the profit of the seller, and investigate the effects of the model parameters and demand volume on the optimal profit and optimal group-buying threshold G. When the retail inconvenience cost and risk aversion coefficient increase, the optimal profit decreases and the optimal G increases. However, when the demand of spot-purchasing consumers increases, the optimal profit increases and the optimal G decreases.

Suggested Citation

  • Chenxu Ke & Bo Yan & Ruofan Xu, 2017. "A group-buying mechanism for considering strategic consumer behavior," Electronic Commerce Research, Springer, vol. 17(4), pages 721-752, December.
  • Handle: RePEc:spr:elcore:v:17:y:2017:i:4:d:10.1007_s10660-016-9232-9
    DOI: 10.1007/s10660-016-9232-9
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    References listed on IDEAS

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    Cited by:

    1. Yi Cui & Jian Mou & Yanping Liu, 2018. "Knowledge mapping of social commerce research: a visual analysis using CiteSpace," Electronic Commerce Research, Springer, vol. 18(4), pages 837-868, December.
    2. Yao Tang, 2023. "A product strategy for daily deal campaigns utilizing demand expansion and consumer leakage," Electronic Commerce Research, Springer, vol. 23(3), pages 1861-1883, September.
    3. Qing Zhu & Renxian Zuo & Shan Liu & Fan Zhang, 2020. "Online dynamic group-buying community analysis based on high frequency time series simulation," Electronic Commerce Research, Springer, vol. 20(1), pages 81-118, March.
    4. Zuzana Svobodová & Jaroslava Rajchlová, 2020. "Strategic Behavior of E-Commerce Businesses in Online Industry of Electronics from a Customer Perspective," Administrative Sciences, MDPI, vol. 10(4), pages 1-24, October.
    5. Erbao Cao & He Li, 2020. "Group buying and consumer referral on a social network," Electronic Commerce Research, Springer, vol. 20(1), pages 21-52, March.

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