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Threshold Effects in Online Group Buying

Author

Listed:
  • Jiahua Wu

    (Imperial College Business School, Imperial College London, London SW7 2AZ, United Kingdom)

  • Mengze Shi

    (Rotman School of Management, University of Toronto, Toronto, Ontario M5S 3E6, Canada)

  • Ming Hu

    (Rotman School of Management, University of Toronto, Toronto, Ontario M5S 3E6, Canada)

Abstract

This paper studies two types of threshold-induced effects: a surge of new sign-ups around the time when the thresholds of group-buying deals are reached, and a stronger positive relation between the number of new sign-ups and the cumulative number of sign-ups before the thresholds are reached than afterward. This empirical study uses a data set that records the intertemporal cumulative number of sign-ups for group-buying deals in 86 city markets covered by Groupon, during a period of 71 days when Groupon predominantly used “a deal a day” format for each local market and posted the number of sign-ups in real time. We find that the first type of threshold effect is significant in all product categories and in all markets. The second type of threshold effect varies across product categories and markets. Our results underscore the importance of considering product and market characteristics in threshold design decisions for online group buying.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.2015 . This paper was accepted by Pradeep Chintagunta, marketing .

Suggested Citation

  • Jiahua Wu & Mengze Shi & Ming Hu, 2015. "Threshold Effects in Online Group Buying," Management Science, INFORMS, vol. 61(9), pages 2025-2040, September.
    • Handle: RePEc:inm:ormnsc:v:61:y:2015:i:9:p:2025-2040
    DOI: 10.1287/mnsc.2014.2015
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    References listed on IDEAS

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    6. Zike Cao & Kai-Lung Hui & Hong Xu, 2018. "When Discounts Hurt Sales: The Case of Daily-Deal Markets," Information Systems Research, INFORMS, vol. 29(3), pages 567-591, September.
    7. Jenn-Bing Ong & Wee-Keong Ng & Artem Vorobev & Thanh-Nghia Ho, 2019. "Groupon and Groupon Now: Participating Firm’s Profitability Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 617-632, February.
    8. Jochen Reiner & Bernd Skiera, 2018. "Helping Merchants to Assess the Profitability of Deal-of-the-Day Promotions," Interfaces, INFORMS, vol. 48(3), pages 247-259, June.
    9. Liu, Hongfei & Jayawardhena, Chanaka & Shukla, Paurav & Osburg, Victoria-Sophie & Yoganathan, Vignesh, 2024. "Electronic word of mouth 2.0 (eWOM 2.0) – The evolution of eWOM research in the new age," Journal of Business Research, Elsevier, vol. 176(C).
    10. Tang, Yao & Chen, Rachel R. & Guan, Xu, 2021. "Daily-deal market with consumer retention: Price discrimination or quality differentiation," Omega, Elsevier, vol. 102(C).
    11. Ming Hu & Joseph Milner & Jiahua Wu, 2016. "Liking and Following and the Newsvendor: Operations and Marketing Policies Under Social Influence," Management Science, INFORMS, vol. 62(3), pages 867-879, March.
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    13. Francesca De Canio & Marco Ieva & Cristina Ziliani, 2017. "Beyond the "mobile versus PC" dichotomy: Profiling online shoppers based on device usage," MERCATI & COMPETITIVIT?, FrancoAngeli Editore, vol. 2017(2), pages 99-121.
    14. Xitong Li, 2018. "Impact of Average Rating on Social Media Endorsement: The Moderating Role of Rating Dispersion and Discount Threshold," Information Systems Research, INFORMS, vol. 29(3), pages 739-754, September.
    15. Xia, Feihong & Chatterjee, Rabikar & Venkatesh, R., 2022. "Clinching the deal: An empirical study of the drivers of diffusion of daily deals," Journal of Business Research, Elsevier, vol. 149(C), pages 824-832.
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    18. 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.

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    threshold effects; group buying;

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