IDEAS home Printed from https://ideas.repec.org/a/eee/ijrema/v34y2017i1p120-136.html
   My bibliography  Save this article

The “tipping point” feature of social coupons: An empirical investigation

Author

Listed:
  • Hu, Mantian (Mandy)
  • Winer, Russell S.

Abstract

Groupon has pioneered a new business model that combines the features of daily deals and group buying. Utilizing a large proprietary dataset of Groupon users, the authors formulate three hypotheses about the effects of the tipping point (i.e., whether enough people have purchased the deal before it can be redeemed) on consumer behavior. The results indicate that (1) surprisingly, the tipping point does not stimulate consumers to refer the deal to others, (2) after controlling for detailed deal characteristics, information about the tipping point increases deal purchase probability and accelerates deal purchase speed by removing consumers' uncertainty about whether the deal will eventually tip, and (3) through a comparison of the different effects of prior purchases on purchase likelihood before and after a tipping point, conformity rather than social learning is identified as playing the dominant role in contagious purchases. Taken together, our results support the fact that the tipping point can alter consumer behavior and affect sales. However, recent changes made by Groupon are inconsistent with our empirical results and keeps the company from fully utilizing its potential. This study also provides an example of using web analytics tools to augment clickstream data and consolidate information from other sources.

Suggested Citation

  • Hu, Mantian (Mandy) & Winer, Russell S., 2017. "The “tipping point” feature of social coupons: An empirical investigation," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 120-136.
  • Handle: RePEc:eee:ijrema:v:34:y:2017:i:1:p:120-136
    DOI: 10.1016/j.ijresmar.2016.05.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167811616300507
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijresmar.2016.05.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    2. Ming Hu & Mengze Shi & Jiahua Wu, 2013. "Simultaneous vs. Sequential Group-Buying Mechanisms," Management Science, INFORMS, vol. 59(12), pages 2805-2822, December.
    3. Mark Bagnoli & Barton L. Lipman, 1989. "Provision of Public Goods: Fully Implementing the Core through Private Contributions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 56(4), pages 583-601.
    4. Alan L. Montgomery & Shibo Li & Kannan Srinivasan & John C. Liechty, 2004. "Modeling Online Browsing and Path Analysis Using Clickstream Data," Marketing Science, INFORMS, vol. 23(4), pages 579-595, November.
    5. Xiaoqing Jing & Jinhong Xie, 2011. "Group Buying: A New Mechanism for Selling Through Social Interactions," Management Science, INFORMS, vol. 57(8), pages 1354-1372, August.
    6. Enrico Moretti, 2011. "Social Learning and Peer Effects in Consumption: Evidence from Movie Sales," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(1), pages 356-393.
    7. Christophe Van den Bulte & Stefan Stremersch, 2004. "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test," Marketing Science, INFORMS, vol. 23(4), pages 530-544, July.
    8. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    9. Wendy W. Moe & Peter S. Fader, 2004. "Dynamic Conversion Behavior at E-Commerce Sites," Management Science, INFORMS, vol. 50(3), pages 326-335, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ming Hu & Xi Li & Mengze Shi, 2015. "Product and Pricing Decisions in Crowdfunding," Marketing Science, INFORMS, vol. 34(3), pages 331-345, May.
    2. Steven M. Shugan, 2005. "Brand Loyalty Programs: Are They Shams?," Marketing Science, INFORMS, vol. 24(2), pages 185-193.
    3. Kris J. Ferreira & Sunanda Parthasarathy & Shreyas Sekar, 2022. "Learning to Rank an Assortment of Products," Management Science, INFORMS, vol. 68(3), pages 1828-1848, March.
    4. Hui Li & Qiaowei Shen & Yakov Bart, 2018. "Local Market Characteristics and Online-to-Offline Commerce: An Empirical Analysis of Groupon," Management Science, INFORMS, vol. 64(4), pages 1860-1878, April.
    5. Benjamin Reed Shiller, 2020. "Approximating Purchase Propensities And Reservation Prices From Broad Consumer Tracking," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(2), pages 847-870, May.
    6. Duncan Sheppard Gilchrist & Emily Glassberg Sands, 2016. "Something to Talk About: Social Spillovers in Movie Consumption," Journal of Political Economy, University of Chicago Press, vol. 124(5), pages 1339-1382.
    7. Christa Brelsford & Caterina De Bacco, 2018. "Are `Water Smart Landscapes' Contagious? An epidemic approach on networks to study peer effects," Papers 1801.10516, arXiv.org.
    8. 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.
    9. Longyuan Du & Ming Hu & Jiahua Wu, 2022. "Contingent stimulus in crowdfunding," Production and Operations Management, Production and Operations Management Society, vol. 31(9), pages 3543-3558, September.
    10. Michael Bailey & Drew Johnston & Theresa Kuchler & Johannes Stroebel & Arlene Wong, 2022. "Peer Effects in Product Adoption," American Economic Journal: Applied Economics, American Economic Association, vol. 14(3), pages 488-526, July.
    11. Bi, Gongbing & Geng, Botao & Liu, Lindong, 2019. "On the fixed and flexible funding mechanisms in reward-based crowdfunding," European Journal of Operational Research, Elsevier, vol. 279(1), pages 168-183.
    12. Lizhen Xu & Jason A. Duan & Andrew Whinston, 2014. "Path to Purchase: A Mutually Exciting Point Process Model for Online Advertising and Conversion," Management Science, INFORMS, vol. 60(6), pages 1392-1412, June.
    13. T. Marshalkina V. & Т. Маршалкина В., 2015. "Модели Прогнозирования Спроса На Инновационную Продукцию // Models For Innovative Products Demand," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, issue 6, pages 171-178.
    14. Laciana, Carlos E. & Rovere, Santiago L. & Podestá, Guillermo P., 2013. "Exploring associations between micro-level models of innovation diffusion and emerging macro-level adoption patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1873-1884.
    15. Goh, Khim-Yong & Chu, Junhong & Wu, Jing, 2015. "Mobile Advertising: An Empirical Study of Temporal and Spatial Differences in Search Behavior and Advertising Response," Journal of Interactive Marketing, Elsevier, vol. 30(C), pages 34-45.
    16. Hinz, Oliver & Schulze, Christian & Takac, Carsten, 2014. "New product adoption in social networks: Why direction matters," Journal of Business Research, Elsevier, vol. 67(1), pages 2836-2844.
    17. Amedeo Piolatto, 2015. "Online booking and information: competition and welfare consequences of review aggregators," Working Papers 2015/11, Institut d'Economia de Barcelona (IEB).
    18. Pallant, Jason I. & Danaher, Peter J. & Sands, Sean J. & Danaher, Tracey S., 2017. "An empirical analysis of factors that influence retail website visit types," Journal of Retailing and Consumer Services, Elsevier, vol. 39(C), pages 62-70.
    19. Preyas S. Desai & Devavrat Purohit & Bo Zhou, 2018. "Allowing Consumers to Bundle Themselves: The Profitability of Family Plans," Marketing Science, INFORMS, vol. 37(6), pages 953-969, November.
    20. Simone Marinesi & Karan Girotra & Serguei Netessine, 2018. "The Operational Advantages of Threshold Discounting Offers," Management Science, INFORMS, vol. 64(6), pages 2690-2708, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ijrema:v:34:y:2017:i:1:p:120-136. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/international-journal-of-research-in-marketing/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.