Group buying in social coupon: Myths or facts
Refereed conference paper presented and published in conference proceedings


Times Cited
Altmetrics Information
.

Other information
AbstractThe social coupons industry, such as Groupon and LivingSocial, has experienced explosive growth in recent years. Social coupons that combine the features of daily deals and group buying create a new business strategy. In previous literature, theoretical hypotheses regarding this novel strategy have been developed. However, empirical investigation using real world data is few. In this paper, we aim to examine whether the group buying, as the main feature of social coupon, is effective. Utilizing a proprietary clickstream dataset about Groupon, we study three 'myths' about the group buying feature. We use Web tools to crawl information from other sources to augment clickstream data, and analytics tools to process and mine the information. From this study, we discover three significant 'facts' that: (1) group buying does not stimulate referrals, no matter whether the deal is tipped or not; (2) the information that the deal is tipped will increase purchase probability by removing consumer's uncertainty about whether the deal can tip or not eventually, and it will accelerate the purchase speed; (3) the information of prior purchases affects individual's purchase decision through the mechanism of herding rather than social learning. The findings suggest the effectiveness of the group buying feature in promoting purchase, as they change consumer behavior and affect sales.
All Author(s) ListMan Y., Hu M., King I.
Name of ConferenceInternational Joint Conference on Neural Networks, IJCNN 2015
Start Date of Conference12/07/2015
End Date of Conference17/07/2015
Place of ConferenceKillarney
Country/Region of ConferenceIreland
Detailed descriptionorganized by IJCNN 2015,
Year2015
Month9
Day28
Volume Number2015-September
ISBN9781479919604
LanguagesEnglish-United Kingdom
KeywordsAcceleration, Electronic publishing, Facebook, Graphics, Sociology, Statistics, Uniform resource locators

Last updated on 2020-29-11 at 00:56