Collective Attention and the Dynamics of Group Deals

10 Pages Posted: 27 Oct 2011 Last revised: 29 Nov 2011

See all articles by Mao Ye

Mao Ye

Hewlett-Packard Laboratories

Chunyan Wang

Stanford University - Department of Applied Physics

Christina Aperjis

Hewlett-Packard Enterprise - Social Computing Lab

Bernardo A. Huberman

CableLabs

Thomas E. Sandholm

Hewlett-Packard Laboratories

Date Written: October 25, 2011

Abstract

We present a study of the group purchasing behavior of daily deals in Groupon and LivingSocial and introduce a predictive dynamic model of collective attention for group buying behavior. In our model, the aggregate number of purchases at a given time comprises two types of processes: random discovery and social propagation. We find that these processes are very clearly separated by an inflection point. Using large data sets from both Groupon and LivingSocial we show how the model is able to predict the success of group deals as a function of time. We find that Groupon deals are easier to predict accurately earlier in the deal lifecycle than LivingSocial deals due to the final number of deal purchases saturating quicker. One possible explanation for this is that the incentive to socially propagate a deal is based on an individual threshold in LivingSocial whereas it is based on a collective threshold, which for the most part is reached very early on in Groupon. Furthermore, the personal benefit of propagating a deal is also greater in LivingSocial.

Keywords: economics of attention, group deals

JEL Classification: D70

Suggested Citation

Ye, Mao and Wang, Chunyan and Aperjis, Christina and Huberman, Bernardo A. and Sandholm, Thomas E., Collective Attention and the Dynamics of Group Deals (October 25, 2011). Available at SSRN: https://ssrn.com/abstract=1949452 or http://dx.doi.org/10.2139/ssrn.1949452

Mao Ye

Hewlett-Packard Laboratories ( email )

1501 Page Mill Road
Palo Alto, CA 94304
United States

Chunyan Wang

Stanford University - Department of Applied Physics ( email )

CA
United States

Christina Aperjis

Hewlett-Packard Enterprise - Social Computing Lab ( email )

1501 Page Mill Road
Palo Alto, CA 9434
United States

Bernardo A. Huberman (Contact Author)

CableLabs ( email )

400 W California Ave
Sunnyvale, CA 94086
United States

Thomas E. Sandholm

Hewlett-Packard Laboratories ( email )

1501 Page Mill Road
Palo Alto, CA 94304
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
213
Abstract Views
2,597
Rank
258,178
PlumX Metrics