Buy-it-now or take-a-chance: a simple sequential screening mechanism

Authors:
L. Elisa Celis;Gregory Lewis;Markus M. Mobius;Hamid Nazerzadeh
Affiliations:
University of Washington, Seattle, WA, USA;Harvard University, Cambridge, MA, USA;Harvard University, Cambridge, MA, USA;Microsoft Research, Cambridge, MA, USA
Venue:
Proceedings of the 20th international conference on World wide web
Year:
2011

Citing 4
Cited 1

Simple versus optimal mechanisms

Proceedings of the 10th ACM conference on Electronic commerce
Sponsored search with contexts

WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Computing optimal bundles for sponsored search

WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Multi-parameter mechanism design and sequential posted pricing

Proceedings of the forty-second ACM symposium on Theory of computing

Ad auctions with data

SAGT'12 Proceedings of the 5th international conference on Algorithmic Game Theory

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a simple auction mechanism which extends the second-price auction with reserve and is truthful in expectation. This mechanism is particularly effective in private value environments where the distribution of valuations are irregular. Bidders can "buy-it-now", or alternatively "take-a-chance" where the top d bidders are equally likely to win. The randomized take-a-chance allocation incentivizes high valuation bidders to buy-it-now. We show that for a large class of valuations, this mechanism achieves similar allocations and revenues as Myerson's optimal mechanism, and outperforms the second-price auction with reserve. In addition, we present an evaluation of bid data from Microsoft's AdECN platform. We find the valuations are irregular, and counterfactual experiments suggest our BIN-TAC mechanism would improve revenue by 11% relative to an optimal second-price mechanism with reserve.