Auctions with online supply

Moshe Babaioff, Liad Blumrosen, Aaron Roth*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Online advertising auctions present settings in which there is uncertainty about the number of items for sale. We study mechanisms for selling identical items when the total supply is unknown but is drawn from a known distribution. Items arrive dynamically, and the seller must make immediate allocation and payment decisions with the goal of maximizing social welfare. We devise a simple incentive-compatible mechanism that guarantees some constant fraction of the first-best solution. A surprising feature of our mechanism is that it artificially limits supply, and we show that limiting the supply is essential for obtaining high social welfare. Although common when maximizing revenue, commitment to limit the supply is less intuitive when maximizing social welfare. The performance guarantee of our mechanism is in expectation over the supply distribution; We show that obtaining similar performance guarantee for every realization of supply is impossible.

Original languageAmerican English
Pages (from-to)227-246
Number of pages20
JournalGames and Economic Behavior
StatePublished - 1 Mar 2015

Bibliographical note

Funding Information:
Aaron Roth was supported in part by an NSF Graduate Research Fellowship, and portions of his work were done while visiting Microsoft Research-Silicon Valley. Portions of this work were done while Liad Blumrosen was a post-doc researcher in Microsoft Research-Silicon Valley, and Liad Blumrosen was also supported by the Israel Science Foundation (grant No. 230/10 ) and by the Google Inter-university center for Electronic Markets and Auctions. We thank Andrew Goldberg and Ilya Segal for helpful discussions.

Publisher Copyright:
© 2015 Elsevier Inc.


  • Approximation
  • Dynamic auctions
  • Dynamic mechanism design
  • Online auctions
  • Stochastic supply
  • Unknown supply


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