skip to main content
10.1145/1242572.1242644acmconferencesArticle/Chapter ViewAbstractPublication PageswwwConference Proceedingsconference-collections
Article

Dynamics of bid optimization in online advertisement auctions

Published:08 May 2007Publication History

ABSTRACT

We consider the problem of online keyword advertising auctions among multiple bidders with limited budgets, and study a natural bidding heuristic in which advertisers attempt to optimize their utility by equalizing their return-on-investment across all keywords. We show that existing auction mechanisms combined with this heuristic can experience cycling (as has been observed in many current systems), and therefore propose a modified class of mechanisms with small random perturbations. This perturbation is reminiscent of the small time-dependent perturbations employed in the dynamical systems literature to convert many types of chaos into attracting motions. We show that the perturbed mechanism provably converges in the case of first-price auctions and experimentally converges in the case of second-price auctions. Moreover, the point of convergence has a natural economic interpretation as the unique market equilibrium in the case of first-price mechanisms. In the case of second-price auctions, we conjecture that it converges to the "supply-aware" market equilibrium. Thus, our results can be alternatively described as a tâtonnement process for convergence to market equilibriumin which prices are adjusted on the side of the buyers rather than the sellers. We also observe that perturbation in mechanism design is useful in a broader context: In general, it can allow bidders to "share" a particular item, leading to stable allocations and pricing for the bidders, and improved revenue for the auctioneer.

References

  1. G. Aggarwal, A. Goel, and R. Motwani. Truthful auctions for pricing search keywords. In Proceedings of the 7th ACM Conference on Electronic Commerce, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. K. Arrow and G. Debreu. Existence of an equilibrium for a competitive economy. Econometrica, 22:265--290, 1954.Google ScholarGoogle ScholarCross RefCross Ref
  3. M. Dellnitz, M. Field, M. Golubitsky, A. Hohmann, and J. Ma. Cycling chaos. Intern. J. Bifur. & Chaos, 5:1243--1247, 1995.Google ScholarGoogle ScholarCross RefCross Ref
  4. N. R. Devanur, C. H. Papadimitriou, A. Saberi, and V. V. Vazirani. Market equilibrium via a primal-dual-type algorithm. In Proceedings of the 43rd Symposium on Foundations of Computer Science, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. J. Feng, H. K. Bhargava, and D. Pennock. Comparison of allocation rules for paid placement advertising in search engines. In Proceedings of the 5th International Conference on Electronic Commerce, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. M. J. Field. Equivariant dynamical systems. Trans. Amer. Math. Soc., 259:185--205, 1980.Google ScholarGoogle ScholarCross RefCross Ref
  7. T. Ibaraki and N. Katoh. Resource Allocation Problems: Algorithmic Approaches. MIT Press, Cambridge, MA, 1988. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. O. H. Ibarra and C. E. Kim. Fast approximation algorithms for the knapsack and sum of subset problems. Journal of the ACM, 22(4):463--468, 1975. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. K. Jain and K. Talwar. Truth revealing market equilibria. Manuscript, 2004.Google ScholarGoogle Scholar
  10. C. Meek, D. Chickering, and D. Wilson. Stochastic and contingent-payment auctions. In 1st Workshop on Sponsored Search Auctions, 2005.Google ScholarGoogle Scholar
  11. M. Ostrovsky, B. Edelman, and M. Schwarz. Internet advertising and the generalized second price auction: Selling billions of dollars worth of keywords. In 2nd Workshop on Sponsored Search Auctions, 2006.Google ScholarGoogle Scholar
  12. E. Ott, C. Grebogi, and J. A. Yorke. Controlling chaos. Physics Review Letters, 64, 1990.Google ScholarGoogle Scholar
  13. A. Palacios. Cycling chaos in one-dimensional couple interated maps. Intern. J. Bifur. & Chaos, 12m:1859--1868, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  14. A. Palacios. Heteroclinic cycles in coupled systems of diference equations. J. Diference Eqs & Appl., 9:671--686, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  15. P. Rusmevichientong and D. Williamson. An adaptive algorithm for selecting profitable keywords for search-based advertising services. In Proceedings of the 7th ACM Conference on Electronic Commerce, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. H. Varian. Position auctions. Manuscript, 2006.Google ScholarGoogle Scholar
  17. X. M. Zhang and J. Feng. Price cycles in online advertising auctions. In Proceedings of the 26th International Conference on Information Systems (ICIS), 2005.Google ScholarGoogle Scholar

Index Terms

  1. Dynamics of bid optimization in online advertisement auctions

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      WWW '07: Proceedings of the 16th international conference on World Wide Web
      May 2007
      1382 pages
      ISBN:9781595936547
      DOI:10.1145/1242572

      Copyright © 2007 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 8 May 2007

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • Article

      Acceptance Rates

      Overall Acceptance Rate1,899of8,196submissions,23%

      Upcoming Conference

      WWW '24
      The ACM Web Conference 2024
      May 13 - 17, 2024
      Singapore , Singapore

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader