IDEAS home Printed from https://ideas.repec.org/a/eee/gamebe/v123y2020icp342-358.html
   My bibliography  Save this article

Clinching auctions with online supply

Author

Listed:
  • Goel, Gagan
  • Mirrokni, Vahab
  • Paes Leme, Renato

Abstract

Auctions for perishable goods such as Internet ad inventory need to make real-time allocation and pricing decisions as the supply of the good arrives in an online manner, without knowing the entire supply in advance. In this work, we consider a multi-unit model where buyers have global budget constraints, and the supply arrives in an online manner. Our main contribution is to show that for this setting there is an individually-rational, incentive-compatible and Pareto-optimal auction that allocates these units and calculates prices on the fly, without knowledge of the total supply. We do so by showing that the Adaptive Clinching Auction satisfies a supply-monotonicity property.

Suggested Citation

  • Goel, Gagan & Mirrokni, Vahab & Paes Leme, Renato, 2020. "Clinching auctions with online supply," Games and Economic Behavior, Elsevier, vol. 123(C), pages 342-358.
  • Handle: RePEc:eee:gamebe:v:123:y:2020:i:c:p:342-358
    DOI: 10.1016/j.geb.2015.11.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0899825615001566
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.geb.2015.11.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sushil Bikhchandani & Sven de Vries & James Schummer & Rakesh V. Vohra, 2011. "An Ascending Vickrey Auction for Selling Bases of a Matroid," Operations Research, INFORMS, vol. 59(2), pages 400-413, April.
    2. Roger B. Myerson, 1981. "Optimal Auction Design," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 58-73, February.
    3. Dobzinski, Shahar & Lavi, Ron & Nisan, Noam, 2012. "Multi-unit auctions with budget limits," Games and Economic Behavior, Elsevier, vol. 74(2), pages 486-503.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kazumura, Tomoya & Mishra, Debasis & Serizawa, Shigehiro, 2020. "Mechanism design without quasilinearity," Theoretical Economics, Econometric Society, vol. 15(2), May.
    2. SHINOZAKI, Hiroki, 2024. "Shill-proof rules in object allocation problems with money," Discussion paper series HIAS-E-137, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    3. Jinsoo Bae & John H. Kagel, 2022. "Selling shares to budget-constrained bidders: an experimental study of the proportional auction," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 8(1), pages 45-55, December.
    4. Piotr Dworczak & Scott Duke Kominers & Mohammad Akbarpour, 2021. "Redistribution Through Markets," Econometrica, Econometric Society, vol. 89(4), pages 1665-1698, July.
    5. Tomoya Kazumura & Debasis Mishra & Shigehiro Serizawa, 2017. "Strategy-proof multi-object auction design: Ex-post revenue maximization with no wastage," ISER Discussion Paper 1001, Institute of Social and Economic Research, Osaka University.
    6. Condorelli, Daniele, 2013. "Market and non-market mechanisms for the optimal allocation of scarce resources," Games and Economic Behavior, Elsevier, vol. 82(C), pages 582-591.
    7. Kotowski, Maciej H., 2020. "First-price auctions with budget constraints," Theoretical Economics, Econometric Society, vol. 15(1), January.
    8. Li, Yunan, 2017. "Approximation in mechanism design with interdependent values," Games and Economic Behavior, Elsevier, vol. 103(C), pages 225-253.
    9. Alireza Fallah & Michael I. Jordan & Annie Ulichney, 2024. "Fair Allocation in Dynamic Mechanism Design," Papers 2406.00147, arXiv.org, revised Oct 2024.
    10. Baisa, Brian, 2017. "Auction design without quasilinear preferences," Theoretical Economics, Econometric Society, vol. 12(1), January.
    11. Aadityan Ganesh & Jason Hartline, 2023. "Combinatorial Pen Testing (or Consumer Surplus of Deferred-Acceptance Auctions)," Papers 2301.12462, arXiv.org, revised Dec 2024.
    12. Paul Dütting & Felix Fischer & David C. Parkes, 2019. "Expressiveness and Robustness of First-Price Position Auctions," Mathematics of Operations Research, INFORMS, vol. 44(1), pages 196-211, February.
    13. Boulatov, Alexei & Severinov, Sergei, 2021. "Optimal and efficient mechanisms with asymmetrically budget constrained buyers," Games and Economic Behavior, Elsevier, vol. 127(C), pages 155-178.
    14. Hummel, Patrick, 2017. "Endogenous budget constraints," Mathematical Social Sciences, Elsevier, vol. 88(C), pages 11-15.
    15. Kevin Leyton-Brown & Paul Milgrom & Neil Newman & Ilya Segal, 2024. "Artificial Intelligence and Market Design: Lessons Learned from Radio Spectrum Reallocation," NBER Chapters, in: New Directions in Market Design, National Bureau of Economic Research, Inc.
    16. Dütting, Paul & Fischer, Felix & Parkes, David C., 2019. "Expressiveness and robustness of first-price position auctions," LSE Research Online Documents on Economics 85877, London School of Economics and Political Science, LSE Library.
    17. L. Elisa Celis & Gregory Lewis & Markus Mobius & Hamid Nazerzadeh, 2014. "Buy-It-Now or Take-a-Chance: Price Discrimination Through Randomized Auctions," Management Science, INFORMS, vol. 60(12), pages 2927-2948, December.
    18. Chen, Ning & Ghosh, Arpita & Lambert, Nicolas S., 2014. "Auctions for social lending: A theoretical analysis," Games and Economic Behavior, Elsevier, vol. 86(C), pages 367-391.
    19. Carbajal, Juan Carlos & Mu'alem, Ahuva, 2020. "Selling mechanisms for a financially constrained buyer," Games and Economic Behavior, Elsevier, vol. 124(C), pages 386-405.
    20. Tomoya Kazumura & Debasis Mishra & Shigehiro Serizawa, 2017. "Strategy-proof multi-object allocation: Ex-post revenue maximization with no wastage," Working Papers e116, Tokyo Center for Economic Research.

    More about this item

    Keywords

    Auction design; Online allocation; Online supply;
    All these keywords.

    JEL classification:

    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:gamebe:v:123:y:2020:i:c:p:342-358. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622836 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.