IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2403.07928.html
   My bibliography  Save this paper

Strategic Bidding in Knapsack Auctions

Author

Listed:
  • Peyman Khezr
  • Vijay Mohan
  • Lionel Page

Abstract

This paper examines knapsack auctions as a method to solve the knapsack problem with incomplete information, where object values are private and sizes are public. We analyze three auction types-uniform price (UP), discriminatory price (DP), and generalized second price (GSP)-to determine efficient resource allocation in these settings. Using a Greedy algorithm for allocating objects, we analyze bidding behavior, revenue and efficiency of these three auctions using theory, lab experiments, and AI-enriched simulations. Our results suggest that the uniform-price auction has the highest level of truthful bidding and efficiency while the discriminatory price and the generalized second-price auctions are superior in terms of revenue generation. This study not only deepens the understanding of auction-based approaches to NP-hard problems but also provides practical insights for market design.

Suggested Citation

  • Peyman Khezr & Vijay Mohan & Lionel Page, 2024. "Strategic Bidding in Knapsack Auctions," Papers 2403.07928, arXiv.org, revised Apr 2024.
    • Handle: RePEc:arx:papers:2403.07928
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2403.07928
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peyman Khezr & Anne Cumpston, 2022. "A review of multiunit auctions with homogeneous goods," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1225-1247, September.
    2. Martino Banchio & Andrzej Skrzypacz, 2022. "Artificial Intelligence and Auction Design," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.
    3. Bae, Jinsoo & Kagel, John H., 2019. "An experimental study of the generalized second price auction," International Journal of Industrial Organization, Elsevier, vol. 63(C), pages 44-68.
    4. Lawrence M. Ausubel & Peter Cramton & Marek Pycia & Marzena Rostek & Marek Weretka, 2014. "Demand Reduction and Inefficiency in Multi-Unit Auctions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(4), pages 1366-1400.
    5. Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2007. "Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords," American Economic Review, American Economic Association, vol. 97(1), pages 242-259, March.
    6. Orly Sade & Charles Schnitzlein & Jaime F. Zender, 2006. "Competition and Cooperation in Divisible Good Auctions: An Experimental Examination," The Review of Financial Studies, Society for Financial Studies, vol. 19(1), pages 195-235.
    7. George B. Dantzig, 1957. "Discrete-Variable Extremum Problems," Operations Research, INFORMS, vol. 5(2), pages 266-288, April.
    8. Mu'alem, Ahuva & Nisan, Noam, 2008. "Truthful approximation mechanisms for restricted combinatorial auctions," Games and Economic Behavior, Elsevier, vol. 64(2), pages 612-631, November.
    9. repec:cup:cbooks:9781316779309 is not listed on IDEAS
    10. Roughgarden,Tim, 2016. "Twenty Lectures on Algorithmic Game Theory," Cambridge Books, Cambridge University Press, number 9781316624791.
    11. Roughgarden,Tim, 2016. "Twenty Lectures on Algorithmic Game Theory," Cambridge Books, Cambridge University Press, number 9781107172661.
    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. Vijay Mohan & Peyman Khezr, 2024. "Blockchains, MEV and the knapsack problem: a primer," Papers 2403.19077, arXiv.org.
    2. Mu'alem, Ahuva & Schapira, Michael, 2018. "Setting lower bounds on truthfulness," Games and Economic Behavior, Elsevier, vol. 110(C), pages 174-193.
    3. Tom Johnston & Michael Savery & Alex Scott & Bassel Tarbush, 2023. "Game Connectivity and Adaptive Dynamics," Papers 2309.10609, arXiv.org, revised Nov 2023.
    4. Konstantinos Georgalos & Indrajit Ray & Sonali SenGupta, 2020. "Nash versus coarse correlation," Experimental Economics, Springer;Economic Science Association, vol. 23(4), pages 1178-1204, December.
    5. Tommaso Denti & Doron Ravid, 2023. "Robust Predictions in Games with Rational Inattention," Papers 2306.09964, arXiv.org.
    6. Emerson Melo, 2021. "Learning in Random Utility Models Via Online Decision Problems," Papers 2112.10993, arXiv.org, revised Aug 2022.
    7. Ben Amiet & Andrea Collevecchio & Marco Scarsini & Ziwen Zhong, 2021. "Pure Nash Equilibria and Best-Response Dynamics in Random Games," Mathematics of Operations Research, INFORMS, vol. 46(4), pages 1552-1572, November.
    8. Estrella Alonso & Joaquín Sánchez-Soriano & Juan Tejada, 2020. "Mixed Mechanisms for Auctioning Ranked Items," Mathematics, MDPI, vol. 8(12), pages 1-26, December.
    9. Tim Roughgarden, 2018. "Complexity Theory, Game Theory, and Economics: The Barbados Lectures," Papers 1801.00734, arXiv.org, revised Feb 2020.
    10. Berliant, Marcus, 2017. "Commuting and internet traffic congestion," MPRA Paper 77378, University Library of Munich, Germany.
    11. Bayona, Anna & Brandts, Jordi & Vives, Xavier, 2020. "Information frictions and market power: A laboratory study," Games and Economic Behavior, Elsevier, vol. 122(C), pages 354-369.
    12. Cumpston, Anne & Khezr, Peyman, 2020. "Multi-Unit Auctions: A Survey of Theoretical Literature," MPRA Paper 101336, University Library of Munich, Germany.
    13. Schnitzlein, Charles R. & Shao, Minjie, 2013. "Capacity constraints and the winner's curse in multi-unit common value auctions," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(2), pages 188-201.
    14. Austin Knies & Jorge Lorca & Emerson Melo, 2020. "A Recursive Logit Model with Choice Aversion and Its Application to Transportation Networks," Papers 2010.02398, arXiv.org, revised Oct 2021.
    15. Shunta Akiyama & Mitsuaki Obara & Yasushi Kawase, 2022. "Optimal design of lottery with cumulative prospect theory," Papers 2209.00822, arXiv.org.
    16. Guillermo Angeris & Tarun Chitra & Theo Diamandis & Kshitij Kulkarni, 2023. "The Specter (and Spectra) of Miner Extractable Value," Papers 2310.07865, arXiv.org, revised Oct 2023.
    17. Campbell, Michael, 2020. "Speculative and hedging interaction model in oil and U.S. dollar markets—Long-term investor dynamics and phases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    18. Damianov, Damian S. & Oechssler, Jörg & Becker, Johannes Gerd, 2010. "Uniform vs. discriminatory auctions with variable supply - experimental evidence," Games and Economic Behavior, Elsevier, vol. 68(1), pages 60-76, January.
    19. Maryam Bahrani & Pranav Garimidi & Tim Roughgarden, 2023. "Transaction Fee Mechanism Design with Active Block Producers," Papers 2307.01686, arXiv.org, revised Oct 2023.
    20. Carlos Carrion & Zenan Wang & Harikesh Nair & Xianghong Luo & Yulin Lei & Xiliang Lin & Wenlong Chen & Qiyu Hu & Changping Peng & Yongjun Bao & Weipeng Yan, 2021. "Blending Advertising with Organic Content in E-Commerce: A Virtual Bids Optimization Approach," Papers 2105.13556, arXiv.org.

    More about this item

    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:arx:papers:2403.07928. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.