IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v33y2022i4p1174-1195.html
   My bibliography  Save this article

Bidder Support in Multi-item Multi-unit Continuous Combinatorial Auctions: A Unifying Theoretical Framework

Author

Listed:
  • Gediminas Adomavicius

    (Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455)

  • Alok Gupta

    (Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455)

  • Mochen Yang

    (Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455)

Abstract

Despite known advantages of combinatorial auctions, wide adoption of this allocation mechanism, especially in consumer-oriented marketplaces, is limited partially by the lack of effective bidder support information that can assist bidders to make bidding decisions. In this paper, we study the bidder support problem for general multi-item multi-unit (MIMU) combinatorial auctions, where multiple heterogeneous items are being auctioned and multiple homogeneous units are available for each item. Specifically, we consider continuous MIMU auctions, which impose minimal restrictions on bidding activities, thereby reducing the complexity of participation. Two prevalent bidding languages: OR bidding and XOR bidding, are discussed separately. For MIMU auctions with XOR bids, we derive theoretical results to calculate important bidder support metrics. We further demonstrate that bidder support results for MIMU auctions with OR bids can be derived directly from those with XOR bids, by viewing OR bids as XOR bids with each bid submitted by a unique bidder. Consequently, we establish MIMU auctions with XOR bids as the most general case, and unify the theoretical insights on bidder support problem for different bidding languages as well as different special cases of general MIMU auctions, namely single-item multi-unit (SIMU) auctions and multi-item single-unit (MISU) auctions. The derived theoretical results lead to algorithmic procedures that are capable of providing bidder support information efficiently in practice, and that outperform the commonly used integer programming approach. Theoretical insights of the general MIMU auctions also extend to auctions with additional bidding constraints, including batch-based combinatorial auctions, hierarchical combinatorial auctions, and combinatorial reverse auctions.

Suggested Citation

  • Gediminas Adomavicius & Alok Gupta & Mochen Yang, 2022. "Bidder Support in Multi-item Multi-unit Continuous Combinatorial Auctions: A Unifying Theoretical Framework," Information Systems Research, INFORMS, vol. 33(4), pages 1174-1195, December.
  • Handle: RePEc:inm:orisre:v:33:y:2022:i:4:p:1174-1195
    DOI: 10.1287/isre.2021.1068
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.2021.1068
    Download Restriction: no

    File URL: https://libkey.io/10.1287/isre.2021.1068?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
    ---><---

    References listed on IDEAS

    as
    1. Peter Cramton, 2013. "Spectrum Auction Design," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 42(2), pages 161-190, March.
    2. Anthony M. Kwasnica & John O. Ledyard & Dave Porter & Christine DeMartini, 2005. "A New and Improved Design for Multiobject Iterative Auctions," Management Science, INFORMS, vol. 51(3), pages 419-434, March.
    3. Ausubel Lawrence M & Milgrom Paul R, 2002. "Ascending Auctions with Package Bidding," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 1(1), pages 1-44, August.
    4. Ioannis Petrakis & Georg Ziegler & Martin Bichler, 2013. "Ascending Combinatorial Auctions with Allocation Constraints: On Game Theoretical and Computational Properties of Generic Pricing Rules," Information Systems Research, INFORMS, vol. 24(3), pages 768-786, September.
    5. Gediminas Adomavicius & Alok Gupta, 2005. "Toward Comprehensive Real-Time Bidder Support in Iterative Combinatorial Auctions," Information Systems Research, INFORMS, vol. 16(2), pages 169-185, June.
    6. Sven de Vries & Rakesh V. Vohra, 2003. "Combinatorial Auctions: A Survey," INFORMS Journal on Computing, INFORMS, vol. 15(3), pages 284-309, August.
    7. Gediminas Adomavicius & Shawn P. Curley & Alok Gupta & Pallab Sanyal, 2012. "Effect of Information Feedback on Bidder Behavior in Continuous Combinatorial Auctions," Management Science, INFORMS, vol. 58(4), pages 811-830, April.
    8. Martin Bichler & Zhen Hao & Gediminas Adomavicius, 2017. "Coalition-Based Pricing in Ascending Combinatorial Auctions," Information Systems Research, INFORMS, vol. 28(1), pages 159-179, March.
    9. Michael H. Rothkopf, 2007. "Thirteen Reasons Why the Vickrey-Clarke-Groves Process Is Not Practical," Operations Research, INFORMS, vol. 55(2), pages 191-197, April.
    10. Sang Won Kim & Marcelo Olivares & Gabriel Y. Weintraub, 2014. "Measuring the Performance of Large-Scale Combinatorial Auctions: A Structural Estimation Approach," Management Science, INFORMS, vol. 60(5), pages 1180-1201, May.
    11. Martin Bichler & Pasha Shabalin & Alexander Pikovsky, 2009. "A Computational Analysis of Linear Price Iterative Combinatorial Auction Formats," Information Systems Research, INFORMS, vol. 20(1), pages 33-59, March.
    12. Xia, Mu & Stallaert, Jan & Whinston, Andrew B., 2005. "Solving the combinatorial double auction problem," European Journal of Operational Research, Elsevier, vol. 164(1), pages 239-251, July.
    13. Peter Cramton & Yoav Shoham & Richard Steinberg (ed.), 2006. "Combinatorial Auctions," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262033429, April.
    14. S.J. Rassenti & V.L. Smith & R.L. Bulfin, 1982. "A Combinatorial Auction Mechanism for Airport Time Slot Allocation," Bell Journal of Economics, The RAND Corporation, vol. 13(2), pages 402-417, Autumn.
    15. Robert W. Day & Peter Cramton, 2012. "Quadratic Core-Selecting Payment Rules for Combinatorial Auctions," Operations Research, INFORMS, vol. 60(3), pages 588-603, June.
    16. Tuomas Sandholm & Subhash Suri & Andrew Gilpin & David Levine, 2005. "CABOB: A Fast Optimal Algorithm for Winner Determination in Combinatorial Auctions," Management Science, INFORMS, vol. 51(3), pages 374-390, March.
    17. Tobias Scheffel & Alexander Pikovsky & Martin Bichler & Kemal Guler, 2011. "An Experimental Comparison of Linear and Nonlinear Price Combinatorial Auctions," Information Systems Research, INFORMS, vol. 22(2), pages 346-368, June.
    18. Brewer, Paul J. & Plott, Charles R., 1996. "A binary conflict ascending price (BICAP) mechanism for the decentralized allocation of the right to use railroad tracks," International Journal of Industrial Organization, Elsevier, vol. 14(6), pages 857-886, October.
    19. Michael H. Rothkopf & Aleksandar Pekev{c} & Ronald M. Harstad, 1998. "Computationally Manageable Combinational Auctions," Management Science, INFORMS, vol. 44(8), pages 1131-1147, August.
    20. Antonio Moreno & Christian Terwiesch, 2014. "Doing Business with Strangers: Reputation in Online Service Marketplaces," Information Systems Research, INFORMS, vol. 25(4), pages 865-886, December.
    21. Marcelo Olivares & Gabriel Y. Weintraub & Rafael Epstein & Daniel Yung, 2012. "Combinatorial Auctions for Procurement: An Empirical Study of the Chilean School Meals Auction," Management Science, INFORMS, vol. 58(8), pages 1458-1481, August.
    22. Lehmann, Benny & Lehmann, Daniel & Nisan, Noam, 2006. "Combinatorial auctions with decreasing marginal utilities," Games and Economic Behavior, Elsevier, vol. 55(2), pages 270-296, May.
    23. Elena Katok & Alvin E. Roth, 2004. "Auctions of Homogeneous Goods with Increasing Returns: Experimental Comparison of Alternative "Dutch" Auctions," Management Science, INFORMS, vol. 50(8), pages 1044-1063, August.
    24. Jeffrey S. Banks & John O. Ledyard & David P. Porter, 1989. "Allocating Uncertain and Unresponsive Resources: An Experimental Approach," RAND Journal of Economics, The RAND Corporation, vol. 20(1), pages 1-25, Spring.
    25. Goeree, Jacob K. & Holt, Charles A., 2010. "Hierarchical package bidding: A paper & pencil combinatorial auction," Games and Economic Behavior, Elsevier, vol. 70(1), pages 146-169, September.
    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. Pallab Sanyal, 2016. "Characteristics and Economic Consequences of Jump Bids in Combinatorial Auctions," Information Systems Research, INFORMS, vol. 27(2), pages 347-364, June.
    2. Gediminas Adomavicius & Shawn P. Curley & Alok Gupta & Pallab Sanyal, 2012. "Effect of Information Feedback on Bidder Behavior in Continuous Combinatorial Auctions," Management Science, INFORMS, vol. 58(4), pages 811-830, April.
    3. Andor Goetzendorff & Martin Bichler & Pasha Shabalin & Robert W. Day, 2015. "Compact Bid Languages and Core Pricing in Large Multi-item Auctions," Management Science, INFORMS, vol. 61(7), pages 1684-1703, July.
    4. Gediminas Adomavicius & Shawn P. Curley & Alok Gupta & Pallab Sanyal, 2020. "How Decision Complexity Affects Outcomes in Combinatorial Auctions," Production and Operations Management, Production and Operations Management Society, vol. 29(11), pages 2579-2600, November.
    5. Bart Vangerven & Dries R. Goossens & Frits C. R. Spieksma, 2021. "Using Feedback to Mitigate Coordination and Threshold Problems in Iterative Combinatorial Auctions," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(2), pages 113-127, April.
    6. Kemal Guler & Martin Bichler & Ioannis Petrakis, 2016. "Ascending Combinatorial Auctions with Risk Averse Bidders," Group Decision and Negotiation, Springer, vol. 25(3), pages 609-639, May.
    7. G. Anandalingam & Robert W. Day & S. Raghavan, 2005. "The Landscape of Electronic Market Design," Management Science, INFORMS, vol. 51(3), pages 316-327, March.
    8. Kazumori, Eiichiro & Belch, Yaakov, 2019. "t-Tree: The Tokyo toolbox for large-scale combinatorial auction experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 24(C).
    9. Ioannis Petrakis & Georg Ziegler & Martin Bichler, 2013. "Ascending Combinatorial Auctions with Allocation Constraints: On Game Theoretical and Computational Properties of Generic Pricing Rules," Information Systems Research, INFORMS, vol. 24(3), pages 768-786, September.
    10. Avenali, Alessandro, 2009. "Exploring the VCG mechanism in combinatorial auctions: The threshold revenue and the threshold-price rule," European Journal of Operational Research, Elsevier, vol. 199(1), pages 262-275, November.
    11. Jawad Abrache & Teodor Crainic & Michel Gendreau & Monia Rekik, 2007. "Combinatorial auctions," Annals of Operations Research, Springer, vol. 153(1), pages 131-164, September.
    12. Thomas Kittsteiner & Marion Ott & Richard Steinberg, 2022. "Competing Combinatorial Auctions," Information Systems Research, INFORMS, vol. 33(4), pages 1130-1137, December.
    13. Martin Bichler & Pasha Shabalin & Georg Ziegler, 2013. "Efficiency with Linear Prices? A Game-Theoretical and Computational Analysis of the Combinatorial Clock Auction," Information Systems Research, INFORMS, vol. 24(2), pages 394-417, June.
    14. Martin Bichler & Zhen Hao & Gediminas Adomavicius, 2017. "Coalition-Based Pricing in Ascending Combinatorial Auctions," Information Systems Research, INFORMS, vol. 28(1), pages 159-179, March.
    15. Scott Duke Kominers & Alexander Teytelboym & Vincent P Crawford, 2017. "An invitation to market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 541-571.
    16. Zhiling Guo & Gary J. Koehler & Andrew B. Whinston, 2012. "A Computational Analysis of Bundle Trading Markets Design for Distributed Resource Allocation," Information Systems Research, INFORMS, vol. 23(3-part-1), pages 823-843, September.
    17. Vangerven, Bart & Goossens, Dries R. & Spieksma, Frits C.R., 2017. "Winner determination in geometrical combinatorial auctions," European Journal of Operational Research, Elsevier, vol. 258(1), pages 254-263.
    18. Vohra, Rakesh V., 2015. "Combinatorial Auctions," Handbook of Game Theory with Economic Applications,, Elsevier.
    19. Larson, Nathan & Elmaghraby, Wedad, 2008. "Procurement auctions with avoidable fixed costs: an experimental approach," MPRA Paper 32163, University Library of Munich, Germany, revised 2011.
    20. De Liu & Adib Bagh, 2020. "Preserving Bidder Privacy in Assignment Auctions: Design and Measurement," Management Science, INFORMS, vol. 66(7), pages 3162-3182, July.

    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:inm:orisre:v:33:y:2022:i:4:p:1174-1195. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.