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Strategic Free Information Disclosure for a Vickrey Auction

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Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets (AMEC/TADA 2015, AMEC/TADA 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 271))

Abstract

In many auction settings we find a self-interested information broker, that can potentially disambiguate the uncertainty associated with the common value of the auctioned item (e.g., the true condition of an auctioned car, the sales forecast for a company offered for sale). This paper extends prior work, that has considered mostly the information pricing question in this archetypal three-ply bidders-auctioneer-information broker model, by enabling the information broker a richer strategic behavior in the form of anonymously eliminating some of the uncertainty associated with the common value, for free. The analysis of the augmented model enables illustrating two somehow non-intuitive phenomena in such settings: (a) the information broker indeed may benefit from disclosing for free some of the information she wishes to sell, even though this seemingly reduces the uncertainty her service aims to disambiguate; and (b) the information broker may benefit from publishing the free information to the general public rather than just to the auctioneer, hence preventing the edge from the latter, even if she is the only prospective customer of the service. While the extraction of the information broker’s optimal strategy is computationally hard, we propose two heuristics that rely on the variance between the different values, as means for generating potential solutions that are highly efficient. The importance of the results is primarily in providing information brokers with a new paradigm for improving their expected profit in auction settings. The new paradigm is also demonstrated to result, in some cases, in a greater social welfare, hence can be of much interest to market designers as well.

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Notes

  1. 1.

    Being rational, all bidders hold the same belief in equilibrium.

  2. 2.

    Our evaluation framework was built in Matlab R2011b and run on top of Windows7 on a PC with Intel(R) Xeon(R) CPU E5620 (2 processors) with 24.0 GB RAM.

  3. 3.

    For example, in oil drilling surveys, geologists usually specify 3–4 possible ranges for the amount of oil or gas that is likely to be found in a given area. Similarly, when requesting an estimate of the amount of traffic next to an advertising space, the answer would usually be in the form of ranges rather than exact numbers.

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Authors and Affiliations

  1. Bar-Ilan University, 52900, Ramat-Gan, Israel

    Shani Alkoby & David Sarne

Authors
  1. Shani Alkoby
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  2. David Sarne
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Corresponding author

Correspondence to Shani Alkoby .

Editor information

Editors and Affiliations

  1. School of Informatics, University of Edinburgh , Cambridge, United Kingdom

    Sofia Ceppi

  2. Department of Computer Science, Ashkelon Academic College , Ashkelon, Israel

    Esther David

  3. Department of EE and CS, Vanderbilt University , Nashville, Tennessee, USA

    Chen Hajaj

  4. Smart Systems Group, Heriot-Watt University , Edinburgh, United Kingdom

    Valentin Robu

  5. Information Technology, The American College of Greece , Agia Paraskevi, Athens, Greece

    Ioannis A. Vetsikas

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Alkoby, S., Sarne, D. (2017). Strategic Free Information Disclosure for a Vickrey Auction. In: Ceppi, S., David, E., Hajaj, C., Robu, V., Vetsikas, I. (eds) Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets. AMEC/TADA AMEC/TADA 2015 2016. Lecture Notes in Business Information Processing, vol 271. Springer, Cham. https://doi.org/10.1007/978-3-319-54229-4_1

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  • DOI: https://doi.org/10.1007/978-3-319-54229-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54228-7

  • Online ISBN: 978-3-319-54229-4

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