research-article

Third-Party Data Providers Ruin Simple Mechanisms

Authors:

Federico Echenique,

Katrina Ligett,

Juba ZianiAuthors Info & Claims

Proceedings of the ACM on Measurement and Analysis of Computing Systems, Volume 4, Issue 1

Article No.: 12, Pages 1 - 31

https://doi.org/10.1145/3379478

Published: 27 May 2020 Publication History

Abstract

Motivated by the growing prominence of third-party data providers in online marketplaces, this paper studies the impact of the presence of third-party data providers on mechanism design. When no data provider is present, it has been shown that simple mechanisms are "good enough'' -- they can achieve a constant fraction of the revenue of optimal mechanisms. The results in this paper demonstrate that this is no longer true in the presence of a third-party data provider who can provide the bidder with a signal that is correlated with the item type. Specifically, even with a single seller, a single bidder, and a single item of uncertain type for sale, the strategies of pricing each item-type separately (the analog of item pricing for multi-item auctions) and bundling all item-types under a single price (the analog of grand bundling) can both simultaneously be a logarithmic factor worse than the optimal revenue. Further, in the presence of a data provider, item-type partitioning mechanisms---a more general class of mechanisms which divide item-types into disjoint groups and offer prices for each group---still cannot achieve within a $łog łog$ factor of the optimal revenue. Thus, our results highlight that the presence of a data-provider forces the use of more complicated mechanisms in order to achieve a constant fraction of the optimal revenue.

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Cited By

Ko SMunagala K(2024)Optimal Price Discrimination for Randomized MechanismsACM Transactions on Economics and Computation10.1145/365010712:2(1-37)Online publication date: 5-Mar-2024
https://dl.acm.org/doi/10.1145/3650107
Ravindranath SJiang YParkes DOh ANaumann TGloberson ASaenko KHardt MLevine S(2023)Data market design through deep learningProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3666414(6662-6689)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.5555/3666122.3666414
Alijani RBanerjee SMunagala KWang KPennock DSegal ISeuken S(2022)The Limits of an Information Intermediary in Auction DesignProceedings of the 23rd ACM Conference on Economics and Computation10.1145/3490486.3538370(849-868)Online publication date: 12-Jul-2022
https://dl.acm.org/doi/10.1145/3490486.3538370
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Index Terms

Third-Party Data Providers Ruin Simple Mechanisms
1. Theory of computation
  1. Theory and algorithms for application domains
    1. Algorithmic game theory and mechanism design
      1. Algorithmic mechanism design

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cover image Proceedings of the ACM on Measurement and Analysis of Computing Systems

Proceedings of the ACM on Measurement and Analysis of Computing Systems Volume 4, Issue 1

SIGMETRICS

March 2020

467 pages

EISSN:2476-1249

DOI:10.1145/3402934

Editors:
Augustin Chaintreau
Columbia University
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Leana Golubchik
University of Southern California
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Zhi-Li Zhang
University of Minnesota

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Copyright © 2020 ACM.

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Publication History

Published: 27 May 2020

Online AM: 07 May 2020

Published in POMACS Volume 4, Issue 1

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Israel Science Foundation
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Fonds de Recherche du Québec - Nature et Technologies
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Cited By

Ko SMunagala K(2024)Optimal Price Discrimination for Randomized MechanismsACM Transactions on Economics and Computation10.1145/365010712:2(1-37)Online publication date: 5-Mar-2024
https://dl.acm.org/doi/10.1145/3650107
Ravindranath SJiang YParkes DOh ANaumann TGloberson ASaenko KHardt MLevine S(2023)Data market design through deep learningProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3666414(6662-6689)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.5555/3666122.3666414
Alijani RBanerjee SMunagala KWang KPennock DSegal ISeuken S(2022)The Limits of an Information Intermediary in Auction DesignProceedings of the 23rd ACM Conference on Economics and Computation10.1145/3490486.3538370(849-868)Online publication date: 12-Jul-2022
https://dl.acm.org/doi/10.1145/3490486.3538370
Ko SMunagala KPennock DSegal ISeuken S(2022)Optimal Price Discrimination for Randomized MechanismsProceedings of the 23rd ACM Conference on Economics and Computation10.1145/3490486.3538335(477-496)Online publication date: 12-Jul-2022
https://dl.acm.org/doi/10.1145/3490486.3538335

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