Year: 2018
Type: preprint
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 $\log \log$ 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.
Source: arXiv (Cornell University)
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
Funders: National Science Foundation, Alfred P. Sloan Foundation, California Institute of Technology, Hebrew University of Jerusalem, Israel Science Foundation, Israel National Cyber Directorate, Defense Advanced Research Projects Agency, Natural Sciences and Engineering Research Council of Canada, Fonds de recherche du Québec – Nature et technologies
Awards: G2630897251, BSF:2012348:The Boundaries of Privacy, G4713059963, G560051739, CAREER: The Value of Privacy, G6378952298, AitF: Algorithmic challenges in smart grids: control, optimization & learning, Choices under Uncertainty, NeTS: Large: Networked Markets: Theory and Applications, G8039803440, G924159479
OpenAlex ID: W2788097582