In digital goods auctions, the auctioneer sells an item in unlimited supply to a set of potential buyers. The objective is to design a truthful auction that maximizes the auctioneer's total profit. Motivated by the observation that the buyers' valuation of the good might be interconnected through a social network, we study digital goods auctions with positive externalities among buyers. This defines a multi-parameter auction design problem where the private valuation of every buyer is a function of the set of other winning buyers. The main contribution of this paper is a truthful competitive mechanism for subadditive valuations. Our competitive result is with respect to a new solution benchmark F3. On the other hand, we show a surprising impossibility result if comparing to the stronger benchmark F2, where the latter has been used quite successfully in digital goods auctions without externalities [16]. © 2013 Springer-Verlag.
CITATION STYLE
Gravin, N., & Lu, P. (2013). Competitive auctions for markets with positive externalities. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7966 LNCS, pp. 569–580). https://doi.org/10.1007/978-3-642-39212-2_50
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