Competitive auctions for markets with positive externalities

  • Authors:
  • Nick Gravin;Pinyan Lu

  • Affiliations:
  • Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore;Microsoft Research Asia, China

  • Venue:
  • ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part II
  • Year:
  • 2013

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Abstract

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 $\mathcal{F}^{(3)}$. On the other hand, we show a surprising impossibility result if comparing to the stronger benchmark $\mathcal{F}^{(2)}$, where the latter has been used quite successfully in digital goods auctions without externalities [16].