Crowdsourced Referral Auctions

Chandra, Praphul and Gujar, Sujit and Narahari, Y (2016) Crowdsourced Referral Auctions. In: 22nd European Conference on Artificial Intelligence (ECAI), AUG 29-SEP 02, 2016, Hague, NETHERLANDS, pp. 1654-1655.

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Abstract

Motivated by web based marketplaces where the number of bidders in an auction is a small subset of potential bidders, we consider auctions where the auctioneer (seller) wishes to increase her revenue and/or social welfare by expanding the pool of participants. To this end, the seller crowdsources this task by offering a referral bonus to the participants. With the introduction of referrals, a participant can now bid and/or refer other agents to bid. We call our auctions crowdsourced referral auctions since the seller exploits the knowledge that agents have about other potential participants in the crowd. We introduce the notion of price of locality to quantify the loss in social welfare due to restricted (local) access of the seller to potential bidders. We introduce the notion of Crowdsourced Referral Auction Mechanisms (CRAMs), propose two novel versions of CRAMs and study the induced referral game in the canonical context of an auction for selling a single indivisible item. We compare their revenue performance and game theoretic properties and show that both of them outperform the baseline auction without referrals.

Item Type:	Conference Proceedings
Series.:	Frontiers in Artificial Intelligence and Applications
Additional Information:	Copy right for this article belongs to the IOS PRESS, NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	03 Dec 2016 09:45
Last Modified:	03 Dec 2016 09:45
URI:	http://eprints.iisc.ac.in/id/eprint/55370

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