Persistent Link:
http://hdl.handle.net/10150/293592
Title:
Mitigating Sniping in Internet Auctions
Author:
Nagy, Lindsey Danielle
Issue Date:
2013
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
My dissertation discusses a mechanism that thwarts sniping and improves efficiency in ascending Internet auctions with fixed ending times, specifically eBay. The first research chapter proposes a design of the bidding mechanism and the second chapter tests the effectiveness of the mechanism in a controlled environment. In addition, it presents an innovative theoretical representation of the eBay bidding environment. The first chapter investigates theoretically whether sellers can improve their profits in eBay-like auctions via the implementation of bidder credits. The analysis predicts that providing a credit, similar to a coupon or discount, for early bidding can thwart sniping and increase seller profit. The paper formulates and analyzes a multi-stage auction model with independently and identically distributed private values, where bidders place proxy bids. I show that sniping can emerge as a Bayesian-Nash equilibrium strategy so long as late bids run the risk of not being successfully received by the auctioneer; extending the prior work of Ockenfels and Roth. This equilibrium is inefficient and yields the worst outcome for sellers. The proposed credit mechanism awards a single early bidder a reduction, equal to the value of the credit, in the final price if he wins the auction. The optimal credit satisfies two necessary conditions; first, it increases seller ex-ante profit and second, it incentivizes bidders to deviate from the sniping equilibrium. Relative to the surplus generated by the sniping equilibrium, implementing the credit increases seller surplus and improves welfare. The second chapter experimentally investigates the effectiveness of the credit mechanism. In particular, it compares bidding strategies, seller profit, and overall efficiency in auction environments similar to eBay with and without credit incentives. I observe a significant decline in the frequency of sniping when subjects have the opportunity to receive the credit. The credit also improves auction efficiency primary because subjects overbid in auctions with the credit regardless of which subject has the credit. A within-subjects design allows me to directly compare differences across treatments conditional on the subjects being snipers. Auctions with snipers yield significantly lower profits to sellers because non-sniping rivals are bidding less aggressively when competing against a sniper.
Type:
text; Electronic Dissertation
Keywords:
Experiments; Online Auctions; Proxy Bidding; Sniping; Economics; Consumer Behavior
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Economics
Degree Grantor:
University of Arizona
Advisor:
Reynolds, Stanley

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleMitigating Sniping in Internet Auctionsen_US
dc.creatorNagy, Lindsey Danielleen_US
dc.contributor.authorNagy, Lindsey Danielleen_US
dc.date.issued2013-
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractMy dissertation discusses a mechanism that thwarts sniping and improves efficiency in ascending Internet auctions with fixed ending times, specifically eBay. The first research chapter proposes a design of the bidding mechanism and the second chapter tests the effectiveness of the mechanism in a controlled environment. In addition, it presents an innovative theoretical representation of the eBay bidding environment. The first chapter investigates theoretically whether sellers can improve their profits in eBay-like auctions via the implementation of bidder credits. The analysis predicts that providing a credit, similar to a coupon or discount, for early bidding can thwart sniping and increase seller profit. The paper formulates and analyzes a multi-stage auction model with independently and identically distributed private values, where bidders place proxy bids. I show that sniping can emerge as a Bayesian-Nash equilibrium strategy so long as late bids run the risk of not being successfully received by the auctioneer; extending the prior work of Ockenfels and Roth. This equilibrium is inefficient and yields the worst outcome for sellers. The proposed credit mechanism awards a single early bidder a reduction, equal to the value of the credit, in the final price if he wins the auction. The optimal credit satisfies two necessary conditions; first, it increases seller ex-ante profit and second, it incentivizes bidders to deviate from the sniping equilibrium. Relative to the surplus generated by the sniping equilibrium, implementing the credit increases seller surplus and improves welfare. The second chapter experimentally investigates the effectiveness of the credit mechanism. In particular, it compares bidding strategies, seller profit, and overall efficiency in auction environments similar to eBay with and without credit incentives. I observe a significant decline in the frequency of sniping when subjects have the opportunity to receive the credit. The credit also improves auction efficiency primary because subjects overbid in auctions with the credit regardless of which subject has the credit. A within-subjects design allows me to directly compare differences across treatments conditional on the subjects being snipers. Auctions with snipers yield significantly lower profits to sellers because non-sniping rivals are bidding less aggressively when competing against a sniper.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectExperimentsen_US
dc.subjectOnline Auctionsen_US
dc.subjectProxy Biddingen_US
dc.subjectSnipingen_US
dc.subjectEconomicsen_US
dc.subjectConsumer Behavioren_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineEconomicsen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorReynolds, Stanleyen_US
dc.contributor.committeememberWooders, Johnen_US
dc.contributor.committeememberWalker, Marken_US
dc.contributor.committeememberBlume, Andreasen_US
dc.contributor.committeememberReynolds, Stanleyen_US
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