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ABSTRACT
Online auctions allow the seller to remain anonymous and to easily change identities. Buyers must rely on the seller's description of a product and ability to deliver the product as promised. Internet auction environments make opportunistic behavior more attractive to sellers because the chance of detection and punishment is decreased. In this research, we show how fee structures at eBay, the largest online auction house, motivate shilling behavior. We distinguish between two different types of shilling that exhibit different motivation and behavior: shilling can be used to make the bidders pay more for an item, competitive shilling, and shilling that can be used to avoid paying auction house fees, reserve price shilling. We then use auction data gathered using an Internet-based data collection software agent to examine reserve price shilling using a probit model. We give evidence of reserve price shilling and then show factors that lead to this behavior.
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Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 5
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Shai Rubin , Mihai Christodorescu , Vinod Ganapathy , Jonathon T. Giffin , Louis Kruger , Hao Wang , Nicholas Kidd, An auctioning reputation system based on anomaly, Proceedings of the 12th ACM conference on Computer and communications security, November 07-11, 2005, Alexandria, VA, USA
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Christian Heath , Paul Luff , Dirk Vom Lehn , Jun Yamashita , Hideaki Kuzuoka, Enhancing remote participation in live auctions: an 'intelligent' gavel, Proceedings of the 27th international conference on Human factors in computing systems, April 04-09, 2009, Boston, MA, USA
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