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SUMMARY:Information Asymmetries in Pay-Per-Bid Auctions: How Swoopo Makes 
 Bank - Michael Mitzenmacher\, Harvard University
DTSTART:20100803T100000Z
DTEND:20100803T110000Z
UID:TALK25679@talks.cam.ac.uk
CONTACT:Neil Walton
DESCRIPTION:Recently\, some mainstream e-commerce web sites have begun usi
 ng `pay-per-bid` auctions to sell items\, from video games to bars of gold
 . In these auctions\, bidders incur a cost for placing each bid in additio
 n to (or sometimes in lieu of) the winner`s final purchase cost. Thus even
  when a winner`s purchase cost is a small fraction of the item`s intrinsic
  value\, the auctioneer can still profit handsomely from the bid fees. Our
  work provides novel analyses for these auctions\, based on both modeling 
 and datasets derived from auctions at Swoopo.com\, the leading pay-per-bid
  auction site. While previous modeling work predicts profit-free equilibri
 a\, we analyze the impact of information asymmetry broadly\, as well as Sw
 oopo features such as bidpacks and the Swoop It Now option specifically. W
 e find that even small asymmetries across players (cheaper bids\, better e
 stimates of other players` intent\, different valuations of items\, commit
 ted players willing to play `chicken`) can increase the auction duration s
 ignificantly and thus skew the auctioneer`s profit disproportionately. We 
 discuss our findings in the context of a dataset of thousands of live auct
 ions we observed on Swoopo\, which enables us also to examine behavioral f
 actors\, such as the power of aggressive bidding. Ultimately\, our finding
 s show that even with fully rational players\, if players overlook or are 
 unaware any of these factors\, the result is outsized profits for pay-per-
 bid auctioneers.\n\nBiography: Michael Mitzenmacher is a Professor of Comp
 uter Science in the School of Engineering and Applied Sciences at Harvard 
 University. Michael has authored or co-authored over 140 conference and jo
 urnal publications on a variety of topics\, including Internet algorithms\
 , hashing\, load-balancing\, erasure codes\, error-correcting codes\, comp
 ression\, bin-packing\, and power laws. His work on low-density parity-che
 ck codes shared the 2002 IEEE Information Theory Society Best Paper Award 
 and won the 2009 SIGCOMM Test of Time Award. His textbook on probabilistic
  techniques in computer science\, co-written with Eli Upfal\, was publishe
 d in 2005 by Cambridge University Press.\n\nMichael Mitzenmacher graduated
  summa cum laude with a degree in mathematics and computer science from Ha
 rvard in 1991. After studying math for a year in Cambridge\, England\, on 
 the Churchill Scholarship\, he obtained his Ph. D. in computer science at 
 U.C. Berkeley in 1996. He then worked at Digital Systems Research Center u
 ntil joining the Harvard faculty in 1999.\n
LOCATION:Small public lecture room\, Microsoft Research Ltd\, 7 J J Thomso
 n Avenue (Off Madingley Road)\, Cambridge.
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