BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY: Information Asymmetries in Pay-Per-Bid Auctions: How Swoopo Makes
  Bank - Prof Michael Mitzenmacher - Computer Science\, Harvard
DTSTART:20100803T100000Z
DTEND:20100803T110000Z
UID:TALK25454@talks.cam.ac.uk
CONTACT:Microsoft Research Cambridge Talks Admins
DESCRIPTION:*Abstract:* Recently\, some mainstream e-commerce web sites ha
 ve begun using `pay-per-bid` auctions to sell items\, from video games to 
 bars of gold. In these auctions\, bidders incur a cost for placing each bi
 d in addition to (or sometimes in lieu of) the winner`s final purchase cos
 t. 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 b
 id fees. Our work provides novel analyses for these auctions\, based on bo
 th modeling and datasets derived from auctions at Swoopo.com\, the leading
  pay-per-bid auction site. While previous modeling work predicts profit-fr
 ee equilibria\, we analyze the impact of information asymmetry broadly\, a
 s well as Swoopo features such as bidpacks and the Swoop It Now option spe
 cifically. We find that even small asymmetries across players (cheaper bid
 s\, better estimates of other players` intent\, different valuations of it
 ems\, committed players willing to play `chicken`) can increase the auctio
 n duration significantly and thus skew the auctioneer`s profit disproporti
 onately. We discuss our findings in the context of a dataset of thousands 
 of live auctions we observed on Swoopo\, which enables us also to examine 
 behavioral factors\, such as the power of aggressive bidding. Ultimately\,
  our findings show that even with fully rational players\, if players over
 look or are unaware any of these factors\, the result is outsized profits 
 for pay-per-bid auctioneers. \n\n*Biography:* Michael Mitzenmacher is a Pr
 ofessor of Computer Science in the\nSchool of Engineering and Applied Scie
 nces at Harvard University.\nMichael has authored or co-authored over 140 
 conference and journal\npublications on a variety of topics\, including In
 ternet algorithms\,\nhashing\, load-balancing\, erasure codes\, error-corr
 ecting codes\,\ncompression\, bin-packing\, and power laws. His work on lo
 w-density\nparity-check codes shared the 2002 IEEE Information Theory Soci
 ety\nBest Paper Award and won the 2009 SIGCOMM Test of Time Award.  \nHis 
 textbook on probabilistic techniques in computer science\, co-written \nwi
 th Eli Upfal\, was published in 2005 by Cambridge University Press.\n\nMic
 hael Mitzenmacher graduated summa cum laude with a degree in\nmathematics 
 and computer science from Harvard in 1991.  After studying\nmath for a yea
 r in Cambridge\, England\, on the Churchill Scholarship\,\nhe obtained his
  Ph. D. in computer science at U.C. Berkeley in 1996.\nHe then worked at D
 igital Systems Research Center until joining the\nHarvard faculty in 1999.
 \n
LOCATION:Small public lecture room\, Microsoft Research Ltd\, 7 J J Thomso
 n Avenue (Off Madingley Road)\, Cambridge
END:VEVENT
END:VCALENDAR