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Description - Snipers, Shills, and Sharks by Ken Steiglitz

Every day on eBay, millions of people buy and sell a vast array of goods, from rare collectibles and antiques to used cars and celebrity memorabilia. The internet auction site is remarkably easy to use, which accounts in part for its huge popularity. But how does eBay really work, and how does it compare to other kinds of auctions? These are questions that led Ken Steiglitz--computer scientist, collector of ancient coins, and a regular eBay user--to examine the site through the revealing lens of auction theory. The result is this book, in which Steiglitz shows us how human behaviors in open markets like eBay can be substantially more complex than those predicted by standard economic theory. In these pages we meet the sniper who outbids you in an auction's closing seconds, the early bidder who treats eBay as if it were an old-fashioned outcry auction, the shill who bids in league with the seller to artificially inflate the price--and other characters as well. Steiglitz guides readers through the fascinating history of auctions, how they functioned in the past and how they work today in online venues like eBay. Drawing on cutting-edge economics as well as his own stories from eBay, he reveals practical auction strategies and introduces readers to the fundamentals of auction theory and the mathematics behind eBay. Complete with exercises and a detailed appendix, this book is a must for sophisticated users of online auctions, and essential reading for students seeking an accessible introduction to the study of auction theory.

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Book Details

ISBN: 9780691127132
ISBN-10: 0691127131
Format: Hardback
(229mm x 152mm x 25mm)
Pages: 304
Imprint: Princeton University Press
Publisher: Princeton University Press
Publish Date: 12-Mar-2007
Country of Publication: United States

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Author Biography - Ken Steiglitz

Ken Steiglitz is Professor of Computer Science at Princeton University. He is the author of "A Digital Signal Processing Primer" and the coauthor of "Combinatorial Optimization: Algorithms and Complexity".