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Title: 

Quality Uncertainty And Adverse Selection In Sponsored Search Markets

Authors: Animesh, Animesh - University of Maryland
Ramachandran, Vandana - University of Maryland
Viswanathan, Siva - University of Maryland
Keywords: sponsored search, keyword advertising, pay-for-performance, search, credence, experience
Issue Date: 2005
Series/Report no.: NET Institute Working Paper;05-27
Abstract: Sponsored search mechanisms, where advertisers bid for placement to be as close to the top in the listing of search results, are the fastest growing among online search models. Sponsored search in popular search services such as Google and Yahoo! employ an auction mechanism wherein firms can bid, for a better placement in the (sponsored) search results, on relevant keywords used by consumers in their search process. This provides an unprecedented opportunity to test some of the predictions of earlier research relating quality and advertising, in the online setting. While sponsored search mechanisms have been gaining popularity, they can potentially introduce a bias in the listing of search results. In particular, sponsored search mechanisms that enable low quality bidders to be placed at the top of the search listings can adversely affect consumer welfare. Our study uses data from online sponsored search auctions to examine the relationship between advertisers' quality and their bidding strategies. Specifically we seek to understand if advertisers' bidding strategies differ across products characterized by different degrees of quality-uncertainty. Our results indicate that there are significant differences in the bidding strategies of sellers of search goods as compared to sellers of experience and credence goods, and that there is significant adverse selection in product categories characterized by greater uncertainty. We discuss the implications of our findings for consumers, advertisers, and intermediaries and provide directions for future research in this emerging context.
URI: http://hdl.handle.net/2451/28438
Appears in Collections:NET Institute Working Papers Series

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