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Cyclical bid adjustments in search-engine advertising

  • Xiaoquan Zhang
  • , Juan Feng

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

Keyword advertising, or sponsored search, is one of the most successful advertising models on the Internet. One distinctive feature of keyword auctions is that they enable advertisers to adjust their bids and rankings dynamically, and the payoffs are realized in real time. We capture this unique feature with a dynamic model and identify an equilibrium bidding strategy. We find that under certain conditions, advertisers may engage in cyclical bid adjustments, and equilibrium bidding prices may follow a cyclical pattern: price-escalating phases interrupted by price-collapsing phases, similar to an "Edgeworth cycle" in the context of dynamic price competitions. Such cyclical bidding patterns can take place in both first-and second-price auctions. We obtain two data sets containing detailed bidding records of all advertisers for a sample of keywords in two leading search engines. Our empirical framework, based on a Markov switching regression model, suggests the existence of such cyclical bidding strategies. The cyclical bid-updating behavior we find cannot be easily explained with static models. This paper emphasizes the importance of adopting a dynamic perspective in studying equilibrium outcomes of keyword auctions. © 2011 INFORMS.
Original languageEnglish
Pages (from-to)1703-1719
JournalManagement Science
Volume57
Issue number9
DOIs
Publication statusPublished - Sept 2011

Research Keywords

  • Bid adjustment
  • Edgeworth cycle
  • Keyword auction

Policy Impact

  • Cited in Policy Documents

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