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中国管理科学

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不完全信息下基于GSP的竞价排名问题研究

曹文彬, 浦徐进, 李磊   

  1. 江南大学商学院, 江苏 无锡 214122
  • 收稿日期:2010-04-19 修回日期:2011-07-05 出版日期:2011-10-30 发布日期:2011-10-30
  • 作者简介:曹文彬(1967- ),男(汉族),江苏泰兴人,江南大学商学院,博士,副教授,研究方向:电子商务、供应链管理、博弈论
  • 基金资助:
    国家自然科学基金资助项目(70901034);教育部人文社会科学规划项目(09YJA630050);中央高校基本科研业务费专项资金资助(JUSRP211A65)

Study on Bidding Rank Based on GSP Auction in Incomplete Information

CAO Wen-bin, PU Xu-jin, LI Lei   

  1. School of business, Jiangnan University, Wuxi 214122, China
  • Received:2010-04-19 Revised:2011-07-05 Online:2011-10-30 Published:2011-10-30

摘要: 本文研究对象是不完全信息下搜索引擎基于GSP拍卖的竞价排名问题。基于静态博弈模型,首先给出了按点击付费情况下广告商的贝叶斯均衡出价函数;其次为了保证均衡存在,给出了关于点击率的充分条件,并分析了点击率与均衡存在的关系;最后分析了点击率变化对搜索引擎收益的影响。结果对不完全信息下广告商的出价策略和搜索引擎的广告位置拍卖策略提供了决策依据。

关键词: 广义第二价格拍卖, 竞价排名, 贝叶斯-纳什均衡, 不完全信息

Abstract: This paper discusses the bidding rank of search engines based on GSP auction in an incomplete information setting,differently from extensively studied by the literature in a complete information setting.Based on static game theory,the existence and performance of Bayes-Nash equilibrium of advertisers on GSP auction and its sufficient condition about click through rate have been discussed.The relation among click through rate and existence of equilibrium has been analyzed.Lastly the effects of click-through on the search engine's revenue have been analyzed.Interestingly,our results are in sharp contrast with the previous literature that adopts a complete information framework and provide decision basis for bidding strategy of bidders and auction mechanism of search engine under incomplete information.

Key words: GSP auction, bidding rank, bayes-nash equilibrium, incomplete information

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