运筹与管理 ›› 2022, Vol. 31 ›› Issue (2): 119-125.DOI: 10.12005/orms.2022.0052

• 应用研究 • 上一篇    下一篇

信息不对称条件下竞价排名机制的信息匹配效率研究

蔡祖国, 刘璐, 范莉莉   

  1. 西南交通大学 经济管理学院,四川 成都 610031
  • 收稿日期:2020-04-22 出版日期:2022-02-25 发布日期:2022-03-11
  • 作者简介:蔡祖国(1990-),男,博士研究生,研究方向:互联网平台企业反垄断规制及治理。
  • 基金资助:
    国家自然科学基金面上项目(71473066);国家自然科学基金地区科学项目(71963012)

Research on the Information Matching Efficiency of Bidding Mechanism Under Information Asymmetry

CAI Zu-guo, LIU Lu, FAN Li-li   

  1. School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2020-04-22 Online:2022-02-25 Published:2022-03-11

摘要: 本文聚焦消费者依赖搜索引擎平台的关键词检索实施购买商品行为的现象,尝试将消费者购买策略引入搜索平台竞价排名机制,构造内嵌搜索引擎平台、销售商、消费者三方主体的博弈模型,考察在互联网信息不对称条件下,竞价排名机制的信息匹配效率,阐释产品质量信号改善竞价排名机制信息匹配效率的理论机理。研究发现,在信息不对称及无产品质量信号机制的条件下,竞价排名均衡结果完全不能匹配消费者的购买策略,致使消费者福利因销售商逆向选择而遭受双重损失;植入产品质量信号后,搜索引擎平台能够通过识别销售商自带的产品质量信号,提高竞价排名机制的均衡结果与消费者购买策略的匹配度,进而部分地改善竞价排名机制的信息匹配效率。

关键词: 竞价排名, 信息不对称, 搜索引擎平台, 信息匹配效率

Abstract: Focusing on the phenomenon that consumers rely on the keyword retrieval of search engine platform to make purchase decision, this paper introduces consumer search behavior into the bidding mechanism of search engine platform and construct a game model with search engine platform, seller and consumer, to investigate the information matching efficiency of the bidding mechanism of search engine platform under information asymmetry. Based on that, we investigate the theoretical mechanism of product quality as a signal to improve the information matching efficiency of bidding mechanism. Our research findings show that, under information asymmetry and without the signal of product quality, the equilibrium of the bidding mechanism fails to match the purchase decisions of consumers at all, resulting in double losses of consumer welfare due to the adverse selection of sellers. After the signal of product quality is implanted, the search engine platform can improve the matching degree between the equilibrium of the bidding mechanism and the consumer purchase decisions by identifying the product quality signal of sellers, and then partially improve the information matching efficiency of the bidding mechanism.

Key words: bidding ranking, information asymmetry, search engine platform, information matching efficiency

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