Information Design of Online Platforms

T. Tony Ke, Song Lin, Michelle Y. Lu

科研成果: 书/报告/会议事项章节会议稿件同行评审


We consider the strategic use of information by an online platform to both guide consumers' search through product recommendations and influence sellers' targeted advertising decision. Drawing on Bayesian persuasion, we posit that the platform can design a public signal that influences the beliefs of both consumers and sellers. Upon observing the signal, a consumer can conduct a sequential search with perfect recall among the sellers. After visiting a seller, the consumer observes the product price and whether the product is a match or not. Sellers set prices and decide how much to bid in an ad auction for each consumer, where the winner is granted a prominent position. The consumer can obtain the price and match information of the seller in the prominent position at no cost, but incur search cost to visit additional sellers.
© 2023 Owner/Author(s).
主期刊名EC 2023 - Proceedings of the 24th ACM Conference on Economics and Computation
出版地点London, United kingdom
912 -
已出版 - 2023


Bayesian;Can design;Consumer search;Information design;Online platforms;Personalizations;Platform design;Product recommendation;Sequential search;Targeted advertising;


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