Information Design of Online Platforms

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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).
Original languageEnglish
Title of host publicationEC 2023 - Proceedings of the 24th ACM Conference on Economics and Computation
Place of PublicationLondon, United kingdom
Pages912 -
Publication statusPublished - 2023

Bibliographical note

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


  • Information use
  • Marketing
  • Product design


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