Information Design of Online Platforms

We study how an online platform strategically uses information to both guide consumer search and influence sellers’ targeted advertising. Our model unifies personalized recommendations and targeted ads under an information design framework. We illustrate a fundamental tradeoff facing the platform between improving match efficiency and extracting seller surplus by inducing their competition for prominence. The optimal information design may be socially inefficient because it balances the tradeoff by limiting consumer search and mixing the matched product with a long tail of unmatched ones for recommendation. This implies that sponsored targeted advertising on retail platforms may introduce match inefficiency.

This paper was accepted by Greg Shaffer, marketing.

Funding: T. T. Ke acknowledges financial support from the National Natural Science Foundation of China [Grants 72422003 and 72394395] and the Hong Kong Research Grants Council [Grant 14503122].