Data, Platforms, and Competition

Mer, 01/06/2022 - 12:00 / 13:00

401, Viale Romania

Speaker: Alessandro Bonatti , MIT Sloan School of Management

Co-author: Dirk Bergemann (Yale University)

Abstract

We propose a comprehensive model of digital commerce in which data and (consumer and product) heterogeneity are defining features. A digital platform enables matching of consumers and advertisers online. Each consumer has heterogenous preferences across heterogeneous advertisers. The advertisers can tailor their products to the preferences of the consumer. Each consumer can access each seller's products online or offline.

The platform can improve the quality of the matches through its past and present data collection. The platform monetizes its services by digital advertising that are sold in (generalized) second price auctions. 

We derive the equilibrium surplus sharing between consumers, advertisers and the platform. We evaluate how different data-governance rules affect the creation and sharing of the social surplus. We contrast the unrestricted use of data with contextual and cohort restricted use of data. We show that privacy-enhancing data governance rules, such as federated learning or differential privacy, can increase competition among the advertisers and lead to welfare gains for the platform and the consumers.