About this Event
About the Talk
Algorithms, Data, and Digital Platforms
This talk examines how consumer data and automated advertising shape competition and prices on digital platforms. It compares traditional bidding for sponsored links with managed campaigns, in which advertisers submit budgets and delegate advertising decisions to the platform. The models explain how better matching can coexist with weaker price competition and higher product prices, including outside the platform. They also show how bidding algorithms affect the division of surplus among consumers, sellers, and the platform. The analysis connects the design of advertising mechanisms to questions of platform market power and consumer welfare. It also considers the implications for generative AI-powered search, where sponsored recommendations can be integrated into generated answers.
About the Speaker
Alessandro Bonatti is the John Norris Maguire (1960) Professor of Applied Economics at the MIT Sloan School of Management.
Alessandro is an applied microeconomic theorist working at the intersection of game theory and industrial organization. His research studies the dynamics of incentives in organizations, nonlinear and dynamic pricing strategies, and the economics of digital markets. His most recent work focuses on markets for data, and on the optimal use of data for pricing and personalized advertising by platforms and firms. He also researches the effects of data on user privacy, examining the tradeoffs between privacy concerns and the benefits associated with firms having a more precise understanding of consumer preferences.
Alessandro currently serves as coeditor for the American Economic Journal: Microeconomics and as associate editor for the Quarterly Journal of Economics.
Learn More: https://mitmgmtfaculty.mit.edu/abonatti/
Agenda
🕑: 05:30 PM
Registration
🕑: 05:35 PM
Sharing | Prof. Alessandro Bonatti
🕑: 06:45 PM
Q&A
🕑: 07:00 PM
End of Event
Event venue & nearby stays
MIT Hong Kong Innovation Node, 1/F, Hong Kong Productivity Council, Hong Kong, Hong Kong (SAR)
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