Selling Information in Competitive Environments

We consider a setting where data buyers compete in a game of incomplete information, about which a data seller owns some payoff relevant information. We formulate the problem facing the seller as a joint information and mechanism design problem: deciding which information to sell, while at the same...

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Main Author: Nouripour, Amir
Other Authors: Dahleh, Munther A.
Format: Thesis
Published: Massachusetts Institute of Technology 2022
Online Access:https://hdl.handle.net/1721.1/139898
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author Nouripour, Amir
author2 Dahleh, Munther A.
author_facet Dahleh, Munther A.
Nouripour, Amir
author_sort Nouripour, Amir
collection MIT
description We consider a setting where data buyers compete in a game of incomplete information, about which a data seller owns some payoff relevant information. We formulate the problem facing the seller as a joint information and mechanism design problem: deciding which information to sell, while at the same time eliciting the private value types of the buyers and collecting payments. We derive the welfare- and revenue-optimal mechanisms for a class of binary games. Our results reveal some important features of selling information in competitive environments: (i) the negative externalities arising from competition among buyers increase the profitability of selling exclusive information to one of the buyers; (ii) in order for the buyers to follow the seller’s action recommendations, the extent of exclusive sales must be limited; (iii) these same equilibrium constraints also limit the distortions in the allocation of information distortion that can be introduced by a monopolist data seller; (iv) the fiercer the competition across buyers the stronger the previous two limitations, and the weaker the impact of market power on the equilibrium allocation of information.
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spelling mit-1721.1/1398982022-02-08T03:31:33Z Selling Information in Competitive Environments Nouripour, Amir Dahleh, Munther A. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science We consider a setting where data buyers compete in a game of incomplete information, about which a data seller owns some payoff relevant information. We formulate the problem facing the seller as a joint information and mechanism design problem: deciding which information to sell, while at the same time eliciting the private value types of the buyers and collecting payments. We derive the welfare- and revenue-optimal mechanisms for a class of binary games. Our results reveal some important features of selling information in competitive environments: (i) the negative externalities arising from competition among buyers increase the profitability of selling exclusive information to one of the buyers; (ii) in order for the buyers to follow the seller’s action recommendations, the extent of exclusive sales must be limited; (iii) these same equilibrium constraints also limit the distortions in the allocation of information distortion that can be introduced by a monopolist data seller; (iv) the fiercer the competition across buyers the stronger the previous two limitations, and the weaker the impact of market power on the equilibrium allocation of information. S.M. 2022-02-07T15:11:29Z 2022-02-07T15:11:29Z 2021-09 2021-09-21T19:54:13.098Z Thesis https://hdl.handle.net/1721.1/139898 In Copyright - Educational Use Permitted Copyright MIT http://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology
spellingShingle Nouripour, Amir
Selling Information in Competitive Environments
title Selling Information in Competitive Environments
title_full Selling Information in Competitive Environments
title_fullStr Selling Information in Competitive Environments
title_full_unstemmed Selling Information in Competitive Environments
title_short Selling Information in Competitive Environments
title_sort selling information in competitive environments
url https://hdl.handle.net/1721.1/139898
work_keys_str_mv AT nouripouramir sellinginformationincompetitiveenvironments