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Digital Cluster Markets, Herbert J. Hovenkamp Apr 2022

Digital Cluster Markets, Herbert J. Hovenkamp

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This paper considers the role of “cluster” markets in antitrust litigation, the minimum requirements for recognizing such markets, and the relevance of network effects in identifying them.

One foundational requirement of markets in antitrust cases is that they consist of products that are very close substitutes for one another. Even though markets are nearly always porous, this principle is very robust in antitrust analysis and there are few deviations.

Nevertheless, clustering noncompeting products into a single market for purposes of antitrust analysis can be valuable, provided that its limitations are understood. Clustering contributes to market power when (1) many customers …


The Law Of Employee Data: Privacy, Property, Governance, Matthew T. Bodie Jan 2021

The Law Of Employee Data: Privacy, Property, Governance, Matthew T. Bodie

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The availability of data related to the employment relationship has ballooned into an unruly mass of personal characteristics, performance metrics, biometric recordings, and creative output. The law governing this collection of information has been awkwardly split between privacy regulations and intellectual property rights, with employees generally losing on both ends. This Article rejects a binary approach that either carves out private spaces ineffectually or renders data into isolated pieces of ownership. Instead, the law should implement a hybrid system that provides workers with continuing input and control without blocking efforts at joint production. In addition, employers should have fiduciary responsibilities …


Toward The Personalization Of Copyright Law, Adi Libson, Gideon Parchomovsky Jan 2019

Toward The Personalization Of Copyright Law, Adi Libson, Gideon Parchomovsky

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In this Article, we provide a blueprint for personalizing copyright law in order to reduce the deadweight loss that stems from its universal application to all users, including those who would not have paid for it. We demonstrate how big data can help identify inframarginal users, who would not pay for copyrighted content, and we explain how copyright liability and remedies should be modified in such cases.