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Industrial Data Sharing and Data Readiness: A Law and Economics Perspective


Mueller-Langer,  Frank
MPI for Innovation and Competition, Max Planck Society;

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Jorzik, N., Kirchhof, P., & Mueller-Langer, F. (2023). Industrial Data Sharing and Data Readiness: A Law and Economics Perspective. Max Planck Institute for Innovation & Competition Research Paper, No. 23-22.

Cite as: https://hdl.handle.net/21.11116/0000-000D-E4D7-F
We study the incentives and welfare properties of industrial data sharing taking into account the data (economy) readiness of companies. We differentiate between two regulatory settings. First, there is no compulsionfor companies to provide data. Companies, which also use the data for other corporate purposes, decide whether to share their data voluntarily. Second, there is a regulatory requirement on the minimum amount of data to be shared by the data provider. We assume that data sharing affects the data provider’s value of the data. The magnitude and sign of this effect have an impact on the optimal investment level of data generation and overall welfare in the different cases under study. Our results suggest that the implementation of a data-sharing policy has ambiguous welfare properties. It has positive welfare properties if (a) the data receiving firm does not pay too much for the data, (b) the data receiving firm benefits enough from the data provider’s data generating effort, and (c) the intensified competition due to data sharing is not too harmful to the data provider. In contrast, it will always have negative welfare properties if the data provider’s minimum amount of data to be shared under the policy is prohibitively high such that no data is created in the first place. Our results also suggest that a positive effect of data sharing on the data-generating company’s value of the data and its data economy readiness positively affect the incentives to share data. Finally, we find that data sharing under a data-sharing policy leads to a lower data quality if the data economy readiness of the data-generating company is too low.