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Research

The Chair's key research focus areas include:

The research of the chair is inherently interdisciplinary as it spans across the enabling information technology, the economic value creation and the regulatory environement. At the same time, the research is of high social relevance because of the far-reaching implications of artificial intelligence and the associated fundamental transformation processes.

Selected research projects:

  • Schauer, A., &?Schnurr, D.?(2022).?Competition Between Human and Artificial Intelligence in Digital Markets: An Experimental Analysis.?43rd?International Conference on Information Systems (ICIS 2022). Copenhagen, Denmark. https://ssrn.com/abstract=4139527

  • Fast, V.,?Schnurr, D., & Wohlfarth, M. (2023). Regulation of Data-driven Market Power in the Digital Economy: Business Value Creation and Competitive Advantages from Big Data. Journal of Information Technology, 38(2), 202–229.?https://doi.org/10.1177/02683962221114394

  • Fast, V., &?Schnurr, D.?(2023). Data Donations for Digital Contact-Tracing: Short-and Long-term Effects of Monetary Incentives.?Conference on Information Systems and Technology 2021 (CIST). Newport Beach, USA. https://ssrn.com/abstract=3786245

  • Haberer, B., Kraemer, J., &?Schnurr, D.?(2022). Do Consumers Benefit from Selling their Data? The Economic Effects of Personal Data Brokers in Digital Markets. https://ssrn.com/abstract=3141946

  • Sachs, N., & Schnurr, D. (2022).?Privacy Risks in Digital Markets: The Impact of Ambiguity Attitudes on Transparency Choices.?43rd?International Conference on Information Systems (ICIS 2022). Copenhagen, Denmark. https://ssrn.com/abstract=3987945

  • Schnurr, D. (2022).?Switching and Interoperability Between Data Processing Services in the Proposed Data Act.?Research report prepared for the Centre on Regulation in Europe (CERRE).?https://t.ly/3gMT

  • Kra?mer, J.,?Schnurr, D., & Wohlfarth, M. (2019). Winners, Losers, and Facebook: The Role of Social Logins in the Online Advertising Ecosystem.?Management Science, 65(4), 1678-1699. https://doi.org/10.1287/mnsc.2017.3012


  1. Faculty of Informatics and Data Science

Chair of Machine Learning and Uncertainty Quantification


Sekretariat

+49 941 943-68508
Sekretariat.Schnurr@ur.de