Professor für Maschinelles Lernen, insbes. Uncertainty Quantification
Tel.: +49 941 943-68506
Email: daniel.schnurr@ur.de
Raum 513
Bajuwarenstraße 4
93053 Regensburg
Sprechzeiten:
Mittwoch, jeweils 11:00 - 12:00 Uhr
Anmeldung bitte vorab über das Sekretariat
Daniel Schnurr ist seit August 2022 Inhaber des Lehrstuhls für Maschinelles Lernen, insbesondere Uncertainty Quantification an der Universität Regensburg. Zuvor leitete er die Forschungsgruppe Data Policies an der Universität Passau. Daniel Schnurr promovierte 2016 im Bereich Wirtschaftsinformatik am Karlsruher Institut für Technologie, wo er zuvor drei Jahre als wissenschaftlicher Mitarbeiter am Institut für Informationswirtschaft und Marketing (IISM) tätig war. Von 2007 bis 2013 studierte er Informationswirtschaft (B.Sc. & M.Sc.) am Karlsruher Institut für Technologie mit Auslandsaufenthalten an der John Molson School of Business, Concordia University (Kanada) und der Singapore Management University (Singapur).
In seiner Forschung befasst sich Daniel Schnurr mit den technischen, ökonomischen und gesellschaftlichen Implikationen neuer maschineller Lernverfahren und Daten als entscheidender Wettbewerbsfaktor und Innovationstreiber in digitalen Märkten. Seine Forschungsarbeiten sind in renommierten Fachzeitschriften wie beispielsweise Management Science, Journal of Information Technology, Journal of Industrial Economics, Business & Information Systems Engineering, Information Economics and Policy, Journal of Competition Law & Economics,Telecommunications Policy und MIT Sloan Management Review erschienen.
Seit 2022 ist Daniel Schnurr Research Fellow des Centre on Regulation in Europe (CERRE), einem in Brüssel ansässigen Think Tank. In dieser Rolle hat er zahlreiche Policy Reports u.a. zur Regulierung von Cloud Computing-Diensten, digitalen Plattformen und der Datenökonomie verfasst.
Fast, V. & Schnurr, D. (2024).
Data Donations for Digital Contact Tracing: Short- and Long-Term Effects of Monetary Incentives. Research Note. Information Systems Research. Forthcoming.
[VHB: A+; ABS: Grade 4*; FT50]
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.
doi:10.1177/02683962221114394 [Preprint]
[VHB: A; ABS: Grade 4]
Krämer, J., & Schnurr, D. (2022).
Big Data and Digital Markets Contestability: Theory of Harm and Data Access Remedies. Journal of Competition Law & Economics, 18(2), 255–322.
doi:10.1093/joclec/nhab015 [Preprint]
Krämer, 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.
doi:10.1287/mnsc.2017.3012 [Article]
[VHB: A+; ABS: Grade 4*; FT50]
Horstmann, N., Krämer, J., & Schnurr, D. (2018).
Number Effects and Tacit Collusion in Experimental Oligopolies.
Journal of Industrial Economics, 66(3), 650-700.
doi:10.1111/joie.12181
[VHB: A; ABS: Grade 3]
Krämer, J., & Schnurr, D. (2018).
Margin Squeeze Regulation and Infrastructure Competition.
Information Economics and Policy, 45, 30-46.
doi:10.1016/j.infoecopol.2018.09.001
[ABS: Grade 2]
Krämer, J., & Schnurr, D. (2018).
Is There a Need for Platform Neutrality Regulation in the EU?
Telecommunications Policy, 42(7), 514-529.
doi:10.1016/j.telpol.2018.06.004
[VHB: C; ABS: Grade 1]
Krämer, J., & Schnurr, D. (2014).
A Unified Framework for Open Access Regulation of Telecommunications Infrastructure: Review of the Economic Literature and Policy Guidelines.
Telecommunications Policy, 38(11), 1160-1179.
doi:10.1016/j.telpol.2014.06.006
[VHB: C; ABS: Grade 1]
Schauer, A., & Schnurr, D. (2023)
Data Brokers: Intermediaries for More Efficient Data Markets?
TechREG Chronicle, October 2023, 1-9 [Article]
Krämer, J., Schnurr, D., & Wohlfarth, M. (2018).
Trapped in the Data-Sharing Dilemma.
MIT Sloan Management Review, 60(2), 22-23. [Article]
[VHB: C; ABS: Grade 3; FT50]
Krämer, J., & Schnurr, D. (2016).
Microeconomically Founded Information Systems Research.
In Bichler, M., & Frank, U. (Eds.), Theories in Business and Information Systems Engineering. Business & Information Systems Engineering, 58(4), 291-319.
doi:10.1007/s12599-016-0439-z
[VHB: B; ABS: Grade 2]
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) Kopenhagen, Dänemark.
[VHB: A]
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). Kopenhagen, Dänemark.
[VHB: A]
Fast, V., & Schnurr, D. (2021).
Incentivising the Adoption of COVID-19 Contact-Tracing Apps: A Randomised Controlled Online Experiment on the German Corona-Warn-App.
Proceedings of the ACM SIGMIS Computers and People Research Conference (CPR 2021). Virtuelle Konferenz.
Fast, V., Schnurr, D., & Wohlfarth, M. (2021).
Data-driven Competitive Advantages in Digital Markets: An Overview of Data Value and Facilitating Factors.
16th International Conference on Wirtschaftsinformatik (WI 2021). Duisburg-Essen, Deutschland (Virtuelle Konferenz).
[VHB: C]
Fast, V., & Schnurr, D. (2020).
The Value of Personal Data: An Experimental Analysis of Data Types and Personal Antecedents. Proceedings of the 41st International Conference on Information Systems (ICIS 2020). Hyderabad, India (Virtuelle Konferenz). [Article]
[VHB: A]
Haberer, B., & Schnurr, D. (2018).
An Economic Analysis of Data Portability and Personal Data Markets. Proceedings of the 39th International Conference on Information Systems (ICIS 2018). San Francisco, USA. [Article]
[VHB: A]
Schnurr, D. (2024).
Data Access Remedies: Economic Trade-offs, Data Privacy and Regulatory Implementation. In Ioannidou, M. and Mantzari, M. (Hrsg.), Research Handbook in Competition Law and Data Privacy. Forthcoming. Edward Elgar Publishing Ltd.
Schnurr, D. (2024).
European Data Regulation: Between Data Protection and Free Flow of Data in a Global Digital Economy. In L. Hornuf & M. Denga (Hrsg.). Regulatory Competition in the Digital Economy: Artificial Intelligence, Data, and Platforms. Forthcoming. Springer.
Schnurr, D. (2023).
Global Data Economics: Principles, Strategies and Policies. In Hennemann, M. (Hrsg.), Global Data Strategies - A Handbook, C.H.BECK Verlag. [Link]
Fast, V., Schnurr, D., & Wohlfarth, M. (2019).
Marktmacht durch Daten: Eine Analyse aus ökonomischer Perspektive. In Specht, L., Werry, N. & Werry, S. (Hrsg.), Datenrecht in der Digitalisierung, Erich Schmidt Verlag. [Link]
Schnurr, D. (2016).
Open Access to Telecommunications Infrastructure and Digital Services: Competition, Cooperation and Regulation. doi:10.5445/IR/1000061756
Manganelli, A., & Schnurr, D. (2024).
Competition and Regulation of Cloud Computing Services. Economic Analysis and Review of EU Policies. Centre on Regulation in Europe (CERRE) Policy Report. 3/2024. [Link]
Broughton Micova, S., Schnurr, D., Calef, A., & Enstone, B. (2024).
Cross-Cutting Issues for DSA Systemic Risk Management: An Agenda for Cooperation. Centre on Regulation in Europe (CERRE) Policy Report. 06/2024. [Link]
Broughton Micova, S. & Schnurr, D. (2024).
Systemic Risk in Digital Services: Benchmarks for Evaluating the Management of Risks to Electoral Processes. Centre on Regulation in Europe (CERRE) Policy Report. 05/2024. [Link]
Schnurr, D. (2022).
Switching and Interoperability between Data Processing Services in the Proposed Data Act. Centre on Regulation in Europe (CERRE) Policy Report, 12/2022. [Link]
Broughton Micova, S., Krämer, J., & Schnurr, D. (2020).
The Role of Data for Digital Markets Contestability: Case Studies and Data Access Remedies. Centre on Regulation in Europe (CERRE) Policy Report, 09/2020. [Link]
Krämer, J., Schnurr, D., de Streel, A. (2017).
Internet Platforms and Non-Discrimination. Centre on Regulation in Europe (CERRE) Policy Report, 12/2017. [Link]
VHB: Ranking nach VHB-JOURQUAL 3
ABS: Association of Business Schools Academic Journal Quality Guide June 2021
FT50: Financial Times Top 50 Journals used in FT Business School Research Ranking (2018)