Daniel Schnurr

Prof. Dr. Daniel Schnurr holds the Chair of Machine Learning and Uncertainty Quantification at the University of Regensburg since 2022. Before, he was head of the research group Data Policies at the University of Passau. In his interdisciplinary research, Daniel Schnurr addresses the technical, economic, and societal implications of new machine learning methods and data as a crucial competitive factor and driver of innovation in digital markets. Daniel Schnurr has published in leading academic journals such as Management Science, Journal of Information Technology and Journal of Industrial Economics.
Daniel Schnurr received his Ph.D. in Information Systems in 2016 from the Karlsruhe Institute of Technology (KIT), where he also worked for three years as a research associate. From 2007 to 2013, he studied Information Engineering and Management (B.Sc. & M.Sc.) at the KIT and was a visiting student at John Molson School of Business, Concordia University as well as the Singapore Management University.

Humans vs. Machines: Competing With Artificial Intelligence in Digital Markets

The research project investigates the competitive interactions between human and artificial intelligence and analyzes the economic implications of machine learning in digital markets. A series of laboratory experiments explores the impact of algorithmic decision-making on market outcomes if prices are determined autonomously by machine learning techniques. Based on controlled variation of (1) the type of actors, (2) the applied learning algorithm and (3) the degree of decision support for human decision-makers, the project evaluates determinants and implications of human machine interaction in competitive market settings. The project aims to inform policy makers and managers about potential threats and strategic opportunities of artificial intelligence in digital markets.