Forschung

Ziel unserer Forschung ist es, praxisrelevante Probleme mit den Werkzeugen der Wirtschaftswissenschaften zu lösen. Dabei wird auf quantitative, analytische, simulative, experimentelle und gestaltungsorientierte Methoden zurückgegriffen.

Applied Machine Learning
Assistance Systems
Privacy and Trust
Informationsdiffusion
Soziale Netzwerke
E-Finance
E-Commerce insb. Empfehlungssysteme
Online-Pricing insb. Auktionen und Verhandlungen
Business Value of IT
Social Media
Economics of Security and Privacy
The Car and the Internet (Applications, Business Models, Adoption Behavior)

Ausgewählte Publikationen

von Zahn, Moritz / Bauer, Kevin / Mihale-Wilson, Cristina / Jagow, Johanna / Speicher, Maximilian / Hinz, Oliver (2024): "Smart Green Nudging: Reducing Product Returns through Digital Footprints and Causal Machine Learning", Marketing Science, forthcoming.

Gnewuch, Ulrich / Morana, Stefan / Hinz, Oliver / Kellner, Ralf / Mädche, Alexander (2023): "More than a Bot? The Impact of Disclosing Human Involvement on Customer Interactions with Hybrid Service Agents", Information Systems Research, conditionally accepted.

Bauer, Kevin / von Zahn, Moritz / Hinz, Oliver (2023): "Expl(AI)ned: The Impact of Explainable Artificial Intelligence on Users’ Information Processing", Information Systems Research 34(4), 1582-1602. [View]

Abdel-Karim, Benjamin M. / Pfeuffer, Nicolas / Carl, K. Valerie / Hinz, Oliver (2023): "How AI-Based Systems Can Induce Reflections: The Case of AI-Augmented Diagnostic Work", Management Information Systems Quarterly (MISQ), 47(4), 1395-1424. doi.org/10.25300/MISQ/2022/16773

Li, Xitong / Grahl, Joern / Hinz, Oliver (2022): "How Do Recommender Systems Lead to Consumer Purchases? A Causal Mediation Analysis of a Field Experiment", Information Systems Research, 33(2), 620-637.