Straight Outta Logs: Can Large Language Models Overcome Preprocessing in Next Event Prediction?
K. Brennig, S.B. Kaltenpoth, O. Müller, in: Lecture Notes in Business Information Processing, Springer Nature Switzerland, Cham, 2025.

Bridging the gap between data-driven and theory-driven modelling – leveraging causal machine learning for integrative modelling of dynamical systems
D.R. Zapata Gonzalez, M. Meyer, O. Müller, in: 2025.

Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes
K. Brennig, in: AMCIS 2025 Proceedings. 11., 2025.

LLMs For Warm and Cold Next-Item Recommendation: A Comparative Study across Zero-Shot Prompting, In-Context Learning and Fine-Tuning
H. Halimeh, F. Freese, O. Müller, in: International Conference on Information Systems Development, University of Gdansk, Department of Business Informatics &; University of Belgrade, Faculty of Organizational Sciences, 2025.

Preserving Sovereignty and Privacy for Personalization: Designing a Federated Recommendation System for Data Spaces
H. Halimeh, P. zur Heiden, in: 2025 27th International Conference on Business Informatics (CBI), IEEE, 2025.

Towards Greener Choices: Decision Information Nudging for Sustainability-Aware Recommender Explanations
H. Halimeh, O. Müller, in: 2025.

Positionspapier Use Case 1: Vernetzte Kulturplattformen
M. Althaus, D. Beverungen, B. Flath, H. Halimeh, P. Hansmeier, P. zur Heiden, D. Kundisch, M. Müller, O. Müller, S. Oberthür, C. Vorbohle, M. Momen Pour Tafreshi, S. Mauß, A. Mücke, J. Müller, M. Peter, A. Schmitt-Chandon, K. Sellerberg, M. Steinhäuser, Positionspapier Use Case 1: Vernetzte Kulturplattformen, Universität Paderborn, SICP, 2025.

Designing taxi ridesharing systems with shared pick-up and drop-off locations: Insights from a computational study
M. Stumpe, P. Dieter, G. Schryen, O. Müller, D. Beverungen, Transportation Research Part A: Policy and Practice (2024).

Not your Average Digital Nudge: Heterogeneous Effects of Personalized Nudges with CausalML
K. Bösch, O. Müller, M. Weinmann, in: Proceedings of the Symposium on Statistical Challenges in Electronic Commerce Research, 2024.

Getting in Contract with Large Language Models - An Agency Theory Perspective On Large Language Model Alignment
S.B. Kaltenpoth, O. Müller, in: Wirtschaftsinformatik 2024 Proceedings, 2024.

Digital Responsibility – a Multilevel Framework for Responsible Digitalization
D. Beverungen, D. Kundisch, M. Mirbabaie, O. Müller, G. Schryen, S.T.-N. Trang, M. Trier, Business &; Information Systems Engineering 65 (2023) 463–474.

Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time
D. Leffrang, K. Bösch, O. Müller, in: Hawaii International Conference on System Sciences, 2023.

AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization
D. Leffrang, in: International Conference on Information Systems, 2023.

The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization
D. Leffrang, in: Wirtschaftsinformatik Conference, 2023.

Event Recommendations through the Lens of Vision and Language Foundation Models
H. Halimeh, F. Freese, O. Müller, in: Workshop on Recommenders in Tourism, Co-Located with the 17th ACM Conference on Recommender Systems, 2023.

Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features
H. Halimeh, M. Caron, O. Müller, in: Hawaii International Conference on System Sciences, 2023.

Analyzing the Needs of Ukrainian Refugees on Telegram in Real-Time: A Machine Learning Approach
R. Reimann, M. Caron, in: Wirtschaftsinformatik, 2023.

More Isn’t Always Better – Measuring Customers’ Preferences for Digital Process Transparency
K. Brennig, O. Müller, in: Hawaii International Conference on System Sciences, 2023.

Text-Aware Predictive Process Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter?
K. Brennig, K. Benkert, B. Löhr, O. Müller, in: Business Process Management Workshops, 2023.

HIEF: a holistic interpretability and explainability framework
J.-P. Kucklick, Journal of Decision Systems (2023) 1–41.