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

Leffrang, D. (2023). AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization. International Conference on Information Systems, 10.

Leffrang, D. (2023). The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization. Wirtschaftsinformatik Conference, 19.

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

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

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

Knorr, L., Jungeilges, A., Pfeifer, F., Burmeister, S. C., &; Meschede, H. (2023). Regenerative Energien für einen effizienten Betrieb von Presshärtelinien. 4. Aachener Ofenbau- und Thermoprozess-Kolloquium.

Brennig, K., &; Müller, O. (2023). More Isn’t Always Better – Measuring Customers’ Preferences for Digital Process Transparency. Hawaii International Conference on System Sciences.  56th Hawaii International Conference on System Sciences, Lhain.

Brock, J., Löhr, B., Brennig, K., Seger, T., Bartelheimer, C., von Enzberg, S., Kühn, A., &; Dumitrescu, R. (2023). A Process Mining Maturity Model: Enabling Organizations to Assess and Improve their Process Mining Activities. European Conference on Information Systems.

Brennig, K., Benkert, K., Löhr, B., &; Müller, O. (2023). Text-Aware Predictive Process Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter? In Business Process Management Workshops.https://doi.org/10.1007/978-3-031-50974-2_33 

Bartelheimer, C., Wolf, V., &; Beverungen, D. (2023). Workarounds as generative mechanisms for bottomup process innovation—Insights from a multiple case study. Information Systems Journal, 33(5), 1085–1150.https://doi.org/10.1111/isj.12435 

Seutter, J., Kutzner, K., Stadtländer, M., Kundisch, D., &; Knackstedt,  R. (2023). “Sorry, Too Much Information”. Designing Online Review Systems that Support Information Search and Processing. Electronic Markets, 33(1), 47.

Seutter, J., Müller, M., &; Kundisch, D. (2023). Verdrängen Smart-Product-Service-Systeme die Interaktion in Online-Communities? – Empirische Evidenz aus einer Rezept-Community. Wirtschaftsinformatik &; Management, 15(4), 282–289.

Althaus, M., Grieger, N., Vorbohle, C., Müller, M., &; Kundisch, D. (n.d.). Business Models for Cultural Event Platforms - A Taxonomy Approach. Proceedings of the 15th Mediterranean Conference on Information Systems (MCIS). The 15th Mediterranean Conference on Information Systems (MCIS), The 6th Middle East &; North Africa Conference on digital Information Systems (MENACIS), Madrid, Spanien.

Tavana, M., Khalili Nasr, A., Ahmadabadi, A. B., Amiri, A. S., &; Mina, H. (2023). An interval multi-criteria decision-making model for evaluating blockchain-IoT technology in supply chain networks. Internet of Things, 22, Article 100786.https://doi.org/10.1016/j.iot.2023.100786 

Tavana, M., Soltanifar, M., Santos-Arteaga, F. J., &; Sharafi, H. (2023). Analytic hierarchy process and data envelopment analysis: A match made in heaven. Expert Systems with Applications, 223, Article 119902.https://doi.org/10.1016/j.eswa.2023.119902 

Tavana, M., Hajipour, V., Alaghebandha, M., &; Di Caprio, D. (2023). A bi-objective hybrid vibration damping optimization model for synchronous flow shop scheduling problems. Machine Learning with Applications, 11, Article 100445.https://doi.org/10.1016/j.mlwa.2022.100445 

Tavana, M., Mina, H., &; Santos-Arteaga, F. J. (2023). A general Best-Worst method considering interdependency with application to innovation and technology assessment at NASA. Journal of Business Research, 154, Article 113272.https://doi.org/10.1016/j.jbusres.2022.08.036 

Tavana, M., Soltanifar, M., &; Santos-Arteaga, F. J. (2023). Analytical hierarchy process: revolution and evolution. Annals of Operations Research, 326(2), 879–907.https://doi.org/10.1007/s10479-021-04432-2 

Tavana, M., Heidary, M. S., &; Mina, H. (2023). A fuzzy preference programming and weighted influence non-linear gauge system for mission architecture assessment at NASA. Applied Soft Computing, 145, Article 110572.https://doi.org/10.1016/j.asoc.2023.110572