Brock, Jonathan, et al. “A Process Mining Maturity Model: Enabling Organizations to Assess and Improve Their Process Mining Activities.” European Conference on Information Systems, 2023.

Brennig, Katharina, et al. “Text-Aware Predictive Process Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter?”10.1007/978-3-031-50974-2_33__Business Process Management Workshops, 2023, doi:10.1007/978-3-031-50974-2_33.

Kucklick, Jan-Peter. “Visual Interpretability of Image-Based Real Estate Appraisal.” 55th Annual Hawaii International Conference on System Sciences (HICSS-55), 2022.

Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI Systems.” Wirtschaftsinformatik 2022 Proceedings, 2022.

Shollo, Arisa, et al. “Shifting ML Value Creation Mechanisms: A Process Model of ML Value Creation.”10.1016/j.jsis.2022.101734__The Journal of Strategic Information Systems, vol. 31, no. 3, 101734, Elsevier BV, 2022, doi:10.1016/j.jsis.2022.101734.

Kucklick, Jan-Peter, and Oliver Müller. “Tackling the Accuracy–Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-Based Real Estate Appraisal.”10.1145/3567430__ACM Transactions on Management Information Systems, Association for Computing Machinery (ACM), 2022, doi:10.1145/3567430.

Löhr, Bernd, et al. “Process Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing.”10.1007/978-3-031-16103-2_18__International Conference on Business Process Management, 2022, doi:10.1007/978-3-031-16103-2_18.

Caron, Matthew. “Shortcut Learning in Financial Text Mining: Exposing the Overly Optimistic Performance Estimates of Text Classification Models under Distribution Shift.”10.1109/bigdata55660.2022.10020933__2022 IEEE International Conference on Big Data (Big Data), IEEE, 2022, doi:10.1109/bigdata55660.2022.10020933.

Caron, Matthew, et al. “Towards Automated Moderation: Enabling Toxic Language Detection with Transfer Learning and Attention-Based Models.” 55th Hawaii International Conference on System Sciences (HICSS), 2022.

Kucklick, Jan-Peter, and Oliver Müller. “A Comparison of Multi-View Learning Strategies for Satellite Image-Based Real Estate Appraisal.”  The AAAI-21 Workshop on Knowledge Discovery from Unstructured Data in Financial Services, 2021.

Kucklick, Jan-Peter, et al. “Quantifying the Impact of Location Data for Real Estate Appraisal – A GIS-Based Deep Learning Approach.” European Conference on Information Systems, 2021.

Nagbøl, Per Rådberg, et al. “Designing a Risk Assessment Tool for Artificial Intelligence Systems.”10.1007/978-3-030-82405-1_32__The Next Wave of Sociotechnical Design, Springer International Publishing, 2021, doi:10.1007/978-3-030-82405-1_32.

Müller, Oliver, et al. “PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball Using Tracking Data.” 8th Workshop on Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021).

Caron, Matthew, et al. “To the Moon! Analyzing the Community of ‘Degenerates’ Engaged in the Surge of the GME Stock.” 42nd International Conference on Information Systems (ICIS 2021), 2021.

Leffrang, Dirk, and Oliver Müller. “Should I Follow This Model? The Effect of Uncertainty Visualization on the Acceptance of Time Series Forecasts.”10.1109/TREX53765.2021.00009__IEEE Workshop on TRust and EXpertise in Visual Analytics, 2021, doi:10.1109/TREX53765.2021.00009.

Kucklick, Jan-Peter, and Oliver Müller. “Location, Location, Location: Satellite Image-Based Real-Estate  Appraisal.” Symposium on Statistical Challenges in Electronic Commerce Research (SCECR), 2020.

Thiess, Tiemo, et al. “Design Principles for Explainable Sales Win-Propensity Prediction Systems.”https://doi.org/10.30844/wi_2020_c8-thiess__International Conference on Wirtschaftsinformatik, 2020, doi:https://doi.org/10.30844/wi_2020_c8-thiess.

Grytz, Raphael, et al. “Business Intelligence &; Analytics Cost Accounting: An Action Design Research Approach.” European Conference on Information Systems, 2020.

Kucklick, Jan-Peter, et al. “Extending Loyalty Programs with BI Functionalities A Case Study for Brick-and-Mortar Stores.” Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020.

Kamm, Michael Reiner, et al. “Data Mining for Small Shops: Empowering Brick-and-Mortar Stores through BI Functionalities of a Loyalty Program1.”10.1080/10580530.2020.1855486__Information Systems Management, vol. 38, no. 4, Informa UK Limited, 2020, pp. 270–86, doi:10.1080/10580530.2020.1855486.