Deutsch Intern
Lehrstuhl für BWL und Wirtschaftsinformatik - Prof. Dr. A. Winkelmann

Myriam Schaschek

Sprechstunde: nach Vereinbarung

Forschungsinteressen:

  • Data-driven Decision Support in Organizations
  • Data and Process Analytics
  • Artificial Intelligence for Process Analytics
  • Generative Artificial Intelligence - Use, Trust, and Impact
  • Hyperautomation 

Forschungsprojekte:

  • Plattform für das integrierte Management von Kollaborationen in Wertschöpfungsnetzwerken - PIMKoWe
  • Prediction of Industrial Processes through Explainable Artificial Intelligence - pipeAI
  • Hyperautomation Ökosystem - Hyko

Publikationen:

  • Schaschek M., Spatscheck, N., and Winkelmann, A, For Those About to Rely—A Taxonomy of Experimental Studies on AI Reliance. Wirtschaftsinformatik 2024 Proceedings. 89.
  • Spatscheck, N., Schaschek M., and Winkelmann, A, The Effects of Generative AI's Human-Like Competencies on Clinical Decision-Making. Journal of Decision Systems, (2024), DOI: 10.1080/12460125.2024.2430731,forthcoming.
  • Schaschek, M., Gwinner, F., Neis, N., Tomitza, C., Zeiß, C., Winkelmann, A. Managing next generation BP-x initiatives. Information Systems and e-Business Management, https://doi.org/10.1007/s10257-024-00681-3.
  • Zeiß, C., Schaschek, M., Straub, L., Tomitza, C., Winkelmann, A. Re-intermediation of the crypto asset ecosystem by banks: An empirical study on acceptance drivers among the populace. Electronic Markets 34,  37 (2024).
  • Straub, L., Schaschek M., Tomitza C., Winkelmann, A. (2024). Fantastic AI Text Generations and Where to Trust Them: It's not Magic, it's Science!. In Wirtschaftsinformatik 2024 Proceedings, forthcoming.
  • Zeiß, Christian; Straub, Lisa; Hahn, Viktoria; Lang, Konstanze; Schaschek, Myriam; Tomitza, Christoph; Winkelmann, Axel. Designing For Banking Resilience: A DeFi E-Learning Solution. In International Conference on Design Science Research (DESRIST 2024). 2024.
  • Zeiß, Christian; Straub, Lisa; Schaschek, Myriam; Axel, Winkelmann. The obscure world of digital assets - Design Principles for User-Centered Platforms.  In 32nd European Conference on Information Systems (ECIS). AIS, 2024.
  • Schaschek, M. and Engel, S. (2023). Measuring Trustworthiness of AI Systems: A Holistic Maturity Model In ICIS 2023 Proceedings. 7.
  • Schaschek, M., Gwinner, F., Hein, B. and Winkelmann, A. (2023). From Black Box to Glass Box: Evaluating the Faithfulness of Process Predictions with GCNNs. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - Workshop and Tutorial Track, forthcoming. 
  • Tomitza, C., Schaschek, M., Straub, L. and Winkelmann, A. (2023). What is the Minimum to Trust AI?—A Requirement Analysis for (Generative) AI-based Texts. In Wirtschaftsinformatik 2023 Proceedings. 35 . 
  • Oberdorf, F., Schaschek, M., Weinzierl, S., Stein, N., Matzner, M.,  Flath, C. M., 2022. Predictive End-to-End Enterprise Process Network Monitoring. Business & Information Systems Engineering.
  • Oberdorf, Felix; Schaschek, Myriam; Stein, Nikolai; and Flath, Christoph, "Neural Process Mining: Multi-Headed Predictive Process Analytics in Practice" (2021). ECIS 2021 Research Papers. 54. 
  • Oberdorf, Felix; Wolf, Peter; Schaschek, Myriam; and Stein, Nikolai, "Strategic Decision Support System for Fleet Investments in the Vaccine Supply Chain" (2021). ICIS 2021 Proceedings. 3.