Welcome to the Department of Business Analytics and Decision Making
The Department of Business Decisions and Analytics is dedicated to high-quality research in quantitative economics and decision support. Building upon a data-driven and optimization-oriented perspective, we develop models and solve complex problems in today’s rapidly changing business environment. We are committed to research-based and competent teaching and try to convey a deep understanding of methods and real-world problems.
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Los, J., Schulte, F., Gansterer, M., Hartl, R. F., Spaan, M. T. J., & Negenborn, R. R. (2025). Large-scale collaborative vehicle routing. Annals of Operations Research, 350(1), 201-233. https://doi.org/10.1007/s10479-021-04504-3
Roy, A., Majumdar, A., Ghasemi, P., Sheikh, W., & Ali, S. M. (2025). Investigating the environmental losses in the textile industry of an emerging economy: implications for a sustainable and circular economy. Computers and Industrial Engineering, 209, Artikel 111353. https://doi.org/10.1016/j.cie.2025.111353
Abandansari, S. A. M., Ghasemi, P., Attar, A., Goodarzian, F., & Ahmadi, S. A. (2025). A hybrid biomass supply chain optimization approach using sequential adaptive fuzzy inference learning: Insights from a cogeneration system in Europe. Results in Engineering, 26, Artikel 105261. https://doi.org/10.1016/j.rineng.2025.105261
Amlashi, D. M., Voelz, A., & Karagiannis, D. (2025). Artificial Intelligence and Internet of Things: A Neuro-Symbolic Approach for Automated Platform Configuration. Neurosymbolic Artificial Intelligence. https://doi.org/10.1177/29498732251340187
Schleibaum, S., Teusch, J., Scherr, Y. O., & Müller, J. P. (2025). Spatial-Temporal Patterns of E-Scooter Demand Prediction Across Cities. Transportation Research Procedia, 86, 48-55. https://doi.org/10.1016/j.trpro.2025.04.007
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