Welcome to
the Department of Business Decisions and Analytics
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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Chen, B., & Knyazev, D. (2023). Symmetric mechanism design: Comment. Journal of Mathematical Economics, 109, [102910]. https://doi.org/10.1016/j.jmateco.2023.102910
Akbari, K., Eigruber, M., & Vetschera, R. (2023). Risk attitudes: The central tendency bias. EURO Journal on Decision Processes, 12(100042). https://www.sciencedirect.com/science/article/pii/S2193943823000158?via%3Dihub
Caulkins, J. P., Grass, D., Feichtinger, G., Hartl, R. F., Kort, P. M., Kuhn, M., Prskawetz, A., Sanchez-Romero, M., Seidl, A., & Wrzaczek, S. (2023). The hammer and the jab: Are COVID-19 lockdowns and vaccinations complements or substitutes. European Journal of Operational Research, 311(1), 233-250. https://doi.org/10.1016/j.ejor.2023.04.033
Kadzinski, M., Vetschera, R., & Zaraté, P. (2023). Preface to the Special Issue on Decision Support: Combining Technology and Algorithms to Solve Complex Problems. International Transactions in Operational Research, 30(6), 3398-3399. https://doi.org/10.1111/itor.13312
Fröhlich, G. E. A., Gansterer, M., & Dörner, K. F. (2023). Safe and secure vehicle routing: a survey on minimization of risk exposure. International Transactions in Operational Research, 30(6), 3087-3121. https://doi.org/10.1111/itor.13130
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