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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Rist, Y., Tilk, C., & Forbes, M. (2024). Benders Decomposition with Delayed Disaggregation for the Active Passive Vehicle Routing Problem. European Journal of Operational Research, 318(3), 836-850. https://doi.org/10.1016/j.ejor.2024.05.041
Feichtinger, G., Grass, D., Hartl, R. F., Kort, P. M., & Seidl, A. (2024). The digital economy and advertising diffusion models:Critical mass and the Stalling equilibrium. European Journal of Operational Research, 318(3), 966-978. https://doi.org/10.1016/j.ejor.2024.05.043
Choukolaei, H. A., Mirani, S. E., Ghasemi, P., & Jahangoshai Rezaee, M. (2024). System dynamics simulation follow-up fuzzy cognitive map for investigating the effect of risks on relief in crisis management. Engineering Applications of Artificial Intelligence, 136, Artikel 109002. https://doi.org/10.1016/j.engappai.2024.109002
Knyazev, D. (2024). Buyers’ welfare maximizing auction design: comment. International Journal of Game Theory, 53(3), 1073-1075. https://doi.org/10.1007/s00182-024-00904-4
Otto, A., & Tilk, C. (2024). Intelligent design of sensor networks for data-driven sensor maintenance at railways. Omega (United Kingdom), 127, Artikel 103094. https://doi.org/10.1016/j.omega.2024.103094
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