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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Ahadzadeh, R., Dehghani, E., & Ghasemi, P. (2026). Towards sustainable closed-loop photovoltaic supply chains: A hybrid framework integrating reinforcement learning and mathematical models. Expert systems with applications, 296(D). https://doi.org/10.1016/j.eswa.2025.129182
Vetschera, R., & Knyazev, D. (2025). Does carrier collaboration require combinatorial auctions? European Journal of Operational Research, 326(3), 481-497. https://doi.org/10.1016/j.ejor.2025.04.021
Ghasemi, P., Ehmke, J. F., & Bicher, M. (2025). Managing equitable contagious disease testing: A mathematical model for resource optimization. Omega (United Kingdom), 135, Artikel 103305. https://doi.org/10.1016/j.omega.2025.103305
Goodarzian, F., & Ghasemi, P. (2025). A Case-Driven Simulation-Optimization Model for Sustainable Medical Logistics Network. Socio-Economic Planning Sciences. https://doi.org/10.1016/j.seps.2025.102271
Elting, S., Ehmke, J. F., & Gansterer, M. (2025). Preference learning for efficient bundle selection in horizontal transport collaborations. European Journal of Operational Research, 324(3), 953-968. https://doi.org/10.1016/j.ejor.2025.02.002
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