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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Ghasemi, P., Goodarzian, F., Simic, V., & Babaee Tirkolaee, E. (2023). A DEA-based simulation-optimisation approach to design a resilience plasma supply chain network: a case study of the COVID-19 outbreak. International Journal of Systems Science: Operations & Logistics, 10(1), [2224105]. https://doi.org/10.1080/23302674.2023.2224105
Krebs, C., & Ehmke, J. F. (2023). Solution validator and visualizer for (combined) vehicle routing and container loading problems. Annals of Operations Research, 326(1), 561-579. https://doi.org/10.1007/s10479-023-05238-0
Momenitabar, M., Ebrahimi, Z. D., Bengtson, K., Helmi, W., & Ghasemi, P. (2023). An integrated machine learning and quantitative optimization method for designing sustainable bioethanol supply chain networks. Decision Analytics Journal, 7, [100236]. https://doi.org/10.1016/j.dajour.2023.100236
Guo, S. (2023). The Preference Reversal in a Group When Aggregating Three Types of Decision-Makers Based on Regret Theory. 98-104. Beitrag in 23rd International Conference on Group Decision and Negotiation, Tokio, Japan.
Badghish, S., Ali, I., Ali, M., Yaqub, M. Z., & Dhir, A. (2023). How socio-cultural transition helps to improve entrepreneurial intentions among women? Journal of Intellectual Capital, 24(4), 900-928. https://doi.org/10.1108/JIC-06-2021-0158, https://doi.org/10.1108/JIC-06-2021-0158
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