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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Yaqub, M. Z., Yaqub, R. M. S., Khan, S. Y., & Murad, M. (2024). How does the government's sustainable consumption policy enkindle sustainable consumption behaviors in the consumer public? Cleaner and Responsible Consumption, 13, Artikel 100196. https://doi.org/10.1016/j.clrc.2024.100196
Vetschera, R., Knyazev, D., & Rehsmann, D. (2024). Properties of bundle valuations in carrier collaboration. Central European Journal of Operations Research, 32(2), 241-266. https://doi.org/10.1007/s10100-023-00873-1
Burian, M., Köhler, C., Campbell, A. M., & Ehmke, J. F. (2024). Service time window selection for attended home deliveries: a case study for urban and rural areas. Central European Journal of Operations Research, 32(2), 267-294. https://doi.org/10.1007/s10100-023-00879-9
Hess, C., Müller, A.-G., Dörner, K. F., & Vigo, D. (2024). Waste collection routing: a survey on problems and methods. Central European Journal of Operations Research, 32(2), 399-434. https://doi.org/10.1007/s10100-023-00892-y
Ferdowsi, A., & Dehghan Chenary, M. (2024). Gain and Pain in Graph Partitioning: Finding Accurate Communities in Complex Networks. Algorithms, 17(6), Artikel 226. https://www.mdpi.com/1999-4893/17/6/226
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