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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Haferkamp, J., & Ehmke, J. F. (2022). Effectiveness of demand and fulfillment control in dynamic fleet management of ride-sharing systems. Networks, 79(3), 314-337. https://doi.org/10.1002/net.22062
Jell-Ojobor, M., Alon, I., & Windsperger, J. (2022). The choice of master international franchising: A modified transaction cost model. International Business Review, 31(2), Artikel 101942. https://doi.org/10.1016/j.ibusrev.2021.101942
Aringhieri, R., Hirsch, P., Rauner, M., Reuter-Oppermann, M., & Sommersguter-Reichmann, M. (2022). Central European journal of operations research (CJOR) "operations research applied to health services (ORAHS) in Europe: general trends and ORAHS 2020 conference in Vienna, Austria". Central European Journal of Operations Research, 30(1), 1-18. https://doi.org/10.1007/s10100-021-00792-z
Kinast, A., Dörner, K. F., & Rinderle-Ma, S. (2022). Combing metaheuristics and process mining: Improving cobot placement in a combined cobot assignment and job shop scheduling problem. in Procedia Computer Science (Band 200, S. 1836-1845). Elsevier. https://doi.org/10.1016/j.procs.2022.01.384
Chen, B., Chen, B., & Knyazev, D. (2022). Information disclosure in dynamic research contests. RAND Journal of Economics, 53(1), 113-137. https://doi.org/10.1111/1756-2171.12402
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