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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Elting, S., Ehmke, J. F., & Gansterer, M. (2024). Collaborative transportation for attended home deliveries. Networks, 84(1), 84-106. https://doi.org/10.1002/net.22216
Shamrooz Aslam, M., Bilal, H., S,band, S., & Ghasemi, P. (2024). Modeling of nonlinear supply chain management with lead-times based on Takagi-Sugeno fuzzy control model. Engineering Applications of Artificial Intelligence, 133, Artikel 108131. https://doi.org/10.1016/j.engappai.2024.108131
Saini, M., Prakash, G., Yaqub, M. Z., & Agarwal, R. (2024). Why do people purchase plant-based meat products from retail stores? Examining consumer preferences, motivations, and drivers. Journal of Retailing and Consumer Services, 81, Artikel 103939. https://doi.org/10.1016/j.jretconser.2024.103939
Alabdali, M. A., Khan, S. A., Yaqub, M. Z., & Alshahrani, M. A. (2024). Harnessing the Power of Algorithmic Human Resource Management and Human Resource Strategic Decision-Making for Achieving Organizational Success: An Empirical Analysis. Sustainability (Switzerland), 16(11), Artikel 4854. https://doi.org/10.3390/su16114854
Köhler, C., Campbell, A. M., & Ehmke, J. F. (2024). Data-driven customer acceptance for attended home delivery. OR Spectrum, 46, 295-330. https://doi.org/10.1007/s00291-023-00712-4
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