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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Feichtinger, G., Grass, D., Hartl, R. F., Kort, P. M., & Seidl, A. (2024). The digital economy and advertising diffusion models:Critical mass and the Stalling equilibrium. European Journal of Operational Research, 318(3), 966-978. https://doi.org/10.1016/j.ejor.2024.05.043
Choukolaei, H. A., Mirani, S. E., Ghasemi, P., & Jahangoshai Rezaee, M. (2024). System dynamics simulation follow-up fuzzy cognitive map for investigating the effect of risks on relief in crisis management. Engineering Applications of Artificial Intelligence, 136, Artikel 109002. https://doi.org/10.1016/j.engappai.2024.109002
Sun, Z., Zhao, L., Mehrotra, A., Salam, M. A., & Yaqub, M. Z. (Angenommen/Im Druck). Digital Transformation and Corporate Green Innovation: An Affordance Theory Perspective. Business Strategy and the Environment.
Otto, A., & Tilk, C. (2024). Intelligent design of sensor networks for data-driven sensor maintenance at railways. Omega (United Kingdom), 127, Artikel 103094. https://doi.org/10.1016/j.omega.2024.103094
Rauner, M., & Swyter, B. (2024). The Potential of the Community Emergency Paramedic Strategy for the Ambulance Rescue System in the City of Hamburg, Germany. Manuskript zur Veröffentlichung eingereicht.
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