WI2023 – Track: Prescriptive analytics, mobility & logistics
Track description
The creation and widespread use of neologisms like Economy 4.0, Industry 4.0, or Logistics 4.0, emphasizes that digitalization has released fields to a new era of information systems. Immediate communication via Internet, sensor technologies, data analysis, autonomous technologies and robotics: the influences of digitalization are ubiquitous. In logistics, service providers are actively implementing these technologies and related methodologies into their processes in order to cope with the challenges of globalization and to optimize their work flows in order to stay competitive. In order to be able to deal with the complexity of the resulting planning problems, it is of utmost importance to develop and make use of advanced analytical methods.
In the above context, the track Prescriptive analytics, mobility and logistics focuses on contributions that apply and bring forward the methodology of prescriptive analytics, operations research, management science, decision science, machine learning, statistics, algorithmic game theory, queuing theory, or other related fields in applied mathematics, that are adequately motivated to deal with aspects of mobility and logistics in the design of information systems. We also welcome well-founded empirical research that addresses significant theoretical and practical issues in these fields.
Track Topics
Topics that are of interest cover the full spectrum of problems in logistics and mobility. They include but are not limited to:
- Problems and challenges in the field of intermodal transport (e.g., port operations, container terminals, shunting yards)
- Problems arising in the field of electrical vehicles or autonomous technologies, such as automated guided vehicles and aerial drones (e.g., vehicle routing, green vehicle routing, location of charging facilities)
- Applications in the field of urban mobility solutions, such as public transportation, bike sharing, car sharing, or ride sharing
- Analysis of novel intelligent, green transportation concepts (e.g., e-Highways, platooning)
- Design and analysis of transportation networks, incl. traffic flow modeling and management
- Location and layout theory
- Warehouse management
- Last-mile transport
- Revenue management and pricing with applications in logistics
- Routing games and congestion pricing
- Performance analysis, forecasting methods, value-driven and uncertainty-aware data processing in transportation networks and logistics
Track Chairs
Prof. Dr. Martin Bichler
Technische Universität München
Martin Bichler is a Professor of Decision Sciences & Systems at the Faculty of Computer Science, TU Munich. His research interests include market design, equilibrium learning, and machine learning and optimization with applications in economics. Martin is an Associate Editor in journals such as Information Systems Research, the INFORMS Journal on Computing, and Naval Research Logistics, among others.
Prof. Dr. Jan Fabian Ehmke
Universität Wien
Jan Fabian Ehmke is a Professor of Business Analytics at the University of Vienna. His research interests include analyzing transactional data and processing information to improve the efficiency, environmental friendliness, and reliability of applications in transportation, logistics, and mobility. Jan is an Associate Editor of the journals OR Spectrum and Flexible Services and Manufacturing. He is currently president of the INFORMS Transportation and Logistics Society.
Prof. Dr. Natalia Kliewer
Freie Universität Berlin
Natalia Kliewer is Professor of Information Systems at Freie Universität Berlin. Her research interests include the design of decision support systems in transportation and logistics, as well as network models and algorithms for applications in the aviation industry, public transportation, and revenue management. Natalia is Department Editor for Decision Analytics & Data Science at the journal Business & Information Systems Engineering and Associate Editor at the journals Public Transport Journal and INFORMS Transportation Science.
Jun.-Prof. Dr. Lin Xie
Leuphana Universität Lüneburg
Lin Xie is a junior professor of Information Systems, esp. Operations Research at the Leuphana University of Lüneburg. Her research interests include machine learning, operations research, and emerging technology (including digital twins, robotics, 5G, and virtual reality) with applications to innovative developments in digital logistics and transportation. Lin co-organized MKWI 2018 in Lüneburg and was a member of the program committee at MKWI 2016 and 2018, and Associate Editor at the WI 2021 conference.
Associate Editors
- Bastian Amberg, Freie Universität Berlin
- Christian Bierwirth, University Halle Wittenberg
- Catherine Cleophas, CAU Kiel
- Andreas Fink, Helmut Schmidt University of Hamburg
- Dirk C. Mattfeld, Technical University of Braunschweig
- Stefan Lessmann, HUB
- Lars Mönch, University of Hagen
- Franz Rothlauf, Johannes Gutenberg University of Mainz
- Claudius Steinhardt, Bundeswehr University Munich
- Stefan Voss, University of Hamburg
- Richard Hartl, Universität Wien
- Karl Dörner, Universität Wien
- Martin Ulmer, Universität Magdeburg