With our interdisciplinary research, we empower product companies to thrive in a world of hardware, software, and service. More specifically, we investigate how emerging technologies and corresponding business model innovation can create sustainable competitive advantage for product companies. In addition, we develop, implement, and evaluate smart, connected systems that have the potential to create a meaningful impact for the better. Our research spans multiple disciplines such as information systems, technology and innovation management, and applied computer science. In our interdisciplinary projects we closely collaborate with researchers and industry experts from domains such as health, mobility, and energy.
We organize our core research activities in research labs. While we operate the Bosch Lab, we also contribute to the Centre for Digital Health Interventions. Please follow the links to the respective lab pages.
We aim at scientific rigor and industrial relevance. Hence, we publish our results in scientific journals and in books for practitioners and academics. Please find our most recent books below.
Our transdisciplinary research has been published in journals including Information Systems Research, MIS Quarterly Executive, New England Journal of Medicine AI, Diabetes Care, Applied Energy, Transportation Research, IEEE Internet of Things and at leading Computer Science and Information Systems conferences such as ACM CHI Conference on Human Factors in Computing Systems.
Wörner, A., Tiefenbeck, V., Wortmann, F., Meeuw, A., Ableitner, L., Fleisch, E., & Azevedo, I. (2022). Bidding on a peer-to-peer energy market: An exploratory field study. Information Systems Research, 33(3), 794-808.
Chanson, M., Bogner, A., Bilgeri, D., Fleisch, E., Wortmann, F. (2019), Blockchain for the IoT: Privacy-Preserving Protection of Sensor Data, Journal of the Association for Information Systems, 20(9), 1271-1307.
Bilgeri, D., Gebauer, H., Fleisch, E., Wortmann, F. (2019), Driving Process Innovation in Manufacturing Companies with IoT Field Data, MIS Quarterly Executive, 18(3), 191-207.
Lehmann, V., Zueger, T., Maritsch, M., Notter, M., Schallmoser, S., Bérubé, C., Wortmann, F. & Stettler, C. (2024). Machine Learning to Infer a Health State Using Biomedical Signals—Detection of Hypoglycemia in People with Diabetes while Driving Real Cars. New England Journal of Medicine AI, 1(3), AIoa230001
Lehmann, V., Zueger, T., Maritsch, M., Kraus, M., Albrecht, C., Bérubé, C., Wortmann, F. & Stettler, C. (2023). Machine learning for non‐invasive sensing of hypoglycaemia while driving in people with diabetes. Diabetes, Obesity and Metabolism, 25(6), 1668-1676.
Lehmann, V., Föll, S., Maritsch, M., van Weenen, E., Kraus, M., Lagger, S., Wortmann, F. & Stettler, C. (2023). Noninvasive hypoglycemia detection in people with diabetes using smartwatch data. Diabetes care, 46(5), 993.
Koch, K., Maritsch, M., Van Weenen, E., Feuerriegel, S., Pfäffli, M., Fleisch, E., ... & Wortmann, F. (2023, April). Leveraging driver vehicle and environment interaction: machine learning using driver monitoring cameras to detect drunk driving. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1-32.
Koch, K., Tiefenbeck, V., Liu, S., Berger, T., Fleisch, E., Wortmann, F. (2021), Taking Mental Health & Well-Being to the Streets: An Exploratory Evaluation of In-Vehicle Interventions in the Wild, Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, 1-15.
Ryder, B., Gahr, B., Egolf, P., Dahlinger, A., Wortmann, F. (2017), Preventing Traffic Accidents with In-Vehicle Decision Support Systems – The Impact of Accident Hotspot Warnings on Driver Behaviour, Decision Support Systems, 99, 64-74.
Wörner, A., Tiefenbeck, V., Wortmann, F., Meeuw, A., Ableitner, L., Fleisch, E., & Azevedo, I. (2022). Bidding on a peer-to-peer energy market: An exploratory field study. Information Systems Research, 33(3), 794-808.
Ableitner, L., Tiefenbeck, V., Meeuw, A., Woerner, A., Fleisch, E., Wortmann, F. (2020), User Behavior in a Real-World Peer-to-Peer Electricity Market, Applied Energy, 270.
Woerner, A., Meeuw, A., Ableitner, L., Wortmann, F., Schopfer, S., Tiefenbeck, V. (2019), Trading Solar Energy within the Neighborhood: Field Implementation of a Blockchain-Based Electricity Market, Energy Informatics.
Courses
We teach a wide variety of courses at HSG on all levels including Bachelor, Master, Doctoral and Executive Education. Please find our lectures here
Master and Bachelor Thesis
We also supervise Bachelor and Master thesis related to our research. If you are interested, please contact our lab leaders or check out the current theses topics here.
Professor, Senior Lecturer
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Student
Research Associate