Combining Digitalization and Behavioral Economics
Networked products – from smart meters to cars to heating systems to step counters – make available ever-larger amounts of data. In our research, we
- develop machine learning techniques that extract information from such data traces and provide insights into both the product states and the behavior of their users,
- make use of the data to better understand how individuals act and respond to behavioral interventions in natural environments,
- develop scalable behavioral interventions, e.g., to foster resource conservation and safer driving, and
- help create digital services that make use of the nexus of digitalization and behavioral economics.
Our research goal is to advance the methods and theories in our area of work as well as to develop and validate information systems that deploy the results in the field. For private individuals, our research shall lead to information systems that help them to make better decisions in their every-day lives (e.g., systems that mitigate decision biases regarding energy use). For companies, the results help to develop tools to gain better customer insights, to create products that use behavioral data in a rewarding way, and ultimately to craft digital services around their tangible products.
Recent projects have been named research highlight (e.g., by Nature Energy or the Swiss Federal Office of Energy), served as basis of decision-making for regulatory bodies (e.g., the Smart Meter Impact Assessment for Switzerland) or led to successful spinoff companies (BEN Energy AG and Amphiro AG).
With our work, we are an active member of the Information Systems (IS) and Energy Informatics community. Results have been published in the leading IS and energy journals incl. MIS Quarterly, Management Science, Applied Energy, Energy, Energy Policy, and Transportation Research. The >list of publications is available here.