As a scientist

Since the early stages of my scientific career, I have always been driven by my research questions. The method at hand has to fit the research questions. My research focuses on two important “megatrends”: digitalization and climate change. The term coined by John Naisbitt describes processes that largely affect societies at different levels over a large period. While the exact definition may be vague, all institutional players from governments (e.g. Germany, EU) to companies (e.g. EY, Blackrock) agree that digitalization and climate change are among the megatrends. Therefore, we can be sure that research on these topics will remain as essential as the effects of these trends on our societies. Given the complexity of such megatrends, they have to be investigated from different perspectives, thus involving various methods and an interdisciplinary approach.

Throughout my work experience in science and science advice, I have used a large variety of methods including theoretical analysis, event studies, vector autoregressions, surveys, systematic literature reviews, machine learning, and of course the method I’ve used most often experiments. Given my hands-on mentality, I have even practical experience in the development of open science tools, with one being publicly available on GitHub (https://github.com/MaXLab-OVGU/MTVE) and the second one being in development. This methodological variability enables me to work successfully with researchers from other disciplines, e.g. information systems, environmental psychology, software engineering, bio-informatics, and neuro-information technology.