Research at the Chair of Digital Transformation Management is based on the assumption that management in contemporary organizations is embedded in a societal process of digitalization. From this understanding, three intertwined focus areas emerge.


  • Digital business models in established areas of competition: In this focus area, research is carried out to understand the nature of digital business models and ecosystems in contexts that traditionally do not belong to IT or digital industries. Successful business models in such areas blend new technological opportunities with existing assets such as in IoT platform ecosystems. Apart from that, they target customer demands, which are increasingly affected by digitalized everyday lives. Finally, these business models do not only realize potentials for digital value creation, but also build upon value capture architectures that allow economic benefits for all associated actors.

  • Organizational (re-)configuration for digital business: In this focus area, research is carried out to understand how structural, operational and strategic measures help established organizations to successfully develop and operate digital business models in digital business ecosystems. Here, the incorporation of new roles for leaders (such as a chief digital officer) or units (such as the IT function) is subject to critical scrutiny. Furthermore, strategies to build and cultivate knowledge in emerging digital business ecosystems are under investigation. Finally, the management of emerging tensions between established and evolving structures and strategies by measures of hybrid organizing is an important field of inquiry. 

  • Human-centric use of artificial intelligence (AI): In this focus area, research is carried out with the goal of designing sustainable socio-technical systems of AI use. The importance of data analytics in general, and machine learning in particular, increasingly plays a key role in both digital business models (as an integral part of value creation) and within organizations (as an integral part of business processes). Designed artifacts aim to increase social sustainability of systems of AI use by attending to issues related to privacy, competence, and autonomy.

Research in these areas is carried out with international partners and is based on real-world data gathered in cooperation/collaboration with industry-leading and globally operating firms. Our work is not limited to certain industry contexts. However, a particular focus of our research activities has been the automotive, financial services and manufacturing industries.