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Data-driven Business Model Innovations

The research group combined theory construction on business model innovation with the empirical analysis of sectoral data-led innovation processes, e.g. in education, open data, mobility or the creative industries. Today’s production of infinite amounts of data by humans has a lasting impact on how business models are designed, even forcing well-established market participants to rethink and alter their business models. Data-driven business model innovation is therefore highly relevant for corporate practice and policy.

This research group conducted research at the Weizenbaum Institute from 2017 to 2022. In the newly launched research program, research will henceforth be organised in 16 research groups. These will be flanked and supported by the new Weizenbaum Digital Science Center.

Business model research

In science, business model research has been of increasing relevance since the 1990s. However, the previous research in the course of digitization and the associated networked society must be rethought and researched. In today's society, people produce endless amounts of data that have a lasting impact on business model design. The high agility and innovative power of start-ups forces established market players to rethink their business models. In some industries, such as the automotive sector, the development of digital business models may even change entire value chains and have a huge impact on employment. Data-driven business model innovation is therefore highly relevant for corporate practice and policy.

Analysis of data-driven business models

Consequently, the Research Group combined theory construction on business model innovation and empirical analysis of sectoral data-driven innovation processes in an interdisciplinary team. The focus was on the analysis of data-driven business models from different sectors, such as Education, Open Data / Open Governance, Mobility and Creative Industries, aiming to derive definitions, taxonomies or patterns as a first step. This implied exploring the data-driven business model innovation process itself and analyzing how companies develop data-driven business models in their own or in other industries. Innovative digital methods and tools were designed to empower companies to create radical, data-driven business models or to incrementally optimize certain areas with digital data.

As part of our research, we used a mixed-method approach that integrated both qualitative and quantitative research methods. In addition, we used digital data analysis tools to develop and establish new digital research approaches.

The Research Group on Twitter: JWI_DataDriven

The research group's podcast series "Voices for the Networked Society" contains individual episodes primarily on the topic of "digitalisation in education and continuing education".


Prof. Dr. Dr. Thomas Schildhauer, Associated Principal Investigator

Dr. André Renz, Research Group Lead

  • Ana Burgueño Hopf
  • Bennet Etsiwah
  • Eva-Marie Geier
  • Stefanie Hecht