Data-Driven Business Model Innovation

Research Group 5

The research group combines 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.

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-based business models

Consequently, Research Group 5 combines theory construction on business model innovation and empirical analysis of sectoral data-driven innovation processes in an interdisciplinary team. The focus is 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 implies 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 are 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 use a mixed-method approach that integrates both qualitative and quantitative research methods. In addition, we use digital data analysis tools to develop and establish new digital research approaches.

 

Research Group Members

Publications (Selection)

Etsiwah, B., Hecht, S. and Hilbig, R. (2019) An Interdisciplinary Exploration of Data Culture and Vocational Training, in: Proceedings of the Weizenbaum Conference 2019.

Hilbig, R., Etsiwah, B. and Hecht, S. (2018) Berlin Start-ups – The Rise of Data-Driven Business Models, in: Proceedings of the ISPIM Innovation Symposium.

Schildhauer, T. (2018) Datenbasierte Geschäftsmodellinnovationen, in: Trend Report – Redaktion und Zeitung für moderne Wirtschaft.

 

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