Publications
With our publications we cover the most diverse research areas that arise in the field of man, task and technology. In addition to traditional Business Information Systems topics such as knowledge management and business process management, you will also find articles on current topics such as blended learning, cloud computing or smart grids. Use this overview to get an impression of the range and possibilities of research in Business Information Systems at the University of Duisburg-Essen.
Type of Publication: Article in Collected Edition
Show me the Money: How to monetize data in data-driven business models?
- Author(s):
- Woroch, Robert; Strobel, Gero
- Title of Anthology:
- Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI)
- Location(s):
- Nürnberg, Germany
- Publication Date:
- 2022
- Keywords:
- Data-Driven Business Model, Big Data, Internet of Things, Value Creation, Digitalization
- Talk associated with this publication:
- 17th International Conference on Wirtschaftsinformatik (WI22)
- Citation:
- Download BibTeX
Abstract
Increasing digitization and the associated tremendous usage of technology have led to data of unprecedented quantity, variety, and speed, which is generated, processed, and required in almost all areas of industry and life. The value creation and capturing from data presents companies with numerous challenges, as they must create or adapt appropriate structures and processes. As a link between corporate strategy and business processes, business models are a suitable instrument for meeting these challenges. However, few research has been conducted focusing on data-based monetization in the context of data-driven business models so far. Based on a systematic literature review the paper identifies five key components and 23 characteristics of data-driven business models having crucial influence on data-based value creation and value capturing and thus on monetization. The components represent key factors for achieving commercial benefits from data and serve as guidance for exploring and designing suitable data-driven business models.