A Network-based Tool for Identifying Knowledge Risks in Data-Driven Business Models

Michael Fruhwirth, Viktoria Pammer-Schindler, Stefan Thalmann

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Data-driven technologies enable organizations to innovate new services and business models and thus hold the potential for new sources of revenue and business growth. However, such new data-driven business models impose new ways for unwanted knowledge spillovers. Current research on data-driven business models and knowledge risks provides little help to identify and discuss such novel risks within the innovation process. We have developed a network-based representation of data-driven business models within one case organization, where it helped to identify knowledge risks in the design process of data-driven business models. In this paper, we further evaluated the artifact through 17 interviews with experts from the domain of business models, data analytics and knowledge management. We found that the network-based representation is suitable to visualize, discuss and create awareness for knowledge risks and see types of data-related value objects and quantification of risks as two recommendations for further research.

Original languageEnglish
Title of host publicationProceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021
EditorsTung X. Bui
Number of pages10
ISBN (Electronic)9780998133140
Publication statusPublished - 2021
Event54th Annual Hawaii International Conference on System Sciences: HICSS 2021 - Virtual, Online, United States
Duration: 4 Jan 20218 Jan 2021

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
ISSN (Print)1530-1605


Conference54th Annual Hawaii International Conference on System Sciences
Country/TerritoryUnited States
CityVirtual, Online


  • knowledge protection
  • data-driven business model innovation
  • decision support
  • interview study

ASJC Scopus subject areas

  • Engineering(all)

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