TY - GEN
T1 - A Network-based Tool for Identifying Knowledge Risks in Data-Driven Business Models
AU - Fruhwirth, Michael
AU - Pammer-Schindler, Viktoria
AU - Thalmann, Stefan
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - knowledge protection
KW - data-driven business model innovation
KW - decision support
KW - interview study
UR - http://www.scopus.com/inward/record.url?scp=85108344689&partnerID=8YFLogxK
U2 - http://hdl.handle.net/10125/71254
DO - http://hdl.handle.net/10125/71254
M3 - Conference paper
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 5218
EP - 5227
BT - Proceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021
A2 - Bui, Tung X.
T2 - 54th Annual Hawaii International Conference on System Sciences
Y2 - 4 January 2021 through 8 January 2021
ER -