Unraveling data from an idea management system of 11 radical innovation portfolios: Key lessons and avenues for artificial intelligence integration

• Published in: Journal of innovation and entrepreneurship Vol. 13; no. 1; pp. 1 - 24
• Main Authors: Jakobsen, Henning Sejer, Brix, Jacob, Jakobsen, Rune Sejer
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer 01.12.2024; Springer Berlin Heidelberg; Springer Nature B.V; SpringerOpen
• Subjects: Absorptive capacity; Action convergence; Artificial intelligence; Business and Management; Data analysis; Economic Geography; Economic Policy; Entrepreneurship; Idea management; Innovation capacity building; Innovation management; Innovations; Pattern recognition; Radical innovation; Strategic management; Absorptive capacity; Radical innovation; Action convergence; Innovation management; Innovation capacity building; Pattern recognition; Artificial intelligence; Idea management
• ISSN: 2192-5372; 2192-5372
• DOI: 10.1186/s13731-024-00368-6

In strategic and radical innovation, the degree of uncertainty and the amount of complexity is much higher compared to 'business as usual'. Therefore, idea management systems are often used to support such innovation processes. An interesting question is what we can learn from studying data in such idea management systems and what potential implications we can derive from the innovation management literature. In this study, we were allowed to access and analyze data from the same idea management system used in 11 radical innovation projects from the years 2012-2018. Our analysis unravels 8 findings that in different ways nuance or challenge current research on innovation management. Finally, we discuss how the integration of artificial intelligence (AI) in idea management systems can support innovation team members in increasing the innovation potential of the ideas that are elaborated.