Tatjana Bennat and Rolf Sternberg published their new paper about barriers that hamper combinatorial knowledge dynamics in practice at European Planning Studies.
Due to the greater involvement of users and the co-creation of ideas with suppliers or other firms, innovation processes are increasingly based upon combinatorial knowledge. Thus, innovation is not restricted to research-and-development-driven, science-based knowledge, but is also the result of experiences and creative thinking. This has consequences for regional innovation policies because each knowledge type differs regarding policy requirements. Contributing to the under-researched topic of the barriers of combinatorial knowledge dynamics in practice, the aim of this paper was to guide government policies in transferring theoretical insights into a contemporary, place-based policy approach. In accordance with the knowledge base approach this paper clearly distinguishes between analytical knowledge, synthetic knowledge and symbolic knowledge. The analysis consists of in-depth interviews, conducted in two case-study regions in Germany. This paper deduces several local factors that have hampered combinatorial knowledge dynamics, and identifies obstacles that can only be overcome at the federal state or national levels.
The paper is part of the research project InDUI.
Bennat, T.; Sternberg, R. (2020): Knowledge bases in German regions: what hinders combinatorial knowledge dynamics and how regional innovation policies may help. European Planning Studies 28(2), 319-339. DOI: 10.1080/09654313.2019.1656168