High Innovativeness of SMEs and the Configuration of Learning-by-Doing, Learning-by-Using, Learning-by-Interacting, and Learning-by-Science: a Regional Comparison Applying Fuzzy Qualitative Comparative Analysis

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Abstract

This paper proposes a holistic approach for investigating high innovation performance in SMEs by comparing different German regions. Invoking insights from the innovation mode concept and existing literature on regional innovation, we apply a qualitative comparative analysis (QCA) of 47 interviews with SMEs to show that high innovativeness is based on a bundle of conditions summarized as mechanisms of learning-by-doing, learning-by-using, learning-by-interacting, and learning-by-science. The results indicate that only parts of the DUI mode, in combination with the STI mode, can explain high innovativeness. This has implications for managers as well as for innovation policy, highlighting that there is no universal “best way” to become highly innovative.

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Bennat, T. (2022). High Innovativeness of SMEs and the Configuration of Learning-by-Doing, Learning-by-Using, Learning-by-Interacting, and Learning-by-Science: a Regional Comparison Applying Fuzzy Qualitative Comparative Analysis. Journal of the Knowledge Economy, 13(2), 1666–1691. https://doi.org/10.1007/s13132-021-00774-1

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