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Spinner Model: Prediction of Propensity to Innovate Based on Knowledge-Intensive Business Services

Author

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  • Ronnié Figueiredo

    (Beira Interior University)

  • João José Matos Ferreira

    (Beira Interior University)

Abstract

This study proposes a model for the prediction of propensity to innovate based on KIBS in the service sector of an emerging country (Brazil). The Spinner model presents, in a dynamic form, three dimensions: knowledge creation, knowledge transfer, and innovation, similar to the three axes of interaction of a fidget spinner, KIBS being the center. KIBS were divided in p-KIBS (professional KIBS) and t-KIBS (technological KIBS), according to the analysis carried out in 71 small, medium, and large firms. The Spinner model test was done based on three econometric models of logistic regression (logit), which examined the defined dimensions and variables. The model allowed us to evaluate prediction of propensity to innovate based on KIBS, considering the relationship between knowledge creation and transfer, where dimensions presented a positive sign, as expected. The findings contribute to theory development on knowledge intensive solutions, by revealing elements such as the relationship of knowledge creation and transfer with innovation in KIBS, and their relationships in the assessment prediction of propensity to innovate.

Suggested Citation

  • Ronnié Figueiredo & João José Matos Ferreira, 2020. "Spinner Model: Prediction of Propensity to Innovate Based on Knowledge-Intensive Business Services," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 11(4), pages 1316-1335, December.
    • Handle: RePEc:spr:jknowl:v:11:y:2020:i:4:d:10.1007_s13132-019-00607-2
    DOI: 10.1007/s13132-019-00607-2
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