Cooperating for knowledge and innovation performance: the case of selected Central and Eastern European countries

  • Received June 15, 2020;
    Accepted November 25, 2020;
    Published December 11, 2020
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  • Article Info
    Volume 18 2020, Issue #4, pp. 264-274
  • Cited by
    3 articles

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This work is licensed under a Creative Commons Attribution 4.0 International License

The open innovation concept thrives on knowledge and information flow; their sources for the current innovation performance of the selected Central and Eastern European (CEE) countries have since triggered research interest. This research aimed to explore the different sources of knowledge and information for innovation and the extent to which these different sources contribute to the innovation performance of small and medium-sized enterprises in some selected CEE countries. The study assesses the influence of different knowledge and information sources and their relationships in SMEs engaged in manufacturing activities for innovation performance in the selected CEE countries using structural equation modeling. Data were sourced from the anonymized European Community Innovation Survey (CIS, 2012). The results show that internal sources of information and knowledge from innovative internal activities highly influence SMEs’ innovation performance in these CEE countries. Additionally, SMEs in the selected countries’ sources of information and knowledge influence firm cooperation arrangements. The result is significant for SMEs and policymakers to ensure fostering information and knowledge sharing and support of creating valuable knowledge for innovation, most importantly, in the aftermath of financial and economic crisis.

This work was supported by a grant provided by the scientific research project of the Czech Sciences Foundation Grant No. 20-03037S.

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    • Figure 1. Research analytical framework
    • Table 1. Description of dependent and independent variables
    • Table 2. Summary of the construct reliability and validity
    • Table 3. Goodness-of-fit
    • Table 4. PLS-SEM path coefficient
    • Conceptualization
      Solomon Gyamfi
    • Data curation
      Solomon Gyamfi
    • Investigation
      Solomon Gyamfi
    • Project administration
      Solomon Gyamfi
    • Resources
      Solomon Gyamfi
    • Software
      Solomon Gyamfi
    • Writing – original draft
      Solomon Gyamfi
    • Formal Analysis
      Jan Stejskal
    • Funding acquisition
      Jan Stejskal
    • Methodology
      Jan Stejskal
    • Supervision
      Jan Stejskal
    • Writing – review & editing
      Jan Stejskal