Determinants of innovativeness of Slovak SMEs

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The integration of the Slovak Republic into the European Union and the globalization process create conditions that significantly reduce barriers to entry into particular markets, but, on the other hand, enhance the intensity of competition. The relevance of the study lies in the extent of the European Union’s support for the effectiveness of innovation activities in Slovakia. This paper investigates the influence of endogenous and exogenous factors on the competitiveness of Slovak enterprises over the period 2006–2018. The study is aimed at determining the causal relationship of factors that determine the competitiveness of enterprises. To investigate the relationship between the endogenous and exogenous factors, the Granger causality method is used. Mathematical models are used to identify the relationship between innovation expenditures on the one hand and different types of innovation activity with market expansion on the other. The results of the study provide a statistically significant relationship between the performance measured by the percentage of revenues of enterprises that have introduced innovations with a two-year lag and the concentration measured by the total R&D expenditure of an enterprise. The results of this study should also be used to ensure that, in the case of the Slovak SME sector, R&D expenditure is a significant driver of innovation in enterprises, as innovation in enterprises is expected to improve the quality of products and services, increase profits and expansion in domestic and foreign markets.

Acknowledgment
This paper has been supported by funds of the project VEGA No. 1/0240/20 and VEGA No. 1/0813/19 Managing the development of innovative and start-up forms of businesses in international environment and verification of INMARK concept, which has received funding from the Ministry of Education, Science, Research and Sport of the Slovak Republic.

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    • Figure 1. European innovation scoreboard 2019
    • Figure 2. Q-Q plots for X2, X3, X4, P2, P7, and P8
    • Table 1. ADF test
    • Table 2. Granger causality test – F statistics
    • Table 3. Granger causality test for combinations – F statistics
    • Conceptualization
      Zuzana Hajduova
    • Investigation
      Zuzana Hajduova, Tomáš Peráček
    • Software
      Zuzana Hajduova
    • Validation
      Zuzana Hajduova, Michaela Bruothová
    • Writing – original draft
      Zuzana Hajduova, Tomáš Peráček
    • Funding acquisition
      Tomáš Peráček
    • Supervision
      Tomáš Peráček
    • Writing – review & editing
      Tomáš Peráček
    • Data curation
      Jana Coroničová Hurajová
    • Methodology
      Jana Coroničová Hurajová
    • Resources
      Jana Coroničová Hurajová
    • Visualization
      Jana Coroničová Hurajová
    • Formal Analysis
      Michaela Bruothová
    • Project administration
      Michaela Bruothová