Exploring determinants of innovation potential of enterprises in Kazakhstan

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The study aims to analyze the innovation potential of enterprises, explain the use of the binary regression methodology, and explore different indicators of the enterprises in the regions of Kazakhstan for building an effective management strategy. Methodological substantiation is based on the complex survey data analysis, provided by the World Bank Enterprises Survey (WBES) for Kazakhstan. WBES database has covered a sociological survey of enterprises, which was conducted using a random survey and representativeness among 1,296 enterprises, mainly in the production sector. Besides, the data were collected among companies regarding their experience in environmental perception (including innovation activity), in which they worked. The results have demonstrated that the age of the company, exporter status, type, sector, or activity – all these have a positive influence on the company’s tendency to innovations. However, as part of the study, it has found out that competitors in the marketplace and regions of activity of enterprises predominantly negatively affect the prospects of introducing innovation. It was also in evidence that the same factors (foreign ownership, advanced training, type, size, and sector of an enterprise) are essential determinants of product, technology, R&D, ICT, and innovation. Obtained results can be used by enterprises for building an effective management strategy of own business innovative development, as well as by local authorities to upgrade the competitive performance.

Acknowledgments
This study has been funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (Grant “Priorities and mechanisms of inclusive regional development of Kazakhstan in the context of overcoming the economic recession” No. AP09259004).

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    • Table 1. Classification of enterprises in Kazakhstan by their size
    • Table 2. Occurrence of innovations in enterprises of Kazakhstan
    • Table 3. Probit models applied to the determinants of innovation
    • Table 4. Tobit models applied to aspects that influence overall outcomes of innovation
    • Conceptualization
      Anel Kireyeva, Akan Nurbatsin
    • Formal Analysis
      Anel Kireyeva
    • Investigation
      Anel Kireyeva, Akan Nurbatsin, Aigerim Yessentay, Nazyken Bagayeva
    • Methodology
      Anel Kireyeva, Akan Nurbatsin
    • Project administration
      Anel Kireyeva, Sharbanu Turdalina
    • Supervision
      Anel Kireyeva, Nazyken Bagayeva
    • Visualization
      Anel Kireyeva, Aigerim Yessentay, Nazyken Bagayeva
    • Writing – original draft
      Anel Kireyeva
    • Writing – review & editing
      Anel Kireyeva, Sharbanu Turdalina
    • Funding acquisition
      Akan Nurbatsin
    • Resources
      Akan Nurbatsin, Aigerim Yessentay, Nazyken Bagayeva, Sharbanu Turdalina
    • Software
      Aigerim Yessentay, Nazyken Bagayeva, Sharbanu Turdalina