Global imperatives for development of international production networks: case of Ukraine

  • Received August 4, 2019;
    Accepted January 24, 2020;
    Published February 7, 2020
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/ppm.18(1).2020.06
  • Article Info
    Volume 18 2020, Issue #1, pp. 57-69
  • TO CITE АНОТАЦІЯ
  • Cited by
    2 articles
  • 444 Views
  • 70 Downloads

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

The paper studies the theoretical and methodological principles, regularities, and new trends in the formation of international production networks (IPNs) in the global economic space. It determines the imperatives of their development, substantiating the priority nature of integrating national actors into IPNs. The author applies the methods of fuzzy clustering and classification using the artificial intelligence technologies to data on the dynamics of key economic and technological markers of 35 countries in the 2007–2016 time frame.
The work identifies a clustering-like structure in the sample country set; allowing determining patterns in the correlation between a country’s manifested potential for ascending into and within international production networks and certain development and international integration indicators. The sample is thus grouped into six clusters based on the degree of integration into IPNs. Due to the use of classification analysis, the rules for assigning a country to a particular cluster were obtained. According to the results of the study, it was concluded that the main imperative for the development of international production networks is innovative development. The overall concept of localization of Ukrainian enterprises at all stages of value creation within networks was offered.

view full abstract hide full abstract
    • Table 1. Distribution of countries by clusters by 2016
    • Table 2. Classification rules of a country’s membership in a particular cluster and assessment of the model’s accuracy
    • Table 3. The rules of a country’s belonging to the 2nd cluster in comparison with real values for Ukraine in 2016
    • Table 4. Reliability of classification analysis
    • Table 5. Indicators’ weight in attributing a country to a particular cluster