Assessment of public welfare in Ukraine in the context of the COVID-19 pandemic and economy digitalization

  • Received January 20, 2021;
    Accepted March 18, 2021;
    Published March 29, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/ppm.19(1).2021.35
  • Article Info
    Volume 19 2021, Issue #1, pp. 416-431
  • TO CITE АНОТАЦІЯ
  • Cited by
    8 articles
  • 1218 Views
  • 797 Downloads

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

With the emergence of the global COVID-19 pandemic in 2019, a process of transformation of the modern economic system took place, which requires new approaches to assessing economic processes. One of such processes is the assessment of public welfare. The purpose of this study is to develop an approach to assessing the level of public welfare of the population of Ukraine in the context of the COVID-19 pandemic and economy digitalization. To solve this problem, the methods of artificial intelligence, in particular the method of fuzzy sets theory, which allows using the incomplete information and making high-quality forecast calculations, are used. The factors influencing the level of public welfare during the COVID-19 pandemic have been identified. These are the following factors: gross domestic product, poverty rate, welfare index, human development index, subsistence level, and indicators that characterize the COVID-19 pandemic (i.e. the total number of COVID-19 cases, the total number of deaths from COVID-19, and the total number of vaccinations from COVID-19 in Ukraine). Using fuzzy sets theory, an economic-mathematical model for assessing the level of public welfare in the context of the COVID-19 pandemic in Ukraine was built. Two-dimensional dependences of the level of public welfare of Ukraine in the context of the COVID-19 pandemic on indicators such as gross domestic product, subsistence level, and the total number of cases of COVID-19 in Ukraine were obtained. The results of the study established that the level of public welfare in the context of the COVID-19 pandemic on the 0-100 scale is predicted to be as follows points: 2021 – 17, 2022 – 23, 2023 – 27, 2024 – 19, 2025 – 35 and will not meet international standards.

view full abstract hide full abstract
    • Figure 1. Ukraine’s GDP in current prices, 2020
    • Figure 2. Poverty index of Ukraine, 2020
    • Figure 3. Legatum Prosperity Index of Ukraine, 2020
    • Figure 4. Components of the integral index Legatum Prosperity Index of Ukraine, 2020
    • Figure 5. Human Development Index of Ukraine, 2020
    • Figure 6. Living wage in Ukraine, 2020
    • Figure 7. Coronavirus cases in Ukraine, 2021
    • Figure 8. Total coronavirus deaths in Ukraine, 2021
    • Figure 9. Structural model for assessing public welfare in Ukraine in the context of the COVID-19 pandemic
    • Figure 10. Membership function of the output IPWU
    • Figure 11. The results of the assessment and forecasting the level of public welfare in Ukraine in the context of the COVID-19 pandemic
    • Figure 12. Graph representing the two-dimensional correlation of IPWU (GDP, CC)
    • Figure 13. Graph representing the two-dimensional correlation of IPWU (LW, CC)
    • Table 1. Generalization of values of indicators in an estimation digital economic model of public welfare level in Ukraine in the context of the COVID-19 pandemic
    • Table 2. Database of the IPWU value
    • Conceptualization
      Serhii Kozlovskyi, Viktoriia Baidala
    • Investigation
      Serhii Kozlovskyi
    • Methodology
      Serhii Kozlovskyi, Iaroslav Petrunenko
    • Project administration
      Serhii Kozlovskyi
    • Supervision
      Serhii Kozlovskyi
    • Validation
      Serhii Kozlovskyi, Viktoriia Baidala
    • Writing – original draft
      Serhii Kozlovskyi, Iaroslav Petrunenko
    • Writing – review & editing
      Serhii Kozlovskyi, Viktoriia Baidala
    • Resources
      Iaroslav Petrunenko, Viktoriia Baidala
    • Software
      Iaroslav Petrunenko, Tetiana Kulinich
    • Formal Analysis
      Viktoriia Baidala, Viktoriia Myronchuk
    • Data curation
      Viktoriia Myronchuk, Tetiana Kulinich
    • Funding acquisition
      Viktoriia Myronchuk, Tetiana Kulinich
    • Visualization
      Viktoriia Myronchuk, Tetiana Kulinich