Global migration processes analysis and modelling of migration attractiveness of countries through fuzzy logic

¹ The Bohdan Khmelnytsky National University of Cherkasy, 81 Shevchenko Blvd., Cherkasy, 18031, Ukraine
² State Institution of Higher Education “University of Educational Management”, 52A Sichovykh Striltsiv Str., Kyiv, 04053, Ukraine
³ Kyiv National University of Trade and Economics, 19 Kyoto Str., Kyiv, 02156, Ukraine
⁴ Cardinal Stefan Wyszyński University, 5 Dewajtis Str., 01-815 Warsaw, Poland

^* e-mail: abdanilchuk@gmail.com
^** e-mail: liubovkibalnyk@gmail.com
^*** e-mail: kovtun.oa71@gmail.com
^**** e-mail: Pursky_O@ukr.net
^† e-mail: zenstach@wp.pl

Abstract

The article deals with the analysis the current state of migration in the context of globalization and identifies the most important corridors for the labour movement. The main donor countries of migrants are developing countries, with low socio-economic indicators, difficult environmental conditions and high levels of poverty. According to forecasts, the most migratory flows will take place in the countries of North America and in Europe, which is due to rising trends in unemployment in the countries of the “third world” and the demand for cheap labour, changes in the structure of the economies of developed countries, changes in labour market demand. The main world regional corridors in 1990–2019 have been identified through statistical analysis. And their growing and declining trends. The need to use economic and mathematical modelling techniques to analyse and determine the migration attractiveness of recipient countries in an uncertain environment has been substantiated. It has been shown that fuzzy logic tools are the most effective in this case. Based on the results of the simulation using the Mamdani method, the world’s attractiveness rating for migration is calculated, which with a “high” thermo leads such countries as Italy, France, United Arab Emirates. The findings suggest that migrants are attracted by countries with the lowest inflation rates, high and average GDP per capita and average or low taxation levels.