Abstract
AbstractPurpose The purpose of this work is to determine the impact of global mobility on the sustainability of the economy, as well as to develop recommendations for human capital management to optimize migration flows from a sustainable development perspective. Design/Methodology/Approach The authors conduct optimization modeling according to the following sequence of steps in order to develop a scientific approach to human capital management as a basis for global mobility for the sustainable development of the economy. At the first step, the regression analysis determines the dependence of indicators of sustainable development on migration flow. The second step determines the dependence of the migration flow on the indicators of human capital management—a model of multiple linear regression is compiled. In the third step, the optimal migration flow is determined by the expert method and by averaging. In the fourth step, the simplex method reveals the values of human capital management indicators, at which the optimal value of migration flow is achieved. Findings It was revealed that optimization allows increasing of the global competitiveness index by 2.35 times, the economic growth rate by 3.09 times, GDP per capita—by 26.23 times, but the sustainable development index will decrease by 0.27 times. Originality/Value It is justified that international migration in the modern world economy as a whole contributes to the sustainable development of national economic systems. It improves the global competitiveness of the economy, accelerates economic growth and increases GDP per capita, but impedes the achievement of sustainable development goals. The results of modeling and optimization showed that the optimal migration flow in the world economy on average is 321.2 people per 1000 people of the population. To achieve it, recommendations on human capital management are proposed.KeywordsGovernanceHuman capitalHuman developmentBasisGlobal mobilityInternational migrationSustainable developmentEconomyJEL CodeC31C33C38F63Q01Q56O11O12O31O32O33O38P25P48R11R13R58
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