COGNITIVE APPROACH TO MODELING POPULATIONʼS QUALITY OF LIFE

Anastasiia DIDENKO
Ph.D. (Economics), Associate Professor (Dnipropetrovsk State University of Internal Affairs), Ukraine
ORCID iD: orcid.org/0000-0003-1136-403X
didenko.naya@gmail.com

Yevheniia KOVALENKO-MARCHENKOVA
Ph.D. (Economics), (Dnipropetrovsk State University of Internal Affairs), Ukraine
ORCID iD: orcid.org/0000-0001-7350-7740
kovalenko.marchenkova@gmail.com

Olena KRAVETS
Ph.D. (Economics), (Classic Private University), Ukraine
ORCID iD: orcid.org/0000-0002-2980-5238
ekonom.kpu@gmail.com

Rafał LIZUT
Ph.D. hab. (Economics), Ph.D. (Philosophy), MSc (The John Paul II Catholic University of Lublin), Poland
ORCID iD: orcid.org/0000-0002-6067-1469
k_aem@dduvs.in.ua

UDC 330.4 : 330.3

DOI :10.31733/2786-491X-2021-2-92-100

Keywords: Quality of life, Cognitive Modeling, Static analysis, digraph, Socio-economic indicators

Abstract. Assessing the position of economic and human capital development level, building a strategy to improve the quality of life is extremely important for the state, so the study of indicators that form the quality of life and have the greatest impact on it remains relevant. Since the very concept of quality of life is a multicomponent category, characterized by both objective and subjective indicators, we consider it appropriate to structure knowledge about the factor environment that shapes the quality of life, their reflection by forming a cognitive model, its static analysis to identify the factors that have the greatest impact on quality of life to improve its level, which reflects the purpose of the study. A cognitive model of quality of life in the form of a balanced digraph was built based on 22 indicators of socio-economic conditions of Ukrainian households, grouped into four groups: population, education and health, socio-economic indicators. Structural analysis of the cognitive model made it possible to assess the classes of factors, establish the system characteristics of the model, identify the factors that have the greatest impact on the system, and assess their importance in modeling the self-development of the situation. Considering the weights of factors and external influences, it is determined that the assessment of the quality of life is most influenced by a group of health factors, while the growth of the quality of life indicator contributes most to the growth of the population and reduces its migration.

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