Modeling patterns of human well-being in the context of sustainable development and digital transformation

Abstract

The article is devoted to identifying new factors for the well-being and sustainable development of countries in the context of digital transformation, creating a data bank of well-being indicators using developed index and population data, assessing the impact of ESG factors on the level of well-being in different contexts using advanced econometric methods, as well as creating the author’s ESG tracker based on blockchain technology, aspects of the introduction of machine learning in the tracking process, which will ensure the transparency and integrity of the data system for the implementation of economic and social policies aimed at innovative alignment in each region. The study is based on the development of a theoretical and methodological apparatus for determining the essence and patterns of well-being and modeling the effects of ESG factors and digitalization on the applied aspects of increasing the quality of life. From the formulation to systems of adaptation of ESG factors to achieve well-being through the prism of digital transformation, taking into account country, regional, and corporate characteristics of achieving well-being. This article may be useful for developing a strategic welfare policy within the framework of sustainable development and digital transformation of the Russian economy based on advanced approaches to assessing and managing human well-being.