Multicriterial metric data analysis in human capital modelling

Kamenev G.K., Kamenev I.G.
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The article describes a model of a human in the informational economy and demonstrates the multicriteria optimizational approach to the metric analysis of model-generated data. The traditional approach using the identification and study involves the model’s identification by time series and its further prediction. However, this is not possible when some variables are not explicitly observed and only some typical borders or population features are known, which is often the case in the social sciences, making some models pure theoretical. To avoid this problem, we propose a method of metric data analysis (MMDA) for identification and study of such models, based on the construction and analysis of the Kolmogorov – Shannon metric nets of the general population in a multidimensional space of social characteristics. Using this method, the coefficients of the model are identified and the features of its phase trajectories are studied. In this paper, we are describing human according to his role in information processing, considering his awareness and cognitive abilities. We construct two lifetime indices of human capital: creative individual (generalizing cognitive abilities) and productive (generalizing the amount of information mastered by a person) and formulate the problem of their multi-criteria (two-criteria) optimization taking into account life expectancy. This approach allows us to identify and economically justify the new requirements for the education system and the information environment of human existence. It is shown that the Pareto-frontier exists in the optimization problem, and its type depends on the mortality rates: at high life expectancy there is one dominant solution, while for lower life expectancy there are different types of Paretofrontier. In particular, the Pareto-principle applies to Russia: a significant increase in the creative human capital of an individual (summarizing his cognitive abilities) is possible due to a small decrease in the creative human capital (summarizing awareness). It is shown that the increase in life expectancy makes competence approach (focused on the development of cognitive abilities) being optimal, while for low life expectancy the knowledge approach is preferable.

Keywords: multicriteria optimization, metric net, data visualization, human development, model identification, feasible goals method, interactive decision maps, human capital, metric data analysis
Citation in English: Kamenev G.K., Kamenev I.G. Multicriterial metric data analysis in human capital modelling // Computer Research and Modeling, 2020, vol. 12, no. 5, pp. 1223-1245
Citation in English: Kamenev G.K., Kamenev I.G. Multicriterial metric data analysis in human capital modelling // Computer Research and Modeling, 2020, vol. 12, no. 5, pp. 1223-1245
DOI: 10.20537/2076-7633-2020-12-5-1223-1245
URL: http://crm-en.ics.org.ru/journal/article/2992/
Creative Commons License This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.

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