Assessment of Intellectual Capital in the Transition to the Digital Economy

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Аннотация

Human capital is a priority resource capable of creating innovative technologies and solutions that will generate high incomes. For the rapid spread of digital technologies, high financial costs are required, since new means of production are needed, and domestic ones, if linking to foreign products is not appropriate for competitive reasons. In the near future, we can expect a natural increase in demand for highly qualified specialists who are able to work in rapidly changing economic conditions, who have knowledge in the field of IT technologies used in a particular industry. The purpose of the study is to develop recommendations based on the developed decision-making model for assessing labor productivity in the digital economy. To achieve the goal , the following tasks were solved in the work: 1) a comprehensive analysis of modern models and methods of the impact of the transition to the digital economy on human (intellectual) capital has been carried out; 2) a decision-making model based on the symbiosis of human and computer technologies has been developed, in which the main emphasis is placed on a mathematical model for calculating labor productivity in the digital economy, characterized by a widespread symbiosis of human and computer technologies. Materials and Methods. When modeling, the apparatus of production functions was used, taking into account digital technological progress, as well as correlation analysis. Conclusions: models and methods of the impact of the transition to the digital economy on human (intellectual) capital are analyzed, a model of the productivity of an individual (who is a carrier of intellectual capital) in symbiosis with computer technologies is constructed, a comparative analysis of the estimated values of the actual rates of technological progress and the growth rate of income of a digital enterprise is carried out.

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Авторлар туралы

Natalia Grineva

Financial University under the Government of the Russian Federation

Email: ngrineva@fa.ru
Cand. Sci. (Econ.), Associate Professor; Associate Professor of the Department of data analysis and machine learning Moscow, Russian Federation

Әдебиет тізімі

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