| Issue |
E3S Web Conf.
Volume 460, 2023
International Scientific Conference on Biotechnology and Food Technology (BFT-2023)
|
|
|---|---|---|
| Article Number | 05014 | |
| Number of page(s) | 8 | |
| Section | Eco Education and Food Waste Reduction | |
| DOI | https://doi.org/10.1051/e3sconf/202346005014 | |
| Published online | 11 December 2023 | |
Multicriteria models for structural analysis of human capital reproduction strategies of knowledge-intensive enterprises in the context of digitalization
1 Marine Hydrophysical Institute, Russian Academy of Sciences, 2, Каpitanskaya str., Sevastopol, 299011, Russia
2 Reshetnev Siberian State University of Science and Technology, 31, Krasnoiarskii Rabochii Prospekt, Krasnoyarsk, 660037, Russia
3 The Federal Center of Expertize and Analyzis, 33, p. 4, Talalikhina str., Moscow, 109316, Russia
4 Institute of Astronomy of the Russian Academy of Sciences, 48, Pyatnitskaya str., Moscow, 119017, Russia
5 Federal Research Center “Computer Science and Control” of Russian Academy of Sciences, 40, Vavilov Street, Moscow, 119333, Russia
6 Central Economics and Mathematics Institute of Russian Academy of Sciences, 47, Nakhimovsky Prospekt, Moscow, 117418, Russia France
* Corresponding author: kartsan2003@mail.ru
Improving the human capital reproduction organization, which is a key guideline on the path of innovative development of the digital economy, requires fundamentally new approaches to finding sources of investment in the intangible digital assets formation. It is proposed to calculate the growth rate of the value of intangible digital assets of a knowledge-intensive enterprise on the basis of a reinvestment mechanism according to many criteria. Multi-criteria models have been developed to reflect the potential production capabilities of knowledge-intensive enterprises, their ability to increase investment potential through the introduction of various strategies for the human capital reproduction.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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