Abstract
Purpose: The aim of the work is to determine the meaning and sufficiency of existing social infrastructure for the development of a “green” digital economy, as well as to justify the prospects and provide scientific and methodological recommendations to overcome the deficit in this infrastructure by taking into account the peculiarities of training and digital human resources management for “smart” enterprises of the “green” economy.
Design/methodology/approach: Regression characteristics of the dependence of the “green” economy on robotization and robotization on the digital economy workforce have been compiled, and existing statistics on these indicators have been reviewed and analyzed. The objects of the study are top 10 countries in terms of the number of robots per 10,000 workers in the manufacturing sector, that is, the level of robotization (the development of “smart” entrepreneurship).
Findings: It has been proved that digital human resources for “smart” enterprises of “green” digital economy have a pronounced specificity related to the need to possess both digital and “green” competencies at the same time. This specificity determines the peculiarities of their training and digital human resources management for “smart” enterprises of “green” digital economy.
Originality/value: It is substantiated that insufficient consideration of these features currently leads to a shortage of human resources in this segment of the labour market, which hinders the sustainable development of the digital economy. The author’s recommendations to take into account the peculiarities of training and management of digital human resources for “smart” enterprises of “green” economy on the basis of competency approach will solve this problem.
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Tamakhina, A.Y., Mezhov, S.I., Yungblyudt, S.V. (2020). Digital Workforce for the “Green” Economy “Smart” Enterprises: Training and Management Features. In: Popkova, E., Sergi, B. (eds) Scientific and Technical Revolution: Yesterday, Today and Tomorrow. ISC 2019. Lecture Notes in Networks and Systems, vol 129. Springer, Cham. https://doi.org/10.1007/978-3-030-47945-9_39
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