Methods for Evaluation of the Region’s Needs for Human Resources based on Statistics and Patent Landscapes

Authors

DOI:

https://doi.org/10.17059/ekon.reg.2022-2-19

Keywords:

regional labour market, post-pandemic structural economic transformation, human resources, data mining, patent landscaping, artificial intelligence

Abstract

Implementation of a new technological platform in Russia requires providing promising areas of professional qualification with human resources. Post-pandemic structural economic transformation has accelerated changes in the labour market and highlighted the need to develop new approaches and forecasting methods with the priorities of regional technological development. The study presents a methodology to reveal the regional demand for staffing based on the analysis of the factors affecting staff demands using structured and unstructured datasets. The study is focused on forecasting the region’s needs for human resources based on data mining and patent landscapes. That forecasting should consider the economic focus of a region as well as its location, investment and R&D development programme, labour market specificity. The advantage of the proposed methodology is obtaining reasonable estimates of the region’s needs for human resources with data mining and patent landscaping methods in conditions of limited official statistical data. Our database includes more than 25 million records: full-text collections of Russian and foreign patents, research papers, statistical indicators, etc. As a result, we identified promising training areas attractive for qualified personnel in the Vologda region corresponding with the priorities of regional technological development. The future development of this research is the improvement of the methodology for quantitative assessment of the regional need for professionals in particular industries. The obtained results can be useful to government bodies and research centres for the development of regional strategies.

Author Biographies

Yulia S. Otmakhova , Central Economics and Mathematics Institute of RAS

Cand. Sci. (Econ.), Leading Research Associate; Scopus Author ID: 7194720805; https://orcid.org/0000-0001-8157-0029 (47, Nakhimovskiy Ave., Moscow, 117418, Russian Federation; e-mail: otmakhovajs@yandex.ru).

Dmitry A. Devyatkin , Federal Research Center “Computer Science and Control” of RAS

Research Associate; Scopus Author ID: 56509621200; https://orcid.org/0000-0002-0811-725X (9, 60-letiya Oktyabrya Ave., Moscow, 117312, Russian Federation; e-mail: devyatkin@isa.ru).

Ilya A. Tikhomirov , Federal Research Center “Computer Science and Control” of RAS

Cand. Sci. (Eng.); Scopus Author ID: 36696937000; https://orcid.org/0000-0003-0698-7689 (9, 60-letiya Oktyabrya Ave., Moscow, 117312, Russian Federation; e-mail: tih@isa.ru).

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Published

30.06.2022

How to Cite

Otmakhova Ю. С. ., Devyatkin Д. А. ., & Tikhomirov И. А. . (2022). Methods for Evaluation of the Region’s Needs for Human Resources based on Statistics and Patent Landscapes. Economy of Regions, 18(2), 569–580. https://doi.org/10.17059/ekon.reg.2022-2-19

Issue

Section

Research articles