Methods for Evaluation of the Region’s Needs for Human Resources based on Statistics and Patent Landscapes
Keywords:regional labour market, post-pandemic structural economic transformation, human resources, data mining, patent landscaping, artificial intelligence
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.
How to Cite
This work is licensed under a Creative Commons Attribution 4.0 International License.