Bulletin of
Vitebsk State
Technological
University

Abstract

The growing volume of information about the labor market in the context of economy digitalization, on the one hand, and the increasing transaction costs associated with the recruiting, hiring and dismissing workers due to the mismatch between their skills and the employer requirements on the other hand highlight the need to develop tools for the efficient collection, processing and analysis of data contained in the description of vacancies and resumes posted on online portals. The absence of unique approaches to the analysis of vacancies and skills from online sources in the economic literature underscores the theoretical and practical relevance of the research topic.

The purpose of the study is to theoretically substantiate, develop, and test a methodology for collecting and analyzing vacancies from online sources in order to identify and visualize the most in-demand and highly paid skills they require. The empirical basis of the study is an array of data on 580 vacancies for process engineers and 720 vacancies for related specialists in the light industry of the Republic of Belarus, formed by means of web scraping from open online job portals (as of 11/22/2024), containing information about the required skills and the proposed salary level. Based on real-time big data technologies, information on individual professions (the number of vacancies, the skills indicated in them, and wages) was collected and processed by sites and online portals selected by experts. Using a large language model called Claude, their comparison was carried out, unique and end-to-end skills were highlighted, and the ability to visualize the analysis results in the form of graphs and diagrams was developed, taking into account the interests of various user groups. It has been determined that complex competencies have the greatest value in the market of engineering specialties, especially the combination of knowledge of production processes with managerial skills (salary premium up to 24.5 %) and mastery of state-of-art technologies. A significant regional differentiation of wages was revealed (coefficient of variation 23.8 %), while the average wages in the metropolitan region exceeds the national average ones by 25 %. The most well-paid profession is that of a design technologist in all regions. The proposed approach, unlike the existing ones, is intended for use not only at the macro level, but also at the micro level, since it creates the basis for optimizing HR business processes in organizations. The study was conducted within the framework of the research work “Theoretical approaches and methodological support for the analysis of the labor market in the Republic of Belarus using big data” with the financial support of the Belarusian Foundation for Basic Research under the agreement G24-013.

The use of big data on the labor market in HR business processes of organizations in the Republic of Belarus