Teamwork Skill: A Comparative Analysis of Requirements for Managers and Specialists in Job Vacancies of Russian Companies
DOI:
https://doi.org/10.14515/monitoring.2026.4.3120Keywords:
teamwork skills, job analysis, Russian labor market, managers, specialists, competencies, text data analysisAbstract
The article analyzes the requirements for teamwork skills in job postings of Russian companies. The aim of the study is to identify and quantify differences in the content and structure of requirements for managers and specialists in job vacancies posted by Russian employers based on text analysis. The empirical base consisted of a dataset of 71,931 job postings (collected by the RosNavyk project, which aggregates vacancies from the largest Russian platforms: Rabota v Rossii, HeadHunter, SuperJob, and Rabota.ru) from August 2024 to August 2025. The methodology included the development of original dictionaries of teamwork skills and related competencies, text analysis, statistical methods, and cluster analysis. The results showed that universalization of teamwork skills was discovered (97.7% of vacancies for managers and 89.7% for specialists) with a weak association between the role type and the presence of requirements (Cramér's V = 0.165). Besides, it was identified that job postings for specialists exhibit a higher level of detail in describing teamwork skills. Thematic analysis revealed that managers focus on managerial aspects ("task decomposition"), while specialists focus on operational ones ("problem-solving"). Cluster analysis identified 7 types of "team roles" corresponding to employer requirements. The study concludes that there is a transformation in the nature of labor, associated with the shift to the team focus of professional activities and the erasing of boundaries between managerial and executive functions. The results are significant for developing personnel development programs and adapting educational standards to labor market demands.
Acknowledgements. The authors thank the “RosNavyk” project for providing the empirical data that made this research possible. We also extend our gratitude to the head of the International Laboratory for Applied Network Analysis, D.V. Maltseva, for her support and attention to this work. This article is an output of a research project implemented as part of the Basic Research Program at HSE University.
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