Building Employment Support Ecosystems in Response to Challenges in the World of Work

In many countries, the Public Employment Service (PES) plays a key role in shaping labor market policy, with its activities focused on protecting the rights and guarantees of both citizens and employers in the field of employment. For this purpose, a wide range of measures is implemented to assist in finding jobs, supporting entrepreneurship, improving professional training, assisting the unemployed, selecting necessary personnel, providing information on the labor market situation, etc. In times of socio-economic instability, the importance of the PES is becoming increasingly significant. However, its activities frequently face criticism, as job seekers tend to prefer informal employment channels and online services, while employers express dissatisfaction with the quality of personnel selection. Using the example of a model region of Russia, the study proposes an ecosystem model for the functioning of the PES as a response to global challenges related to ensuring the sustainable development of local territories. The essence of the idea is to form a network of partner organizations (government bodies, businesses, educational institutions, NGOs, etc.), which will allow for a timely response to the various needs of job seekers and employers. As a result, the PES can become a link uniting the interests of diverse parties to address a wide range of labor market and related issues. Moving in this direction will require close cooperation within the local community and the development of new methodological approaches to structuring such activities. The findings served as the foundation for developing proposals for implementing an ecosystem approach in the activities of the PES, which involves enhancing mechanisms of cooperation between stakeholders, creating new forms of collaboration, redefining the role of employment departments, developing digital platforms, and other innovations.

The research was carried out at the expense of a grant from the Russian Science Foundation No. 24-78-10168, https://rscf.ru/en/project/24-78-10168/.