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Human capital in public authorities and innovation institutions: a model of mutual influence

Year: 2025
Type: article
Abstract: The article explores the mutual influence of human capital in public authorities and innovation institutions as a key factor in effective governance and the national innovation system development. The proposed model of mutual influence considers the use of human resources analytics to optimize managerial decision-making, funding of innovation projects through the state grants and venture capital funds, as well as the formation of educational alliances between universities, the state, and businesses. The analysis of international experience has demonstrated that effective human capital management in the public sector is a key driver of innovation development. The implementation of analytical human resources systems in public administration, funding of research, and commercialization of scientific developments, along with simplifying the regulatory environment through public-private partnership mechanisms, contribute to increasing innovation activity. The practical significance of this study lies in the potential application of the proposed model to reform public policy in human capital management. The implementation of initiatives such as developing a national human capital management platform, enhancing international workforce mobility, and supporting educational initiatives will contribute to increased productivity, reduced bureaucratic barriers, and the formation of a competitive knowledge-based economy. The prospects for further research include a detailed analysis of the impact of digital technologies on human capital development, an assessment of the effectiveness of the proposed interaction mechanisms, and the adaptation of international experience to the Ukrainian context. The research findings can be applied to the development of strategic policies in the field of human resource management in public administration and the business environment.
DOI: 10.46299/j.isjmef.20250402.04
Language: English
Open Access status: diamond
OpenAlex ID: W4409073081
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