Scientometrics for Regional Scientific and Technological Management

Ð . Ð . Gataullina ()

University Management: Practice and Analysis, 2026, vol. 30, issue 1

Abstract:   The study examines scientometric analysis as a tool for managing the region’s scientific and technological development, aiming to identify current and promising research areas, cluster them, and develop management strategies for further advancement.  The assessment was conducted using the Republic of Tatarstan as a case study in natural sciences, aggregating data from 43 educational institutions and 52 research organizations.  The research’s significance stems from the state’s active policy in scientific and technological development (including the national S&T development program and regional S&T rankings), where scientometric indicators serve as key metrics for evaluating the success of regional research and education policies in Russia.  By analyzing quantitative metrics (publication volume, citation rates) at global, national, and regional levels, along with matrix modeling and clustering methods, the study identifies dominant and rapidly evolving research fields that attract scientific attention.  The novelty lies in classifying regional scientific publications into thematic clusters: “Growing†(increasing publications in both Russia and Tatarstan), “Lagging†(growth only in Russia), “Advancing†(growth only in Tatarstan), and “Declining†(decrease in both).  Among growing fields, the most prominent in terms of scientific interest include agriculture and crop science, general energy issues, immunology and microbiology, environmental protection, and human ecology, while only five subjects fall into the advancing category, demonstrating relatively limited scientific impact. For each cluster, management solutions were developed, including prioritized funding, staff incentives, and other measures. The research findings can be applied in managing research and educational institutions, developing S&T programs for Russian regions to identify core research schools, and supporting natural science initiatives.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:adf:journl:y:2026:id:2208

DOI: 10.15826/umpa.2026.01.002

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