T. Yu. Kudryavtseva, A. E. Skhvediani. Studying Regional Clusters with the Use of Data Processing Systems: The Case of the Biopharmaceutical Cluster

UDК 338.2:332.14

DOI: https://doi.org/10.15507/2413-1407.110.028.202001.048-079

Introduction. The dynamics of the development of the digital economy necessitates introduction of integrated information and analytical systems. This provides integration with the existing statistics for making managerial decisions in the field of public administration of cluster development in Russia. The objective of this study is to develop an information and analytical system, a database, and test it taking the case the biopharmaceutical cluster as an example.

Materials and Methods. The study employed materials from the Clusters of Russia’s Regions database as well as statistical tools in accordance with the methodology proposed by the European Cluster Observatory. The tools used made it possible to calculate such factors as ‘coefficient of localization’, ‘size’ and ‘focus’; groups of Russian regions (stable, increasing, and decreasing ones) were identified depending on the state of the cluster under study.

Results. Statistical databases containing the number of employees in the constituent entities of the Russian Federation for 2009–2018 have been formed and grouped in accordance with the structure of the core of the biopharmaceutical cluster. The core of the biopharmaceutical cluster includes two codes of the Russian National Classifier of Economic Activities: 24.4 – Manufacture of pharmaceutical products and 24.5 – Manufacture of soap; detergents, cleaning and polishing preparations; perfumes and cosmetic products. Regions of localization of biopharmaceutical clusters in Russia in 2009–2018 have been identified; corresponding cartograms have been developed.

Discussion and Conclusion. The developed methodology enables quick monitoring of the concentration of employment in the regions and can be used to assess the effectiveness of managing the cluster development of the territory. The results of the study can be used by the authorities to substantiate the cluster industrial policy of the regions, as well as by researchers analyzing the state of the cluster structure of the regions, and by teachers implementing higher education programs in the field of Economic Geography and State and Municipal Administration.

Keywords: cluster specialization of regions, biopharmaceutical cluster, coefficient of localization, cluster focus, cluster size, state cluster policy

Funding. The study has been conducted under a grant from the President of the Russian Federation (project NSh – 3792.2018.6).

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Submitted 16.11.2019; accepted for publication 25.12.2019; published online 31.03.2020.

About the authors:

Tatiana Yu. Kudryavtseva, Head, ‘Economics and Management of Innovations’ Scientific Laboratory, Associate Professor, Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University (29 Polytechnicheskaya St., St. Petersburg 195251, Russia), Dr. Sci. (Economics), ORCID: https://orcid.org/0000-0003-1403-3447, Scopus ID: https://www.scopus.com/authid/detail.uri?origin=resultslist&authorId=560..., Researcher ID: http://www.researcherid.com/rid/S-8637-2017, kudryavtseva_tyu@spbstu.ru

Angi E. Skhvediani, Postgraduate, Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University (29 Polytechnicheskaya St., St. Petersburg 195251, Russia), ORCID: https://orcid.org/0000-0001-7171-7357, Scopus ID: https://www.scopus.com/authid/detail.uri?origin=resultslist&authorId=571..., Researcher ID: http://www.researcherid.com/rid/S-8668-2017, shvediani_ae@spbstu.ru

Contribution of the authors:

Tatiana Yu. Kudryavtseva – scientific supervision; statement of the problem; choice of research methodology; critical analysis and refinement of the solution; computer implementation of the solution to the problem.

Angi E. Skhvediani – analysis of scientific sources, theoretical and practical materials on the research topic; critical analysis and revision of the text; computer implementation of the solution to the problem.

For citation:

Kudryavtseva T.Yu., Skhvediani A.E. Studying Regional Clusters with the Use of Data Processing Systems: The Case of the Biopharmaceutical Cluster. Regionology = Russian Journal of Regional Studies. 2020; 28(1):48-79. DOI: https://doi.org/https://doi.org/10.15507/2413-1407.110.028.202001.048-079

The authors have read and approved the final version of the manuscript.
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