Studying Regional Clusters with the Use of Data Processing Systems: The Case of the Biopharmaceutical Cluster

Abstract

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.