Modeling cluster development using programming methods: case of Russian Arctic regions

Abstract

The aim of this research is to show how the process of data analysis can be automated through development of an information system. The information system can be used for the identification of economic clusters and analysis of the regional potential for economic growth. The authors used data on the Russian Arctic regions with extreme social, geographical, and economic conditions collected from 2009 to 2016 as an example. The authors have designed a database using MS Access software. The authors used the methodology of the European cluster observatory and the approach suggested by M. Porter to identify economic clusters. This methodology was complemented by introduction parameters, which mirror the strength and employment dynamic of the clusters. Based on the employment data of 83 Russian regions during the period of 2009-2016 the authors have calculated cluster localization parameters for nine Russian regions, which are partly or fully located in the Arctic zone. The authors suggest that the cluster structure in this area is weak and most of the significant clusters are declining. The only significant cluster, which is growing in all regions, is the «Oil and Gas» cluster. In conclusion, the authors state that the obtained results are vital for policy makers and can be used for elaborating the regional economic development strategy in order to support regional diversification and specialization, which are closely related to positive spillovers.

Transformation of CRM Activities into e-CRM: The Generating e-Loyalty and Open Innovation

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The Impact of Digitalization on the Formation of Human Capital at the Regional Level

“…Therefore, the concept of open innovation can become one of the mechanisms for accomplishing aims in the framework of regional socio-economic policy. The concept of closed innovations assumes that the processes of developing and commercializing innovations become the task of one company, while open innovations include collaboration (an example of this concept is clusters [62,63]). This approach is universal and can be used not only for the tasks of regional policy of the Russian Federation.…”

Cluster Approach For Territorial Development Management

“…Actually, in general, the cluster approach gains popularity in economy. In recent years, many papers on this subject have been published by Russian authors (Gorochnaya et al, 2020;Ilyasov et al, 2019;Koroleva & Kurnikova, 2020;Kudryavtseva et al, 2020;Perminova et al, 2019;Perova & Papko, 2019;Taranova et al, 2015;Zhelnova, 2012) and by authors from other countries (Haddad & Rahman, 2020;Kumar et al, 2017;Ma et al, 2020;Mishchenko & Mishchenko, 2018) on the necessity to group regions depending on their particularities and differentiate the approaches for managing regions (Baranov et al, 2015). Researchers use modern data mining methods, in particular, self-organizing maps as one of the clusterization methods (Gritsay et al, 2018;Liashenko et al, 2018;Orazi et al, 2020).…”