To the Issue on Data Selection for Regional Specialization Identification

Prokopyev, Egor A.

doi:10.17213/2312-6469-2015-4-236-245

Cited by 2 publications

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“…So, Kolchinskaya [17] used the indicators of the volume of goods shipped, the number of organizations, the net financial result, investment, labor productivity, and profitability to analyze the localization of sectors of St. Petersburg. Prokopiev [18] carried out calculations for the forest sector of Russia in terms of tax indicators -collection of regional taxes and separate collections of property tax. Golovin [19] by the example of the Republic of Mari El used the indicators of turnover, labor productivity, and the number of enterprises.…”

Section: Introductionmentioning

confidence: 99%

Modified localization coefficients for cluster processes identification: a comparative analysis (case study: the Russian rye sector)

Костенко

2020

E3S Web Conf.

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The paper presents the results of the identification of agrarian clusters. Research is done in connection with the rye sector of Russia taken as a case study. The localization coefficients were calculated from the gross yield of winter rye grain. Two variants of calculating coefficients were compared -in proportion to the indicators of the gross regional product and employment statistics. Studies have shown that the coefficients in proportion to the gross regional product are more sensitive and allow a more subtle diagnosis of cluster processes. Localization coefficients in proportion to employment statistics are a more stringent method for identifying clusters.

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Section: Introductionmentioning

confidence: 99%

Modified localization coefficients for cluster processes identification: a comparative analysis (case study: the Russian rye sector)

Костенко

2020

E3S Web Conf.

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An Integrated Approach to the Organization of Designing a Shipbuilding Cluster in the Republic of Crimea

Yaroshenko

2021

Èkonomika i upravlenie

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Aim. The presented study aims to develop an organizational and economic mechanism for designing a shipbuilding cluster.Tasks. The author examines legal documents regulating the formation and development of industrial clusters in the Russian Federation, identifies opportunities for designing a shipbuilding cluster in the Republic of Crimea, and provides a comprehensive algorithm for the cluster’s creation.Methods. The author develops an algorithm for the formation of an industrial cluster in the context of the shipbuilding industry. The study uses the methods of structural, functional, and normative analysis as well as organizational design.Results. The developed algorithm for creating an industrial cluster defines the logical sequence of stages in its formation, making it possible to develop a comprehensive approach to the organization of designing a shipbuilding cluster in the Republic of Crimea. The formation and development of a shipbuilding cluster require each potential participant to make an independent decision about joining the cluster; implementation of joint projects by economic subjects on mutually beneficial terms while maintaining competitive relations; stimulation of innovation and promotion of goods, works, and services; interaction with educational and research institutions; development of technological and industrial infrastructure. Cluster-based interaction helps to activate the stages of specialization and cooperation, attract customers and suppliers, reduce the unit cost of completed orders and technical services. Implementation of the cluster approach in the shipbuilding industry involves examining a separate industry in relation to related industries.Conclusions. The essence of the organizational and economic mechanism for designing a cluster in the shipbuilding industry in the Republic of Crimea is characterized by the specific localization of business structures. The cluster is aimed at enhancing the competitiveness and efficient interaction between these structures through specialization and industrial cooperation, attracting financial, research, and educational organizations.

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To the Issue on Data Selection for Regional Specialization Identification

Cited by 2 publications

References 0 publications

Modified localization coefficients for cluster processes identification: a comparative analysis (case study: the Russian rye sector)

Modified localization coefficients for cluster processes identification: a comparative analysis (case study: the Russian rye sector)

An Integrated Approach to the Organization of Designing a Shipbuilding Cluster in the Republic of Crimea

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