Issue |
MATEC Web Conf.
Volume 106, 2017
International Science Conference SPbWOSCE-2016 “SMART City”
|
|
---|---|---|
Article Number | 08071 | |
Number of page(s) | 9 | |
Section | 8 Organization and Planning of Construction Works and Municipal Facilities | |
DOI | https://doi.org/10.1051/matecconf/201710608071 | |
Published online | 23 May 2017 |
Methodological approaches to identification of clusters in regional economy system
Moscow State University of Civil Engineering, Yaroslavskoeshosse, 26, Moscow, 129337, Russia
* Corresponding author: angela-1309.m@yandex.ru
The cluster (cluster group) identification methodology according to Porter includes some successive steps. The basis of the economic agglomeration identification methodology is the method of distribution of employment over industries on the territory, according to which: first, all sectors (industries) are grouped into three types; second, the industries are identified; third, the cluster group composition is determined; fourth, identification of the most significant cluster groups, precluding false correlations between industries, is performed; fifth, the existing intersections in cluster groups are analysed. The authors present the algorithm of identifying the developed region clusters is based on identification of agglomeration effects of concentration, urbanisation and joint localisation of regional industries’ enterprises and their economic efficiency, thus, the algorithm is the scientifically grounded method of forming the regional cluster structure. The use of this algorithm will enable developing the efficient cluster policy aimed at increase of employment in the region, salary, wage and budget income level, growth of the competitive ability of the region.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.