Macroeconomic dataset for comparative studies on coastal and inland regions in innovation space of Russia
This article presents regional-level data that can be used for comparative territorial studies on innovation dynamics. The dataset covers a series of 50 indicators grouped into a matrix of 5 elements of regional innovation system (human resources – HR, infrastructure, research & development sect...
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doaj-2ae5a0356f154743be4daf5da21622532020-11-25T01:38:53ZengElsevierData in Brief2352-34092019-12-0127Macroeconomic dataset for comparative studies on coastal and inland regions in innovation space of RussiaAnna A. Mikhaylova0Andrey S. Mikhaylov1Oksana V. Savchina2Immanuel Kant Baltic Federal University, 23016, Kaliningrad, Russian FederationImmanuel Kant Baltic Federal University, 23016, Kaliningrad, Russian Federation; Saint Petersburg Electrotechnical University “LETI”, 197022, Saint-Petersburg, Russian Federation; Corresponding author. Immanuel Kant Baltic Federal University, 23016, Kaliningrad, Russian Federation.Peoples' Friendship University of Russia, 117198, Moscow, Russian FederationThis article presents regional-level data that can be used for comparative territorial studies on innovation dynamics. The dataset covers a series of 50 indicators grouped into a matrix of 5 elements of regional innovation system (human resources – HR, infrastructure, research & development sector – R&D, innovative milieu, framework conditions) and 5 components of innovation security (economic, scientific and technological – S&T, social, political, geo-ecological). This complex set of interrelated data enables to grasp the catalyst and inhibitor factors that have a significant impact on the sustainable development of a particular regional innovation system. The innovation security approach used enables to consider the locus of innovation processes, account for the relationship between individual components of regional innovation systems and acknowledge for the unique properties of the regions. The database includes statistics for a total set of 85 regions of the Russian Federation over a period of 2015 and 2016. Spatial differentiation is made on to coastal and inland regions. This enables to identify the development patterns as influenced by the global trend of coastalization. Keywords: Coastal region, Regional innovation system, Innovation dynamics, Innovation security, Innovation trajectory, Russiahttp://www.sciencedirect.com/science/article/pii/S2352340919309953 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Anna A. Mikhaylova Andrey S. Mikhaylov Oksana V. Savchina |
spellingShingle |
Anna A. Mikhaylova Andrey S. Mikhaylov Oksana V. Savchina Macroeconomic dataset for comparative studies on coastal and inland regions in innovation space of Russia Data in Brief |
author_facet |
Anna A. Mikhaylova Andrey S. Mikhaylov Oksana V. Savchina |
author_sort |
Anna A. Mikhaylova |
title |
Macroeconomic dataset for comparative studies on coastal and inland regions in innovation space of Russia |
title_short |
Macroeconomic dataset for comparative studies on coastal and inland regions in innovation space of Russia |
title_full |
Macroeconomic dataset for comparative studies on coastal and inland regions in innovation space of Russia |
title_fullStr |
Macroeconomic dataset for comparative studies on coastal and inland regions in innovation space of Russia |
title_full_unstemmed |
Macroeconomic dataset for comparative studies on coastal and inland regions in innovation space of Russia |
title_sort |
macroeconomic dataset for comparative studies on coastal and inland regions in innovation space of russia |
publisher |
Elsevier |
series |
Data in Brief |
issn |
2352-3409 |
publishDate |
2019-12-01 |
description |
This article presents regional-level data that can be used for comparative territorial studies on innovation dynamics. The dataset covers a series of 50 indicators grouped into a matrix of 5 elements of regional innovation system (human resources – HR, infrastructure, research & development sector – R&D, innovative milieu, framework conditions) and 5 components of innovation security (economic, scientific and technological – S&T, social, political, geo-ecological). This complex set of interrelated data enables to grasp the catalyst and inhibitor factors that have a significant impact on the sustainable development of a particular regional innovation system. The innovation security approach used enables to consider the locus of innovation processes, account for the relationship between individual components of regional innovation systems and acknowledge for the unique properties of the regions. The database includes statistics for a total set of 85 regions of the Russian Federation over a period of 2015 and 2016. Spatial differentiation is made on to coastal and inland regions. This enables to identify the development patterns as influenced by the global trend of coastalization. Keywords: Coastal region, Regional innovation system, Innovation dynamics, Innovation security, Innovation trajectory, Russia |
url |
http://www.sciencedirect.com/science/article/pii/S2352340919309953 |
work_keys_str_mv |
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