A typology of the Baltic region states according to excellence in science and technology

IF 0.7 Q2 AREA STUDIES
Danil G. Azhinov, Tatiana E. Lapshova
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引用次数: 0

Abstract

Global manufacturing systems function in such a way that countries develop industrial spe­cialisation, which leads to territorial disparities. The countries of the Baltic region are no exception despite their strong economic ties and developed industries. A signifi­cant element of any manufacturing system is its scientific and technological subsystem, which is described in this article for ten countries (Germany, Sweden, Denmark, Nor­way, Finland, Poland, Estonia, Latvia, Lithuania and Russia), based on an analysis of a clustered set of national character­istics: R&D financing and staffing in the scientific and technological subsystem. A total of ten indicators, absolute and relative, are investigated. The study relies on combined grouping, graphical and cluster analysis to build a typology of countries and distinguish their types ac­cording to their scientific and technological excellence As a result, a typology of the countries of the Baltic Sea region has been pro­posed and types of countries with similar characteristics have been identified: the two main types are traditional market economies and post-socialist countries, whose common features are observed in all sets of main characteristics. Several subtypes are described as well. The research draws on 2010—2019 (2020) statistical data from the European Statistical Office (Eurostat), the Organization for Economic Co-operation and Development (OECD) and Russia’s Federal State Statistics Service (Rosstat).
波罗的海地区的一种类型学,以科学和技术的卓越表现为基础
全球制造系统的运作方式是,各国发展工业专业化,从而导致地域差异。波罗的海地区各国也不例外,尽管它们有着牢固的经济联系和发达的工业。任何制造系统的一个重要元素都是它的科技子系统,本文基于对一组国家特征的分析,对十个国家(德国、瑞典、丹麦、挪威、芬兰、波兰、爱沙尼亚、拉脱维亚、立陶宛和俄罗斯)的科技子系统进行了描述:科技子系统的研发融资和人员配备。总共调查了十个指标,包括绝对指标和相对指标。本研究采用分组、图解和聚类分析相结合的方法,建立了国家类型学,并根据其科学和技术的卓越程度来区分其类型,从而提出了波罗的海地区国家的类型学,并确定了具有相似特征的国家类型:两种主要类型是传统市场经济国家和后社会主义国家,它们的共同特征表现在所有主要特征上。还描述了几种亚型。该研究利用了欧洲统计局(Eurostat)、经济合作与发展组织(OECD)和俄罗斯联邦国家统计局(Rosstat) 2010-2019年(2020年)的统计数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Baltic Region
Baltic Region AREA STUDIES-
CiteScore
1.60
自引率
37.50%
发文量
11
审稿时长
24 weeks
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