The role of interregional relationships in research talent development

Q3 Economics, Econometrics and Finance
I. Naumov, A. Barybina
{"title":"The role of interregional relationships in research talent development","authors":"I. Naumov, A. Barybina","doi":"10.15826/recon.2019.6.1.002","DOIUrl":null,"url":null,"abstract":"The relevance of research. Workforce quality is paramount to the development of innovative economy and socio-economic development of territorial systems. Not all regions, however, are able to train sufficient R&D personnel to meet the needs of their innovative economies. The lack of research talent can be compensated by establishing cooperative relationships with other territorial systems. Therefore, it is important to study the existing interregional interconnections in the development of research talent and to identify the key priorities in this sphere. The aim of the study is to demonstrate the relationship between the indicators of development of research talent in different regions and their innovative activity. Data and Methods. The study uses spatial econometric modeling tools and methods for calculating global and local spatial autocorrelation indices of Moran P. and their dispersion diagrams. The spatial autocorrelation was calculated by using a standardized matrix of distances along the roads between the regional administrative centers. As a result of the analysis, a close relationship was found between the indicators of development of research talent in Russian regions and their innovative activity. The constructed regression model based on spatial data lead us to the conclusion that efficient innovative development requires a pool of STEM talent in the regions, which means that it is necessary to provide sufficient opportunities for training and education in this sphere. Conclusions. The study of the interconnections between the regions using the improved method of spatial autocorrelation of P. Moran revealed a cluster of closely interconnected regions (Moscow - St. Petersburg - Moscow region - Nizhny Novgorod region - Ryazan region - Ivanovo region - Tver region - Kostroma region - Tula region) and three potential clusters: ‘Volga’, ‘Ural’, and ‘Siberia’.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"REconomy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15826/recon.2019.6.1.002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 7

Abstract

The relevance of research. Workforce quality is paramount to the development of innovative economy and socio-economic development of territorial systems. Not all regions, however, are able to train sufficient R&D personnel to meet the needs of their innovative economies. The lack of research talent can be compensated by establishing cooperative relationships with other territorial systems. Therefore, it is important to study the existing interregional interconnections in the development of research talent and to identify the key priorities in this sphere. The aim of the study is to demonstrate the relationship between the indicators of development of research talent in different regions and their innovative activity. Data and Methods. The study uses spatial econometric modeling tools and methods for calculating global and local spatial autocorrelation indices of Moran P. and their dispersion diagrams. The spatial autocorrelation was calculated by using a standardized matrix of distances along the roads between the regional administrative centers. As a result of the analysis, a close relationship was found between the indicators of development of research talent in Russian regions and their innovative activity. The constructed regression model based on spatial data lead us to the conclusion that efficient innovative development requires a pool of STEM talent in the regions, which means that it is necessary to provide sufficient opportunities for training and education in this sphere. Conclusions. The study of the interconnections between the regions using the improved method of spatial autocorrelation of P. Moran revealed a cluster of closely interconnected regions (Moscow - St. Petersburg - Moscow region - Nizhny Novgorod region - Ryazan region - Ivanovo region - Tver region - Kostroma region - Tula region) and three potential clusters: ‘Volga’, ‘Ural’, and ‘Siberia’.
区域间关系在科研人才发展中的作用
研究的相关性。劳动力素质对创新经济的发展和地域系统的社会经济发展至关重要。然而,并非所有地区都有能力培养足够的研发人员来满足其创新型经济的需求。研究人才的缺乏可以通过与其他地域系统建立合作关系来弥补。因此,研究研究人才发展中现有的区域间联系并确定这一领域的关键优先事项非常重要。研究的目的在于揭示不同地区科研人才发展指标与其创新活动之间的关系。数据和方法。利用空间计量模型工具和方法计算了Moran P.的全局和局部空间自相关指数及其离散图。空间自相关性通过使用区域行政中心之间道路距离的标准化矩阵来计算。分析结果表明,俄罗斯各地区科研人才发展指标与其创新活动之间存在密切关系。基于空间数据构建的回归模型表明,高效的创新发展需要区域内的STEM人才储备,这意味着需要提供足够的STEM培训和教育机会。结论。利用改进的P. Moran空间自相关方法对区域之间的相互联系进行了研究,发现了一个紧密联系的区域集群(莫斯科-圣彼得堡-莫斯科地区-下诺夫哥罗德地区-梁赞地区-伊万诺沃地区-特维尔地区-科斯特罗马地区-图拉地区)和三个潜在集群:“伏尔加河”、“乌拉尔”和“西伯利亚”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
REconomy
REconomy Economics, Econometrics and Finance-General Economics, Econometrics and Finance
CiteScore
1.60
自引率
0.00%
发文量
8
审稿时长
14 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信