[1]黄小博,李晓青,陈国富,等.福建省高技术产业创新要素集聚时空演变研究[J].集美大学学报(哲社版),2022,25(04):46-55.
HUANG Xiao-bo,LI Xiao-qing,CHEN Guo-fu,et al.A Study of Spatio-temporal Evolution of Fujian’s High-tech Industry Innovation Elements Agglomeration[J].philosophy&social sciences,2022,25(04):46-55.
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福建省高技术产业创新要素集聚时空演变研究(PDF)
《集美大学学报》(哲社版)[ISSN:1006-6977/CN:61-1281/TN]
- 卷:
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25
- 期数:
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2022年04
- 页码:
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46-55
- 栏目:
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- 出版日期:
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2022-07-28
文章信息/Info
- Title:
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A Study of Spatio-temporal Evolution of Fujian’s High-tech Industry Innovation Elements Agglomeration
- 作者:
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黄小博1; 李晓青1; 陈国富2; 张亚洲1
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(1.厦门理工学院经济与管理学院,福建 厦门361024;2.厦门大学管理学院,福建 厦门 361005)
- Author(s):
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HUANG Xiao-bo1; LI Xiao-qing1; CHEN Guo-fu2; ZHANG Ya-zhou1
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(1.School of Economics and Management,Xiamen University of Technology,Xiamen 361024,China;2.School of Management,Xiamen University,Xiamen 361005,China)
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- 关键词:
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高技术产业; 创新要素集聚; 区位熵; Morans I; 时空演变
- Keywords:
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high-tech industry; innovation elements agglomeration; location quotient; Moran’s I; spatial-temporal evolution
- 分类号:
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- DOI:
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- 文献标志码:
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A
- 摘要:
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福建省高技术产业创新要素资源集聚趋势日益凸显,对高技术产业创新发展的影响也日益增强,掌握创新要素集聚分布的时空演变规律及特征对福建省高技术产业高质量发展至关重要。采用泰尔指数和区位熵测算了福建省高技术产业创新要素空间分布变化情况,进一步采用Morans I分析创新要素空间相关分布的变化情况。研究表明,2008—2018年福建省高技术产业创新要素资源集聚的不平衡程度逐渐减小;福建省大多数城市间呈现空间负相关,主要集聚特征为高-低集聚和低-高集聚。
- Abstract:
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The trend of Fujian’s high-tech industry innovation factors agglomeration is becoming increasingly prominent,and the influence of high-tech industry innovation development is also increasing.Mastering the spatial-temporal evolution laws and characteristics of the agglomeration and distribution of innovative elements is essential for the high-quality development of high-tech industries.The study uses Theil index and location quotient to measure the changes in the spatial distribution of Fujian’s high-tech industries innovation factors,and further uses the Moran’s I to analyze the changes in the spatial distribution of innovation factors.The study found:during the study period,the imbalance of the accumulation of Fujian’s hightech industries innovation factors agglomeration gradually decreased;although a few cities showed a positive spatial correlation during the research process,the majority of cities showed a negative spatial correlation,and the main agglomeration characteristics were high-low agglomeration and low-high agglomeration.
参考文献/References:
相似文献/References:
[1]黄荭,石爱虎.高技术产业R&D投入对经济增长影响实证研究——基于30个省级面板数据的GMM估计[J].集美大学学报(哲社版),2016,19(04):36.
HUANG Hong,SHI Ai-hu.An Empirical Analysis of the Impact of China’s R&D Inputs in High-tech Industry on Economic Growth——Based on Analysis of Inter-provincial Panel Data[J].philosophy&social sciences,2016,19(04):36.
更新日期/Last Update:
2022-09-10