资源与产业 ›› 2020, Vol. 22 ›› Issue (3): 65-73.DOI: 10.13776/j.cnki.resourcesindustries.20200529.007

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中国海洋经济创新发展的时空差异

狄乾斌1,2,徐礼祥2   

  1. (1辽宁师范大学 海洋经济与可持续发展研究中心,辽宁 大连 116029;2辽宁师范大学 地理科学学院,辽宁 大连 116029)
  • 收稿日期:2019-10-05 修回日期:2019-12-17 出版日期:2020-06-20 发布日期:2020-06-25
  • 通讯作者: 徐礼祥 2391650722@qq.com
  • 基金资助:
    国家自然科学基金(41571127);教育部人文社科重点研究基地重大项目(17JJD790010);辽宁省百千万人才工程项目

TEMPORAL-SPATIAL VARIANCE OF INNOVATIVE DEVELOPMENT OF CHINA'S MARINE ECONOMY

DI Qianbin1,2, XU Lixiang2   

  1. (1.Marine Economics and Sustainable Development Research Center, Liaoning Normal University, Dalian 116029, China; 2.School of Geography, Liaoning Normal University, Dalian 116029, China)
  • Received:2019-10-05 Revised:2019-12-17 Online:2020-06-20 Published:2020-06-25

摘要: 基于中国海洋经济的快速发展和创新要求,结合国内外海洋经济创新理论,论文从创新环境、创新投入、创新产出、创新成效4个方面构建海洋经济创新发展评价指标体系,通过原始数据对数中心化处理、协方差改进特征值提取、各主成分熵值法重新赋权,得出中国沿海11省市2010—2016年海洋经济创新发展综合得分,基于此,通过系统聚类对其进行层次划分,计算出全局Moran's I指数并利用Moran散点图进行空间关联分析。结果表明:中国海洋经济创新发展在空间上存在着南北差异较大,中部较为均衡的空间特征,时间上呈现出各省市水平缓慢提升,区域差异不断缩小的态势。

关键词: 海洋经济创新, 时空差异, 非线性主成分, 熵值法, 空间关联

Abstract: This paper, according to China's fast marine economy growth and innovation and combined with marine economy innovation theories in the world, establishes an evaluation index system of marine economy innovation development from innovation environment, input, output and performance, and scores the 11 provinces/cities in their marine economy innovation development during 2010 to 2016 through centralizing the logarithmic primary data, covariance-improved eigenvalues extraction, and entropy-weighting principal component. System clustering is used to classify its hierarchy and to calculate the whole Moran's I index. Spatial correlation of Moran scatter points suggests China's marine economy innovation development is geographically of large difference between the north and the south, and balanced in the central, with each province/city slowly rising and a shrinking regional variance.

Key words: marine economy innovation, temporal-spatial variance, non-linear principal component, entropy, spatial correlation