湖北农业科学 ›› 2022, Vol. 61 ›› Issue (12): 200-205.doi: 10.14088/j.cnki.issn0439-8114.2022.12.039

• 经济·管理 • 上一篇    下一篇

长江经济带第二产业绿色技术创新效率测度及时空演变

陈红1, 沈俊源2, 陈诗雨1   

  1. 1.河海大学商学院,江苏 常州 213022;
    2.河海大学商学院,南京 211100
  • 收稿日期:2021-01-04 出版日期:2022-06-25 发布日期:2022-07-22
  • 通讯作者: 沈俊源(1991-),男,江苏苏州人,博士,主要从事环境经济性评估研究,(电话)15295537852(电子信箱)sjyhere@sina.com。
  • 作者简介:陈 红(2000-),女,河北唐山人,在读本科生,专业方向为资源管理,(电话)15031566723(电子信箱)chenhong9989@163.com
  • 基金资助:
    湖北省教育厅人文社会科学研究项目(17Q143); 中央高校基本科研业务费项目(CZB19020049)

The measurement and temporal and spatial evolution of the green technology innovation efficiency of secondary industry in Yangtze River Economic Belt

CHEN Hong1, SHEN Jun-yuan2, CHEN Shi-yu1   

  1. 1. School of Business, Hohai University, Changzhou 213022,Jiangsu, China;
    2. School of Business,Hohai University,Nanjing 211100,China
  • Received:2021-01-04 Online:2022-06-25 Published:2022-07-22

摘要: 采用SBM的Max-min-DEA模型以及Kernel密度估计函数,对2001—2018年长江经济带沿线11省市第二产业绿色技术创新效率进行测度,并分析其时空差异规律。结果表明,长江经济带沿线11省市第二产业绿色技术创新效率较高,但仍有上升空间,需做好节能减排工作,以提升效率。在观察期内,效率整体呈上升趋势,但长江经济带子地区间和各省市间第二产业绿色技术创新效率的演变规律和趋势存在明显的时空差异。

关键词: 第二产业, 绿色技术创新效率, Max-min-DEA模型, Kernel密度估计函数, 时空差异, 长江经济带

Abstract: The Max-min-DEA model of SBM and Kernel density estimation function were used to measure the green technology innovation efficiency of secondary industry in 11 provinces and cities along the Yangtze River Economic Belt from 2001 to 2018, and their spatial and temporal differences were analyzed. The results showed that the efficiency of green technology innovation of secondary industry in 11 provinces and cities along the Yangtze River Economic Belt was high, but there was still room for improvement. It was necessary to do a good job in reducing consumption and emission to improve efficiency. During the observation period, the overall efficiency was on the rise, but there were obvious spatial and temporal differences in the evolution law and trend of green technology innovation efficiency of the secondary industry among the sub regions and among the provinces in the Yangtze River Economic Belt.

Key words: secondary industry, green technology innovation efficiency, Max-min-DEA model, Kernel density estimation function, temporal and spatial differences, Yangtze River Economic Belt

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