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中国资源型城市工业生态效率:时空动态及其影响因素。

Industrial eco-efficiency of resource-based cities in China: spatial-temporal dynamics and associated factors.

机构信息

College of Geography and Environment, Shandong Normal University, Jinan, 250358, China.

出版信息

Environ Sci Pollut Res Int. 2023 Sep;30(41):94436-94454. doi: 10.1007/s11356-023-28961-4. Epub 2023 Aug 3.

Abstract

Promoting the greening of industry is the key to achieving high-quality and sustainable development of the urban economy. It is particularly important for resource-based cities (RBCs) that exploit natural resources as the leading industries. In this paper, the Windows-Bootstrap-DEA model was used to calculate the industrial eco-efficiency (IEE) of 114 RBCs in China from 2003 to 2016, and the regional differences and dynamic evolution characteristics of the IEE were analyzed. The panel Tobit model was used to explore the factors associated with IEE in RBCs. The results showed that the IEE of RBCs in China was at a low level during the study period, and the resource utilization process had not reached an optimal state. There were large regional differences in IEE, and there was a significant degree of spatial agglomeration. The results of conditional probability density estimation showed that the distribution of IEE had strong internal stability on the whole, and the distributions of IEE of RBCs in different regions, different resource types, and different development stages showed significant differences. The results of the panel Tobit model showed that per capita GDP, ownership structure, science and technology input, and industrial agglomeration had significant positive effects on IEE, while industrial structure and employment structure showed significant negative effects. The conclusions of this paper can provide a scientific decision-making basis for industrial transformation planning of RBCs.

摘要

推动产业绿色化是实现城市经济高质量和可持续发展的关键。对于以自然资源为主导产业的资源型城市(RBCs)来说,这尤为重要。本文采用 Windows-Bootstrap-DEA 模型,计算了 2003-2016 年中国 114 个 RBCs 的产业生态效率(IEE),并分析了 IEE 的区域差异和动态演变特征。采用面板 Tobit 模型探讨了 RBCs 中与 IEE 相关的因素。结果表明,研究期间中国 RBCs 的 IEE 水平较低,资源利用过程尚未达到最优状态。IEE 存在较大的区域差异,且具有显著的空间集聚性。条件概率密度估计结果表明,IEE 的分布整体上具有较强的内部稳定性,不同区域、不同资源类型和不同发展阶段 RBCs 的 IEE 分布存在显著差异。面板 Tobit 模型结果表明,人均 GDP、所有制结构、科技投入和产业集聚对 IEE 具有显著的正向影响,而产业结构和就业结构则具有显著的负向影响。本文的结论可为 RBCs 的产业转型规划提供科学的决策依据。

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