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Spatiotemporal Patterns and Influencing Factors of Industrial Ecological Efficiency in Northeast China

Author

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  • Wai Li

    (College of Geographical Science, Harbin Normal University, Harbin 150025, China)

  • Xiaohong Chen

    (College of Geographical Science, Harbin Normal University, Harbin 150025, China)

  • Ying Wang

    (College of Geographical Science, Harbin Normal University, Harbin 150025, China)

Abstract

Scientific measurement of regional industrial ecological efficiency and discussion of the development and changes of its spatiotemporal pattern are of great significance to accelerate the high-quality development of regional economy and coordinate the development of industrial economy and ecological environment. Taking the old industrial bases in Northeast China as the research case and 2004–2019 as the research period, a super-slack-based model was used to measure the industrial ecological efficiency of 34 prefecture-level cities in the region. Meanwhile, the spatial autocorrelation model and the geographically and temporally weighted regression (GTWR) model were used to analyze the spatiotemporal pattern characteristics and the spatiotemporal heterogeneity of influencing factors. The results showed that: (1) From a time change perspective, the overall industrial ecological efficiency of Northeast China declined, the mean of the 34 cities decreased from 0.675 to 0.612, the number of cities with a high level of industrial ecological efficiency decreased significantly, the number of cities with a low level of industrial ecological efficiency increased significantly, and the development gap between cities within the region widened. (2) In terms of spatial pattern, the difference in the spatial pattern in the east–west direction decreased, and the spatial pattern in the south–north direction was enhanced. The industrial ecological efficiency of the central part of Northeast China gradually became the highest in the whole region. (3) From 2017, the industrial ecological efficiency had stable spatial autocorrelation characteristics. The local spatial autocorrelation was dominated by L-H-type cluster areas in the mountainous regions and L-L-type cluster areas in central and southern Liaoning province. H-H and H-L types had small numbers. In addition, the trend of H-H cities transforming into H-L cities was obvious, and the high level of urban space spillover effect showed good development. (4) The science and technology input, industrial agglomeration intensity, and environmental regulation of the government generally had a promoting effect on the improvement in industrial ecological efficiency, while the economic extroverted degree had a negative impact. The high-value area of science and technology investment and industrial agglomeration intensity concentrated significantly in the central part. The government focused on ecological protection areas and ecologically sensitive areas, and the economic extroverted degree had a significant positive impact on the two major urban agglomerations in central Northeast China. Therefore, differentiating measures should be taken according to the actual situation of each city to improve the industrial ecological efficiency level in Northeast China.

Suggested Citation

  • Wai Li & Xiaohong Chen & Ying Wang, 2022. "Spatiotemporal Patterns and Influencing Factors of Industrial Ecological Efficiency in Northeast China," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9691-:d:881868
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    Cited by:

    1. Yilin Chen, 2024. "Regional decline and structural changes in Northeast China: an exploratory space–time approach," Asia-Pacific Journal of Regional Science, Springer, vol. 8(2), pages 397-427, June.
    2. Mengtian Zhang & Huiling Wang, 2023. "Evolution of Industrial Ecology and Analysis of Influencing Factors: The Yellow River Basin in China," Land, MDPI, vol. 12(7), pages 1-21, June.

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