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Does Optimization of Industrial Structure Improve Green Efficiency of Industrial Land Use in China?

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  • Bingqing Li

    (School of Public Administration, China University of Geosciences, Wuhan 430074, China)

  • Zhanqi Wang

    (School of Public Administration, China University of Geosciences, Wuhan 430074, China)

  • Feng Xu

    (School of Public Administration, China University of Geosciences, Wuhan 430074, China)

Abstract

Improving the green efficiency of industrial land use (GEILU) is essential to promoting low-pollution and highly efficient development, and industrial structure is a key factor in this dynamic. This paper aims to reveal how the optimization of industrial structure (OIS) affects GEILU in China. First, an analytical framework was proposed to understand the effect mechanisms from the perspective of rationalization, upgrading, and ecologization of industrial structure. Second, the panel data of 31 provincial units collected from 2006 to 2020 were taken as cases for empirical study. The super-SBM model was adopted to measure GEILU, and some variables were used to evaluate OIS. Finally, the spatial effects of OIS on GEILU were analyzed based on the spatial Durbin model. The results show that the GEILU presented a wave change and kept increasing after 2016. From a global perspective, the rationalization of industrial structure helped improve GEILU; however, the upgrading and ecologization of industrial structure generated inhibiting effects. When integrating the three perspectives, optimization of industrial structure was considered to have negative effects on GEILU. The negative effects stemmed from an inefficient expansion of industrial land and pollution from heavy chemical industries. From a phased perspective, in the early period of this study, the outdated technology in traditional industries brought about the negative effects; however, with high-knowledge and high-tech industries forming a market scale, optimization of industrial structure gradually became conducive to the improvement of GEILU. This study suggests that eliminating the market segmentation between provinces and accelerating the development of high-knowledge and high-tech industries can help promote low-pollution and highly efficient industrial land use in China.

Suggested Citation

  • Bingqing Li & Zhanqi Wang & Feng Xu, 2022. "Does Optimization of Industrial Structure Improve Green Efficiency of Industrial Land Use in China?," IJERPH, MDPI, vol. 19(15), pages 1-18, July.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9177-:d:873193
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    References listed on IDEAS

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    1. Xie, Hualin & Chen, Qianru & Lu, Fucai & Wu, Qing & Wang, Wei, 2018. "Spatial-temporal disparities, saving potential and influential factors of industrial land use efficiency: A case study in urban agglomeration in the middle reaches of the Yangtze River," Land Use Policy, Elsevier, vol. 75(C), pages 518-529.
    2. Groenwold, Nicolaas & Lee, Guoping & Chen, Anping, 2008. "Inter-regional spillovers in China: The importance of common shocks and the definition of the regions," China Economic Review, Elsevier, vol. 19(1), pages 32-52, March.
    3. Zhao, Zhe & Bai, Yuping & Wang, Guofeng & Chen, Jiancheng & Yu, Jiangli & Liu, Wei, 2018. "Land eco-efficiency for new-type urbanization in the Beijing-Tianjin-Hebei Region," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 19-26.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Deng, Xiangzheng & Gibson, John, 2019. "Improving eco-efficiency for the sustainable agricultural production: A case study in Shandong, China," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 394-400.
    6. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    7. Ahmad, Munir & Wu, Yiyun, 2022. "Natural resources, technological progress, and ecological efficiency: Does financial deepening matter for G-20 economies?," Resources Policy, Elsevier, vol. 77(C).
    8. Khezrimotlagh, Dariush & Zhu, Joe & Cook, Wade D. & Toloo, Mehdi, 2019. "Data envelopment analysis and big data," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1047-1054.
    9. Sun, Yifan & Ma, Anbing & Su, Haorui & Su, Shiliang & Chen, Fei & Wang, Wen & Weng, Min, 2020. "Does the establishment of development zones really improve industrial land use efficiency? Implications for China’s high-quality development policy," Land Use Policy, Elsevier, vol. 90(C).
    10. Troy D. Abel & Jonah White & Stacy Clauson, 2015. "Risky Business: Sustainability and Industrial Land Use across Seattle’s Gentrifying Riskscape," Sustainability, MDPI, vol. 7(11), pages 1-36, November.
    11. Weidong Sun & Zhigang Chen & Danyang Wang, 2019. "Can Land Marketization Help Reduce Industrial Pollution?," IJERPH, MDPI, vol. 16(12), pages 1-16, June.
    12. Yan, Siqi & Peng, Jianchao & Wu, Qun, 2020. "Exploring the non-linear effects of city size on urban industrial land use efficiency: A spatial econometric analysis of cities in eastern China," Land Use Policy, Elsevier, vol. 99(C).
    13. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    14. Liu, Jingming & Hou, Xianhui & Wang, Zhanqi & Shen, Yue, 2021. "Study the effect of industrial structure optimization on urban land-use efficiency in China," Land Use Policy, Elsevier, vol. 105(C).
    15. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    16. Xinqi Zheng & Bing Geng & Xiang Wu & Lina Lv & Yecui Hu, 2014. "Performance Evaluation of Industrial Land Policy in China," Sustainability, MDPI, vol. 6(8), pages 1-16, July.
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    3. 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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