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Study on the Spatio-Temporal Evolution and Influential Factors of Green Innovation Efficiency in Urban Agglomerations of China

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Listed:
  • Shan Feng

    (Institute of Ocean Development, Key Research Base of Humanities and Social Sciences, Ministry of Education, Qingdao 266100, China)

  • Yawen Kong

    (School of Economics, Ocean University of China, Qingdao 266100, China)

  • Shuguang Liu

    (Institute of Ocean Development, Key Research Base of Humanities and Social Sciences, Ministry of Education, Qingdao 266100, China
    School of Economics, Ocean University of China, Qingdao 266100, China)

  • Hongwei Zhou

    (School of Economics, Ocean University of China, Qingdao 266100, China)

Abstract

Promoting green innovation efficiency in urban agglomerations (UAs) can help to ensure the sustainability of China in a competitive but fragile post-industrialization era. This paper applies the Super Slacks-Based Measure model (Super-SBM) to measure the green innovation efficiency in 19 UAs of China from 2006 to 2018. Then, it examines the spatial-temporal evolution characteristics from the perspectives of geography and economics. Furthermore, the spatial econometric model is also established to explore the influential factors of green innovation efficiency, as well as its regional differences. The results reveal the following: (1) From the perspective of temporal differentiation, the green innovation efficiency of most UAs in China presents a fluctuated increase during the study period, and UAs located in the east are more ideal. (2) As for spatial differentiation, the number of UAs of a high value level is relatively stable, and the southeast coastal UAs performs as the core and a stepped pattern of “east > center > west” is clear. (3) A significant positive spatial spillover effect of green innovation efficiency does exist in UAs of China, and the effects of relative factors vary across regions. Differentiated measures should be taken to improve the green innovation efficiency in the UAs of China. This study provides significant guidance for realizing the goal of high-quality development in China, as well as fulfilling the international commitment of carbon peak and carbon neutrality.

Suggested Citation

  • Shan Feng & Yawen Kong & Shuguang Liu & Hongwei Zhou, 2022. "Study on the Spatio-Temporal Evolution and Influential Factors of Green Innovation Efficiency in Urban Agglomerations of China," Sustainability, MDPI, vol. 15(1), pages 1-19, December.
  • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:676-:d:1020705
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    References listed on IDEAS

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    1. 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.
    2. Zhong Fang & Hua Bai & Yuriy Bilan, 2019. "Evaluation Research of Green Innovation Efficiency in China’s Heavy Polluting Industries," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
    3. Tong Zhao & Haihua Zhou & Jinde Jiang & Wenyan Yan, 2022. "Impact of Green Finance and Environmental Regulations on the Green Innovation Efficiency in China," Sustainability, MDPI, vol. 14(6), pages 1-17, March.
    4. Zheming Yan & Rui Shi & Kerui Du & Lan Yi, 2022. "The role of green production process innovation in green manufacturing: empirical evidence from OECD countries," Applied Economics, Taylor & Francis Journals, vol. 54(59), pages 6755-6767, December.
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