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Research on Green Innovation of the Great Changsha-Zhuzhou-Xiangtan City Group Based on Network

Author

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  • Lu Wang

    (School of Business, Hunan University of Science and Technology (HNUST), Xiangtan 411201, China)

  • Wenzhong Ye

    (School of Business, Hunan University of Science and Technology (HNUST), Xiangtan 411201, China)

  • Lingming Chen

    (School of Business, Hunan University of Science and Technology (HNUST), Xiangtan 411201, China
    School of Economics and Management, Xinyu University (XYU), Xinyu 338004, China)

Abstract

This article aims to promote the high-quality development of the Great Changsha-Zhuzhou-Xiangtan City Group and improve the green innovation efficiency of urban agglomeration. This article takes green innovation in networked urban agglomerations as its research subject. Furthermore, it analyzes the impact of network structure characteristics such as network scale and network structure hole on green innovation in urban agglomerations. Moreover, this study uses the unexpected output SBM model to measure green innovation efficiency of the eight prefecture-level cities in the Great Changsha-Zhuzhou-Xiangtan City Group from 2012 to 2018 and analyzes its influencing factors using the panel Tobit model. The results show that the overall green innovation efficiency of the Great Changsha-Zhuzhou-Xiangtan City Group is stable. The distribution of urban green innovation efficiency in the region is characterized by urban gradient and mid-stream drive. In the process of networked innovation, economic development, which has a positive impact on green innovation, promotes the overall effectiveness of the network structure. The low efficiency of urban educational resources, which has a negative impact on green innovation, leads to the redundancy of a network scale. The unapparent advantage of industrial structures, which have a negative impact on the development of green innovation, leads to the insufficient depth and breadth of network openness. Lastly, government support and the level of infrastructure have no impact on green innovation.

Suggested Citation

  • Lu Wang & Wenzhong Ye & Lingming Chen, 2021. "Research on Green Innovation of the Great Changsha-Zhuzhou-Xiangtan City Group Based on Network," Land, MDPI, vol. 10(11), pages 1-15, November.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:11:p:1198-:d:673241
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    References listed on IDEAS

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    Cited by:

    1. Qikang Zhong & Zhe Li & Yujing He, 2023. "Coupling Evaluation and Spatial–Temporal Evolution of Land Ecosystem Services and Economic–Social Development in a City Group: The Case Study of the Chengdu–Chongqing City Group," IJERPH, MDPI, vol. 20(6), pages 1-29, March.
    2. Shumin Dong & Yuting Xue & Guixiu Ren & Kai Liu, 2022. "Urban Green Innovation Efficiency in China: Spatiotemporal Evolution and Influencing Factors," Land, MDPI, vol. 12(1), pages 1-13, December.
    3. Fei He & Luyun Liu & Yu Huang & Komi Bernard Bedra & Minhuan Zhang, 2023. "Investigating the Spatial Heterogeneity of Urban Heat Island Responses to Climate Change Based on Local Climate Zones," Sustainability, MDPI, vol. 15(7), pages 1-19, April.
    4. Jinchao Huang & Shuang Meng & Jiajie Yu, 2023. "The Effects of the Low-Carbon Pilot City Program on Green Innovation: Evidence from China," Land, MDPI, vol. 12(8), pages 1-26, August.
    5. Zhicheng Duan & Tingting Tang, 2022. "Quantitative Simulation and Verification of the Coordination Curves between Sustainable Development and Green Innovation Efficiency: From the Perspective of Urban Agglomerations Development," Sustainability, MDPI, vol. 14(24), pages 1-22, December.
    6. Guangming Yang & Siyi Cheng & Qingqing Gui & Xinlan Chen, 2022. "The Coupling and Coordination Characteristics and Influencing Factors of Green Innovation Efficiency (GIE) and Economic Development Levels in China," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    7. Weisong Mi & Kaixu Zhao & Pei Zhang, 2022. "Spatio-Temporal Evolution and Driving Mechanism of Green Innovation in China," Sustainability, MDPI, vol. 14(9), pages 1-27, April.
    8. Bin Liao & Lin Li, 2023. "Urban green innovation efficiency and its influential factors: the Chinese evidence," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6551-6573, July.
    9. Kaixuan Di & Zuankuo Liu & Shanglei Chai & Kanyong Li & Yu Li, 2024. "Spatial correlation network structure of green innovation efficiency and its driving factors in the Bohai Rim region," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(11), pages 27227-27247, November.
    10. Biao Hu & Kai Yuan & Tingyun Niu & Liang Zhang & Yuqiong Guan, 2022. "Study on the Spatial and Temporal Evolution Patterns of Green Innovation Efficiency and Driving Factors in Three Major Urban Agglomerations in China—Based on the Perspective of Economic Geography," Sustainability, MDPI, vol. 14(15), pages 1-28, July.
    11. Li Li & Xinwen Bai & Yiyong Zhou, 2023. "A Social Resources Perspective of Employee Innovative Behavior and Outcomes: A Moderated Mediation Model," Sustainability, MDPI, vol. 15(3), pages 1-19, February.

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