Analysis of the Spatiotemporal Convergence Effect and Influencing Factors of Industrial Green Technology Innovation Efficiency in the Yangtze River Economic Belt in China

Meng-Chao Yao (), Ren-Jie Zhang and Hui-Zhong Dong
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Meng-Chao Yao: Xinjiang University
Ren-Jie Zhang: China Aerospace Academy of Systems Science and Engineering
Hui-Zhong Dong: Shandong University of Technology

Journal of the Knowledge Economy, 2025, vol. 16, issue 2, No 127, 9430-9465

Abstract: Abstract This study aims to explore the spatiotemporal convergence effects of industrial green technological innovation efficiency and its influencing factors to facilitate the transformation of the Yangtze River Economic Belt from a traditional high-pollution, high-emission, and high-energy-consumption industrial model to a green, efficient, and sustainable economic development model. By applying the Super-SBM model, the absolute beta convergence model, the conditional beta convergence model, and the spatial dynamic Durbin model, this study reveals the dynamic changes in industrial green technological innovation efficiency and its influencing factors in the Yangtze River Economic Belt. The research findings are as follows: (1) Regions with lower industrial green technological innovation efficiency can rapidly improve by learning from more efficient regions, demonstrating a significant “catch-up” effect. The upstream and downstream areas exhibit specific spatial dependencies, while the midstream area does not pass the significance level test. (2) The conditional convergence rate is significantly higher than the absolute convergence rate, indicating the presence of spatial conditional convergence in industrial green technological innovation efficiency among different regions. (3) This study further analyzes the impact mechanisms of six factors—enterprise size, industry-university-research cooperation, enterprise R&D level, environmental regulation, energy consumption structure, and foreign direct investment—on industrial green technological innovation efficiency. The results show that these factors have significant differences in their effects. Finally, this study proposes strategies to optimize green technological innovation efficiency, aiming to provide a reference for the Yangtze River Economic Belt and other regions worldwide to achieve high-quality development with green and low-carbon growth.

Keywords: Yangtze River Economic Belt; Spatiotemporal convergence; Spatial dynamic Durbin model; Influence factor (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13132-024-02286-0

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