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Evaluation of Green Innovation Efficiency in Chinese Provincial Regions under High-Quality Development and Its Influencing Factors: An Empirical Study Based on Hybrid Data Envelopment Analysis and Multilevel Mixed-Effects Tobit Models

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  • Jiying Zhou

    (School of Economics, Henan University, Kaifeng 475004, China)

  • Mingwei Shao

    (School of Economics, Henan University, Kaifeng 475004, China)

Abstract

In the context of China’s high-quality economic development, in-depth research on green innovation efficiency and its influencing factors is crucial for promoting economic transformation and energy conservation. This study employs the Hybrid Data Envelopment Analysis (DEA) method to measure the green innovation efficiency of 30 provinces in China from 2013 to 2019. Subsequently, based on the Multilevel Mixed-Effects (MME) Tobit model and a spatial econometric model, the study investigates the factors influencing green innovation efficiency under the backdrop of high-quality development, and conducts various robustness tests from different perspectives. The results indicate the following: Firstly, the overall level of green innovation efficiency in China is relatively low, but it shows a steady growth trend, with significant differences in green innovation efficiency among provinces in different stages of high-quality development. Secondly, the level of digital economic development, optimization of industrial structure, scale of knowledge dissemination, and degree of openness to the outside world have significant positive effects on green innovation efficiency. On the other hand, the scale of technological innovation, degree of environmental regulation, and guarantee of green innovation have significant negative effects, and the low quality of technological innovation hinders the improvement of green innovation efficiency. Thirdly, the new factors emerging under the backdrop of high-quality development exhibit certain spillover effects on green innovation efficiency. The green innovation efficiency of a province may be influenced by relevant factors in neighboring provinces. This provides new insights for provinces to enhance their green innovation efficiency. The contribution of this study lies in the incorporation of newly emerged factors in the context of high-quality development into the evaluation framework of green innovation efficiency. It accurately measures the green innovation efficiency of each province in China and, based on the analysis of influencing factors, provides novel insights for enhancing green innovation efficiency across provinces.

Suggested Citation

  • Jiying Zhou & Mingwei Shao, 2023. "Evaluation of Green Innovation Efficiency in Chinese Provincial Regions under High-Quality Development and Its Influencing Factors: An Empirical Study Based on Hybrid Data Envelopment Analysis and Mul," Sustainability, MDPI, vol. 15(14), pages 1-31, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11079-:d:1194863
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    1. 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.
    2. Basma Hamrouni & Abdelhabib Bourouis & Ahmed Korichi & Mohsen Brahmi, 2021. "Explainable Ontology-Based Intelligent Decision Support System for Business Model Design and Sustainability," Sustainability, MDPI, vol. 13(17), pages 1-28, September.
    3. Van Den Broeck, C. & Horsthemke, W. & Malek-Mansour, M., 1977. "On the diffusion operator of the multivariate master equation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 89(2), pages 339-352.
    4. Banker, R. D. & Charnes, A. & Cooper, W. W. & Clarke, R., 1989. "Constrained game formulations and interpretations for data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 40(3), pages 299-308, June.
    5. 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.
    Full references (including those not matched with items on IDEAS)

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