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Spatial heterogeneity and evolution trend of regional green innovation efficiency--an empirical study based on panel data of industrial enterprises in China's provinces

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  • Miao, Cheng-lin
  • Duan, Meng-meng
  • Zuo, Yang
  • Wu, Xin-yu

Abstract

Green innovation is of great significance to promote high-quality growth of the national economy and reduce the load on the ecological environment. This study constructs a two-stage SBM-DEA model including energy and undesirable output to measure green innovation efficiency. Tobit model is used to analyze the impact of input variables and influencing factors. The main results are as follows: achievement transformation, technology development and green innovation efficiency in each region all show a trend of fluctuating growth, and green innovation efficiency in the eastern region has always been in a leading position. The total current volumes of R&D personnel and government support strength have a positive relationship and the intensity of R&D funding and environmental protection investment has a negative relationship with the technology development. The number of patent applications and the openness degree to the outside world are positively related to the achievement transformation, and the investment of new products and energy is negatively related to the achievement transformation. Through the comparative analysis of the innovation efficiency differences among different regions, the paper analyzes the main influencing factors, and puts forward countermeasures and suggestions to provide certain theoretical reference for the sustainable and healthy development of China's various regions.

Suggested Citation

  • Miao, Cheng-lin & Duan, Meng-meng & Zuo, Yang & Wu, Xin-yu, 2021. "Spatial heterogeneity and evolution trend of regional green innovation efficiency--an empirical study based on panel data of industrial enterprises in China's provinces," Energy Policy, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:enepol:v:156:y:2021:i:c:s0301421521002408
    DOI: 10.1016/j.enpol.2021.112370
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    1. Kiani Mavi, Reza & Saen, Reza Farzipoor & Goh, Mark, 2019. "Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 553-562.
    2. Avilés-Sacoto, Sonia Valeria & Cook, Wade D. & Güemes-Castorena, David & Zhu, Joe, 2020. "Modelling Efficiency in Regional Innovation Systems: A Two-Stage Data Envelopment Analysis Problem with Shared Outputs within Groups of Decision-Making Units," European Journal of Operational Research, Elsevier, vol. 287(2), pages 572-582.
    3. Cojoianu, Theodor F. & Clark, Gordon L. & Hoepner, Andreas G.F. & Veneri, Paolo & Wójcik, Dariusz, 2020. "Entrepreneurs for a low carbon world: How environmental knowledge and policy shape the creation and financing of green start-ups," Research Policy, Elsevier, vol. 49(6).
    4. Kontolaimou, Alexandra & Giotopoulos, Ioannis & Tsakanikas, Aggelos, 2016. "A typology of European countries based on innovation efficiency and technology gaps: The role of early-stage entrepreneurship," Economic Modelling, Elsevier, vol. 52(PB), pages 477-484.
    5. Namazi, Mehdi & Mohammadi, Emran, 2018. "Natural resource dependence and economic growth: A TOPSIS/DEA analysis of innovation efficiency," Resources Policy, Elsevier, vol. 59(C), pages 544-552.
    6. Wang, Ya & Pan, Jiao-feng & Pei, Rui-min & Yi, Bo-Wen & Yang, Guo-liang, 2020. "Assessing the technological innovation efficiency of China's high-tech industries with a two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    7. Wang, Qunwei & Hang, Ye & Sun, Licheng & Zhao, Zengyao, 2016. "Two-stage innovation efficiency of new energy enterprises in China: A non-radial DEA approach," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 254-261.
    8. Frondel, Manuel & Horbach, Jens & Rennings, Klaus, 2008. "What triggers environmental management and innovation? Empirical evidence for Germany," Ecological Economics, Elsevier, vol. 66(1), pages 153-160, May.
    9. Galeotti, Marzio & Salini, Silvia & Verdolini, Elena, 2020. "Measuring environmental policy stringency: Approaches, validity, and impact on environmental innovation and energy efficiency," Energy Policy, Elsevier, vol. 136(C).
    10. Eunkwang Seo & Hyo Kang & Jaeyong Song, 2020. "Blending talents for innovation: Team composition for cross-border R&D collaboration within multinational corporations," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 51(5), pages 851-885, July.
    11. Wurlod, Jules-Daniel & Noailly, Joëlle, 2018. "The impact of green innovation on energy intensity: An empirical analysis for 14 industrial sectors in OECD countries," Energy Economics, Elsevier, vol. 71(C), pages 47-61.
    12. Haschka, Rouven E. & Herwartz, Helmut, 2020. "Innovation efficiency in European high-tech industries: Evidence from a Bayesian stochastic frontier approach," Research Policy, Elsevier, vol. 49(8).
    13. Durusu-Ciftci, Dilek & Soytas, Ugur & Nazlioglu, Saban, 2020. "Financial development and energy consumption in emerging markets: Smooth structural shifts and causal linkages," Energy Economics, Elsevier, vol. 87(C).
    14. Bian, Junsong & Zhang, Guoqing & Zhou, Guanghui, 2020. "Manufacturer vs. Consumer Subsidy with Green Technology Investment and Environmental Concern," European Journal of Operational Research, Elsevier, vol. 287(3), pages 832-843.
    15. Eunkwang Seo & Hyo Kang & Jaeyong Song, 0. "Blending talents for innovation: Team composition for cross-border R&D collaboration within multinational corporations," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 0, pages 1-35.
    16. Hosseini, Keyvan & Stefaniec, Agnieszka, 2019. "Efficiency assessment of Iran's petroleum refining industry in the presence of unprofitable output: A dynamic two-stage slacks-based measure," Energy, Elsevier, vol. 189(C).
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