IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i8p6342-d1117978.html
   My bibliography  Save this article

The Technological Innovation Efficiency of China’s Renewable Energy Enterprises: An Estimation Based on a Three-Stage DEA Model

Author

Listed:
  • Yuanyuan Chen

    (School of Japanese Economy, Dongguk University, Seoul 04620, Republic of Korea)

  • JungHyun Song

    (School of Japanese Economy, Dongguk University, Seoul 04620, Republic of Korea)

Abstract

The advantages of clean, ecologically friendly, and renewable energy have drawn considerable attention from all nations in the world. The growth of the renewable energy industry has frequently been elevated to the status of national policy. By evaluating the technical innovation effectiveness of China’s renewable energy sector, the energy crisis may be alleviated, and the innovation potential of renewable energy can be boosted. At present, the research content of domestic renewable energy enterprises mainly adopts DEA and Cobb–Douglas production functions. Moreover, there is limited literature on the factors impacting efficiency, and most research results center on efficiency assessment. This study employs a three-step DEA method to determine the technological innovation efficiency for China’s A-share renewable energy firms from 2016 to 2020. To investigate the factors influencing technological innovation’s effectiveness, the panel Tobit model is then developed. In light of the empirical data, the main conclusions of this paper are as follows: First, despite a slow but steady improvement, Chinese renewable energy companies still need to increase their technological innovation efficiency. Pure technical efficiency is the main factor contributing to low innovation efficiency. Second, environmental laws such as reliance on global commerce, industrial structure, and local science and technology affect the innovation effectiveness of listed renewable energy enterprises. After excluding environmental factors, the comprehensive technical efficiency of listed renewable energy companies has decreased. Finally, the innovation and technological efficiency of renewable energy firms are positively impacted by government subsidies, top operational revenue, and enterprise scale.

Suggested Citation

  • Yuanyuan Chen & JungHyun Song, 2023. "The Technological Innovation Efficiency of China’s Renewable Energy Enterprises: An Estimation Based on a Three-Stage DEA Model," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6342-:d:1117978
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/8/6342/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/8/6342/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fei Fan & Huan Lian & Song Wang, 2020. "Can regional collaborative innovation improve innovation efficiency? An empirical study of Chinese cities," Growth and Change, Wiley Blackwell, vol. 51(1), pages 440-463, March.
    2. Galindo, Miguel-Ángel & Méndez, María Teresa, 2014. "Entrepreneurship, economic growth, and innovation: Are feedback effects at work?," Journal of Business Research, Elsevier, vol. 67(5), pages 825-829.
    3. 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).
    4. Willoughby, Kelvin W. & Mullina, Nadezhda, 2021. "Reverse innovation, international patenting and economic inertia: Constraints to appropriating the benefits of technological innovation," Technology in Society, Elsevier, vol. 67(C).
    5. Aytekin, Ahmet & Ecer, Fatih & Korucuk, Selçuk & Karamaşa, Çağlar, 2022. "Global innovation efficiency assessment of EU member and candidate countries via DEA-EATWIOS multi-criteria methodology," Technology in Society, Elsevier, vol. 68(C).
    6. Michael Fritsch, 2004. "Cooperation and the efficiency of regional R&D activities," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 28(6), pages 829-846, November.
    7. Yuan, Chaoqing & Liu, Sifeng & Wu, Junlong, 2009. "Research on energy-saving effect of technological progress based on Cobb-Douglas production function," Energy Policy, Elsevier, vol. 37(8), pages 2842-2846, August.
    8. Wang, Qiang & Dong, Zequn & Li, Rongrong & Wang, Lili, 2022. "Renewable energy and economic growth: New insight from country risks," Energy, Elsevier, vol. 238(PC).
    9. Inglesi-Lotz, Roula, 2016. "The impact of renewable energy consumption to economic growth: A panel data application," Energy Economics, Elsevier, vol. 53(C), pages 58-63.
    10. Xi, Xun & Xi, Baoxing & Miao, Chenglin & Yu, Rongjian & Xie, Jie & Xiang, Rong & Hu, Feng, 2022. "Factors influencing technological innovation efficiency in the Chinese video game industry: Applying the meta-frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    11. Danish I. Godil & Zhang Yu & Arshian Sharif & Rimsha Usman & Syed Abdul Rehman Khan, 2021. "Investigate the role of technology innovation and renewable energy in reducing transport sector CO2 emission in China: A path toward sustainable development," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(4), pages 694-707, July.
    12. Zhang, Caiqing & Chen, Panyu, 2022. "Applying the three-stage SBM-DEA model to evaluate energy efficiency and impact factors in RCEP countries," Energy, Elsevier, vol. 241(C).
    13. Ali, Syed Ahtsham & Alharthi, Majed & Hussain, Hafezali Iqbal & Rasul, Farhat & Hanif, Imran & Haider, Jahanzaib & Ullah, Saad & ur Rahman, Saeed & Abbas, Qaiser, 2021. "A clean technological innovation and eco-efficiency enhancement: A multi-index assessment of sustainable economic and environmental management," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    14. Zhang, Wenting & Wang, Zibang & Adebayo, Tomiwa Sunday & Altuntaş, Mehmet, 2022. "Asymmetric linkages between renewable energy consumption, financial integration, and ecological sustainability: Moderating role of technology innovation and urbanization," Renewable Energy, Elsevier, vol. 197(C), pages 1233-1243.
    15. Seema Sharma & V. J. Thomas, 2008. "Inter-country R&D efficiency analysis: An application of data envelopment analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 483-501, September.
    16. Ali, Aamer & Tufa, Ramato Ashu & Macedonio, Francesca & Curcio, Efrem & Drioli, Enrico, 2018. "Membrane technology in renewable-energy-driven desalination," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1-21.
    17. Weisser, Daniel, 2004. "On the economics of electricity consumption in small island developing states: a role for renewable energy technologies?," Energy Policy, Elsevier, vol. 32(1), pages 127-140, January.
    18. Wang, Zilong & Wang, Xinbin, 2022. "Research on the impact of green finance on energy efficiency in different regions of China based on the DEA-Tobit model," Resources Policy, Elsevier, vol. 77(C).
    19. Chae Hyun Im & Keun Tae Cho, 2021. "Comparing and Identifying Influential Factors of Technological Innovation Efficiency in Manufacturing and Service Industries Using DEA: A Study of SMEs in South Korea," Sustainability, MDPI, vol. 13(23), pages 1-21, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Junhua Chen & Qiaochu Li & Peng Zhang & Xinyi Wang, 2024. "Does Technological Innovation Efficiency Improve the Growth of New Energy Enterprises? Evidence from Listed Companies in China," Sustainability, MDPI, vol. 16(4), pages 1-28, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ostadzad, Ali Hossein, 2022. "Innovation and carbon emissions: Fixed-effects panel threshold model estimation for renewable energy," Renewable Energy, Elsevier, vol. 198(C), pages 602-617.
    2. Riza Radmehr & Samira Shayanmehr & Ernest Baba Ali & Elvis Kwame Ofori & Elżbieta Jasińska & Michał Jasiński, 2022. "Exploring the Nexus of Renewable Energy, Ecological Footprint, and Economic Growth through Globalization and Human Capital in G7 Economics," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    3. Wei, Shuxin & Wei, Wenshan & Umut, Alican, 2023. "Do renewable energy consumption, technological innovation, and international integration enhance environmental sustainability in Brazil?," Renewable Energy, Elsevier, vol. 202(C), pages 172-183.
    4. Xiao-Ying Dong & Qiying Ran & Yu Hao, 2019. "On the nonlinear relationship between energy consumption and economic development in China: new evidence from panel data threshold estimations," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 1837-1857, July.
    5. Dhunny, A.Z. & Allam, Z. & Lobine, D. & Lollchund, M.R., 2019. "Sustainable renewable energy planning and wind farming optimization from a biodiversity perspective," Energy, Elsevier, vol. 185(C), pages 1282-1297.
    6. Keyan Zheng & Fagang Hu & Yaliu Yang, 2023. "Data-Driven Evaluation and Recommendations for Regional Synergy Innovation Capability," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
    7. Rabie Said & Muhammad Ishaq Bhatti & Ahmed Imran Hunjra, 2022. "Toward Understanding Renewable Energy and Sustainable Development in Developing and Developed Economies: A Review," Energies, MDPI, vol. 15(15), pages 1-12, July.
    8. Song Wang & Jiexin Wang & Chenqi Wei & Xueli Wang & Fei Fan, 2021. "Collaborative innovation efficiency: From within cities to between cities—Empirical analysis based on innovative cities in China," Growth and Change, Wiley Blackwell, vol. 52(3), pages 1330-1360, September.
    9. Puertas, Rosa & Carracedo, Patricia & Garcia−Mollá, Marta & Vega, Virginia, 2022. "Analysis of the determinants of market capitalisation: Innovation, climate change policies and business context," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    10. Qian Wang & Yang Chen & Heshan Guan & Oleksii Lyulyov & Tetyana Pimonenko, 2022. "Technological Innovation Efficiency in China: Dynamic Evaluation and Driving Factors," Sustainability, MDPI, vol. 14(14), pages 1-16, July.
    11. Teng, Mingming & Shen, Minghao, 2023. "Fintech and energy efficiency: Evidence from OECD countries," Resources Policy, Elsevier, vol. 82(C).
    12. Stepan Zemtsov & Maxim Kotsemir, 2019. "An assessment of regional innovation system efficiency in Russia: the application of the DEA approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 375-404, August.
    13. Bakari, Sayef, 2022. "The Impact of Natural resources, CO2 Emission, Energy use, Domestic Investment, Innovation, Trade and Digitalization on Economic growth: Evidence from 52 African Countries," MPRA Paper 114323, University Library of Munich, Germany.
    14. Syed Abdul Rehman Khan & Ridwan Lanre Ibrahim & Abul Quasem Al-Amin & Zhang Yu, 2022. "An Ideology of Sustainability under Technological Revolution: Striving towards Sustainable Development," Sustainability, MDPI, vol. 14(8), pages 1-21, April.
    15. Weijiang Liu & Yue Bai, 2021. "An Analysis on the Influence of R&D Fiscal and Tax Subsidies on Regional Innovation Efficiency: Empirical Evidence from China," Sustainability, MDPI, vol. 13(22), pages 1-24, November.
    16. Mihaela Simionescu & Magdalena Rădulescu & Javier Cifuentes-Faura, 2023. "Renewable Energy Consumption-Growth Nexus in European Countries: A Sectoral Approach," Evaluation Review, , vol. 47(2), pages 287-319, April.
    17. Siran Fang & Xiaoshan Xue & Ge Yin & Hong Fang & Jialin Li & Yongnian Zhang, 2020. "Evaluation and Improvement of Technological Innovation Efficiency of New Energy Vehicle Enterprises in China Based on DEA-Tobit Model," Sustainability, MDPI, vol. 12(18), pages 1-22, September.
    18. Reynolds, Travis & Kolodinsky, Jane & Murray, Byron, 2012. "Consumer preferences and willingness to pay for compact fluorescent lighting: Policy implications for energy efficiency promotion in Saint Lucia," Energy Policy, Elsevier, vol. 41(C), pages 712-722.
    19. Shahbaz, Muhammad & Hoang, Thi Hong Van & Mahalik, Mantu Kumar & Roubaud, David, 2017. "Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis," Energy Economics, Elsevier, vol. 63(C), pages 199-212.
    20. Michael Adusei, 2016. "Does Entrepreneurship Promote Economic Growth in Africa?," African Development Review, African Development Bank, vol. 28(2), pages 201-214, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6342-:d:1117978. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.