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Research on the promotion path of green technology innovation of an enterprise from the perspective of technology convergence: configuration analysis using new energy vehicles as an example

Author

Listed:
  • Kai Guo

    (Henan University of Science & Technology
    Henan Collaborative Innovation Center of Nonferrous Metals)

  • Tiantian Zhang

    (Henan University of Science & Technology)

  • Yan Liang

    (Henan University of Science & Technology)

  • Jiyao Zhao

    (University of Birmingham Joint Institute at Jinan University, Jinan University)

  • Xiangmin Zhang

    (Henan University of Science & Technology
    Henan Collaborative Innovation Center of Nonferrous Metals)

Abstract

In this study, taking the field of new energy vehicles as an example, the green patent data have been obtained from the smart bud patent database, and 243 organizations have been selected as the research samples based on their technical convergence and lack of data of their patents. From the perspective of technology convergence, five factors, including its degree of convergence, influence, knowledge maturity, experience, and originality, have been selected, and the fuzzy-set qualitative comparative analysis technology has been employed for conducting a configuration analysis. It has been found that there are three high green technological innovation paths, namely, the ‘high convergence-high cognitive legitimacy’ type, the ‘high convergence-high influence’ type, and the ‘high convergence-high quality’ type. In addition, five low green technological innovation paths have been obtained, which can be divided into three types, including the ‘low convergence-high impact’ type, the ‘high convergence-low experience’ type, and the ‘high convergence-low quality’ type. Depending on the low green technological innovation paths, the steps of configuring the specific conditions of the included samples and matching them with the most suitable upgrade path should be performed in order to achieve a quick and efficient improvement in the green technology innovation level of an enterprise.

Suggested Citation

  • Kai Guo & Tiantian Zhang & Yan Liang & Jiyao Zhao & Xiangmin Zhang, 2023. "Research on the promotion path of green technology innovation of an enterprise from the perspective of technology convergence: configuration analysis using new energy vehicles as an example," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(6), pages 4989-5008, June.
    • Handle: RePEc:spr:endesu:v:25:y:2023:i:6:d:10.1007_s10668-022-02253-2
    DOI: 10.1007/s10668-022-02253-2
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    References listed on IDEAS

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    1. Wang, Zhinan & Porter, Alan L. & Wang, Xuefeng & Carley, Stephen, 2019. "An approach to identify emergent topics of technological convergence: A case study for 3D printing," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 723-732.
    2. Ying Tang & Xuming Lou & Zifeng Chen & Chengjin Zhang, 2020. "A Study on Dynamic Patterns of Technology Convergence with IPC Co-Occurrence-Based Analysis: The Case of 3D Printing," Sustainability, MDPI, vol. 12(7), pages 1-26, March.
    3. 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.
    4. Manuel Trajtenberg & Rebecca Henderson & Adam Jaffe, 1997. "University Versus Corporate Patents: A Window On The Basicness Of Invention," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 5(1), pages 19-50.
    5. Minyoung Kim, 2013. "Many roads lead to Rome: Implications of geographic scope as a source of isolating mechanisms," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 44(9), pages 898-921, December.
    6. Keijl, S. & Gilsing, V.A. & Knoben, J. & Duysters, G., 2016. "The two faces of inventions: The relationship between recombination and impact in pharmaceutical biotechnology," Research Policy, Elsevier, vol. 45(5), pages 1061-1074.
    7. Jian Cheng Guan & Xia Gao, 2009. "Exploring the h‐index at patent level," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(1), pages 35-40, January.
    8. Du, Jian & Li, Peixin & Guo, Qianying & Tang, Xiaoli, 2019. "Measuring the knowledge translation and convergence in pharmaceutical innovation by funding-science-technology-innovation linkages analysis," Journal of Informetrics, Elsevier, vol. 13(1), pages 132-148.
    9. Jiwon Yu & Jong-Gyu Hwang & Jumi Hwang & Sung Chan Jun & Sumin Kang & Chulung Lee & Hyundong Kim, 2020. "Identification of Vacant and Emerging Technologies in Smart Mobility Through the GTM-Based Patent Map Development," Sustainability, MDPI, vol. 12(22), pages 1-22, November.
    10. Song, Bomi & Suh, Yongyoon, 2019. "Identifying convergence fields and technologies for industrial safety: LDA-based network analysis," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 115-126.
    11. Rene Kemp & Saeed Parto & Robert B. Gibson, 2005. "Governance for sustainable development: moving from theory to practice," International Journal of Sustainable Development, Inderscience Enterprises Ltd, vol. 8(1/2), pages 12-30.
    12. Kose, Toshihiro & Sakata, Ichiro, 2019. "Identifying technology convergence in the field of robotics research," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 751-766.
    13. Chul Lee & Gunno Park & Jina Kang, 2018. "The impact of convergence between science and technology on innovation," The Journal of Technology Transfer, Springer, vol. 43(2), pages 522-544, April.
    14. Jeeeun Kim & Sungjoo Lee, 2017. "Forecasting and identifying multi-technology convergence based on patent data: the case of IT and BT industries in 2020," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 47-65, April.
    15. Song, Chie Hoon & Elvers, David & Leker, Jens, 2017. "Anticipation of converging technology areas — A refined approach for the identification of attractive fields of innovation," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 98-115.
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