IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i5p2221-d1080043.html
   My bibliography  Save this article

Technology Trend Analysis of Japanese Green Vehicle Powertrains Technology Using Patent Citation Data

Author

Listed:
  • Jiaming Jiang

    (Center for Artificial Intelligence and Mathematical Data Science, Okayama University, 2-1-1 Tsushimanaka, Kitaku, Okayama 700-8530, Japan)

  • Yu Zhao

    (School of Management, Department of Management, Tokyo University of Science, Tokyo 162-8601, Japan)

Abstract

As automobiles are major contributors to greenhouse gas emissions, the technological shift towards vehicle powertrain systems is an attempt to lower problems such as emissions of carbon dioxide and nitrogen oxides. Patent data are the most reliable measure of business performance for applied research and development activities when investigating knowledge domains or technology evolution. This is the first study on Japanese patent citation data of the green vehicle powertrains technology industry, using the social network analysis method, which emphasizes centrality estimates and community detection. This study not only elucidates the knowledge by visualizing flow patterns but also provides a precious and congregative method for verifying important patents under the International Patent Classification system and grasping the trend of the new technology industry. This study detects leading companies, not only in terms of the number of patents but also the importance of the patents. The empirical result shows that the International Patent Classification (IPC) class that starts with “B60K”, which includes hybrid electric vehicle (HEV) and battery electric vehicle (BEV), is more likely to be the technology trend in the green vehicle powertrains industry.

Suggested Citation

  • Jiaming Jiang & Yu Zhao, 2023. "Technology Trend Analysis of Japanese Green Vehicle Powertrains Technology Using Patent Citation Data," Energies, MDPI, vol. 16(5), pages 1-14, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2221-:d:1080043
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/5/2221/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/5/2221/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    2. Sternitzke, Christian & Bartkowski, Adam & Schramm, Reinhard, 2008. "Visualizing patent statistics by means of social network analysis tools," World Patent Information, Elsevier, vol. 30(2), pages 115-131, June.
    3. Faria, Lourenço Galvão Diniz & Andersen, Maj Munch, 2017. "Sectoral patterns versus firm-level heterogeneity - The dynamics of eco-innovation strategies in the automotive sector," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 266-281.
    4. Jiaming Jiang & Yu Zhao & Junshi Feng, 2022. "University–Industry Technology Transfer: Empirical Findings from Chinese Industrial Firms," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    5. Jiaming Jiang & Rajeev K. Goel & Xingyuan Zhang, 2020. "IPR policies and determinants of membership in Standard Setting Organizations: a social network analysis," Netnomics, Springer, vol. 21(1), pages 129-154, December.
    6. Loet Leydesdorff & Liwen Vaughan, 2006. "Co‐occurrence matrices and their applications in information science: Extending ACA to the Web environment," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(12), pages 1616-1628, October.
    7. Cohen, Wesley M. & Goto, Akira & Nagata, Akiya & Nelson, Richard R. & Walsh, John P., 2002. "R&D spillovers, patents and the incentives to innovate in Japan and the United States," Research Policy, Elsevier, vol. 31(8-9), pages 1349-1367, December.
    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. Jian Xue & YiXue Fan & Yang Lv, 2024. "The evolution of patent cooperation network for new energy vehicle power battery," SN Business & Economics, Springer, vol. 4(7), pages 1-17, July.

    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. Jiaming Jiang & Yu Zhao & Junshi Feng, 2022. "University–Industry Technology Transfer: Empirical Findings from Chinese Industrial Firms," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    2. Hao Wang & Sanhong Deng & Xinning Su, 2016. "A study on construction and analysis of discipline knowledge structure of Chinese LIS based on CSSCI," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1725-1759, December.
    3. De Paulo, A.F. & Porto, G.S., 2023. "Unveiling the cooperation dynamics in the photovoltaic technologies’ development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    4. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    5. Jiaming Jiang & Rajeev K. Goel & Xingyuan Zhang, 2020. "IPR policies and determinants of membership in Standard Setting Organizations: a social network analysis," Netnomics, Springer, vol. 21(1), pages 129-154, December.
    6. Heyoung Yang & Hyuck Jai Lee, 2018. "Research Trend Visualization by MeSH Terms from PubMed," IJERPH, MDPI, vol. 15(6), pages 1-14, May.
    7. Jiaming Jiang & Rajeev K. Goel & Xingyuan Zhang, 2019. "Knowledge flows from business method software patents: influence of firms’ global social networks," The Journal of Technology Transfer, Springer, vol. 44(4), pages 1070-1096, August.
    8. Yan, Erjia, 2014. "Research dynamics: Measuring the continuity and popularity of research topics," Journal of Informetrics, Elsevier, vol. 8(1), pages 98-110.
    9. Alex Fabianne de Paulo & Evandro Marcos Saidel Ribeiro & Geciane Silveira Porto, 2018. "Mapping countries cooperation networks in photovoltaic technology development based on patent analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 667-686, November.
    10. Seyedmohammadreza Hosseini & Hamed Baziyad & Rasoul Norouzi & Sheida Jabbedari Khiabani & Győző Gidófalvi & Amir Albadvi & Abbas Alimohammadi & Seyedehsan Seyedabrishami, 2021. "Mapping the intellectual structure of GIS-T field (2008–2019): a dynamic co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2667-2688, April.
    11. Calvin Weng & Tugrul Daim, 2012. "Structural Differentiation and Its Implications—Core/Periphery Structure of the Technological Network," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 3(4), pages 327-342, December.
    12. Feng, Feng & Zhang, Leiyong & Du, Yuneng & Wang, Weiguang, 2015. "Visualization and quantitative study in bibliographic databases: A case in the field of university–industry cooperation," Journal of Informetrics, Elsevier, vol. 9(1), pages 118-134.
    13. Tingcan Ma & Ruinan Li & Guiyan Ou & Mingliang Yue, 2018. "Topic based research competitiveness evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 789-803, November.
    14. Jacob Wood & Gohar Feroz Khan, 2015. "International trade negotiation analysis: network and semantic knowledge infrastructure," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 537-556, October.
    15. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    16. Xingwen Chen & Li Zhu & Chao Liu & Chunhua Chen & Jun Liu & Dongxia Huo, 2023. "Workplace Diversity in the Asia-Pacific Region: A Review of Literature and Directions for Future Research," Asia Pacific Journal of Management, Springer, vol. 40(3), pages 1021-1045, September.
    17. Hille, Erik & Althammer, Wilhelm & Diederich, Henning, 2020. "Environmental regulation and innovation in renewable energy technologies: Does the policy instrument matter?," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    18. Crass, Dirk & Garcia Valero, Francisco & Pitton, Francesco & Rammer, Christian, 2016. "Protecting innovation through patents and trade secrets: Determinants and performance impacts for firms with a single innovation," ZEW Discussion Papers 16-061, ZEW - Leibniz Centre for European Economic Research.
    19. Ziwen Wei & Man Yuan, 2023. "Research on the Current Situation and Future Development Trend of Immersive Virtual Reality in the Field of Education," Sustainability, MDPI, vol. 15(9), pages 1-18, May.
    20. Hrosul, Viktoriia & Kruhlova, Olena & Kolesnyk, Alina, 2023. "Digitalization of the agricultural sector: the impact of ICT on the development of enterprises in Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(4), December.

    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:jeners:v:16:y:2023:i:5:p:2221-:d:1080043. 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.