ID | 65057 |
フルテキストURL | |
著者 |
Jiang, Jiaming
Center for Artificial Intelligence and Mathematical Data Science, Okayama University
Zhao, Yu
School of Management, Department of Management, Tokyo University of Science
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抄録 | 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.
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キーワード | patents
green innovation
social network analysis
carbon reduction
transportation management
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発行日 | 2023-02-24
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出版物タイトル |
Energies
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巻 | 16巻
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号 | 5号
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出版者 | MDPI
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開始ページ | 2221
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ISSN | 1996-1073
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資料タイプ |
学術雑誌論文
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言語 |
英語
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OAI-PMH Set |
岡山大学
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著作権者 | © 2023 by the authors.
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論文のバージョン | publisher
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DOI | |
Web of Science KeyUT | |
関連URL | isVersionOf https://doi.org/10.3390/en16052221
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ライセンス | https://creativecommons.org/licenses/by/4.0/
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Citation | Jiang, J.; Zhao, Y. Technology Trend Analysis of Japanese Green Vehicle Powertrains Technology Using Patent Citation Data. Energies 2023, 16, 2221. https:// doi.org/10.3390/en16052221
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助成機関名 |
Japan Society for the Promotion of Science
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助成番号 | 22K01462
22H00846
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