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

Jiaming Jiang () and Yu Zhao
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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

Energies, 2023, vol. 16, issue 5, 1-14

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.

Keywords: patents; green innovation; social network analysis; carbon reduction; transportation management (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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