Trade Network Pattern and Factors Influencing New Energy Vehicles in RCEP Agreement Countries

Authors

  • Weihua Pan School of Economics and Management, Hubei University of Automotive Technology, Shiyan 442002, China
  • Caihua Liu School of Economics and Management, Hubei University of Automotive Technology, Shiyan 442002, China
  • Ying Liu School of Foreign Language, Hubei University of Automotive Technology, Shiyan 442002, China

Abstract

This study uses social network analysis as a tool to investigate the structure of the trade network and the factors that influence the trade of new energy vehicles in the 15 countries party to the 2022 RCEP agreement. The findings reveal that: (1) The density and correlation of the trade network for new energy vehicles among the countries in the agreement are significant, suggesting strong connection and considerable trade opportunities; (2) South Korea, China, and Japan occupy central positions within the trade network, and the “RCEP” trade network can be divided into three distinct trade clusters; (3) A country’s level of economic development and logistics performance index have a significant and positive impact on the establishment of new energy vehicle trade relationships; lithium battery trade discrepancies, fuel trade levels, the presence of a shared border between countries has a
significant impact on the establishment and strength of trade partnershipswith newenergy vehicles; and similarities in business convenience indices and geographical distance facilitate the establishment of new energy vehicle trade connections and enhance trade intensity among nations. Consequently, countries party to the agreement should continue to develop the construction of their transportation infrastructure and increase investment in industrial chain and infrastructure development.

Keywords: “RCEP” agreement; new energy vehicle trade; social network analysis; QAP analysis

Cite As

W. Pan, C. Liu, Y. Liu, "Trade Network Pattern and Factors Influencing New Energy Vehicles in RCEP
Agreement Countries", Engineering Intelligent Systems, vol. 32 no. 6, pp. 613-623, 2024.






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Published

2024-11-01

Issue

Vol. 32 No. 6 (2024): International Journal of Engineering Intelligent Systems

Section

Article

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