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<p>Lithium-ion batteries (LIBs) play a crucial role in efforts to reduce carbon emissions, promote electrification, and enhance environmental sustainability. While existing research has explored the network structure and supply risks of LIBs, the factors shaping the global LIB trade network remain understudied. This research addresses the gap by examining the determinants of the global LIB trade network from 2012 to 2022, utilizing complex network theory, global trade theory, and temporal exponential random graph model (TERGM). The analysis reveals several key findings: (1) Reciprocity, transitivity, and stability have a positive influence on the formation of LIB trade relationships. (2) Countries with similar levels of R&amp;D investment, technological innovation, and LIB production and sales are less likely to establish trade connections. (3) Nations with advanced manufacturing capabilities, political stability, and strong environmental performance tend to import LIBs, while those with larger economies, higher industrialization, and greater urbanization are more likely to export. (4) Geographical proximity, historical colonial ties, and regional trade agreements facilitate LIB trade between countries. These insights provide valuable guidance for policymakers and stakeholders seeking to navigate the complex dynamics of the global LIB trade landscape and promote sustainable energy transitions.</p>

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The determinants of global lithium-ion battery trade network based on temporal exponential random graph model

  • 期刊论文

  • 发表日期：

    2026年2月26日

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  • Chao Wang,
  • Kangyu Tan,
  • Xiaoqian Hu,
  • Boxue Sun,
  • Xianfeng Zhao

摘要

Lithium-ion batteries (LIBs) play a crucial role in efforts to reduce carbon emissions, promote electrification, and enhance environmental sustainability. While existing research has explored the network structure and supply risks of LIBs, the factors shaping the global LIB trade network remain understudied. This research addresses the gap by examining the determinants of the global LIB trade network from 2012 to 2022, utilizing complex network theory, global trade theory, and temporal exponential random graph model (TERGM). The analysis reveals several key findings: (1) Reciprocity, transitivity, and stability have a positive influence on the formation of LIB trade relationships. (2) Countries with similar levels of R&D investment, technological innovation, and LIB production and sales are less likely to establish trade connections. (3) Nations with advanced manufacturing capabilities, political stability, and strong environmental performance tend to import LIBs, while those with larger economies, higher industrialization, and greater urbanization are more likely to export. (4) Geographical proximity, historical colonial ties, and regional trade agreements facilitate LIB trade between countries. These insights provide valuable guidance for policymakers and stakeholders seeking to navigate the complex dynamics of the global LIB trade landscape and promote sustainable energy transitions.