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<p>With the rapid development of China's new energy vehicle industry and the continuous growth of lithium battery consumption scenarios and demand, it is of significant importance to examine the impact on the operational efficiency and ESG performance of Chinese lithium mining companies. However, current research utilizing Data Envelopment Analysis (DEA) to explore this issue remains limited. Therefore, this study selects 19 A-share listed lithium mineral resource companies to construct a two-stage Dynamic Slacks-Based Measure (DSBM) efficiency analysis model and evaluates efficiency across different stages and input–output indicators through common boundary analysis. Additionally, the sample companies are grouped based on different lithium metal extraction processes to explore technical efficiency differences and efficiency changes before and after the pandemic. Subsequently, a Partial Least Squares Regression (PLSR) model and variable projection importance analysis are employed to further analyze the driving factors of organizational efficiency for Chinese lithium resource companies. The analysis results indicate: (1) Significant technical differences exist among lithium mining companies. (2) Operating revenue and total pollutant equivalents play a key role in operational efficiency, while environmental governance investment, corporate governance investment, and ESG indices are significantly associated with ESG performance. (3) Efficiency changes among the sample companies exhibit a complex pattern during the observation period.</p>

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The Efficiency analysis of China’s Lithium Resources Enterprises Organizational Performance Based on ESG perspective

  • 期刊论文

  • 发表日期：

    2026年1月21日

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  • Shaoyu Chen,
  • Jianlin Wang,
  • Zehao Wu

摘要

With the rapid development of China's new energy vehicle industry and the continuous growth of lithium battery consumption scenarios and demand, it is of significant importance to examine the impact on the operational efficiency and ESG performance of Chinese lithium mining companies. However, current research utilizing Data Envelopment Analysis (DEA) to explore this issue remains limited. Therefore, this study selects 19 A-share listed lithium mineral resource companies to construct a two-stage Dynamic Slacks-Based Measure (DSBM) efficiency analysis model and evaluates efficiency across different stages and input–output indicators through common boundary analysis. Additionally, the sample companies are grouped based on different lithium metal extraction processes to explore technical efficiency differences and efficiency changes before and after the pandemic. Subsequently, a Partial Least Squares Regression (PLSR) model and variable projection importance analysis are employed to further analyze the driving factors of organizational efficiency for Chinese lithium resource companies. The analysis results indicate: (1) Significant technical differences exist among lithium mining companies. (2) Operating revenue and total pollutant equivalents play a key role in operational efficiency, while environmental governance investment, corporate governance investment, and ESG indices are significantly associated with ESG performance. (3) Efficiency changes among the sample companies exhibit a complex pattern during the observation period.