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<p>In terms of resource conservation and eco—protection, as well as the long—term stable development of the new energy vehicle industry, the proper recycling of new energy vehicle power batteries holds a vital position. However, the learning effect and carbon trading income significantly impact the decision-making of power battery recyclers. This paper constructs an evolutionary game model involving three stakeholders: the government, power battery recyclers, and consumers. The model incorporates static and dynamic regulatory mechanisms to analyze the stability of decision-making processes. Results show that the three-party game system can achieve asymptotic stability only under a dynamic supervision mechanism, where government subsidies and penalties decrease with the increasing proportion of enterprises engaged in formal recycling. The learning effect promotes formal recycling behaviour among enterprises and consumers, reducing the probability and cost of government regulation when the learning rate index for carbon emission reduction R&amp;D is 0.02. Additionally, enterprises are most sensitive to penalties, while consumers are most sensitive to subsidies. This study proposes new ideas for the government to create a policy environment suitable for dual carbon targets and to promote the formal recycling of power batteries.</p>

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Evolutionary analysis of stakeholder decisions in power battery recycling with learning effects and carbon trading

  • 期刊论文

  • 发表日期：

    2025年9月11日

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  • Jingjing Li,
  • Zhaoxin Wang,
  • Yelong Dong,
  • Jiabao Zhou

摘要

In terms of resource conservation and eco—protection, as well as the long—term stable development of the new energy vehicle industry, the proper recycling of new energy vehicle power batteries holds a vital position. However, the learning effect and carbon trading income significantly impact the decision-making of power battery recyclers. This paper constructs an evolutionary game model involving three stakeholders: the government, power battery recyclers, and consumers. The model incorporates static and dynamic regulatory mechanisms to analyze the stability of decision-making processes. Results show that the three-party game system can achieve asymptotic stability only under a dynamic supervision mechanism, where government subsidies and penalties decrease with the increasing proportion of enterprises engaged in formal recycling. The learning effect promotes formal recycling behaviour among enterprises and consumers, reducing the probability and cost of government regulation when the learning rate index for carbon emission reduction R&D is 0.02. Additionally, enterprises are most sensitive to penalties, while consumers are most sensitive to subsidies. This study proposes new ideas for the government to create a policy environment suitable for dual carbon targets and to promote the formal recycling of power batteries.