生态经济

在“人工智能+”行动与“双碳”目标协同推进的背景下，资源型企业面临资源依赖锁定与环境监管强化的双重挑战，传统绿色转型路径已收效甚微，亟须探索人工智能驱动绿色创新绩效的作用机制。基于2012—2024年中国资源型上市公司数据，实证检验人工智能对其绿色创新绩效的作用及内在机制。研究发现，人工智能会显著提升资源型企业绿色创新绩效，其作用主要通过增强技术创新动态能力、知识重组创造能力和绿色资源配置能力三条路径产生。而环境不确定性会削弱人工智能的赋能效果，组织韧性和媒体关注度则进一步增强人工智能对绿色创新绩效的作用。异质性分析表明，融资约束低、高学历人才比重大的，以及位于非资源型城市和数字基础设施水平较高地区的资源型企业，人工智能的绿色创新潜力更大。由此提出促进人工智能驱动资源型企业绿色创新绩效提升的启示和建议。

Against the backdrop of the “artificial intelligence+” initiative and the coordinated advancement of the dual carbon goals， resource-based enterprises face the dual challenges of resource dependence lock-in and intensified environmental regulation. Traditional pathways for green transformation have become less effective， highlighting the urgent need to explore how artificial intelligence drives green innovation performance. Based on data from China’s resource-based listed companies from 2012 to 2024， this study empirically examines the impact of artificial intelligence on their green innovation performance and the underlying mechanisms. The findings reveal that artificial intelligence significantly enhances the green innovation performance of resource-based enterprises， primarily through three pathways: Strengthening technological innovation dynamic capabilities， knowledge reconfiguration and creation capabilities， and green resource allocation capabilities. However， environmental uncertainty weakens the empowering effect of artificial intelligence， while organizational resilience and media attention further amplify its impact on green innovation performance. Heterogeneity analysis indicates that resource-based enterprises with lower financing constraints， higher proportions of highly educated talent， located in non-resource cities， and in regions with advanced digital infrastructure exhibit greater green innovation potential driven by artificial intelligence. Consequently， insights and recommendations are proposed to promote the enhancement of green innovation performance in resource-based enterprises through artificial intelligence.