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人工智能赋能制造业企业绿色转型:机制与非线性特征OA

Artificial intelligence empowering green transformation of manufacturing enterprises:mechanisms and nonlinear characteristics

中文摘要英文摘要

推动制造业绿色转型对于实现"双碳"目标、促进经济社会高质量发展具有重要意义.该研究基于绿色创新、效率优化和环境绩效3个维度构建企业绿色转型综合指标,采用2010-2023年制造业上市公司数据,系统考察人工智能发展对企业绿色转型的影响.研究发现:①人工智能可以推动制造业企业绿色转型,该结论经过一系列稳健性检验后仍然成立.②机制检验表明,人工智能通过缓解融资约束、优化人力资本结构、增强管理能力,进而推动企业绿色转型.③异质性分析显示,人工智能对制造业企业绿色转型的驱动作用在大型企业、国有企业以及环境规制较强地区的企业中更为突出.④进一步研究发现,人工智能对企业绿色转型的影响具有边际效应递增的非线性特征;从3个组成维度来看,其在绿色创新、效率优化两个维度同样表现出边际效应递增的特征,但在环境绩效维度却呈现出先促进后抑制的特征.⑤以数据资产为调节变量研究其对非线性关系的影响,结果显示,随着数据资产的增加,人工智能对企业绿色转型的影响将依次呈现先抑制后促进、边际效应递增的正向促进、线性促进、边际效应递减的正向促进、先促进后抑制5种状态.基于上述结论,该研究提出如下建议:①推动人工智能与制造业深度融合,促进制造业智能化、绿色化发展;②充分发挥人工智能在缓解融资约束、优化人力资本结构和提升管理能力等方面的赋能效应,推动企业绿色转型;③结合企业特征与人工智能发展阶段,采取差异化的支持策略;④充分挖掘数据资产潜力,加强数字基础设施建设.

Promoting the green transformation of the manufacturing sector is of great significance for achieving the"dual carbon"goals and promoting high-quality economic and social development.Based on the three dimensions of green innovation,efficiency optimiza-tion,and environmental performance,this study constructed a comprehensive index of corporate green transformation.Using data from listed manufacturing firms from 2010 to 2023,it systematically examined the impact of artificial intelligence(AI)development on corpo-rate green transformation.The results showed that:(1)AI could promote the green transformation of manufacturing firms,and this con-clusion remained valid after a series of robustness tests.(2)Mechanism tests indicated that AI promoted corporate green transformation by alleviating financing constraints,optimizing the human capital structure,and enhancing management capability.(3)Heterogeneity analysis showed that the driving effect of AI on corporate green transformation was more pronounced in large enterprises,state-owned enterprises,and firms located in regions with stronger environmental regulation.(4)Further analysis revealed that the impact of AI on corporate green transformation exhibited a nonlinear pattern characterized by increasing marginal effects.From the perspective of three sub-dimensions,AI also exhibited increasing marginal effects in the dimensions of green innovation and efficiency optimization,where-as in the dimension of environmental performance,it showed a pattern of promotion followed by inhibition.(5)Taking data assets as a moderating variable,this study further examined their impact on the nonlinear relationship between AI and green transformation.The results showed that,as data assets increased,the impact of AI on green transformation evolved sequentially through five states:an initial inhibiting-then-promoting effect,a positive promoting effect with increasing marginal effects,a linear promoting effect,a positive pro-moting effect with decreasing marginal effects,and a promoting-then-inhibiting effect.Based on the above findings,this study proposes the following policy recommendations:(1)promote the deep integration of AI with the manufacturing sector so as to advance the intelli-gent and green development of manufacturing;(2)fully leverage the enabling role of AI in alleviating financing constraints,optimizing the human capital structure,and enhancing management capability so as to support corporate green transformation;(3)adopt differenti-ated support strategies that take into account firm characteristics and the stage of AI development;and(4)fully tap the potential of data assets and strengthen digital infrastructure construction.

石建勋;辛沛远

同济大学经济与管理学院,上海 200092||同济大学城市高质量发展与规划决策实验室,上海 200092同济大学经济与管理学院,上海 200092||同济大学城市高质量发展与规划决策实验室,上海 200092

资源环境

人工智能绿色转型绿色创新效率优化环境绩效

artificial intelligencegreen transformationgreen innovationefficiency optimizationenvironmental performance

《中国人口·资源与环境》 2026 (8)

1-16,16

国家社会科学基金重大专项课题(批准号:21VGQ005).

10.12062/cpre.20251219

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