人工智能应用对制造业企业绿色转型的影响研究

Impacts of Artificial Intelligence Applications on the Green Transformation of Manufacturing Enterprises

摘要

制造业企业绿色转型是实现“双碳”目标的有力支撑，以智能化和自动化为核心特征的人工智能应用成为制造业企业智能化升级和绿色转型的新动能。论文基于2010—2023年沪深A股制造业上市公司数据，构建双向固定效应模型和中介效应模型，探究人工智能应用对制造业企业绿色转型的影响效应及作用机制。研究发现：1）人工智能应用能够显著促进制造业企业绿色转型，考虑内生性问题并进行稳健性检验后结论依旧成立；2）机制检验显示，人工智能应用能够发挥成本节约效应、绿色创新效应、低技能劳动力替代效应，并从生产末端治理、生产前端控制、生产流程优化上促进制造业企业绿色转型；3）异质性分析发现，当企业生命周期处于成长期和成熟期、行业属性为低碳行业、位于胡焕庸线东侧地区时，人工智能应用对企业绿色转型的促进效应更强；4）拓展性研究表明，人工智能应用能够促进企业发展与减排遐迩一体，推动经济增长和环境保护协同发展。基于以上研究结论提出应高度重视人工智能技术的绿色价值、推动企业智能制造与绿色转型深度融合、释放人工智能技术的增效与减排双重作用，以智能技术提效扩产、节能降耗助力绿色转型。研究为制造业企业实现数智化、绿色化深度融合与协同发展提供了经验证据。

Abstract

The green transformation of manufacturing enterprises is a strong support for achieving the “dual carbon” goals, and applications of artificial intelligence (AI)—characterized by intelligence and automation—have become a new driver for intelligent upgrading and green transformation in manufacturing. Based on data for Shanghai and Shenzhen A-listed manufacturing firms from 2010 to 2023, this study builds a two-way fixed-effects model and a mediation-effect model to examine the impact of AI applications on manufacturing firms' green transformation and its mechanisms. The results show that: 1) AI applications significantly promote green transformation in manufacturing firms, and the conclusion remains robust after addressing endogeneity and conducting robustness checks; 2) mechanism tests indicate that AI applications contribute through cost-saving effects, green-innovation effects, and substitution of low-skilled labor, and promote green transformation via end-of-pipe treatment, front-end control, and production-process optimization; 3) heterogeneity analysis shows stronger effects when firms are in the growth or maturity stages, when the industry is low-carbon, and when firms are located east of the Huhuanyong Line; and 4) extended analysis suggests that AI applications help integrate enterprise development with emission reduction, promoting coordinated progress in economic growth and environmental protection. Based on these findings, the paper proposes placing greater emphasis on the green value of AI technologies, promoting deeper integration of intelligent manufacturing and green transformation, and releasing AI's dual roles in efficiency enhancement and emission reduction—using intelligent technologies to improve efficiency and expand production while saving energy and reducing consumption to facilitate green transformation. This study provides empirical evidence for manufacturing enterprises to achieve deeper integration and coordinated development of digital intelligence and greening.

关键词

人工智能应用 / 绿色转型 / 成本节约 / 绿色创新 / 制造业企业

Key words

artificial intelligence applications / green transformation / cost savings / green innovation / manufacturing-enterprises

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基金资助

国家社会科学基金项目(23BGL237)