Can artificial intelligence technology improve companies' capacity for green innovation? Evidence from listed companies in China

IF 14.2 2区 经济学 Q1 ECONOMICS Energy Economics Pub Date : 2025-02-07 DOI:10.1016/j.eneco.2025.108280
Yingji Liu , Fangbing Shen , Ju Guo , Guoheng Hu , Yuegang Song
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Abstract

Green innovation in the digital economy is characterized by complex adaptive systems. It is challenging to effectively improve corporate green innovation capacity (CGIC) by relying on traditional technological innovation. The integration of enterprises' green innovation and artificial intelligence technology (AIT) is becoming a significant driver for addressing global environmental challenges and promoting enterprises' energy efficiency and low-carbon development. Combining patent datasets for listed companies in China, this study explores the driving effect of AIT on CGIC from the perspective of “artificial intelligence +”. This study empirically examines how AIT affects CGIC, and further investigates AIT's impact on the duration of enterprises' green innovation. The findings reveal that AIT's intervention can effectively improve CGIC. Enterprises with different characteristics have heterogeneous effects on improving CGIC by applying AI, indicating that the application of AIT has a more prominent impact on heavily polluting, nontechnology-intensive, and highly competitive enterprises. Mechanism analysis demonstrates that AIT can improve CGIC by absorbing high-skilled labor and increasing investment in research and development. Further examination reveals that AIT application can significantly reduce the potential for enterprises interrupting green innovation activities and prolong the duration of green innovation. This study provides valuable insights concerning the effect of enterprises' AIT application on improving CGIC, empowering enterprises to improve energy efficiency and achieve low-carbon development.
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人工智能技术能提高企业的绿色创新能力吗?来自中国上市公司的证据
数字经济中的绿色创新具有复杂适应系统的特点。依靠传统的技术创新来有效提高企业绿色创新能力是一个挑战。企业绿色创新与人工智能技术的融合,正成为应对全球环境挑战、推动企业节能低碳发展的重要动力。本研究结合中国上市公司专利数据集,从“人工智能+”的视角探讨在台投资对CGIC的驱动效应。本研究实证考察了美国在台投资对企业绿色创新能力的影响,并进一步探讨了美国在台投资对企业绿色创新持续时间的影响。研究结果表明,AIT干预可以有效改善CGIC。不同特征的企业应用人工智能提高CGIC的效果存在异质性,说明应用人工智能对重污染、非技术密集型、竞争力强的企业的影响更为突出。机制分析表明,在台投资可以通过吸收高技能劳动力和增加研发投入来提高CGIC。进一步研究发现,应用在台技术可以显著降低企业中断绿色创新活动的可能性,延长绿色创新的持续时间。本研究为企业应用AIT对提高CGIC、增强企业能效、实现低碳发展的作用提供了有价值的见解。
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来源期刊
Energy Economics
Energy Economics ECONOMICS-
CiteScore
18.60
自引率
12.50%
发文量
524
期刊介绍: Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.
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