机器人应用如何助力工业低碳发展：基于减碳增效视角的研究

IF 13.3 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change Pub Date : 2025-08-11 DOI:10.1016/j.techfore.2025.124301

Shan Wang , Haiqian Chen , Donghua Yu

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引用次数: 0

摘要

在数字经济时代，机器人应用已成为提高工业碳排放效率的有效途径。本文从减少碳排放和提高效率的双重视角，从理论上分析了机器人应用对推动工业低碳发展的作用和机制。本文基于2010 - 2019年中国212个城市的数据进行实证检验。结果表明，机器人的应用提高了工业碳排放效率。具体而言，它对工业碳排放具有显著的抑制作用，对工业增加值具有显著的促进作用，表现出碳减排和效率提升的双重效应。机理研究表明，机器人的应用可以显著促进绿色技术创新，表现为绿色发明专利和绿色实用新型专利的增加，以及能源强度的降低。异质性分析表明，在碳排放高、规模大、技术人才丰富的城市，机器人应用对工业低碳发展的赋能作用更为明显。本文不仅为数字经济的减碳效应研究提供了有价值的补充，而且从减碳增效的角度为加快工业低碳发展提供了政策见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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How robot application empowers industrial low-carbon development: A study based on the perspective of carbon reduction and efficiency enhancement

In the digital economy era, robot application has become an effective pathway to enhance the industrial carbon emission efficiency. This paper theoretically analyzes the effect and mechanism of robot application in empowering industrial low-carbon development from the dual perspectives of carbon reduction and efficiency enhancement. Empirical tests are conducted based on 212 cities data in China from 2010 to 2019. The results show that the robot application improves the industrial carbon emission efficiency. Specifically it has a significant inhibitory effect on industrial carbon emissions and a promotive effect on industrial added-value, demonstrating a dual effect of carbon reduction and efficiency enhancement. Mechanism research shows that the robot application can significantly promote green technology innovation, manifested by an increase in green invention patents and green utility model patents, as well as the decrease in energy intensity. Heterogeneity analysis indicates that the empowering effect of robot application on industrial low-carbon development is more pronounced in cities with higher carbon emissions, larger scale, and richer technical talents. This paper not only provides a valuable supplement to the research of the carbon reduction effect of digital economy, but also offers policy insights for accelerating industrial low-carbon development from the perspectives of carbon reduction and efficiency enhancement.

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来源期刊

Technological Forecasting and Social Change Multiple-

CiteScore

21.30

自引率

10.80%

发文量

813

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