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Does AI promote synergistic efficiency in reducing textile industry pollution and carbon emissions?

Year: 2025

Type: article

Abstract: This study uses 102 textile enterprises listed in China’s A-share market from 2012 to 2022 as the research objects to explore the impact of artificial intelligence (AI) on enhancing textile enterprises’ pollution and carbon emissions reduction. Findings reveal that AI can significantly promote textile enterprises’ coordinated enhancement of pollution and carbon emissions reduction, and this finding holds after a series of robustness tests. The mechanism analysis demonstrates that textile enterprises’ pollution and carbon emissions reduction can be promoted by AI through improving textile raw material suppliers’ total factor productivity, increasing the fixed investment for pollution and carbon emissions reduction, and reducing the price of cotton. Heterogeneity analysis reveals that the positive impact of AI is more significant for textile enterprises with high environmental regulation intensity, executives with digital backgrounds, and intellectual property demonstration cities. In response to these findings, we propose relevant policy suggestions to provide references for accelerating textile enterprises’ transformation and upgrading and promoting steady economic growth.

Source: Journal of Innovation & Knowledge

DOI: 10.1016/j.jik.2025.100904

Authors: Lelai Shi, Qiuhang Chen, Hong Lin

Institution: Wuhan Textile University

Language: English

Topic: Energy, Environment, Economic Growth

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Responsible consumption and production, Climate action

Open Access status: gold

Estimated APC paid: $2,200