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Sustainability
Volume 18
Issue 11
10.3390/su18115616
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

The Impact of Artificial Intelligence on Urban Green Total Factor Productivity—Evidence from Chinese Cities

by
Xupei Wang
1,
Minghuan Wu
1,
Yuan Feng
2 and
Liang Zhao
1,*
1
School of Economics, Guangdong Ocean University, Zhanjiang 524000, China
2
School of Management, Guangdong Ocean University, Zhanjiang 524000, China
*
Author to whom correspondence should be addressed.
Sustainability 2026, 18(11), 5616; https://doi.org/10.3390/su18115616
Submission received: 21 April 2026 / Revised: 23 May 2026 / Accepted: 31 May 2026 / Published: 2 June 2026
(This article belongs to the Special Issue AI- and Data-Driven Urban Solutions for Sustainability, Resilience, and City Operations)
Review Reports Versions Notes

Abstract

Green total factor productivity (GTFP) plays an important role in urban sustainability. In the context of rapid advances in artificial intelligence (AI), this study examines whether and how the accumulation of AI technologies affects urban GTFP. We construct a city-level AI development index based on patent data. Using panel data on 120 Chinese prefecture-level cities from 2010 to 2023, we employ two-way fixed-effects models, instrumental-variables estimation, and multiple robustness checks to identify the impact of AI on urban GTFP. The results show that AI significantly improves urban GTFP. A one-standard-deviation increase in AI development is associated with an increase of approximately 0.75 in GTFP, which represents a substantial improvement within the distribution of GTFP. Mechanism analysis indicates that this effect operates primarily through green innovation and industrial upgrading. The positive impact is more pronounced in cities with stronger economic and institutional foundations.
Keywords: artificial intelligence; green total factor productivity; green innovation; industrial upgrading; Chinese cities artificial intelligence; green total factor productivity; green innovation; industrial upgrading; Chinese cities

Share and Cite

MDPI and ACS Style

Wang, X.; Wu, M.; Feng, Y.; Zhao, L. The Impact of Artificial Intelligence on Urban Green Total Factor Productivity—Evidence from Chinese Cities. Sustainability 2026, 18, 5616. https://doi.org/10.3390/su18115616

AMA Style

Wang X, Wu M, Feng Y, Zhao L. The Impact of Artificial Intelligence on Urban Green Total Factor Productivity—Evidence from Chinese Cities. Sustainability. 2026; 18(11):5616. https://doi.org/10.3390/su18115616

Chicago/Turabian Style

Wang, Xupei, Minghuan Wu, Yuan Feng, and Liang Zhao. 2026. "The Impact of Artificial Intelligence on Urban Green Total Factor Productivity—Evidence from Chinese Cities" Sustainability 18, no. 11: 5616. https://doi.org/10.3390/su18115616

APA Style

Wang, X., Wu, M., Feng, Y., & Zhao, L. (2026). The Impact of Artificial Intelligence on Urban Green Total Factor Productivity—Evidence from Chinese Cities. Sustainability, 18(11), 5616. https://doi.org/10.3390/su18115616

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