AI–Driven Green Transformation of Manufacturing Enterprises: A Green Total Factor Productivity Perspective
- DOI
- 10.2991/978-94-6239-787-3_78How to use a DOI?
- Keywords
- AI; green transformation of manufacturing enterprises; green total factor productivity
- Abstract
Under China’s “dual carbon” goals, AI has become an important driver of manufacturing firms’ green transformation. Based on Chinese A-share listed manufacturing firms from 2012 to 2023, this study employs a two-way fixed-effects model and a mediation model to examine the effect and mechanisms of AI on green transformation. The results show that AI significantly promotes manufacturing firms’ green transformation, and this conclusion remains robust after a series of tests. Mechanism analysis reveals that AI facilitates green transformation by promoting green technological innovation and alleviating financing constraints. Heterogeneity analysis further shows that this green enabling effect is more pronounced in heavily polluting, capital-intensive, and highly competitive industries. These findings provide theoretical support for “AI + green manufacturing” and offer policy implications for strengthening green technology guidance, improving the green financial system, and promoting high-quality and sustainable manufacturing development.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Simin Guo PY - 2026 DA - 2026/09/29 TI - AI–Driven Green Transformation of Manufacturing Enterprises: A Green Total Factor Productivity Perspective BT - Proceedings of the 2026 4th International Conference on Management Innovation and Economy Development (MIED 2026) PB - Atlantis Press SP - 803 EP - 813 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6239-787-3_78 DO - 10.2991/978-94-6239-787-3_78 ID - Guo2026 ER -