A Study on the Threshold of Organizational Complexity for Artificial Intelligence-Enabling Green Transformation in heavily Polluted Manufacturing Industries Under the TOE Framework
- DOI
- 10.2991/978-94-6239-787-3_22How to use a DOI?
- Keywords
- Artificial Intelligence; Green Transformation; Heavy-Polluting Manufacturing Industries; Threshold Effect
- Abstract
As the core driving force behind industrial transformation, artificial intelligence serves as a critical pillar for advancing the green and intelligent development of heavily polluting manufacturing sectors. Based on data from A-share heavily polluting manufacturing firms over the period 2009–2024, this paper examines the mechanism through which artificial intelligence affects the green transformation of heavily polluting manufacturing industries. The study finds that AI can promote green transformation by optimizing the labor force structure and attracting patient capital. Moreover, once organizational complexity reaches a certain threshold, this effect can be effectively unleashed. This study provides policy implications for promoting the differentiated advancement of intelligent and green development in the manufacturing industry.
- 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 - Yuanhao Shi PY - 2026 DA - 2026/09/29 TI - A Study on the Threshold of Organizational Complexity for Artificial Intelligence-Enabling Green Transformation in heavily Polluted Manufacturing Industries Under the TOE Framework BT - Proceedings of the 2026 4th International Conference on Management Innovation and Economy Development (MIED 2026) PB - Atlantis Press SP - 194 EP - 206 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6239-787-3_22 DO - 10.2991/978-94-6239-787-3_22 ID - Shi2026 ER -