AI and Green Efficiency in Technological Innovation: A Two-Stage Analysis of Chinese Rare Earth Enterprises

As a scarce strategic resource, the efficient utilization of rare earth resources is crucial for ensuring national economic security and promoting sustainable development. AI, the core engine of the Fourth Technological Revolution, provides a favorable opportunity to drive green technological innovation. Green efficiency in technological innovation has not been adequately studied, and the relationship between green efficiency in the rare earth era and AI is still unclear. Based on the above research gap, this study employs the slack-based measure model to perform both static and dynamic evaluations of green efficiency in technological innovation during the technology development and transformation phases of eight listed Chinese rare earth enterprises from 2017 to 2021. This study aims to provide a policy basis for improving the green efficiency of the rare earth industry and the application of AI in the industrial chain. The findings reveal the following: (1) the green efficiency of technological innovation among these rare earth listed enterprises remains low in both phases, with low pure technical efficiency being a key factor contributing to the overall low green technology innovation efficiency; (2) total factor productivity in the technology development phase exhibits a fluctuating upward trajectory while demonstrating a general downward trend in the achievement transformation phase; and (3) the application of AI significantly enhances the green efficiency of technological innovation during the transformation phase, with a more pronounced impact compared to the technology development phase. This study contributes to the existing literature by extending previous research on AI and green efficiency, particularly within the context of the rare earth industry. The empirical results offer valuable policy recommendations for improving the utilization of rare earth resources and enhancing green technological innovation through AI integration.

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Publication Details

Journal
Systems
Published
2025-03-04
DOI
https://doi.org/10.3390/systems13030176
Citations
4
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
12.52

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article

AI and Green Efficiency in Technological Innovation: A Two-Stage Analysis of Chinese Rare Earth Enterprises

Xiaoli Xu, Xiaofeng Xu, Y.Q. Shi
4 citations
Systems
Energy, Environment, Economic Growth
12.52
article

AI and Green Efficiency in Technological Innovation: A Two-Stage Analysis of Chinese Rare Earth Enterprises

Xiaoli Xu, Xiaofeng Xu, Y.Q. Shi
article en
4 citations

Abstract

As a scarce strategic resource, the efficient utilization of rare earth resources is crucial for ensuring national economic security and promoting sustainable development. AI, the core engine of the Fourth Technological Revolution, provides a favorable opportunity to drive green technological innovation. Green efficiency in technological innovation has not been adequately studied, and the relationship between green efficiency in the rare earth era and AI is still unclear. Based on the above research gap, this study employs the slack-based measure model to perform both static and dynamic evaluations of green efficiency in technological innovation during the technology development and transformation phases of eight listed Chinese rare earth enterprises from 2017 to 2021. This study aims to provide a policy basis for improving the green efficiency of the rare earth industry and the application of AI in the industrial chain. The findings reveal the following: (1) the green efficiency of technological innovation among these rare earth listed enterprises remains low in both phases, with low pure technical efficiency being a key factor contributing to the overall low green technology innovation efficiency; (2) total factor productivity in the technology development phase exhibits a fluctuating upward trajectory while demonstrating a general downward trend in the achievement transformation phase; and (3) the application of AI significantly enhances the green efficiency of technological innovation during the transformation phase, with a more pronounced impact compared to the technology development phase. This study contributes to the existing literature by extending previous research on AI and green efficiency, particularly within the context of the rare earth industry. The empirical results offer valuable policy recommendations for improving the utilization of rare earth resources and enhancing green technological innovation through AI integration.

SystemsVol. 13(3)
City University of Hong Kong (HK), China University of Petroleum, East China (CN), East China University of Political Science and Law (CN)
National Natural Science Foundation of China, National Office for Philosophy and Social Sciences
Industry, innovation and infrastructure
Openalex Percentile: Top 2%
Energy, Environment, Economic Growth
12.52
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