摘要
Green technology innovation (GTI) in China's waste power battery recycling (WPBR) sector is a key driver for sustainable resource management, environmental protection, and economic prosperity. Using the PSR-BN-GPT-4 model and multi-source data, this study explores China's WPBRenterprises' high-level GTI mechanism. The research concludes that (1) Compared to traditional expert knowledge, the Bayesian network model based on GPT-4 exhibits superior causal reasoning capability. (2) The current level of GTI in China's WPBR industry is relatively low, with the probability of high-level GTI being only 19%. (3) Key factors identified include incentives like R&D investment, bottlenecks such as green finance policy tools, and hindrances like government procurement policy tools. (4) “Supporting Infrastructure Policy Tools - Recycling Outlets Number - Market Potential -Green Technology Innovation” and “Green Finance Policy Tools - R&D Investment - Green Technology Innovation” are two critical paths for enhancing the high-level development of GTI in WPBR enterprises. The study offers valuable insights for governmental, industrial, and corporate decision-making regarding GTI in battery recycling.
| 源语言 | 英语 |
|---|---|
| 文章编号 | 124343 |
| 期刊 | Journal of Environmental Management |
| 卷 | 375 |
| DOI | |
| 出版状态 | 已出版 - 2月 2025 |
| 已对外发布 | 是 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
-
可持续发展目标 9 产业、创新和基础设施
学术指纹
探究 'The secrets to high-level green technology innovation of China's waste power battery recycling enterprises' 的科研主题。它们共同构成独一无二的指纹。引用此
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver