我校91吃瓜 张伟老师在T1级别期刊——《 Sustainable Development》上发表题为“Sustainable development pathways: Exploring the impact of green finance on urban metabolic efficiency”。论文作者张伟为91吃瓜 教授、博士生导师。
Abstract / 摘要：
Improving urban metabolic efficiency is crucial for sustainable development. This paper examines how green finance affects urban metabolic efficiency and its underlying mechanisms using city‐level green finance data from China between 2010 and 2022. Additionally, the non‐linear impact of green finance on urban metabolic efficiency is analyzed using a PLFC model. The research findings indicate that green finance notably improves urban metabolic efficiency via its constraint effect, incentive effect, and innovation compensation effect. The conclusion remains valid after conducting robustness tests. The analysis of mechanisms indicates that the incentive effect outweighs the constraint effect. Heterogeneity analyses demonstrate that the impact of green finance on urban metabolic efficiency varies depending on regions, city sizes, and city attributes. Furthermore, further investigation demonstrates that green finance exhibits a non‐linear impact on urban metabolic efficiency, with education level and robotics application serving as significant moderating factors. This paper offers fresh insights into the correlation between green finance and urban metabolic efficiency, along with valuable references and insights for crafting more targeted policies.
论文信息;
Title/题目:
Sustainable development pathways: Exploring the impact of green finance on urban metabolic efficiency
Authors/作者:
Han, Jie; Zhang, Wei; Işık, Cem; Zhao, Wenju; Anas, Muhammad; Zheng, Qinglan; Xie, Danxi; Bakhsh, Satar1
Keyword / 关键词
*Sustainable development; *Robotics; Sustainable urban development; Incentive (Psychology); Heterogeneity
Indexed by / 核心评价
AHCI;EI;SCI;Scopus;WAJCI
DOI：10.1002/sd.3081
全文链接：
//libresource.91chiguaweb.com/next/resource/eds/detail?eid=e46b3496f2baacb9696b9b7824fdc4c42d9a5e1536485219a33531083f4989b25ee6b463d1ae1a97cde73c4a8bacb4b97bba3d6223d9e236dc97d81ce643c3a823b5d720a41820a7df10f16b332d397e