School of Statistics, Dongbei University of Finance and Economics, Dalian, 116025, China.
School of Statistics, Dongbei University of Finance and Economics, Dalian, 116025, China.
J Environ Manage. 2024 Nov;370:122458. doi: 10.1016/j.jenvman.2024.122458. Epub 2024 Sep 12.
Artificial intelligence (AI) technology serves as a powerful tool to optimize energy efficiency and lessen ecological footprints. Using data from 30 provinces in China over the period from 2018 to 2022, this study investigates how regional AI development affects the per capita ecological footprint and explores the underlying mechanisms. The results show that: (1) Regional AI development can significantly decrease the ecological footprint, and this conclusion remains robust after a series of robustness checks. (2) Mediation effect analysis indicates that AI technology mainly decreases the ecological footprint by improving energy utilization efficiency. (3) The panel threshold model results show that AI's influence on the ecological footprint has a single energy efficiency threshold. Only when regional energy efficiency exceeds a certain threshold can AI fully exert its suppressive effect on the ecological footprint. (4) Regional heterogeneity analysis shows that the reduction effect of AI on the ecological footprint is more pronounced in the central and eastern regions of China. This paper helps clarify the specific impact of AI technology development on the ecological footprint and provides scientific evidence for regional technology development, energy efficiency improvement, and ecological environment policy formulation.
人工智能(AI)技术是优化能源效率和减少生态足迹的有力工具。本研究利用 2018 年至 2022 年中国 30 个省份的数据,探讨了区域 AI 发展如何影响人均生态足迹,并探讨了其潜在机制。结果表明:(1)区域 AI 发展可以显著降低生态足迹,且在经过一系列稳健性检验后,该结论仍然成立;(2)中介效应分析表明,AI 技术主要通过提高能源利用效率来降低生态足迹;(3)面板门槛模型结果表明,AI 对生态足迹的影响存在单一的能源效率门槛。只有当区域能源效率超过一定门槛时,AI 才能充分发挥其对生态足迹的抑制作用;(4)区域异质性分析表明,AI 对生态足迹的降低效应在中国中东部地区更为明显。本文有助于阐明 AI 技术发展对生态足迹的具体影响,为区域技术发展、能源效率提高和生态环境政策制定提供了科学依据。