文献类型：期刊文献

英文题名：Smart Cities with Green Resilience: A Quasi-Natural Experiment Based on Artificial Intelligence

作者：Huo, Da[1];Sun, Tianying[2];Gu, Wenjia[2];Qiao, Li[3]

第一作者：Huo, Da

通讯作者：Gu, WJ[1]

机构：[1]Beijing Foreign Studies Univ, Int Business Sch, Beijing 100089, Peoples R China;[2]Cent Univ Finance & Econ, Sch Int Trade & Econ, Beijing 102206, Peoples R China;[3]Beijing Union Univ, Business Coll, Beijing 100025, Peoples R China

第一机构：Beijing Foreign Studies Univ, Int Business Sch, Beijing 100089, Peoples R China

通讯机构：[1]corresponding author), Cent Univ Finance & Econ, Sch Int Trade & Econ, Beijing 102206, Peoples R China.

年份：2025

卷号：8

期号：2

外文期刊名：SMART CITIES

收录：Scopus(收录号：2-s2.0-105003498099);WOS:【ESCI(收录号:WOS:001475667600001)】；

基金：Beijing Social Science Foundation General project (24JCC093); National Social Science Foundation of China General Project (20BJL055).

语种：英文

外文关键词：smart cities; green resilience; carbon emissions trading; artificial intelligence; spatial effects

摘要：Highlights What are the main findings? The CET policy can reduce the total energy consumption and promote the renewable energy consumption locally, with no significant influence on total energy consumption in surrounding areas. However, it causes a decrease in the renewable energy consumption ratio in neighboring regions. AI significantly reduces energy consumption and promotes renewable energy consumption in surrounding areas. Benefiting from AI-enabled smart city construction, the local region achieves a notable 8.55% reduction in total energy consumption, which exceeds the effect of implementing CET policy alone. What is the implication of the main finding? The CET policy of cities exerts a catalytic effect, increasing energy consumption and carbon emission costs in local regions, promoting energy structure transformation, while avoiding the relocation of high-energy-consuming enterprises to surrounding areas. However, due to the "siphoning effect", the policy absorbs renewable resources from neighboring regions, necessitating enhanced coordination with adjacent areas. AI can break down regional barriers through spatial effects, fostering cross-regional spillovers of green concepts and the application of green technological innovations, thereby counterbalancing the "siphoning effect" and facilitating the formation of a green smart city cluster. Smart city development enables the compatibility of "green resilience" and "smart functionality".Highlights What are the main findings? The CET policy can reduce the total energy consumption and promote the renewable energy consumption locally, with no significant influence on total energy consumption in surrounding areas. However, it causes a decrease in the renewable energy consumption ratio in neighboring regions. AI significantly reduces energy consumption and promotes renewable energy consumption in surrounding areas. Benefiting from AI-enabled smart city construction, the local region achieves a notable 8.55% reduction in total energy consumption, which exceeds the effect of implementing CET policy alone. What is the implication of the main finding? The CET policy of cities exerts a catalytic effect, increasing energy consumption and carbon emission costs in local regions, promoting energy structure transformation, while avoiding the relocation of high-energy-consuming enterprises to surrounding areas. However, due to the "siphoning effect", the policy absorbs renewable resources from neighboring regions, necessitating enhanced coordination with adjacent areas. AI can break down regional barriers through spatial effects, fostering cross-regional spillovers of green concepts and the application of green technological innovations, thereby counterbalancing the "siphoning effect" and facilitating the formation of a green smart city cluster. Smart city development enables the compatibility of "green resilience" and "smart functionality".Abstract Amidst climate change and the energy crisis worldwide, the synergy between smart city and environmental policies has become a key path to improving the green resilience of cities. This study examines the spatial effects of carbon emission trading (CET) policy on urban energy performance under the context of artificial intelligence (AI)-empowered smart cities. Using the spatial Durbin model (SDM) and analyzing data from 262 Chinese cities covering the period 2013-2021, the results reveal that: (1) smart cities significantly benefit from the institutional support of the local CET policy, resulting in an 8. 55% reduction in energy consumption in the pilot city; (2) AI advancement contributes directly to reducing energy consumption in surrounding areas by 21.84% through spatial effects, and compensates for the imbalance of regional renewable energy caused by the "siphon effect" of CET policy. This study provides empirical evidence for developing countries to build green and resilient cities. This paper proposes the need to build a national CET market, strengthen government supervision, and make reasonable use of AI technology, transforming the green and resilient model of smart cities from Chinese experience to global practice.