Evidence map›Paper›PMID 41852734›Full record

ArticleiScience2026

Evaluating the impact of artificial intelligence development on urban resilience: Evidence from Chinese cities.

Xing Zhang, Weida Liang, Xiao Yu, Bingna Xie, Chang Liu

Abstract read
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xing ZhangSchool of Public Administration, Guangdong University of Finance and Economics, Guangzhou 510320, China.
Weida LiangSchool of Public Administration, South China University of Technology, Guangzhou 510641, China.
Xiao YuSchool of Customs and Public Administration, Shanghai Customs College, Shanghai 201204, China.
Bingna XieSchool of Public Administration, Guangdong University of Finance and Economics, Guangzhou 510320, China.
Chang LiuSchool of Public Administration, Guangdong University of Finance and Economics, Guangzhou 510320, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urban management faces unprecedented challenges in addressing uncertainty, maintaining ecological balance, and safeguarding social welfare. Despite artificial intelligence (AI) providing opportunities while also posing risks, empirical evidence of its impact on urban resilience remains limited. Using panel data from 266 prefecture-level cities in China for the period between 2011 and 2022, this study examined the impact of AI development on urban resilience and elucidated the underlying mechanisms based on the technology-organization-environment framework. The key findings are as follows: AI development exerts an inverted U-shaped influence on urban resilience; the partial mediating roles of fiscal decentralization and financial resources are identified; governmental response exhibits a moderating effect on the relationship and moderates the mediating effect of fiscal decentralization; and economic development moderates the effect of AI on urban resilience, operating partially through financial resources. Several policy recommendations are provided to support cities in leveraging AI development to strengthen urban resilience.

Indexed as

environmental policyurban planning

Identifiers

PMID41852734
PMCPMC12992962

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.