Evidence map›Paper›PMID 40794786›Full record

ArticlePloS one2025

Applications of artificial intelligence and urban innovation performance: A quasi-natural experiment based on the pilot zones for the innovative application of artificial intelligence.

Shuang Han, Xianmin Sun, Shen Zhong

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Shuang HanSchool of Economics, Harbin University of Commerce, Harbin, China.
Xianmin SunSchool of Economics, Harbin University of Commerce, Harbin, China.ORCID https://orcid.org/0009-0000-7635-6386
Shen ZhongSchool of Economics, Harbin University of Commerce, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Innovation is the core driving force behind the ability to cope with risks and enhance urban competitiveness. Against the backdrop of frequent global crises and intensified competition, improving urban innovation performance is important. This study uses 283 Chinese cities from 2012 to 2023 to empirically analyze the impact of artificial intelligence (AI) applications on urban innovation performance and the underlying mechanism. The results show that AI significantly promotes urban innovation performance while simultaneously improving both the quality and quantity of urban innovation. Moreover, through testing, it was found that the enhancement of human capital and absorptive capacity has become an important channel through which AI drives urban innovation. Additionally, the degree of government intervention weakens the positive impact of AI applications on urban innovation performance. Further research reveals that the impact of AI applications on urban innovation performance varies according to geographical region, implementation time of policies, and scale of cities.

Indexed as

Artificial IntelligenceInventionsChinaCitiesHumans

Identifiers

PMID40794786
PMCPMC12342255

What OpenQuestion holds

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LicenceCC BY
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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.