Evidence map›Paper›PMID 41674532›Full record

ArticleFrontiers in public health2026

Leveraging artificial intelligence policy for inclusive and sustainable youth entrepreneurship: micro evidence from China.

Lili Wang

Abstract read
In one paragraph

Article in Frontiers in public health, 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

1 author.

Lili WangDepartment of Management Science and Engineering, Northeast Petroleum University, Daqing, Heilongjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) policy is increasingly used to align digital transformation with the Sustainable Development Goals by fostering decent work, innovation, and reduced inequality. Youth entrepreneurship is a key channel through which these objectives materialize, yet the micro level pathways linking AI policy to entrepreneurial entry among young adults remain under specified. Using five waves of China Family Panel Studies microdata from 2014 to 2022 and the staggered introduction of AI pilot cities, I estimate a two way fixed effects difference in differences model with rich individual, household, and regional controls. AI pilot status increases the probability of youth entrepreneurship, with baseline effects statistically significant at conventional levels and robust to event study tests of parallel trends, placebo reallocations, alternative time trend controls, and trimming of extreme values. Mechanism analyses show that AI policy operates by reducing relational spending and relaxing credit constraints, as verified by structural equation modeling and multiple mediation tests. Effects are stronger among healthier respondents, those with internet access, and rural residents. This study contributes to the international literature by providing micro-evidence from an emerging economy on how place-based AI policies can function as environmental equalizers. The findings suggest that the observed surge in youth entrepreneurship is structurally motivated by the substitution of digital rules for informal Guanxi and the replacement of physical collateral with digital credit scoring, offering scalable lessons for designing inclusive innovation policies.

Indexed as

Artificial IntelligenceEntrepreneurshipSustainable DevelopmentAdolescentChinaFemaleHumansartificial intelligence policyentrepreneurial environmentrelational spendingsustainable developmentyouth entrepreneurship

Identifiers

PMID41674532
PMCPMC12886425

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.