Evidence map›Paper›PMID 42558491›Full record

ArticleFrontiers in artificial intelligence2026

Enterprise AI applications and stock price crash risk.

Zhao Yang

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 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.

Zhao YangJining University, Jining, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With Chinese A-share listed enterprises (2015-2024), this paper studies the influence of artificial intelligence applications on stock price crash risk. Our conclusion includes that AI applications significantly reduce the crash risk. The mechanism analysis reveals that artificial intelligence works by improving internal controls quality (ICQ) and decision-making efficiency (DME). Heterogeneity tests show the effect is stronger for enterprises with digital expertise among CEO and located in eastern China. This paper provides a theoretical basis for enterprises to optimize their development strategies and prevent capital market risk.

Indexed as

artificial intelligenceCEO’S digital expertisedual-channel mechanismfinancial market stabilitystock price crash risk

Identifiers

PMID42558491
PMCPMC13437685

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.