Evidence map›Paper›PMID 38507430›Full record

ArticlePloS one2024

Enterprise digital transformation's impact on stock liquidity: A corporate governance perspective.

Hui Liu, Jia Zhu, Huijie Cheng

Abstract read
In one paragraph

Article in PloS one, 2024. 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.

Hui LiuSchool of Business, Zhengzhou University of Aeronautics, Zhengzhou, Henan, China.
Jia ZhuSchool of Business, Zhengzhou University of Aeronautics, Zhengzhou, Henan, China.ORCID https://orcid.org/0009-0001-5387-3249
Huijie ChengSchool of Business, Zhengzhou University of Aeronautics, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The innovation in technology and economic growth, which are brought about by digital transformation in enterprises, will inevitably impact their performance in the capital market. Using a sample of Chinese A-share listed companies from 2012 to 2021, this study extensively examines the impact, mechanism, and economic consequences of enterprises digital transformation on stock liquidity. The research reveals that enterprises digital transformation can significantly improve stock liquidity. From the perspective of corporate governance, a further analysis indicates that the digital transformation of enterprises can improve stock liquidity by three mechanisms: easing financing constraints, improving the quality of internal control, and enhancing information disclosure. The results of the heterogeneity analysis indicate that the digital transformation of enterprises, combined with a high level of financial technology, developed financial markets, and policy guidance, has a significantly more significant effect on improving stock liquidity. The analysis of economic consequences reveals that the digital transformation of enterprises can lower the risk of a stock price crash and enhance the accuracy of analysts' forecasts, primarily by improving stock liquidity. This study offers empirical evidence from a micro-mechanism perspective that elucidates the spillover effect of enterprise digital transformation on the capital market. It provides insight into the impact of enterprise digital transformation on stock liquidity and offers theoretical guidance to promote the adoption of enterprise digital transformation across different countries and enhance stock liquidity in the capital market.

Identifiers

PMID38507430
PMCPMC10954117

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.