Evidence map›Paper›PMID 40425679›Full record

ArticleScientific reports2025

Empirical evidence and role mechanisms of big data enabling corporate green development.

Yao Wang, Yitao Li, Zhen Ruan, Zihan Tang, Tilei Gao

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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.

Yao WangSchool of Finance, Yunnan University of Finance and Economics, Kunming, 650221, China.
Yitao LiSchool of Finance, Yunnan University of Finance and Economics, Kunming, 650221, China.
Zhen RuanSchool of Finance, Yunnan University of Finance and Economics, Kunming, 650221, China.
Zihan TangSchool of Finance, Yunnan University of Finance and Economics, Kunming, 650221, China. zihan_tang6@163.com.
Tilei GaoSchool of Information, Yunnan University of Finance and Economics, Kunming, 650221, China.

Funding

Foundation of Yunnan University of Finance and Economics No. 2023D07National Natural Science Foundation of China No. 72364035Yunnan Fundamental Research Projects No. 202301AT070421
6 · The paper itself

Abstract

Driven by the growing challenges of global climate change and the urgent need to meet Sustainable Development Goals (SDGs), the green transformation of the economy has become a global consensus, with enterprises playing a crucial role. Using data from China's A-share listed companies between 2010 and 2022, this paper examines the impact of big data advancements on corporate green development through the construction of a quasi-natural experiment. Specifically, the "National Big Data Comprehensive Pilot Zone" is used as a policy intervention to explore the causal effects of big data on corporate green practices. The findings indicate that the implementation of the big data pilot policy has fostered the adoption of more sustainable business practices, particularly in the eastern and central regions, as well as among large-scale enterprises. These positive effects are primarily driven by improved resource allocation and the reduction of agency costs. Based on these findings, the paper proposes a series of policy recommendations aimed at accelerating the green transition of the economy, offering valuable insights for policymakers and researchers.

Indexed as

Agency costBig data comprehensive pilot zoneGreen developmentResource allocation efficiency

Identifiers

PMID40425679
PMCPMC12117066

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.