Evidence map›Paper›PMID 42106461›Full record

ArticleScientific reports2026

The impact of the Big Data Pilot Policy on urban green energy efficiency.

Shixin Wang

Abstract read
In one paragraph

Article in Scientific reports, 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.

Shixin WangChongqing Industry Polytechnic University, Chongqing, 401120, China. 15178735343@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Promoting urban green transformation has become a key pathway to achieving sustainable development. As an essential component of the modern economy, data factors demonstrate significant potential in enhancing the efficiency of energy systems and facilitating green transformation. Based on panel data from 273 prefecture-level cities in China over the period 2010-2023, this study employs a difference-in-differences (DID) model to assess the impact and underlying mechanisms of the Big Data Pilot Policy (TECH) on green energy efficiency (GEEF). The findings are as follows: First, China's GEEF exhibits an overall upward trend and displays a spatial pattern of "higher in the east and lower in the west." Second, TECH significantly improves GEEF, with green innovation (GREEN) and financial development (FINA) playing positive moderating roles. Third, the policy effect of TECH is significant in eastern regions but not in western regions. Finally, TECH exerts cross-regional spillover effects on GEEF. This study expands the theoretical perspective on urban green energy efficiency and provides empirical evidence and policy implications for the deep integration of digital development and green transition, as well as the realization of coordinated regional development.

Indexed as

Big Data Pilot PolicyData factorsGreen energy efficiencySustainable development

Identifiers

PMID42106461
PMCPMC13346912

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.