Evidence map›Paper›PMID 39104472›Full record

ArticleHeliyon2024

The nexus of poverty energy in China's industrial productive efficiency and energy transition in digital economy.

Guozhi Li, Mengying Jiang, Yidan Yuan, Xunuo Chen, Dandan Fu

RetractedAbstract readRetracted Publication
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. 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

5 · Who and what money

Authors and funding

5 authors.

Guozhi LiSchool of Business, Wenzhou University, Wenzhou 325035, China.
Mengying JiangSchool of Business, Wenzhou University, Wenzhou 325035, China.
Yidan YuanSchool of Business, Wenzhou University, Wenzhou 325035, China.
Xunuo ChenSchool of Business, Wenzhou University, Wenzhou 325035, China.
Dandan FuSchool of Business, Wenzhou University, Wenzhou 325035, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research explores the relationship between energy poverty, industrial efficiency, and the energy transition within China's digital economy from 2010 to 2022, spanning 30 provinces. Addressing the significant issue of energy poverty, where many lack access to affordable and reliable energy, the study seeks to understand its impact on industrial productivity and the broader imperative of energy transition in the face of rapid digitalization in China. Using panel data analysis, the research examines how energy poverty affects industrial production efficiency and evaluates its influence on China's ability to shift to cleaner energy sources within the digital economic framework. Findings highlight a complex interplay between energy poverty, industrial efficiency, and energy transition. It is revealed that energy poverty significantly impedes industrial productivity, with notable differences across provinces. Furthermore, the study finds a positive link between industrial efficiency and the speed of energy transition, indicating that enhancing industrial efficiency can aid in a smoother shift to cleaner energy sources. The digital economy is identified as a crucial factor in this process, providing innovative solutions to reduce energy poverty, improve productive efficiency, and accelerate the energy transition. The study emphasizes the importance of integrated strategies to tackle energy poverty, enhance industrial efficiency, and support the energy transition, particularly through the utilization of digital economy tools.

Indexed as

Cleaner energy sourcesDigitilizationEnergy transitionProductive efficiency

Identifiers

PMID39104472
PMCPMC11298877

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.