Evidence map›Paper›PMID 36011442›Full record

ArticleInternational journal of environmental research and public health2022

Can Digital Economy Promote Energy Conservation and Emission Reduction in Heavily Polluting Enterprises? Empirical Evidence from China.

Rongwu Zhang, Wenqiang Fu, Yingxu Kuang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Digitalization, Electricity Consumption and Carbon Emissions-Evidence from Manufacturing Industries in China.International journal of environmental research and public health · 2023
    Article
  3. Moving towards Environmental Sustainability: Can Digital Economy Reduce Environmental Degradation in China?International journal of environmental research and public health · 2022
    Article
  4. 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.

Rongwu ZhangSchool of Management, Guangzhou University, Guangzhou 510006, China.
Wenqiang FuSchool of Management, Guangzhou University, Guangzhou 510006, China.ORCID 0000-0002-4535-1774
Yingxu KuangCollege of Business, University of Houston-Victoria, Victoria, TX 77901, USA.ORCID 0000-0001-7238-2376

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper examines the impact of digital economy on corporate energy conservation and emission reduction (CECER) using China's A-share listed heavily polluting enterprises from 2012 to 2019 as a sample. Our results show that: (1) Digital economy can significantly increase CECER, and this effect is significant for mining and manufacturing enterprises, and less significant for power, heat production and supply enterprises; (2) Mechanism research shows that digital economy promotes CECER through enhancing the green technology innovation capability, easing the financing constraints, and boosting market competition; (3) Heterogeneity research indicates that the promotion of digital economy to CECER is more significant in economically developed regions and regions with less financial pressure from local governments. This paper clarifies the factors influencing CECER and provides empirical evidence for achieving digital economy development and government goals for CECER.

Indexed as

Economic DevelopmentInventionsChinaCommerceOrganizationscorporate energy conservation and emission reductiondigital economygreen innovationheavily polluting enterprises

Identifiers

PMID36011442
PMCPMC9408474

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.