Evidence map›Paper›PMID 39652617›Full record

ArticlePloS one2024

The impact of household digital transformation on household energy efficiency: Empirical evidence from Chinese households.

Suxu Lin, Lin He, Xin Lin, Weicheng Li

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. 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

4 authors.

Suxu LinSchool of Management, Guangdong Polytechnic Normal University, Guangzhou, Guangdong, China.
Lin HeSchool of Finance and Economics, Guangdong Polytechnic Normal University, Guangzhou, Guangdong, China.
Xin LinSchool of Finance and Economics, Guangdong Polytechnic Normal University, Guangzhou, Guangdong, China.ORCID 0000-0002-8525-4207
Weicheng LiSchool of Finance and Economics, Guangdong Polytechnic Normal University, Guangzhou, Guangdong, China.ORCID 0000-0003-4430-9192

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carbon emissions from household consumption are an important part of global energy consumption, and household digital transformation is vital for realizing green and low-carbon development. Using data from the 2019 China Household Finance Survey, this study empirically examines the effect of household digital transformation on household energy efficiency. The results show that household digital transformation significantly improves household energy efficiency across all quantiles. This effect varies by consumption type, with the most pronounced improvements in food, housing, and other consumption categories. The impact is stronger for households with elderly members. Per capita household income and education level serve as important mediating and moderating mechanisms, respectively. Unlike previous macro-level studies, this research provides micro-evidence on the impact of household digital transformation on energy efficiency, explores the underlying mechanisms through income and education effects, and examines heterogeneous impacts across different consumption types and household characteristics. These findings offer important policy implications for leveraging digital transformation to enhance household energy efficiency and promote sustainable development.

Indexed as

Family CharacteristicsAdultChinaEast Asian PeopleFemaleHousingHumansIncomeMale

Identifiers

PMID39652617
PMCPMC11627378

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.