Evidence map›Paper›PMID 36862739›Full record

ArticlePloS one2023

A moderated mediation model to predict the adoption intention of renewable wind energy in developing countries.

Sohaib Mustafa, Wen Zhang, Muhammad Tayyab Sohail, Sehrish Rana, Ying Long

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. 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
17.4field-weighted citation impact, top 1% of its field
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, 30 citations in OpenAlex.

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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 at 3 institutions in 2 countries.

Sohaib MustafaCollege of Economics and Management, Beijing University of Technology, Beijing, PR. China.
Wen ZhangCollege of Economics and Management, Beijing University of Technology, Beijing, PR. China.
Muhammad Tayyab SohailSchool of Public Administration, Xiangtan University, Xiangtan, PR. China.
Sehrish RanaGovernment Islamia Graduate College for Women, Faisalabad, Pakistan.ORCID 0000-0001-7826-6130
Ying LongBeijing University of Technology, Beijing, PR. China.
Beijing University of Technology · CNGovernment College Women University Faisalabad · PKXiangtan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developing countries are deprived of resources, and their economies are dwindling. Energy shortfall is one of the leading issues in developing countries that not only shatter economies but is the leading cause of depletion of natural resources and environmental pollution. There is an urgent need to shift to renewable energy sources to save economies and natural resources and to save our ecological system. Aiming for this, we have collected a cross-sectional data set to study the household intentions of shifting to wind energy and analysed the moderated mediation interactions of the variable to better understand socio-economic and personal factors. 840 responses were analysed using smart-PLS 4.0; results revealed that cost value and social influence directly relate to renewable energy adoption. Environmental knowledge directly influences attitude towards the environment, and health consciousness influences perceived behavioural control. Results also revealed that social influence strengthens the indirect relationship between awareness of renewable energy and its adoption, while it weakens the indirect relationship between health consciousness and renewable energy adoption.

Indexed as

IntentionWindCross-Sectional StudiesDeveloping CountriesRenewable Energy

Identifiers

PMID36862739
PMCPMC9980790
OpenAlexW4322757314

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.