Evidence map›Paper›PMID 39071706›Full record

ArticleHeliyon2024

Mechanism analysis of rural residents' participation in green energy transition: A community-level case study in Nanjing, China.

Ling Li, Jintu Gu, Di Wu, Abdul Rasool Khoso

Abstract read
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. 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.

Ling LiDepartment of Sociology, Hohai University, China.
Jintu GuDepartment of Sociology, Hohai University, China.
Di WuDepartment of Sociology, Hohai University, China.
Abdul Rasool KhosoDepartment of Sociology, Hohai University, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Achieving a transition to green energy requires the government to adopt new policies on green industrial products and energy. Throughout this process, rural residents often face various challenges due to economic and other factors. However, some rural residents are motivated to participate in this transition due to the economic benefits of energy usage and rooftop photovoltaic (PV). This study takes a rural community in the outskirts of Nanjing, China, as an example and applies Granovetter's embeddedness theory and a threshold model to analyze the factors influencing rural residents' engagement in a fair transition to green energy. Research hypotheses are proposed accordingly. The results indicate that rural residents are influenced by multiple factors in the adoption process of rooftop PV projects, primarily encompassing economic and trust-related aspects. From an economic perspective, rural residents evaluate the viability of rooftop PV systems by considering the marketing strategies employed by PV enterprises and the governmental pressure to reduce carbon emissions. They make rational calculations to determine the return on investment, and only when the economic threshold is surpassed will they reach the anticipated level of participation. From the perspective of trust, rural residents' participation in rooftop PV projects is also influenced by trust factors. The level of trust that rural residents have in rooftop PV enterprises, governments, and community organizations plays an important role in their willingness to participate in the green energy transition. Based on these findings, the research paper concludes that local government should continue providing tailored public information and services to facilitate the progress of rooftop PV projects.

Indexed as

China government policiesEmbedding theoryGreen energyRooftop photovoltaicSelf-funded rural residentsThreshold model

Identifiers

PMID39071706
PMCPMC11283147

What OpenQuestion holds

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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.