Evidence map›Paper›PMID 38707362›Full record

ArticleHeliyon2024

Acceptance model of new energy vehicles based on PLS-SEM model.

Jing Liu, Nan Zhang, Yifan Yang

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

3 authors.

Jing LiuEconomics and Management Institute, Xinjiang University, Urumqi, 830046, China.
Nan ZhangEconomics and Management Institute, Xinjiang University, Urumqi, 830046, China.
Yifan YangEconomics and Management Institute, Xinjiang University, Urumqi, 830046, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current energy crisis is worsening worldwide, and in China, urban expansion and per capita vehicle ownership have created a growing energy imbalance and increased pressure to reduce carbon emissions.The popularization of new energy vehicles (NEVs) can provide a step forward to solving energy shortage problems, environmental pollution, and global warming. In 2022, the average penetration rate, which is ratio of new energy vehicle sales to vehicle sales, is just 19.1 %. This paper analysed the reasons for the differences in the penetration rates of new energy vehicles in China's 269 prefecture-level cities, using a Geo Detector approach, and the results showed that the level of economic development, the average annual temperature difference, the density of charging piles, the charging price and the number of population all had significant effects(q>0.12) on the penetration rate. Based on the above studies, a questionnaire was used to investigate the public's acceptance of new energy vehicles in Xinjiang Uygur Autonomous Region, and a PLS-SEM regression analysis was conducted. The results showed that men, young people and people with a certain level of basic education were 5 % more likely to accept new energy vehicles.Unlike previous studies, perceived cost had no significant correlation with the acceptance of new energy vehicles. Perceived risk had a significant negative correlation with the acceptance of new energy vehicles,the path coefficient is -0.1.The acceptance of new energy vehicles was significantly and positively correlated with vehicle quality and service, the public's understanding of new energy vehicles, and subjective norms, their average path coefficients are above 0.1. We argues that the government should maintain a certain level of promotion of new energy vehicles and accelerate the construction of charging piles, based on the aforementioned results.

Indexed as

Geo detectorLow-carbon transportationNew energy vehiclesStructural equation modelTechnology acceptance model

Identifiers

PMID38707362
PMCPMC11068814

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.