Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 361

The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.

Consumer purchase intention of electric vehicles in China: The roles of perception and personality

He, Xiuhong, Zhan, Wenjie, Hu, Yingying·2018·Journal of Cleaner Production

Abstract

Abstract Electric vehicles (EVs) have been developed rapidly with the strong support of governments in recent years, but the market share of EVs is still small in China and the vast majority of Chinese consumers hesitate to adopt them. Thus, for the successful development of EVs, this paper proposes a personality-perception-intention framework to explore consumers' EV adoption behavior. The research model is empirically tested with data collected from 369 participants in China. Results indicate that the EV purchase intention can be explained 57.1% variance by consumer perception and personality. Two types of personality, such as personal innovativeness and environmental concern, significantly affect EV purchase intention directly. They are also significantly mediated by two kinds of perceptions (i.e. positive and negative utilities). The findings give a deeper understanding of EV adoption behavior, and provide recommendations for policymakers and manufacturers on promoting EVs.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.jclepro.2018.08.260

Cites

68 of 68 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 68 references

Cited by

See all 361

Metadata

Authors
He, X., Zhan, W., & Hu, Y.
Venue
Journal of Cleaner Production
Publisher
Elsevier BV
Published
2018-12
Volume
204
Pages
1060-1069
ISSN
0959-6526 (ISSN-L)
OpenAlex
W2891105042
Cited by
361
References
68
FWCI
6.68
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Consumer purchase intention of electric vehicles in China: The roles of perception and personality. https://app.cochat.ai/papers/10.1016/j.jclepro.2018.08.260
The paper
He, X., Zhan, W., & Hu, Y. (2018). Consumer purchase intention of electric vehicles in China: The roles of perception and personality. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2018.08.260

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.