Evidence map›Paper›PMID 38658608›Full record

ArticleScientific reports2024

Modelling interest in co-adoption of electric vehicles and solar photovoltaics in Australia to identify tailored policy needs.

Elham Hajhashemi, Patricia Sauri Lavieri, Neema Nassir

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
4.6field-weighted citation impact, top 5% 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

1 citing paper in PubMed, 22 citations in OpenAlex.

  1. Article
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 at 1 institution in 1 country.

Elham HajhashemiDepartment of Infrastructure Engineering, The University of Melbourne, Melbourne, VIC, Australia.
Patricia Sauri LavieriDepartment of Infrastructure Engineering, The University of Melbourne, Melbourne, VIC, Australia. patricia.lavieri@unimelb.edu.au.
Neema NassirDepartment of Infrastructure Engineering, The University of Melbourne, Melbourne, VIC, Australia.
University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electric vehicles (EVs) and solar photovoltaic systems (PVs) are two technologies that are gaining popularity in households as a means of reducing carbon emissions and improving energy security. However, little is known about the characteristics of households that adopt these technologies jointly. This study investigates the adoption patterns of electric vehicles and solar photovoltaics in Australia. We explain the likelihood of consumers belonging to four distinct groups (those who adopt both PVs and EVs, those who only adopt EVs, those who only adopt PVs, and those who adopt none) based on demographic and attitudinal factors. Using survey data from a representative sample of 2219 Australian heads of households, we found that dwelling ownership, ownership of a home energy management system, gender, and household size were significant predictors of the joint adoption of EVs and PVs. While both pro-environmental and pro-technology attitudes demonstrated a significant role in shaping PV-EV co-adoption patterns, the latter has a much stronger effect than the former. Based on the results, we identified that actions are needed in three key areas to encourage co-adoption: reducing technology adoption constraints associated with living arrangements (such as dwelling type and ownership), providing bundled financial incentives for both technologies, and fostering technology awareness and perceived usefulness among consumers.

Identifiers

PMID38658608
PMCPMC11043074
OpenAlexW4395081842

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.