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Public Attitudes towards Electric Vehicle adoption using Structural Equation Modelling

Lookup NU author(s): Dr Paulus AditjandraORCiD, Dr Dilum Dissanayake



This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).


This paper aims to analyse the public attitudes towards Electric Vehicles (EV) and to explore barriers in adoption of Electric vehicles in UK. The survey data was obtained from UK Data Service regarding public attitudes towards EV which possesses 1800 plus sample population. Previous research regarding recent technological development in EV field, market deployment and penetration studies, and public attitudes in different countries, were used to inform the development of model mechanism on how public adopt EV. We identify the correlation of diverse groups of consumers with various socio-economic and attitudinal barriers encountered in EV adoption. Data was analysed by Structural Equation Modelling (SEM) approach establishing the link between travel behaviour, car ownership and EV adoption level controlled by socio-demographic characteristics. We found that battery (range confidence), recharging infrastructure and technology (unreliability) can be considered as major indicators in influencing EV adoption. We also found that resale value, environmental performance and recharging infrastructure are the major enablers of EV adoption. Perhaps none of these findings are new to many but the implication that this study has brought is the fact that general UK public is far from EV realm and more has to be done before the ban of internal combustion engines taken place in 20 years from now.

Publication metadata

Author(s): Tiwari V, Aditjandra P, Dissanayake D

Publication type: Article

Publication status: Published

Journal: Transportation Research Procedia

Year: 2020

Volume: 48

Pages: 1615-1634

Print publication date: 17/09/2020

Online publication date: 15/09/2020

Acceptance date: 02/09/2020

Date deposited: 24/10/2020

ISSN (electronic): 2352-1465

Publisher: Elsevier BV


DOI: 10.1016/j.trpro.2020.08.203

Notes: World Conference on Transport Research - WCTR 2019


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