The University of Southampton
University of Southampton Institutional Repository

Cognitive consistency and preferences for alternative fuel vehicles: a latent class model

Cognitive consistency and preferences for alternative fuel vehicles: a latent class model
Cognitive consistency and preferences for alternative fuel vehicles: a latent class model
Long-term decisions, such as electric vehicle purchases, typically involve assessing complex interactions among several cognitive components. These psychological constructs are often a source of heterogeneity in the preferences for instrumental attributes. In this paper, we analyse vehicle fuel type choices using a latent class-discrete choice model where attitudinal and emotional appraisals of the electric vehicle purchase decision influence both class membership and preferences within each class. The model is estimated using data from a stated choice experiment and an attitudinal questionnaire. Attitudinal and emotional outputs come from the hot coherence (HOTCO) model, where motivation and behavioural response interact with each other to produce a consistent assessment. Our results reveal three distinct user segments in the sample – potential innovators, laggards, and sceptics, with markedly different purchase motives, preference parameters, and decision-making profiles. The HOTCO attributes help identifying the cognitive aspects that shape decision-making which is beneficial for effective policy design.
Cognitive consistency, Electric vehicles, Hot coherence, Hybrid-electric vehicles, Latent class choice models, Stated choice
1361-9209
Domarchi, Cristian
12770dd9-ec99-4d57-acfc-4ca745b63f07
Cherchi, Elisabetta
0bb4e26d-ed34-4fa4-b948-848d7565168f
Vuong, Quoc C.
9c3e8507-5762-4e63-9338-2bc5541cb253
Domarchi, Cristian
12770dd9-ec99-4d57-acfc-4ca745b63f07
Cherchi, Elisabetta
0bb4e26d-ed34-4fa4-b948-848d7565168f
Vuong, Quoc C.
9c3e8507-5762-4e63-9338-2bc5541cb253

Domarchi, Cristian, Cherchi, Elisabetta and Vuong, Quoc C. (2025) Cognitive consistency and preferences for alternative fuel vehicles: a latent class model. Transportation Research Part D: Transport and Environment, 143, [104729]. (doi:10.1016/j.trd.2025.104729).

Record type: Article

Abstract

Long-term decisions, such as electric vehicle purchases, typically involve assessing complex interactions among several cognitive components. These psychological constructs are often a source of heterogeneity in the preferences for instrumental attributes. In this paper, we analyse vehicle fuel type choices using a latent class-discrete choice model where attitudinal and emotional appraisals of the electric vehicle purchase decision influence both class membership and preferences within each class. The model is estimated using data from a stated choice experiment and an attitudinal questionnaire. Attitudinal and emotional outputs come from the hot coherence (HOTCO) model, where motivation and behavioural response interact with each other to produce a consistent assessment. Our results reveal three distinct user segments in the sample – potential innovators, laggards, and sceptics, with markedly different purchase motives, preference parameters, and decision-making profiles. The HOTCO attributes help identifying the cognitive aspects that shape decision-making which is beneficial for effective policy design.

Text
1-s2.0-S1361920925001397-main - Version of Record
Available under License Creative Commons Attribution.
Download (4MB)

More information

Accepted/In Press date: 31 March 2025
e-pub ahead of print date: 11 April 2025
Published date: 11 April 2025
Keywords: Cognitive consistency, Electric vehicles, Hot coherence, Hybrid-electric vehicles, Latent class choice models, Stated choice

Identifiers

Local EPrints ID: 501314
URI: http://eprints.soton.ac.uk/id/eprint/501314
ISSN: 1361-9209
PURE UUID: ee239cf1-64e3-4ef4-bfa3-d6ff80d1fc0a
ORCID for Cristian Domarchi: ORCID iD orcid.org/0000-0002-9068-704X

Catalogue record

Date deposited: 28 May 2025 17:08
Last modified: 22 Aug 2025 02:42

Export record

Altmetrics

Contributors

Author: Cristian Domarchi ORCID iD
Author: Elisabetta Cherchi
Author: Quoc C. Vuong

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×