What drives continuance intention to use electric vehicles: an extension of expectation-confirmation model
Year: 2025
Type: article
Study design: Observational Study
Abstract: In recent years, the electric vehicle (EV) industry has developed rapidly, so it is crucial to examine the factors influencing the continued use of EVs. Despite the growing interest, there remains a gap in understanding how perceived risks, task-technology fit, environmental concern, perceived value, and government support affect the continuation of EV usage. This study addresses this gap by integrating these factors into an extended expectation‒confirmation model (ECM) to explore confirmation, perceived usefulness, satisfaction, and continuance intention to use EVs. Data were collected through a nonprobability sampling design, and responses from 752 participants were analyzed via the partial least squares structural equation modeling (PLS-SEM) technique. On the basis of the TTF and ECM frameworks, the empirical results reveal that (1) several factors, including government support, task-technology fit, satisfaction, environmental concern, and perceived usefulness, significantly impact continuance intention; (2) confirmation, perceived usefulness, satisfaction, and continuance intention explain 8.6%, 12%, 37.5%, and 56.8% of the variance in EVs, respectively; and (3) unexpectedly, government support has a stronger influence on the continuance intention of female users than on that of male users, highlighting its crucial role in their decision to continue using EVs. The research findings offer important theoretical and practical insights into drivers’ continuance intention to use EVs.
Source: Transportation
Authors: Teng Yu, Ai Ping Teoh, Qing Bian, Chengliang Wang
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,990
OpenAlex ID: W4413296828