Modeling User Intentions for Electric Vehicle Adoption in Thailand: Incorporating Multilayer Preference Heterogeneity

Abstract

Background: The automotive industry is pivotal in advancing sustainability, with electric vehicles (EVs) essential for reducing emissions and promoting cleaner transport. This study examines the determinants of EV adoption intentions in Thailand, integrating demographic and psychographic factors from Environmental psychology and innovation diffusion theory; Methods: Data from a structured questionnaire, administered to 4003 respondents at gas stations with EV charging facilities across Thailand, were analyzed using a Correlated Mixed-Ordered Probit Model with Heterogeneity in Means (CMOPMHM); Results: Findings indicate that younger adults, particularly those aged 25–34 years old and 45–54 years old, are more likely to adopt EVs, whereas conventional or hybrid vehicle owners are less inclined. Rural residency or travel also hinders adoption. Individuals with strong environmental values and openness to new technologies are more likely to adopt EVs; Conclusions: The proposed model quantified the relative importance of these factors and uncovered heterogeneity in user preferences, offering reliable and valuable insights for policymakers, EV manufacturers, and researchers. The study suggests targeted policies and enhanced charging infrastructure, especially in rural areas, and recommends leveraging environmental values and trialability through communication campaigns and test drive events. These insights can guide the development of targeted incentives, infrastructure expansion, communication strategies, and trialability programs to effectively promote wider EV adoption in Thailand and similar markets.

Keywords

• environmental psychology
• innovation diffusion theory
• mixed-ordered probit model
• random parameter
• heterogeneity in means