Modeling consumer acceptance of new energy vehicles in Guangdong Province, China: An empirical study

This study examines the behavioral intention to adopt new energy vehicles (NEVs) in China through an integrated framework that combines the technology acceptance model, the theory of planned behavior, and contextual policy support. Drawing on survey data from 983 respondents across 21 cities spanning Tiers 1–4, we employ structural equation modeling, multi-group regression with multiple-testing correction, and fuzzy-set qualitative comparative analysis. Measurement invariance is established across gender, age, and city tiers. Results demonstrate that policy support, perceived usefulness, and trust are the most influential determinants of NEV adoption, while environmental concern exerts a positive but context-specific effect. Multi-group analysis reveals that functional and environmental values are more salient in higher-tier cities, whereas economic incentives and infrastructure play stronger roles in lower-tier contexts. Fuzzy-set qualitative comparative analysis further identifies multiple sufficient pathways to high adoption intention (consistency = 0.86; coverage = 0.72), corroborating the robustness of parametric results. The findings contribute methodologically by advancing theory-driven benchmarking and substantively by highlighting differentiated policy levers across urban tiers in a rapidly evolving market.