A thriving electric vehicles (EVs) market serves as a pivotal embodiment of the global push towards sustainable mobility. As one of the leading global EV sellers, China owns a huge used EV market, which should be spotlighted. While most studies focus on the mechanism of new EV purchases, few put their insight into the trade of used EVs. To fill this gap, this paper aims to clarify the mechanism of consumption behaviour towards used EVs. First, we identified 11 variables that have a direct or indirect impact on consumers’ purchase intention and constructed a conceptual framework. Then, we checked the structural relationships of the model through an empirical study (n = 431). The results showed that purchase intention was determined by two variables: perceived risk and attitude. We also observed an association between income and purchase intention. Functional risk had a direct and significant impact on perceived risk. Economic value, brand trust, and after-sales service were crucial predictors of attitude. Education could moderate the relationship between attitudes and purchase intention. Based on theoretical findings, we present the design strategies to enhance consumers’ purchase willingness from car companies’ and policymakers’ viewpoints. In practical situations, this article offers valuable insights for stakeholders related to the used EV industry, providing a critical reference for advancing sustainable mobility.

The emergence of artificial intelligence (AI)-powered creativity support tools (CSTs) is recently transforming the creative design industry. Yet within the specific industrial design field, such tools are neither widespread nor well-tailored to unique needs of the community. This gap makes the industrial design community’s acceptance of AI-CSTs uncertain. To address the issue, this study explored key factors influencing the acceptance of AI-CSTs by extending the unified theory of acceptance and use of technology (UTAUT) model. The authors used a structural equation modeling approach to carried out an empirical study. Data were collected through a questionnaire survey with 515 industrial design stakeholders in China. The results indicated that technology optimism and personal innovativeness positively affected performance expectancy. Interactivity and facilitating conditions were positive determinants of effort expectancy. The variable “perceived risk” was constructed by three first-order components, namely ethical risk, privacy risk and output risk. Finally, intention to use was significantly affected by performance expectancy, effort expectancy, price value, and perceived risk. Based on the theoretical findings, we presented general AI-CST promotion strategies and specific AI-CST optimization strategies for the industrial design community. This study contributed to a deeper understanding of designers’ behavioral intentions toward AI-CSTs and provides actionable insights for stakeholders to improve system usability, risk control, and technology fit in creative domains.