This study, using ChatGPT as a case, based on the Unified Theory of Acceptance and Use of Technology 3 (UTAUT3) model, explores university students’ attitudes, Behavioral Intentions (BI), and influencing factors towards Generative Artificial Intelligence (GenAI). It focuses on two crucial moderating variables: Habit (H) and Personal Innovativeness (PI). The goal is to uncover the mechanisms through which H and PI influence GenAI BI, providing a deeper understanding of GenAI Usage Behavior (UB). This study conducted a comprehensive survey of 510 college students, utilizing SPSS 26.0 and AMOS 24.0 for data analysis. Results reveal significant positive impacts of Performance Expectations (PE), Effort Expectations (EE), Social Influence (SI), and Hedonic Motivation (HM) on students’ BI to use ChatGPT, except for Price Value (PV). Additionally, BI significantly influences actual UB. Moderation analysis shows H negatively moderates the BI-UB relationship, indicating its inhibitory effect, while PI positively moderates this relationship, emphasizing the innovative role in promoting GenAI usage. These findings contribute to a theoretical understanding of GenAI UB and offer practical product design and promotion insights.

The Structure and Evolution of Renewable Energy Trade Networks in the RCEP Region: Application of SNA Method-RCEP, Renewable Energy, Trade Network, Social Network Analysis