Research identifies how ethical awareness and anxiety impact usage behaviors in college students, suggesting improvements for generative AI acceptance.
This study aims to explore the factors influencing college students' behavioral intentions (BI) and usage behaviors (UB) of using Generative AI products from an ethical perspective. Based on ethical decision-making theory, the research extends the UTAUT2 model and introduces three key variables: ethical awareness (EA), perceived ethical risk (PER), and AI ethical anxiety (AIEA). The data of 253 college students were analyzed through the partial least squares structural equation model (PLS-SEM).The research results verified the effectiveness of the UTAUT2 model and indicated that performance expectation (PE), hedonic motivation (HM), price value (PV), and social impact (SI) have a positive impact on college students' behavioral intentions to use generative artificial intelligence products, while effort expectation (EE) has no significant effect. Furthermore, convenience conditions (FC) and habits (HB) do not directly affect BI, but they play a decisive role in UB.Among the ethics-related factors, AlEA and PER are not the main determinants of BI, but AIEA can directly inhibit UB. Furthermore, although PER does not directly affect UB, it can have a negative impact indirectly through AIEA. Ethical awareness (EA) can positively influence BI, but it will also increase PER. These findings help to encourage college students to better accept and use generative artificial intelligence products in an ethical manner.
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He et al. (2025) studied this question.
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