<![CDATA[Academic writing habits in higher education have changed due to the increasing use of generative artificial intelligence (AI), particularly among students in the English as a Foreign Language (EFL) context. However, little is known about the variables that influence students’ intention to use generative AI in academic writing. This study uses the modified Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, where price value is replaced by learning value to examine the factors that influence EFL graduate students’ behavioral intentions to use generative AI. An online questionnaire was used to gather data from 115 EFL graduate students using a quantitative explanatory approach. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze the data. The results show that while performance expectancy, effort expectancy, hedonic motivation, learning value, and facilitating conditions were found to be insignificant, habit and social influence had significant effect on behavioral intention. The biggest predictor was habit, suggesting that generative AI use has become commonplace and habitual. The findings suggest that students may prioritize efficiency and task completion over perceived learning benefits when using generative AI for academic writing. Additionally, this study shows that the use of generative AI in academic writing is becoming more-behavior-driven and socially influenced rather than cognitively driven.]]>
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