Examining factors influencing university students’ adoption of generative artificial intelligence: a cross-country study
基于UTAUT2模型和个人因素，调查马来西亚和中国大学生采用生成式人工智能的影响因素，发现两国影响因素存在显著差异，为高校制定针对性策略提供参考。
The introduction of Generative Artificial Intelligence (GenAI) has transformed the way university students learn. To understand the factors that affect the adoption of GenAI among university students, we proposed a comprehensive research model based on the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2), along with personal factors customized for GenAI. We conducted a cross-sectional survey to collect data from university students in Malaysia and China through an online questionnaire, yielding a total of 500 valid responses. The data were analyzed using the Partial Least Squares method to assess the influence of various factors on GenAI adoption. Our findings reveal notable differences in the factors affecting GenAI adoption between the two countries, with the Malaysian group showing a more diverse range of influencing factors compared to the Chinese group. This study highlights the importance of considering country-specific differences when devising strategies for the adoption of GenAI. By integrating UTAUT2 with personal factors and conducting a cross-country comparative analysis, this study offers significant insights into how factors influencing GenAI adoption vary between countries. These insights can be valuable for university stakeholders.