Abstract: 【Purpose/significance】Generative Artificial Intelligence (GAI) is widely used in academia, and analyzing the factors influ⁃ encing the initial usage behavior (IUB) of GAI university users is of great significance for GAI platform managers to optimize user expe⁃ rience and motivate user usage.【Method/process】The article obtains first-hand information through semi-structured interviews with 20 representative university users. It adopts programmed grounded theory to analyze the interview data in depth, extract 15 indepen⁃ dent categories and five main categories, and use them to construct a model of the factors influencing the IUB of GAI users in colleges and universities.【Result/conclusion】The study shows that: Perceptual factors, including perceived risk and perceived anthropomor⁃ phism, can directly influence the IUB of GAI university users. In addition, platform factors, such as the technical environment and in⁃ teraction design, and contextual factors, such as subjective norms and network environment, can indirectly affect the IUB of GAI uni⁃ versity users through. The mediation of perceptual factors and individual factors, such as personality traits and experiential back⁃ ground, and competence factors, such as digital literacy and usage habits, can modulate the influence of platform and contextual fac⁃ tors on IUB. Finally, based on the above findings, several optimization strategies for GAI are proposed.【Innovation/limitation】The ar⁃ ticle provides an in-depth analysis of the influencing factors and role mechanisms of the IUB of GAI college users at the theoretical level. It proposes detailed strategies for GAI optimization at the practical level. The next step will be to make further improvements in optimizing the research methodology and increasing the diversity of the samples.