The influence of social norms and word-of-mouth marketing on behavioral intention and behavioral use of generative AI chatbots among university students

The increasing prevalence of artificial intelligence (AI)-driven chatbots, particularly generative AI tools such as ChatGPT and similar large language models, in higher education necessitates a deeper understanding of the factors influencing their adoption and use by university students. This study examines the impact of word-of-mouth (WOM) marketing and social norms on the behavioral intention and effective use of generative AI chatbots among university students in Peru. Using a partial least squares structural equation modeling (PLS-SEM) approach, data from 562 university students were analyzed. The results revealed that both WOM (β = 0.569∗∗∗) and social norms (β = 0.253∗∗) significantly influence the intention to use chatbots, with WOM having a stronger effect. Furthermore, behavioral intention was found to be a significant predictor of actual chatbot use (β = 0.711∗∗∗). The study contributes to existing technology adoption models by incorporating social dimensions specific to the university context. These findings have important implications for chatbot designers, educators, and university administrators in the development of effective strategies for implementing and promoting these technologies in educational settings. The study underscores the need to consider social dynamics and peer networks in chatbot implementation strategies within university environments, potentially improving students' educational experiences and academic outcomes.