Fostering User Attachment to Generative Artificial Intelligence—A Theoretical Perspective Based on Awe and Gamification
Li Zhao, Yun Xu, Sheng-kai Zhou, Wang Ping · International Journal of Human-Computer Interaction · 2025
This study aims to explore the attachment mechanism of users to GAI, investigating the impact of awe and gamification arising from user interactions with GAI on user attachment. Firstly, by analyzing user comment data (174,709) through LDA topic modeling, the study aims to identify GAI features influencing user attachment using real-world data. Subsequently, by combining a survey (N = 782) with the use of PLS-SEM and fsQCA methods, the study reveals that awe and gamification significantly enhance user attachment, with gamification exhibiting stronger effects. Additionally, the functionality and anthropomorphic features of GAI have a significantly positive impact on awe, gamification, and attachment. The study also identifies mediating effects exhibited by awe and gamification. Finally, through fsQCA for configurational analysis, the study discovers that all variables play crucial roles in explaining user attachment. In conclusion, this paper employs a comprehensive approach to investigate the attachment mechanism of users to GAI.