What Drives AIGC Product Users to Keep Coming Back? Unveiling the Key Factors Behind Continuance Intention
Chuanfeng Sun, Guihuang Jiang, Zhang Jingqiang, Daoyin Sun · International Journal of Human-Computer Interaction · 2025
Artificial Intelligence Generated Content (AIGC) products, driven by disruptive technological integration, have triggered a remarkable surge in usage due to their strong attraction. However, identifying the specific features that distinguish certain AIGC products and consistently attract users amidst a vast array of options remains a critical area for exploration. Based on data from 423 valid samples, we employed PLS techniques to examine the key factors influencing continuance intention. The results indicate that positive expectancy violation serves as a crucial mediator between AIGC product attraction (task, affective, and physical) and continuance intention. All three dimensions of attraction significantly contribute to positive expectancy violation, with task attraction exerting the strongest influence. Furthermore, high personal innovativeness strengthens the positive impact of affective attraction on positive expectancy violation while weakening the effect of task attraction. The findings offer valuable insights for AIGC product design and marketing strategy development.