Image Co-Creation from Fun to Fee: An Empirical Research on Chinese User Interaction Mechanisms and Willingness to Pay for Generative AI Tools
Junping Xu, Zhizhong Fan, Tao Yu, Qianghong Huang, Shan Jiang · International Journal of Human-Computer Interaction · 2026
The rapid advancement of generative AI is reshaping the digital creative industry. This study integrates user experience and flow theories to investigate consumers' willingness to pay (WTP) for AI art design tools (AIADT) through a survey of 309 Chinese users and PLS-SEM analysis. The results show that 14 out of 19 hypotheses were supported. Specifically, content experience, functionality experience, interactive experience, and emotional experience significantly enhance concentrated attention and perceived enjoyment. While perceived enjoyment directly drives satisfaction and WTP, concentrated attention only improves satisfaction without directly influencing WTP. Notably, technology discomfort and insecurity significantly inhibit WTP. These findings extend theoretical applications of user experience in the digital economy and reveal the dynamics of AI commercialization. In practice, developers should optimize modularity to lower technical barriers and enhance market competitiveness, supporting sustainable growth and business model innovation within the green digital economy.