The Effects of An Integrated Model of Technology Acceptance Model, Innovation Diffusion Theory, and Innovation Resistance Theory on Intention to Use AI Beauty Services: Focusing on the Moderating Effect of User Experience

This study aimed to examine the structural relationships among key factors influencing the intention to use AI-based beauty services and the moderating effect of user experience by applying an integrated research model that combines the Technology Acceptance Model, Innovation Diffusion Theory, and Innovation Resistance Theory. A survey was conducted with 500 residents of Seoul and metropolitan area, Korea. The results indicate that among innovation characteristics, compatibility and observability positively influence perceived ease of use and perceived usefulness while reducing innovation resistance. In contrast, complexity negatively affects perceived ease of use and increases innovation resistance. Furthermore, perceived ease of use and perceived usefulness have positive effects on intention to use, whereas innovation resistance exerts a negative effect. Moderation analysis reveals that for users without prior experience, perceived ease of use and innovation resistance significantly influence intention to use, while for experienced users, perceived usefulness shows a stronger effect. These findings suggest that as user experience accumulates, consumers place greater emphasis on practical value and utility rather than ease of use in the technology adoption process. This study contributes to the literature by empirically validating an integrated theoretical framework and highlighting the importance of experience-based differentiated strategies for the design and implementation of AI beauty services.