온라인 쇼핑 피로도가 AI 쇼핑 에이전트의 지각된 유용성과 사용자 만족, 행동의도에 미치는 영향

초록

This study examines the structural relationships among online shopping fatigue, perceived usefulness, user satisfaction, and behavioral intention toward AI shopping agents in the context of digital transformation and information overload. Unlike previous studies that have mainly focused on the technological performance of AI or cognitive acceptance factors, this study empirically examines shopping fatigue as an antecedent variable within the technology acceptance context. Data were collected through an online survey conducted from November 22 to December 21, 2025, targeting consumers in their 20s who had experience using AI-based product recommendation and curation services. A total of 97 valid responses were used in the final analysis. The collected data were analyzed using SPSS Statistics 26.0. Reliability and validity tests, correlation analysis, and regression analysis were conducted. In addition, bootstrapping analysis using PROCESS macro Model 4 was performed to examine the mediating effect of user satisfaction, with 5,000 bootstrap resamples. This study proposes a research model in which shopping fatigue influences perceived usefulness, which in turn affects user satisfaction and behavioral intention. The empirical results indicate that shopping fatigue has a significant positive effect on perceived usefulness, while perceived usefulness positively influences both user satisfaction and behavioral intention. Furthermore, user satisfaction plays a mediating role in the relationship between perceived usefulness and behavioral intention. The findings contribute to the literature by integrating shopping fatigue into the technology acceptance framework and provide practical implications for designing AI shopping agents that effectively reduce consumer fatigue and enhance perceived value.

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