AI 기반 자산 가치평가 서비스 특성이 수용의도에 미치는 영향: 성과기대의 매개효과

This study examines the effects of key service characteristics—accuracy, expertise, reliability, and compatibility—of AI-based asset valuation services on users’ intention to adopt such services. A total of 357 valid responses were collected from adults in the Seoul metropolitan area with prior experience using AI-based property valuation platforms. The results demonstrate that all four service characteristics have significant positive effects on performance expectancy and adoption intention. Moreover, performance expectancy plays a significant mediating role in the relationship between service characteristics and adoption intention. Among the four characteristics, compatibility showed the strongest influence on both performance expectancy and adoption intention, highlighting the importance of contextual integration and policy alignment in AI-powered proptech services. This study empirically examines the causal structure among technological characteristics, performance expectancy, and adoption intention, thereby providing a framework to systematically understand the complex factors influencing technology acceptance. In particular, by going beyond a mere technology-function-centered approach and incorporating contextual factors such as users’ psychological expectations and institutional acceptance, this study offers significant implications for both the theoretical development of technology acceptance research and its practical applications.