모듈러 설계 기반 리조트디자인이 사용자 만족도에 미치는 영향 연구-AI 맞춤 알고리즘 서비스를 중심으로-

(Background and Purpose) The traditional hotel and resort industry has relied on standardized service systems to ensure consistent quality across branches. While this approach guarantees operational efficiency and service reliability, it limits the ability to address diverse individual preferences and experiential expectations. As user-centered design and personalization gain importance, spatial and service strategies capable of flexibly responding to individual users are increasingly required. This study proposes a resort design approach that integrates modular spatial adaptability with AI-based customized algorithmic services. Modular design allows physical reconfiguration, expansion, and functional adjustment of spaces, while AI-driven systems analyze user behavior data to automatically adjust environmental conditions. Through this integration, resort environments may offer more adaptive and personalized experiences. The purpose of this study is to empirically examine how the combination of modular design and AI-based customization influences user satisfaction in resort settings. (Method) A literature review identified the key characteristics of modular design, AI customized algorithmic services, and user satisfaction. Modular design was categorized into variability, expandability, flexibility, and sustainability. AI service factors included convenience, interactivity, data learning, and novelty. User satisfaction was defined through emotional responses, expectation–performance comparison, and perceived value. Based on these constructs, a structured online questionnaire using 5-point Likert-scale items was administered to 80 adults with prior hotel or resort experience. Data were analyzed using SPSS 27, including reliability tests, KMO and Bartlett's validity tests, correlation analysis, and regression analysis. (Results) The findings showed that modular design had a statistically significant positive effect on both AI customized algorithmic services and user satisfaction. This indicates that spatial structure and design characteristics directly influence satisfaction as well as the perceived effectiveness of AI-based services. However, AI customized algorithmic services did not demonstrate a statistically significant direct effect on user satisfaction and did not mediate the relationship between modular design and satisfaction. These results suggest that current AI applications in resort environments primarily function at a practical level focused on convenience rather than emotional or experiential enhancement. (Conclusions) This study confirmed that modular design–based resort design significantly influences user satisfaction and that structural spatial characteristics play an important role in shaping emotional stay experiences. In contrast, AI customized algorithmic services showed no significant direct or mediating effects and remain at a functional level. However, when combined with modular design, AI services have the potential to expand personalized spatial experiences. Accordingly, a second-phase study will conduct in-depth case analyses to examine how the integration of these two elements influences user experience.