The emotional algorithm: nostalgia, artificial intelligence and buying intentions

Purpose Technological advancements, particularly in artificial intelligence (AI), are reshaping consumer experiences in the hospitality industry. This study aims to investigate how nostalgic triggers, both nostalgia proneness and nostalgic cues, influence hotel guests’ emotional responses, brand attachment and ultimately, purchase intentions. Grounded in attachment theory, the research further explores the moderating role of AI-driven recommendations in enhancing or weakening these psychological connections. Design/methodology/approach A quantitative research design was adopted, with data collected from 406 hotel guests. Structural equation modeling (SEM) using SmartPLS 4.1 was used to analyze direct, indirect and moderating effects among the study variables. Findings The findings reveal a sequential mediation effect, where nostalgia influences guest purchase intentions through emotional response and brand attachment. While AI-driven recommendations significantly enhance the emotional responses of guests exposed to nostalgic cues, their effect is insignificant for individuals high in nostalgia proneness. Research limitations/implications This study provides both theoretical and practical implications. Theoretically, it extends attachment theory by highlighting the importance of emotional and cognitive mechanisms in understanding technology–emotion dynamics within hospitality marketing. Practically, the findings offer actionable insights for hotel managers and marketers to leverage nostalgic design elements and AI personalization strategically. By tailoring AI-driven recommendations to evoke appropriate emotional responses, hospitality firms can enhance guest engagement, strengthen brand attachment and ultimately increase purchase intentions. Originality/value This study offers a novel contribution by integrating the constructs of nostalgia and AI-driven personalization within the framework of attachment theory, an approach not extensively examined in the hospitality literature. While nostalgia and AI have individually been explored in consumer behavior, their combined effect on emotional responses and purchase intentions, particularly in the hospitality sector, is under-researched. This integration allows for a deeper understanding of how emotional triggers mediated by AI technologies can shape consumer−brand attachment and drive behavior. In practice, the study provides actionable strategies for hotel marketers to craft emotionally engaging, AI-personalized guest experiences that enhance customer loyalty and decision-making.