The Impact of Recommender Type on Tourist Price Sensitivity to Travel Plans

Artificial intelligence (AI) has increasingly replaced humans in providing travel recommendations to tourists. Previous research has predominantly focused on investigating tourists’ willingness to adopt AI. Given the perceived differences in recommendation capabilities between AI and human service providers, tourists may react differently to the prices of AI- and human-recommended travel plans. This study, therefore, examines how tourist price sensitivity to travel plans is influenced by each recommender. The study hypotheses were tested through four experiments. The results show that tourists have lower price sensitivity to travel plans recommended by AI (vs. human). This effect is mediated by tourists’ illusion of understanding, wherein they perceive themselves to be more capable of understanding humans than AI. Furthermore, tourists’ sense of uniqueness of travel needs moderates the effect of recommender type on price sensitivity, whereby the effect diminishes with an increase in tourists’ sense of uniqueness. This study contributes to the reconsideration of tourist responses to AI recommendations from a price sensitivity perspective. By further exploring the shaping mechanism of tourists’ different price sensitivities to AI and human recommendations, we also contribute to the understanding of tourists’ comprehension processes regarding AI.