Refining hospitality in a post-pandemic landscape: Tourist food choices through a latent class nested logit lens

Abstract

In the post-pandemic landscape, scant research has been conducted on the timely, in-depth examination of how food-related attributes affect tourist food choices. To tackle this issue, this study employed a discrete choice experiment and latent class nested logit models for a nuanced exploration of tourist food preferences. This approach captured both tourists’ preference heterogeneity and substitution effects among fast, local, and hometown-style food options. Findings reveal that price, food taste rating, waiting time, service, and environment are key determinants of tourists’ food choices. Our model identified two distinct tourist classes, Local-food-image class and Anti-price-quality class, each displaying unique food preferences and substitution patterns. This research contributes to tourism and hospitality literature by offering an updated and nuanced understanding of post-pandemic tourists’ food preferences and decision-making trade-offs. It offers practical recommendations for targeted marketing and effective resource allocation, ultimately strengthening resilience and fostering sustainable development within hospitality, catering, and tourism sectors.