Understanding Customer Satisfaction in Korean Fine Dining Abroad: Insights from Online Reviews of Michelin-Starred Restaurants

In the digital era, customers increasingly share dining experiences online, making big data analytics vital for understanding consumer perceptions in global hospitality. This study investigates how international diners perceive K-Food(Korean cuisine) through Michelin-starred Korean restaurants abroad by analyzing large-scale online reviews. A total of 9,535 Google Maps reviews from 17 overseas Michelin-starred Korean restaurants were collected using Outscraper. Qualitative text mining with KH Coder identified high-frequency terms and co-occurrence structures, producing six thematic clusters: Korean Food, Service, Reservation, Reputation, Atmosphere and Experience. Building on these insights, quantitative analyses were conducted in SPSS 29.0. Exploratory factor analysis validated six dimensions of dining perception, Korean Food, Service, Reservation, Reputation, Atmosphere and Experience which together explained 80.27% of total variance (KMO=0.707; Bartlett’s χ²=156,696, p