The aim of this paper is to understand consumers' perception of luxury hotel brands. To this end, the research evaluates consumers' "big" visual data on TripAdvisor through a machine learning approach. Results shed light on the significant part of non-textual elements of the hotel experience such as pictures, which cannot be explored through traditional methods as content analysis. In particular, the analysis of 7,395 consumers' pictures leads to the identification of the attributes that had the higher impact on their experience. These attributes emerged as specific features of interior elements of the hotels (rooms and restaurant).Finally, the study shows how big data analytics and machine learning algorithms can (i) help monitoring social media and understand consumers perception of luxury hotels through the new analysis of visual data, and (ii) turn into better brand management strategies for luxury hotel managers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.