Cultural differences in hospitality service evaluations: mining insights of user generated content

Online peer-to-peer platforms have been widely utilized to facilitate sharing vast amounts of user-generated content (UGC) in the hospitality industry. However, research on the cultural impacts of the broad spectrum of UGC remains nascent and limited. This study therefore elaborates how the hospitality service dimensions that are reflected in UGC both predict service evaluation and are contingent on a reviewer’s prevailing culture. We analyzed a usable sample of 9,257 hotel reviews from 148 countries with latent Dirichlet allocation and aspect-based sentiment analysis algorithms to identify the top service features and corresponding polarity scores. Machine learning identified three dimensions of hospitality service quality: adaptability, reliable delivery, and tangibles. These three dimensions predict customers’ overall hotel ratings, and the magnitude and direction of their effects depend on alignments of cultural orientations. Following Hofstede’s cultural dimensions, reliable delivery and tangibles align with individualism and uncertainty avoidance cultures. Adaptability aligns with power distance, masculinity, long-term orientation, and indulgence cultures.