Understanding service quality attributes that drive user ratings: A text mining approach

Abstract

Studies based on online textual data are increasingly used in the hospitality sector to gain better consumer insights. Using text mining of TripAdvisor reviews and mapping it to hard and soft attributes of SERVQUAL dimensions, this research attempts to identify service quality characteristics that influence the customers’ online ratings of hotels. The moderating effects of the reviewer characteristics, namely (a) domestic vs foreign (b) novice vs experienced, (c) less vs more popular and (d) brief vs elaborate writing, on the relationship between quality attributes and online hotel ratings are also analyzed. The results imply that reviewers emphasize hard attributes of service quality in general, such as tangibles, reliability, and responsiveness, while providing online ratings to hotels. Furthermore, reviewer characteristics also influence the attributes emphasized in reviews and the resultant ratings. Finally, along with the theoretical contributions, managerial contributions, such as the usefulness of service planning outcomes, are discussed.