Understanding Cruise Tourists' Satisfaction by Analysing Their Online Ratings and Reviews

Abstract

Associating online ratings with reviews provides a potentially cost-effective way for cruise tourism managers to capture satisfaction and quality improvement information from customers so as to facilitate the sustainable development of the tourism industry. For this purpose, this study proposes an integrated approach that leverages text mining and empirical modeling to quantitatively correlate online ratings with reviews. From TripAdvisor.com, 4248 pairs of rating and review regarding Chicago’s First Lady Cruises were examined, with major topics identified. Subsequently, multilinear regression was employed to screen out the most impactful factors that influence overall ratings. Managerially, the idea of triggering the synergistic benefit from customer ratings and reviews is referential for market practitioners both within and beyond the tourism industry.