Motivation and satisfaction of Chinese and U.S. tourists in restaurants: A cross-cultural text mining of online reviews

Abstract

Tourists with dissimilar cultural backgrounds think and behave differently. Precisely capturing and correctly understanding the cultural difference will help tourism managers generate greater customer satisfaction and increased business revenue. To this end, this paper uncovers and compares the motivation and satisfaction of restaurant tourist customers coming from China and U.S. by investigating their online ratings and reviews. From two major online review communities, customer ratings and reviews have been retrieved, quantified, text-mined, compared, and interpreted using statistics, latent Dirichlet allocation, and frequency analysis. Results suggest that Chinese tourists are less inclined to assign lower ratings to restaurants, and are more strongly fascinated by the food offered, whereas U.S. tourists are more apt to be fun-seeking, and are less uncomfortable with crowdedness.