An analysis of Tripadvisor shopping mall reviews in Thailand

Abstract

Shopping is an important tourism activity. However, knowledge regarding the understanding of tourist experiences at shopping malls in Thailand is limited. Currently, COVID-19 has impacted the profitability of shopping malls that also face competition from the worldwide rise of e-commerce. Factors that drive positive and negative tourist experiences at Thai shopping malls were investigated using data from online reviews, which have now become an important source of information. A total of 40,504 TripAdvisor reviews concerning 46 major shopping malls in Thailand were analysed using the latent Dirichlet allocation (LDA) machine learning algorithm. Five types of tourist shopping experiences were identified as plenitude, connectivity, food, merchandise and commercialism. A textual salience-valence analysis was also performed to investigate words that drove positive and negative tourist shopping experiences. IMPLICATION OF THE THESIS This research attempts to discover the types of experiences of shopping malls in Thailand. This is for The Tourism Authority of Thailand (TAT) and shopping malls to improve the shopping experiences of tourists and stimulate economic growth.