Spatial and temporal analysis of accommodation preference based on online reviews

Knowledge about where tourists stay during their trips, and at what time of year, is important to destination marketing, management, and planning. However, analysis of the spatial and temporal accommodation patterns of tourists often requires comprehensive data sets, advanced analytical techniques, and massive cost and workloads. Perhaps for these reasons few studies have attempted to construct a profile of tourists' accommodation preferences. This study contributes to the extant literature by introducing a method that utilizes spatial and temporal data embedded in online travel reviews to address these challenges. The effectiveness of the proposed method was demonstrated in a case study of inbound tourists in Hong Kong, using a large data set comprising 115, 649 online reviews of 314 hotels. Particular location preferences for hotel stays were revealed for the whole market and for different source markets. The seasonal demand patterns for different market segments (i.e. business, family, couple, and solo) from different regions of the world were identified. The presented approach is valuable for hotel practitioners, who can use online reviews as a source of information regarding tourists' choices regarding hotel stays.