Looking into the Word-of-Mouth in Tourist Accommodations Based on Big Data

Abstract

Online word-of-mouth information can reflect tourists’ consumption choices and behavioral patterns. Existing studies mainly analyze word-of-mouth in tourism from internal factors (service level, price, facility condition, etc.), and there is a lack of extended studies focusing on external factors, e. g. the spatial distribution of tourist accommodations. Based on the Point of Interest and User Generated Content information of 71 accommodations around Chengdu Research Base of Giant Panda Breeding, this paper uses social network and sentiment analysis tools to filter relevant variables affecting word-of-mouth. Spatial econometric models are then built and examined, and we further identified the optimal model to discuss the key factors affecting word-of-mouth in the accommodation industry from the perspective of spatial distribution. Results show that: (1) there is significant spatial clustering and spillover effect of word-of-mouth in the study accommodations. (2) network structure has a significant impact on word-of-mouth, which enables reference for site selection. (3) the improvement of service level and geographical location of tourist accommodation has a significant positive effect on word-of-mouth.