Cluster analysis of China’s inbound tourism market: A new multi-attribute approach based on association rule mining of tourist preferences at scenic spots

ABSTRACT

This study adopts association rules to identify the co-occurrence of attributes concerned by inbound tourists visiting scenic spots and further make a cluster analysis. In total, 72,890 online reviews of 218 scenic spots in China from inbound travelers from TripAdvisor used for analysis. It is found that the tourists could be clustered into three groups: view-sensitive travelers, crowding-sensitive travelers, and price-sensitive travelers. This study makes an early attempt to cluster travelers according to their conjoint preference patterns based on the co-occurrence of destination attributes, and provides a new multi-attribute approach to the investigation of tourist preferences and market segmentation.

KEYWORDS:

• Inbound tourism
• conjoint preference
• multi-attributes
• tourism online reviews
• association rule mining

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Natural Science Foundation of China [number 72074126, 71702081, 71971124 and 71932005].