Analyzing International Travelers' Profile with Self-Organizing Maps

ABSTRACT

It is generally agreed that knowledge is the most valuable asset to an organization. Knowledge enables a business to effectively compete with its competitors. In the tourism context, an in-depth knowledge of the profile of international travelers to a destination has become a crucial factor for decision makers to formulate their business strategies and better serve their customers. In this research, a self-organizing map (SOM) network was used for segmenting international travelers to Hong Kong, a major travel destination in Asia. An association rules discovery algorithm is then utilized to automatically characterize the profile of each segment. The resulting maps serve as a visual analysis tool for tourism managers to better understand the characteristics, motivations, and behaviors of international travelers.

KEYWORDS:

• Data mining
• market segmentation
• activity pattern analysis
• Hong Kong

The authors would like to thank the three anonymous reviewers for their constructive comments on improving an early version of this article. This project was partly supported by a research grant funded by the Hong Kong Polytechnic University.