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.
| Original language | English |
|---|---|
| Pages (from-to) | 113-131 |
| Number of pages | 19 |
| Journal | Journal of Travel and Tourism Marketing |
| Volume | 27 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Mar 2010 |
Keywords
- Activity pattern analysis
- Data mining
- Hong Kong
- Market segmentation
ASJC Scopus subject areas
- Tourism, Leisure and Hospitality Management
- Marketing
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