Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10717
Title: Analyzing international travelers' profile with self-organizing maps
Authors: Li, G
Law, R 
Wang, J
Keywords: Data mining
Market segmentation
Activity pattern analysis
Hong Kong
Issue Date: 2010
Publisher: Routledge, Taylor & Francis Group
Source: Journal of travel & tourism marketing, 2010, v. 27, no. 2, p. 113-131 How to cite?
Journal: Journal of travel & tourism marketing 
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.
URI: http://hdl.handle.net/10397/10717
ISSN: 1054-8408
EISSN: 1540-7306
DOI: 10.1080/10548400903579647
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