Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8245
Title: Identifying changes and trends in Hong Kong outbound tourism
Authors: Law, R 
Rong, J
Vu, HQ
Li, G
Lee, HA
Keywords: Contrast analysis
Association rules
Machine learning
Data mining
Hong Kong
Outbound tourism
Issue Date: 2011
Publisher: Pergamon Press
Source: Tourism management, 2011, v. 32, no. 5, p. 1106-1114 How to cite?
Journal: Tourism management 
Abstract: Despite the numerous research endeavors aimed at investigating tourists' preferences and motivations, it remains very difficult for practitioners to utilize the results of traditional association rule mining methods in tourism management. This research presents a new approach that extends the capability of the association rules technique to contrast targeted association rules with the aim of capturing the changes and trends in outbound tourism. Using datasets collected from five large-scale domestic tourism surveys of Hong Kong residents on outbound pleasure travel, both positive and negative contrasts are identified, thus enabling practitioners and policymakers to make appropriate decisions and develop more appropriate tourism products.
URI: http://hdl.handle.net/10397/8245
ISSN: 0261-5177
EISSN: 1879-3193
DOI: 10.1016/j.tourman.2010.09.011
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