Identifying changes and trends in Hong Kong outbound tourism

Law, Rob, Rong, Jia, Vu, Huy Quan, Li, Gang and Lee, Hee Andy 2011, Identifying changes and trends in Hong Kong outbound tourism, Tourism management, vol. 32, no. 5, pp. 1106-1114.

Attached Files
Name Description MIMEType Size Downloads

Title Identifying changes and trends in Hong Kong outbound tourism
Author(s) Law, Rob
Rong, Jia
Vu, Huy Quan
Li, Gang
Lee, Hee Andy
Journal name Tourism management
Volume number 32
Issue number 5
Start page 1106
End page 1114
Total pages 9
Publisher Pergamon
Place of publication Oxford, England
Publication date 2011-10
ISSN 0261-5177
1879-3193
Keyword(s) contrast analysis
association rules
machine learning
data mining
hong kong
outbound tourism
Summary 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.
Notes Now published. Available online 6 October 2010.
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
150603 Tourism Management
Socio Economic Objective 900302 Socio-Cultural Issues in Tourism
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2011
Copyright notice ©2010, Elsevier Ltd. All rights reserved.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30033028

Document type: Journal Article
Collection: School of Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 7 times in TR Web of Science
Scopus Citation Count Cited 9 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 379 Abstract Views, 7 File Downloads  -  Detailed Statistics
Created: Fri, 25 Feb 2011, 11:24:23 EST by Sandra Dunoon

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.