Title of article :
Identifying changes and trends in Hong Kong outbound tourism
Author/Authors :
Law، نويسنده , , Rob and Rong، نويسنده , , Jia and Vu، نويسنده , , Huy Quan and Li، نويسنده , , Gang and Lee، نويسنده , , Hee Andy، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
Pages :
9
From page :
1106
To page :
1114
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.
Keywords :
Machine Learning , Hong Kong , DATA MINING , Contrast analysis , Association rules , Outbound tourism
Journal title :
Tourism Management
Serial Year :
2011
Journal title :
Tourism Management
Record number :
2330985
Link To Document :
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