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