Identifying changes and trends in Hong Kong outbound tourism |
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Authors: | Rob Law Jia Rong Huy Quan Vu Gang Li Hee Andy Lee |
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Institution: | 1. School of Hotel & Tourism Management, The Hong Kong Polytechnic University, Hong Kong;2. School of Information Technology, Deakin University, Vic 3125, Australia |
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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. |
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Keywords: | Contrast analysis Association rules Machine learning Data mining Hong Kong Outbound tourism |
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