Towards a rough classification of business travelers

Authors:
Rob Law;Thomas Bauer;Karin Weber;Tony Tse
Affiliations:
School of Hotel & Tourism Management, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;School of Hotel & Tourism Management, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;School of Hotel & Tourism Management, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;School of Hotel & Tourism Management, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Venue:
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Year:
2006

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Abstract

The significant economic contributions of the fast growing tourism industry have drawn worldwide attention on understanding the behavioral and demographic patterns of visitors. This research makes an attempt to develop a rough sets based model that can capture the essential information from business travelers, a segment of the market that to date has been entirely overlooked by academic researchers in data mining. Utilizing the primary data collected from an Omnibus survey carried out in Hong Kong in late 2005, experimental findings showed that the induced decision rules could classify 82% of the cases in the testing set and 41% of the classified cases were correctly estimated. Most importantly, there was no statistically significant difference between the estimated values and actual values.