Using Data Mining Techniques to Design a Customized Travel Experience – An Example Based on the Inbound Visitors

• Main Authors: Jian-Yu Chen, 陳建宇
• Other Authors: 林金賢
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/p42999

碩士 === 國立中興大學 === 企業管理學系所 === 107 === The dataset used in this study is the “Survey of Visitors Expenditure and Trends in Taiwan” from the Tourism Bureau of the Ministry of Communications from 2014 to 2017. The growth of international passengers and the diversification of information channels in the future will make the competition between destinations become fiercer. The accumulation of tourism materials will make the tourism industry more in need of data exploration technology to more accurately capture the needs of each tourist. In the past literature, in the design and recommendation of the itinerary, it was not possible to propose a suitable method to create an exclusive tourism product that accurately conforms to each different traveler. In the context of paying more attention to the travel experience today. In this study, the decision tree is combined with the return of Logistic regression, and the variables such as travel motivation and travel quality are added. In order to improve the prediction accuracy, a travel experience that can accurately meet the needs of passengers is proposed. The results show that the model combined with decision tree and Logis regression has the highest prediction accuracy, which is more than 80% among the four groups of tourism products. Finally, how to apply this similar situation process as management meaning.