Trans. Planning Journal
| Title | Application of Data Mining to Explore International Airline Passenger Online Booking Behavior |
|---|---|
| Author | Hsiang-Sheng Lin and I-Hao Liu |
| Summary | In recent years, more and more airlines regard on-line booking as the basic function of their homepage. Since the Internet becomes more popular day by day, the traditional travel agencies are facing the crisis of having the middleman removed. However, a new interaction has appeared between airlines and passengers. While the e-commerce develops vigorously, the airlines go through passengers' online booking behavior, namely to obtain more customer information and transaction records. Therefore, how to use this data to understand the customers, experience suitable data processing technology, and provide the customized marketing service to riders, all have become issues of future airlines. This research will explore data mining to discuss airline passengers’ online booking behaviors. First, we adopt the RFM model (Recency, Frequency, Monetary), the average mileage and classes as five customer value index items to process clustering for riders. The result will make a classification and quickly distinguish customer group belongings. Again, we aim at service products classification to understand the consumers’ behavior of each route. Finally, the association analysis is carried out for different trip purposes, thence appears customers’ implicit connecting demands between all routes. |
| Vol. | 37 |
| No. | 2 |
| Page | 197 |
| Year | 2008 |
| Month | 6 |