資料探勘技術應用於航空業顧客再搭意願區隔與服務滿意項目組合之分析

Data Mining Techniques Applied in Airline Industry to Explore Segmentation of Repurchase Intentions and the Best Service Items Mix on Customer Satisfaction

翁振益(Jehn-Yih Wong) ； 張德儀(Te-Yi Chang) ； 鄭光遠(Kung-Yeun Jeng) ； 鍾碧姮(Pi-Heng Chung) ； 林雅藝(Ya-Yi Lin)

《觀光研究學報》 12卷2期 (2006/06) Pp. 139-154

https://doi.org/10.6267/JTLS.2006.12(2)3

摘要

高速鐵路即將營運，未來國內線航空業所面臨之競爭與挑戰重加激烈。在有限旅客市場，要如何保留顧客與增加再搭意願是國內各家航空公司關注的顧客管理問題。服務品質是形成顧客滿意重要原因之一，航空業者如能滿足旅客在服務品質上之要求，不僅可維繫與提高顧客滿意度，進而提升顧客之再搭意願。
本研究以國內某航空公司之顧客資料庫為例，利用資料探勘技術之C4.5決策樹挖掘不同再搭意願旅客之服務品質區隔，分析不同區隔之服務品質需求與顧客屬性之差異及購物籃分析挖掘旅客有高滿意度之服務品質組台組台。
探勘結果發現，個案航空業者短期急需改善機場之櫃檯人員和空服人員服務態度，長期需改善公司形象和飛航安全，提升顧客整體滿意度，進而讓旅客之再搭意願較高。這些決策資訊不僅是針對此個案航空公司，亦提供國內其他航空業者在實務上改善顧客關係管理之參考。

關鍵字

航空業 ； 資料探勘 ； 決策樹 ； 購物籃分析

並列摘要

As the High-Speed Rail will be started recently, the competition is very fierce in the domestic airlines in Taiwan. According to the minority of travelers in Taiwan, the domestic airlines care about the issue that how to retain customer and raise their repurchase intention. Generally speaking, the service quality significantly influences customer satiation and repurchase intention. Therefore, the purposes of this research are exploring ”which service could increase customer repurchase intention” and ”which service could improve customer satisfaction” by applying data mining techniques.
For this research, the research subject is one of the domestic airlines. To use C4.5 decision tree to mine segmentations of high repurchase intention customers from service quality data and basket analysis to elicit high satisfaction rules.
The results of analysis indicated the airline manager must improve service attitude of the counter and the flight staff in the sort-term and advance image and flight safety in the long-term. The finding is not only useful for this airline but also to provide others in customer relationship management.

並列關鍵字

airlines ； data mining ； decision trees ； basket analysis

參考文獻

陳垂呈、林志鴻(2005)。利用探勘技術分析景點最適性之旅遊行程。餐旅暨家政學刊。2(2)，145-159。

陳垂呈(2004)。有效率探勘旅遊景點最適性之消費者。餐旅暨家政學刊。1(2)，163-173。

Agrawal, R.,Imilienski, T.,Swami, A.(1993).Mining association rules between sets of items in large databases.Proceedings of the ACM SIGMOD International Conference on the Management of Data.(Proceedings of the ACM SIGMOD International Conference on the Management of Data).:

BaFail, A. O.(2004).Applying data mining techniques to forecast number of airline passengers in Saudi Arabia.Journal of Air Transportation.9(1),100-115.

Berry, M. J. A.,Linoff, G.(2000).Mastering Data Mining, the Art and Science of Customer Relationship Management.NY:John Wiley and Sons.