Understanding Customer Experience of Airline Lounge Using Text Mining of Online Review

다국어 초록 (Multilingual Abstract)

In this study, the experience of airline lounge was analyzed through text mining of online review to provide marketing implications that could be used to establish sustainable strategy of airline lounge. Analyzing online review is an effective way to understand customer needs and to identify key attributes for customer satisfaction. The number of online reiviews extracted is 3,573. And those reviews were written from January 1st 2008 to March 31st 2019. This study conducted a semantic network analysis as part of text mining by collecting online reviews of airline lounge. According to the analysis, the top five frequent words are ‘food’, ‘staff’, ‘drink’, ‘selection' and ’busy’. Through a CONCOR (CONvergence of iterated CORrelation) analysis, keywords were divided into four clusters. Each cluster was named as ‘Physical environment’, 'Brand’. ‘Service’, and 'F&B’(Food & Beverage). The results enable a better understanding of customer’s experience in airline lounge. These findings suggest important implications with empirical evidence for building an effective marketing strategy based on deeper understanding of customers' experience of lounge areas. These are key elements in business mana gement throughout the airline industry.

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