Investigating key attributes in experience and satisfaction of hotel customer using online review data

Abstract

With the development of social media, customers are sharing their experiences, and it is rapidly spreading as a form of online review. That is why the online review has become a significant information source affecting customers' purchase intention and behavior. Therefore, it is important to understand the customer's experience shown in the online review in order to maintain sustainable customer satisfaction and loyalty. The purpose of this study is to investigate what are the key attributes and the structural relationship of those key attributes. To accomplish this purpose, a total of 6596 hotel reviews were collected from Google (google.com). A frequency analysis using text mining was performed to figure out the most frequently mentioned attributes. In addition, semantic network analysis, factor analysis, and regression analysis were applied to understand the experience and satisfaction of the hotel customer. As a result, the top 99 keywords were divided into four groups such as "Intangible Service", "Physical Environment", "Purpose", and "Location". The factor analysis reduced the dimension of the original 64 keywords to 22 keywords, and grouped them into five factors, which are "Access", "F&B (Food and Beverage)", "Purpose", "Tangibles", and "Empathy". Based on these results, theoretical and practical implications for sustainable hotel marketing strategies are suggested.