Airbnb 후기 분석을 통한 P2P 숙박 경험의 영향 요인 식별에 대한 연구

Abstract

Customers' online reviews have important business value in the age of big data. Especially in the accommodation industry, online review analysis has become one of the important data sources for researchers to understand customer behavior and investigate customer satisfaction. Based on 5715 online reviews of airbnb in Lijiang, China, Dec, 2020. This study analyzes the attractive factors of homestays in Lijiang, China, and explores consumers' views and attitudes towards Lijiang homestays. Through keyword analysis, hierarchical clustering analysis and Critical Incidents Technique, 15 attractive factors of Lijiang Airbnb were extracted from the corpus. The research results show that room and location are the most important attributes in consumer reviews, followed by environment and service. In addition, in the accommodation experience, the host as a service provider plays an important role in all aspects. These factors have an important impact on consumer satisfaction and booking propensity. Combined with the content of the comments, it explains how each factors affects the consumer's living experience. This research expands the attributes that affect the airbnb consumer experience and provides marketing advice to homestay operators to help them better understand customer online review behavior and to help operators understand how to get a positive word-of-mouth evaluation in online reviews. Methodologically, this research has contributed to how to use and visualize big data in the P2P accommodation industry.