Abstract
Airbnb has emerged as a platform where unique accommodation options can be found. Due to the uniqueness of each accommodation unit and host combination, each listing offers a one-of-a-kind experience. As consumers increasingly rely on text reviews of other customers, managers are also increasingly gaining insight from customer reviews. Thus, this present study aimed to extract those insights from reviews using latent Dirichlet allocation, an unsupervised type of topic modeling that extracts latent discussion topics from text data. Findings of Hong Kong’s 185,695 and Singapore’s 93,571 Airbnb reviews, two long-term rival destinations, were compared. Hong Kong produced 12 total topics that can be categorized into four distinct groups whereas Singapore’s optimal number of topics was only five. Topics produced from both destinations covered the same range of attributes, but Hong Kong’s 12 topics provide a greater degree of precision to formulate managerial recommendations. While many topics are similar to established hotel attributes, topics related to the host and listing management are unique to the Airbnb experience. The findings also revealed keywords used when evaluating the experience that provide more insight beyond typical numeric ratings.
Highlights
When Airbnb was launched, it was considered as a safer and more exciting alternative to couch surfing, so most industry experts and global hotel chains did not take much notice [1,2]
The approach allowed for comparisons at two stages, number of topics, and extracted content. This present study aims to fulfill the lack of comparative studies in topic modeling research by comparing topics extracted from guest reviews of Airbnb in Hong Kong to those in Singapore
The difference between Hong Kong and Singapore reviews already started at the optimal number of topics, where Hong Kong recommends 12 topics whereas Singapore suggests only five
Summary
When Airbnb was launched, it was considered as a safer and more exciting alternative to couch surfing, so most industry experts and global hotel chains did not take much notice [1,2]. Together with other companies such as Uber (ride-sharing), Lime (bike rental), JustPark (car parking space) among many others representing the sharing economy, Airbnb takes most of the headlines [4] What most of these companies have in common is that the idea began as being so radical, that mainstream consumers did not find their attributes to be appealing. Airbnb competes in most levels of the accommodation market, from low-end to luxury, solo to large groups, and accommodates both leisure and business travelers [2,5]. This life-cycle is typical of disruptive innovations [1]
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