This study employs advanced text-mining techniques to offer an in-depth and comprehensive overview of the extensive body of research on Airbnb. By analyzing 1021 articles published in 416 journals spanning the period from 2015 to 2022, this study aims at revealing Airbnb research topics and trends. The results show that the primary focus of academic inquiry regarding Airbnb revolves around two domains: the company's operational practices and its impacts on various domains. Within the realm of Airbnb's operational practices, four distinct research topics emerge as particularly prominent and extensively explored. These encompass the dynamics of ‘trust in Airbnb,’ the formulation and implementation of ‘house rules,’ the mechanisms of governing ‘Airbnb pricing’ strategies, and the critical examination of ‘value creation in Airbnb’ initiatives. Meanwhile, the most researched impacts of Airbnb are on urban tourism, rental housing markets, tourist destinations, and hotels. These spheres have received significant scholarly attention due to the profound implications and transformative effects engendered by Airbnb's disruptive presence in these areas. Moreover, the findings underscore that research pertaining to Airbnb's operational aspects has witnessed a significant increase in popularity over time, indicating a marked shift in the focal points of Airbnb research. Notably, the research topics that have experienced substantial growth include ‘trust in Airbnb,’ ‘Airbnb pricing,’ and ‘impacts on tourist destinations.’ Lastly, this study found that Airbnb-related research articles in hospitality and tourism journals tend to be more delving into industry-specific phenomena and challenges. Conversely, non-hospitality and tourism journals provide a broader coverage of topics related to Airbnb, encapsulating diverse areas of inquiry beyond the boundaries of the industry. This literature review provides valuable insights into existing research on Airbnb and highlights several critical areas for future research.

Introduction: Online reviews have become an important source of information for investigating customers’ consumption experiences in academic studies. In the context of sharing economy-based accommodation, various studies have been conducted to investigate the user experience of Airbnb by analyzing online reviews; however, most previous Airbnb studies had focused on analyzing the user experience of Airbnb at a holistic level without distinguishing the accommodation attributes of Airbnb. Therefore, this article aimed to investigate how the preferences revealed by Airbnb users in online reviews vary across Airbnb listings with different levels of sharing and price ranges.Methods: This study analyzed 181,190 online reviews under Airbnb listings in Kuala Lumpur, Malaysia, using the structural topic model (STM).Results: This study identified 21 topics related to Airbnb service and product attributes.Discussion: The findings show that Airbnb users who stay at entire property are more concerned with the hedonic value of their stay, while those who stay at shared property are more concerned with the utilitarian value. The purposes of the host–guest interaction were also found to differ between these two types of Airbnb accommodations. Regarding the effect of listing prices on users’ preferences, findings reveal that those staying at lower-priced rooms were more concerned about the convenience of exploring the surrounding area, while those who stayed at higher-priced rooms were more concerned about the surrounding environment and the interior facilities of the property.

This study aims to examine key attributes affecting Airbnb users' satisfaction and dissatisfaction through the analysis of online reviews. A corpus that comprises 59,766 Airbnb reviews form 27,980 listings located in 12 different cities is analyzed by using both Latent Dirichlet Allocation (LDA) and supervised LDA (sLDA) approach. Unlike previous LDA based Airbnb studies, this study examines positive and negative Airbnb reviews separately, and results reveal the heterogeneity of satisfaction and dissatisfaction attributes in Airbnb accommodation. In particular, the emergence of the topic “guest conflicts” in this study leads to a new direction in future sharing economy accommodation research, which is to study the interactions of different guests in a highly shared environment. The results of topic distribution analysis show that in different types of Airbnb properties, Airbnb users attach different importance to the same service attributes. The topic correlation analysis reveals that home like experience and help from the host are associated with Airbnb users' revisit intention. We determine attributes that have the strongest predictive power to Airbnb users' satisfaction and dissatisfaction through the sLDA analysis, which provides valuable managerial insights into priority setting when developing strategies to increase Airbnb users' satisfaction. Methodologically, this study contributes by illustrating how to employ novel approaches to transform social media data into useful knowledge about customer satisfaction, and the findings can provide valuable managerial implications for Airbnb practitioners.