Segmenting collaborative users based on their physiological factors toward AirBnB

Abstract

Collaborative consumption has generated the appearance of new business models, such as those created by peer-to-peer platforms, such as AirBnB, focused on renting the accommodation of the users themselves to other users. The growing popularity of AirBnB has resulted in an emerging body of literature examining the factors that drive or deter consumers from choosing AirBnB (Sakr et al., 2024;). This work is based on a sample of 405 travellers who regularly use AirBnB to book accommodation on their journeys. They are asked about about their different motivations toward use of this type of reservation (e.g. hedonic, environmental sustainability, economic benefit, convenience, etc.), user personality values (i.e. individualism-collectivism; communal-exchange relationships), engagement with the AirBnB brand, and some personal characteristics (e.g. gender, age, education, economic situation, etc). A latent segmentation -through Latent Gold® software- was developed to obtain different profiles of AirBnB users based on above variables. Preliminary results show quite heterogeneity in the motivations and effects on the indicated dimensions. This helps to segment the users and detect different profiles with different motivational connections with the personal characteristics of users, engagement with this platform and their communal orientation about this type of sharing tourism. This motivational and physiological heterogeneity can make it easier for people to be reached through different communication strategies and arguments both by the tourism sector’s businesses and by public agencies with interests in city tourism management.