A big data analysis of COVID-19 impacts on Airbnbs' bookings behavior applying construal level and signaling theories. (May 2023) - Filieri, Raffaele; Milone, Francesco Luigi; Paolucci, Emilio; Raguseo, Elisabetta
Abstract: This study investigates the impact of the COVID-19 pandemic on consumer booking behavior in the peer-to-peer accommodation sector. This study used a dataset composed of 2041, 966 raws containing 69, 727 properties located in all 21 Italian regions in the pre- and post-COVID-19 1 . Results show that after the COVID-19 pandemic, consumers preferred P2P accommodations with price premiums and located in rural (versus urban) areas. Although the findings reveal a preference for entire apartments over shared accommodation (i.e., room, apartment), this preference did not change significantly after COVID-19 lockdowns. The contribution of this study lies in combining psychological distance theory and signaling theory to assess P2P performance in the pre- and post-COVID-19 periods. Highlights: We assess the impact of the COVID-19 pandemic on Airbnb users' booking behavior. The study combines construal level and signaling theory and uses a dataset of all Italian Airbnbs. Travellers prefer rural (versus urban) P2P accommodation after the pandemic. Travellers are more willing to pay price premium accommodation compared to pre-COVID-19. Travelers' booking of entire apartments and shared accommodations did not change after COVID-19.