A big data analysis of COVID-19 impacts on Airbnbs' bookings behavior applying construal level and signaling theories

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. Results show that in the pre-COVID-19 period, 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.