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

Raffaele Filieri; Francesco Luigi Milone; Emilio Paolucci; Elisabetta Raguseo

doi:10.1016/j.ijhm.2023.103461

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

Int J Hosp Manag. 2023 May:111:103461. doi: 10.1016/j.ijhm.2023.103461. Epub 2023 Mar 10.

Authors

Raffaele Filieri¹, Francesco Luigi Milone², Emilio Paolucci³, Elisabetta Raguseo^{3

4}

Affiliations

¹ Audencia Business School, Marketing Department, 8 Rte de la Jonelière, 44300 Nantes, France.
² Department of Management and Production Engineering (DIGEP), The Future Urban Legacy Lab (FULL), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy.
³ Department of Management and Production Engineering (DIGEP), The Future Urban Legacy Lab (FULL), Entrepreneurship and Innovation Center (EIC), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy.
⁴ Aix-Marseille Université, CERGAM, Aix-en-Provence, France.

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. 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.

Keywords: Airbnb; COVID-19; Consumer behavior; Price premium; Psychological distance; Spatial and social distance.