Airbnb is currently one of the most developed new forms of hospitality. It is essentially an online platform that connects the owners of apartments or rooms with potential guests. The core of the Airbnb model is the host, who offers a support to guests and favor a link between the guests and the tourism destination. Airbnb awards the best hosts with the badge of “Superhost”, which is attributed according to four elements: the occupancy rate, the number of reservations, the response rate and the cancellation policy. This paper focuses on hosts and their activities. Specifically, the main goal is understanding if the four aforementioned elements actually influence the attribution of the “Superhost” badge to hosts operating in two of the main Italian touristic destinations: Sardinia and Sicily. Furthermore, the link between the four basic elements and other “managerial factors” is analyzed. Logistic and Probit models are used for these purposes and the main findings are derived from the computation of marginal effects. The results show a direct impact of the four Airbnb variables and of other “managerial” variables, as for instance the presence of extra fees for cleaning or similar services, on the probability to be a superhost.

Identifying factors affecting the status of superhost: evidence from Sardinia and Sicily

Contu Giulia;Conversano Claudio;Frigau Luca;Mola Francesco
2020-01-01

Abstract

Airbnb is currently one of the most developed new forms of hospitality. It is essentially an online platform that connects the owners of apartments or rooms with potential guests. The core of the Airbnb model is the host, who offers a support to guests and favor a link between the guests and the tourism destination. Airbnb awards the best hosts with the badge of “Superhost”, which is attributed according to four elements: the occupancy rate, the number of reservations, the response rate and the cancellation policy. This paper focuses on hosts and their activities. Specifically, the main goal is understanding if the four aforementioned elements actually influence the attribution of the “Superhost” badge to hosts operating in two of the main Italian touristic destinations: Sardinia and Sicily. Furthermore, the link between the four basic elements and other “managerial factors” is analyzed. Logistic and Probit models are used for these purposes and the main findings are derived from the computation of marginal effects. The results show a direct impact of the four Airbnb variables and of other “managerial” variables, as for instance the presence of extra fees for cleaning or similar services, on the probability to be a superhost.
2020
Airbnb; Logistic regression; Marginal effects; Probit regression; Superhost;
Airbnb; Logistic regression; Marginal effects; Probit regression; Superhost
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/277850
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