Airbnb and their performances in Milan, analysis of the performances of the Airbnb in Milan in relation with the distance from the “points of interests” pre, during and post Covid-19

In this master thesis will be studied how the distances between each Airbnb and its closest ‘point of interest’ affect the performances of the listings in the city of Milan. As ‘point of interest’ have been identified the following parameters as the ones that can affect the choice of a customer in the booking: metro station, public parking, ZTL or pedestrian area, sport facility and area or building in degradation conditions. The work has been conducted from June 2023 to March 2024 reviewing first the literature and then conducting the analysis using the software of Python, Excel, and STATA. In this script will be explored in depth the phenomenon in the city of Milan during the four-year period from 2019 to 2022. Some of the trends that this research highlighted have been: the strong and positive relation between the nearness from the closest pedestrian area and the performance of an Airbnb; a positive relation between the listings and the closeness to a metro station and a public parking.