The Sharing Economy, or the economy of sharing, is an economic phenomenon that has rapidly spread in recent years, transforming the ways in which resources and services are accessed and consumed. This phenomenon has had a significant impact on consumption dynamics, redefining the concept of ownership and promoting the idea of temporary and shared access to goods. An emblematic example is represented by Airbnb, a multinational company founded in 2008 and valued at 35 billion dollars. With over 4 million hosts and 800 million guests in more than 220 countries and regions, Airbnb offers communities the opportunity to make the most of their cultural and scenic heritage, attracting a variety of visitors eager for authentic experiences. In this regard, the present study proposes a methodological model capable of empirically analyzing the Airbnb market in four Italian cities, adopting an integrated approach that combines Principal Component Analysis (PCA) and clustering based on the use of the k-means algorithm, to arrive at a deeper understanding of the data. The results emerging from the research highlight a significantly negative correlation between price and distance from the city center, also revealing a negative correlation between reviews and price, as well as between reviews and distance from the city center. Through the analysis of the research results, it aims to make a relevant contribution to academic literature, providing new perspectives and insights for further studies on Airbnb dynamics, as well as on the economic and social implications of resource and service sharing in the context of the Sharing Economy.