摘要：Over the years, as people's lives have improved, our need for transportation andaccommodation has increased, driving the rapid growth of the sharing economy.Some well-known network sharing platforms, such as Uber, Drip and Airbnb,provide a large number of convenient options for users with transactional needs,make more use of idle tourism, accommodation and other resources. Sharingeconomy platforms continue to improve the content and format of their products,but at the same time, the future of sharing platforms and the difficulty of competitionis a concern as more platform companies become involved and prices become moretransparent. Under this circumstance, optimizing product pricing has become anurgent need for many sharing economy platforms. In this paper, we take Airbnb asthe starting point and conduct an empirical analysis of the blocking behavior ofhomeowners based on proprietary data to explore the factors that affect their productsupply. We find that price, number of beds, and listing type all have a significantimpact on blocking houses. After that, we conducted further research on pricefactors and developed a model aiming at profit maximization to obtain the bestpricing range for the region and provide suggestions for pricing strategies.
