Over the years, as people's lives have improved, our need for transportation and
accommodation 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. Sharing
economy 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 competition
is a concern as more platform companies become involved and prices become more
transparent. Under this circumstance, optimizing product pricing has become an
urgent need for many sharing economy platforms. In this paper, we take Airbnb as
the starting point and conduct an empirical analysis of the blocking behavior of
homeowners based on proprietary data to explore the factors that affect their product
supply. We find that price, number of beds, and listing type all have a significant
impact on blocking houses. After that, we conducted further research on price
factors and developed a model aiming at profit maximization to obtain the best
pricing range for the region and provide suggestions for pricing strategies.
Keywords: Sharing Economy, Blocking behavior, Pricing Strategy, Airbnb
Indirect Network Effects in New Product Growth
