Modeling Price Elasticity for Occupancy Prediction in Hotel Dynamic Pricing

Fliggy), dynamic pricing is extremely important as similar hotels on the platform compete to share the market demand, and the inventory Demand estimation plays an important role in dynamic pricing (i.e., the available rooms) of each hotel is perishable on each where the optimal price can be obtained via maximizing the revenue day. Thus, a good pricing policy can benefit the matching of supply based on the demand curve. In online hotel booking platform, and demand, and improve the overall revenue. In practice, most the demand or occupancy of rooms varies across room-types and pricing strategies recommend an optimal price to maximize the changes over time, and thus it is challenging to get an accurate revenue based on a demand curve [5] that depicts the relationship occupancy estimate. In this paper, we propose a novel hotel demand between the price of a room and the demanded rooms, or particularly function that explicitly models the price elasticity of demand for referred to as occupancy, at that price. Therefore, occupancy occupancy prediction, and design a price elasticity prediction model estimation is the key to the success of dynamic pricing.