General dynamic pricing algorithms based on universal exponential booking curves

Abstract

We propose a new dynamic pricing algorithm based on the universal exponential law of booking curves in services with reservations. The algorithm includes a parametric learning model which makes it possible to simulate the effect of changes in prices on quantity demanded from historical data continuously for practical use. Furthermore, we show an example, where some real data in a hotel applies for the learning model. Our proposed algorithm with the learning model, which can dynamically update the optimum parameters, is envisaged to be utilized as a practical dynamic pricing strategy.

Average booking curves draw exponential functions

“…One of the advantages of the application is that it is industrially unlimited. Some forecasting or dynamic pricing applications that can be applied in various perishable asset industries have already been proposed 21 , 45 .…”

Cross-Industry Statistical Law: Average Booking Curves Draw Exponential Functions

“…One of the advantages of the application is that it is industrially unlimited. Some applications for forecasting or dynamic pricing that can be applied in various perishable asset industries have already been proposed [21,45].…”