Implementing dynamic pricing across multiple pricing groups in real estate

The article presents a mathematical model of dynamic pricing for real estate that incorporates multiple pricing groups, thereby expanding the capabilities of existing models. The developed model solves the problem of maximizing aggregate cumulative revenue at the end of the sales period while meeting the revenue and sales goals. The basic formulation of the problem of optimizing revenue from the sale of all real estate objects in inventory by the end of the sales period is considered. Theoretical results describing the general form of the pricing policy for this problem are presented. A method is proposed for distributing aggregate cumulative revenue goals across different for real estate pricing groups. The model is further modified to account for the time value of money and the real estate value increase as construction progresses. The algorithm for constructing a pricing policy for multiple pricing groups is described, and numerical simulations are performed to demonstrate how the algorithm operates. The relevance of the developed model lies in the need to account for multiple pricing groups when forming the pricing policy, as well as the time value of money and the value of real estate increase as construction progresses. The obtained results can be applied to price management of real estate objects in practice.

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