Implementing Dynamic Pricing Across Multiple Pricing Groups in Real Estate

TL;DR

This paper develops a mathematical model for dynamic real estate pricing across multiple groups, optimizing revenue while considering time value and property appreciation, with demonstrated numerical simulations.

Contribution

Introduces a novel dynamic pricing model for real estate with multiple groups, including a revenue distribution method and algorithms for pricing policy construction.

Findings

Effective revenue maximization across multiple pricing groups

Incorporates time value of money and property appreciation

Numerical simulations validate the proposed algorithms

Abstract

This article presents a mathematical model of dynamic pricing for real estate (RE) 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. A method is proposed for distributing aggregate cumulative revenue goals across different RE 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.