Contextual Demand Elasticity Modelling and Competitive Pricing Intelligence: Reinforcement Learning for Dynamic Retail Price Optimisation

Authors

  • Andrés Herrera Professor of Industrial Engineering, Universidad de los Andes (UNIANDES)

Keywords:

contextual demand elasticity modelling, competitive pricing intelligence, reinforcement learning, dynamic retail price optimisation, machine learning

Abstract

Artificial intelligence (AI) technologies and machine learning algorithms have become increasingly relevant in recent retail experiences. They can help retailers of all sizes, especially online stores, create unique pricing strategies tailored to a specific product, customer segment, micro-segment, or contextual regulation. This essay outlines these pricing strategies and some real problems faced by enterprises.

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Published

31-12-2023

How to Cite

[1]
“Contextual Demand Elasticity Modelling and Competitive Pricing Intelligence: Reinforcement Learning for Dynamic Retail Price Optimisation”, Blockchain Tech. & Distributed Sys., vol. 3, no. 2, pp. 13–26, Dec. 2023, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/btds/article/view/843