AI-Driven Dynamic Pricing Models for E-commerce: Balancing Profitability and Consumer Fairness
AI-Driven Dynamic Pricing Models for E-commerce: Balancing Profitability and Consumer Fairness
Authors:
Dr. Suresh Kurumalla¹, Dr. Kasa Ravindra2, Muriki Sathvika 3
¹Professor, Department of Computer Science and Engineering, St. Martin’s Engineering College, Hyderabad, India, kurumallasuresh@gmail.com
2Professor&Director, Department of Electronics and Communication Engineering,St. Martin’s Engineering College, Hyderabad, India,drkasaravindra@gmail.com
3Student, Department of Computer Science and Engineering, St. Martin’s Engineering College, Hyderabad, India,murkisathvika@gmail.com
Abstract
Dynamic pricing has become a fundamental strategy in modern e-commerce platforms to maximize revenue and respond to rapidly changing market conditions. However, traditional pricing mechanisms often focus primarily on profitability, sometimes overlooking issues related to consumer fairness and transparency. This paper proposes an AI-driven dynamic pricing model that aims to balance profitability for businesses while ensuring fair pricing for consumers. The proposed system utilizes machine learning algorithms to analyze multiple factors such as customer demand, competitor pricing, purchasing behavior, seasonal trends, and inventory levels to dynamically adjust product prices in real time.
In addition to optimizing revenue, the model incorporates fairness-aware constraints that prevent excessive price fluctuations and discriminatory pricing practices. By integrating predictive analytics and fairness metrics, the system ensures that pricing strategies remain competitive while maintaining consumer trust. The study evaluates the effectiveness of the proposed model using simulated e-commerce datasets and performance metrics such as revenue growth, price stability, and fairness indicators. Experimental results demonstrate that the AI-driven approach can significantly improve pricing efficiency while maintaining balanced and transparent pricing decisions. The findings highlight the potential of combining artificial intelligence with ethical considerations to develop sustainable and consumer-friendly dynamic pricing systems for modern e-commerce platforms.
Keywords: Dynamic Pricing, Artificial Intelligence, Machine Learning, E-commerce, Consumer Fairness, Price Optimization, Demand Prediction, Algorithmic Fairness, Real-Time Pricing.