Dynamic Pricing Optimization Using Real-Time Demand Elasticity Modeling in Online Retail
Keywords:
Dynamic Pricing, Demand Elasticity Modeling, Artificial Intelligence in E-Commerce, Machine Learning for Pricing Optimization, Revenue Management, Online Retail AnalyticsAbstract
Dynamic pricing has become an essential strategy for online retailers seeking to remain competitive in rapidly evolving digital marketplaces. Advances in artificial intelligence and data analytics have enabled firms to utilize real-time information to optimize pricing decisions based on customer demand patterns. This study proposes a data-driven framework for dynamic pricing optimization using real-time demand elasticity modeling in online retail environments. The proposed methodology integrates demand forecasting, elasticity estimation, and revenue optimization within a unified analytical architecture. A simulated e-commerce dataset is used to evaluate the performance of the model under varying market conditions. Demand prediction is implemented through regression-based learning models, while elasticity parameters are incorporated into a revenue optimization function to identify optimal pricing levels. The results demonstrate that the proposed approach effectively captures the nonlinear relationship between price and demand and dynamically adjusts product prices to maximize revenue. Experimental simulations further show that the dynamic pricing framework outperforms traditional static pricing strategies by improving revenue generation and responding more efficiently to demand fluctuations. Additionally, the integration of machine learning with economic demand theory provides both predictive accuracy and interpretability in pricing decisions. The findings highlight the potential of artificial intelligence–driven pricing systems to enhance decision-making processes in online retail platforms. The proposed framework contributes to the development of intelligent pricing strategies capable of adapting to real-time market dynamics and improving profitability in competitive e-commerce environments.
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