Optimizing Pricing Strategies in E-commerce Supply Chain Management

Abstract

In the competitive realm of e-commerce, optimizing pricing strategies within supply chain man agement is essential for maximizing revenue while remaining competitive. This study provides a thorough analysis of pricing strategies using real-world data from various sources, with a focus on the Indian e-commerce landscape. We develop and apply mathematical optimization models to enhance pricing decisions by incorporating supply chain performance metrics, transaction data, merchant category classifications, and payment service provider (PSP) performance. The study demonstrates how both dummy values and actual data can be utilized to formulate and solve these models, offering insights into optimization under diverse market conditions. To understand the impact of variable changes on optimal pricing strategies, sensitivity analysis is employed. This approach helps identify how fluctuations in parameters affect pricing decisions and overall supply chain performance. The research emphasizes the importance of data-driven methods in refining pricing strategies within e-commerce. By applying mathematical models and analyzing real-world data, we provide actionable recommendations for improving decision-making processes in supply chain management. Our findings suggest that leveraging optimization techniques and incorporating performance metrics can significantly enhance revenue and competitive positioning. This study not only underscores the practical benefits of data-driven optimization but also serves as a valuable resource for businesses seeking to advance their pricing strategies in the dynamic e commerce environment. Through these insights, companies can achieve better alignment between pricing strategies and supply chain performance, leading to improved financial outcomes and opera tional efficiency.