Ananth Selvakumar
Papers
1
Total Citations
6
H-Index
1
About
Ananth Selvakumar is a forward-thinking researcher at the intersection of artificial intelligence and digital commerce, with a primary focus on dynamic pricing strategies and machine learning integration in e-commerce systems. His most cited work, "Dynamic Pricing Strategies Implementing Machine Learning Algorithms in E-Commerce" (2024), has garnered 6 citations and provides a critical assessment of how businesses can leverage computational intelligence to optimize real-time pricing decisions. Selvakumar’s major contribution lies in bridging the gap between theoretical machine learning models and practical e-commerce applications, offering frameworks that enable companies to maintain competitiveness while maximizing revenue. His research addresses the pressing challenge of algorithmic pricing in rapidly evolving digital marketplaces, exploring how adaptive systems can respond to consumer behavior, market trends, and competitor actions. By examining the implementation of machine learning for dynamic pricing, Selvakumar has laid groundwork for more sophisticated, data-driven commerce strategies. His work is particularly valuable for students and researchers interested in the practical deployment of AI in business contexts, demonstrating how computational methods can transform traditional pricing models into intelligent, responsive systems that drive both efficiency and profitability in modern e-commerce environments.
Research Focus
Key Achievements
Top Papers
- 1