This track focuses on the application of big data analytics techniques to enhance decision-making in e-commerce. It aims to explore innovative methodologies that leverage large datasets for improved business outcomes.

This session will delve into the analysis of consumer behavior through big data applications. Researchers are invited to present studies that reveal insights into purchasing patterns and preferences.

This track emphasizes the use of predictive modeling techniques to forecast trends and consumer behavior in e-commerce. Contributions should highlight methodologies that drive strategic business decisions.

This session will explore the role of personalization in enhancing customer experiences in online retail. Papers should discuss the implementation of personalized marketing strategies using big data.

This track investigates the integration of artificial intelligence technologies in e-commerce platforms. Submissions should focus on AI-driven solutions that optimize operations and enhance customer engagement.

This session will cover the development and effectiveness of recommendation systems in e-commerce. Researchers are encouraged to present findings on how these systems influence consumer choices and satisfaction.