Saima Batool

Work place: Institute of Computing, Muhammad Nawaz Sharif University of Agriculture, Multan, Pakistan

E-mail: naqvi3083@gmail.com

Website: https://orcid.org/0009-0007-6959-642X

Research Interests:

Biography

Saima Batool is currently working as a computer Lecturer at Concordia College Lahore from January 2025. She received BS in computer science from University of Agriculture Multan in 2022, MS computer science from Muhammad Nawaz Sharif University of Agriculture Multan. She has done research work in the field of machine learning and IoT. Her research interests include IoT, Machine Learning, Block chain, and Deep Learning.

Author Articles
Analyzing the Impact of Artificial Intelligence on Shaping Consumer Demand in E-Commerce: A Critical Review

By Asif Raza Salahuddin Ghazanfar Ali Muhammad Hanif Soomro Saima Batool

DOI: https://doi.org/10.5815/ijieeb.2025.05.04, Pub. Date: 8 Oct. 2025

The surge in scholarly articles on e-Commerce mirrors its rapid ascent in the market's legitimacy. According to customer product recommendation theory, e-Commerce research may exhibit a bias toward specific customer product recommendations due to its evolving nature. To address this concern, this study examines five of the leading e-Commerce journals. The findings reveal a predominant focus on two main groups: customers and the integration of artificial intelligence (AI) in e-commerce recommendation systems. However, there is a notable lack of attention toward other critical groups, such as suppliers, indirect stakeholders, investors, and regulators. With e-Commerce continuing to mature, it is crucial to explore these neglected themes, sectors, and entities. This paper identifies gaps in current research through targeted keyword searches by aiming to bring these overlooked areas to the forefront. By highlighting persisting challenges in e-Commerce research, this study seeks to raise discourse and innovation in the field by ensuring that emerging topics are not overlooked. The role of AI in e-Commerce, particularly in the development of advanced recommendation systems, is identified as a key area shaping consumer experiences and market dynamics.

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