Effectiveness of AI-Based Personalized Recommendations in Reducing Choice Overload on E-Commerce Platforms

Hu, Mengdie (2025) Effectiveness of AI-Based Personalized Recommendations in Reducing Choice Overload on E-Commerce Platforms. Masters thesis, Dublin, National College of Ireland.

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Abstract

The rapid growth of e-commerce platforms has given consumers opportunities to access an extensive range of options, which can sometimes lead to a phenomenon named choice overload. It means when individuals are faced with an abundance of choices, they will find it difficult to make decisions. This study will examine how AI-based personalized recommendation systems can help people reduce this situation during the online shopping experience. The recommendation system can greatly save decision time and improve the user experience by customizing suggestions based on users' behaviors, preferences, and interactions. The research will adopt a quantitative methodology, collecting data through online surveys. This study will explore metrics like the time it takes to make decisions, how satisfied users are, and the key factors influencing their choices. The findings are expected to contribute valuable insights to existing research on AI in consumer behavior and offer practical recommendations for e-commerce platforms to enhance their recommendation systems.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Tan, Eileen UNSPECIFIED
Uncontrolled Keywords:	AI; Recommendation system; Choice overload; E-commerce
Subjects:	Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence H Social Sciences > HF Commerce > Marketing > Consumer Behaviour H Social Sciences > HF Commerce > Electronic Commerce
Divisions:	School of Business (- 2025) > Master of Science in Management
Depositing User:	Ciara O'Brien
Date Deposited:	09 Jan 2026 14:24
Last Modified:	09 Jan 2026 14:24
URI:	https://norma.ncirl.ie/id/eprint/9082

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