Date of Award

2026

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Library and Information Science

First Advisor

Dr. Qiping Zhang

Second Advisor

Dr. Alireza Ebrahimi

Third Advisor

Dr. Greg Hunter

Abstract

This study delves into the complexities of integrating Artificial Intelligence (AI) into e- commerce, exploring its profound impact on marketing strategies, customer personalization, and decision-making processes. As AI technology rapidly becomes a staple in digital commerce, businesses encounter formidable challenges. These include the hurdles of seamlessly implementing sophisticated AI personalization tools, safeguarding consumer privacy amidst growing ethical concerns, and the daunting task of adhering to evolving regulatory standards. This study aimed to explore how AI-driven personalization influences customer engagement in e-commerce environments. It examined technologies such as recommendation systems and personalized marketing, analyzing their relationship on user interaction. This study adopted a mixed-methods approach to examine AI-powered personalization in e-commerce from both user and policy perspectives. Quantitative data were collected through an online survey, targeting participants with recent online shopping experience and familiarity with AI-driven personalization features. A total of 199 valid responses were analyzed. Qualitative content analysis was carried out to examine how different regulatory frameworks: GDPR (EU), CPRA/CCPA (California, USA), and PIPL (China) address ethical concerns related to AI in e-commerce. A structured coding scheme, based on widely recognized ethical AI principles such as transparency, accountability, fairness, privacy, autonomy, and reliability, was applied to the selected legal provisions. The findings of this study show that AI-powered personalization in e-commerce improves aspects of the user experience, particularly in terms of recommendation quality and convenience. However, it has only a limited and statistically non-significant impact on purchase frequency and user engagement, suggesting that personalization alone is not sufficient to drive long-term customer interaction. The study also identified key ethical concerns associated with AI personalization, with privacy and data breach risks emerging as the most significant issues. Users expressed concerns about how their data is collected, used, and protected, as well as a lack of transparency in how AI systems generate recommendations. Algorithmic bias was also recognized as a concern, highlighting the need for fairness and accountability in AI systems. From a policy perspective, the analysis revealed that while global regulatory frameworks (GDPR, CPRA/CCPA, and PIPL) addressed similar ethical challenges, they differed in their scope and emphasis. Accountability and transparency are consistently emphasized across all frameworks, while GDPR provides the most comprehensive and balanced approach. PIPL places stronger emphasis on privacy and control, whereas CPRA/CCPA focuses more on consumer rights and procedural protections. This research can guide e-commerce companies and policymakers in understanding how AI powered personalization can enhance processes and interact with consumers. It aims to bridge the gap between theory and practice, providing a deeper understanding of AI's potential in e-commerce. The study helps stakeholders navigate the complexities of digital transformation in the retail sector.

Download

Share

COinS