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dc.contributor.author | Syed Muhammad Baqar Ali Shah, 01-321232-044 | |
dc.date.accessioned | 2025-04-24T09:37:03Z | |
dc.date.available | 2025-04-24T09:37:03Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | http://hdl.handle.net/123456789/19434 | |
dc.description | Supervised by Dr. Muhammad Usman | en_US |
dc.description.abstract | The growth of e-commerce in Pakistan presents both opportunities and challenges for enhancing consumer experiences and driving purchase intentions. This thesis explores the relationships among Customer Engagement (CE), AI-Driven Personalization (AIP), Privacy Concerns (PC), and Purchase Intention (PI) within Pakistan’s digital marketplace. Utilizing a quantitative approach, data were collected from e-commerce users in Rawalpindi and Islamabad through structured surveys and analyzed using Structural Equation Modeling (SEM). Results indicate that Customer Engagement significantly and positively influences both AI-Driven Personalization (path coefficient = 0.835, p < 0.001) and Purchase Intention (path coefficient = 0.626, p < 0.001). However, AI-Driven Personalization alone does not significantly impact Purchase Intention (path coefficient = 0.033, p = 0.360). Privacy Concerns exhibit a dual moderating role by negatively moderating the relationship between AI-Driven Personalization and Purchase Intention (path coefficient = -0.254, p < 0.001) and positively moderating the relationship between Customer Engagement and Purchase Intention (path coefficient = 0.195, p = 0.002). Additionally, demographic factors such as gender, age, and income significantly influence perceptions of personalization, privacy concerns, and purchase intentions. The study contributes to the theory by positioning Customer Engagement as a key driver of personalization and expanding the Privacy Calculus Model to capture its complex role in consumer behavior. Practically, it offers actionable insights for e-commerce practitioners, emphasizing the need for integrated engagement and personalization strategies, robust data protection measures, and tailored approaches for diverse demographic segments. Despite its valuable contributions, the study is limited by its cross-sectional design and geographical focus, suggesting future research should employ longitudinal designs and broader geographic sampling. Ultimately, this thesis underscores the importance of balancing personalized consumer experiences with privacy protections to foster trust and drive sustainable growth in Pakistan’s competitive e-commerce landscape. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Business Studies | en_US |
dc.relation.ispartofseries | MBA (Mkt);T-11795 | |
dc.subject | Customer Engagement | en_US |
dc.subject | Purchase Intention | en_US |
dc.subject | AI-Driven Personalization | en_US |
dc.title | Customer Engagement and Purchase Intention: The Mediating Role of AI-Driven Personalization and the Moderating Effect of Privacy Concerns in E-commerce | en_US |
dc.type | Thesis | en_US |