Personalization and Consumer Behavior in Digital Marketing
Permanent URI for this collectionhttps://hdl.handle.net/10125/112515
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Item type: Item , Tool, Assistant, or Advisor? Consumer Experience across Modalities in AI-Powered Product Search(2026-01-06) Liu, Weizi; Ma, Lizi; Yao, MikeThis study investigates how different AI-powered search interface designs—traditional keyword search, AI-generated summaries, and conversational agents—influence users’ mental representations of AI and their subsequent evaluations and behaviors. Across an experimental design involving 345 participants, we found that interface modality significantly shaped how users conceptualized the AI system's role. Cluster analyses revealed three distinct user types with divergent expectations and evaluative priorities (e.g., as a tool, assistant, or advisor). These perceived roles, in turn, moderated how traditional usability constructs—perceived usefulness, ease of use, and control—predicted decision confidence and purchase intention. These factor are weighted differently within each cluster. Our findings show that interface design actively constructs interaction realities that guide technology acceptance and consumer behavior. We discuss implications for adaptive interface design and the ontological framing of AI in user experience.Item type: Item , Millionaire Shoppers’ Struggles? Exploring User Experiences with Ultra-Low-Cost E-Commerce Platforms through Text Mining(2026-01-06) Jo, Gi Jun; Nam, Kwang Min; Choi, HanbyulThis study empirically analyzes consumer sentiment and behavior from user-generated reviews of ultra-low-cost e-commerce platforms, Temu and AliExpress. Using a Gated Recurrent Unit (GRU) model, reviews were classified as either positive or negative, while Latent Dirichlet Allocation (LDA) was employed to extract key thematic structures. A multiple regression analysis examined the influence of topics on review ratings, identifying structural links between emotions and evaluations. Results show that “delivery speed and convenience”, “value-for-money”, and “shopping convenience” drove positive sentiment. Conversely, “excessive marketing”, “system instability”, and “perceived quality issues” led to negative evaluations. Notably, the emergence of “ggang culture”—impulsive bulk buying followed by disposal—highlights a shift toward emotionally driven, irrational consumption behavior. This study contributes to quantifying the sentiment-topic-rating relationship, offering valuable implications for Chinese ultra-low-cost e-commerce expansion.Item type: Item , Navigating the Paradox: The Dynamic AI Trust Framework for Ethical Persuasion in Digital Marketing(2026-01-06) Broady, Lora LouiseGenerative Artificial Intelligence (GenAI) is reshaping digital marketing by enabling more personalized content and persuasive user experiences at scale. While these capabilities offer significant value to marketers, they also heighten consumer concerns about data privacy, algorithmic transparency, and the authenticity of AI-generated content. This paper introduces the Dynamic AI Trust Framework, a conceptual model that explores how GenAI’s persuasive functions interact with consumer trust and privacy perceptions in digital environments. The framework outlines five interrelated dimensions — algorithmic transparency, user control and agency, data sourcing and security, fairness and bias mitigation, and authenticity and disclosure — as critical components for designing trustworthy and ethical AI-driven marketing strategies. By clarifying how these dimensions operate in practice, the framework provides a foundation for balancing innovation with responsibility, helping brands engage consumers more effectively while respecting their evolving expectations around data and trust.Item type: Item , Introduction to the Minitrack on Personalization and Consumer Behavior in Digital Marketing(2026-01-06) Schau, Hope; Key, Martin; Akaka, Melissa