Exploring Generation Z's Interaction With Voice Assistants in Online Shopping: A Multi-Method Approach

Abstract

The present study explores how Generation Z interacts with voice assistants and reacts to their product recommendations when shopping online. This research combines a self-report survey, the Zaltman Metaphor Elicitation Technique, and an eye-tracked product choice experiment, guided by the Technology Acceptance Model, the Media Richness Theory, and the Visual Attention Theory. This design captures the cognitive, emotional, and attentional processes influencing the intention of using voice assistants and the likelihood of following their product recommendations. The survey shows low intention to use voice assistants due to their concerns over perceived usefulness and ease of use. The Zaltman Metaphor Elicitation Technique supports these findings, revealing that while cognitive load for low-enjoyability products was reduced, skepticism persists in product categories where personal preferences and emotional connections are stronger. The product choice experiment further demonstrates that when voice assistants recommend products, those products attract greater visual attention (e.g., a higher number of fixations), especially for low-enjoyability items like detergent and drills. However, participants tend to rely on their own preferences for high-enjoyability products, such as bicycles and couches, despite engaging with the recommendations, as shown by the average fixation duration. These results suggest that voice assistants are most effective in assisting Generation Z's decision-making for products they have limited experience with or interest in. In contrast, recommendations have less impact when Generation Z has emotional or aesthetic preferences. The findings highlight that marketers should tailor voice assistants' recommendations by product category to increase Generation Z's engagement.