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5.6 Thesis.AvaRambo
Embargoed Access, Embargo ends: 07/16/2028
Thesis
AI IN STYLE: ANALYZING GEN Z CONSUMERS’ PERCEIVED USE OF GAI CHATBOTS IN THE FASHION INDUSTRY
Master of Science (MS), Washington State University
2026
Abstract
This mixed-methods study examines how Generation Z consumers interact with generative artificial intelligence (GAI) chatbots in the context of fashion retail. Unlike traditional chatbots, GAI chatbots generate responses dynamically rather than relying on pre-programmed replies, enabling more natural and interactive engagement. Study One explores how consumers use GAI chatbots across hedonic and utilitarian product tasks to satisfy different needs, guided by the Uses and Gratifications (U&G) framework. Data were collected through focus group interviews with 17 participants and analyzed to identify key themes and subthemes. Findings revealed that cognitive, affective, and personal integrative needs were fulfilled through chatbot interaction, while social integrative and tension release needs were not. Personalized responses also emerged as a key factor enhancing the consumer experience.Study Two further investigates chatbot adoption using the U&G framework, with trust modeled as a mediating variable. Data were collected through an online survey, yielding 397 valid responses, and analyzed using partial least squares structural equation modeling (PLS-SEM). Results indicate that cognitive needs were the strongest predictor of trust, followed by personalized responses, while affective and tension release needs were not significant. Product type did not significantly influence chatbot trust.
These findings suggest that retailers can leverage GAI chatbot tools to enhance customer engagement, deliver personalized shopping experiences, and build trust, ultimately increasing adoption and purchase intention.
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Details
- Title
- AI IN STYLE: ANALYZING GEN Z CONSUMERS’ PERCEIVED USE OF GAI CHATBOTS IN THE FASHION INDUSTRY
- Creators
- Ava James Rambo
- Contributors
- Yini Chen (Advisor)Ting Chi (Committee Member)Sivasankari Gopalakrishnan (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Department of Apparel, Merchandising, Design and Textiles
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Number of pages
- 87
- Identifiers
- 99901393705801842
- Language
- English
- Resource Type
- Thesis