Merchandising/Marketing/Retailing: Management

Privacy Fatigue: AI-powered 3D Visualization Services

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Abstract

This study explores the impact of privacy concerns on consumer behavior toward AI-powered 3D visualization services in fashion retail. Using the extended Concerns for Information Privacy (CFIP) model and Privacy Calculus Theory (PCT), it examines how privacy concerns, including data collection, errors, secondary use, and improper access, influence privacy fatigue—emotional exhaustion and cynicism—and perceived risks. The study also assesses how digital privacy literacy moderates these relationships. Data from 510 U.S. consumers were analyzed using PLS-SEM. Results indicate that privacy concerns about data collection and errors significantly increase emotional exhaustion and cynicism, while concerns about secondary use elevate perceived risks. Emotional exhaustion amplifies perceived risks, which negatively affect adoption intentions. Additionally, digital privacy literacy reduces the impact of emotional exhaustion on perceived risks and mitigates the link between perceived risks and adoption intentions. These findings emphasize the importance of transparent and ethical data management practices to alleviate consumer privacy concerns and support the adoption of AI-driven services.

Keywords: privacy concern, privacy fatigue, AI-powered service, 3D visualization

How to Cite:

Swazan, I., Youn, S. & Rana, M., (2025) “Privacy Fatigue: AI-powered 3D Visualization Services”, International Textile and Apparel Association Annual Conference Proceedings 81(1). doi: https://doi.org/10.31274/itaa.18623