Toronto Metropolitan University
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Data-Responsible Technology Solutions for Fit in Online Fashion Retail

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posted on 2024-08-30, 21:15 authored by Oluwatobi Oyenekan
<p>This study discusses the datafication processes and their ethical implications in the conduct of virtual try-on (VTO) technologies for fit in the online fashion industry, current practices in the business of VTO, and the physiological and psychological complications that are critical to shoppers' evaluation of fit and sizing. VTO solutions currently work by applying Augmented Reality technology or Artificial Intelligence to visualize the shopper digitally "wearing" the product to help the shopper evaluate garment fit. However, shopper satisfaction is impacted by augmentation quality and user control of access to user data. Furthermore, hedonic and utilitarian aspects of shopping are mediated by the shopper's inherent body satisfaction and technology acceptance; hence, shoppers do not always relate positively to a 3D visualization (avatar) of themselves. At the same time, research shows shoppers are impacted positively by images of model bodies similar to theirs and that while using an AR VTO, their perception of augmentation quality is impacted by the feeling that they have control over the access and use of their own data. A conceptual framework was developed for critical analysis to review the product quality, technical quality, and data handling practices of 3 main case studies, and a summary of findings was produced using thematic, content, and psychometric analysis. The research presents its results through practice-led research to document the activities and processes involved in the creative practice of the development of a prototype for a data-responsible alternative solution for fit comparison and evaluation in virtual try-on, to provide users total freedom to provide or withhold their data without implications to the quality of service.</p>

History

Language

English

Degree

  • Master of Digital Media

Program

  • Digital Media

Granting Institution

Toronto Metropolitan University

LAC Thesis Type

  • MRP

Thesis Advisor

Adrian Ma

Year

2023

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