Browsing by Author "Chang, Hyo Jung (TTU)"
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Item An Exploration of Transformative Learning Applied to the Triple Bottom Line of Sustainability for Fashion Consumers(2023) Chang, Hyo Jung (TTU); Rakib, Nasir; Min, JaehanGrowing awareness and concern about sustainability worldwide has drawn attention to the sustainability practices of the textile and apparel industry and its consumers. In particular, educating consumers about sustainability becomes more important as it can increase their sustainability awareness and prompt action. Therefore, based on the transformative learning theory, this study was designed to explore the current knowledge of sustainability of Generation Z fashion consumers by observing and analyzing a focus group discussion. A qualitative research method was used, twenty participants in four focus groups participated, and two activities were implemented during the focus group sessions in this study. A thematic analysis was used to interpret the qualitative transcribed data. Five themes emerged from the focus group discussion, including Normalizing Customer Activism, Short-Sighted Actions, Story Sharing with Others, Filling the Information Gap, and Challenging but Not Impossible. The results show that consumers have a limited understanding of sustainability, i.e., they are primarily concerned about the environmental aspect of sustainability. However, the knowledge and discussion extracted through video and website browsing led to transformative learning among the participants, thereby changing their understanding of sustainability from a predominantly environmental perspective to one that encompasses social aspects. In addition, after this learning process, fashion consumers can perceive sustainability more holistically as a balance of the three aspects of sustainability. The findings of this study can be applied to inform educational programs and create opportunities for reframing marketing strategies by leveraging various technological platforms.Item Body size measurement using a smartphone(2021) Foysal, Kamrul Hasan (TTU); Chang, Hyo Jung (TTU); Bruess, Francine (TTU); Chong, Jo Woon (TTU)Measuring body sizes accurately and rapidly for optimal garment fit detection has been a challenge for fashion retailers. Especially for apparel e-commerce, there is an increasing need for digital and convenient ways to obtain body measurements to provide their customers with correct-fitting products. However, the currently available methods depend on cumbersome and complex 3D reconstruction-based approaches. In this paper, we propose a novel smartphone-based body size measurement method that does not require any additional objects of a known size as a reference when acquiring a subject’s body image using a smartphone. The novelty of our proposed method is that it acquires measurement positions using body proportions and machine learning techniques, and it performs 3D reconstruction of the body using measurements obtained from two silhouette images. We applied our proposed method to measure body sizes (i.e., waist, lower hip, and thigh circumferences) of males and females for selecting well-fitted pants. The experimental results show that our proposed method gives an accuracy of 95.59% on average when estimating the size of the waist, lower hip, and thigh circumferences. Our proposed method is expected to solve issues with digital body measurements and provide a convenient garment fit detection solution for online shopping.