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<p>With its unique advantages, computers are applied to various fields, and the garment industry is no exception. The study explores the role of computer-aided design technology in the apparel industry from the perspective of apparel design, production, and sales. We aim to evaluate the effect of computer technology on clothing design and production by constructing a clothing style migration model based on CycleGAN and evaluating its image style migration effect and aesthetic quality. Then, after completing the research design, we analyze the effect of virtual fitting rooms on consumers’ purchase intentions so as to support the role of computer technology in clothing sales. According to the findings, the clothing style migration model’s generated images are of excellent quality, with an average evaluation score of 6.68, and are acknowledged by nearly 80% of the respondents. All four characteristic elements of the virtual fitting room positively and significantly affect consumers’ purchase intention at the level of 0.01, and perceived risk and perceived value play a mediating role, which explains the process of generating consumers’ apparel purchase intention based on the virtual fitting room. Computer-aided design technology can be utilized effectively in apparel design to boost apparel sales and foster the transformation and advancement of the apparel industry.</p>
</abstract>

With its unique advantages, computers are applied to various fields, and the garment industry is no exception. The study explores the role of computer-aided design technology in the apparel industry from the perspective of apparel design, production, and sales. We aim to evaluate the effect of computer technology on clothing design and production by constructing a clothing style migration model based on CycleGAN and evaluating its image style migration effect and aesthetic quality. Then, after completing the research design, we analyze the effect of virtual fitting rooms on consumers’ purchase intentions so as to support the role of computer technology in clothing sales. According to the findings, the clothing style migration model’s generated images are of excellent quality, with an average evaluation score of 6.68, and are acknowledged by nearly 80% of the respondents. All four characteristic elements of the virtual fitting room positively and significantly affect consumers’ purchase intention at the level of 0.01, and perceived risk and perceived value play a mediating role, which explains the process of generating consumers’ apparel purchase intention based on the virtual fitting room. Computer-aided design technology can be utilized effectively in apparel design to boost apparel sales and foster the transformation and advancement of the apparel industry.

The transformative role of computer-aided design technology in innovation in the apparel industry

Shaanxi University of Science and Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With its unique advantages, computers are applied to various fields, and the garment industry is no exception. The study explores the role of computer-aided...

The transformative role of computer-aided design technology in innovation in the apparel industry

Data publikacji: 05 sie 2024

Zakres stron: -

Otrzymano: 14 kwi 2024

Przyjęty: 01 lip 2024

DOI: https://doi.org/10.2478/amns-2024-2230

Słowa kluczowe
Computer-aided design technology, CycleGAN, Multiple regression analysis, Style migration effect, Clothing industry

© 2024 Ning Sun et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

The transformative role of computer-aided design technology in innovation in the apparel industry

Data publikacji: 05 sie 2024

Zakres stron: -

Otrzymano: 14 kwi 2024

Przyjęty: 01 lip 2024

DOI: https://doi.org/10.2478/amns-2024-2230

Słowa kluczoweComputer-aided design technology, CycleGAN, Multiple regression analysis, Style migration effect, Clothing industry

© 2024 Ning Sun et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Computer-aided design technology, CycleGAN, Multiple regression analysis, Style migration effect, Clothing industry