• Journal of Fashion Business
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• 제26권2호
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• pp.28-47
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• 2022

Rapid development of information and communication technology is leading the digital transformation (hereinafter, DT) of various industries. At this point in rapid online transition, fashion manufacturers operating offline-oriented businesses have become highly interested in DT and artificial intelligence (hereinafter AI), which leads DT. The purpose of this study is to examine the development status and application case of AI-based digital technology developed for the fashion industry, and to examine the DT stage and AI application status of domestic fashion manufacturers. Hence, in-depth interviews were conducted with five domestic IT companies developing AI technology for the fashion industry and six domestic fashion manufacturers applying AI technology. After analyzing interviews, study results were as follows: The seven major AI technologies leading the DT of the fashion industry were fashion image recognition, trend analysis, prediction & visualization, automated fashion design generation, demand forecast & optimizing inventory, optimizing logistics, curation, and ad-tech. It was found that domestic fashion manufacturers were striving for innovative changes through DT although the DT stage varied from company to company. This study is of academic significance as it organized technologies specialized in fashion business by analyzing AI-based digitization element technologies that lead DT in the fashion industry. It is also expected to serve as basic study when DT and AI technology development are applied to the fashion field so that traditional domestic fashion manufacturers showing low growth can rise again.

• Journal of the Korean Society of Clothing and Textiles
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• 제47권4호
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• pp.743-759
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• 2023

Collaboration between AI and fashion designers is becoming essential. Thus, this study explored (1) 321 consumer responses to fashion designers, comparing their capabilities and product quality across different designer types, (2) the relationship between designer capabilities and perceived product quality, and (3) the moderating role of AI knowledge in the effect of capabilities on perceived product quality. Data were analyzed using EFA, ANOVA, regression, and moderation analysis. The results indicated that subjects perceived human designers as having higher capabilities and perceived product quality than AI designers. All subjects' perceived creativity and empathy significantly impacted the perceived functionality, aesthetics, and symbolism-sociality of clothing. Additionally, the perceived creativity of AI and human+AI designers, and the perceived empathy of human and human+AI designers, significantly influenced the perceived functionality and symbolism-sociality, but the perceived creativity of human designers and empathy of AI designers did not directly impact perceived functionality and symbolism-sociality. Moreover, perceptions of the designers' capabilities significantly aesthetics in all subjects. Furthermore, low levels of perceived consumer AI knowledge enhanced the positive impact of perceived human+AI designers' creativity and empathy on perceived functionality and aesthetics. The study suggests that fashion companies should refrain from revealing AI designers at this time.

• Journal of Fashion Business
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• 제28권4호
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• pp.129-148
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• 2024

With the advent of the 4th industrial era and the development of digital technologies such as artificial intelligence (AI), metaverse, 3D printing, and 3D virtual wearing systems, the fashion industry continues to attempt to use digital technology and introduce it into various areas. The purpose of this study was to determine whether fashion and digital technology could be combined to create works and to suggest ways to apply digital technology in the fashion industry. As a research method, image generative AI, Midjourney was applied to the initial design ideation stage to derive inspiration images. 3D printing technique was then introduced as a production method to print fashion jewelry. As a result of the research, a total of six jewelry designs printed with a 3D printer were developed. One necklace, one bracelet, three earrings, and one ring were developed. This study identified the possibility of applying digital technology to real fashion jewelry design products by designing jewelry based on inspirational images derived from image generation AI and producing pieces of fashion jewelry with 3D modeling tasks and 3D printing outputs. This study is significant in that it expands the expression area of fashion jewelry design that combines digital technology.

• Journal of Fashion Business
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• 제28권3호
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• pp.122-139
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• 2024

Image-generated AI is rapidly emerging as a powerful tool to augment human creativity and transform the art and design process through deep learning capabilities. The purpose of this study was to propose and demonstrate the feasibility of a new design development method that combined traditional design methods and technology by constructing image-generated AI prompts based on artists' formative elements. The study methodology consisted of analyzing Kazmir Malevich's theoretical considerations and applying them to AI prompts for design, print pattern development, and 3D digital design. This study found that the suprematist works of Kazmir Malevich were suitable as design and print pattern prompts due to their clear geometric shapes, colors, and spatial arrangement. The AI-prompted designs and print patterns produced diverse results quickly and enabled an efficient design process compared to traditional methods, although additional refinement was required to perfect the details. The AI-generated designs were successfully produced as 3D garments, thereby demonstrating that AI technology could significantly contribute to fashion design through its integration with artistic principles. This study has academic significance in that it proposes a prompt composition method applicable to fashion design by combining AI and artistic elements. It also has industrial significance in that it contributes to design innovation and the implementation of creative ideas by presenting an AI-based design process that can be practically applied.

• Journal of Fashion Business
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• 제27권4호
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• pp.141-162
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• 2023

With the prospect that integrating creative AI in the fashion design field will become more visible, this study considered the case of creative fashion design development through Human-AI Co-creation (HAIC). Methodologically, this research encompasses a literature review and empirical investigations. In the literature review, the fashion design and creative HAIC processes, and the possibilities of integrating AI in fashion design were considered. In the empirical study, based on the case analysis of generating fashion design through HAIC, the HAIC type according to the role and interaction method, and characteristics of humans and AI was considered, and the HAIC process for fashion design was derived. The results of this study are summarized as follows. First, HAIC types in fashion design are divided into four types: AI-driven passive HAIC, human-driven passive HAIC, flexible interaction-based HAIC, and integrated interaction-based value creation HAIC. Second, the stages of the HAIC process for creative fashion design can be broadly divided into semantic data integration, visual ideation, design creation and expansion, design presentation, and design/manufacturing solution and UX platform creation. Third, in fashion design, HAIC contributes to human ability, enhancement of creativity, achievement of efficient workflow, and creation of new values. This research suggests that HAIC has the potential to revolutionize the fashion design industry by facilitating collaboration between humans and AI; consequently, enhancing creativity, and improving the efficiency of the design process. It also offers a framework for understanding the different types of HAIC and the stages involved in the creative fashion design process.

• Journal of Fashion Business
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• 제26권1호
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• pp.1-15
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• 2022

Digital transformation has induced changes in human life patterns; consumption patterns are also changing to digitalization. Entering the era of industry 4.0 with the 4th industrial revolution, it is important to pay attention to a new paradigm in the fashion industry, the shift from developer-centered to user-centered in the era of the 3rd industrial revolution. The meaning of storing users' changing life and consumption patterns and analyzing stored big data are linked to consumer sentiment. It is more valuable to read emotions, then develop and distribute products based on them, rather than developer-centered processes that previously started in the fashion market. An AI(Artificial Intelligence) deep learning algorithm that analyzes user emotion big data from user experience(UX) to emotion and uses the analyzed data as a source has become possible. By combining AI technology, the fashion industry can develop various new products and technologies that meet the functional and emotional aspects required by consumers and expect a sustainable user experience structure. This study analyzes clear and useful user experience in the fashion industry to derive the characteristics of AI algorithms that combine emotions and technologies reflecting users' needs and proposes methods that can be used in the fashion industry. The purpose of the study is to utilize information analysis using big data and AI algorithms so that structures that can interact with users and developers can lead to a sustainable ecosystem. Ultimately, it is meaningful to identify the direction of the optimized fashion industry through user experienced emotional fashion technology algorithms.

• Fashion & Textile Research Journal
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• 제23권3호
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• pp.337-346
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• 2021

In the fourth industrial revolution, fashion students are expected to work with various technologies to show creativity. This study aimed to conduct project-based learning(PBL) in collaboration with industry experts to design and operate artificial intelligence(AI) in the practice subject of fashion curation through the industrial academic teaching method. We first looked at teaching methods and strategies incorporating PBL in various academic fields. Next, we analyzed fashion projects and fashion curation services applying AI. Then through the question-and-answer method and by consulting with industry experts, we developed a curriculum for AI fashion curation, applying PBL(fashion market and trend analysis; new styles and time, place, and occasion planning; AI machine learning data set production; curation model development; and evaluation) suitable for the university's educational environment, information technology company conditions, and fashion students. As part of a close cooperation system with the industry, we conducted a 15-week Fashion Project II (Capstone Design) course and evaluated the outcomes and student satisfaction with the course. Students were able to develop new style, and time, place, and occasion categories and to utilize strategies for AI fashion curation services reflecting the unique needs of Millennials and Generation Z. Students showed high satisfaction with the curriculum. Further, it was confirmed that the study successfully applied PBL in class using AI technology in fashion education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.676-691
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• 2022

An increasing number of companies in the fashion industry are using AI curation services. The purpose of this study is to investigate perceptions of and intentions to use AI fashion curation services among customers by using text mining. To accomplish this goal, we collected a total of 34,190 online posts from two Korean portals, Naver and Daum. We conducted frequency analysis to identify the most frequently mentioned keywords using Textom. The analysis extracted "various," "good," "many," "right," and "new" at the highest frequency, indicating that consumers had positive perceptions of AI fashion curation services. In addition, we conducted a semantic network analysis with the top-50 most frequently used keywords, classifying customers' perceptions of AI fashion curation services into three groups: shopping, platform, and business profit. We also identified the factors that boost continuous use intentions: usability, usefulness, reliability, enjoyment, and personalization. We conclude this paper by discussing the theoretical and practical implications of these findings.

• Journal of the Korean Society of Clothing and Textiles
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• 제47권4호
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• pp.666-683
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• 2023

This research aims to develop based clothing design process tailored to the industry-university collaborative setting and apply it in a fashion design class. into three distinct phases: designing and organizing our fashion design class, conducting our class at a university, and gathering student feedback. First, we conducted a literature review on employing new technologies in traditional clothing design processes. We consulted with industry professionals from the Samsung C&T Fashion Group to develop an AI-based clothing design process. We then developed in-class learning activities that leveraged fashion brand product databases, a supervised learning AI model, and operating an AI-based Creativity Support Tool (CST). Next, we setup an industry-university fashion design class at a university in South Korea. Finally, we obtained feedback from undergraduate students who participated in the class. The survey results showed a satisfaction level of 4.7 out of 5. The evaluations confirmed that the instructional methods, communication, faculty, and student interactions within the class were both adequate and appropriate. These research findings highlighted that our AI-based clothing design process applied within the fashion design class led to valuable data-driven convergent thinking and technical experience beyond that of traditional clothing design processes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2867-2881
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• 2022

This study investigates fashion Artificial Intelligence (AI) curation services to expand sustainable consumption. We analyzed the factors that affect the AI fashion curation service experience of women in their 20s and 30s using their clothes. An online survey was conducted from March 29, 2021, to June 4, 2021, for women of the previously mentioned age groups residing in the metropolitan area. Before answering the questionnaire, they installed the "Style Bot" application on their phone, took five or more photos of their clothes according to the manual provided by the application, stored them in a virtual wardrobe on the application, and then responded to the questionnaire using the AI recommended coordinating function. The effect of the properties of fashion AI curation service application on the use of clothes was investigated. Among the attributes of the fashion AI curation service application, convenience, speed, and usefulness were found to have a positive effect on the use of clothes, and promptness had no effect. Second, regarding the impact of clothing utilization on environmental sustainability, clothing utilization was found to have a positive effect on environmental sustainability. Third, environmental sustainability was found to have a positive effect on satisfaction. Fourth, clothing utilization had a positive effect on satisfaction. Thus, fashion AI curation service would help promote service development so that clothes could be used actively through an in-depth understanding of the properties of these services. Finally, the results of this study would contribute to promoting environmental sustainability.