Fashion and Textiles最新文献

The purpose of this study is to identify the entry conditions that could form a co-evolutionary relationship between a sewing contractor company and a fashion brand, and reveal the outcome of such a relationship. In the Republic of Korea, many fashion brands and sewing companies coexist, and the situation in the fashion industry changes with the rapid development of the country, so it is a suitable environment for investigating their co-evolution strategies. A qualitative research methodology was used to examine the co-evolution process of the fashion brand and the sewing industry. In addition, an objective evaluation was conducted by using interviews with sewing contractor companies and fashion brands that have business relationships with the sewing contractor companies. The results indicated that sewing contractor companies evolve into either mass production or small production systems. In the co-evolutionary process, relational resources and business-to-business transaction suitability are the main entry conditions for sewing contractor companies to coevolve with fashion brands. Knowledge exchange, experience optimization, off-season ordering, and investment in trading companies were observed among sewing contractor companies that formed a co-evolutionary relationship with their fashion brand partners. This study identified and conceptualized factors that played a major role in the process of co-evolution and proved suitable for each production system of sewing contractor companies.

In the realm of retailing, various methods of product presentation exert a significant influence on consumers' perceptions and behaviors. In the context of fashion retailing, one crucial aspect of presentation revolves around outfit coordination (OC), which can be displayed in either an assembled or unassembled manner. Assembled OC entails displaying fashion items collectively on a body, while unassembled OC involves presenting them individually on a flat background. Drawing from the literature on the Elaboration Likelihood Model of attention, this research explores the impact of assembled versus unassembled OC on consumers' imagery elaboration, attention, and product evaluations, employing three online experiments. In the first study (N = 126), we demonstrate that assembled OC, in contrast to unassembled OC, fosters greater imagery elaboration and elicits more positive product evaluations. Building upon these findings, the second study (N = 214) employs a serial mediation analysis to unveil the underlying mechanism involving shifted attention. The third study (N = 182) explores the moderating effect of fashion involvement, revealing that for consumers with a high level of fashion involvement, unassembled OC, rather than assembled OC, leads to higher levels of imagery elaboration and more favorable product evaluations. This research not only enriches the literature on online retailing and visual communication, but also provides actionable insights for industry practitioners on effectively presenting fashion products to online shoppers.

Ultraviolet resistance upon four different types of weft knitted fabrics including Lacoste, Single Jersey, Rib and Interlock were experimentally measured and evaluated by ultraviolet–visible spectroscopy under effects of gauge, specific weight, fiber composition and finishing agent as benzotriazole derivatives. The results showed that ultraviolet protection factor (UPF) of Interlock sample reached the highest value at 42.7. Simultaneously, the higher gauge of Single Jersey knitted fabrics was, the better its ultraviolet protection exhibited. Also, insertion of polyester fibers or spandex fibers into cotton knitted fabrics with a certain ratio strongly increased UPF values. Notably, all UPFs of coated fabrics with a given content of benzotriazole were significantly improved and almost coated samples could undergo several washing cycles and still retain their inherent breathability. This work demonstrated that cotton knitted fabrics coated with benzotriazoles were excellently enhanced ultraviolet protection. Especially, the UPF values on Interlock or Rib specimens as well as Single Jersey samples blended with polyester/spandex fibers were found to be higher than 15.

The purpose of this study is to investigate Thai, Vietnamese and Indonesian consumers’ responses to cross-border online shopping for Korean fashion products using 3D virtual fitting technology. In order to examine the factors affecting a consumer’s attitude toward virtual fitting technology and the purchase intention of Korean fashion products, technology acceptance model, which represents cross-border site characteristics, and technology readiness, which represents a consumer's belief in technology, were used in combination with technology readiness and acceptance model. An online survey was conducted with male and female consumers in their 20 s and 30 s residing in Vietnam, Indonesia, and Thailand. A structural equation model analysis was performed using smart PLS to verify the research model. Among the dimensions of technological readiness, optimism and innovativeness had a positive effect on consumers' perceptions of the cross-border site, and discomfort had a negative effect. Perceived usefulness, enjoyment, and perceived fit had a significant effect on the attitude toward virtual fitting technology, and the effect of enjoyment was the greatest. This study highlighted the role of each dimension of technology readiness by verifying consumer acceptance of virtual fitting technology in cross-border online transactions. It also emphasized the role of perceived enjoyment in technology acceptance.

This study aimed to address the diversity issue in fashion design education by developing two prototypes for Inclusive Fashion Design (IFD) education. The prototypes were constructed based on the 3C3R model of Project-Based Learning (PBL) and incorporated the Persona/Scenario (P/S) toolkit for IFD. Additionally, the study examined the effectiveness of the FEA (Function, Expressive, and Aesthetics) self-checklist and the P/S toolkit in the IFD process. The experiments involved two design instructors, two teaching assistants, and 12 senior-level students divided into four teams. Thematic analysis was conducted on the interview data collected from the participants. The results revealed that FEA factors were highly considered in both education prototypes, regardless of the presence of the P/S toolkit. Maintaining consistency of the IFD concept throughout each stage of the process was found to be crucial, and the use of the P/S toolkit played a significant role in achieving this consistency. Team communication emerged as an essential factor in IFD education, as team collaboration using the P/S toolkit triggered diverse perspectives on targets, facilitated design expansion, and extended individual competences. Overall, this study contributes to the understanding of the diversity issue in fashion design education and promotes the adoption of the IFD education methodology, emphasizing the significance of consistent concept development, effective toolkits, and team collaboration in achieving inclusive design practices.

This research intended to establish a new fashion-related artificial intelligence research topic concerning fashion editorials which could induce streams of further studies. A new fashion editorial dataset, which is a prerequisite in training an AI model, has been established in this study to meet the research purpose. A total of over 150K fashion editorials were initially collected and processed to satisfy necessary dataset conditions. A novel dataset of fashion editorials consisting of approximately 60K editorials is proposed through the process. In order to prove the adequacy of the new dataset, data distribution was analyzed and a generative model was selected and trained to attest that new fashion editorials can be created with the proposed editorial dataset. The results generated by the trained model were qualitatively investigated. The model has shown to have learned various features that compose editorials with the dataset, successfully generating fashion editorials. Quantitative evaluation with FID scores was conducted to support the selection of the generative model used for the qualitative assessment.

There is a necessity to use digital data and tools when developing children’s products. The present study was designed to provide digital methods to guide product development and problem-solving when using 3D body scans and face mask simulations for 6-year-olds. First, key facial measurements were evaluated to better understand the variables that might affect face mask sizing for children for the selected age group. Then the findings were used to optimize the size and fit of a cloth face mask design. Next, the fit of the digital, optimized face mask design was tested on 44 head scans from Size North America by using subjective and objective fit assessment techniques. Study findings suggested that width and length-related measurements are critical for children’s face masks. Body mass index (BMI) and ethnicity were also found to be the main factors for identifying size ranges in the selected age group. As BMIs increase, face mask sizes should increase. Additionally, the results indicated a need to use a larger database of children of all ethnicities to design an inclusive facemask that would provide a comfortable and protective fit for different facial proportions. Although the results cannot be generalized due to the case study approach of the present research and its focus on methods development, they can provide manufacturers, designers, and researchers with guidelines on how to develop proper sizing and use digital data to conduct functional fit analysis for facemasks.

When producing clothing using virtual fitting technology or purchasing textile and clothing products online, it is challenging to make judgments or communicate information about sensory characteristics, such as drapability and tactile sensations, as there are no clear objective indicators for these factors. Therefore, the study aims to develop a classification system for the sensory properties of fabrics using drapability and tactile characteristics as quantitative indicators. The developed system was verified through subjective evaluations by an expert group, and it was found to be meaningful in reflecting classification levels in practice. The drapability and tactile sensation (softness; TS7) of the fabric were classified using fuzzy c-means cluster analysis, and the results were confirmed through a subjective evaluation by experts. The classification system was then used to predict the classification group, constituted by drapability and tactile characteristics, from mechanical properties using an artificial neural network. The network was trained on 534 fabric samples for drapability and tactile sensation (softness), and it correctly predicted 202 samples out of 243 validation data, with a forecasting accuracy of 83.5%. The developed classification system enables predictions and judgments about subjective characteristics like fabric drapability and tactile sensation based on the mechanical property values of various samples.

Developing energy-efficient and multifunctional wearable electronic textiles (E-textiles) is a significant challenge. This study investigates MXene-coated cellulose hybrid fibers, focusing on their electrical properties, heating performance, and thermal stability. The fabrication process involves continuous dipping of cellulose fibers into an aqueous MXene solution, resulting in the creation of MXene-coated cellulose hybrid fibers. We confirm the uniform coating of MXene sheets on the cellulose fiber surfaces, with increasing content throughout the dip coating cycle, as evidenced by X-ray diffraction and scanning electron microscopy analysis. The high thermal conductivity of MXene acts as a heat source, impacting the thermal stability of cellulose fibers at lower temperatures. Additionally, the electrical properties of MXene/cellulose hybrid fiber composites are influenced at elevated temperatures. Remarkably, the longitudinal electrical conductivity of the MXene-coated cellulose fiber composites exhibits a notable increase of 0.06 S/cm after the final coating cycle, demonstrating the effective and conductive nature of the layer-by-layer MXene network formed on the cellulose fibers.

This study quantitatively analyzes the data of 3D seam shapes that alter according to easing conditions. By numerically approaching easing, which is only taught using traditional methods, this study suggests a method of analyzing the changes in 3D surface area, volume, and seam shape. The 3D data of the completed samples were obtained through a 3D scanner, the solid shapes were analyzed using reverse engineering, and a new program was developed. The shape, area, and volume of the data were analyzed, and the deformation rate was measured using the radius of curvature. Linear seam lines were bent because of the mechanical pushing inflicted by the garment with easing. The area increased dramatically as the ease amount increased when the seam lines were short, whereas it was relatively unaffected when seam lines were long. The radii of curvature for curved seam lines show that, for all samples, the waveform is high at the center where the seam is. The peak value did not increase for curved seams when the ease amount increased. The sum of the areas increased with a larger radius of curvature for the curved seams. It is a crucial reference for easing in garments regarding quantitative changes in seam shapes and volumes according to easing type and amount.