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The research evaluated the feasibility of 3D dynamic fit utilizing female compression tops by comparatively analyzing the virtual and actual dynamic fit.

Six female participants were 3D body-scanned and photographed in compression tops in four types of athletic movements (pull-up, kettlebell swing, circle-crunch and sit-up). Fit measurements, waist cross-sectional areas, waist width, waist depth, numerical simulation of clothing pressure (kPa) and objective pressure measurements (kPa) were collected from 3D virtual animation, 3D fit scan data and actual photos with the four types of athletic motions. The data were comparatively investigated between virtual and actual dynamic fit.

The 3D-animated body was not reflected with human body deformation because only bone structure was changed while maintaining the constant forms of muscle and body surface in athletic movements. Due to this consistency of virtual dynamic fit, there were significant differences with the actual dynamic fit at the top length, shoulder width and waist cross-sectional areas. Also, the virtual dynamic pressure indicated significantly higher levels than the objective dynamic pressure while presenting no significant correlations at the front neckline, breast, lateral waist, upper back, back armhole and back waist.

This study is the first to verify multiple aspects of virtual dynamic fit using 3D digital technology. This study provided useful information about which aspects of the current virtual animation need to be improved to apply in the dynamic fit evaluation.

Virtual garment fit will be an important determinant for the online purchase decision of consumers in the near future. Therefore, the purpose of this study was to develop a conceptual model to explore the factors that might impact consumers’ virtual garment fit satisfactions (VFS).

Virtual body satisfaction (VBS), acceptance of the virtual try-on technology and virtual fabric properties were examined as factors that would potentially impact consumers’ VFS. Forty-five women, from 18 to 35 years old, were recruited for the study. Participants were scanned by using a 3D body scanner and their scans were used for virtual try-on. Seven circular skirts with different fabric properties were created by using a commercial 3D simulation software. Participants evaluated the fit of these virtual skirts on their own virtual bodies. Participants’ VFSs and their correlations with VBSs, acceptance of virtual try-on technology and virtual fabric properties were analyzed by Pearson’s correlation test.

Participants’ VBSs at hips were correlated fairly good with their VFSs (r = 0.50, N = 180, p < 0.01) and their acceptance of virtual try-on technology was weakly correlated to VFSs (r = 0.24, N = 180, p < 0.01). However, no significant correlation was found between virtual fabric properties and participants’ VFSs.

This study did not examine the ideal beauty notion, which may affect consumers’ expectations about how the garments should fit on them. Another limitation was the use of a single skirt design as a stimulus.

Studies that explore virtual garment fit often measure the garment ease or the virtual fabric tension and ignore consumer perspective, which is essential for online purchase decision. This study is unique as it prioritizes consumers’ perspectives.

The purpose of this paper is to present a fit prediction case study of virtual twins of women jacket. For this reason, several basic principles of clothes fit prediction were developed and verified.

To develop the principles of fit prediction, the women's jacket sleeve was selected as the study object. The study objects were categorized into three types: the patterns and two virtual sleeves generating on full avatar from Clo3D and on dummy (arm partly removed). Through series of subjective and objective evaluation experiments, the relationship between the similar indexes of the patterns and the virtual sleeves was built, including fit criteria range, the categorization of the indexes in terms of its sensitiveness, and the linear regressions to predict several indexes of virtual sleeves after its pattern parameterization. The results obtained were verified in case study by the virtual and real sleeves generating.

The proposed principles of clothing fit prediction based on parallel research of the flat patterns and its virtual 3D shapes. The principles include the choosing of virtual twins of human body for virtual try-on, the establishing of indexes common schedule for patterns and virtual sleeves, the creation of criteria and its ranges for perfect fit and poor fit evaluation, and the application of existing relations between the patterns and the sleeves for predicting indexes responsible for fit.

The authors propose and verify the validity of the principles to predict several parameters of virtual 3D sleeve of women's jacket which are forming the level of fit. The result of this study can be used to convenient fit prediction and to find the misfit reasons.

This study developed basic principles for predicting the fit of the clothing through the virtual simulation and the statistical analysis. Through studying the jacket sleeve, the several related ranges, the row of more sensitive indexes, and the equations were presented and verified, which certified the validity of proposed principles.

The results can effectively predict the sleeve fit before sewing, which reduce the time and materials cost and the operator's skill requirements.

The authors propose and verify the validity of the principles to predict several parameters of virtual 3D sleeve of women's jacket which form the level of fit. The result of this study can be used for convenient fit prediction and to find the misfit reasons.

Augmented reality (AR) has become a trend, and the effects of Pokémon Go, the most popular online and mobile game, have been explored in many studies. However, few studies have developed questionnaires of fit to investigate the relationship between the fit and the integration of the game's virtual world and reality. The paper intends to integrate the models of stimulus-organism-response (S-O-R) and information systems success with cognitive fit theory to explore the fit and reactions of users in the integration of real and virtual worlds.

Following MacKenzie's scale development, two surveys were conducted. The first survey was conducted to perform a scale development of fit. The second survey was collected from 315 Pokémon Go players to validate the fit scale and it was analyzed via structural equation modeling.

The results show that scale development of fit has good reliability and validity. Furthermore, game information quality, game system quality and virtual (Pokémon) characteristics have significantly positive effects on cognitive and emotional fit. Cognitive and emotional fit have significant positive effects on user satisfaction, and user satisfaction has significant positive effects on continued intention to play. The results suggest that maintaining the quality of the game and improving the virtual interface will provide a better fit between the real and virtual worlds, enhancing user satisfaction with the fit as well as their intention for continued use.

Although fit has been widely studied in various contexts, the application of AR has been rarely discussed. This study develops a scale of fit and takes Pokémon Go as the subject to validate the fit measurement and discuss players' cognition and feelings regarding the game. The authors measure user reactions to different stimuli and explore cognitive and emotional fit as well as the integration of virtual worlds and reality. In sum, to the best of the authors’ knowledge, this is one of the earliest studies to explore and develop a cognitive and emotional fit scale for future researchers and practitioners.

Drawing on virtual liminoid theory, the purpose of this paper is to examine factors that induce a multisensory flow experience in an e-shopping context through the use of augmented-reality interactive technology (ARIT).

To validate the research framework, a task-based laboratory study was performed. Participants were recruited through a snowball e-mail method and requested to freely and independently use ARIT for clothes fitting in the laboratory, after which they completed a questionnaire; 336 valid responses were received.

Empirical results revealed that three decorating psychological states (sense of body ownership, sense of ownership control, and self-explorative engagement) directly induced a multisensory flow experience. Furthermore, two multisensory factors (sense of self-location and haptic imagery) mediated the multisensory flow experience through these three decorating psychological states.

Consumers not only rely on generating self-display for optimal fitting in virtual avatar decoration in an e-shopping context but also concentrate more on expression and control of self-body. As consumers’ decorating psychological states require an ideal form of self-expression, a high degree of autonomy in exploring self-decoration options will create more value for consumers. Considering that expressing and controlling the self-body in addition to self-explorative engagement in virtual avatar decoration will trigger the flow experience in an e-shopping context, increasing the use of multisensory ARIT to trigger decorating psychological states in e-shopping contexts is highly recommended.

In this study, a relationship was constructed among virtual liminoid theory, flow theory, and multisensory technology, and an integrated conceptual framework was developed for the relationship between decorating psychological states and multisensory flow experience.

The purpose of this paper is to use body shape analysis and develop a 3D virtual body formation and deformation model that can accurately express size and shape.

In this paper, 1,882 sets of direct measurement data of Korean women in their 20s (19–29 years) were analyzed. These data sets were sourced from the sixth and seventh “Size Korea” anthropometric survey data. Through body shape analysis, the authors classified them into seven body types and selected their representative bodies. A 2D image based on the height, breadth, depth and length was first formed, and the representative virtual body was modeled using the polygon technique. The authors calculated the grading ratios for each body type according to the clothing sizing system, and modified the virtual body size type by morphing technique.

In order to accurately evaluate the fit in a virtual fitting system, it is necessary to study the body size and shape of the target age; this makes it possible to form virtual body reflecting the size and shape.

In this paper, the authors propose a new 3D virtual body formation method that is more accurate in shape and size compared to the present system. Through this, it will be possible to grasp the accurate simulation state in the virtual fitting system, and thereby evaluate the accurate fit.

This study establishes the principles and process steps of a new basic trousers pattern using measurements obtained according to the rules of the anthropometric measurement system. The newly developed pattern-making system in this study will be called the “Anthropometric Measurements Based Pattern Making System” (AnMePa). It is aimed at producing trousers that are more fitting to the body, thanks to this pattern-making system.

In this research, four pattern-making systems used in many parts of the world were compared with the “Anthropometric Measurements Based Pattern Making System” (AnMePa) with regard to the overall appearance and body fit of trousers prepared according to these systems. 10 virtual mannequins (VM) with different adult female body measurements were created, and trousers patterns were prepared for these mannequins. The trousers’ patterns were made and dressed on the mannequins in a 3D virtual dressing system. The body fit of the virtual garments was evaluated by five experts. The scores given by the experts were evaluated using the fuzzy logic method.

According to the results, it is seen that the new basic trousers pattern developed by utilizing the anthropometric measurement system, AnMePa, provides the best body fit among the basic trousers patterns created according to the other examined pattern-making systems. The combination of 3D virtual dressing and fuzzy logic in the evaluation of garment body fit is considered an innovative method for the future of fashion design and production.

In the developed AnMePa, unlike the existing pattern-making systems, values that can be associated with the body measurements of individuals in a way that could be suitable for each community were used instead of constant values in the pattern-making process. Furthermore, the integration of 3D virtual fitting and fuzzy logic in assessing garment fit is considered a pioneering approach with significant implications for the future landscape of fashion design and production.

This study aims to investigate the rising trend of virtual influencers – digitally created characters with human-like attributes. It aims to evaluate and compare their effectiveness with human influencers in terms of brand attitudes and purchase intentions. It uncovers the mechanisms underlying the differences in effectiveness observed between virtual influencers and their human counterparts.

The research uses a 2 (influencer type: human vs virtual) × 3 (product type: functional vs symbolic vs experiential) between-subjects design. Through a pilot study (n = 334) and a main study (n = 352), the research examines the interactive effects of influencer and product type on brand attitude and purchase intentions. Hypotheses were developed and tested using moderating mediation models centered on authenticity and product–endorser fit.

Virtual influencers are perceived as less authentic than human influencers across all product types, negatively influencing brand attitude and purchase intention. However, the extent to which influencer type affects brand attitudes and purchase intentions, mediated by product–endorser fit, varies based on the product type.

This research emphasizes two key mechanisms – authenticity and product–endorser fit – influencing the effectiveness of virtual influencers. It suggests that aligning virtual influencers with suitable product types can offset their perceived authenticity deficit, significantly affecting their endorsement effectiveness.

The purpose of this paper is to investigate basic block pattern modification according to fabric used and the mismatch between 2D and 3D measure lines at bust, waist and hip girths when ease allowance is changed uniformly.

For the investigation, virtual try-on software Modaris 3D Fit (CAD Lectra) was used. The straight shape dress fitting was done using seven cotton and cotton blended plain weave fabrics. After virtual try-on, the mismatch d (d_bust, d_waist, d_hip) between 2D and 3D measure lines was measured in order to determine base pattern adjustments using different fabrics.

It was found that the position and length of 3D measure lines at bust, waist and hip girths does not match the position and length of corresponding lines in 2D base patterns after virtual try-on due to fabrics deformation, which is related to mechanical properties. It was proved that derived linear equations presenting a relation between mismatch and ease allowance values could be used for basic block pattern modification that 3D and 2D measure lines would coincide during clothing try-on.

This research is limited to cotton/cotton blended woven fabrics and straight dress; therefore, other fabric types and other clothing could be investigated in the future to expand data basis.

The main practical point of the proposed method is that in order to obtain particular 3D ease value in a garment, it can be calculated from 2D ease allowance value and the fabric’s tensile properties using linear equations. The basic block patterns could be modified using this method not only for tested fabrics but also for other fabrics with similar composition, structural and mechanical properties. 3D ease values in garment can be easily checked by using virtual try-on technology without production of real prototypes. The method is applicable for making ready-to-wear or individually tailored clothing.

The proposed method in this paper presented opportunity to modify the basic block patterns of the dress according to the fabric’s tensile properties and 2D ease allowance. The basic block patterns could be modified according to presented linear functions for each tested fabric. The application of this method can fully ensure the interaction between the garment 2D patterns to 3D garment so that a desired 3D garment fitting effect to the body can easily be satisfied by the adjustment of particular fabric characteristics. It offers further possibilities, especially with developing virtual try-on technologies.

The paper seeks to evaluate and present the usability of one pattern customising technology in the achievement and testing of garment fit.

This study focuses on the use of 3D technology in the testing of garment fit. It examines the usability of one pattern customising technology in the achievement and testing of fit and presents primary data from experiments on the provision and testing of garment fit of specified size patterns for a jacket and skirt. Findings on virtual and human fit trials and an evaluation of the 3D technology are presented.

The study found that 3D software for fit provision and testing is still in its infancy, although advancements are currently being made in this area. It establishes that while fit can be virtually tested with 3D technology, its usability is not yet fine‐tuned. It evaluates procedures and presents problematic features of the 3D software. It underscores that although some issues concerning efficient provision and testing of fit still exist, 3D technology overall provides adequate evaluation of fit.

This study highlights areas for fine tuning and provides a basis for further research. While discussing usability of one pattern technology, this paper presents a platform for comparative evaluation of other technology.