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This study aims to automate the process of converting grading patterns into parametric patterns using artificial intelligence and to objectively evaluate the fitness of the converted patterns.

The developed system consists of a user interface that defines input data by importing multi-size grading patterns, an artificial neural network that learns the relationship between human body size and pattern geometry, and a module that converts training results into parametric patterns. In order to evaluate the fitness of the generated pattern, an objective fitting evaluation method using drape simulation was developed.

The body sizes of the wearer were input to the converted parametric pattern to generate a customized pattern. Resulting pattern showed a better fit than the grading pattern on the off-average body model.

In this study, a method has been developed that enables the users with minimal pattern drafting knowledge to convert grading patterns into parametric patterns using artificial intelligence and drape simulation. The human body's symmetry and the physical properties of fabric were not considered.

The system developed in this study requires less data compared to existing methods that attempt to design clothing patterns with machine learning. In addition, it was possible to evaluate pattern fitness on various body models through drape simulation based fit evaluation process for the first time.

Low-fit brand extensions offer several potential benefits, yet their success is challenging. Building on construal level theory, this study aims to investigate how different advertising appeals can improve the evaluations of low-fit brand extensions through two different processes (cognitive and affective).

Two experiments were conducted with US consumers. Study 1 used a 2 (extension fit: high, low) × 2 (ad appeal: abstract, concrete) between-subjects design. Study 2 applied a 2 (brand associations: promotion, prevention) × 2 (ad appeal: promotion, prevention) between-subjects design. Multivariate analyses and follow-up means comparisons were used to analyse data.

Study 1 found that an abstract ad appeal is more effective for promoting low-fit brand extension because it improves the perception of fit. Study 2 showed promotion vs prevention ad appeals lead to better evaluation of low-fit brand extensions when matched with parent brand associations (promotion vs prevention) in terms of construal level. This matching effect is underpinned by processing fluency.

Ad appeals can influence low-fit brand extension evaluation by influencing the perception of fit (cognitive process) or processing fluency (affective process). Future research could consider different ad appeals and other construal related factors to generalise these findings.

Marketers can design different ad appeals to effectively advertise low-fit brand extensions. These findings can guide managers in the development of effective advertising strategies.

This research offers a new perspective on how ad appeals can enhance low-fit brand extension evaluation.

The innovativeness of dressmakers is a concern to respondents to satisfy their clothing needs. The purpose of this study is to determine the criteria that respondents use to judge the quality of clothing and its influences on the innovative ability of dressmakers in the clothing manufacturing industries.

Three hundred and ninety-seven (397) respondents in the Takoradi Metropolis of Ghana filled out a questionnaire, and the results were used to compile data for the study. The sample size was calculated using Miller and Brewer formula. The data was analysed using structural equational modelling with the SmartPLS v.4 software.

The results showed that respondents are very interested in the calibre of clothing produced by their dressmakers. However, the study revealed that when evaluating the quality of a garment, respondents do not simply accept what has been sewn for them but also consider the performance, appearance, fit and shape of the garment. Findings revealed that there was a significant relationship between garment appearance quality (t = 2.605; p < 0.05), garment performance quality (t = 3.915; p < 0.05), garment shape quality (t = 6.248; p <0.05) and fashion innovations. Subsequently, the evaluation of garment fit quality by respondents revealed it does not bring about innovations (t = 1.310; p > 0.05).

The continuous evaluation of custom-made clothing from customers will go a long way towards highlighting the relative criteria they use to evaluate the innovation of dressmakers. This will help improve the creativity of the dressmakers since such feedback will help them understand and innovate their production skills to meet the preferences of customers.

The present study provides an in-depth understanding of how garment quality evaluation by customers influences the innovation of dressmakers in Takoradi, Ghana. The constructs were developed for the study to capture the appropriate data from customers for the study. This presents an evaluation criterion on four garment quality variables imperative for use or modification by other studies.

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.

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.

Body shape is a critical variable influencing consumers' garment choices (Zakaria, 2017), yet research investigating how UK females with varying body shapes evaluate and experience fit is limited. Moreover, while digital methods exist to classify female body shapes, application in a commercial setting is limited. To fill this gap within the literature, this study aims to understand the influence of body shape variation on garment fit evaluations of 30 UK females aged 18–34 years.

This study conducts a physical garment try-on session whereby 30 UK females aged 18–34 years were body-scanned and categorised into a body shape, using the Female Figure Identification Technique method. Participants verbalised their fit experiences during a physical try-on session through semi-structured interviews to gain a deeper understanding of individuals' fit appraisals.

The findings demonstrate that UK females who share the same body shape classification experience the same issues when appraising dress fit, challenging Makhanya and Mabuza (2020) who found that body shape does not influence apparel fit satisfaction. The results shed light on the importance of body shape during the fit appraisal process.

Despite the contribution, future research to improve the limitations should be addressed. First, although it was necessary to investigate a UK demographic to address research gaps, the finding of this study cannot be generalised to the entire UK female population nor to other areas of the world. Hence, future research should overcome this limitation by extending this study further to other countries, cultures and ethnicities.

The findings of the present study shed light on the role of body shape in determining satisfactory clothing fit and how females' fit experiences will differ depending on their body shape classification. Thus, fashion retailers should use this insight to better inform their promotional strategies, not only making them more inclusive but also to help assist this particular consumer segment with their clothing decisions based on their body shape.

The present study provides an in-depth understanding of how females with the same body shape experience garment fit, contributing novel findings to the literature through a mixed-method inquiry previously lacking in this area, with a UK demographic which has not previously been explored.

To examine how perceptions of complementary and supplementary fit and relationship quality contribute to successful mentorship co-creation.

Data were collected via cross-sectional survey of 145 mentor–protégé dyads within institutions of higher education in the USA. Mentors evaluated their perceptions of supplementary and complementary fit and relationship quality with their protégés and vice versa. Additionally, mentors evaluated their protégés’ performance, whereas protégés reported on their own learning. Data were analyzed using the actor–partner interdependence model.

Results suggest that one's own fit perceptions are most important in predicting one's evaluation of relationship quality. Additionally, for both mentor and protégé, complementary fit and supplementary fit predict evaluations of relationship quality to a similar degree. Finally, each person's perceptions of relationship quality mediated the relationships between their own perceptions of fit and mentor-rated protégé performance, but not the relationships between perceptions of fit and protégé-rated learning.

Research has often studied mentorships from the perspective of one party, which limits our understanding of mentorship co-creation. This study investigates how both parties simultaneously contribute to mentorship success, as indicated by protégé learning and performance. Additionally, the authors clarify the extent to which perceptions of different types of fit are instrumental in co-creating successful mentorships.

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.

Past work on the role of brands in the acceptance of organic products is partial and inconclusive. Research has failed to examine the consumer sense-making process underpinning fit assessment, despite the centrality of this assessment in the acceptance of line extensions. This study reconceptualizes the fit construct, showing the relationship of the fit dimensions (noncompensatory) and contributes to the literature with a deeper understanding of the role of a brand's association in the assessment process, which has been poorly examined in the past.

Grounded theory was used to unearth the process followed by consumers to assess the fit of organic line extensions. The study was based on 14 in-depth interviews.

The findings show that the dimensions of fit that consumers consider in assessing organic line extensions depend on the schema used in the assessment process. Moreover, it demonstrates that these dimensions have disparate structural relationships with one another, depending on consumers' previous commitment to organic products. Finally, the paper identifies three possible behavioral reactions by consumers toward organic line extensions.

The main limitation of this research concerns the settings in which it was developed. Therefore, and as stated by Strauss and Corbin (1990) the model applies to the situation analyzed and not to others. Future research could study if there are cultural differences in the assessment process of an organic line extension. Moreover, the contribution presented in this paper needs further empirical testing; specifically, the configuration of dimensions needed to accept an organic line extension and the relationship among dimensions.

This paper contributes to the literature by studying the impact of brand association on assessing an organic line extension and reconceptualizing the fit construct by showing the dimensions and the relationship between them that are not additive to the overall fit, as shown in past literature. Additionally, it provides a guide to brands wishing to launch an organic product using a line extension strategy and the potential implications for the parent brand that should be considered.

This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for virtual fitting.

In this study, we briefly analyze the mainstream datasets of models of the human body used in the area to provide a foundation for parametric methods of such reconstruction. We then analyze and compare parametric methods of reconstruction based on their use of the following forms of input data: point cloud data, image contours, sizes of features and points representing the joints. Finally, we summarize the advantages and problems of each method as well as the current challenges to the use of parametric modeling in virtual fitting and the opportunities provided by it.

Considering the aspects of integrity and accurate of representations of the shape and posture of the body, and the efficiency of the calculation of the requisite parameters, the reconstruction method of human body by integrating orthogonal image contour morphological features, multifeature size constraints and joint point positioning can better represent human body shape, posture and personalized feature size and has higher research value.

This article obtains a research thinking for reconstructing a 3D model for virtual fitting that is based on three kinds of data, which is helpful for establishing personalized and high-precision human body models.