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This study explores clothing disposal in a developing economy. It focuses on how consumers dispose of clothing and what motives influence them to use a specific disposal method.

Semi-structured interviews, a qualitative research method, were conducted with a purposive sample of 27 participants from diverse demographic backgrounds within the developing economy of Ethiopia. The interviews were coded and analysed using thematic analysis to identify categories and themes.

The findings reveal various clothing disposal methods, such as bartering, donating, gifting, repurposing and reusing, and discarding. Different motives drive consumers to use these methods, including economic benefits, altruism, and convenience.

The study bridges an important knowledge gap in literature mainly on three aspects, as highlighted by previous research. Theoretically, in addition to proposing a different perspective of bartering as a disposal method, the study investigates the motives behind clothing disposal methods from diverse consumer groups and proposes a conceptual framework to illustrate the link between clothing disposal methods and motives. Methodologically, the study addresses the call for a more inclusive and diverse sample, considering gender and varied socio-economic groups. Contextually, while previous research has focused on developed economies, this study explains clothing disposal methods and motives from a developing economy context, specifically Ethiopia.

Accurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.

Physics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.

The results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.

The main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

Amidst escalating sustainability challenges, product and brand managers face a pressing need to foster responsible consumption and marketing strategies. Guided by the theory of planned behavior, this paper aims to explore consumers’ motivation to purchase second-hand clothing, a type of product that contributes to Sustainable Development Goal (SDG) 12 on Responsible Consumption and Production by democratizing the brand, extending the life-cycle of the product, promoting a circular economy, while reducing economic costs for consumers and environmental costs for companies.

A two-stage study was conducted: 20 consumers were initially interviewed to identify the salient beliefs about second-hand clothing, and following that, a survey was conducted with 449 consumers to statistically analyze consumers’ motivation to purchase second-hand clothing. The data were analyzed using partial least squares-structural equation modeling (PLS-SEM) and necessary condition analysis (NCA).

From a “should-have” perspective (PLS-SEM), the study reveals that behavioral beliefs, injunctive normative beliefs, descriptive normative beliefs and control beliefs positively shape attitudes, injunctive norms, descriptive norms and perceived behavioral control toward second-hand clothing, whereas attitudes, injunctive norms, moral norms and perceived behavioral control positively influence consumers’ purchases of second-hand clothing. From a “must-have” perspective (NCA), the study shows that behavioral beliefs, injunctive normative beliefs and descriptive normative beliefs are necessary conditions to positively shape attitudes, injunctive norms and descriptive norms toward second-hand clothing, whereas attitudes, injunctive norms and perceived behavioral control are necessary conditions to stimulate second-hand clothing purchases.

The study offers a deep dive into consumers’ motivation to purchase second-hand clothing using a multimethod approach that enables not only the elicitation of salient beliefs (through interviews) but also the empirical examination of these beliefs alongside varying subjective norms in motivating consumers to purchase second-hand clothing (via survey). Given that beliefs are deeply rooted, the rigorous unfolding and validation of consumers’ beliefs about second-hand clothing, including the “should-haves” versus the “must-haves,” provide finer-grained insights that product and brand managers can strategically use to encourage consumers to purchase second-hand clothing.

This study aims to integrate fall-protection function into the elderly clothing to meet both the daily life and fall-protection needs of the elderly people, thereby upgrading the performance of elderly clothing.

This study identified the design strategies of elderly clothing using an Extended Kansei Engineering methodology. Extended Kansei Engineering methodology is a new design framework developed from the traditional Kansei Engineering methodology to meet the design requirements of the product-service system. This study focuses on the product section of product-service system design. According to the product design process of the Extended Kansei Engineering methodology, this study first collected and organized the design elements and Kansei words of elderly clothing. Then a questionnaire was designed using Semantic Differential Scale. Finally, the questionnaire survey was conducted and the collected data was analysed to understand the consumption preferences of elderly people. A total of 399 elderly people aged 65 and older provided valuable design insights for this survey.

The research findings include the product design strategies for the development of elderly clothing, as well as a product prototype canvas and a product prototype elderly clothing developed based on the design strategies.

The research findings can provide competitive design strategies for the development of elderly clothing, thereby upgrading the performance of elderly clothing.

This elderly clothing integrates fall-protection function to reduce the risk of injury for elderly people due to falls, thereby helping society alleviate the medical and healthcare pressure caused by falls for elderly people.

The research findings can provide competitive design strategies for the development of elderly clothing. Furthermore, the Extended Kansei Engineering methodology introduced in this study can provide product and service designers with design methods that are more in line with the development trend of modern product-service system business models.

This study aims to increase the novelty of clothing design and fabric texture. The element library that can be used for design is systematically summarized. The element database can also be continuously filled according to the existing logic to realize the diversity of design. Improve the theory of fashion design, expand the designer's design ideas and improve design efficiency. Clear design steps and logic can help students and machines learn the design process and promote the development of intelligent design. And verify the feasibility of the simulation software to assist pleated clothing design.

Firstly, according to the logical framework of origami theory, different innovative designs and combined designs are made for the basic units of hyperbolic paraboloid, and the element library that can be used for design is systematically summarized. This database can also be continuously filled according to the existing logic to realize the diversity of design. Secondly, it summarizes three methods of pleated element filling clothing – uniform filling method, the irregular filling method and geometric addition method – that improve the theory of fashion design, expand the designer's design ideas and improve design efficiency. Clear design steps and logic can help students and machines learn the design process and promote the development of intelligent design. Finally, the virtual software is used to simulate the effect of pleated clothing, and the three-dimensional simulation software 3dclo is used to make an empirical study on the application of hyperbolic paraboloid origami in clothing pleated design to verify the feasibility of the simulation software to assist pleated clothing design.

The theoretical results of hyperbolic paraboloid origami are collected and arranged to establish the element library of hyperbolic paraboloid origami. The results expand the designer's design ideas and auxiliary design technology and improve the design efficiency using a sample of hyperbolic paraboloid fabric to verify its practicability and three-dimensional clothing simulation software for exploring the design. The design rules of hyperbolic paraboloid clothing and the realization method of fabric are summarized, including the expansion and combing of elements, the application of size and shape and the method of combination.

Owing to the hyperbolic paraboloid origami’s length shrinkage, the loose computation of clothing requires targeted computation. This paper solely applies a paper model for estimating the shrinkage, and then we tend to subsequently explore the way to precisely compute the porosity, to determine the existing differences in the two-dimensional shrinkage of hyperbolic paraboloid creases of varying materials and to know if the clothing after large-scale production is capable of reaching the anticipated value.

The exploration of this experiment brings a new 3D experiment process to the design process.

This experiment brings new possibilities for the development of virtual fitting and virtual display in the industry.

This study combines hyperbolic paraboloid origami and clothing and combs and expands the unit with logical thinking to expand the designer's design ideas.

Single-shot multi-category clothing recognition and retrieval play a crucial role in online searching and offline settlement scenarios. Existing clothing recognition methods based on RGBD clothing images often suffer from high-dimensional feature representations, leading to compromised performance and efficiency.

To address this issue, this paper proposes a novel method called Manifold Embedded Discriminative Feature Selection (MEDFS) to select global and local features, thereby reducing the dimensionality of the feature representation and improving performance. Specifically, by combining three global features and three local features, a low-dimensional embedding is constructed to capture the correlations between features and categories. The MEDFS method designs an optimization framework utilizing manifold mapping and sparse regularization to achieve feature selection. The optimization objective is solved using an alternating iterative strategy, ensuring convergence.

Empirical studies conducted on a publicly available RGBD clothing image dataset demonstrate that the proposed MEDFS method achieves highly competitive clothing classification performance while maintaining efficiency in clothing recognition and retrieval.

This paper introduces a novel approach for multi-category clothing recognition and retrieval, incorporating the selection of global and local features. The proposed method holds potential for practical applications in real-world clothing scenarios.

This paper aims to answer the questions of what clothing practices related to sustainable fashion can be observed in young consumers' daily lives in Finland’s capital region and what prevents their further proliferation.

This is qualitative research that draws from 22 semi-structured interviews with high school students in the capital area of Finland. The data were analyzed with the use of thematic analysis, a flexible method of data analysis that allows for the extraction of categories from both theoretical concepts and data.

This paper contributes to studies of young people’s consumption with the practice theory approach, putting forward the category of following sustainable fashion as an integrative practice. The three-element model of the practice theory allows answering the question of challenges that prevent the practice from shaping. The paper further advances this approach by identifying a list of context-specific dispersed practices incorporated into sustainable fashion.

The study suggests practical ways of improving clothing consumption based on the practice theory approach and findings from empirical research. Sustainable practices require competences, knowledge and skills that the school, as an institution working closely with high school students, could help develop.

The study contributes to the current studies of sustainability and youth culture of consumption with a practice theory approach and findings, related to a particular context of a country from Northern Europe.

The aim of this paper is to achieve a reasonable microclimate between clothing and the human body and optimize the custom dress pattern.

An interactive design method of 3D modeling, virtual try-on and heat transfer simulation are used. First, a 3D dress is designed with nonuniform rational B-splines curves and tried on virtually. After that, the heat transfer in the body-air-clothing microclimate and temperature distributions on the clothing surface are obtained. Based on the heat transfer in the body-air-clothing system, we design a method to improve the thermal comfort by optimizing the garment pattern digitally. Then, this paper utilized two heat transfer validating indexes to quantify the improvement of thermal comfort, and evaluate the modified model of dress.

The microclimate under the clothing is varied with the air gap distance, and the heat transfer on the area of the clavicle, bust point and front abandon are higher than other parts due to the narrow air gaps. In view of thermal comfort, the pattern optimization changes the distance ease and reforms the air circulating efficiency. The mean heat transfer and its standard variance are changing by about 10% and more than 20%. Thus, the heat transfer evaluation indexes are suitable to represent the heat transfer and thermal comfort in the microclimate system.

It can be concluded that the methodology proposed in this paper has the advantage of interactive design, 3D visualization and local heat transfer simulation. This technology meets the need of personalized customization and well-considered garment and has broad application prospects.

This study demonstrates that modifying the distance ease on body key girths based on heat transfer is a reliable way to improve thermal comfort. This method meets the consumers’ demand of the comfort of body-fit clothing under the condition of daily activities.

• 3D air gap distributions.

• Heat transfer varies with air gap distance.

• Thermal comfort can be improved by optimizing garment pattern.

3D air gap distributions.

Heat transfer varies with air gap distance.

Thermal comfort can be improved by optimizing garment pattern.

The purpose of this paper is to investigate the distribution characteristics of airflow in mine ventilation suits with different pipeline structures when the human body is bent at various angles. On this basis, the stress points are extracted to investigate the pressure variation of a ventilation suit under different ventilation rates and pipeline structures.

Based on the three-dimensional human body scanner, portable pressure test and other instruments, a human experiment was conducted in an artificial cabin. The study analyzed and compared the distribution characteristics of clearance under three different pipeline structures, as well as the pressure variation of the ventilation suit.

The study found that the clearance in front of two pipeline structures gradually increased in size as the degree of bending increased, and there was minimal clearance in the chest and back. The longitudinal structure exhibits a significant decrease in clearance compared to the spiral structure. The pressure value of the spiral pipeline structure with the same ventilation volume is low, followed by the transverse structure, while the longitudinal structure has the highest pressure value. The increase in clothing pressure value of a spiral pipeline structured ventilation suit with varying ventilation volumes is minimal.

The ventilation suit has a promising future as a type of personal protective equipment for mitigating heat damage in mines. It is of great value to study the pipeline structure of the ventilation suit for human comfort.

Based on the knowledge-attitude-behavior model, this study is aimed at investigating the influential mechanism underlying the purchase of green clothing by dividing this clothing category into green home-in wear and home-out wear within the context of green consumption. The mediating effects of perceived greenwashing (PG), perceived value (PV) and expected moral benefit (EMB) and the moderating effect of green clothing type (GCT) were examined.

The data for this study were collected from 366 valid samples through a between-subject design survey administered in China. Moderation analysis and mediation analysis using SPSS/PROCESS macro were applied to test the proposed hypotheses.

The results indicate that consumers' level of environmental knowledge (EKL) not only has a direct effect on purchase intention (PI) but also has an indirect effect through perceived value and expected moral benefit. However, perceived greenwashing did not play a mediating role in this relationship.

The study's findings show a moderating effect of green clothing type (green home-in wear vs green home-out wear). That is, compared to green home-out wear, the relationship between expected moral benefit and perceived greenwashing for green home-in wear had a weaker negative effect on purchase intentions.