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The Web 3D virtual display technology for personalized clothing based on Unity3D is studied in this paper. The framework of the technology is described. The development steps including personalized clothing design and modeling, interaction and virtual display technology based on Unity3D are given out. The purpose of this paper is to provide a feasible technical route and support for the virtual display for the customized products.

The paper opted for an exploratory study using the open-ended approach of grounded theory, including the Web 3D virtual display technology for personalized clothing based on Unity3D.

A feasible technical route for the virtual display of the customized products is provides in this paper.

This paper fulfills a software and has practical use.

Today clothing has become the largest category in online shopping in China, and even in Asia-Pacific. The satisfaction degree of apparel online shopping can be improved by effective personalized recommendation. The purpose of this paper is to propose a personalized recommendation model and algorithm based on Kansei engineering, traditional filtering algorithm and the knowledge relating to apparel.

Users’ perceptual image and the design elements of apparel based on Kansei engineering are discussed to build the mapping relation between the design elements and user ratings employing verbal protocol, semantic differential and partial least squares. The implicit knowledge and emotional needs pertaining to users are accessed using analytic hierarchy process. A personalized recommendation model for apparel online shopping is established and the algorithm for the personalized recommendation process is proposed. To present the personalized recommendation model, men’s plaid shirts are taken as the example, and the recommendations of apparel for online shopping were implemented and ranked in the context of differing users’ emotional needs. A comparison between the traditional model and this model is made to verify the effectiveness.

The recommendation model is capable of analyzing data and information effectively, and providing fast, personalized apparel recommendation services in accordance with users’ emotional needs. The experimental results suggest that the model is effective.

Similar researches of recommendation mainly focus on the field of computer science, the basic idea of which is using users’ history accessing records or the preferences of other similar users for determination of users’ preferences. Since the attributes of apparel products are not factored in the approach referred above, the issue of personalized recommendation cannot be solved in a really effective way. Combining Kansei engineering and recommendation algorithm, a framework for apparel product recommendation is presented and it is a new way for improvement of recommendations for apparel products on shopping sites.

Global economic growth provides new opportunities for the development of clothing enterprises, but at the same time, the rapid growth of clothing customization demand and the gradual increase of clothing costs also pose new challenges for the development of clothing enterprises. In this context, 3D printing technology is injecting new vitality and providing a new development direction for the vigorous development of clothing enterprises. However, with the application of 3D printing technology, more and more clothing enterprises are facing the problem of business model innovation. In view of the lack of relevant research, it is necessary to carry out exploratory research on this issue.

The business model canvas method was adopted to design business model for clothing enterprises using 3D printing. The simulation model of the designed business model was constructed by a system dynamics method, and the application of the designed business model was analysed by a scenario simulation.

Mass selective customization-centralized manufacturing (MSC-CM) business model was constructed for clothing enterprises using 3D printing, and a static display was carried out using the BMC method. A dynamic simulation model of the MSC-CM business model was constructed. The future scenario of clothing enterprises using 3D printing was developed, and a simulated enterprise was analysed. The results show that the MSC-CM business model has a good application value. The simulation model of the MSC-CM business model performs the function of a business strategy experiment platform and also has a good practical application value.

The MSC-CM business model is only a typical business model for clothing enterprises using 3D printing. It is necessary to further develop other business models, and some elements of the MSC-CM business model need to be further improved. In addition, the MSC-CM business model simulation uses a general model, which is not suitable for all clothing enterprises using 3D printing. When the model is applied, the relevant enterprises can further adjust and optimize it, thereby improving the validity of the simulation model.

To the best of the authors’ knowledge, this is the first paper on the MSC-CM business model for garment enterprises using 3D printing. Secondly, it is the first time that the business model of clothing enterprises using 3D printing has been simulated. In particular, the proposed business model simulation provides the possibility for testing the business strategy of clothing enterprises using 3D printing. In addition, a positive attempt has been made in the collaborative research of using both a static display business model and a dynamic simulation business model.

Changing ecosystems with digitalisation, the value of information affects all sub-ecosystems, and due to societal changes, management approaches have started to be implemented. This new administration digitalisation, which is the basis of their strategy, made it mandatory for them to adapt to technology. This article details the theoretical basis of the business ecosystem to investigate the integration of human-computer interaction (HCI) technology and platform business ecosystem into the artificial intelligence (AI) environment and to create practicality for the intellectual development of platform business strategy ecosystem management. Then, in the context of textile e-commerce, the intelligent clothing ecosystem is recommended, and the structure of the smart clothing ecosystem is created. A flexible production planning model with multiple constraints and maximum cost savings has been developed within system constraints and objective function scope. The standard genetic algorithm after optimisation was used to solve the aim of model function (based on double-layer integer coding). In the context of the parameters of the algorithm and textile layout, the algorithm was calculated with the MATLAB simulation tool, and then a textile experiment was carried out to solve the problem of system management. Finally, the audio, interactive customer survey results were analysed with structural equation modelling, and a human-computer interactive customer trust model was proposed. The results indicate that the calculation results of the objective function with 6 order sizes and 40 order sizes tend to be good and that the 6th order, respectively, tends to be good. The Gantt chart, calculated by the optimisation algorithm, can show the equipment selection strategy, start time and end time of each order in different workshops. The combination of each operation planning strategy is the production planning chart that corresponds to the order. It is thought that this study, AI-oriented HCI technology for future studies, can solve the strategic management problem of the platform business ecosystem, realise the efficient ecological functioning of the system and benefit businesses in this context.

More and more enterprises have realized the importance of business model innovation. However, the model tools for it are still scarce. There is a clear research gap in this academic field. Therefore, the aim of this study is to put forward a visual business model innovation model.

The scientific literature clustering paradigm of grounded theory is used to design business model innovation theory model (BMITM). BMITM and the business model innovation options traced back from 870 labels in the grounded process are integrated into a unified framework to build the business model innovation canvas (BMIC).

BMIC composed of three levels and seven modules is successfully developed. 145 business model innovation options are designed in BMIC. How to use BMIC is explained in detail. Through the analysis of innovation hotspots, the potential business model innovation directions can be found. A new business model of clothing enterprises using 3D printing is innovated with BMIC as an example.

Compared with the previous tools, BMIC owns a clearer business model innovation framework and provides a problem-oriented business model innovation process and mechanism.

BMIC provides a systematic business model innovation solution set and roadmap for business model innovation practitioners.

BMIC, a new tool for business model innovation is put forward for the first time. “Mass Selection Customization-Centralized Manufacturing” designed with BMIC for the clothing enterprises using 3D printing is put forward for the first time.

3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.

A business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.

First, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.

The new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.

The new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.

A new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.

Considering only two-dimensional (2D) ease allowance cannot fully reflect the three-dimensional (3D) relationship between the position of clothing and the human body. The purpose of this paper is to propose a method with a 3D space vector and corresponding distance ease to characterize fitting garments and then used to construct personalized clothing for similar shape body.

Firstly, a 3D scanner was used to obtain mannequin and fitted garment data, and 17 layers of cross-sections of the upper body were extracted. Then, 37 space vectors and corresponding space angles on each cross-section were obtained with the original point. Secondly, the detailed distance ease between the mannequin and garment was constructed due to the difference between garment vectors and body vectors. Thirdly, the distance ease mathematical models were achieved and used to calculate distance ease on a similar shape body. Additionally, the fit garment is constructed, and the garment pattern is altered by the geometric pattern alteration method.

The results show that 3D space vectors can explain the relationship between body skin and garment surface of the upper body properly. The distance ease is modeled by mathematic expressions and successfully used to make a new garment to fit a similar shape body.

The proposed method of constructing garments based on distance ease and 3D space vectors can create a fitted garment for a similar shape body effectively and accurately. It is useful for the personalized garment design and suitable for the manufacturing process.

With the developments of e-commerce markets, novel recommendation technologies are becoming an essential part of many online retailers’ economic models to help drive online sales. Initially, the purpose of this paper is to undertake an investigation of apparel recommendations in the commercial market in order to verify the research value and significance. Then, this paper reviews apparel recommendation techniques and systems through academic research, aiming to acquaint apparel recommendation context, summarize the pros and cons of various research methods, identify research gaps and eventually propose new research solutions to benefit apparel retailing market.

This study utilizes empirical research drawing on 130 academic publications indexed from online databases. The authors introduce a three-layer descriptor for searching articles, and analyse retrieval results via distribution graphics of years, publications and keywords.

This study classified high-tech integrated apparel systems into 3D CAD systems, personalised design systems and recommendation systems. The authors’ research interest is focussed on recommendation system. Four types of models were found, namely clothes searching/retrieval, wardrobe recommendation, fashion coordination and intelligent recommendation systems. The forth type, smart systems, has raised more awareness in apparel research as it is equipped with advanced functions and application scenarios to satisfy customers. Despite various computational algorithms tested in system modelling, existing research is lacking in terms of apparel and users profiles research. Thus, from the review, the authors have identified and proposed a more complete set of key features for describing both apparel and users profiles in a recommendation system.

Based on previous studies, this is the first review paper on this topic in this subject field. The summarised work and the proposed new research will inspire future researchers with various knowledge backgrounds, especially, from a design perspective.

It is widely known that fast-fashion retailers are struggling to keep up with consumer attention for quick responses within the fashion industry. With the advance of Internet and e-commerce, consumers prefer to purchase online. Online platform information has become an essential source for exploring consumer attention. However, there is often a mismatch between the information provided by retailers and the feedback received from consumers, leading to an imbalance between the supply side and demand side of online information. The purpose of this study is therefore to provide a unified approach to discover consumer attention from the design topic aspect by revealing the information imbalance between supply side and demand side.

To address the issue of online information imbalance and discover consumer attention, this study proposed an approach that focuses on the design topic perspective. The design topic is a collection of design elements that represent a clothing-design feature more comprehensively and accurately compared to a single design element. The proposed approach begins with generating design topics through topic modeling based on online information provided by retailers on e-commerce platforms. Two indicators, influence degree and attention degree, are then used to quantify the intensity of supply information and consumer attention related to design topics. Finally, design topic strategy diagrams are constructed to reveal information imbalance and discover consumer attention.

The experimental case demonstrates the existence of information imbalance, indicating that the intensity of supply information and consumer attention from the perspective of design topics is not uniform, although both follow the Pareto principle. The results of consumer attention distribution with heavy power-law tails are consistent with current research findings. This further demonstrates that the proposed approach is capable of discovering consumer attention in the design topic strategy diagrams.

The issue of information imbalance between retailers and consumers poses a challenge in keeping up with customer attention. The proposed approach offers a practical solution by visually identifying the symptoms of information imbalance and discovering consumer attention through design topic strategy diagrams. This approach provides fast-fashion retailers with a valuable reference to seize market opportunities, improve product design and adjust marketing or management strategies.

This study proposes a novel approach to disclose the issue of information imbalance between supply side and demand side and therefore to discover consumer attention from the perspective of design topics. In addition, guidelines for applying the proposed approach for fast-fashion marketing and management are presented.

Exercising is a key approach adopted by muscular dystrophy patients to halt the weakening of muscles as it can eventually lead to serious immobility issues. Though it is essential to exercise on a daily basis for healthy living, there is no mention of any research effort in the current literature regarding the development of an apparel product for these mobility-affected patients that might assist them both in meeting their exercising needs and providing them some comfort in their daily living. Thus, this paper aims to focus on identifying the specific needs of muscular dystrophy victims and proposing special adaptive clothing solutions to support their daily exercise and mobility needs.

To achieve the objectives of this study, attention was focused on the muscular dystrophy afflicted women in Sri Lanka. Semi-structured interviews were conducted with the female victims of muscular dystrophy and their lifestyles were observed carefully; additional data were gathered by holding semi-structured interviews with their physiotherapists. Further, interviews were conducted with both garment technologists and fabric technologists too. Data gathered through these methods were analyzed qualitatively using the principles of thematic analysis and then aggregate conclusions were drawn.

It was observed that the patients were engaged in special activities such as exercising three times a day besides following their normal day-to-day activities to maintain and develop muscle strength. It soon became evident that these women found it difficult to perform their daily exercise routines with their regular clothing and were looking for custom made clothing they could wear all day long in comfort and avoid the problems that arose while exercising. The study specifies the requirements that must be met to satisfy both generic and specific needs. Considering all these aspects some adaptive clothing solutions were proposed to support daily exercising activity with respect to comfort, convenience, health and safety, as well as socio-cultural and psychological needs.

The area of fusing generic and specific features to support the daily exercising needs of muscular dystrophy victims is an untouched field of experimentation and being a need of the disabled, the present study marks a milestone on the way to a novel area of apparel design, besides exploring a new field of research.