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To enhance the pleasure experience of clothes shopping online, finding satisfactory clothing and similar clothing recommendations to customers should be available and accurate. The purpose of this paper is to present a method for automatically computing the similarity between two apparels and giving an effective recommendation.

Based on a tabular layout of article characteristics the authors built a clothing information model to describe clothing. The clothing attributes are classified according to excavating features of the model. After the proposal of the computation algorithm for various attributes, an efficient similarity computation method is developed to obtain similar clothes with the given cloth. To prevent error and information omission during the computation, the analytic hierarchy process method and entropy method are adopted by the integrated weights as a control.

Clothing is a non‐rigid product which has a lot of crossover and complicated attributes and features. This paper found a tabular layout of article characteristics can explain the clothing clearly. Through experiments the authors found the weight of attributes to have a great influence on similar results during the similarity computation.

This paper presents a new way to describe clothing information, and present the algorithm for attributes computation.

Clothing retrieval is very useful to help the clients to efficiently search out the apparel they want. Currently, the mainstream clothing retrieval methods are attribute semantics based, which however are inconvenient for common clients. The purpose of this paper is to provide an easy‐to‐operate apparels retrieval mode with the authors' novel approach of clothing image similarity measurement.

The authors measure the similarity between two clothing images by computing the weighted similarities between their bundled features. Each bundled feature consists of the point features (SIFT) which are further quantified into local visual words in a maximally stable extremal region (MSER). The authors weight the importance of bundled features by the precision of SIFT quantification and local word frequency that reflects the frequency of the common visual words appeared in two bundled features. The bundled features similarity is computed from two aspects: local word frequency; and SIFTs distance matrix that records the distances between every two SIFTs in a bundled feature.

Local word frequencies improves the recognition between two bundled features with the same common visual words but different local word frequency. SIFTs distance matrix has the merits of scale invariance and rotation invariance. Experimental results show that this approach works well in the situations with large clothing deformation, background exchange and part hidden, etc. And the similarity measurement of Weight+Bundled+LWF+SDM is the best.

This paper presents an apparel retrieval mode based on local visual features, and presents a new algorithm for bundled feature matching and apparel similarity measurement.

This paper examines the problem of lack of historical data and inadequate consideration of factors influencing demand in the forecasting of demand for fast fashion clothing and proposes an improved Bass model for the forecasting of such a demand and the demand for new clothing products.

From the perspective of how to solve the lack of data and improve the precision of the clothing demand forecast, this paper studies the measurement of clothing similarity and the addition of demand impact factors. Using the fuzzy clustering–rough set method, the degree of resemblance of clothing is determined, which provides a basis for the scientific utilisation of historical data of similar clothing to forecast the demand for new clothing. Besides, combining the influence of consumer preferences and seasonality on demand forecasting, an improved Bass model for a fast fashion clothing demand forecast is proposed. Finally, with a forecasting example of demand for clothing, this study also tests the validity of the method.

The objective measurement method of clothing similarity in this paper solves the problem of the difficult forecasting of demand for fast fashion clothing due to a lack of sales data at the preliminary stage of the clothing launch. The improved Bass model combines, comprehensively, consumer preferences and seasonality and enhances the forecast precision of demand for fast fashion clothing.

The paper puts forward a scientific, quantitative method for the forecasting of new clothing products using historical sales data of similar clothing, thus solving the problem of lack of sales data of the fashion.

The purpose of this paper is to investigate the effect of product description cues as a way to differentiate luxury products for the absolute luxury consumer and the effect of individual traits such as need for uniqueness, product involvement, and product knowledge on consumers’ perceptions of expected price.

An adult sample of 253 female US consumers were recruited for an online survey.

Consumers’ need for uniqueness was related to their level of clothing involvement, which in turn was related to clothing knowledge. Fashion clothing involvement was positively related to participants’ product knowledge which in turn positively influenced participants’ perceived change in expected price of products in response to various product descriptors or cues related to absolute luxury products. In addition, younger consumers were found to be more involved in fashion clothing than older consumers.

This study extends the research into the luxury market and identifies elements of the marketing mix which might be manipulated to better inform potential customers about the luxury product. The study further emphasizes that product descriptors or cues can have an impact on price judgments, especially for highly involved and knowledgeable consumers. This is especially important to academicians as well as marketers since high fashion involved consumers have often been seen as drivers, influential, and legitimists of the fashion adoption 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.

This study examines fashion consciousness among Chinese, Japanese and US teenagers. The purpose of the study was to examine similarities and differences in attitudes toward fashion across these three markets. The results show that significant differences in fashion consciousness exist between Chinese teens and their Japanese and US counterparts. At the same time, the US and Japanese teens show similarities in their attitudes toward fashion. The findings may support the idea of market differences in fashion consciousness between developed countries and less developed countries. While there are opportunities for fashion merchants to benefit from market similarities, an understanding of the idiosyncrasies underlying motivations of teen fashion in each market is needed.

In view of high consumption situation of raw materials in the apparel industry due to unique and diversified style, the purpose of this paper is to investigate the application of pattern transformation between clothing and tent, explore the feasibility of extending multi-functional product and provide experimental demonstration for realizing 5R (Reduce, Reevaluate, Reuse, Recycle, Rescue) design goal of garment product.

According to the results of market research, in order to make single product have the functions of both outdoor couple clothing and simple tent, the planar patterns of clothing and tent are compared and transformed to make them compatible with each other, then the removable multi-functional design and technique processing are adopted.

It was found that outdoor clothing and tent with similar application occasions and raw materials could realize the assumption of multi-functional product. Their combination has the functions of both clothing and tent by wearing and assembling.

By means of this transformation design, the diversification and enjoyment of garment styles and functions can be realized. This helps to improve the energy efficiency of raw materials and accessories by increasing the frequency of product reuse and sharing. In addition, the enjoyment design of products also helps to lead and promote ecological consumption.

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.

Self‐esteem is an important motivational drive for consumption involving both the acceptance and rejection/avoidance of symbolic goods. This paper examines the relationship between self‐esteem and the rejection of goods and brands within the context of fashion consumption by young professionals. A conceptualisation which accounts for consumers’ use of various strategies in their efforts to maintain or enhance their self‐esteem is suggested. A small‐scale exploratory study is used to examine first, how consumers invest products and brands with negative symbolic meanings; and second, how this leads consumers to reject products and brands. The importance of understanding negative symbolic consumption when marketing high involvement products such as fashion goods is identified; and the implications for fashion retailers and marketing management are discussed.

The purposes of this research are to examine the extent to which daughters view their mothers as consumption role models, the extent to which daughters serve as consumption role models for their mothers, and the extent to which external role models are shared by mothers and their adolescent daughters.

Two qualitative studies focused on mothers‐adolescent daughters‐vicarious role models interactions as drivers of consumption behaviors in Western cultures. Study 1 included 20 in‐depth interviews with mothers and their adolescent daughters (conducted separately). Study 2 included five of the original dyads interviewed jointly and observed in fashion stores.

Regarding adolescent daughters' use as role models and fashion markers for their mothers, most mothers confirmed that their adolescent daughters' fashion opinion was very important. Second, based on consumer socialization arguments, mothers served as role models for their adolescent daughters. Most dyads shop for fashion items together and in the same stores. Regarding the issue of cognitive versus chronological ages, the studies suggest that there is a gap between mothers' cognitive and chronological ages in support of cognitive age theory and the youthfulness ideal of Western cultures. Notably, such a gap mostly failed to materialize for adolescent daughters. Hence, consumption similarity appears to be driven more by the gap for mothers than the gap for daughters. Finally, external role models such as celebrities did not have a great influence on mothers or their adolescent daughters.

The research used in‐depth interviews with and in‐store observation of mothers and adolescent daughters. Future research might use similar interviews with younger daughters. Another extension of the work reported here that can provide triangulation for the findings is to change from a qualitative to a quantitative methodology.