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The purpose of this study was to explore the determinant factors of the adaptive clothing market for disabled customers and to identify the influential elements in the fashion industry, with the aim of establishing the influential factors that drive the adaptive apparel business in the local market. The study developed a path model of relationships incorporating the disabled consumer background, consumer purchase intention and demand and elements of the fashion industry. This model can be used as a reference for fashion practitioners.

A quantitative approach was adopted for this empirical study. A survey was designed to investigate the connections between the consumer-related and industry-related variables. A set of measurements was developed and validated for the survey. The data were collected from a sample of 175 local wheelchair users, with a response rate of approximately 6.6 per cent. The data were analysed using SmartPLS, and structural equation model analysis was applied to identify the relationships between the variables.

The results of this study demonstrated that consumer purchase intention for adaptive apparel was affected closely by environmental factors, and consumer demand was significantly related to industry aspects including the product complexity and the business operations along with all elements of the industrial practice. The findings also revealed that the disability level was related to the users' purchase intentions, but the financial capability of the disabled consumers did not affect the intention to purchase adaptive clothes products. These results could suggest that economic issues are not the consumer's prior concern when purchasing apparel, but rather the disability condition. Those who demand adaptive apparel require advanced performance levels of product design, technology application and service.

The study originated from the situation that the Hong Kong fashion market lacks an adaptive market specifically for the minority group of disabled consumers. Why such a niche market has not been developed is unclear to the practitioners. It is necessary to investigate from both consumer-related and industry-related factors. Specifically, the research explored the consumer background and industry elements to identify the factors that influence disabled consumers to purchase apparel, in order to inform fashion practitioners who are interested in the niche market of disabled consumers in Hong Kong. It is anticipated that the determinants of adaptive market development can be extended to wider areas of the Chinese or other Asian markets.

The purpose of this study is to examine relationship between numerous factors (fashion orientation, conspicuous consumption and environmental consciousness) that influence fast fashion (FF) purchase intention and their impact on FF purchase behavior and exploring the moderating effect of sustainable clothing consumption attitude.

This study uses quantitative analysis approach, wherein data have been collected from 571 college students by using non-probability snowball sampling. Partial least square structural equation modeling (PLS-SEM) has been applied to analyze the relationships among variables.

Determinants fashion orientation and conspicuous consumption have substantial impact on the desire to buy FF, which has strong association with FF purchasing behavior. Environmental awareness, contrarily, has detrimental impact on FF purchasing intentions. Furthermore, sustainable clothing consumption attitude significantly moderates FF intention–behavior relationship.

Findings may be viewed as a driving course in textile and garment sector for entrepreneurs as they represent customers’ intents and behavior in connection to the adoption of FF. Strategists can understand the product’s lifecycle; marketers can define innovative ways of marketing, advertising and promotion; start-ups can look for opportunities in sustainable fashion industry by innovating, manufacturing and dealing in eco-friendly sustainable products; and policymakers can make suitable policies to create awareness regarding sustainable fashion.

To the best of the authors’ knowledge, there is no study that comprehensively deals with defining, structuring and validating factors affecting purchase intention and behavior in case of fashion industry, accompanied by the role of sustainable consumption attitude as a moderator between FF intention and behavior, in a single model.

This study aims to analyze and discuss whether and how consumer-to-manufacturer (C2M) mode empowered by e-commerce retail platforms’ big data affects the stock returns of firms in supply chains.

This study selects 195 companies affected by four C2M events as samples and empirically analyzes the impact mechanisms of C2M mode on supply chain firms’ stock returns by event study.

This paper finds that C2M announcements own a positive impact on the stock returns of supply chain firms. Further, the results show that the business and financial characteristics play a significant impact on the relationship between the C2M mode and firm stock return performance. For example, C2M mode leads to huge stock returns when firms cooperate with the platforms related to their business content. In addition, the business scope can strengthen the positive promotion of C2M mode in stock returns, while business concentration weakens the positive promotion of C2M mode in stock returns.

The results found in this paper can provide practical guidance for the firms in supply chains to further apply C2M mode from the business characteristics and financial performance view.

Existing clothing parsing methods make little use of dataset-level information. This paper aims to propose a novel clothing parsing method which utilizes higher-level outfit combinatorial consistency knowledge from the whole clothing dataset to improve the accuracy of segmenting clothing images.

In this paper, the authors propose an Outfit Memory Net (OMNet) that augments original feature by aggregating dataset-level prior clothing combination information. Specifically, the authors design an Outfit Matrix (OM) to represent clothing combination information of single image and an Outfit Memory Module (OMM) to store the clothing combination information of all images in the training set, i.e. dataset-level clothing combination information. In addition, the authors propose a Multi-scale Aggregation Module (MAM) to aggregate the clothing combination information in a multi-scale manner to solve the problem of large variance in the scale of objects in the clothing images.

Experiments on Colorful Fashion Parsing Dataset (CFPD) dataset show that the authors' method achieves 93.15% pixel accuracy (PA) and 51.24% mean of class-wise intersection over union (mIoU), which are satisfactory parsing results compared with existing methods such as PSPNet, DANet and DeepLabV3. Moreover, through comparing the segmentation accuracy of different methods for each category, MAM could effectively improve the segmentation of small objects.

With the rise of various online shopping platforms and the continuous development of deep learning technology, emerging applications such as clothing recommendation, matching, classification and virtual try-on system have emerged in the clothing field. Clothing parsing is the key technology to realize these applications. Therefore, improving the accuracy of clothing parsing is necessary.

The purpose of this article is to investigate whether the corporate social responsibility (CSR) and innovation activity of Certified B Corps® is comparable to listed companies in the Italian fashion industry.

The study includes a systematic literature review performed on Scopus® and combining keywords related to CSR and the fashion industry. Moreover, the literature review involves empirical analyses performed using a mixed-methods approach. First, a text-based content analysis was carried out on the companies' sustainability reports using the keyword scoring approach. The innovation index was then calculated, and multiple ordinary least squares (OLS) linear regressions were performed.

Based on the data available, it has emerged that Certified B Corps® who pursue a more significant number of SDGs are more likely to implement circular economy principles. Moreover, Certified B Corps® that have higher transparency standards and assume social responsibility practices also have higher innovation activity; in contrast, companies who used CSR only as a marketing tool have lower activity.

The analyses were influenced by the coronavirus disease 2019 (COVID-19) pandemic, revealing weaker relationships between the variables, as the analyses involved 2020 data. Furthermore, although the analysis considers the entire population of Certified B Corps® and listed companies in the Italian fashion industry, the size of the sample analyzed influenced the results and insights. Therefore, the analysis does not allow for generalizability. Finally, the study was conducted on a single country whose economic and social contexts have influenced some variables.

The paper highlights some managerial implications. Managers should consider CSR to be an investment and an opportunity to survive the post-COVID-19 pandemic by applying the triple bottom line (TBL) approach in formulating strategies and increasing investments to develop sustainable innovations.

The article explores B Corps, which has received minimal attention in the literature, to propose a deeper understanding of the topic.

Using resource-based theory and social cognitive theory, this study aimed to investigate crucial resources that new US fashion ventures need to survive the initial stage of business development. It also intended to discover the role and characteristics of founders that contribute to the success of a fashion business, as well as challenges and struggles that fashion entrepreneurs face.

For the study, a qualitative research method with in-depth personal interviews was conducted. Participants were recruited through purposeful sampling methods. Using a grounded theory approach, we analyzed the approximately 308 pages of primary source data, transcribed from the records of the interviews.

Findings were categorized into three major themes. First, financial resources and literacy, marketing, merchandising, as well as legal resources were identified as critical resources at the firm level. Second, at the individual level, four important human agency factors, including intentionality, forethought, reactiveness and reflectiveness were revealed as essential for the success of fashion entrepreneurs. Lastly, relationships and networks were highlighted at both firm and individual levels.

This study contributes to the understanding of fashion entrepreneurship, an understudied area. The study identified critical resources for the success of fashion startups, especially during the initial business development process. The findings also emphasized the importance of human agency factors and networks at both firm and individual levels.

This study aims to examine the effects of the characteristics of apparel professionals on their attitude toward sustainability-related technology in the context of a developing country, Bangladesh.

A quantitative approach was used to investigate the apparel professionals’ perception of sustainability-related technology. A survey was conducted, and 204 valid responses were used in data analysis. The structural equation modeling technique was used to analyze the data.

The findings demonstrate that apparel professionals’ personal innovativeness positively impacts their knowledge of apparel technology. Knowledge of apparel technology and environmental issues in apparel manufacturing both significantly and positively impact their level of awareness of sustainability-related technology in apparel manufacturing. The findings also suggest that managers’ level of awareness of sustainability-related technology has a significant positive impact on their attitude toward sustainability-related technology.

Fishbein’s attitude theory was applied to examine how the various characteristics of apparel professionals (i.e. personal innovativeness in technology, knowledge of apparel technology, knowledge of environmental issues of apparel manufacturing) affect their awareness of and attitude toward sustainability-related technology. This study expands our understanding of the causal flow among cognitive variables of apparel professionals, including their innovativeness, knowledge, awareness and attitudes. The findings of the study can be helpful to the apparel industry to improve apparel professionals’ adoption of sustainable technology.

T Education is a leading educational science and technology enterprise in China with technology-driven, talent intimacy and quality leadership as the core development objectives. Since its inception, it has been committed to creating better learning experience for children. As the predecessor of T-education, X-education was founded in Beijing in 2003. At first, it mainly provided after-school math counseling for school-age children. Over the past 10 years, its business has been expanding, covering almost every aspect of school-age education. This case studies accounting issues and business ethics challenges that firms may face when they transform from a single (traditional education) line of business to a multiple channel business.

The purpose of this paper is to investigate how fairness evaluations are constructed in a B2B context.

This paper conducts a field study of Air Greenland and its internal and external customers based on strong structuration theory (Stones, 2005). The authors employ context and conduct analysis to analyze how fairness evaluations emerge across four levels of structuration.

The paper finds that fairness evaluations emerge as a result of the interaction between external institutional pressures, agents' internal structures, and situated reflection and outcomes. The construction of fairness evaluations was embedded in contradictory institutional structures, where groups of actors constructed different evaluations of fair profits, procedures and prices. Actors furthermore worked on changing position-practice relations which shifted relations, external structures and affected outcomes and fairness evaluations.

This paper offers a conceptualization of embedded agency as emerging across the four levels of structuration. This contributes to debates in strong structuration theory through conceptualizing and analyzing how actors may be both be constrained and oriented by structures while reflexively adapting structures across the four levels of structuration. The paper extends extant pricing fairness research by illustrating how actors' construction of fairness flexibly develop fairness evaluations while responding to legitimacy and societal demands, including the needs of particular customer groups.