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Nowadays, artificial intelligence (AI) technology has demonstrated extensive applications in the field of art design. Attribute editing is an important means to realize clothing style and color design via computer language, which aims to edit and control the garment image based on the specified target attributes while preserving other details from the original image. The current image attribute editing model often generates images containing missing or redundant attributes. To address the problem, this paper aims for a novel design method utilizing the Fashion-attribute generative adversarial network (AttGAN) model was proposed for image attribute editing specifically tailored to women’s blouses.

The proposed design method primarily focuses on optimizing the feature extraction network and loss function. To enhance the feature extraction capability of the model, an increase in the number of layers in the feature extraction network was implemented, and the structure similarity index measure (SSIM) loss function was employed to ensure the independent attributes of the original image were consistent. The characteristic-preserving virtual try-on network (CP_VTON) dataset was used for train-ing to enable the editing of sleeve length and color specifically for women’s blouse.

The experimental results demonstrate that the optimization model’s generated outputs have significantly reduced problems related to missing attributes or visual redundancy. Through a comparative analysis of the numerical changes in the SSIM and peak signal-to-noise ratio (PSNR) before and after the model refinement, it was observed that the improved SSIM increased substantially by 27.4%, and the PSNR increased by 2.8%, serving as empirical evidence of the effectiveness of incorporating the SSIM loss function.

The proposed algorithm provides a promising tool for precise image editing of women’s blouses based on the GAN. This introduces a new approach to eliminate semantic expression errors in image editing, thereby contributing to the development of AI in clothing design.

This study aims to investigate how configurations of boundary objects (BOs) support innovation teams in developing innovative product concepts. Specifically, it explores the effectiveness of different artefact configurations in facilitating collaboration and bridging knowledge boundaries during the concept development process.

The research is based on data from ten undergraduate innovation teams working with an industry partner in a creative industry. Six categories of BOs are identified, which serve as tools for collaboration. The study applies fsQCA (fuzzy-set qualitative comparative analysis) to analyse the configurations employed by the teams to bridge knowledge boundaries and support the development of innovative product concepts.

The findings of the study reveal two distinct groups of configurations: product envisioning and product design. The configurations within the “product envisioning” group support the activities of visioning and pivoting, enabling teams to innovate the product concept by altering the product vision. On the other hand, the configurations within the “product design” group facilitate experimenting, modelling and prototyping, allowing teams to design the attributes of the innovative product concept while maintaining the product vision.

This research contributes to the field of innovation by providing insights into the role of BOs and their configurations in supporting innovation teams during concept development. The results suggest that configurations of “product envisioning” support bridging semantic knowledge boundaries, while configurations within “product design” bridge pragmatic knowledge boundaries. This understanding contributes to the broader field of knowledge integration and innovation in design contexts.

Businesses embark on cause-related marketing (CRM) initiatives as a marketing strategy to fortify consumers' behavioural intentions. Prior research indicates that human values could be tapped to understand the consumers' responses to perceived organizational motives behind undertaking social cause initiatives. This research employs Schwartz's theory of human values to examine consumers' patronage intentions towards CRM-linked fashion products. Moreover, fashion leaders play a crucial role in the diffusion of the latest fashion and fashion trends. This research investigates by integrating human values and fashion leadership, offering insights into CRM-linked fashion consumption motives.

The overarching goal was to investigate the complex interplay between human values and female fashion leadership to predict CRM patronage intention (CPI). Hence, a large-scale research study on 2,050 samples was undertaken by adopting threefold partial least squares–multigroup analysis–artificial neural network (PLS-MGA-ANN) to establish and empirically test a comprehensive model.

This study is unique as it establishes and validates the relative or normalized importance placed on human values by fashion leaders, thereby predicting CPIs. The results revealed that women with high-fashion leadership and specific value types (benevolence, universalism, self-direction) are more likely to patronize CRM-linked fashion retailers. In addition, the findings validated that women with low-fashion leadership and specific value types (tradition, security, conformity) are more likely to patronize CRM-linked fashion stores.

The findings provide a valuable rationale to non-profit marketers, fashion marketing experts and practitioners to design customer value-based profiling and manage crucial CRM decisions.

Shortly before the Second World War, a woman who had never accepted her orphan status, Gabrielle Bonheur Chanel, nicknamed ‘Little Coco’ by her father and known as ‘Coco’ to her relatives, became the first women in history to build a world-class industrial empire. By 1935, Coco, a fashion designer and industry captain, was employing more than 4,000 workers and had sold more than 28,000 dresses, tailored jackets and women's suits. Born into a poor family and raised in an orphanage, she enjoyed an intense social life in Paris in the 1920s, rubbing shoulders with artists, creators and the rising stars of her time.

Thanks to her entrepreneurial skills, she was able to innovate in her methods and in her trendsetting approach to fashion design and promotion. Coco Chanel was committed and creative, had the soul of an entrepreneur and went on to become a world leader in a brand new sector combining fashion, accessories and perfumes that she would help shape. By the end of her life, she had redefined French elegance and revolutionized the way people dressed.

This study aims to examine the conceptual distinction of two clothing orientations – style orientation and fashion orientation. Style and fashion orientations both express identity and individuality, but the fashion orientation may more strongly reflect materialistic values, which extensive evidence shows are detrimental to well-being. This study investigates how the clothing orientations are associated with materialism and subjective well-being.

The conceptual distinction between style and fashion orientations and their associations with materialism and subjective well-being were investigated via an online survey (N = 4,591) conducted in Germany, Poland, Sweden and the USA. Participants aged 18–65 were recruited based on national representative quotas for age, gender, education and region.

The regression results support a conceptual distinction between the style and fashion orientation. Style orientation was positively associated with subjective well-being compared to fashion orientation. Both the style and fashion orientations were positively correlated with materialism, but the association was much stronger for fashion orientation and materialism exhibited a strong negative association with subjective well-being. Interestingly, materialism moderated the association between fashion orientation and well-being but not between style orientation and well-being.

The four examined countries were Western, and, thus, the findings cannot be generalized to other populations. In addition, this study specifically examined relationships in a clothing context. To enable wider generalization, the relationships tested must be explored in other countries, especially non-Western, and also across other product categories.

The findings of this study can help retailers develop their marketing programs, product and service offerings and specifically their communications more closely targeted to consumers’ clothing orientations.

This study contributes by conceptually distinguishing between clothing style and fashion orientations and investigating their divergent associations to materialism and subjective well-being. This research also raises the question of whether fashion orientation is independent or rather, an aspect of materialism, which has implications for other consumption domains as well.

Customer experience has become a vital premise in service theory and practice. Despite researchers' and managers' growing interest, the customer experience remains a complex and multidimensional concept that is challenging for service providers to understand. This study aims to graph the experience in its multidimensionality by categorizing and proposing matching practices for service marketing managers to channel and foster customer experiences in customer journeys.

To support the predominantly conceptual nature of the study, an abductive approach underpinned by the authors' vast experience in academia and practice, real-life autohermeneutic phenomenological experience tales and theory on customer experience and its management by providers is deployed to craft a model that addresses and highlights the multidimensionality of experience.

This study introduces the “GraphEx” (Graph Experience) hip-pocket model, which expresses customer experience in a simple yet multidimensional fashion and offers managerial practices to foster the customer's experience. The model contains three dimensions (valence, type of experience and visceral intensity) and five managerial practices (urgent patchwork, restoring, activating and stimulating desire, bolstering and safeguarding appreciation).

This study contributes to the service literature by creating granularity in the multidimensionality of customer experience. This study advances customer experience management in practice by providing service managers with novel possibilities for understanding and managing customer experiences intelligently. This can help service providers streamline and innovate customer experience strategies during customer journeys and foster customer loyalty.

This paper aims to integrate the consumption perspective within the Industrial Marketing and Purchasing (IMP) debate. The study delves into how consumer communities can be conceived like other network business actors. The perspective of sustainable new ventures (SNVs) in the fashion industry is adopted, considering their specific connection with consumer communities.

Adopting a multiple case study methodology, this paper uses a qualitative approach. Data collection mainly relies on interviews conducted with 10 SNVs in the fashion industry; this sector is a fertile ground for studying sustainability and consumer communities. For data analysis, the abductive approach of systematic combining is applied.

The paper identifies four distinct types of consumer communities and four roles that they can assume as business actors in the business network. Owing to their engagement in these specific roles, consumer communities become part of the SNVs’ network, akin to other business-to-business players.

This study represents one of the initial endeavors to introduce consumption into the IMP theoretical framework. In this paper’s conceptualization, consumer communities are groups of consumers and collective actors in the business network. Additionally, this study advances the research on sustainability as a network concept by including consumer communities’ roles in business networks.

Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning technique, generative adversarial networks (GANs). GANs are a type of deep learning architecture capable of generating new data similar to the training data that were used to train it, and thus, it is designed to learn a generative model that can produce new samples. GANs have been used in multiple marketing areas, especially in creating images and video and providing customized consumer contents. Through providing a holistic picture of GANs, including its advantage, disadvantage, ethical considerations, and its current application, the study attempts to provide business some strategical orientations, including formulating strong marketing positioning, creating consumer lifetime values, and delivering desired marketing tactics in product, promotion, pricing, and distribution channel. Through using GANs, marketers will create unique experiences for consumers, build strategic focus, and gain competitive advantages. This study is an original endeavor in discussing GANs in marketing, offering fresh insights in this research topic.

The study investigates the factors that influence young consumers (Gen Zs and Ys) in emerging markets to engage fashion ads of non-luxury fashion retail small- to medium-size enterprises (SMEs) on social media. Through a desk assessment of practice and the phenomenon's available evidence in the extant literature, four main drivers were delineated, reviewed and subsequently tested to influence young consumers' behavioural engagements of emerging markets' fashion SMEs' social media contents.

A non-probability sample of 1,150 respondents (Gen Y and Z combined) in Ghana, an emerging market, formed the sample for the study. The respondents assessed four empirically identified antecedents (sales campaigns, relevant sales-related information, catchy and inspiring product/brand photo/video and consumer-generated contents) that are likely to influence their behavioural engagement on social media platforms (Instagram, Facebook, WhatsApp and Twitter). SmartPLS (version 3.3.3) was employed to perform partial least square structural equation modelling.

The results showed that to engage fashion-related ads, particularly from non-luxury fashion SMEs, young consumers consider sales campaigns, cues from consumer-generated contents, as well as quality and inspiring videos and photos. Less attention is given to relevant sales-related information.

The three significant drivers of engagement found in the current study provide managerial knowledge for non-luxury fashion SMEs in emerging markets. Videos and still pictures must be of high definition and quality. Short and long promotional campaigns may drive positive behavioural engagements. Interactivity between fashion SMEs and young consumers is encouraged as it precipitates the positive engagement behaviours enabled by social media. The study concludes with actionable recommendations for the non-luxury fashion SME sector in emerging economies.

The study is the first of its kind to ascertain what drives young consumers' engagement with non-luxury fashion SMEs on social media. It provides managerial insights and guidance to SMEs in emerging markets on effective social media fashion retailing targeted mainly at digital natives, the dominant generational cohorts on social media in most emerging economies.

This study aims to explore the patterns and transformational dynamics of the executive–interpreter network in the innovation processes of small- and medium-sized enterprises in hospitality.

Grounded in social network theory and adopting a case-based approach, this study features a multi-case design focusing on three Chinese boutique hotels. Data were collected through Web page and document reviews, participant observations and semistructured interviews.

Results capture how executive–interpreter network dynamics contribute to innovation in small- and medium-sized hotels. Key factors in social networks (e.g. size, scope and strength) shift throughout innovation. This study presents a design-driven approach as a means of innovation. Findings also delineate the network development conditions under which innovation dynamically occurs in boutique hotels.

Practical implications center on how network dynamics help small- and medium-sized hotels innovate more effectively. These insights can assist hotel operators and prospective market entrants in improving their hotels’ performance and competitiveness.

This study blends social network theory with a design-driven approach to explore innovation mechanisms in small- and medium-sized hotels. It offers empirical evidence for practitioners regarding design-driven innovation. Findings enrich the body of knowledge on both design-driven innovation theory and hospitality innovation.