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This study aims to examine the research trends in fashion industry during the coronavirus disease 2019 (COVID-19) pandemic. Besides, it also provides an overview on the new marketing and operational strategies, and reveals the corresponding business challenges of a footwear enterprise in Hong Kong during the COVID-19 pandemic.

A comprehensive literature review is first conducted to identify the research trends in fashion industry during the COVID-19 pandemic. A qualitative exploratory case study is then used to illustrate how a footwear enterprise has coped with the COVID-19 pandemic.

The case study has showed that omni-channel retailing, collaboration with e-tailers, quick response system and mixed production strategy are adopted in the targeted case during the COVID-19 pandemic. Besides, the targeted case has also faced the challenges in the areas of sales, customer relationship management, and demand forecasting and inventory planning during the COVID-19 pandemic.

This study provides managerial insights on the real practices used to deal with the COVID-19 pandemic and proposes various academic future research directions in fashion industry based on the real-world observations.

The purpose of this study is to develop an empirical model by understanding the relative significance of interactive technological forces, such as chatbots, virtual try-on technology (VTO) and e-word-of-mouth (e-WOM), to improve interactive marketing experiences among consumers. This study also validates the moderating role of the perceived effectiveness of e-commerce institutional mechanism (PEEIM) as a moderator between attitude and continued intention.

Data were collected through personal visits and an online survey. The link to the survey questionnaire was shared on different social media platforms and social networking sites. A total of 362 responses obtained in the online and offline modes were considered for this study.

e-WOM emerged as the strongest predictor of attitude, followed by chatbots and VTO. The results of this study revealed that PEEIM did not moderate the relationship between attitude and continued intention.

Using the self-determination theory and behavioral reasoning theory as theoretical frameworks, this study is an initial endeavor in the online shopping context to empirically validate interactive forces like chatbots, VTO, e-WOM and PEEIM as moderators together to arrive at a holistic framework. These forces, in turn, act as significant contributors to online shopping satisfaction.

To gain a deeper understanding of the determinants impacting the intention of Chinese young consumers to utilize virtual try-on apps (VTOs), this study adopts a modified version of the electronic technology acceptance model (e-TAM). The primary objective is to investigate how consumers' characteristics influence their post-use feelings, subsequently affecting their attitude towards VTOs and their intention to use them. Additionally, this research aims to explore potential gender differences within this process.

In this study, a sample of 243 college students from a university in China was recruited to participate in on-site software use. A total of 227 valid questionnaires were collected and used for data analysis. Structural equation modeling (SEM) was employed to empirically evaluate the data and test the research hypotheses. Additionally, multiple group comparisons were conducted based on gender to examine potential differences in the acceptance process.

The findings of this study reveal a significant association between users' individual characteristics and post-use feelings. Moreover, there are notable differences between male and female students in terms of their perceptions of innovativeness, knowledge and understanding regarding post-use feelings. Notably, four variables within post-use feelings, except for perceived compatibility, are found to be predictive of attitude towards VTOs. Additionally, it is observed that attitude towards VTOs directly influences users' intention to utilize them.

This study contributes to the research on consumers' intention to use VTOs by examining the antecedents of post-use feelings, specifically four consumers’ individual characteristics. The findings of this study offer managerial insights for professionals to formulate marketing positioning and communication strategies.

The purpose of this study is to investigate the influence of augmented reality (AR) media characteristics on consumers’ purchase intention (PI) for fashion goods within the fashion industry context.

This study establishes five independent variables of salient AR media characteristics derived from existing studies which includes interactivity, vividness, augmentation, simulated physical control and environmental embedding. A quantitative online survey method is conducted with a sample of 172 respondents.

The findings suggest that all five AR media characteristics have a positive and significant influence on consumers’ PI for fashion goods. Among these five characteristics, interactivity and simulated physical control have the strongest positive impact on PI, followed by vividness, environmental embedding and augmentation.

This study provides valuable insights for fashion brands to better understand the media characteristics that consumers may be looking out for in AR experiences that could have an influence on their PI for fashion goods. This study also contributes to the literature by identifying the most influential AR media characteristics in the context of the fashion industry.

This study aims to investigate the impact of customer perceptions of Augmented Reality (AR) attributes such as augmentation, interactivity and vividness on attitudes towards AR mobile apps, virtual product and behavioural intentions. Also, the mediation role of customer engagement in the effect of perceptions of AR attributes on attitudes and behavioural intentions is examined using the Theory of Interactive Media Effects.

The study used a cross-sectional design. A total of 456 valid data were collected from the Millennials and Generation Z cohorts using purposive sampling. The conceptual framework was assessed using Partial Least Squares-Structural Equation Modelling (PLS-SEM) and Partial Least Squares-Multi Group Analysis (PLS-MGA).

The research revealed that customer perceptions of AR features such as augmentation, interactivity and vividness significantly influenced customer engagement, leading to favourable attitudes towards both the AR mobile app and the Virtual product as well as behavioural intentions. Furthermore, the study substantiates the role of customer engagement as a mediator in the relationship between customer perceptions of AR attributes and both attitudinal and behavioural outcomes.

To the best of the authors’ knowledge, this is the first attempt to investigate the significance of perceived augmentation as an antecedent to customer engagement and the mediating role of customer engagement on the influence of perceptions of AR attributes on attitudinal and behavioural intention.

In an era where complex technological advances increasingly govern service delivery, it is incumbent on service firms to pioneer innovative strategies to sustain customer engagement and cultivate loyalty. This conceptual paper examines the transformative potential of artificial intelligence (AI) in the realm of online customer communities, with a particular focus on its creation, management and enhancement facets. The authors explore how AI can revolutionize the dynamics of customer interaction, feedback mechanisms and overall engagement within the service industry.

This conceptual paper draws from marketing and management literature focusing on customer communities and AI in service and customer engagement contexts with a robust future research agenda.

A classification of online customer community engagement is provided along with a conceptual framework to guide our understanding of the integration of AI into online customer communities.

This exploration underscores the imperative for service firms to embrace AI-driven approaches to online customer community management, not only as a means to optimize their operations but as a vital strategy to stay competitive in the ever-evolving digital landscape. This paper examines the novel combination of AI with online customer communities and provides the framework in the form of an input-process-output (IPO) model for future research into this integration.

This teaching case aims to analyze the business model of Amaro, a company that directly sells lifestyle goods to end consumers (B2C), focused on the women's market. Amaro's original business model is introduced and a challenging dilemma is proposed: could Amaro innovate its business model, moving from a digitally native vertical brand (DNVB)-type company to a platform, specifically a vertical marketplace focused on the female audience? Would Amaro be prepared for this evolution or would it be more appropriate to focus on or strengthen the DNVB model?

This teaching case was developed based on in-depth interviews with Amaro's leadership. The teaching notes were proposed based on business model innovation, competitive positioning and market trends concepts. The teaching case considers a new type of business model called DNVB. Students can review the concepts, create analyses and recommend which strategic options can leverage the company for a new growing cycle.

Using the case study in the classroom should promote the discussion and reflections on business model innovation and the future of retail in omnichannel contexts - Amaro offers products online (on an e-commerce platform and native mobile applications) and physically in locations called guide shops. The authors suggested the adoption of frameworks and tools (e.g. the competitive positioning map to allow students to visualize ways to compare strategies and make decisions).

The case introduces a fictional dilemma related to the decision to maximize offline or online investments or completely change the company's business model by adding a new vertical marketplace approach.

This teaching case contributes to the student's learning about business model innovation and evolution. Case discussions could explore contemporary concepts such as value proposition, disintermediation and omnichannel commerce.

Offering goods directly to the consumers by using modern technological architecture through vertical integration within the supply chain makes the DNVB business model an original topic in the start-up segment.

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.

Despite the potential of virtual fitting rooms (VFRs) to enhance the consumer experience, their adoption is in the preliminary stages. Little is known about inherent reasons why consumers would adopt VFRs. As consumers' attributional processes can be influenced by their enduring chronic traits, this study aims to investigate the influence of chronic regulatory focus on consumers' VFR adoptions via consumers' perceptions of value provided by VFRs. Additionally, the mediating effects of perceived functional and experiential values were examined. Further, the moderating effect of prior VFR experience was tested to allow for variations in consumer experiences.

Data were collected via an online survey of 480 consumers who have at least heard of VFRs via convenience sampling. Established measures were utilized to develop the survey questionnaire. Data were analysed using structural equation modelling to test the main model with mediation effects as well as multi-group comparisons to test the moderating effect.

Empirical results revealed that respective chronic regulatory foci, as preconceived factors that drive consumers' differences in processing, exerted significant influences on consumers' perceptions of VFRs, which, in turn, positively influenced their adoption intention. Also, perceived values mediated the relationship between regulatory foci and consumers' adoption intention. Further, prior VFR experience moderated the relationship between regulatory focus and perceived value.

The paper empirically tested the importance of chronic regulatory foci in understanding consumers' cognitive and affective attributional processes, explaining inherent psychological reasons why consumers would (not) adopt VFRs.

This study investigates the key factors that influence customer satisfaction when interacting with augmented reality shopping assistance applications (ARSAPs). ARSAPs grant consumers the capability to experience products in a virtually simulated user environment before product acquisition. With the development of mobile e-commerce due to breakthroughs in smartphone and augmented reality (AR) technologies, there is an increasing potential for these emergent AR mobile services, yet there is a need for further improvement.

This study initially explored the key satisfaction factors for ARSAPs by utilizing topic modeling of a collection of actual user reviews. These factors are subsequently revisited and complemented by existing literature, and finally verified through logistic regression analysis supported by sentiment analysis.

This study identified the key factors that influence customer satisfaction with ARSAPs, including visuality, sense of reality, credibility, format, completeness, understandability, relevance, flexibility, response time, reliability, availability, ease of use and privacy. In particular, two additional factors (i.e. visuality and sense of reality) were newly identified as important in the context of AR, despite their previous omissions in existing literature.

This study is the first to investigate the key factors that influence customer satisfaction with ARSAPs from users' perspectives, utilizing topic modeling of a large amount of real-world data on actual user feedback. By identifying new factors (i.e. visuality and sense of reality) that were not identified in previous literature, this study provides important academic implications for a broader understanding of AR and related technologies that are essential elements of the metaverse. This study also provides valuable insights for developers and companies in the e-commerce industry on how to optimize AR applications and develop more targeted and effective marketing strategies in this field.