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This paper seeks to demonstrate the value of using social media to capture fashion trends, including the popularity of specific features of clothing, in order to improve the speed and accuracy of supply chain response in the era of fast fashion.

This study examines the role that text mining can play to improve trend recognition in the fashion industry. Researchers used n-gram analysis to design a social media trend detection tool referred to here as the Twitter Trend Tool (3Ts). This tool was applied to a Twitter dataset to identify trends whose validity was then checked against Google Trends.

The results suggest that Twitter data are trend representative and can be used to identify the apparel features that are most in demand in near real time.

The 3Ts introduced in this research contributes to the field of fashion analytics by offering a novel method for employing big data from social media to identify consumer preferences in fashion elements and analyzes consumer preferences to improve demand planning.

The 3Ts improves forecasting models and helps inform marketing campaigns in the apparel retail industry, especially in fast fashion.

Organisations are investing in systems such as product lifecycle management (PLM) to support product development, collaboration across complex supply chains and to provide a framework for digital transformation. Graduates of apparel programmes would benefit from a knowledge of PLM to help realise the opportunities that PLM offers. The purpose of this paper is to report on an educational research project that used PLM as a context for practice-based learning and as a mechanism to update the learning experience and stimulate the development of future practice.

This paper reports on the experiences, critical reflections and data from an action research study to establish a learning community through an educational partnership for PLM software within an undergraduate fashion business course. The cohort of the first year of the intervention (n = 28) is the main study population.

The findings indicate that PLM provided a stimulating learning context supportive of a detailed understanding of current industry practice, critical and innovative thinking and the development of a professional identity.

The opportunity for the development of both industry and educational practice is outlined.

A general introduction to PLM provides important information to support and advance Fashion Industry 4.0. Educational partnerships can reduce barriers to the integration of advanced technologies into the higher education curriculum.

Applications of PLM are under researched in textiles and apparel. The paper contributes to the broadening of the knowledge base of PLM and its potential to achieve strategic transformation of the sector.

It becomes a strategic option for enterprises to upgrade and improve supply chain efficiency (SCE) by promoting the digital transformation (DT). This study formulated a parallel mediation model to analyze the relationships among DT, supply chain transparency (SCT), supply chain agility (SCA) and SCE to reveal how DT affects SCE through the mediation of SCT and SCA.

Three paradigms, i.e. resource-based view (RBV), dynamic capability view (DCV) and structure-conduct-performance (SCP) were employed to address the parallel mediation effects. A total of 392 questionnaires (samples) from the port-hinterland supply chain in the DT pilot project of New Land-Sea Corridor in western China were collected, which was then applied to formulate a structural equation model (SEM) to verify the proposed hypotheses.

The results confirmed the existences of parallel mediating effects of SCT and SCA between DT and SCE. On one hand, the direct effect of DT on SCE is not significant when SCT and SCE plays jointly impacts on DT and SCE. On the other hand, SCT and SCA play a positive parallel full mediating effect of DT on SCE.

This study contributed to the literature on changing activities of SCE in DT processes. Specifically, it highlighted how DT leads to SCE via SCT and SCA activities. In addition, this study specified the conditions that the insignificant direct effect of DT has reflects on SCE, it is the time when SCT and SCE are jointly acting on DT and SCE.

By integrating insights from the RBV, DCV and SCP paradigms, this study clarified the mechanisms of DT on SCE, and provided insight on the role of SCT and SCA in the relationship between DT and SCE. The novelty of this study and the results extend the existing literature and provide implications for future research.

This paper aims to identify and empirically analyze useful and applicable metrics for measuring and managing the sustainability performance of small and medium-sized enterprises (SMEs).

To achieve the objective of the paper, potential metrics were adopted from previous research related to industrial sustainability and an empirical analysis was carried to assess the applicability of the metrics by collecting empirical data from Italian footwear SMEs using a structured questionnaire. The SMEs were selected using a convenience sampling method.

The results of the within-case analysis and the cross-case analysis indicate that the majority of the metrics were found to be useful and applicable to each of the SMEs and across the SMEs, respectively. These metrics emphasized measuring industrial sustainability performance related to financial benefits, costs and market competitiveness for the economic sustainability dimension; resources for the environmental sustainability dimension; and customers, employees and the community for the social sustainability dimension.

Apart from the within-case analysis and cross-case analysis, it was not possible to conduct statistical analysis since a small number of SMEs were accessible to collect empirical data.

The findings of the paper have considerable academic, managerial and policy implications and will provide a theoretical basis for future research on measuring and managing industrial sustainability performance. By providing a set of empirically supported metrics based on the triple bottom line approach (i.e. economic, environmental and social metrics), this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement.

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.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

Purpose: This study examines the effect of uncertainties on the hospitality industry from different perspectives across the globe. The hospitality industry faces several contemporary issues and challenges that have the potential to impact its growth and development. This study aims to analyse the current problems and uncertainties in the hospitality sector.

Need for the Study: The hospitality industry plays a significant role in the global economy with various services, including accommodation, food and beverage, events, and tourism. However, the sector faces several contemporary issues and challenges that have the potential to impact its growth and development. This study provides an overview of the most significant problems and challenges facing the hospitality industry today.

Methodology: A systematic literature review was conducted to identify and synthesise relevant studies on the effect of uncertainties issues on the hospitality industry. A systematic search of the Web of Science and Scopus databases was conducted to determine relevant studies published between 2010 and 2021. Studies were screened and selected based on pre-defined inclusion and exclusion criteria. A thematic analysis was performed to categorise the uncertainties and issues in the hospitality industry.

Findings: The study identified several uncertainties and issues facing the hospitality industry, including the pandemic uncertainties, financial crisis, whether positive and negative impacts, terrorism attacks on hotels and tourist places, uncertainties in government policies, situational risks like uncertainties, ambiguity, cultural differences, changes in tourist preferences and changing habits of the tourist.

The case is written on the basis of published sources only.

Doodlage, a start-up incorporated in 2012 by Kriti Tula, Paras Arora and Vaibhav Kapoor, used discarded waste to create sustainable fashion products. It had a first-mover advantage in recycled fashion goods in the first 10 years of its existence. The company contributed to sustainable fashion by providing an alternative to fast fashion production, creating enormous clothing waste and environmental degradation. In the first quarter of 2022, it saved and reused 15,000 m of fabric waste. From 2018 to 2021, the company grew 150% annually, targeting the right customers and regions to expand its business. It ensured that postproduction industrial waste and postconsumption garments were used to produce clothes. It also confirmed that the waste generated in its fabric screening process was used to create stationery items and other valuable accessories.

However, the sustainable fashion model that gave the company a competitive advantage became obsolete in 2022 due to increasing competition in the industry as various players using unique ideas entered the market. The company is encountering operational and logistical challenges that are affecting its performance. The demand for its products was also subdued due to high prices of upcycled and recycled clothes and less consumer spending post-COVID pandemic. The competitors of Doodlage offered multiple products produced using environmentally friendly farming and manufacturing techniques, attracting sustainable purchasers. What should be the new portfolio of products for the company to explore future growth opportunities? Considering their vast price, can consumers be encouraged to buy upcycled clothes? How should the company ride the winds of change in the industry?

The instructor should initiate the class discussion by asking questions such as how frequently do you shop for clothes? Do you care about the fabric of your apparel? After you discard your clothes, do you think about where these goods finally end up? Data on the amount of total waste generated in the fashion industry should be communicated to students to connect it with the importance of the concept of circular economy. Post this, the instructor should introduce the business model of Doodlage to bring the discussion into the context of the fashion industry before going ahead to discuss the company’s dilemma.

The objective of this paper is to further the understanding of netnography as a research method for supply chain academics. Netnography is a method for gathering and gaining insight from industry-specific online communities. We prescribe that viewing netnography through the lens of the supply chain will permit researchers to explore, discover, understand, describe or report concepts or phenomena that have previously been studied via survey research or quantitative modeling.

To introduce netnography to supply chain research, we propose a framework to guide how netnography can be adopted and used. Definitions and directions are provided, highlighting some of the practices within netnographic research.

Netnography provides the researcher with another avenue to pursue answers to research questions, either alone or in conjunction with the dominant methods of survey research and quantitative modeling. It provides another tool in the researchers’ toolbox to engage practitioners in the field.

The development of netnography as a research method is associated with Robert Kozinets. He developed the method to study online communities in consumer behavior. We justify why this method can be applied to supply chain research, how to collect data and provide research examples of its use. This technique has room to grow as a supply chain research method.

Motivated by the real-world practice that the boom of the online selling induces a higher product return as well, selecting which online channel mode indicates who takes ownership over the product and thus bears the loss of the product return. This paper aims to seek the optimal online channel modes for the two members in a platform supply chain in the presence of product returns.

This study aims to develop a platform supply chain that consists of one platform company and one supplier. Along with an offline distribution channel, the supplier can choose two alternative online selling modes (i.e. the reselling and agency modes) to sell its product through the online marketplace. This paper applies Stackelberg game to derive the equilibrium with different business scenarios and selects the optimal online channel modes for two parties, respectively. Moreover, this paper extends to a different supply chain with a reverse channel leadership and a different product return policy for testing the robustness.

Several interesting and important results are derived in this paper. Firstly, it is found that the relative pricing are largely relied on the costs of two channels. Secondly, the platform supply chain may benefit from a pure channel rather than the dual-channel when this channel enjoys a relatively low cost and/or a sufficiently high consumer preference. Then, the platform and the supplier act contradictorily when selecting their optimal online channel modes. To be specific, the platform motivates to choose the online reselling mode when both the commission rate and the slotting fee are relatively low, whereas the supplier is likely to select the online agency mode under this circumstance. Finally, a win-win situation in regards to the optimal online channel mode for two parties is achievable with numerical experiments.

Based on the analytical studies, the results derived in the authors’ work can provide managerial insights to assist the supplier and the platform company in determining the operational decision and selecting the optimal online channel mode to deal with consumer returns. In addition, appropriate commission rate along with slotting fee will make both parties achieve a win-win situation in determining their optimal online channel mode.

To the authors’ best knowledge, this paper makes the first move to determine the optimal online channel mode in the content of consumer returns and study how it is affected by different product return policies.