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This study examines the effectiveness of the marketing mix practiced on Twitter across high-end and low-end fashion brands and explores whether any four Ps activities have changed across the different pandemic stages. A quantitative research method was designed to analyze text data scraped from identified fashion brands' Twitter accounts. A classification instrument was developed to group tweets based on the four Ps marketing mix. Then the developed instrument was applied to a small set of 145 tweets randomly sampled from the collected data. Logistic regression models were then trained using the sample set to predict four Ps activities on all the collected 144k tweets. The numbers of likes per tweet and frequencies of being retweeted per tweet were used to measure engagement effectiveness across brands.

PurposeTwo-dimensional (2D) measurement technology has become more popular than before, thanks to the widespread availability of smartphones and smart devices. However, most existing 2D body measurement systems have background constraints and may raise privacy concerns. The purpose of this research was to test the idea of designing a 2D measurement system that works with a color-coded measurement garment for background removal and privacy protection. Clothing consumers can use the proposed system for daily apparel shopping purposes.Design/methodology/approachA 2D body measurement system was designed and tested. The system adopted a close-fitted color-coded measurement garment and used neural network models to detect the color-code in the garment area and remove backgrounds. In total, 78 participants were recruited, and the collected data were split into training and testing sets. The training dataset was used to train the neural network and statistical prediction models for the 2D system. The testing dataset was used to compare the performance of the 2D system with a commercial three-dimensional (3D) body scanner.FindingsThe results showed that the color-coded measurement garment worked well with the neural network models to process the images for measurement extraction. The 2D measurement system worked better at close-fitted areas than loose-fitted areas.Originality/valueThis research combined a color-coded measurement garment with neural network models to solve the privacy and background challenges of the 2D body measurement system. Other researchers have never studied this approach.

PurposeA two-dimensional (2D) body measurement system was implemented to study the application of sportswear design in measurement garment development. A total of 50 participants were recruited. The basic demographic information and sportswear preference data were collected through a survey to understand consumer preferences and acceptance of the new designs. The body measurements were collected through both the selected 2D measurement system and a commercial three-dimensional scanning booth to evaluate measurement accuracy.Design/methodology/approachFinding the right size has been a long-existing problem for clothing consumers. Size problem is the most common reason for e-commerce returns and adds a high cost for retailers. One possible solution is to offer consumers an easy-to-use method that extracts accurate body measurements to be used for clothing size selection. The purpose of this research is to apply sportswear design elements on measurement garments to see if consumers’ interest in using the 2D measurement system can be increased without influencing the measurement accuracy.FindingsThe results showed that the added design features increased consumers’ interest in using 2D body measuring technology without significantly influencing measurement accuracy.Originality/valueThis research applied sportswear elements to convert a 2D measurement bodysuit to a fashionable clothing product. The solution resolved users’ privacy concerns and increased their acceptance and use of the technology. Other studies have not focused on using aesthetic features to improve the 2D measurement technology.

There are long-standing arguments that challenge the resale business as a circular fashion model. Considering the whole fashion industry and market, luxury resale is still quite small. To scale the industry, it is critical to attract more consumers to embrace fashion resale and circular fashion. However, many of the customers most likely to embrace resale might have already opted into the market, indicating that online or in-store resale businesses are competing for a limited pool of customers. As a result, it is challenging for the industry to scale. Therefore, it is imperative to understand how consumers engage with luxury resale platforms, what value they are looking for, and to what degree resale customers’ desires for fashion clothing and sustainability can be met in a reconciling manner. Such understanding will facilitate luxury resale platforms to grow their customer base and scale up the industry. This exploratory study focuses on understanding online luxury platform customers and their consumption experience to determine what key attributes affect customer value and engagement. The research explores customer experience using a text-mining approach to provide answers to identified research questions: (1) How do online luxury resale platforms provide customer value to buyers and sellers? What are the driving values for consumers to buy or sell pre-owned products? (2) Are there any issues regarding buying and selling pre-owned products using online luxury resale platforms? (3) Does sustainability play a role in individuals’ consumption using online luxury resale platforms? The article discusses the implications of the study, its limitations, and future research directions.

PurposeThis study aims to discover clothing consumption shifts and explore the effect of consumer resilience in changing clothing consumption patterns or establishing new clothing consumption routines after experiencing disruptions caused by the Covid-19 pandemic.Design/methodology/approachA two-phase multi-method approach was employed. The first phase of qualitative inquiry was conducted to identify clothing consumption shifts using a content mining approach on a text data sample of 17,195 tweets posted from 1 January to 30 September 2020. The second phase of the quantitative study was conducted to explore consumer resilience's effect on clothing consumption shifts based on a collected national sample of 418 respondents through an online survey.FindingsThis study identified clothing consumption changes including value shifts, style shifts and spending shifts. It was also found that resilient consumers care about a company's ethical practices and value the quality instead of the number of items in their wardrobe. Consumers spend more time wearing comfortable clothing and are used to the working-from-home lifestyle.Originality/valueThis study explored approaches to making use of social media data for a better understanding of consumers' clothing behaviour. Also, this study attempted to explore and understand clothing consumption practices during and post the Covid-19 global pandemic, focusing on identifying shifts that might last longer for fashion businesses to explore growth opportunities.

The purpose of this research is to investigate consumer values of secondhand fashion (SHF) consumption from online platforms in both the mass market and luxury market. The luxury SHF business is closely related to the business of SHF mass market. A cross-market value analysis would provide better insights to understand consumers’ motivations to purchase secondhand fashion products. Three mass-market SHF companies and three luxury SHF companies were selected as sample companies based on their revenues in the U.S. market. Consumers’ comments and reviews from a third-party business review site, trustpilot.com, were collected using the web-scraping technique. Recurrent Neural Network (RNN) analysis, as part of a machine learning algorithm, was applied to detect the most co-occurring word combinations and underlying values discussed in the reviews. The findings identified major consumer-perceived ‘source of values’, i.e., ‘possession/ownership transfer’, and ‘interaction between consumer to business platform’, which might negatively impact the performance of the business of SHF mass market compared to the luxury SHF business. The ’possession/ownership transfer’ source-related values are the most ignored value in the SHF mass market. By adopting the product-oriented value strategy practiced in the luxury market, SHF mass market might improve the consumer perception of product-related value areas.

Understanding how consumers have shifted in clothing consumption in the midst of the global COVID-19 pandemic is critical for fashion clothing brands and businesses to identify what value means to consumers to locate growth opportunities. This exploratory study intends to provide a picture of consumers’ clothing consumption evolution while going through the pandemic crisis. We take a viewpoint that integrates the perspectives of life status changes and stress coping to examine consumers’ responses to clothing consumption during the COVID-19 global pandemic. A total of 68,511 relevant tweets were collected from January 1, 2020, through September 31, 2020. Sentiment and content analysis identified five themes which are revealed by 16 topics associated with clothing consumption over the phases of pre-lockdown, lockdown, and reopening. Pent-up demand for clothing products and changed clothing consumption habits were identified. Our findings provide evidence that consumption change is the fundamental mechanism of stress coping.

PurposeThis study intends to examine consumers' fashion customization experiences through a web content mining (WCM) approach. By applying the theory of customer value, this study explores the benefits and costs of two levels of mass customization (MC) to identify the values derived from style (i.e. shoe customization) and fit customization experiences (i.e. apparel customization) and further to compare the dominating dimensions of value derived across style and fit customization.Design/methodology/approachA WCM approach was applied. Also, two case studies were conducted with one focusing on style customization and the other focusing on fit customization. The brand Vans was selected to examine style customization in study 1. The brand Sumissura was selected to examine fit customization in study 2. Consumers' comments on customization experiences from these two brands were collected through social networks, respectively. After data cleaning, 394 reviews for Vans and 510 reviews for Sumissura were included in the final data analysis. Co-occurrence plots, feature extraction and grouping were used for the data analysis.FindingsThe emotional value was found to be the major benefit for style customization, while the functional value was indicated as the major benefit for fit customization, followed by ease of use and emotional value. In addition, three major themes of costs, including unsatisfied service, disappointing product performance and financial risk, were revealed by excavating and evaluating consumers' feedback of their actual clothing customization experiences with Sumissura.Originality/valueThis study initiates the effort to use web mining, specifically, the WCM approach to thoroughly investigate the benefits and costs of MC through real consumers' feedback of two different types of fashion products. The analysis of this study also reflects the levels of customization: style and fit. It provides an in-depth text analysis of online MC consumers' feedback through the use of feature extraction analysis and word co-occurrence networks.

A modern way of collecting body measurements is through 3Dbody scanners. However, it is challenging to define the right measurement locations in a 3D environment. Waist girth is a key body measurement and is hard to define on a 3D body model following existing manual body measurement standards. The purpose of this research is to explore some commonly used waist definitions and analyze them to see which one provides the best and most consistent results. Four waist definitions were selected and labeled on sample scans from the Size USA database. The researcher then evaluated each location and marked the level that best represented the real waist level. It was found that the Center-b/w-bust-hips was the most effective way to find the waist level on a 3D model. However, a new 3D waist definition with better performance is demanded.

Innovative pattern drafting methods existing in research papers are not promoted to the general public or getting enough attention from the industry. This project aims to promote traditional and innovative basic block drafting methods existing in academia to other researchers and educators, related industry personnel, and fashion amateur, by designing a web-based automatic basic block application and establishing a web-based communication platform. To test this idea, a web app was developed to automatically generate customized basic block patterns based on input measurements using the Armstrong method. The pilot study showed that the pipeline is processable, and the next step will be scaling the number of available basic block drafting methods in the app.

Body measurements play an import role in pattern generation and size determination. Traditionally, body measurements were captured with tape measures. The tape measure technique is often time-consu...

Literature reviews show that consumers are not satisfied with the fit of garments sold in stores, primarily due to outdated sizing systems used by companies and the limited number of sizes being produced. The purpose of this article is to present a sizing system creation method, which can be applied on body measurement data to improve the overall fit of garments. Data from the SizeUSA study was used. The sizing system creation process included natural log-transformation, principle component analysis, multivariate linear regression, size range determination, and measurements calculation. The created sizing system was then compared with ASTM D5585-11e1. Analysis of the results showed that the method used to create the sizing system was reliable and repeatable. This was an important research effort for apparel manufactures, as it demonstrated a method to create a sizing system that is flexible and can be altered to fit target consumer groups!