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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.

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.