This study assessed the effectiveness of brand image communication on consumer perceptions of cruelty-free fashion brands. Brand messaging data were gathered from postings on the official Instagram accounts of three cruelty-free fashion brands and consumer perception data were gathered from Tweets containing keywords related to each brand. Web crawling and natural language processing were performed using Python and sentiment analysis was conducted using the BERT model. By analyzing Instagram content from Stella McCartney, Patagonia, and Freitag from their inception until 2021, this study found these brands all emphasize environmental aspects but with differing focuses: Stella McCartney on ecological conservation, Patagonia on an active outdoor image, and Freitag on upcycled products. Keyword analysis further indicated consumers perceive these brands in line with their brand messaging: Stella McCartney as high-end and eco-friendly, Patagonia as active and environmentally conscious, and Freitag as centered on recycling. Results based on the assessment of the alignment between brand-driven images and consumer-perceived images and the sentiment evaluation of the brand confirmed the outcomes of brand communication performance. The study revealed a correlation between brand image and positive consumer evaluations, indicating that higher alignment of ethical values leads to more positive consumer assessments. Given that consumers tend to prioritize search keywords over brand concepts, it’s important for brands to focus on using visual imagery and promotions to effectively convey brand communication information. These findings highlight the importance of brand communication by emphasizing the connection between ethical brand images and consumer perceptions.

With the digitalization of production and consumption environments, consumers are no longer merely targets of marketing, but key players in creating value jointly with companies by participating in various decision-making processes. Much virtual content in particular, such as fashion shows, exhibitions, games, social activities, and shopping, which fashion brands implement in virtual worlds, cannot be completed without consumers’ active engagement and interaction. Thus, this study considers consumers’ participation in virtual content provided by fashion brands as value co-creation in virtual worlds. This study aims to examine how consumer (i.e., consumer smartness) and fashion firm (i.e., perceived intellectual capital) factors influence value co-creation behavior intention in virtual worlds. Data were collected from 410 consumers in their 20s nationwide through an online survey, and a higher-order structural equation modeling analysis was conducted to test the research model. The results showed that both consumer smartness and perceived intellectual capital positively influenced customer participation behavior and citizenship behavior intentions. Specifically, perceived intellectual capital had a greater impact on value co-creation behavior in the virtual world than consumer smartness. The findings provide empirical evidence that the fashion firms’ intangible assets and consumers’ competence in the digital shopping environment encourage their intentions to co-create value in virtual worlds.

In response to the global trend of making sustainable development an urgent task, luxury fashion brands actively embrace it in their corporate philosophies and management policies. However, despite the widespread consensus in the related industry and the strong will of companies for the sustainable development of luxury brands, there are still few cases of luxury fashion brands successfully implementing sustainable development. This study examined the impact of the types of message framing on the sustainability marketing of luxury fashion brands, focusing on their effects on perceived message effectiveness, sustainable brand image, and brand attitudes. An online survey was administered to 464 Korean consumers in their 20s to 40s to test the hypotheses. The results showed that perceived effectiveness was higher for negatively framed messages (loss) than for their positive counterparts (gain). The types of message framing did not significantly affect sustainable brand messages, and no significant difference in perceived brand image was found, regardless of message type. Perceived message effectiveness exerted a significant positive effect on sustainable brand image, and such an image had a significant positive effect on brand attitudes. The results provide implications for related research and practical implications for the development of competitive sustainability marketing strategies for luxury fashion—an industry still in its infancy.

This study analyzes consumer fashion purchase patterns from a big data perspective. Transaction data from 1 million transactions at two Korean fashion brands were collected. To analyze the data, R, Python, the SPADE algorithm, and network analysis were used. Various consumer purchase patterns, including overall purchase patterns, seasonal purchase patterns, and age-specific purchase patterns, were analyzed. Overall pattern analysis found that a continuous purchase pattern was formed around the brands’ popular items such as t-shirts and blouses. Network analysis also showed that t-shirts and blouses were highly centralized items. This suggests that there are items that make consumers loyal to a brand rather than the cachet of the brand name itself. These results help us better understand the process of brand equity construction. Additionally, buying patterns varied by season, and more items were purchased in a single shopping trip during the spring season compared to other seasons. Consumer age also affected purchase patterns; findings showed an increase in purchasing the same item repeatedly as age increased. This likely reflects the difference in purchasing power according to age, and it suggests that the decision-making process for purchasing products simplifies as age increases. These findings offer insight for fashion companies’ establishment of item-specific marketing strategies.

The online shopping market is expanding, with online shopping malls now subdivided into personal computer(PC) and mobile versions. Meanwhile, various efforts to promote online sales are being carried out in a bid to improve performance, and detailed research is required to inform such strategies. The purpose of this study was to classify online shopping mall types into PC fashion malls and mobile fashion malls with the aim of assessing sales promotion satisfaction and investigating the relationship between sales promotion satisfaction and consumers’ behavioral intentions. Data were collected by a survey firm in June 2023, and 248 copies of the data were used for analysis. SPSS 28.0 was used to process the data, and frequency analysis, factor analysis, reliability analysis, and regression analysis were performed. The satisfaction factors for various sales promotions used by PC and mobile fashion shopping malls were empirically subdivided in consideration of consumer perspectives, and potentially effective marketing strategies were presented. Differences were observed in the type of satisfaction with sales promotion between PC fashion shopping malls and mobile fashion shopping malls and in the effect of sales promotion satisfaction on behavioral intention. Based on the study’s findings, effective sales promotion strategies that can increase satisfaction and enhance behavioral intention may be developed and implemented through the use of various and different sales promotion strategies in PC and mobile fashion shopping malls.

This study focused on how retail tech promotes differentiated customer experiences in offline fashion stores. The purpose of this study is to determine the effects of the characteristics of fashion retail tech stores on consumers’ flow and satisfaction. We surveyed Koreans aged 10 to 50 who had experienced offline fashion retail tech stores. The survey was conducted from April 28, 2023, to May 21, 2023. The total number of survey respondents was 200. The quantitative data collected through questionnaires was analyzed using SPSS 25.0. To reveal the effects of fashion retail tech store characteristics on consumer’s flow and satisfaction, frequency analysis, we conducted frequency analysis, factor analysis, reliability analysis, correlation analysis, and regression analysis. The results of this study, figured out that fashion retail tech store’s characteristics, including playfulness, efficiency, interaction, and information provision, have a significant impact on behavior flow, emotional flow, and satisfaction. As a result of analyzing the influence of consumers’ flow led to satisfaction, it was confirmed that emotional flow positively influenced satisfaction, but behavioral flow had no meaningful effect on satisfaction. The results of our study can be used to make a successful marketing strategy and can serve as foundational data for consumer research on retail-tech-applied offline fashion stores.