This study examines gender differences in language use in online shopping reviews through an analysis of five-star reviews posted on the fashion platform Musinsa. Focusing on reviews of a single unisex sneaker product, a corpus of 977 reviews by male users and 998 reviews by female users were compiled and analyzed. This study used morphological analysis and frequency-based methods to compare high-frequency vocabulary, part-of-speech distributions, abbreviated forms, loanwords, original-language expressions, sentence-ending forms (haeyo-che and hasipsio-che), and symbolic language such as emoticons. The findings show that male users tend to use verbs and nouns directly related to functions and outcomes, whereas female users more frequently employ adjectives and adverbs expressing aesthetics, emotions, and overall impressions. Although the use of hybrid abbreviations and emoticons differed significantly by gender, sentence-ending forms also showed a statistically significant association with gender. These results suggest that gender does not rigidly determine the overall stylistic structure of review discourse but influences language use by shaping evaluative focus, emotional marking, and rhetorical emphasis in positive reviews.

This study examined how perceived scarcity influences consumer purchase decisions in the context of preorder fashion, with a focus on the mediating role of purchase pressure and the moderating role of hedonic shopping value. A survey was conducted with 300 consumers who had previously purchased fashion products through preorder platforms in Korea. The key constructs –limited time/quantity scarcity, product scarcity, time pressure, financial pressure, purchase delay, purchase intention, and compulsive buying– were validated using exploratory and confirmatory factor analysis. Structural equation modeling showed that perceived scarcity significantly increased purchase pressure. Specifically, limited time/quantity scarcity heightened time pressure, while product scarcity heightened both time and financial pressure. In turn, time pressure positively influenced both purchase intention and compulsive buying, whereas financial pressure led to increased purchase delay. Mediation analysis confirmed that time pressure fully mediated the relationship between limited time/quantity scarcity and both purchase intention and compulsive buying, while product scarcity exerted both direct and indirect effects, particularly on compulsive buying. A multigroup analysis further revealed that hedonic shopping value did not moderate the overall structural model but had significant effects on specific paths. Consumers with high hedonic shopping value were more sensitive to product scarcity and experienced greater purchase pressure than those with low hedonic shopping value. These findings offer valuable insights for marketers who employ scarcity tactics in preorder strategies and highlight the importance of psychological mechanisms in shaping consumer behavior. Theoretical implications and future research directions are also discussed.

This study investigates the effects of experiential marketing by categorizing fashion pop-up store experiences according to the strategic experiential modules (SEMs): sensory, emotional, cognitive, behavioral, and relational. It analyzes how these experiential factors influence shopping flow, impulse buying, and word-of-mouth intentions. A survey was conducted with 400 participants, equally distributed by gender and age group (20 and 30-year-old). Valid responses from 320 participants were analyzed using factor analysis, reliability testing, correlation analysis, and regression analysis in SPSS. Findings revealed four key elements of experiential marketing: sensory/emotional, relational, cognitive, and behavioral. Sensory/emotional, relational, and cognitive factors positively affected shopping flow, which enhanced impulse buying and word-of-mouth intentions. However, behavioral factors did not have a significant effect. These results underscore the impact of experiential marketing on pop-up store customer behavior and highlight the understudied area of word-of-mouth marketing. The study specifically targeted consumers most likely to visit pop-up stores, ensuring practical significance by providing data to develop strategies for increasing experiential marketing efficiency. Additionally, the results identify the critical elements of experiential marketing in pop-up stores and examine how they interact with shopping flow and impulse buying. This research contributes valuable insights into optimizing consumer engagement in pop-up retail environments, emphasizing the importance of sensory and relational experiences in driving consumer behavior and addressing gaps in existing marketing literature.

In recent years, with the advancement of virtual reality (VR) technology, research in related fields has gradually increased. As personal head-mounted display devices become more prevalent in the market, this study explores the phenomenon of integrating VR technology with online shopping from the consumer's perspective. The study focuses on consumers' acceptance of VR technology in online shopping and analyzes the types of virtual environments most likely to stimulate consumer purchase intention. Based on the SOR (Stimulus-Organism-Response) and TAM (Technology Acceptance Model) theories, a TAM-SOR integrated model was constructed. Taking into account influencing factors in the current online shopping environment, the model was built and tested using SPSS and AMOS to validate the hypotheses. Structural equation modeling and mediation effect analyses on the collected samples indicate that external stimulus variables in a VR shopping environment—such as flow experience, spatial presence, and entertainment—have a significant positive impact on purchase intention. Additionally, perceived ease of use and perceived usefulness serve as chain mediators, enabling external stimulus variables to further influence consumer purchase intention through these mediating variables.

This study aims to establish an online shopping mall marketing strategy based on big data analysis methods. The customer cluster analysis method was utilized to analyze customer purchase patterns and segment them into customer groups with similar characteristics. Data was collected from orders placed over one year in 2023 at ‘Jeonbuk Saengsaeng Market’, the official online shopping mall for agricultural, fish, and livestock products of Jeonbuk Special Self-Governing Province. K-means clustering was conducted by creating variables such as ‘TotalPrice’ and ‘ElapsedDays’ for analysis. The study identified four customer groups, and their main characteristics. Furthermore, regions corresponding to customer groups were analyzed using pivot tables. This facilitated the proposal of a marketing strategy tailored to each group’s characteristics and the establishment of an efficient online shopping mall marketing strategy. This study is significant as it departs from the traditional reliance on the intuition of the person in charge to operate a shopping mall, instead establishing a shopping mall marketing strategy through objective and scientific big data analysis. The implementation of the marketing strategy outlined in this study is expected to enhance customer satisfaction and boost sales.