This study investigates the preferences and purchase intentions of ZEPETO users regarding fashion brands that have recently joined ZEPETO, a leading metaverse platform in South Korea. The study surveyed 279 users in their 20s to 40s about their usage patterns, preferences, and purchase intentions toward products from brands like MCM, DKNY, Nike, and Puma. The results reveal that users in their 20s exhibited higher preference and purchase intention for Nike products, as well as greater purchase intention for Puma products. On the other hand, users in their 40s displayed a higher preference and purchase intention for MCM and DKNY products and a stronger preference for Puma products compared to other age groups. Users in their 30s showed a lower preference and purchase intention for both MCM and Puma products, a lower purchase intention for DKNY products, but a preference for Nike products compared to other age groups. Furthermore, men showed a higher preference and purchase intention for most brands, including MCM, Nike, and Puma. These results suggest that fashion brands on ZEPETO need to implement effective marketing strategies targeting users in their 20s and 40s, as well as male users. This study lays the groundwork for further research on the ZEPETO metaverse platform and provides foundational data for understanding user behavior, essential for establishing effective promotional strategies.

The study investigated the influence of website features on the purchase intention of online fashion among Generation Z consumers in South Africa. This topic has received increasing attention against the backdrop of the rapidly growing ‘Digital Generation’, or ‘Millennial consumers’, who are one of the most tech-savvy generations. Despite the benefits that online shopping offers to both the business and the consumer, the act of buying clothes online has presented some challenges to customers. This study therefore aims to gather further insight in an attempt to provide fashion businesses with guidance to better succeed in encouraging customers to shop online. This study selected two visual elements (website aesthetics and product presentation) and two functional website features (website navigation, and security and privacy) and social norms, the test the effect they have on perceived ease of use, attitude and intention to purchase clothing online. The proposed conceptual model tested seven hypotheses of which four were supported. By means of an empirical study, 166 online surveys were collected from individuals within the Generation Z cohort and the analysis was done using SPSS27 by running multiple regression analysis to test the relationships between the variables. The results from this study provide global and local fashion brands with valuable insight into the consumption habits of young consumers in an emerging economy, and factors that drive online fashion consumption.

This study analyzed differences in the purchase satisfaction and repurchase intention of customers who buy clothing products from online platforms. The participants were teenage individuals to those in their 50s residing in Busan, Ulsan, and Gyeongsangnam-do. The data were examined via factor analysis, a t-test, Analysis of variance(ANOVA), Duncan’s multiple range test, two-way ANOVA, and linear regression analysis. The factors for satisfaction with clothing products from online platforms were wearing comfort and quality, design, and price and purchase convenience. The findings revealed that purchase satisfaction based on these factors significantly varied among the participants depending on marital status, age, and occupation. Satisfaction with wearing comfort, quality, and design differed by gender. Satisfaction with wearing comfort, quality, and price and purchase convenience varied by type of purchase and type of online platforms. The interaction effects among the variables that affected purchase satisfaction were as follows. The interaction effects among the variables for wearing comfort and quality showed significant interactions between gender and type of purchase and between occupation and type of online platforms. Those for design showed significant interactions between marital status and age, between age and occupation, and so on. The interaction effects for price and purchase convenience showed significant interactions between marital status and gender and between age and occupation. The results on repurchase intention showed significant differences in such intention by marital status, age, and occupation. Repurchase intention was influenced by wearing comfort and quality, price and purchase convenience, design, and age.

이 연구는 다차원적 배경음악 속성(유형，볼륨，리듬，친숙도)이 소비자의 심리적 정서 및 충 동구매에 미치는 영향을 연구함으로써 중국 또는 한국 소비자를 대상으로 하는 화장품 매장에서 매출 향상 측면에서 배경음악의 중요성을 인식시키는 목적을 가지고 연구되었다. 연구방법은 한 국 오프라인 화장품 매장에서 구매 경험이 있는 한국 및 중국 소비자를 대상으로 온라인 설문을 통해 각 150명의 유효 샘플을 사용하며 구조 방정식 모형으로 경로분석 및 다중집단 분석을 통해 변수간의 인과관계 및 집단간의 경로 차이에 대해 분석하였다. 분석한 결과，음악의 유형，볼 륨，리듬 및 친숙도가 모두 소비자의 심리적 정서 및 충동구매에 영향을 주었다. 한국 및 중국 소비자의 차이를 보면, 음악의 유형 및 친숙도는 한국 소비자들의 충동구매에 더 큰 영향을 미쳤 으며 음악의 불륨 및 리듬은 중국 소비자의 충동구매에 더 큰 영향을 주었다. 연구 결과 본 연구는 화장품 가게 매장에서 배경음악을 사용하여 소비자의 충동구매 행위를 자극하는 효과를 향상시켜 매장의 매출을 높이는 데 도움을 주었다고 도출하였다.

This study contemplates the effect of social media advertising attributes on consumers’ purchasing decisions in cosmetic products. It will serve as basic data for SNS’s advertising strategy and marketing that promotes cosmetics sales. This study conducted a survey and went through the analysis process of SPSS v.25.0 statistical program. Frequency analysis, exploratory factor analysis, descriptive statistical analysis, correlation analysis, and regression analysis were conducted to analyze that informativity, reliability, entertainment, interactivity, and disturbance among SNS advertising attributes were used as effective advertising strategies, which had a positive effect on consumers' purchasing decisions. Therefore, in the cosmetics industry, it is necessary to seek strategies to actively utilize marketing in the social media space to promote consumers' purchase needs and to activate purchases.

Until now, research on consumers’ purchasing behavior has primarily focused on psychological aspects or depended on consumer surveys. However, there may be a gap between consumers’ self-reported perceptions and their observable actions. In response, this study aimed to investigate consumer purchasing behavior utilizing a big data approach. To this end, this study investigated the purchasing patterns of fashion items, both online and in retail stores, from a data-driven perspective. We also investigated whether individual consumers switched between online websites and retail establishments for making purchases. Data on 516,474 purchases were obtained from fashion companies. We used association rule analysis and K-means clustering to identify purchase patterns that were influenced by customer loyalty. Furthermore, sequential pattern analysis was applied to investigate the usage patterns of online and offline channels by consumers. The results showed that high-loyalty consumers mainly purchased infrequently bought items in the brand line, as well as high-priced items, and that these purchase patterns were similar both online and in stores. In contrast, the low-loyalty group showed different purchasing behaviors for online versus in-store purchases. In physical environments, the low-loyalty consumers tended to purchase less popular or more expensive items from the brand line, whereas in online environments, their purchases centered around items with relatively high sales volumes. Finally, we found that both high and low loyalty groups exclusively used a single preferred channel, either online or in-store. The findings help companies better understand consumer purchase patterns and build future marketing strategies around items with high brand centrality.