The Metaverse’s virtual world is used in various industries and is expected to continue to grow in the future. In addition, the Metaverse is a new type of society that integrates various new technologies, and NFT products play an essential role. Therefore, NFT product characteristics and industry trends should be assessed to revitalize the NFT market. To this end, this study confirms the influence relationship between social presence and NFT product characteristics in the Metaverse environment and examines the impact of each characteristic on consumer satisfaction and continued engagement intention to NFT product. Statistical analysis such as exploratory factor analysis, reliability analysis, confirmatory factor analysis, correlation analysis, and structural equation modeling (SEM) using IBM SPSS Amos was conducted on data collected through a survey targeting male and female Korean consumers in their age group 10 to 50. Study results indicate that social presence significantly impacted all characteristics of NFT products (authenticity, scarcity, rarity, collectability, and interactivity). Scarcity and authenticity significantly impacted consumer satisfaction, and both authenticity and consumer satisfaction significantly impacted continued engagement intention. Thus, effective product development and marketing strategies can be established only by presenting different emphasized characteristics depending on the type of NFT product and the Metaverse’s social presence.

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.