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.