As the COVID-19 pandemic confirmed the culture of non-face-to-face consumption. In retail commerce, the 'live commerce' market, where sales are made by communicating with customers in the form of live streaming broadcasts, has grown rapidly. Although previous studies have consistently confirmed the phenomenon of "influencers" in society and culture, there is a lack of research on the "sales expertise" of live commerce broadcasters such as Wang Hong in China. In China, "Wang Hong" is short for "Wang Luo Hong Ren", a combination of "Wang Luo", which means the Internet, and "Hong Ren", which means star, and refers to a person who is popular through social platforms and is gaining popularity from many fans. Therefore, this study focuses on Wang Hong's developing "selling expertise" and examines it from the perspective of a shopping curator. In particular, we applied Harold Jarche(2011)'s "Seek-Sense-Share" model to influencers to verify their influence on trust and purchase intention in live commerce. Furthermore, we analyzed the differences between Korea and China.A survey was conducted among live commerce users in Korea and China, and a total of 228 questionnaires were used in the final analysis. Basic statistical analysis was conducted using SPSS and hypotheses were tested using PLS 3.0. The results of the hypothesis testing showed that influencers' curatorial competence "Seek-Sense-Share" had a significant effect on trust, and trust had a positive effect on purchase intention. In addition, there is a significant difference between Korean and Chinese consumers in this relationship.

This study explores the tendency of corporations and organizations to continue with their current processes despite having incentives for better Information Technology (IT) innovation or transition. In this context, the study argues that organizations may struggle with 'outsourcing inertia,' a well-known concept referring to an organization's deficient adaptability to environmental changes, particularly defined here as the organization's slow adaptation to changes in outsourcing levels. To verify this, the study analyzes how key variables identified from existing IT Outsourcing (ITO) decision-making research and recent studies on cloud computing transitions actually affect a firm's transition intentions. In the process, this study investigates the moderating effect of a firm's outsourcing inertia, utilizing the Technology-Organization-Environment (TOE) framework and the Push-Pull-Mooring (PPM) model based on migration theory to propose a research model. The study aims to contribute to finding strategic approaches necessary for facilitating IT innovation and transition by understanding the impact of outsourcing inertia on the decision-making process related to IT outsourcing. It is important to note that the majority of domestic conglomerates own IT subsidiaries, which significantly influence the process of transitioning to cloud computing. Nevertheless, research on the impact of IT subsidiaries on cloud computing transition is relatively scarce. Based on this background, this study proposes that IT subsidiaries within domestic conglomerates can act as a significant mooring factor of organizational inertia in the decision-making process for adopting cloud computing. Through this, the study seeks to provide strategic insights for overcoming organizational inertia faced by IT subsidiaries during the cloud computing transition process.

This study explores the barriers to using health and medical data in research and development (R&D) within the healthcare industry and suggests ways to enhance data utilization. As artificial intelligence technology drives transformative changes across industries, there is an increased demand for robust health and medical data, highlighting its critical economic value and utility in fostering innovation. Using qualitative analysis through Grounded Theory, the study involves ten R&D professionals from healthcare industry, including both medical centers and corporations, using surveys and in-depth interviews to gather diverse experiences and perspectives on the challenges and opportunities in health and medical data use. Key findings point to legislative, regulatory, and data quality and integration issues, as well as complexities in patient data access and usage. Technological limitations and inadequate data governance frameworks also emerge as significant obstacles. Recommendations focus on improving regulatory frameworks, enhancing data standardization and quality, and fostering stronger partnerships between data custodians and users. The study concludes that overcoming these obstacles requires a comprehensive strategy involving legislative changes, improved technological infrastructure, and increased stakeholder collaboration. Implementing these recommendations could greatly enhance health and medical data utilization in R&D, significantly advancing medical science and patient care services.

To grasp the structure of an industry and monitor its changes, it is essential to utilize relevant statistics. Various statistics are being compiled regarding the software (SW) industry, presenting diverse numerical values. However, without a precise understanding of the scope and measurement methods inherent to each statistic, gaining a rigorous understanding of the industry's structure and evolving trends becomes challenging. Moreover, significant discrepancies between similar statistics often lead to confusion among users. In the software (SW) industry, key statistics commonly used include SW production value and SW market size. As of 2022, the annual domestic SW production value is reported as 77.4 trillion KRW (based on ICT Survey), while the SW market size for the same year is stated as 38.5 trillion KRW (according to IDC data). Although production value and market size may seem conceptually similar, there is approximately a twofold difference between the figures provided. Without understanding the meanings of each statistic and the differences between them, there are limitations in utilizing these statistics effectively. While statistics are utilized for various purposes such as policy development or causal analysis of policy using statistical raw data, research that presents and analyzes the precise meanings and limitations of each SW-related statistic is virtually non-existent. Thus, this study aims to compare and analyze the methodologies and differences among key statistics used to represent the SW industry: SW production value, SW market size, and SW GDP statistics. Through this analysis, the goal is to contribute to a better understanding of the SW industry's structure and enable more accurate and rigorous utilization of relevant statistics.

This study aims to enhance the continuous utilization of community mapping by structurally understanding the intentions behind its ongoing use and the impacts related to it, grounded in prior research. By analyzing existing community mapping cases through literature studies on community mapping, this research identifies the characteristics of community mapping that motivate its sustained use. Moreover, based on the Uses and Gratifications Theory and the Participatory Communication Model (PCM), this study proposes a research model to investigate the factors influencing the intention to continue using community mapping. Unlike previous studies, which primarily focused on developing and applying community mapping processes for case studies, this research not only develops and applies a community mapping process but also aims to apply the findings related to the intention of continued use in future community mapping activity processes for sustained engagement.

Based on the analysis of 174 Young Startups Project Papers from university students majoring in entrepreneurship, this study aimed to identify the thoughts and characteristics of prospective entrepreneurs and derive their main agendas. Detailed information was collected on their preparation and ambitions for entrepreneurship, market research in their fields of interest, analysis of potential target users, requirements, and team management. We refined, categorized, and interpreted 84,818 words across 396 digital pages on LMS, and visualized using word clouds program. Additionally, interviews about peer learning were conducted by Zoom. The analysis revealed unique differences in students' perspectives on entrepreneurship based on their major, academic year, and gender. Also we could find that they actively utilize AI tech with a strong spirit of challenge in the startups. Interestingly, they emphasized horizontal communication and collaboration capabilities to improve productivity. This suggests the need to consider diversity in the design of entrepreneurship incubating content and programs for generation Z technically and academically.

Due to the advancement of virtual reality technology, virtual idols are widely used in industrial and cultural content industries. However, it is difficult to utilize virtual idols' social perceptions because they are not properly understood. Therefore, this paper collected and analyzed YouTube comments to identify differences about social perception through comparative analysis between virtual idols and general idols. The dataset was constructed by crawling comments from music videos with more than 10 million views of virtual idols and more than 10,000 comments. Keyword frequency and TF-IDF values were derived from the collected dataset, and the connection centrality CONCOR cluster was analyzed with a semantic network using the UCINET program. As a result of the analysis, it was found that virtual idols frequently used keywords such as "person," "quality," "character," "reality," "animation," while reactions and perceptions were derived from general idols. Based on the results of this analysis, it was found that while general idols are mainly evaluated with their appearance and cultural factors, social perceptions of virtual idols' values are mixed with evaluations of cultural factors such as "song," "voice," and "choreography," focusing on technical factors such as "people," "quality," "character," and "animation." However, keywords such as "song," "voice," "choreography," and "music" are included in the top 30 like regular idols and appear in the same cluster, suggesting that virtual idols are gradually shifting away from minority tastes to mainstream culture. This study aims to provide academic and practical implications for the future expansion of the industry and cultural content industry of virtual idols by grasping the social perception of virtual idols.