2024, Vol.8, No.3

The Journal of Transdisciplinary Studies 2023 KCI Impact Factor : 0.22

pISSN : 2586-5439 / eISSN : 2713-7457
https://journal.kci.go.kr/jts

This study develops a competency diagnostic tool for fostering individualswho think convergently across advanced technology and the humanities. With growing emphasis on interdisciplinary research and education, systematic assessment tools for such integration are increasingly necessary. Focusing on the COSS (Advanced Convergence) and HUSS (Humanitiesand Social Science Convergence) initiatives, this study applies the Delphimethod to gather expert input and validate identified competencies. Through a literature review, preliminary tool development, and expertfeedback collection, customized competency definitions and diagnostictools were created for both COSS and HUSS. COSS emphasizes understanding advanced technologies and generating convergent value, whileHUSS focuses on identifying and addressing future issues from a humanities perspective. This tool evaluates competencies in convergent attitudes,knowledge, learning, and problem-solving, and can be used for self-assessment to support individualized educational planning.

This study investigates the success factors of technology transfer and commercialization by analyzing journal abstracts through a semi-su pervised keyword topic modeling approach. Leveraging predefined topics and keywords based on prior research, it identifies key factors influencing technology transfer and commercialization within South Korea. The results highlight the persistent significance of company features, while CEO characteristics and business skills appear less impactful. Notably, collaboration factors were initially prominent but diminished over time, whereas technology and innovation features and government-led ini tiatives exhibited a distinctive “W”-shaped trend in importance. The findings suggest that, to bolster public technology transfer and commerci alization, the South Korean government should prioritize enhancing busi ness processes and knowledge management within public research institutes. Consistent with Chang (2022), the study calls for more qual itative improvements in patent performance, which could be achieved by fostering an environment supported by innovation-focused policies, strategic frameworks, and enhanced TTO activities. Future research is encouraged to employ validation methods, such as expert interviews, to refine topic interpretations and enhance data quality by broadening data sources.

This study aimed to examine veterinary research trends by applying a semantic network analysis to the main keywords of articles. The analysis was conducted on 283 academic articles published in the Journal of Veterinary Science from 2020 to 2022, and the main words were refined and extracted from the English keywords presented in each article. When term frequency-inverse document frequency and term frequency were combined, the top 10 research keywords were canine, swine, feline, avian, and bovine for livestock species, and virus, cell, disease, fever, and analysis for non-livestock species. The results of an N-gram analysis also revealed that African swine fever and stem cells were the top research topics identified. The results of a centrality analysis showed that disease, analysis, and virus ranked highest in terms of research interest and impact for non-livestock species, whereas swine ranked highest in terms of those for livestock species. The results of a research trend analysis provided further useful information to guide future research and present directions on the topic. The results of this study are expected to provide evidence for identifying research trends in veterinary science and provide useful information for future research.