A Study on the Development of a Classification System for Industry-Academia-Research Cooperation Information - Noh, Younghee; Kim, Ho-won; Roh, Jeong-won (International Journal of Knowledge Content Development & Technology, 2025)
Purpose: This study aims to develop a systematic classification system for efficiently managing and utilizing information related to industry-academia-research cooperation, addressing the gaps in structured data management. Methodology: The study employs literature review, case studies, expert interviews (FGI), and integrated analysis. A hierarchical decimal coding system was designed to ensure logical organization and accessibility of data. Findings: The proposed classification system comprises six major categories—organization, infrastructure, workforce development, entrepreneurship and employment, research and development, and commercialization—enhancing data usability, ㅊ, and policy support. Implication: This study provides a foundational framework for managing industry-academia-research cooperation information, contributing to ecosystem sustainability. Future work should focus on governance policies for data protection, quality control, and institutional accountability.