A Study on the Development of a Classification System for Industry-Academia-Research Cooperation Information
Keywords:
Classification System, Industry-Academia-Research Cooperation Information, logical organization and accessi bility of data, logical organization, and accessi bility of dataAbstract
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.
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Copyright (c) 2025 Younghee Noh, Ho-won Kim, Jeong-won Roh

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