A Study on the Development of a Classification System for Industry-Academia-Research Cooperation Information
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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 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.
Abstract
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 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.