Exploring a Technology Information Platform Using the Exterior Model of Recessive Knowledge

Abstract

This study investigates the development of a technology information platform utilizing the exterior model of recessive knowledge. In an era characterized by rapid technological advancements and information proliferation, the effective dissemination and utilization of knowledge are crucial for innovation and competitiveness. The exterior model of recessive knowledge emphasizes the existence of tacit or implicit knowledge embedded within individuals, organizations, and communities, which may not be readily apparent or codified. Drawing on this model, the research aims to design and implement a technology information platform that facilitates the sharing, exchange, and integration of both explicit and recessive knowledge among stakeholders. Through a combination of theoretical exploration, case studies, and prototype development, the study explores how the platform can leverage emerging technologies such as artificial intelligence, machine learning, and natural language processing to extract, analyze, and utilize recessive knowledge for problem-solving, decision-making, and innovation purposes. Furthermore, the research examines the role of user engagement, trust-building mechanisms, and governance structures in fostering a collaborative and participatory ecosystem around the technology information platform. By providing a conceptual framework and practical insights into the development of such platforms, this study contributes to the advancement of knowledge management practices and technology-enabled innovation ecosystems. The findings have implications for organizations, policymakers, and technology developers seeking to harness the potential of recessive knowledge for driving technological advancement and sustainable development.