Analyzing the Structure of International Knowledge Transfer Networks: An Empirical Study Based on Patent Data

Abstract

This empirical study investigates the structure of international knowledge transfer networks using patent data as a proxy for innovation activities. Drawing upon network analysis methodologies and theories of knowledge transfer and innovation diffusion, this research examines the patterns and dynamics of knowledge flows across countries and regions. By analyzing patent citation data from multiple countries and industries, this study aims to uncover the structure of international knowledge transfer networks, including the density, centrality, and clustering of connections between countries. Furthermore, this research explores the factors influencing the formation and evolution of international knowledge transfer networks, such as geographical proximity, technological similarity, and institutional linkages. Through quantitative analysis techniques applied to large-scale patent databases, this study provides insights into the mechanisms driving the globalization of innovation and the diffusion of knowledge across borders. The findings offer practical implications for policymakers, industry practitioners, and researchers interested in fostering international collaboration, technology transfer, and innovation-driven economic development.