出版社：Grupo de Pesquisa Metodologias em Ensino e Aprendizagem em Ciências
摘要：Knowledge-intensive significantly contribute to technological development. This paper aims to explore technological routes (TR) on high analytics information (HAI) technologies for sake of technological forecasting through social network analysis (SNA) in a patent database from 2001 to 2020. Applying search path link count (SPLC) algorithm, this study provides five different TR in various business sectors. This study support decision makers to find additional core of technologies for their innovation strategies and help researchers in identifying HAI technologies that may still emerge in different industries support strategic R&D decisions about prioritizing investments, identifying partnerships to innovate, and collaborating in public policies based on promoting new HAI technologies development.
