Detecting Emerging Complex Technological Fields in Robotics

Abstract

Robots are composed of various sophisticated technologies, such as mechanics, control systems, electronics, software, and technology convergence, which could be some of the key factors driving innovation in robotics. In addition, in the era of the Internet of Things, companies are required to take measures to make alliances with possible partners, or undertake mergers and acquisitions as a means of open innovation. However, it is increasingly difficult to identify emerging technological innovation because of the speed of innovation, the uncertainty of the possible combinations that could lead to innovation, and the complex convergence of technologies. Although bibliometrics has enabled us to identify major technologies and the approximate relationship between different fields of technologies, precise methodologies are required that will be able to detect emerging technological fields in detail, especially in the case of complex technologies like robotics. By applying a citation network analysis to both clustering and detecting technology convergence, this paper proposes a methodology to precisely detect emerging complex technological fields. The patents data containing robotics in their titles and abstracts were retrieved from Derwent Innovation, and 65,796 patent citations, from 1974 to 2018, were extracted through the Academic Landscape System. This study contributes to information on decision-making on collaborations or other open innovation measures for organizations.