Spatio-temporal clustering analysis and technological forecasting of nanotechnology using patent data

Abstract

ABSTRACT This paper proposes to scrutinise the evolution of technological diversification of organisations whose activities are mainly nanotechnologies. We resort to the InnoVue search platform to gather patent information related to the world's largest intellectual property organisations. We apply a five-step analysis on a panel dataset of 16042 distinct patents published between 1985 and 2020 and recorded on June 29, 2021. Text mining has been employed to explore key topics with high-level technological activeness, while a trend analysis has been applied to study diversification characteristics and evolution patterns. Moreover, we initiate spatial autocorrelation modelling to detect spatiotemporal patterns of technical innovation in nanotechnology. Results show that nanobiotechnology and nanophotonics have become new technical hotspots over the last decade. Furthermore, spatial analysis returns a significant clustered pattern among nanotechnology patent distributions and shows that nanotechnology activities were mainly concentrated in Asian countries during the period under study. Our research has policy implications and may interest decision-makers and academics looking to explore nanotechnology's evolution.