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

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.

KEYWORDS:

• Nanotechnology foresight
• patent map
• text mining
• relative R&D capability

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Roberto Louis Forestal

Roberto Louis Forestal is a Ph.D. candidate in Information Management within the College of Business at Chung Yuan Christian University. His research interests include Information Technology, operations management and patent analysis.

Hsin Inn Lee

Hsin Inn Lee received his Master degree from Chung Yuan Christian University. He is the Manager of LearningTech Corp., a telecom products supplier in Taiwan. His areas of interest include Information Technology and Business Operation.

Shih-Ming Pi

Shih-Ming Pi received his Ph.D. from National Cheng-Chi University. He is a professor of Production and Operation Management Information System at the Department of Information Management at Chung Yuan Christian University, and he is the Dean of College of Business of Chung Yuan Christian University. His research interests include quality management, IT Strategy, and Supply Chain Management.

Su-Houn Liu

Su-Houn Liu received his Ph.D. from Auburn University. He is a professor of Big Data Theory and Application at the Department of Information Management at Chung Yuan Christian University. His research interests include Information Technology and Communication and Business Software Application.