Quantifying technology–industry spillover effects based on patent citation network analysis of unmanned aerial vehicle (UAV)

Abstract

Unmanned aerial vehicle (UAV) technologies have been fast developing over the past 20years and are expected to generate extensive spillovers into other industry sectors. However, no previous studies have investigated such spillover effects. In this study, we propose the framework of two-mode network analysis to quantify the spillover effects of UAV technology into various industries using patent citation data of the United States Patent and Trademark Office. A two-mode matrix consists of rows corresponding to UAV technologies and columns corresponding to beneficiary industries, and the value depicts the spillover probability obtained using International Patent Classification codes and the technology/industry concordance table. The out- and in-degree centralities of the spillover network are used to identify strong spillover-generating UAV technologies and strong spillover-receiving industries, respectively. We observed that the weapon industry received extensive spillover effects during the period 2005–2009. Based on Mann–Kendall tests, the spillover effects of UAV-related software technologies exhibited a consistently upward trend during both the last 10 and 20years. The past significant trend of spillovers can help us to forecast future trends. The proposed quantification method can be readily applied to investigate other specific technology–industry spillover patterns.