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 20 years 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 20 years. 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.

[1]  So Young Sohn,et al.  Identifying patterns in rare earth element patents based on text and data mining , 2014, Scientometrics.

[2]  So Young Sohn,et al.  Patent-based QFD framework development for identification of emerging technologies and related business models: A case of robot technology in Korea , 2015 .

[3]  S. Breschi,et al.  Knowledge networks from patent data: Methodological issues and research targets , 2004 .

[4]  A. Jaffe,et al.  Evidence from Patents and Patent Citations on the Impact of Nasa and Other Federal Labs on Commercial Innovation , 1997 .

[5]  Ozcan Saritas,et al.  Future of sustainable military operations under emerging energy and security considerations , 2016 .

[6]  Frederic M. Scherer,et al.  Inter-Industry Technology Flows and Productivity Growth , 1982 .

[7]  Kwanghui Lim.  The Many Faces of Absorptive Capacity: Spillovers of Copper Interconnect Technology for Semiconductor Chips , 2006 .

[8]  So Young Sohn,et al.  Analyzing technological convergence trends in a business ecosystem , 2015, Ind. Manag. Data Syst..

[9]  Manuel Trajtenberg,et al.  Patents, Citations, and Innovations: A Window on the Knowledge Economy , 2002 .

[10]  Woo Jin Lee,et al.  Patent analysis to identify shale gas development in China and the United States , 2014 .

[11]  Yih-Chearng Shiue,et al.  Forecasting Unmanned Vehicle Technologies: Use of Patent Map , 2010, 2010 Second International Conference on Computer Research and Development.

[12]  M. Bayazit,et al.  The Power of Statistical Tests for Trend Detection , 2003 .

[13]  Zvi Griliches,et al.  Issues in Assessing the Contribution of Research and Development to Productivity Growth , 1979 .

[14]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[15]  Bait Verspagen,et al.  Estimating international technology spillovers using technology flow matrices , 1997 .

[16]  Rachel Finn,et al.  Unmanned aircraft systems: Surveillance, ethics and privacy in civil applications , 2012, Comput. Law Secur. Rev..

[17]  So Young Sohn,et al.  Technological convergence in standards for information and communication technologies , 2016 .

[18]  Hsin-Yu Shih,et al.  International diffusion of embodied and disembodied technology: A network analysis approach , 2009 .

[19]  Manuel Trajtenberg,et al.  THE NBER/SLOAN PROJECT ON INDUSTRIAL TECHAIOLOGY AND PRODUCTIVITY: INCORPORATING LEARNING FROM PLANT VISITS AND INTERVIEWS INTO ECONOMIC RESEARCHt Knowledge Spillovers and Patent Citations: Evidence from a Survey of Inventors , 2000 .

[20]  K. Pavitt.  Technologies, Products and Organization in the Innovating Firm: What Adam Smith Tells Us and Joseph Schumpeter Doesn't , 1998 .

[21]  Najib Harabi,et al.  Channels of R&D spillovers: An empirical investigation of Swiss firms , 1995 .

[22]  E. Goldman,et al.  The information revolution in military affairs in Asia , 2004 .

[23]  Tong Heng Lee,et al.  A brief overview on miniature fixed-wing unmanned aerial vehicles , 2010, IEEE ICCA 2010.

[24]  So Young Sohn,et al.  Valuing academic patents and intellectual properties: Different perspectives of willingness to pay and sell , 2013 .

[25]  Majlinda Zhegu,et al.  Aerospace Clusters: Local or Global Knowledge Spillovers? , 2005 .

[26]  M. Nakagawa,et al.  Changes in the technology spillover structure due to economic paradigm shifts: A driver of the economic revival in Japan's material industry beyond the year 2000 , 2009 .

[27]  Xiaoping Hu,et al.  Structure and Location of Innovative Activity in the Italian Economy, 1981–85 , 1994 .

[28]  Jonghwa Kim,et al.  Monitoring the Change of Technological Impacts of Technology Sectors Using Patent Information: the Case of Korea , 2015 .

[29]  Bart Verspagen,et al.  Technology Spillovers between Sectors and over Time. , 1999 .

[30]  Martin G. Everett,et al.  Network analysis of 2-mode data , 1997 .

[31]  Yongtae Park,et al.  Patent analysis for promoting technology transfer in multi-technology industries: the Korean aerospace industry case , 2012 .

[32]  W. Hoeffding,et al.  Rank Correlation Methods , 1949 .

[33]  Yutao Sun,et al.  Measuring international trade-related technology spillover: a composite approach of network analysis and information theory , 2012, Scientometrics.

[34]  Bart Verspagen,et al.  MERIT concordance table: IPC - ISIC (rev.2) , 1994 .

[35]  So Young Sohn,et al.  Patent valuation based on text mining and survival analysis , 2015 .

[36]  Linton C. Freeman,et al.  The gatekeeper, pair-dependency and structural centrality , 1980 .