Assessing Patents based on Their Structural Significance in Patent Citation Network

This study proposes a patent assessment method based on a patent's structural role within a patent citation network. The proposed method includes two major steps: (1) assigning a weight to each citation of the patent citation network according to its traversal count within the network, and (2) obtaining a pivotalness value for each patent by summing the weights of its citations. A patent's pivotalness value is, therefore, the patent's traversal count within the network. If a citation may be deemed as a flow of knowledge or a step of technology evolution from the cited to the citing, the pivotalness value reflects a patent's significance in knowledge dissemination or technology evolution within the field. To observe this measure, this study selects for empirical analysis patents in the field of carbon dioxide capture, storage, recovery, delivery, and regeneration and collects a total of 34,083 US utility patents issued between 1976/1/1 and 2017/3/31 by the United States Patent and Trademark Office database.

[1]  Diana Lucio-Arias,et al.  Main-path analysis and path-dependent transitions in HistCiteTM-based historiograms , 2008, J. Assoc. Inf. Sci. Technol..

[2]  Jenine K Harris,et al.  Mapping the multidisciplinary field of public health services and systems research. , 2011, American journal of preventive medicine.

[3]  Ed C. M. Noyons,et al.  Combining mapping and citation network analysis for a better understanding of the scientific development: The case of the absorptive capacity field , 2008, J. Informetrics.

[4]  Roberto Fontana,et al.  Mapping technological trajectories as patent citation networks. An application to data communication standards , 2009 .

[5]  Francis Narin,et al.  Patent bibliometrics , 2005, Scientometrics.

[6]  John Metcalfe,et al.  Mapping evolutionary trajectories: Applications to the growth and transformation of medical knowledge , 2007 .

[7]  John S. Liu,et al.  Data envelopment analysis 1978-2010: A citation-based literature survey , 2013 .

[8]  Vladimir Batagelj,et al.  Analysis and visualization of large networks with program package Pajek , 2016, Complex Adapt. Syst. Model..

[9]  Christopher L. Magee,et al.  Tracing Technological Development Trajectories: A Genetic Knowledge Persistence-Based Main Path Approach , 2016, PloS one.

[10]  Arianna Martinelli,et al.  An emerging paradigm or just another trajectory? Understanding the nature of technological changes using engineering heuristics in the telecommunications switching industry , 2012 .

[11]  John S. Liu,et al.  An integrated approach for main path analysis: Development of the Hirsch index as an example , 2012, J. Assoc. Inf. Sci. Technol..

[12]  Vladimir Batagelj,et al.  Efficient Algorithms for Citation Network Analysis , 2003, ArXiv.

[13]  Chih-Hung Hsieh,et al.  Development trajectory and research themes of foresight , 2016 .

[14]  B. Verspagen,et al.  Knowledge flows : analyzing the core literature of innovation, entrepreneurship and science and technology studies , 2012 .

[15]  Bart Verspagen,et al.  Mapping Technological Trajectories as Patent citation Networks: a Study on the History of Fuel Cell Research , 2007, Adv. Complex Syst..

[16]  Holger Ernst,et al.  Patent information for strategic technology management , 2003 .

[17]  F. Strozzi,et al.  Supply chain risk management: a new methodology for a systematic literature review , 2012 .

[18]  Norman P. Hummon,et al.  Connectivity in a citation network: The development of DNA theory☆ , 1989 .