Li, X (Li, Xin); Chen, H (Chen, Hsinchun); Huang, Z (Huang, Zan); Roco, MC (Roco, Mihail C.) Patent citation network in nanotechnology (1976-2004) JOURNAL OF NANOPARTICLE RESEARCH, 9 (3): 337-352 JUN 2007
Eugene Garfield
garfield at CODEX.CIS.UPENN.EDU
Fri Jul 11 16:52:28 EDT 2008
E-mail Address: xinli at eller.arizona.edu
Author(s): Li, X (Li, Xin); Chen, H (Chen, Hsinchun); Huang, Z (Huang,
Zan); Roco, MC (Roco, Mihail C.)
Title: Patent citation network in nanotechnology (1976-2004)
Source: JOURNAL OF NANOPARTICLE RESEARCH, 9 (3): 337-352 JUN 2007
Language: English
Document Type: Article
Author Keywords: citation networks; knowledge discovery; knowledge
transfer; nanoscale science and engineering (NSE); nanotechnology; patent
analysis; topological analysis
Keywords Plus: KNOWLEDGE DIFFUSION; TECHNOLOGY FIELD; SCIENCE;
INSTITUTION; COUNTRY
Abstract: The patent citation networks are described using critical node,
core network, and network topological analysis. The main objective is
understanding of the knowledge transfer processes between technical
fields, institutions and countries. This includes identifying key
influential players and subfields, the knowledge transfer patterns among
them, and the overall knowledge transfer efficiency. The proposed
framework is applied to the field of nanoscale science and engineering
(NSE), including the citation networks of patent documents, submitting
institutions, technology fields, and countries. The NSE patents were
identified by keywords "full-text" searching of patents at the United
States Patent and Trademark Office (USPTO). The analysis shows that the
United States is the most important citation center in NSE research. The
institution citation network illustrates a more efficient knowledge
transfer between institutions than a random network. The country citation
network displays a knowledge transfer capability as efficient as a random
network. The technology field citation network and the patent document
citation network exhibit a less efficient knowledge diffusion capability
than a random network. All four citation networks show a tendency to form
local citation clusters.
Addresses: Univ Arizona, Eller Coll Management, Dept Management Informat
Syst, Artificial Intelligence Lab, Tucson, AZ 85721 USA; Penn State Univ,
Smeal Coll Business, Dept Supply Chain & Informat Syst, University Pk, PA
16802 USA; Natl Sci Fdn, Arlington, VA 22230 USA
Reprint Address: Li, X, Univ Arizona, Eller Coll Management, Dept
Management Informat Syst, Artificial Intelligence Lab, Tucson, AZ 85721
USA.
E-mail Address: xinli at eller.arizona.edu
Cited Reference Count: 22
Times Cited: 0
Publisher: SPRINGER
Publisher Address: VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
ISSN: 1388-0764
29-char Source Abbrev.: J NANOPART RES
ISO Source Abbrev.: J. Nanopart. Res.
Source Item Page Count: 16
Subject Category: Chemistry, Multidisciplinary; Nanoscience &
Nanotechnology; Materials Science, Multidisciplinary
ISI Document Delivery No.: 166OK
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