Inter-cluster connectivity analysis for technology opportunity discovery

Byunghoon Kim, Gianluca Gazzola, Jae-Min Lee, Dohyun Kim, Kanghoe Kim and Myong K. Jeong ()
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Byunghoon Kim: Rutgers, The State University of New Jersey
Gianluca Gazzola: Rutgers, The State University of New Jersey
Jae-Min Lee: Korea Institute of Science and Technology Information
Dohyun Kim: Korea Institute of Science and Technology Information
Kanghoe Kim: Korea Institute of Science and Technology Information
Myong K. Jeong: Rutgers, The State University of New Jersey

Scientometrics, 2014, vol. 98, issue 3, No 14, 1825 pages

Abstract: Abstract In today’s competitive business environment, the timely identification of potential technology opportunities is becoming increasingly important for the strategic management of technology and innovation. Existing studies in the field of technology opportunity discovery (TOD) focus exclusively on patent textual information. In this article, we introduce a new method that tackles TOD via technology convergence, using both patent textual data and patent citation networks. We identify technology groups with high convergence potential by measuring connectivity between clusters of patents. From such technology groups we select pairs of core patents based on their technological relatedness, on their past involvement in convergence, and on the impact of their new potential convergence. We finally carry out TOD by extracting representative keywords from the text of the selected patent pairs and organizing them into the basic description of a new invention, which the potential convergence of the patent pair might produce. We illustrate our proposed method using a data set of U.S. patents in the field of digital information and security.

Keywords: Technology opportunity; Technology convergence; Inter-cluster connectivity; Patent citation network; Keyword; Core patent (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (15)

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DOI: 10.1007/s11192-013-1097-2

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