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Generating Competitive Technical Intelligence Using Topical Analysis, Patent Citation Analysis, and Term Clumping Analysis

In: Anticipating Future Innovation Pathways Through Large Data Analysis

Author

Listed:
  • Ying Huang

    (Beijing Institute of Technology)

  • Yi Zhang

    (Beijing Institute of Technology
    University of Technology Sydney)

  • Jing Ma

    (Beijing Institute of Technology)

  • Alan L. Porter

    (Georgia Institute of Technology
    Search Technology Inc.)

  • Xuefeng Wang

    (Beijing Institute of Technology)

  • Ying Guo

    (Beijing Institute of Technology)

Abstract

Because of the flexibility and complexity of Newly Emerging Science and Technologies (NESTs), traditional statistical analysis fails to capture technology evolution in detail. Tracking technology evolution pathways supports industrial, governmental, and academic decisions to guide future development trends. Patents are one of the most important NESTs data sources and are pertinent to developmental paths. This paper draws upon text analyses, augmented by expert knowledge, to identify key NESTs sub-domains and component technologies. We then complement those analyses with patent citation analysis to help track developmental progressions. We identify key sub-domain patents, associated with particular component technology trajectories, then extract pivotal patents via citation analysis. We compose evolutionary pathways by combining citation and topical intelligence obtained through term clumping. We demonstrate our approach with empirical analysis of dye-sensitized solar cells (DSSCs), as an example of a promising NESTs, contributing to the remarkable growth in the renewable energy industry. The systematic approach we proposed not only offers a macro-perspective covering technology development levels and future trends, but also makes R&D information accessible for micro-level probes as needed. We work to uncover developmental trends and to compile mentions of possible applications, and this study informs NESTs management by spotting prime opportunities for innovation.

Suggested Citation

  • Ying Huang & Yi Zhang & Jing Ma & Alan L. Porter & Xuefeng Wang & Ying Guo, 2016. "Generating Competitive Technical Intelligence Using Topical Analysis, Patent Citation Analysis, and Term Clumping Analysis," Innovation, Technology, and Knowledge Management, in: Tugrul U. Daim & Denise Chiavetta & Alan L. Porter & Ozcan Saritas (ed.), Anticipating Future Innovation Pathways Through Large Data Analysis, chapter 0, pages 153-172, Springer.
    • Handle: RePEc:spr:innchp:978-3-319-39056-7_9
    DOI: 10.1007/978-3-319-39056-7_9
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    Cited by:

    1. Xuefeng Wang & Shuo Zhang & Yuqin liu, 2022. "ITGInsight–discovering and visualizing research fronts in the scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6509-6531, November.

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