• DocumentCode
    1073226
  • Title

    Development of New Technology Forecasting Algorithm: Hybrid Approach for Morphology Analysis and Conjoint Analysis of Patent Information

  • Author

    Yoon, Byungun ; Park, Yongtae

  • Author_Institution
    Dongguk Univ., Seoul
  • Volume
    54
  • Issue
    3
  • fYear
    2007
  • Firstpage
    588
  • Lastpage
    599
  • Abstract
    Despite being a strong stimulus for the invention of new alternatives, morphology analysis (MA) suffers the limitations of being a nonquantitative, vague, and static methodology. As a consequence, the MA outcomes typically do not provide practical technology opportunities. This paper, therefore, proposes a new hybrid approach that enhances the performance of MA by combining it with conjoint analysis (CA) and citation analysis of patent information. First, keywords are extracted from patent documents using text mining, and the morphology of existing patents is identified by these keywords. Alternatives for new technology development from among the emerging technologies are presented by combining the valuable levels of each attribute in a morphology matrix predefined by domain experts. Then, configurations of new technology are suggested in order of priority using CA, and the technological feasibility of each new configuration is subsequently investigated. The technological competitiveness of a company can be analyzed by a newly suggested index, ldquotechnology share,rdquo which is analogous to the concept of market share in traditional CA. The proposed MA-CA hybrid process is illustrated with a case example of patent information from the thin film transistor-liquid crystal display (TFT-LCD) patent database.
  • Keywords
    citation analysis; data mining; mathematical morphology; patents; technological forecasting; text analysis; citation analysis; conjoint analysis; morphology analysis; morphology matrix; new technology forecasting algorithm; patent information; text mining; thin film transistor-liquid crystal display patent database; Algorithm design and analysis; Citation analysis; Data mining; Indexes; Information analysis; Morphology; Performance analysis; Technology forecasting; Text mining; Thin film transistors; Conjoint analysis (CA); hybrid approach; morphology analysis (MA); patent information; technology forecasting;
  • fLanguage
    English
  • Journal_Title
    Engineering Management, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9391
  • Type

    jour

  • DOI
    10.1109/TEM.2007.900796
  • Filename
    4278022