IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v79y2012i1p3-15.html
   My bibliography  Save this article

Using patent analysis to establish technological position: Two different strategic approaches

Author

Listed:
  • Chang, Shann-Bin

Abstract

Discussions on business strategy formation in the past 50years can be separated into two categories: the inside-out and the outside-in approach. Technology is a critical factor when manager formulate their business strategy, and patents have served as an important indicator of technology. A patent portfolio can be used to understand the capabilities of a firm, as an inside resource pattern; and the patent citation of firms can be used to find the relationship of a firm, as an outside dependency. This study uses patent information to establish an effective model for the technological position of business methods. The 5 by 6 matrix was generated and four situations between firms were induced. Researchers and managers can use that matrix and situations to recognize the real competitors or cooperators, and formulate the technological strategies which include competition, cooperation, or complementary cooperation.

Suggested Citation

  • Chang, Shann-Bin, 2012. "Using patent analysis to establish technological position: Two different strategic approaches," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 3-15.
  • Handle: RePEc:eee:tefoso:v:79:y:2012:i:1:p:3-15
    DOI: 10.1016/j.techfore.2011.07.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162511001387
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Katia Angue & Cécile Ayerbe & Liliana Mitkova, 2014. "A method using two dimensions of the patent classification for measuring the technological proximity: an application in identifying a potential R&D partner in biotechnology," The Journal of Technology Transfer, Springer, vol. 39(5), pages 716-747, October.
    2. Hanlin You & Mengjun Li & Jiang Jiang & Bingfeng Ge & Xueting Zhang, 2017. "Evolution monitoring for innovation sources using patent cluster analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 693-715, May.
    3. H. Simon & N. Sick, 2016. "Technological distance measures: new perspectives on nearby and far away," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1299-1320, June.
    4. Johannes van der Pol, 2015. "Structural dynamics of the French aerospace sector: A network analysis," Working Papers hal-01284993, HAL.
    5. Hanlin You & Mengjun Li & Keith W. Hipel & Jiang Jiang & Bingfeng Ge & Hante Duan, 2017. "Development trend forecasting for coherent light generator technology based on patent citation network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 297-315, April.
    6. Antonio Messeni Petruzzelli & Daniele Rotolo & Vito Albino, 2014. "Determinants of Patent Citations in Biotechnology: An Analysis of Patent Influence Across the Industrial and Organizational Boundaries," SPRU Working Paper Series 2014-05, SPRU - Science Policy Research Unit, University of Sussex Business School.
    7. Li, Yung-Ta & Huang, Mu-Hsuan & Chen, Dar-Zen, 2014. "Positioning and shifting of technology focus for integrated device manufacturers by patent perspectives," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 363-375.
    8. Faria, Lourenço Galvão Diniz & Andersen, Maj Munch, 2017. "Sectoral patterns versus firm-level heterogeneity - The dynamics of eco-innovation strategies in the automotive sector," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 266-281.
    9. Kato, Masatoshi & Zhou, Haibo, 2018. "Numerical labor flexibility and innovation outcomes of start-up firms: A panel data analysis," Technovation, Elsevier, vol. 69(C), pages 15-27.
    10. Pantano, Eleonora & Priporas, Constantinos-Vasilios & Stylos, Nikolaos, 2018. "Knowledge Push Curve (KPC) in retailing: Evidence from patented innovations analysis affecting retailers' competitiveness," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 150-160.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:79:y:2012:i:1:p:3-15. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.