IDEAS home Printed from https://ideas.repec.org/h/spr/innchp/978-3-030-15409-7_20.html
   My bibliography  Save this book chapter

Technology Licensing Performance and Strategy of US Research Institutions

In: R&D Management in the Knowledge Era

Author

Listed:
  • Jisun Kim
  • Tuğrul Daim
  • João Ricardo Lavoie

Abstract

This study aims to develop institutional strategies improving licensing practice of academic research institutions based on understanding licensing performance and influencing institutional characteristics. The study resulted in a new approach that integrated the steps of identification of time lags in licensing, efficiency change analysis, and exploration of the influence of organizational characteristics on the efficiency change. A super-efficiency variable returns-to-scale DEA model was applied to the time-lag neutralized licensing data. This model measured the efficiency of US research institutions’ licensing performance over time. The study also included an innovative approach to resolve issues with the super efficiency DEA model, including mathematical infeasibility and zero data considerations. The results that are grounded on the comprehensive observations over multiple time durations provide an insight into the licensing practices of US research institutions. The recommendations for the research institutions are built on the relationships identified among academic prestige, research intensity, organizational characteristics of the technology licensing office, and licensing performance.

Suggested Citation

  • Jisun Kim & Tuğrul Daim & João Ricardo Lavoie, 2019. "Technology Licensing Performance and Strategy of US Research Institutions," Innovation, Technology, and Knowledge Management, in: Tuğrul Daim & Marina Dabić & Nuri Başoğlu & João Ricardo Lavoie & Brian J. Galli (ed.), R&D Management in the Knowledge Era, chapter 0, pages 531-549, Springer.
    • Handle: RePEc:spr:innchp:978-3-030-15409-7_20
    DOI: 10.1007/978-3-030-15409-7_20
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:innchp:978-3-030-15409-7_20. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.