IDEAS home Printed from https://ideas.repec.org/h/spr/eurchp/978-3-319-76288-3_18.html
   My bibliography  Save this book chapter

Pricing of the License Agreements: Improvement of the Methodology on the Basis of the Game Approach

In: Consumer Behavior, Organizational Strategy and Financial Economics

Author

Listed:
  • Dmitriy G. Rodionov

    (Peter the Great St. Petersburg Polytechnic University)

  • Iuliia V. Boiko

    (Peter the Great St. Petersburg Polytechnic University)

  • Olga S. Nadezhina

    (Peter the Great St. Petersburg Polytechnic University)

Abstract

Dealing with practical issues concerning pricing is a topical problem of innovation commercialization and is related to controversial approaches of experts to evaluation of profits or losses when using intellectual property items and establishing “fair” amounts of payoffs under license agreements. Based on this approach, the authors created the methodology of pricing of the license agreements. In the result, authors can conclude that the game approach is developed and reviewed statistical methods and made possible to take in touch factors which are not represented explicitly, such as the preferences of constituent entities of the transaction. Obtaining a coherent assessment under conditions of incomplete and insufficiently accurate information makes it possible to justify the formation of a value chain in the process of commercialization of innovation and to assess the effectiveness of the strategy.

Suggested Citation

  • Dmitriy G. Rodionov & Iuliia V. Boiko & Olga S. Nadezhina, 2018. "Pricing of the License Agreements: Improvement of the Methodology on the Basis of the Game Approach," Eurasian Studies in Business and Economics, in: Mehmet Huseyin Bilgin & Hakan Danis & Ender Demir & Ugur Can (ed.), Consumer Behavior, Organizational Strategy and Financial Economics, pages 241-252, Springer.
    • Handle: RePEc:spr:eurchp:978-3-319-76288-3_18
    DOI: 10.1007/978-3-319-76288-3_18
    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.

    Citations

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


    Cited by:

    1. Andrey Zaytsev & Ekaterina Mihel & Nikolay Dmitriev & Dmitry Alferyev & Ungvari Laszlo, 2024. "Optimization of Interaction with Counterparties: Selection Game Algorithm under Uncertainty," Mathematics, MDPI, vol. 12(13), pages 1-26, July.

    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:eurchp:978-3-319-76288-3_18. 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.