[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/h/wsi/wschap/9789811202391_0054.html
   My bibliography  Save this book chapter

Applications of Fuzzy Set to International Transfer Pricing and Other Business Decisions

In: HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING

Author

Listed:
  • Wikil Kwak
  • Yong Shi
  • Heeseok Lee
  • Cheng Few Lee
Abstract
In today’s dynamic but ambiguous business environment the fuzzy set applications are growing continuously as one of a manager’s most useful decision-making tools. Recent fuzzy set business applications show promising results (Alcantud et al., 2017; Frini, 2017; Toklu, 2017; Wang et al., 2017). International transfer pricing recently has received more attention as the US wages trade wars with China and other countries as some firms try to choose minimizing taxes as a transfer pricing strategy. This chapter demonstrates how to apply the fuzzy set in international transfer pricing problems. Applications of Fuzzy Set to Other Business Decision are also discussed in some detail.

Suggested Citation

  • Wikil Kwak & Yong Shi & Heeseok Lee & Cheng Few Lee, 2020. "Applications of Fuzzy Set to International Transfer Pricing and Other Business Decisions," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 54, pages 1991-2009, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789811202391_0054
    as

    Download full text from publisher

    File URL: https://www.worldscientific.com/doi/pdf/10.1142/9789811202391_0054
    Download Restriction: Ebook Access is available upon purchase.
    File URL: https://www.worldscientific.com/doi/abs/10.1142/9789811202391_0054
    Download Restriction: Ebook Access is available upon purchase.
    ---><---

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

    More about this item

    Keywords

    Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    Statistics

    Access and download statistics

    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:wsi:wschap:9789811202391_0054. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscientific.com/page/worldscibooks .

    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.