IDEAS home Printed from https://ideas.repec.org/a/taf/jsustf/v12y2022i2p536-553.html
   My bibliography  Save this article

Forming methodologies to improving the efficiency of innovative companies based on leasing tools

Author

Listed:
  • Andrey S. Nechaev
  • Sergey V. Zakharov
  • Yuliya N. Barykina
  • Marina V. Vel'm
  • Olga N. Kuznetsova

Abstract

This study is relevant since the formation of methodologies to improve the efficiency of innovative leasing-based companies is vital since the leasing form of financing are significant in updating the fixed assets of small and medium enterprises. The aim is to create an original leasing tool to improve the efficiency of innovative companies. The study uses comparative analysis, economic and mathematical modeling of synthesis, and graphical methods of data processing. Methodology to use leasing tools to improve the efficiency of innovative enterprises are presented. The result is the method of calculating lease payments for operating leasing regarding both the method of calculating depreciation based on the sum of years and the amounts of insurance payments for financial and property insurance. This method allows those who uses operational leasing to vary the indicators that form the lease payment through a variable coefficient of the depreciable part of the leasing property.

Suggested Citation

  • Andrey S. Nechaev & Sergey V. Zakharov & Yuliya N. Barykina & Marina V. Vel'm & Olga N. Kuznetsova, 2022. "Forming methodologies to improving the efficiency of innovative companies based on leasing tools," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 12(2), pages 536-553, April.
  • Handle: RePEc:taf:jsustf:v:12:y:2022:i:2:p:536-553
    DOI: 10.1080/20430795.2020.1784681
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/20430795.2020.1784681
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/20430795.2020.1784681?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Luigi De Cesare & Lucianna CananĂ  & Tiziana Ciano & Massimiliano Ferrara, 2024. "Modeling financial leasing by optimal stopping approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 47(1), pages 199-213, June.

    More about this item

    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:taf:jsustf:v:12:y:2022:i:2:p:536-553. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSFI20 .

    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.