IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-030-26284-6_1.html
   My bibliography  Save this book chapter

Modeling of Wage Payment System Choosing Task

In: Global Economics and Management: Transition to Economy 4.0

Author

Listed:
  • A. S. Shilnikov

    (NPK “ETT” LLC)

  • Artur A. Mitsel

    (Tomsk State University of Control Systems and Radioelectronics
    Tomsk State University)

Abstract

The article proposes the authors’ approach to the assessment of wage payment systemsWage payment systems, comparing them with each other and an approach to forecasting the results from the introduction of a particular wage payment system. The article assesses the time-premium and piece-premium wage payment system. To obtain statistical data and approbation of the approach, the Monte Carlo methodMonte Carlo method was used with two different types of distribution of random variables: discrete uniform and normal. Using the regression analysisRegression analysis method, we interpret the data obtained and draw up the conclusions. The main conclusions of the study can be considered as follows: first, the assessment of wage payment systemsWage payment systems shall be carried out using the normal distributionNormal distribution. Second, both wage payment systems have advantages and disadvantages, which are clearly shown in numbers. Thus, the systems can demonstrate a positive economic effect, but a negative social one. What to give preference to is already becoming a matter of choice to be made by the management personnel at the enterprises.

Suggested Citation

  • A. S. Shilnikov & Artur A. Mitsel, 2019. "Modeling of Wage Payment System Choosing Task," Springer Proceedings in Business and Economics, in: Mikhail Kaz & Tatiana Ilina & Gennady A. Medvedev (ed.), Global Economics and Management: Transition to Economy 4.0, chapter 0, pages 3-13, Springer.
  • Handle: RePEc:spr:prbchp:978-3-030-26284-6_1
    DOI: 10.1007/978-3-030-26284-6_1
    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:prbchp:978-3-030-26284-6_1. 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.