IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-319-68762-9_48.html
   My bibliography  Save this book chapter

The First and the Second Generation of Statistical Methods in Management Accounting Research

In: The Impact of Globalization on International Finance and Accounting

Author

Listed:
  • Ladislav Šiška

    (Masaryk university, Faculty of Economics and Administration)

Abstract

Calls for more frequent application of the second-generation statistical methods such as structural equation modeling (SEM) have emerged in the field of management accounting recently. The aim of this article is to compare these statistical methods to the first-generation methods using the real-life example. Specifically, the relationship between the organizational capabilities and perceived nonfinancial performance is investigated. Firstly, the sequential combination of principal component analysis and regression analysis is deployed to the outlined case example. Secondly, partial least squares structural equation modeling (PLS-SEM) is applied to the case example. The comparison of both approaches proves SEM to be more vigilant statistical method for capturing the strength of relationship between latent constructs.

Suggested Citation

  • Ladislav Šiška, 2018. "The First and the Second Generation of Statistical Methods in Management Accounting Research," Springer Proceedings in Business and Economics, in: David Procházka (ed.), The Impact of Globalization on International Finance and Accounting, pages 441-448, Springer.
  • Handle: RePEc:spr:prbchp:978-3-319-68762-9_48
    DOI: 10.1007/978-3-319-68762-9_48
    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:978-3-319-68762-9_48. 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.