IDEAS home Printed from https://ideas.repec.org/a/taf/rpxmxx/v22y2020i2p206-233.html
   My bibliography  Save this article

Attractiveness of public sector employment at the pre-entry level – a hierarchical model approach and analysis of gender effects

Author

Listed:
  • Sanja Korac
  • Jörg Lindenmeier
  • Iris Saliterer

Abstract

Understanding what characterizes individuals who choose to work for the public sector is critical to public management research and practice. This article explores the effect of Big Five personality traits, PSM, and work values on the attractiveness of public sector employment. The hierarchical model approach allows disentangling possible existing relationships between those concepts and provides answers to whether specific work values and PSM dimensions drive the attractiveness of public sector employment or whether the variance is accounted for by deeper level personality traits. Multi-group analyses revealed important gender effects, suggesting that considering gender as a control variable may be insufficient.

Suggested Citation

  • Sanja Korac & Jörg Lindenmeier & Iris Saliterer, 2020. "Attractiveness of public sector employment at the pre-entry level – a hierarchical model approach and analysis of gender effects," Public Management Review, Taylor & Francis Journals, vol. 22(2), pages 206-233, February.
  • Handle: RePEc:taf:rpxmxx:v:22:y:2020:i:2:p:206-233
    DOI: 10.1080/14719037.2019.1582688
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14719037.2019.1582688
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/14719037.2019.1582688?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.

    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:rpxmxx:v:22:y:2020:i:2:p:206-233. 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/rpxm .

    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.