IDEAS home Printed from https://ideas.repec.org/a/eee/jobhdp/v154y2019icp34-48.html
   My bibliography  Save this article

“I want to serve but the public does not understand:” Prosocial motivation, image discrepancies, and proactivity in public safety

Author

Listed:
  • Patil, Shefali V.
  • Lebel, R. David

Abstract

Scholars typically find that prosocial motivation is positively related to employee proactivity. However, we argue that in highly visible contexts such as public safety, this relationship is contingent on how employees think the public sees their jobs. Specifically, drawing on image discrepancy theories, we hypothesize that the relationship between prosocial motivation and proactive behavior is weakened when employees believe that the public fails to understand the difficulties of their jobs. This interaction is supported in multisource studies of 183 police officers across six agencies (Study 1a) and 238 firefighters across eight stations (Study 1b). In a time-separated, multisource study of 203 police officers at a metropolitan agency (Study 2), we further find that the interaction indirectly relates to proactivity via employees’ physical engagement. Overall, our studies highlight the importance of accounting not only for employees’ prosocial motivation, but also their perceived public image, especially in highly visible, high-risk contexts.

Suggested Citation

  • Patil, Shefali V. & Lebel, R. David, 2019. "“I want to serve but the public does not understand:” Prosocial motivation, image discrepancies, and proactivity in public safety," Organizational Behavior and Human Decision Processes, Elsevier, vol. 154(C), pages 34-48.
    • Handle: RePEc:eee:jobhdp:v:154:y:2019:i:c:p:34-48
    DOI: 10.1016/j.obhdp.2019.07.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0749597817300675
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.obhdp.2019.07.002?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. Cho, Eunae & Chen, Miaohua & Toh, Shi Min & Ang, Jansen, 2021. "Roles of effort and reward in well-being for police officers in Singapore: The effort-reward imbalance model," Social Science & Medicine, Elsevier, vol. 277(C).

    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:eee:jobhdp:v:154:y:2019:i:c:p:34-48. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/obhdp .

    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.