IDEAS home Printed from https://ideas.repec.org/p/dar/wpaper/131771.html
   My bibliography  Save this paper

You Got the Job! Understanding Hiring Decisions for Robots as Organizational Members

Author

Listed:
  • Heitlinger, Lea
  • Stock-Homburg, Ruth
  • Wolf, Franziska Doris

Abstract

As social robots will likely be central to future human-robot interactions at work, we assess hiring decisions for social robots as a natural first step prior to their integration into organizations. With a basis in the technology acceptance model and social identity theory, this study focuses on differences between humanoid robotic, android robotic and human candidates. We first examine performance-based evaluations of the applicants by focusing on expectation disconfirmation. While for the human candidate, the interplay between expectations and experiences is decisive for the judgement, for social robots, the actual experience of the hiring situation dominates the decision. Besides the rational decision criteria, we further look into social-cue-based evaluations as social biases in hiring situations. Categorization as social ingroup leads to an absolute preference for the human candidate (i.e., ingroup favoritism) with no differences in preference for the robotic social outgroup (i.e., outgroup homogeneity effect).

Suggested Citation

  • Heitlinger, Lea & Stock-Homburg, Ruth & Wolf, Franziska Doris, 2022. "You Got the Job! Understanding Hiring Decisions for Robots as Organizational Members," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 131771, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
  • Handle: RePEc:dar:wpaper:131771
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/131771/
    as

    Download full text from publisher

    File URL: https://dl.acm.org/doi/10.5555/3523760.3523830
    Download Restriction: no
    ---><---

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:dar:wpaper:131771. 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: Dekanatssekretariat (email available below). General contact details of provider: https://edirc.repec.org/data/ivthdde.html .

    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.