IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-031-34589-0_23.html
   My bibliography  Save this book chapter

Predicting the Performance of New Hires: The Role of Humility, Interpersonal Understanding, Self-Confidence, and Flexibility

In: State of the Art in Partial Least Squares Structural Equation Modeling (PLS-SEM)

Author

Listed:
  • Debolina Dutta

    (Indian Institute of Management)

  • Chaitali Vedak

    (Indian Institute of Management)

  • Varghees Joseph

    (Indian Institute of Management)

Abstract

High performance of new hires is of imminent interest to organizations. Therefore, understanding antecedents that enhance job performance among new hires would be of interest to research and practice. However, there are contradictory and limited studies focusing on relevant traits of new hires that improve on-job performance. Drawing on Human Capital Theory, we argue that job applicants demonstrating humility, accompanied by interpersonal understanding, self-confidence, and flexibility deliver higher on-job performance. We find that humility is a significant predictor of job performance through a longitudinal field survey spanning 16 months, using multisource data of 205 real job applicants and their performance ratings, analyzed using PLS-SEM: since it allows the researchers to examine the relationships between multiple latent variables (i.e., humility, interpersonal understanding, self-confidence, and flexibility) and a single observed variable (i.e., new hire performance) in a single model. Further, humility wholly mediates the effect of interpersonal understanding, self-confidence, and flexibility on new hire performance.

Suggested Citation

  • Debolina Dutta & Chaitali Vedak & Varghees Joseph, 2023. "Predicting the Performance of New Hires: The Role of Humility, Interpersonal Understanding, Self-Confidence, and Flexibility," Springer Proceedings in Business and Economics, in: Lăcrămioara Radomir & Raluca Ciornea & Huiwen Wang & Yide Liu & Christian M. Ringle & Marko Sarstedt (ed.), State of the Art in Partial Least Squares Structural Equation Modeling (PLS-SEM), pages 239-244, Springer.
  • Handle: RePEc:spr:prbchp:978-3-031-34589-0_23
    DOI: 10.1007/978-3-031-34589-0_23
    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:978-3-031-34589-0_23. 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.