IDEAS home Printed from https://ideas.repec.org/a/vrs/poicbe/v12y2018i1p975-982n87.html
   My bibliography  Save this article

Human resource performance predictors based on the human energy profile

Author

Listed:
  • Torp Andronicus
  • Purcarea Anca Alexandra

    (Politehnica University of Bucharest, Bucharest, Romania)

  • Andrei Andreia Gabriela

    (Alexandru Ioan Cuza University of Iasi, Iasi, Romania)

Abstract

This paper is a comparative study on the findings regarding the connection between a person’s energy profile and that person’s professional performance. As the performance predictors that are used within Human Resource Management may provide a company with important information regarding the future performance of an employee, it is of great importance that these performance predictors be kept up-to-date, both in what regards the precision of each predictor, and by including new performance predictors to the present array of HR predictors should such new predictors be found. This paper is an empirical examination of two such predictors, stress and energy, and argues that, based on the available empirical material, it seems to be possible to expand the present selection of HR predictors with these two predictors as well. This study is based on the ontological framework set forth by academics such as Einstein, Hawking, Tiller, Hunt, Motoyama, regarding the possibility of assessing the human being based on their energy profile. The part concerning Human Resource Management is based on the scientific framework put forth by Hunter & Hunter. Their study shows the validity of the vast majority of the performance predictors used within Human Resource Management, and discusses their practical validity. Then, there is the trans-disciplinary approach, where it is shown based on the empirical studies conducted by Torp et al. if, and how, the present array of performance indicators that are used in the field of Human Resource Management may be improved. Here, different and complementary scientific studies are included to document that the proposed Human Resource Management performance predictor is in reality more than just a predictor, it is an assessment tool that can both predict, and at the same time help quantify a series of the most modern initiatives within Human Resource Management, such as integrating sport, mindfulness, diet, etc. in the workday in order to improve performance.

Suggested Citation

  • Torp Andronicus & Purcarea Anca Alexandra & Andrei Andreia Gabriela, 2018. "Human resource performance predictors based on the human energy profile," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 12(1), pages 975-982, May.
    • Handle: RePEc:vrs:poicbe:v:12:y:2018:i:1:p:975-982:n:87
    DOI: 10.2478/picbe-2018-0087
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/picbe-2018-0087
    Download Restriction: no
    File URL: https://libkey.io/10.2478/picbe-2018-0087?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
    ---><---

    References listed on IDEAS

    as
    1. Andronicus TORP & Adrian BUNEA & Corina CIPU, 2016. "Company Aikido – It Seems To Be A Practical Method To Reduce Stress And Increase A Person’S Energy," SEA - Practical Application of Science, Romanian Foundation for Business Intelligence, Editorial Department, issue 10, pages 27-31, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:vrs:poicbe:v:12:y:2018:i:1:p:975-982:n:87. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.