IDEAS home Printed from https://ideas.repec.org/a/igg/joris0/v7y2016i4p38-66.html
   My bibliography  Save this article

A Fuzzy TOPSIS+Worst-Case Model for Personnel Evaluation Using Information Culture Criteria

Author

Listed:
  • Rasim M. Alguliyev

    (Institute of Information Technology, Azerbaijan National Academy of Sciences, Baku, Azerbaijan)

  • Ramiz M. Aliguliyev

    (Institute of Information Technology, Azerbaijan National Academy of Sciences, Baku, Azerbaijan)

  • Rasmiyya S. Mahmudova

    (Institute of Information Technology, Azerbaijan National Academy of Sciences, Baku, Azerbaijan)

Abstract

Personnel evaluation process is aimed at choosing the best alternative to fill the defined vacancy in an organization. It determines the input quality of personnel and thus plays an important role in human resource management. The multi criteria nature and the presence of qualitative factors make it considerably more complex. This paper proposes a hybrid fuzzy MCDM model for personnel evaluation. It combines the fuzzy TOPSIS method with fuzzy worst-case (or entropy) method for linguistic reasoning under group decision making. Fuzzy worst-case and entropy methods are used to get weights of criteria, while fuzzy TOPSIS is utilized to rank the alternatives. The weights obtained from fuzzy worst-case and entropy methods are included in fuzzy TOPSIS computations and the alternatives are evaluated. The fuzzy MCDM for group decision making enables to aggregate subjective assessments of the decision-makers and thus offer an opportunity to perform more robust personnel evaluation procedures. To evaluate the alternatives the authors have formed an executive group consisting of five decision-makers. For evaluation the group has decided to consider five information culture criteria expressed in linguistic variables. A numerical example demonstrated the possibilities of application of the proposed method.

Suggested Citation

  • Rasim M. Alguliyev & Ramiz M. Aliguliyev & Rasmiyya S. Mahmudova, 2016. "A Fuzzy TOPSIS+Worst-Case Model for Personnel Evaluation Using Information Culture Criteria," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 7(4), pages 38-66, October.
    • Handle: RePEc:igg:joris0:v:7:y:2016:i:4:p:38-66
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJORIS.2016100102
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. María Carmen Carnero, 2020. "Fuzzy TOPSIS Model for Assessment of Environmental Sustainability: A Case Study with Patient Judgements," Mathematics, MDPI, vol. 8(11), pages 1-43, November.

    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:igg:joris0:v:7:y:2016:i:4:p:38-66. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.