IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/3664709.html
   My bibliography  Save this article

A Novel Contractor Selection Technique Using the Extended PROMETHEE II Method

Author

Listed:
  • Kuei-Hu Chang
  • Ali Ahmadian

Abstract

Selecting suitable contractors directly influences product quality, corporate profits, and even sustainable development. The selection problem of contractors is, therefore, a critical issue for the sustainable development of an enterprise. However, traditional contractor selection techniques are unable to handle information regarding the relative importance of criteria or handle nonexistent or missing data in the assessment process of contractor selection. In order to effectively address this problem, this study proposes a new contractor selection technique that integrates the concept of soft set and the PROMETHEE II method to select suitable contractors. Three numerical examples are applied to prove the correctness and effectiveness of the proposed technique. This study also compares the simulation results achieved using the proposed method with those achieved using the traditional weighted arithmetic averaging method and the data envelopment analysis (DEA) technique. The simulation results show that the proposed method is a more general contractor selection technique for handling incomplete information than the traditional weighted arithmetic averaging method and the DEA method.

Suggested Citation

  • Kuei-Hu Chang & Ali Ahmadian, 2021. "A Novel Contractor Selection Technique Using the Extended PROMETHEE II Method," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-11, November.
  • Handle: RePEc:hin:jnlmpe:3664709
    DOI: 10.1155/2021/3664709
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/3664709.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/mpe/3664709.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2021/3664709?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
    ---><---

    Citations

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


    Cited by:

    1. Huixia Huang & Chi Zhou & Hepu Deng, 2024. "A DEA Game Cross-Efficiency Model with Loss Aversion for Contractor Selection," Mathematics, MDPI, vol. 12(10), pages 1-18, May.
    2. Katerina Fotova Čiković & Ivana Martinčević & Joško Lozić, 2022. "Application of Data Envelopment Analysis (DEA) in the Selection of Sustainable Suppliers: A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(11), pages 1-30, May.

    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:hin:jnlmpe:3664709. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.