IDEAS home Printed from https://ideas.repec.org/a/ids/injdan/v6y2014i2p121-136.html
   My bibliography  Save this article

Robustness and sensitivity of conjoint analysis versus multiple linear regression analysis

Author

Listed:
  • Fahri Karakaya
  • Abhrawashyu Awasthi

Abstract

This study compares the robustness of conjoint analysis versus multiple linear regression when using orthogonal data. The explained variance (R²) by four independent variables was utilised to test the robustness of the regression analysis while Pearson's R and Kendall's tau were used for testing conjoint method. The results indicate that the two methods produce somewhat different results and conjoint analysis is more robust compared to regression.

Suggested Citation

  • Fahri Karakaya & Abhrawashyu Awasthi, 2014. "Robustness and sensitivity of conjoint analysis versus multiple linear regression analysis," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 6(2), pages 121-136.
    • Handle: RePEc:ids:injdan:v:6:y:2014:i:2:p:121-136
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=62461
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Mohamed Akli Achabou, 2021. "Is animal welfare a central issue for consumers of luxury goods?," Natural Resources Forum, Blackwell Publishing, vol. 45(1), pages 18-36, February.
    2. Shahzad Nazir & Muhammad Asif & Shahbaz Ahmad & Faisal Bukhari & Muhammad Tanvir Afzal & Hanan Aljuaid, 2020. "Important citation identification by exploiting content and section-wise in-text citation count," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-19, March.

    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:ids:injdan:v:6:y:2014:i:2:p:121-136. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=282 .

    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.