IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-02311647.html
   My bibliography  Save this paper

Using neutral network analysis to uncover the trace effects of national culture

Author

Listed:
  • John F. Veiga

    (EM - EMLyon Business School)

  • Michael Lubatkin
  • Roland Calori
  • Philippe Véry
  • Alex Tung

Abstract

The primary objective of this paper is to demonstrate the usefulness of an artificial intelligence technique known as neural network analysis as an aid to uncovering the underlying patterns, or trace effects, of national culture. To make our case, we provide an application of the technique's pattern recognition capability utilizing survey data from top executives in French and British firms. We conclude by interpreting the trace effects found and encouraging the use of this tool by cross-cultural researchers in the future.

Suggested Citation

  • John F. Veiga & Michael Lubatkin & Roland Calori & Philippe Véry & Alex Tung, 2000. "Using neutral network analysis to uncover the trace effects of national culture," Post-Print hal-02311647, HAL.
    • Handle: RePEc:hal:journl:hal-02311647
    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.

    Citations

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


    Cited by:

    1. Messner, Wolfgang, 2022. "Advancing our understanding of cultural heterogeneity with unsupervised machine learning," Journal of International Management, Elsevier, vol. 28(2).
    2. Jesús Manuel De Sancha-Navarro & Juan Lara-Rubio & María Dolores Oliver-Alfonso & Luis Palma-Martos, 2021. "Cultural Sustainability in University Students’ Flamenco Music Event Attendance: A Neural Networks Approach," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    3. Stavrou, Eleni T. & Charalambous, Christakis & Spiliotis, Stelios, 2007. "Human resource management and performance: A neural network analysis," European Journal of Operational Research, Elsevier, vol. 181(1), pages 453-467, August.
    4. Hu, Michael Y. & Zhang, G. Peter & Chen, Haiyang, 2004. "Modeling foreign equity control in Sino-foreign joint ventures with neural networks," European Journal of Operational Research, Elsevier, vol. 159(3), pages 729-740, December.
    5. Brouthers, Lance Eliot & Mukhopadhyay, Somnath & Wilkinson, Timothy J. & Brouthers, Keith D., 2009. "International market selection and subsidiary performance: A neural network approach," Journal of World Business, Elsevier, vol. 44(3), pages 262-273, July.

    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:hal:journl:hal-02311647. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.