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Towards the implementation of corporate governance best practices for Tunisian listed firms: an empirical approach using the artificial neuronal networks

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  • Wided Khiari
  • Azhaar Lajmi

Abstract

The object of this study is to propose a code allowing the assessment of some corporate governance best practices for Tunisian listed firms. This code is based on the most reputable set of codes of good governance practices worldwide and on the point of view of a sample of Tunisian experts. This code is presented as a potential tool that measures the quality of some corporate governance characteristics, such as board of directors and its committees, transparency and information policy, directors' compensation and entrenchment, and ownership structure. Using a questionnaire distributed to a sample of Tunisian experts (about 102 experts) and referring to a new approach based on the artificial neural networks, this study allowed us first, to identify the importance given by the experts to a number of criteria in assessing corporate governance of Tunisian listed firms, and second, to create consensus among experts on the values that should take the different criteria in order to achieve good governance.

Suggested Citation

  • Wided Khiari & Azhaar Lajmi, 2018. "Towards the implementation of corporate governance best practices for Tunisian listed firms: an empirical approach using the artificial neuronal networks," African Journal of Accounting, Auditing and Finance, Inderscience Enterprises Ltd, vol. 6(1), pages 21-42.
    • Handle: RePEc:ids:ajaafi:v:6:y:2018:i:1:p:21-42
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    Cited by:

    1. Luciano Barcellos‐Paula & Carlos Agüero‐Olivos, 2022. "The strengthening of corporate governance based on applied fuzzy logic," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 29(5), pages 1736-1746, September.

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