Duality CEO-Chairman and its relation with the effectiveness of the board control

  • Received July 31, 2019;
    Accepted November 22, 2019;
    Published December 16, 2019
  • Author(s)
  • DOI
  • Article Info
    Volume 17 2019, Issue #4, pp. 239-251
  • Cited by
    3 articles

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This work is licensed under a Creative Commons Attribution 4.0 International License

The study focused on analyzing the duality CEO-Chairman and its relation on the effectiveness of the board control. A sample of 347 companies with annual sales volume greater than five million US dollars was selected; a questionnaire was provided in order to measure the effectiveness of the board control. To measure the duality CEO-Chairman secondary information was used, and verification was made about the existence of the duality. The effectiveness of the board was measured by an index obtained through the use of confirmatory factorial analysis. Statistical tests were performed, such as Student’s t-test for mean difference, Chi-square to measure the dependence and regression by simultaneous equations to answer the questions. As a result, it was found out that the duality CEO-Chairman is connected in a significant way with the performance of independent directors and risk supervision of the board. The results regarding the duality relationship CEO-Chairman and performance of independent directors are shown to be inverse, while with risk supervision it becomes direct. The obtained results theoretically contribute to the knowledge regarding the practices of good corporate governance.

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    • Table 1. Distribution of the sample
    • Table 2. Cronbach’s alpha coefficient per construct
    • Table 3. Description of model variables
    • Table 4. Univariate normality test – asymmetry and kurtosis
    • Table 5. Mardia multivariate normality test
    • Table 6. Indexes of goodness adjustment for the models of the constructs
    • Table 7. T-test of average contrast between the constructs and duality CEO-Chairman
    • Table 8. Associativity test between the study variables
    • Table 9. Regression by simultaneous equations through MCO
    • Table A1. Variables names