The relationship between corporate governance mechanisms and financial performance: The case of listed industrial companies in Oman

  • Received March 31, 2023;
    Accepted May 15, 2023;
    Published June 1, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.20(2).2023.21
  • Article Info
    Volume 20 2023, Issue #2, pp. 244-255
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This work is licensed under a Creative Commons Attribution 4.0 International License

The purpose of the study is to examine the impact of corporate governance mechanisms on the financial performance of listed industrial companies in Oman. As the main research method, panel data regression analysis was used to analyze data from 36 Omani industrial companies, listed on the Muscat Stock Exchange for the period 2017–2021. Three regression models were developed using three dependent variables (Return on Assets, Return on Equity, Return on Sales), seven independent variables (Board Size, Independent and Non-executive Board Members, Board Meeting, Chief Executive Officer, Dummy variable for Board Change, Dummy variable for the Secretary on the Board, Dummy variable for Internal Auditor), and two control variables (Leverage, Size of the company). According to the research results, a negative influence of the Board Size and Dummy variable for the presence of the Secretary on the Board on the Return on Assets indicator at 10% and 5% significance level was found; moreover, there is a positive influence of Leverage and Size of the company at the 1% and 5% significance level on Return of Assets. Although, none of the independent variables used has a significant impact on the Return on Equity indicator. Return on Sales is significantly affected only by two control variables, i.e., a negative impact of Leverage at the 10% significance level and a positive impact of the Size of the company at the 10% significance level. The results obtained in the study indicate the imperfection of the corporate governance mechanisms implemented by Omani industrial companies in the field of ensuring financial efficiency.

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    • Table 1. Scientific papers on the research topic and their citations in the academic literature for the period 2018–2022
    • Table 2. Research variables (definitions, calculation and abbreviations)
    • Table 3. Descriptive statistics of variables (based on observations 1:1 - 36:5)
    • Table 4. Correlation coefficients (based on observations 1:1 – 36:5)
    • Table 5. Models 1-3 (ROA, ROE, and ROS). Pooled OLS, REM using the observations 1-180
    • Conceptualization
      Alina Raboshuk, Dmytro Zakharov, Serhii Lehenchuk
    • Funding acquisition
      Alina Raboshuk, Oksana Morgulets, Olena Hryhorevska
    • Project administration
      Alina Raboshuk, Dmytro Zakharov, Serhii Lehenchuk
    • Resources
      Alina Raboshuk, Dmytro Zakharov, Oksana Morgulets
    • Software
      Alina Raboshuk, Dmytro Zakharov, Olena Hryhorevska
    • Supervision
      Alina Raboshuk, Serhii Lehenchuk
    • Writing – review & editing
      Alina Raboshuk, Serhii Lehenchuk
    • Data curation
      Dmytro Zakharov, Oksana Morgulets, Olena Hryhorevska
    • Investigation
      Dmytro Zakharov, Serhii Lehenchuk, Oksana Morgulets, Olena Hryhorevska
    • Methodology
      Dmytro Zakharov, Serhii Lehenchuk
    • Visualization
      Dmytro Zakharov, Olena Hryhorevska
    • Writing – original draft
      Dmytro Zakharov, Serhii Lehenchuk, Oksana Morgulets, Olena Hryhorevska
    • Formal Analysis
      Serhii Lehenchuk, Olena Hryhorevska
    • Validation
      Serhii Lehenchuk, Oksana Morgulets