An Exploratory Analysis of Corporate Governance using Supervised Data Mining Learning
Jyotsna Ghildiyal Bijalwan1, Anchit Bijalwan2, Lisanework Amare3
1Jyotsna Ghildiyal Bijalwan*, Department of Finance & Accounting, Arba Minch University, Arba Minch, Ethiopia.
2Anchit Bijalwan, Faculty of Electrical & Computer Engineering, Arba Minch University, Arba Minch, Ethiopia.
3Lisanework Amare, Department of Finance & Accounting, Arba Minch University, Arba Minch, Ethiopia.
Manuscript received on 4 August 2019. | Revised Manuscript received on 8 August 2019. | Manuscript published on 30 September 2019. | PP: 3546-3557 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5279098319/2019©BEIESP | DOI: 10.35940/ijrte.C5279.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The corporate governance is a much discussed issue among the corporate and regulators. With the time and advancement in information and technology, the methods of investigations in the field have also changed for the better and accurate outputs. The study primarily investigates the nature and effect of good corporate governance on the firm’s financial performance using data mining analysis. For the investigation the board meetings and board remunerations are taken as the components of corporate governance whereas firm performance is a depended variable which is measured by return on capital employed (ROCE), return on equity (ROE), and return on assets (ROA). The study results are suggestive of a positive and significant relationship between board meetings and the firm performance whereas the board remuneration has no impact over the firm performance.
Keywords: Supervised Data Mining; Corporate Governance; Firm Performance; Board Meeting; Board Remuneration; Classification.
Scope of the Article: Classification