The impact of priority issues for publicly traded companies in corporate governance (CG) rating notes: an empirical study in Turkey.

Purpose: This paper aims to determine priority issues in the corporate governance (CG) principles to increase CG rating notes of publicly traded companies. Design/methodology/approach: This study defines the priority issues for publicly traded companies that should be focused to increase the CG rating notes. In this context, this study considers the companies in Borsa Istanbul CG index (XKURY), use data for 2018, 2019, 2020, and applies machine learning algorithms. Findings: Overall, importance of each CG principle changes for the CG rating notes; first five CG principles in terms of significance have a total of 43.6% importance for the CG rating notes; following a straight-line approach in completing deficiencies of the CG principles cannot help increase the CG rating notes. Hence, empirical results highlight the impact of the most significant CG principles in terms of the CG rating notes that should be focused on by publicly traded companies so that CG ratings can be increased. Research limitations/implications: This study uses Turkey data and considers publicly traded companies in the XKURY index. The main cause of this condition is that consolidated data of compliance report format for all publicly traded companies cannot be obtained. Practical implications: The publicly traded companies can increase the CG rating notes by considering the results of this study while focusing on priority issues in the CG principles. Social implications: The study determines the most important CG principles that companies can focus on, highlights the importance of usage of machine learning algorithms in determining the most influential CG principles in terms of the CG rating notes and reflects on the difficulties for gathering consolidated CG principles compliance reporting data for all publicly traded companies. Hence, societies can have better companies that are ruled more efficiently and corporately by increasing their compliance with the CG principles. Originality/value: To the best of the authors' knowledge, this is the first empirical study that determines the priority issues to increase the CG rating notes of publicly traded companies based on the new CG principles compliance reporting scheme in Turkey. Following this aim, machine learning algorithms, which can present better results with regard to most of the econometric models, are used in this study. [ABSTRACT FROM AUTHOR]