a mathematical model for measuring corporate governance using multi-criteria decision making (mcdm)technique

There has not been presented any comprehensive index for corporate governance despite its crucial role in resolution and responsiveness. although diverse methods have been sought for measuring corporate governance in previous studies, this study proposes a comprehensive index for measuring corporate governance, taking other indexes into account through mathematical equations. to test and measure the functionality of the designed model, a set of data related to 149 firms from 2014 to 2019 has also been jointly used. to achieve this, a questionnaire is created and distributed to experts to gather their opinions on the weight and significance of the criteria for measuring the corporate governance of the firm. the weight and significance of the criteria are determined using the shannon entropy method, a multi-criteria decision model. additionally, a confirmatory factorial analysis is conducted to measure the changeable hidden relationship in the corporate governance study, based on the measurement items. the results indicate that the proposed model serves as a suitable index for corporate governance. this mixed index includes criteria such as the size, independence, meetings, and education of the board of directors; the ceo's permanence; the size, independence, financial speciality, financial experience, tenure, and meetings of the auditorship committee; ownership concentration; organizational ownership; govern mental ownership; deals with dependent persons; the quality of disclosure; proper information; and weaknesses in internal controls. among these criteria, the quality of disclosure and proper information hold the most paramount significance and the highest weight, while the meetings of the board of directors have the least importance and weight.