Predicting Information Quality Ranking with Factor Analysis and Artificial Intelligence Approach

This study examines the ranking of information quality ranking with the approach of factor analysis and artificial intelligence in companies listed on the Tehran Stock Exchange. The independent variable used in this research is the criteria of the management system and the dependent variable of this research is the criteria of accounting information quality, which based on factor analysis method, all criteria have been converted into a single variable. The present study is part of experimental accounting research and artificial intelligence method has been used to test the research hypotheses. The results indicate that according to the variable selection method of neighborhood analysis, among the variables of the management system, the percentage of institutional owners "," dual role of CEO "," CEO tenure "," management ownership "," government ownership "have the highest correlation with rank Other results of Jackie's research are that the linear and non-linear artificial intelligence method pls has a high ability to predict the quality rating of accounting information of companies listed on the Tehran Stock Exchange.