ﭘﯿﺶﺑﯿﻨﯽ رﺗﺒﻪ ﺑﻨﺪي ﮐﯿﻔﯿﺖ اﻃﻼﻋﺎت ﺑﺎ روﯾﮑﺮد ﺗﺤﻠﯿﻞ ﻋﺎﻣﻠﯽ و ﻫﻮش ﻣﺼﻨﻮﻋﯽ

Predicting Information Quality Ranking with Factor Analysis and Artificial Intelligence Approach

از آﻧﺠﺎﯾﯽ ﮐﻪ ﺳﻬﺎﻣﺪاران، ﺳﺮﻣﺎﯾﻪﮔﺬاران، اﻋﺘﺒﺎردﻫﻨﺪﮔﺎن و ﺳﺎﯾﺮ اﺳﺘﻔﺎدهﮐﻨﻨﺪﮔﺎن از ﺻﻮرتﻫﺎي ﻣﺎﻟﯽ ﺑﺮاي ﻣﻘﺎﺻﺪ ﺗﺼﻤﯿﻢﮔﯿﺮي از اﻃﻼﻋﺎت دروﻧﯽ ﺷﺮﮐﺖ آﮔﺎﻫﯽ ﮐﺎﻓﯽ ﻧﺪارﻧﺪ و ﻫﻤﻮاره ﺑﻪ دﻧﺒﺎل ﮐﺴﺐ اﻃﻼﻋﺎﺗﯽ ﺑﺮاي ارزﯾﺎﺑﯽ ﻋﻤﻠﮑﺮد و رﯾﺴﮏ ﺳﻨﺠﯽ ﺷﺮﮐﺖﻫﺎي ﻣﻮرد ﻧﻈﺮ ﺧﻮد ﻣﯽﺑﺎﺷﻨﺪ ﺗﺎ ﺑﺘﻮاﻧﻨﺪ در آﻧﻬﺎ ﺳﺮﻣﺎﯾﻪﮔﺬاري ﮐﻨﻨﺪ، ﻟﺬا ﮐﯿﻔﯿﺖ اﻃﻼﻋﺎت ﺣﺴﺎﺑﺪاري ﮐﻪ ﺷﺮﮐﺖ ﻫﺎ اﻓﺸﺎ ﻣﯽ ﻧﻤﺎﯾﻨﺪ ﺟﻬﺖ ﺗﺼﻤﯿﻢ ﮔﯿﺮي آن ﻫﺎ داراي اﻫﻤﯿﺖ ﻣﯽ ﺑﺎﺷﺪ. اﯾﻦ ﭘﮋوﻫﺶ ﭘﯿﺶ ﺑﯿﻨﯽ رﺗﺒﻪ ﺑﻨﺪي ﮐﯿﻔﯿﺖ اﻃﻼﻋﺎت ﺑﺎ روﯾﮑﺮد ﺗﺤﻠﯿﻞ ﻋﺎﻣﻠﯽ و ﻫﻮش ﻣﺼﻨﻮﻋﯽ در ﺷﺮﮐﺖ ﻫﺎي ﭘﺬﯾﺮﻓﺘﻪ ﺷﺪه در ﺑﻮرس اوراق ﺑﻬﺎدار ﺗﻬﺮان را ﻣﻮرد ﺑﺮرﺳﯽ ﻗﺮار ﻣﯽ دﻫﺪ. ﻣﺘﻐﯿﺮ ﻣﺴﺘﻘﻞ اﺳﺘﻔﺎده ﺷﺪه در اﯾﻦ ﭘﮋوﻫﺶ، ﻣﻌﯿﺎرﻫﺎي ﻧﻈﺎم راﻫﺒﺮي ﻣﯽ ﺑﺎﺷﺪ و ﻣﺘﻐﯿﺮ واﺑﺴﺘﻪ، ﻣﻌﯿﺎرﻫﺎي ﮐﯿﻔﯿﺖ اﻃﻼﻋﺎت ﺣﺴﺎﺑﺪاري اﺳﺖ ﮐﻪ ﺑﺮ اﺳﺎس روش ﺗﺤﻠﯿﻞ ﻋﺎﻣﻠﯽ ﺗﻤﺎم ﻣﻌﯿﺎرﻫﺎ ﺑﺼﻮرت ﯾﮏ ﻣﺘﻐﯿﺮ واﺣﺪ ﺗﺒﺪﯾﻞ ﺷﺪه اﺳﺖ. ﭘﮋوﻫﺶ ﺣﺎﺿﺮ ﺟﺰ ﺗﺤﻘﯿﻘﺎت ﺗﺠﺮﺑﯽ ﺣﺴﺎﺑﺪاري ﺑﻮده و ﺟﻬﺖ آزﻣﻮن ﻓﺮﺿﯿﻪﻫﺎي ﭘﮋوﻫﺶ از روش ﻫﻮش ﻣﺼﻨﻮﻋﯽ اﺳﺘﻔﺎده ﺷﺪه اﺳﺖ. ﻧﺘﺎﯾﺞ ﭘﮋوﻫﺶ ﺣﺎﮐﯽ از آن اﺳﺖ ﮐﻪ ﻃﺒﻖ روش ﻣﺘﻐﯿﺮ ﮔﺰﯾﻨﯽ ﻫﻮش ﻣﺼﻨﻮﻋﯽ آﻧﺎﻟﯿﺰ ﻫﻤﺴﺎﯾﮕﯽ از ﺑﯿﻦ ﻣﺘﻐﯿﺮﻫﺎي ﻧﻈﺎم راﻫﺒﺮي درﺻﺪ ﻣﺎﻟﮑﺎن ﻧﻬﺎدي"، ﻧﻘﺶ دوﮔﺎﻧﻪ ﻣﺪﯾﺮﻋﺎﻣﻞ"، دوره ﺗﺼﺪي ﻣﺪﯾﺮﻋﺎﻣﻞ"، ﻣﺎﻟﮑﯿﺖ ﻣﺪﯾﺮﯾﺖ" و ﻣﺎﻟﮑﯿﺖ دوﻟﺘﯽ" ﺑﺎﻻﺗﺮﯾﻦ ﻫﻤﺒﺴﺘﮕﯽ را ﺑﺎ رﺗﺒﻪ ﮐﯿﻔﯿﺖ اﻃﻼﻋﺎت دارﻧﺪ. ﺳﺎﯾﺮ ﻧﺘﺎﯾﺞ ﺗﺤﻘﯿﻖ ﺣﺎﮐﯽ از اﯾﻦ اﺳﺖ ﮐﻪ روش ﻫﻮش ﻣﺼﻨﻮﻋﯽ ﺧﻄﯽ و ﻏﯿﺮ ﺧﻄﯽ ﺗﻮاﻧﺎﯾﯽ ﺑﺎﻻﯾﯽ در ﭘﯿﺶ ﺑﯿﻨﯽ رﺗﺒﻪ ﮐﯿﻔﯿﺖ اﻃﻼﻋﺎت ﺣﺴﺎﺑﺪاري ﺷﺮﮐﺖﻫﺎي ﭘﺬﯾﺮﻓﺘﻪ ﺷﺪه در ﺑﻮرس اوراق ﺑﻬﺎدار ﺗﻬﺮان را دارﻧﺪ.

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.