Evaluating the Corporate Tax Performance and Analyzing the Tax Trends through the Utilization of Data Mining Algorithms
There is always a considerable difference between the corporate performance and the tax levy that is identified by the taxation authorities which has become a common practice. This fact has led to no fairness among taxpayers, a fact that influences the horizontal and vertical sides of equity. Horizo...
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| Format: | Article |
| Language: | fas |
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University of Tehran
2015-09-01
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| Series: | تحقیقات مالی |
| Subjects: | |
| Online Access: | https://jfr.ut.ac.ir/article_57311_e47b9a6a26850fb9407b7cd94fe95f4e.pdf |
| _version_ | 1819144741874302976 |
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| author | Babak Sohrabi Iman Raeesi Vanani Vahideh Ghanooni Shishone |
| author_facet | Babak Sohrabi Iman Raeesi Vanani Vahideh Ghanooni Shishone |
| author_sort | Babak Sohrabi |
| collection | DOAJ |
| description | There is always a considerable difference between the corporate performance and the tax levy that is identified by the taxation authorities which has become a common practice. This fact has led to no fairness among taxpayers, a fact that influences the horizontal and vertical sides of equity. Horizontal equity is created when people feel the benefits of the tax gain that is proportional to the loss of benefits. People with more financial means should also pay more taxes that is equivalent to vertical equity. One reason for the difficulty of attaining the horizontal and vertical equities is to identify the taxpayers based on their previous taxation behavior and to deal with them effectively. The aim of this study is the design of a predictive system that evaluates the corporates taxation behavior based on their previous payments. The predicting system uses key performance variables that are identified during research and it will also help in the classification of companies based on their taxation behavior into three groups of high risk, medium risk and low risk. The system is specifically designed for the taxation authorities who are attempting to effectively assessing the risk of corporate taxes gaining. In this study, the taxation clusters of customers are identified and a decision tree is designed with 80% of accuracy by the utilization of clustering and classification algorithms and effective validation methods. The resulting models of applied algorithms investigate the taxation behavior of each customer and are capable of predicting the tax payment risk of taxpayers in the future with the addition of new corporates to the list. |
| first_indexed | 2024-12-22T12:46:58Z |
| format | Article |
| id | doaj.art-cd126fe44bb2484c8172231bf7dd4f69 |
| institution | Directory Open Access Journal |
| issn | 1024-8153 2423-5377 |
| language | fas |
| last_indexed | 2024-12-22T12:46:58Z |
| publishDate | 2015-09-01 |
| publisher | University of Tehran |
| record_format | Article |
| series | تحقیقات مالی |
| spelling | doaj.art-cd126fe44bb2484c8172231bf7dd4f692022-12-21T18:25:18ZfasUniversity of Tehranتحقیقات مالی1024-81532423-53772015-09-0117221923810.22059/jfr.2015.5731157311Evaluating the Corporate Tax Performance and Analyzing the Tax Trends through the Utilization of Data Mining AlgorithmsBabak Sohrabi0Iman Raeesi Vanani1Vahideh Ghanooni Shishone2استاد گروه مدیریت فناوری اطلاعات، دانشکدة مدیریت، دانشگاه تهران، تهران، ایراناستادیار گروه مدیریت صنعتی، دانشکدة مدیریت و حسابداری، دانشگاه علامه طباطبایی، تهران، ایراندانشجوی کارشناسی‌ارشد رشتة مدیریت فناوری اطلاعات، دانشکدة مدیریت و حسابداری، دانشگاه تهران، تهران، ایرانThere is always a considerable difference between the corporate performance and the tax levy that is identified by the taxation authorities which has become a common practice. This fact has led to no fairness among taxpayers, a fact that influences the horizontal and vertical sides of equity. Horizontal equity is created when people feel the benefits of the tax gain that is proportional to the loss of benefits. People with more financial means should also pay more taxes that is equivalent to vertical equity. One reason for the difficulty of attaining the horizontal and vertical equities is to identify the taxpayers based on their previous taxation behavior and to deal with them effectively. The aim of this study is the design of a predictive system that evaluates the corporates taxation behavior based on their previous payments. The predicting system uses key performance variables that are identified during research and it will also help in the classification of companies based on their taxation behavior into three groups of high risk, medium risk and low risk. The system is specifically designed for the taxation authorities who are attempting to effectively assessing the risk of corporate taxes gaining. In this study, the taxation clusters of customers are identified and a decision tree is designed with 80% of accuracy by the utilization of clustering and classification algorithms and effective validation methods. The resulting models of applied algorithms investigate the taxation behavior of each customer and are capable of predicting the tax payment risk of taxpayers in the future with the addition of new corporates to the list.https://jfr.ut.ac.ir/article_57311_e47b9a6a26850fb9407b7cd94fe95f4e.pdftaxation assessmentclusteringpredictiontrend analysisdata mining |
| spellingShingle | Babak Sohrabi Iman Raeesi Vanani Vahideh Ghanooni Shishone Evaluating the Corporate Tax Performance and Analyzing the Tax Trends through the Utilization of Data Mining Algorithms تحقیقات مالی taxation assessment clustering prediction trend analysis data mining |
| title | Evaluating the Corporate Tax Performance and Analyzing the Tax Trends through the Utilization of Data Mining Algorithms |
| title_full | Evaluating the Corporate Tax Performance and Analyzing the Tax Trends through the Utilization of Data Mining Algorithms |
| title_fullStr | Evaluating the Corporate Tax Performance and Analyzing the Tax Trends through the Utilization of Data Mining Algorithms |
| title_full_unstemmed | Evaluating the Corporate Tax Performance and Analyzing the Tax Trends through the Utilization of Data Mining Algorithms |
| title_short | Evaluating the Corporate Tax Performance and Analyzing the Tax Trends through the Utilization of Data Mining Algorithms |
| title_sort | evaluating the corporate tax performance and analyzing the tax trends through the utilization of data mining algorithms |
| topic | taxation assessment clustering prediction trend analysis data mining |
| url | https://jfr.ut.ac.ir/article_57311_e47b9a6a26850fb9407b7cd94fe95f4e.pdf |
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