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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Main Authors: Babak Sohrabi, Iman Raeesi Vanani, Vahideh Ghanooni Shishone
Format: Article
Language:fas
Published: University of Tehran 2015-09-01
Series:تحقیقات مالی
Subjects:
Online Access:https://jfr.ut.ac.ir/article_57311_e47b9a6a26850fb9407b7cd94fe95f4e.pdf
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spelling doaj-cd126fe44bb2484c8172231bf7dd4f692020-11-25T02:27:39ZfasUniversity 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
collection DOAJ
language fas
format Article
sources DOAJ
author Babak Sohrabi
Iman Raeesi Vanani
Vahideh Ghanooni Shishone
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
author_facet Babak Sohrabi
Iman Raeesi Vanani
Vahideh Ghanooni Shishone
author_sort Babak Sohrabi
title 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_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_sort evaluating the corporate tax performance and analyzing the tax trends through the utilization of data mining algorithms
publisher University of Tehran
series تحقیقات مالی
issn 1024-8153
2423-5377
publishDate 2015-09-01
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.
topic taxation assessment
clustering
prediction
trend analysis
data mining
url https://jfr.ut.ac.ir/article_57311_e47b9a6a26850fb9407b7cd94fe95f4e.pdf
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AT imanraeesivanani evaluatingthecorporatetaxperformanceandanalyzingthetaxtrendsthroughtheutilizationofdataminingalgorithms
AT vahidehghanoonishishone evaluatingthecorporatetaxperformanceandanalyzingthetaxtrendsthroughtheutilizationofdataminingalgorithms
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