Designing a Model for Analyzing Structural Interpretation of Factors Affecting Income Tax Evasion of Legal Persons

Taxation is the transfer of a part of the company’s profits to the government. According to the representation theory and despite of the information asymmetry between taxpayers and the government, companies naturally try to evade tax payments. On the other hand, governments, due to the existing limitations, are trying to collect maximum taxes by identifying high-risk taxpayers in accordance with the laws and regulations, and researchers in this field are also seeking to identify the factors affecting income tax evasion of legal persons. The aim of this study is to identify and prioritize these factors. In this study, fuzzy screening technique and interpretive structural modeling (ISM) analysis were used to identify the criteria and express the relationships between the criteria, after studying the literature of related researches and interviewing experts in the field of tax evasion. After analyzing the data, the variables were classified in eight different levels and drawn according to the ISM graph relationships. After MICMAC analysis, variables were divided into three groups of independent or key variables, communication and dependent, and no variables were placed in the self-governing variables group. Determining the relationships between variables and types of variables can lead to the better understanding of the subject and making appropriate decisions in the issue of income tax evasion of legal persons.