Journal of Tax Research
Year:2023 | Volume:34 | Issue:60|Papers Count:7

Organizations rely heavily on human capital to carry out their tasks and missions. The development of organizational capital requires educational planning and the use of educational models and methods that achieve maximum efficiency and effectiveness. What is of fundamental importance in this regard is the structures, conditions and characteristics of the organization that provide the possibility of successful implementation of educational programs and implementable models. The favorable structure and conditions lead to learning in the direction of the organizational mission and helps to improve the social culture of that society outside the organization. Today, in order to overcome today's turbulent and unstable environment, every organization is obliged to improve the capability of human resources in terms of knowledge, skills, attitude and strengthen continuous training and to plan, design and implement a long-term written program in order to overcome the challenges ahead. In a sense, it can be said that continuous education is the only way to survive and cope with challenges along with sustainable development and personal plans. The concept of continuous education has emerged in order to adapt to the fast and changing social and cultural life and has become an important indicator of the level of education and employment conditions in developed and developing countries. Another necessity to pay attention to continuous education lies in the nature of learning (forgetting in learning). This problem can be overcome by creating a continuous training and learning program. Continuous training transfers the responsibility from a system to an individual, according to which individuals are responsible for self-actualization and transformation in themselves. This transfer of the role of responsibility of continuous education leads to building a sustainable and coherent social future as well as equipping people to learn how to know, do, and play an essential role in life. In this research, the aspects of learning in the tax affairs organization will be investigated and analyzed in order to achieve a comprehensive and barrier model that will determine the status of continuous education in the tax affairs organization for us, and an introduction for future researches.

Considering the importance and role of tax in the economic cycle of the country, in this research we are looking for the design of the tax ecosystem model. The purpose of this research is to provide a model of antecedent and consequential factors of the value added tax ecosystem model, which causes the agility of the supply chain. This research is qualitative and basic in terms of its purpose. Also, according to the method of data collection, it is considered a type of field research. The statistical population of the research is university professors, employees of tax audit offices and senior managers of tax administration in the country. The data collection tool in this study was a semi-structured interview. In this research, theoretical sampling was used and the sample size was 10 people according to theoretical saturation. For the validation of the model, the fuzzy Delphi method was used, and in this section, 16 people were considered as a sample, and according to the results, the indicators identified in the qualitative section were confirmed. According to the results of the research, there are two categories of themes. The main themes were discovered. The first group includes the main themes that have been identified as antecedent or influencing factors on the creation of the VAT ecosystem, and the second group includes the main themes that have been identified as consequential or influencing factors. According to the results of the antecedent and consequent model of the tax ecosystem, factors such as the reduction of tax costs, the tax culture of self-disclosure and the reduction of tax evasion can be important consequences of planning the tax ecosystem.

In this research, the relationship between geographical location and income tax of companies listed on the Tehran Stock Exchange was examined. The impact of the distance index relative to the country center and the provincial center on corporate taxation was analyzed using systematic exclusion (screening) sampling method. Considering the specified conditions, a total of 132 companies were analyzed over a five-year period since 2018 to 2022 (573 company-years) and were analyzed using panel data and generalized least squares (EGLS) method. The results show that the relationship between the company's distance from the center of the country (Tehran) and the income tax, as well as the relationship between the provincial centers and the income tax, is inverse and significant. In other words, the greater the distance of the company from the center of the country and the center of the province, the lower the ratio of the company's fixed tax to their operating income. Also, in the survey of different industries that were tested separately in the industries of "pharmaceutical products, chemical products, machinery and electrical devices, tiles and ceramics, and automobiles and parts" both in terms of distance from the center of the country and distance from the center There is an inverse and significant relationship in the province, and there is a positive and significant relationship in the "basic metals" industry.

Entrepreneurship is interpreted as one of the axes of endogenous development, creating sustainable employment and strengthening economic foundations. Many institutional and economic factors influence the level and quality of entrepreneurship, the most important of which are the duties of the government and its support policies. Considering the importance of the subject and the investigation of the effectiveness of entrepreneurship from environmental variables, the current research is focused on investigating the effect of government performance and especially the effect of tax policies, government size and corruption on types of entrepreneurship (opportunity-oriented and necessity-oriented). In this research, using panel data estimation method with incomplete data, the effect of variables such as tax rate, corruption index and a wide range of government expenses on the development of entrepreneurship at two levels of necessity and opportunity-based has been tested. In this regard, the information of 33 countries was used between 2010 and 2018. The results show that increasing taxes in selected countries limits opportunity-oriented and necessity-oriented entrepreneurship. Government spending in the public sector has a positive effect on the growth of opportunity-based entrepreneurship. Public corruption has an adverse effect on opportunity-oriented entrepreneurship, while positive and significant effects on necessity-oriented entrepreneurship have been calculated. Also, indicators of the national per capita income level, human capital, credit amount to the private sector, business density, unemployment rate and labor force participation rate are other factors affecting the level and quality of entrepreneurship.

The present study predicts the effect of connecting the transaction of card readers to the tax affairs system on the increase in the collection of the tax affairs organization of West Azarbaijan province in 2022. The present study by forecasting the tax revenues of West Azarbaijan province based on the Data up to March 1400 has investigated this issue that if the tax revenues of West Azarbaijan province had the same trend as the previous years and the card readers was not connected The tax affairs system how much did this organization collect? . In fact, the difference between this forecast and its actual amount shows that by connecting the card readers to the tax affairs system, the collection amount of this organization has increased to what extent. For this purpose, the present study using the monthly data of the tax revenues of West Azarbaijan province during the years 2005 to 2022 and by applying three models of state space, Markov Switching and Arima models showed that the provincial tax based on the transaction performance of the card reader device has increased the percentage of realization of total tax revenues of West Azarbaijan province in 2022 by almost 32%. Also, the effect of this plan on increasing the percentage of corporate tax, personal income tax, wealth tax and indirect tax of West Azerbaijan province in 2022 was equal to 29, 11, 6 and 65% respectively. On the other hand, according to the forecast of the total tax revenues of West Azerbaijan province in 2023, It is expected that they will be realized Minimum 117 and maximum 130 percent of the approved income.

One of the most important issues in designing a tax on aggregate personal income is the specification of tax rates and brakets. The purpose of this[s1] study is to design the optimal framework of personal income tax in terms of tax rates and brakets and to evaluate its effects. In doing so, microsimulation model is used and required micro data were obtained using the Household Expenditure Survey of Iranian Statistics Center in 2017. [s2] The tax rates, income brackets, deductions, exemptions, and subsidies to low-income people have been determined in such a way that the best works are determined according to the [s3] gini coefficient and progressivity index, with the restriction of providing current amount of tax revenue for the government. The results show that by introducing the new personal income tax, while maintaining the government's tax revenues and paying a negative tax to the low-income, horizontal inequality (measured by the Gini coefficient) and vertical inequality (measured by the Progressivity Index) can be significantly improved.

By using artificial intelligence methods, tax evasion of legal entities which is a continuous concern of tax system, has been detected based on financial data recorded in financial transactions of collections. The phenomenon of tax evasion can be considered in the sense that it reduces the ratio of tax revenues to GDP while reducing government revenues and increasing the level of the tax gap. Since data mining technology has many predictive and classification capabilities, it can facilitate the decision-making process in financial matters. The different methods for transaction data modeling are based on matching labeled data and the reviews of legal taxpayers' files by tax experts, which are marked as tax/non-tax evasion cases. There are various methods for modeling on this method. With the increasing use of artificial intelligence modeling, this article, by using three modern methods of artificial intelligence, on the aforementioned data set, validates the use of these methods by using the parameters of accuracy, sensitivity, and precision, which determine the quality of the produced model from various aspects. It validates, the feasibility of using these models has also been done on local financial transaction data. Therefore, in this research, it has been tried to use artificial intelligence algorithms such as artificial neural network algorithms, support vector machine and artificial bee colony algorithm to detect tax evasion. The statistical population of the current research includes 3600 taxpayers in the studied years (2002-2012) of Tehran province. One of the new methods of financial data modeling is the use of hybrid methods, in which the combination of several artificial intelligence methods is used to increase the quality of the model. It is obvious that the combination of the mentioned methods has favorable results in some situations and may not be so in other situations. Therefore, in this article, this issue has been investigated in detail and the use of different methods and a combination of artificial intelligence methods has been discussed. Therefore, by using the combined algorithms in this research, we were able to with an accuracy of 85. 59%, For training data and accuracy of 83. 79% for test data, let's identify and classify taxpayers who are late in paying taxes and taxpayers who pay taxes on time. Therefore, according to the obtained results, we find that the proposed method in this research has a high ability to identify taxpayers who cheat on paying taxes. The use of artificial intelligence systems can be used as an economic stimulus in order to reduce tax evasion. In this regard, it is suggested to first form an integrated system as an economic data center, and this center will take on the responsibility of keeping the country's financial data safe. Then, a standard for the use of artificial intelligence and data mining of financial data should be developed. With this method of scientific and academic research, without providing sensitive data to outside the required organizations, it is possible to take a step forward from the scientific ability of experts regarding factors such as tax evasion detection, terrorism financing detection and money laundering in order to improve the country's economic system.