مطالب

Escalating urban heat island effects and rising energy demands in Iran's hot, dry climate pose a serious challenge for educational buildings, where high occupant density intensifies cooling needs and operational costs. This research addresses the urgency of adopting cool roof technologies—such as reflective coatings, green roofs, high-albedo materials, and radiative cooling roofs—to mitigate extreme indoor temperatures, reduce carbon footprints, and enhance student and staff well-being. Drawing on empirical data, simulation models, and a comprehensive literature review, we employ a weighted-scoring framework that evaluates each technology's thermal performance, energy savings, cost factors, durability, and environmental impact. Findings reveal that while radiative cooling roofs offer the greatest potential for reducing cooling loads (up to 30–40%) and maintaining comfortable indoor temperatures, they demand more advanced materials and higher initial investment. Green roofs yield substantial insulation and environmental benefits, but are limited by water scarcity and elevated setup costs. Conversely, reflective coatings and high-albedo materials strike a balance between effectiveness and affordability, making them viable for retrofits in budget-constrained educational facilities. The results underscore the need for context-specific solutions that consider local climate, water resources, building typology, and policy incentives. By clarifying the strengths and trade-offs of each cool roof approach, this study provides actionable guidance for architects, policymakers, and school administrators seeking sustainable and cost-effective interventions. Future research should focus on long-term performance monitoring, integrating complementary passive strategies (e.g., shading, natural ventilation), and developing localized materials tailored to resource-limited contexts.

The purpose of this research is to investigate the impact of tax avoidance on investment efficiency with emphasis on the role of institutional ownership and managerial ownership. Tax avoidance can be used as internal source of financing to enable financially distressed companies to access valuable investments with savings from tax avoidance. For this, a sample of 152 companies was selected from the companies listed in the Tehran Stock Exchange and by collecting data related to the research during the years of 2015 to 2022. The data related to the research variables for a period of 8 years were collected from reliable statistical databases. The hypotheses inspired by the title of the research were estimated according to the Chow test and the Hausman test using related statistical methods. The result of the first hypothesis indicates the existence of a significant and positive relationship between tax avoidance and investment efficiency. Also, the result of the second hypothesis showed that there is a direct and significant relationship between tax avoidance in companies with institutional ownership and investment efficiency. While the result of the third hypothesis showed that there is no significant relationship between tax avoidance in companies with managerial ownership and investment efficiency.

The equitable distribution of income is considered as a development indicator in countries. Thus it is required to identify factors impacting the equitable distribution of income to make suitable policies to improve it. The present study aims to determine the optimal inflation rate in order to minimize income inequality by using the dynamic stochastic general equilibrium (DSGE) method in Iran during 1997-2017. The results revealed the optimal inflation rate to be 3.74%. An increase or reduction in the optimal inflation rate of 3.74% enhances income inequality. Thus, the government should target the inflation rate in its policies to achieve minimum inequality. Hence, inequality fluctuations (rises and declines) will be probable.

Financial resilience in businesses refers to their ability to withstand economic shocks and challenges while maintaining financial stability under difficult conditions. This study adopts an applied research approach with both descriptive and prescriptive future-oriented methods. It is qualitative research that uses Causal Layered Analysis (CLA) to identify financial resilience in entrepreneurial businesses. To achieve a deep understanding of causal layers, scenarios are developed based on the global business network perspective. Two rounds of interviews were conducted with 35 experts, both structured and unstructured, to extract financial resilience indicators in Iranian entrepreneurial businesses. From the literature review and expert interviews, 35 factors were identified. Two factors, enthusiasm and fear of failure, were eliminated, resulting in 33 final factors. The matrix of financial resilience scenarios for entrepreneurial businesses was presented in four scenarios: economic crisis, economic boom, old technology, and new technology. Subsequently, SWOT analysis was used to analyze and propose strategies aimed at directing towards the third scenario. The findings indicate that utilizing the CLA approach aims to offer a plan in the field of financial resilience for entrepreneurial businesses. This helps planners to set aside current thinking and consider possible and probable futures, which may not necessarily be a continuation of past trends, to achieve a long-term plan to enhance financial resilience in entrepreneurial businesses.

Given the increasing prevalence of online learning and the absence of a validated instrument for assessing the critical writing skills of Iranian EFL learners in Computer-Mediated Communication (CMC) contexts, this study aimed to develop and validate an analytic rubric to enhance critical writing in CMC environments. The participants were 236 EFL students and 10 EFL/ESL teachers, representing a diverse range of demographics, experiences, and qualifications. The rubric development process was guided by a comprehensive literature review, the administration of a critical thinking questionnaire, expert feedback, thematic analysis of semi-structured interviews, integration of Paul and Elder’s (2019) Intellectual Standards, and the development and application of a Likert-scale critical writing questionnaire. Subsequent pilot testing facilitated refinements based on feedback. Accordingly, the finalized analytic rubric featured four principal components: (1) Clarity, Accuracy, and Precision (CAP); (2) Relevance and Logic (RL); (3) Depth and Significance (DS); and (4) Breadth and Fairness (BF). A rigorous validation process, including expert evaluation, factor analysis, and structural equation modeling (SEM), confirmed the rubric's reliability and validity. The findings demonstrated satisfactory internal consistency, as well as convergent and discriminant validity. This study offers valuable pedagogical implications for English as a Foreign Language (EFL) teachers, learners, researchers, and curriculum developers.

Taxes serve as a vital source of funding for governments and significantly influence economic growth and income distribution, which varies based on a country's level of development and economic framework. Recently, researchers have introduced methods to identify effective factors in preventing tax evasion. Most of these methods rely on basic techniques such as regression, structural equations, and non-intelligent methods that cannot effectively analyze the relationship between the values of the variables involved in this field. Therefore, in this study, we introduce a method that leverages artificial intelligence techniques, specifically a meta-heuristic optimization approach and a perceptron neural network. This method effectively analyzes the nonlinear relationships within the data while addressing both the intrinsic and extrinsic aspects of the data dimensions simultaneously. The research sample consists of 25 experts from the Tax Affairs Organization, and the study was conducted in the year 2022. The results indicate a high prediction accuracy of approximately 98%. Additionally, it highlights the significant role of various factors contributing to tax evasion, including income concealment, money laundering, economic crises, political trust, the weaknesses, and complexities of tax laws and regulations, inadequate clarification of tax laws, contradictions in legal tax articles, administrative bureaucracy, and an inefficient tax structure.

Tax fraud is the legal minimization of tax liability through appropriate financial planning techniques, which often involve techniques, accounting methods, and fraudulent transactions, and pursue little or no purpose other than creating a tax advantage. There is no doubt that tax fraud is a legal way to reduce the amount of tax, and individuals with different personality traits can take dissimilar procedures to reduce the amount of tax. In this study, the impact of personality traits on tax fraud concerning gender (male and female) and type of firm (listed and non-listed) is investigated. The statistical population of the study includes all financial managers of listed and non-listed firms in 2020 who are not exempt from taxes. Information about personality traits was collected through a questionnaire and SPSS software version 21 was used to test the hypotheses. The results suggest that the personality traits of neuroticism, extraversion, flexibility (openness to experience), and agreement have a positive and significant effect on tax fraud. In contrast, the personality trait of conscientiousness has a negative effect on tax fraud. This effect was also observed in both male and female financial managers. The results also indicate that the effect of personality traits of neuroticism, extraversion, and agreement on tax fraud in the managers of listed firms is positive and the effect of personality traits of flexibility (openness to experience) and conscientious is negative on tax fraud, but the effect of personality trait of neuroticism is negative and the effect of flexibility (openness to experience) on tax fraud in listed firms is not statistically significant. In non-stock firms, personality traits of neuroticism, extraversion, flexibility (openness to experience), and agreement have a positive and significant effect on tax fraud, and the personality trait of conscientiousness has a negative effect on tax fraud.

Systemic risk is a type of financial instability that disrupts the functioning of the financial system and affects economic growth. The present study was developed with the aim of presenting a systemic risk warning model based on the entropy criterion in the financial markets of Iran. In terms of direction, the present research is of applied type and in terms of explanatory purpose, and the data collection method is library method. The statistical population of the country's financial markets research includes the capital market, money market, etc., and the time frame of this research is the data related to variables affecting systemic risk in the years 1998 to 2022. In this research, firstly, the identified criteria and indicators affecting systemic risk were ranked using Shannon entropy, Rennie entropy, and Tsallis entropy, and then systemic risk was measured with the MES criterion. The results of this research show that the most systemic risk is caused by the variable of banks' debt to the central bank, and the two variables of government debt and the ratio of government debt to GDP also have the highest systemic risk. According to the general theory of systems and the effectiveness and influence of financial markets on each other, the government and policy makers of the economic and financial sectors must take the necessary measures in order to create a systemic supervisory institution.

The main goal of this article is to Investigating Factors Affecting the Financial Wealth of Insurance Companies in Iran. The method of this article is descriptive in terms of practical purpose and library data collection method. The data collection tool in this article was a standard questionnaire that was adapted from Masoumi et al.'s questionnaire and model. The statistical population of the research is all the experts in the country's insurance industry. The results of this article showed that the country's insurance industry experts, including university professors and senior managers of Iran Insurance Company, agree with these four main risks in the Financial Wealth model . However, these four main risks are not enough for the model of Financial Wealth . In the final, the optimal pattern of financial wealth in the Iranian insurance company includes four main pillars, which include 6 basic and general contain asset/liability mismatch risk, reinvestment risk, exchange rate risk, international market risk, life insurance account separation risk from non-life insurance account, life insurance account investment risk risks in the insurance industry each of the basic and general risks of the insurance industry also has several risks and sub-categories.

Resource management is a part of project management and its ultimate goal is to achieve maximum efficiency with the lowest level of inventory. Resource management is built around optimization and increased efficiency. In this paper, inventory optimization is done using fuzzy approach and statistical averaging methods are used to solve fuzzy multi-objective linear programming problems. These methods have been used to form a goal function of fuzzy multi-objective linear programming problems. First, in order to optimize inventory and find the weight of each product in Isfahan Steel Company, a model of fuzzy multi-objective linear programming problem is estimated. The highest weight of products is related to commodity ingots and the lowest weight related to other products. The Fuzzy Multi-Objective Linear Programming Estimation Model has compared the statistical methods with the Chondrasen method. The results show that this method has the capacity to optimize the amount of inventory, reduce storage costs and reduce interest costs due to working capital.