Business, Marketing, and Finance Open

Strategic Analysis of Social Responsibility in the Iranian National Tax Administration: Institutional Alignment, Challenges, and Solutions

Ehsan Farahani iD , Seyed Hossein Kazemi ^* iD , Atefeh Zarei iD , Reza Taghvaei iD

In recent years, the Iranian National Tax Administration has sought to move beyond its traditional revenue-generation role and transform into a development-oriented institution with responsibilities in the economic, social, and environmental dimensions. Measures such as enhancing tax transparency, combating tax evasion, supporting vulnerable enterprises, promoting public education, and digitalizing administrative processes have been implemented; however, their effectiveness requires more systematic structuring and comprehensive evaluation. The organization's mission emphasizes tax justice and transparency, its vision focuses on intelligent transformation, and its core values are centered on accountability and trust-building, although these principles have not yet been fully institutionalized within its executive structure. The findings indicate that the concepts of social responsibility reflected in official organizational documents are aligned with the organization's macro-level objectives; nevertheless, gaps remain in their practical implementation. The key influencing factors include managerial commitment, performance indicators, employees' attitudes, and stakeholder engagement. Accordingly, strategies such as establishing a specialized social responsibility unit, designing social performance indicators, and strengthening education and stakeholder participation are proposed.

Design and Validation of a Model for the Development of Asset Management FinTechs in the Iranian Capital Market

Mohammadreza Navaeean iD , Mehdi Khoshnood ^* iD , Mojtaba Maleki Choobari iD

The present study aimed to design and validate a model for the development of asset management FinTechs in the Iranian capital market. Given the expansion of digital financial services, the growth of intelligent investment instruments, and the role of FinTechs in reducing transaction costs, increasing accessibility, and improving the quality of decision-making, the absence of an integrated framework compatible with the institutional, legal, technological, and behavioral characteristics of the Iranian capital market was identified as the principal research problem. In terms of purpose, the study was applied and developmental, and in terms of methodology, it employed an exploratory mixed-methods design. In the qualitative phase, purposive sampling was used to conduct 10 semi-structured interviews with managers and experts possessing specialized experience in the capital market and FinTech sectors. The data were analyzed through open, axial, and selective coding. In the quantitative phase, a researcher-developed questionnaire was distributed among 169 professionals and managers in the field, and the model was evaluated using the partial least squares approach. In addition, the opinions of 10 experts and the Analytical Hierarchy Process (AHP) and Interpretive Structural Modeling (ISM) techniques were used to prioritize the components and determine the hierarchical structure of the relationships. The qualitative findings revealed 33 categories across six dimensions: causal conditions, the central phenomenon, contextual conditions, intervening conditions, strategies, and consequences. Cronbach’s alpha coefficients for the constructs ranged from 0.780 to 0.910, while composite reliability values ranged from 0.846 to 0.931. The R² values for the central phenomenon, strategies, and consequences were 0.671, 0.700, and 0.509, respectively. In the AHP prioritization, consequences ranked first with a weight of 0.3641, followed by strategies and contextual conditions. The ISM results also placed causal conditions at the most fundamental level and consequences at the final level of the model. Accordingly, the sustainable development of WealthTech in Iran requires the simultaneous reform of the regulatory environment, data and technological infrastructures, financial literacy, public trust, innovation-support mechanisms, and the design of multifunctional platforms.

Generation Z and Audit Quality

Rasoul Pourfeizollah iD , Mahmood Samadi Largani ^* iD , Morteza Haji Abbasi iD , Mohammad Ali Nasimi iD

This study aimed to examine the effect of Generation Z on audit quality and to test an applied model incorporating technological empowerment, generational values and behaviors, organizational requirements, and risks and challenges. This applied, quantitative, descriptive-correlational study was conducted among 315 professionals working in audit firms, including Generation Z auditors, senior auditors and audit team managers, newly recruited auditing employees, and other practicing auditors. Data were collected using researcher-developed Generation Z and audit quality questionnaires based on themes extracted from the qualitative phase of the research. Construct validity was examined through exploratory factor analysis, while internal consistency was evaluated using Cronbach’s alpha, Guttman, and Spearman–Brown coefficients. The Kaiser–Meyer–Olkin index and Bartlett’s test were used to assess factorability. Because the study variables were non-normally distributed, the measurement and structural models were analyzed using partial least squares structural equation modeling in SmartPLS. Generation Z had a strong, positive, and statistically significant direct effect on audit quality (β = 0.824, t = 45.650, p < 0.001). Technological empowerment had the largest significant indirect effect on audit quality through Generation Z (β = 0.282, t = 22.546, p < 0.001), followed by generational values and behaviors (β = 0.252, t = 24.899, p < 0.001), risks and challenges (β = 0.216, t = 19.852, p < 0.001), and organizational requirements (β = 0.212, t = 17.559, p < 0.001). All factor loadings were statistically significant, composite reliability coefficients exceeded 0.85, average variance extracted values exceeded 0.50, and all Stone–Geisser Q² values were positive and above 0.25, indicating acceptable reliability, convergent validity, and predictive relevance. Generation Z constitutes an important determinant of audit quality, particularly when younger auditors are supported by appropriate technological infrastructure, organizational policies, professional development opportunities, and effective risk-management practices. Audit firms can improve audit outcomes by aligning managerial and technological systems with the characteristics and workplace expectations of Generation Z.

Determinants of Bank Risk-Taking: The Role of Regulation, Competition, and Financial Disclosure

Jinan Haleem Sharhan iD , Ezatollah Abbasian ^* iD , Islam Fakher iD

This study aimed to examine the determinants of risk-taking behavior among Iraqi commercial banks by assessing the effects of regulation, competition, financial disclosure, bank-specific characteristics, macroeconomic conditions, and institutional quality. This study employed a quantitative causal-explanatory design using a dynamic panel-data framework. The study population included licensed Iraqi commercial banks operating between the first quarter of 2010 and the fourth quarter of 2024. After data screening, the final unbalanced panel included 38 commercial banks and 2,036 bank-quarter observations. Bank-level data were extracted from audited quarterly financial statements, while regulatory and sector-level indicators were obtained from Central Bank of Iraq reports. Macroeconomic variables, including real GDP growth, inflation, exchange-rate volatility, and oil-price volatility, were collected from international databases. Institutional quality indicators were also incorporated. Data were analyzed using descriptive statistics, correlation analysis, static panel regressions, and dynamic System-Generalized Method of Moments estimation. Semi-structured expert interviews were used only to contextualize the quantitative findings. The inferential results showed that regulatory intensity had a significant negative effect on bank risk-taking in both static and dynamic models. Financial disclosure quality, capital adequacy, liquidity, profitability, and institutional quality also significantly reduced risk-taking. In contrast, banking competition pressure, bank size, inflation, exchange-rate volatility, and oil-price volatility significantly increased risk exposure. The dynamic System-GMM results confirmed strong persistence in bank risk-taking over time. Institutional quality significantly strengthened the risk-reducing effect of regulation, while financial disclosure significantly weakened the risk-enhancing effect of competition. Ownership-based robustness analysis indicated that privately owned banks were more sensitive to competition-driven risk, whereas foreign-affiliated banks benefited more strongly from disclosure discipline. The study concludes that bank risk-taking in Iraq is shaped by the interaction of regulatory enforcement, competitive pressure, disclosure transparency, internal financial resilience, institutional quality, and macroeconomic instability. Strengthening prudential regulation alone is insufficient unless accompanied by improved disclosure standards, stronger governance mechanisms, and more credible institutional enforcement.

Designing a Conceptual Model of the Impact of Signals Embedded in Fake News on the Cryptocurrency Market

Hamideh Tabatabaei iD , Seyed Mahmoud Reza Mortazavi ^* iD , Shadi Zabet iD

This study aimed to design a conceptual model of the impact of signals embedded in fake news on the cryptocurrency market. The research method was qualitative and was conducted using the Delphi technique in five rounds with the participation of five experts in the fields of media and business. The interview data were coded and analyzed using MAXQDA software, and seven main concepts were ultimately extracted: the legal status of cryptocurrency, cryptocurrency management strategies, factors affecting the cryptocurrency market, the type of impact of fake news on cryptocurrency, understanding the effects of signals in fake news, methods for detecting signals in fake news, and strategies for managing fake news, signals, and the cryptocurrency market. The findings showed that fake news, whether explicit or implicit, can lead to severe price fluctuations, reduced public trust, the growth of informal markets, and intensified instability. Accordingly, improving media literacy, formulating transparent regulations, using advanced technologies, and strengthening cooperation between public and private institutions are proposed as key strategies for managing these challenges. The results of this study can help policymakers and cryptocurrency market actors in Iran reduce the destructive effects of fake news through a comprehensive approach and benefit from the economic opportunities offered by this technology.

Examining the Effect of Sustainability and Corporate Social Responsibility Disclosure on Reporting Quality and Economic Sustainability in Companies Listed on the Tehran Stock Exchange

Hadi Ghasemi iD , Reza Ziari ^* iD

This study examines the effect of corporate social responsibility and corporate sustainability disclosure on financial reporting quality among companies listed on the Tehran Stock Exchange. The research sample consisted of 120 companies over the 2019–2024 period. Financial reporting quality was measured using the absolute value of discretionary accruals, and a fixed-effects panel data regression model was employed to test the hypotheses. The results indicated that corporate social responsibility and sustainability disclosure had a negative and statistically significant effect on discretionary accruals, meaning that a higher level of disclosure was associated with improved financial reporting quality. Sales growth, loss status, and firm age also had significant effects on financial reporting quality, whereas firm size, financial leverage, and return on assets were not statistically significant. Overall, the findings indicate that strengthening corporate social responsibility and sustainability disclosure can reduce earnings management and enhance financial reporting transparency.

Examination and Elucidation of the Dimensions of a Fair Fee-Determination Model in Islamic Banking

Hassan Tajik iD , Mohammad Saeed Panahi Boroujerdi ^* iD

The interest-free banking industry in Iran faces a serious challenge in determining service fees. Many current tariffs are based on historical practices and lack a clear relationship with actual costs and risks. This situation has reduced customer trust and is insufficiently consistent with the jurisprudential principles of justice and fairness. The present study aimed to design a computational model for determining fair fees in Islamic banking based on jurisprudential-economic foundations and to validate the model within Iran’s banking system. The study employed an exploratory sequential mixed-methods approach. In the qualitative phase, the jurisprudential constraints and economic criteria governing fees were extracted through interviews with 12 experts and a review of jurisprudential documents. In the quantitative phase, these findings were converted into operational variables and tested on selected services provided by Bank “A” using activity-based costing and the analytic hierarchy process. The results showed that a fair fee is determined, in the first stage, through a combination of full cost, customary profit, and legitimate risk and, in the second stage, by applying an ethical adjustment coefficient based on service necessity and the customer’s financial capacity. Application of the model to three sample services showed that the proposed fee for credit-related services was aligned with market tariffs, while the fee for basic services covered the bank’s actual costs. Sensitivity analysis confirmed that full cost had the greatest effect on the model. The jurisprudential assessment also confirmed the model’s conformity with the principles of the prohibition of usury, the no-harm rule, and fairness. The model provides a practical framework for achieving fee justice in Islamic banking.

Ranking the Factors Affecting Financial Flexibility Using Artificial Neural Networks and Machine Learning

Ebrahim Lotfinia iD , Vali Khodadadi ^* iD , Alireza Jorjor Zadeh iD , Saeed Nasiri iD

This study aimed to identify and rank the factors affecting the financial flexibility of companies listed on the Tehran Stock Exchange and Iran Fara Bourse using artificial neural network and XGBoost machine-learning models. This applied, quantitative, retrospective, and correlational study used longitudinal firm-level data from companies listed on the Tehran Stock Exchange and Iran Fara Bourse during 2020–2024. Following the application of the inclusion and exclusion criteria, 143 companies were selected through a census approach. Financial flexibility was assessed based on cash holdings and debt capacity. The predictors included default risk, political connections, market power, managerial ability, environmental uncertainty, managerial overconfidence, chief executive officer power, management turnover, and board financial expertise. After data screening and preprocessing, an artificial neural network and the XGBoost algorithm were trained and evaluated. Model performance was assessed using the coefficient of determination and root mean squared error, while variable importance and the direction of predictor effects were interpreted through normalized importance scores and SHAP values. Both algorithms successfully ranked the determinants of financial flexibility, although the artificial neural network demonstrated superior predictive performance. The neural network achieved an (R^2) of 0.499 and an RMSE of 0.179, whereas XGBoost produced an (R^2) of 0.413 and an RMSE of 0.194. Default risk was the most influential predictor in both models, and lower default risk was associated with greater predicted financial flexibility. In the neural network, managerial ability, market power, political connections, and environmental uncertainty followed default risk in importance. In XGBoost, political connections, environmental uncertainty, managerial ability, and market power received the next highest rankings. Managerial overconfidence had moderate importance, whereas chief executive officer power, management turnover, and board financial expertise made comparatively limited predictive contributions. Training and validation errors converged satisfactorily, indicating acceptable model stability and no severe overfitting. Financial flexibility is primarily determined by credit quality, managerial competence, competitive position, institutional access, and environmental conditions, and artificial neural networks provide a more accurate framework than XGBoost for predicting and ranking these nonlinear determinants.

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The Impact of Blockchain on Corporate Financial Reporting Based on Iranian Reporting Standards and IFRS

The Threshold Effect of Oil Rent on Non-Oil Economic Growth in Light of Financial Development: A Case Study of Iraq

Empirical and Comparative Analysis of the Efficiency of Nonlinear Option Pricing Models (Quantum-Based and Heston) and Conventional Linear Models (Black–Scholes and Binomial Tree) in the Tehran Stock Exchange

The Role of Behavioral Empowerment and Smart Technologies in Enhancing Investor Decision-Making and Portfolio Optimization in the Iranian Capital Market

Designing a Model to Explain the Role of Customer Knowledge Management Strategy in Achieving Competitive Advantage in Iraq's Electronic Banking Sector

The Role of Blockchain Technology in the Development of Accounting in Iran

Providing and Validating a Systemic Risk Model in the Tehran and Iraq Stock Exchanges

Examining Audit Strategies Affecting the Quality of Financial Reporting

The Impact of Behavioral, Demographic, Financial Self-Efficacy, and Investors’ Longevity Preferences on Their Decision-Making

Analyzing the Moderating Role of Corporate Reputation in the Relationship between Managerial Ownership and Voluntary Disclosure in Leveraged and Capital-Based Firms

The Impact of Oil Shocks on Business Cycles and Structural Inflation in Iran: An SVAR Approach

Analysis of the Effect of Energy Price Volatility on the Export Competitiveness of Iranian Industries

Identifying the Factors Influencing the Development of Medical Tourism from a Marketing Mix Perspective in Gilan Province

Designing a Model and Ranking the Digital Transformation Components Affecting the Quality of Accounting Information in Iran’s Capital Market: A Fuzzy Delphi Approach

The Role of Earnings Quality and Future Returns: A Rational Decision-Making Simulation Approach

Identification and Analysis of Barriers to the Realization of Synergy Between the Supreme Audit Court of Iran and Internal Auditing in the National Iranian South Oil Company

Presenting a Predictive Model of Stock and Over-the-Counter Market Price Indices Based on Macroeconomic Indicators Using Artificial Neural Networks

Econometric Analysis of the Effects of Dividend Policy Changes on the Implied Cost of Equity Capital under Different Levels of Return on Assets

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