Financial and Banking Strategic Studies

Abstract This study examines the effects of market principles and behavioral biases on shareholders’ investment decisions, considering the moderating role of uncertainty in companies listed on the Tehran Stock Exchange.
Research Methodology:
This applied study adopts a descriptive research design. Data were collected from 295 financial analysts and active individual investors, with a focus on shareholders residing in Mashhad, during 2025–2026, using a standardized questionnaire. The data were analyzed using structural equation modeling and SPSS and PLS software.
Findings:
The results indicate that market principles have a significant negative effect on investment decisions, whereas behavioral biases have a significant positive effect. Uncertainty also plays a moderating role in the relationships among the research variables. The findings highlight the importance of psychological factors alongside rational market principles in investors’ decision-making.
Originality/Value:
The study contributes by simultaneously examining rational and behavioral factors and the moderating role of uncertainty in investment decisions in the Tehran Stock Exchange.

Abstract Purpose: Today, some scholars believe that exchange rate volatility may reduce the arrival of tourists. Therefore, the purpose of this study was to investigate the effect of exchange rate volatility on the tourism flow in the Iranian economy during the period from the first quarter of 2000 to the fourth quarter of 2020. Methodology: In most past surveys, the standard deviation of the moving average of the exchange rate logarithm has been used as a criterion for calculating exchange rate volatility; in this research, a new criterion was used to assess exchange rate volatility. The research method is based on cointegration theory, including correcting the error in the exchange rate volatility criteria using the ARDL econometric model for cointegration. Findings: The results showed: 1) in addition to the attractions of visiting countries as expected, the ratio of GDP per capita to relative proportions has a positive and significant impact on the flow of tourism, 2) relative prices in most cases are negative and meaningful, meaning that the relative price level between the country of origin and destination has a significant and negative effect, and 3) the exchange rate volatility affect the flow of tourism and the arrival of tourists. Originality/Value: Exchange rate fluctuations have a negative and significant effect on the arrival of foreign tourists to Iran. Therefore, it is necessary for policymakers to consider this category when designing their policy measures. Although, in recent years, with the rise in the exchange rate, the arrival of a significant number of foreign tourists to Iran is expected to increase, the rise in inflation has eroded the advantage of cheap travel to Iran.

Abstract Purpose: The rapid pace of technological change has led to greater use of artificial intelligence and prompted various industries to pay special attention to this emerging phenomenon to advance their goals, improve quality, and reduce costs. The banking industry is working to improve service quality and enhance customer satisfaction by leveraging artificial intelligence alongside other industries. This research presents an overview of the applications, current situation, and future scenarios of using artificial intelligence in the banking industry of Iran in the horizon of 2030.
Methodology: First, by conducting library studies on the application of artificial intelligence in statistical banking, and in the next step, by using the targeting method, 24 experienced banking experts were selected and, through unstructured (in-depth) interviews, and by using the Max Quda software, the current state of the application of sample intelligence was assessed. Artificial intelligence in banking was identified and analyzed, and, based on expert opinion and the GBN method, future scenarios for its application in the banking industry were drawn for the horizon of 2030.
Findings: According to the findings, currently, three processes: security and fraud prevention, credit risk, and identification of money laundering and terrorism financing activities are making use of artificial intelligence, and are most used in the field of security and fraud prevention. Also, based on the two main uncertainties, the international activity of the bank and the support of senior managers, four scenarios of authoritative influence, forced success, growth in confinement, and silent death were written as future scenarios of the application of artificial intelligence in the banking industry in the horizon of 2030.
Originality/Value: In this research, while identifying the application of artificial intelligence in the banking industry, the current state of its application was investigated, and the future of its application in Iran's banking industry was outlined for the horizon of 2030.

Abstract Purpose: This study examines the impact of predictor variables, including Information and Communications Technology (ICT) infrastructure, the level of interoperability in banking systems, human resources, financial resources, and policies and regulations, on the development of big data infrastructure within the Iranian banking system. Methodology: Data were collected using a Likert-scale questionnaire administered to 104 employees from Meli, Saderat, Mellat, Tejarat, and Sepah banks in the Hamedan province. Findings: Correlation tests revealed that all predictor variables are positively and significantly related to big data infrastructure. Multiple regression analysis further indicated that these factors explain approximately 56% of the variation in big data infrastructure (R² = 0.560). Additionally, the instrument's reliability was confirmed, with Cronbach's alpha values ranging from 0.769 to 0.821. Originality/Value: The findings are consistent with previous domestic and international studies, underscoring the importance of improving ICT infrastructures, enhancing system interoperability, strengthening human resource expertise, securing appropriate financial investments, and formulating supportive policies as fundamental prerequisites for the development of big data technology. Consequently, addressing these factors may pave the way for increased efficiency and competitiveness of the Iranian banking system in the digital era.

Abstract This research, based on logic-based method, has analyzed DuPont's financial performance of 30 large companies in Tehran's capital market for the period 1398 to 1400. In this research, using a mathematical model, logical aggregation of components has been used in order to model possible patterns according to business models. Also, the obtained mathematical models were used to calculate the level of realization of the observed patterns. The obtained results showed that logical aggregation, apart from econometric models, can be suitable for analyzing the financial performance of companies based on the DuPont ratio, and also among the large companies on the stock exchange, Bank Mellat (with a weight of 49%), Iran telecom (with a weight of 49%) 48% and Boali Sina Petrochemical with weight (28%) got the highest quality for investment based on investment priority.

Abstract Accounting disclosure is made through the publication of annual financial reports of companies. The disclosed information should have appropriate features that facilitate understanding for user groups. On the other hand, the credibility of financial reports is created by hiring independent auditors, which creates significant audit costs to achieve this credibility. The readability of financial reports is one of the issues that affects the auditor's credit performance and audit costs. It seems that complex annual financial reports, which are less readable, increase the amount of tests required by auditors, and unlike financial reports with high readability, the auditor's proof tests reduce the time and cost of processing. . The aim of the present study is to evaluate the effect of the readability of the financial reports of banks admitted to the Tehran Stock Exchange on the audit fee during the years 2005 to 2021. For this purpose, 10 accepted banks were examined during these years with the unbalanced panel method. To measure the readability of financial reports, three indicators of fog, flash and report length were used. The results of the research indicate that the readability of financial reports has an effect on the audit fee, but the first audit does not strengthen the intensity of this relationship. Also, the results showed that the tenure of auditors plays a moderating role for the relationship between readability and audit fees.

Abstract Bank facilities are the main outputs of the bank, through which the society's liquidity, which is placed in a wandering way at the level of the society, is injected into defined and targeted economic sources. In this regard, one of the major problems faced by decision-makers in banks is prioritizing loan applicants. Therefore, this research was conducted to identify the effective factors in developing a model for measuring customers' credit risk and determining a suitable algorithm for prioritizing bank applicants on a case study in Sepeh Bank. In this research, experts' intuitive and imprecise judgments were considered hesitant fuzzy data, and a simple distance-based algorithm was proposed. The output of the proposed algorithm is a detailed ranking of applicants for bank loans. The presented problem in this research is a decision-making one that is done intuitively, and so far, no research has been done to provide a prioritization algorithm in this field.

Abstract Purpose: Bond tokenization holds transformative potential for financial markets, promising enhanced liquidity, lower transaction costs, and democratized access. Yet, the existing literature remains fragmented and contradictory, failing to offer a comprehensive picture of its actual effects. This paper aimed to systematically integrate existing findings and provide a holistic analysis of the benefits, barriers, and structural impacts of tokenization on bond markets.
Methodology: Using a qualitative meta-synthesis approach based on Sandelowski and Barroso's seven-step model, 25 articles were selected through systematic database searching and screening, then qualitatively assessed using the CASP tool. Findings were synthesized via thematic synthesis in three stages. Reliability was confirmed through Cohen's Kappa, the Intraclass Correlation Coefficient, and an expert panel.
Findings: Three overarching themes emerged: 1) Practical efficiency gains, reduced settlement time and transaction costs, though enhanced liquidity remains unrealized; 2) The regulatory labyrinth, legal ambiguities and fragmented frameworks creating a vicious cycle of uncertainty; and 3) Structural and governance evolution, revealing a fundamental paradox whereby decentralized technology does not eliminate intermediaries but reinvents them through hybrid models.
Originality/Value: Previous studies have operated in silos, addressing efficiency, regulation, or technical architecture in isolation. This research, for the first time, integrates these three streams into a unified analytical framework. Critically, this synthesis uncovers the "Governance Paradox", where technological benefits, constrained by regulatory barriers, lead to the reinvention rather than elimination of intermediaries. This feedback loop, visible only through integrated analysis, constitutes the paper's principal theoretical innovation, advancing knowledge while providing a coherent roadmap for policymakers and market participants.