Accounting tools
Zahra Masoumi Bilondi; Maryam Sadat Tabatabaeian; Nasrin Yousefzadeh
Abstract
In recent years, increasing attention has been paid to the adoption of information technology (IT) in organizations, particularly in the field of internal auditing. Integrating IT tools and systems into traditional auditing practices is a key driver for improving the efficiency, effectiveness, and accuracy ...
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In recent years, increasing attention has been paid to the adoption of information technology (IT) in organizations, particularly in the field of internal auditing. Integrating IT tools and systems into traditional auditing practices is a key driver for improving the efficiency, effectiveness, and accuracy of internal audit processes. This study aimed to explore the challenges, barriers, and solutions for IT integration in the internal auditing processes of companies listed on the Tehran Stock Exchange. A qualitative approach was adopted, and data were collected in 2024 through interviews with 18 internal audit experts. Thematic analysis was performed using MAXQDA software. The findings revealed that the primary challenges and barriers to IT integration in internal auditing were organizational limitations, technical constraints, auditors' perceived barriers, and insufficient training. To address these issues, the following solutions were proposed: promoting a culture of IT adoption, organizational commitment to implementing new technologies, providing the necessary infrastructure, and reinforcing employees’ training and IT-related skills.IntroductionIn recent years, the role of technology in organizations, particularly in internal auditing, has become increasingly critical. It is now essential for improving processes and ensuring accountability in today’s digital environment (Mohd Noor & Mansor, 2019; Ronkko et al., 2018). Traditional auditing approaches, which rely on manual work and paperwork, are both time-intensive and resource-heavy (Eulerich et al., 2021). Adopting technology in internal auditing is crucial for several reasons. First, technology can simplify auditing processes by automating repetitive tasks, giving auditors more capacity to focus on important areas such as risk evaluation (Al-Hiyari, 2019). Second, it can enhance the precision of audits by processing complex data and minimizing errors, resulting in higher-quality reports (Jaber & Abu Wadi, 2018). Third, using technology enables real-time access to data, allowing auditors to monitor financial activities and compliance more effectively (Mohd Noor & Mansor, 2019). This study examines the challenges and potential approaches to introducing technology into internal auditing in companies listed on the Tehran Stock Exchange. It seeks to answer the question: What challenges and approaches do experts identify for integrating technology into internal auditing?Theoretical Background and Literature ReviewDavis’s (1989) Technology Acceptance Model explains two factors that influence whether people adopt new tools: how useful they believe the tools will be and how simple they are to use. These factors shape the decisions of internal auditors when considering new technologies (Radner & Rothschild, 1975). Ease of use refers to how much effort a person expects will be needed to work with a system. For auditors, this includes whether the tools are straightforward, easy to learn, and well-supported. Integrating technology with traditional auditing practices offers opportunities for improvement, such as making processes faster, more accurate, and more effective. However, studies show that despite these advantages, technology adoption in auditing has not progressed as expected in Iran. While some research has explored the reasons behind this slow uptake, there is little analysis of the specific challenges and solutions involved. This study aims to fill that gap by examining these issues and providing recommendations.Research MethodologyThis research is qualitative and uses thematic analysis. It is a cross-sectional study carried out in 2024. The participants included internal auditors from companies listed on the Tehran Stock Exchange, selected using the snowball sampling method. The reliability of the interviews conducted in this research, calculated using the above formula, is 77%. Since this value is greater than 60%, the coding reliability of this study is confirmed.Discussion and ConclusionThis study aimed to explore the challenges, obstacles, and approaches to incorporating information technology into internal auditing through an analysis of participant responses. The findings point to several difficulties, including structural issues within organizations, technical challenges, and auditors’ perceptions of technology use. The study also highlights a gap in providing proper training for internal auditors in this area. Despite rapid advancements in technology, companies are not allocating enough resources to prepare their staff. Moreover, since many auditors are older, offering training often requires significant effort and expense. To address these issues, organizations can focus on helping managers and employees better understand the benefits of using technology in internal auditing. Explaining how it adds value to their work and showing clear examples of cost efficiency can reduce resistance. Another important step is creating a workplace environment that encourages fresh thinking and supports the adoption of modern tools. This can inspire auditors to explore and use technology more confidently.
Accounting tools
Amir Hajizadeh Amini; Seyd Abbas Borhani; Mojgan Safa
Abstract
This study seeks to provide a framework for facilitating tokenization implementation processes in the context of cloud accounting platforms and to evaluate its core and propositional contexts at the level of capital market companies. In terms of methodology, this study combines exploratory and developmental ...
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This study seeks to provide a framework for facilitating tokenization implementation processes in the context of cloud accounting platforms and to evaluate its core and propositional contexts at the level of capital market companies. In terms of methodology, this study combines exploratory and developmental approaches and, in the qualitative part, aims to identify areas that facilitate the processes of implementing tokenization in cloud accounting platforms. The qualitative results derived from 12 interviews and the creation of 284 open codes indicate the identification of three categories with six components and thirty-one propositional themes. Then, through Delphi analysis, six propositional themes were eliminated in two rounds, leaving a total of twenty-five propositional themes along with six core components for fuzzy network analysis. The results of the fuzzy network analysis first showed that the two components of security support and cyber support are more effective in implementing tokenization to improve the security of cloud accounts of capital market companies. Second, it was found that defining a digital signature for each user to secure cloud accounts and defining user authentication to secure cloud accounts are considered the most important propositional themes in this regard.IntroductionThe increasing changes in the world of communication and information have significantly transformed the functional systems of accounting knowledge compared to the past and have become part of companies’ business strategies in exchanging information with stakeholders. The extent of these changes has led the accounting profession to consider more comprehensive aspects of reflecting information to stakeholders by modifying its functional infrastructure in information disclosure, while still maintaining its classic practices. In this way, these changes have reduced the costs of comparing financial statements for information users and have improved the quality of financial decisions, both by accelerating the receipt and analysis of information and by enhancing the allocation of competitive resources. Literature ReviewCloud accounting is a type of cloud computing program designed specifically for processing financial data. It can shorten financial procedures through a system that enables the processing, storage, and feedback of financial functions to stakeholders at a higher speed than in the past. These services are provided to information users online and through remote servers by companies and accounting units. On the other hand, cloud accounting can also be regarded as a form of data mining and data storage that, through online or web-based reporting, improves the quality of financial decisions by providing more reliable information disclosure. Cloud accounting typically includes a set of applications that allow information users to access data more quickly and conveniently through the Internet. MethodologhyIn this study, the methodology is a so-called multi-method approach to implementing the research objectives. The data collection methods are diverse and combine both qualitative and quantitative tools. The qualitative methodological process uses interviews, while the quantitative methodological process relies on fuzzy checklists. In terms of the philosophical nature of the study, it should be considered inductive-deductive. By relying on the inductive philosophy, the study seeks to identify the underlying dimensions that facilitate tokenization implementation processes in the context of cloud accounting platforms. On the other hand, the deductive philosophy supports the generalization of the central components and propositional themes to the study context, enabling the evaluation of the identified dimensions at the level of capital market companies. From an objective approach, it should be acknowledged that, due to the emerging nature of the phenomenon under study, this research is classified as exploratory. From a results perspective, the study should be considered developmental, as it attempts to create a more coherent understanding of this phenomenon in accounting knowledge by integrating a set of contextual factors that influence the facilitation of tokenization implementation processes in cloud accounting. ResultSince the conceptual nature of tokenization is based on securing both physical and digital accounts, this study sought to identify the prerequisite functions required to facilitate its implementation processes in the context of a cloud accounting platform, using grounded theory analysis. Considering the emergence of theoretical saturation in the twelfth interview with research experts, 284 open codes were created. Based on axial and selective coding, three categories, six components, and thirty-one propositional themes were identified. These dimensions represent three general mechanisms that facilitate tokenization in enhancing the effectiveness of cloud accounting: management support, strategic/strategic support, and institutional/social support. Each refers to areas that can be addressed by allocating resources and providing professional training in a timely manner. First, professional operators can be prepared for the adoption of cloud accounting through both mental and professional empowerment, while resources are allocated for software and infrastructure development to improve the security of accounts. Second, internal supervisory units should provide security and cyber support to ensure users receive higher-quality, more secure financial information. Third, through institutional and social functions, upstream organizations should work toward the standardization and integration of companies' practices in using cloud accounting platforms by setting more specific requirements, thereby create a higher level of support for shareholders and other information users. DiscussionThis study seeks to provide a framework for facilitating tokenization implementation processes in the context of cloud accounting platforms and to evaluate its core and propositional contexts at the level of capital market companies. In interpreting the results, it should be noted that security support, as a foundation for facilitating tokenization and enhancing the effectiveness of cloud accounting functions, is considered both a structural and strategic approach to strengthening the cloud accounting platform against hacker intrusion. Based on the ranking of propositional themes, it was determined that accounting units using this platform need to maintain proper supervision over the registration of documents, payments, and receipts by designating operators with the ability to digitally sign, in order to prevent the hacking of companies' accounts and financial systems. ConclusionIn line with the results obtained, strategists of leading companies using the effective functions of cloud accounting platforms are advised to develop the security and cyber capabilities of accounts beyond the tools currently defined in cloud computing.
Financial Accounting
Marzieh Poursaedi; Mahmood Hematfar; Seyed Enayatallah Alavi; Roya Nasirzadeh
Abstract
The aim of this study is to model the detection of firms’ financial fraud using artificial neural network evaluation algorithms. Quadratic Programming (QP) processes were applied in artificial neural network algorithms to, first, determine the basic algorithm and, second, choose the technical parameters ...
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The aim of this study is to model the detection of firms’ financial fraud using artificial neural network evaluation algorithms. Quadratic Programming (QP) processes were applied in artificial neural network algorithms to, first, determine the basic algorithm and, second, choose the technical parameters of the artificial neural network, based on time-series data from 2013 to 2022. A diagnostic model was then developed using test and control scales to examine innovative algorithms with the highest accuracy coefficients in predicting financial fraud at the level of capital market companies. Based on systematic sampling, 95 stock exchange companies were selected, providing 950 firm-year observations. The distinction between financially healthy companies and those with the potential for financial fraud was determined through decimalization, and companies placed in the fraud-prone deciles were examined using the parameters of the artificial neural network's effectiveness.IntroductionWith the advent of technology and digital business exchanges, today's era is far more affected by the negative consequences of fraud in financial statements than in the past, making the development of fraud detection methods a technical necessity in the field of financial knowledge. By providing appropriate assessment opportunities for optimal decision-making, highly efficient financial markets facilitate a balanced flow of information among firms, thereby maintaining the attractiveness of entering this market compared to other markets, such as money markets. In particular, implementing such processes can be considered a strategic financial necessity in developing economies that face serious challenges due to resource constraints. However, reference to scientific evidence and the operational reality of financial markets in these countries indicates the existence of information rents for certain groups of financial decision-makers, which create information asymmetry without requiring expertise, technical evaluation methods, or fundamental analysis. 2. Literature ReviewDisclosure of transparent financial information is considered an important resource in stakeholders’ economic decision-making and can contribute significantly to balancing investment markets. However, with theoretical and structural changes in the field of financial transparency, fraud as a behavioral and functional issue has become a challenge to the financial transparency of companies. To understand the official definition of financial fraud, the best reference is Section 240, Clause 4 of the Iranian Auditing Standards, which defines this phenomenon as the intentional actions of companies’ executive managers, governing bodies, employees, or third parties that result in the acquisition of illegitimate benefits and cause widespread damage to other stakeholders. An important point noted in Clause 9 of the same standard is the distinction between fraud and error, where intent is considered the only distinguishing feature. In practice, however, drawing a clear boundary between these two in order to protect stakeholders’ rights is not an easy task. MethodologyIn terms of data type, this study is classified as a semi-experimental and post-event study in the field of positive financial research, implemented using the neural network analysis method and related techniques. In terms of results, this study can be classified as applied research, and in terms of implementation, it is correlational and algorithmic. First, based on a set of analytical procedures using software such as MATLAB and WEKA, the evaluation processes of artificial neural network algorithms are examined. Then, by comparing the selected algorithms, the most effective type of analysis is determined from the perspective of evaluating financial ratios to predict the probability of fraud in companies. It should be noted that the analytical implementation in this process is based on three steps: extracting financial ratios, evaluating extracted ratios, and finally applying neural networking to the evaluated algorithms. ResultIn this study, a systematic review of the literature related to the research field over recent years was first conducted to select financial ratios appropriate for evaluating fraud in capital market companies. Then, based on quadratic programming (QP), the basic algorithm for evaluating the accuracy of corporate fraud was determined using firm-year observations by minimizing the gap between predicted and actual data obtained from the identified financial ratios. Through the adaptive neural fuzzy inference system (ANFIS) test and the cross-validation process (k-fold), it was determined that the unsupervised learning algorithm, which incorporates evaluation parameters based on a meta-heuristic approach and provides higher prediction accuracy, was selected as the foundation for the algorithms in this study. To create a reference index for assessing fraud probability based on financial ratios, the decile method was used to identify which companies with a coefficient of D>1 could be distinguished between financially healthy firms and those with fraud probability, under the constant return to scale (CRS) and variable return to scale (VRS) evaluation scales. The results indicate that companies with fraud probability were concentrated in four deciles, suggesting that two algorithms, genetic and bee colony selection, were used to further evaluate prediction accuracy. Finally, it was found that the bee colony algorithm had a higher accuracy coefficient in predicting fraud accuracy probability compared to the genetic algorithm. It was also found that the ratio of net profit to sales is the most important criterion for evaluating the accuracy of fraud prediction in the companies under study. DiscussionIn interpreting the results, it should first be noted that the bee colony algorithm performs better in solving complex problems due to its multi-process optimization through collective intelligence. This algorithm can be more effective in financial decision-making at the capital market level because it shows higher convergence power and accuracy in predicting the probability of fraud in the companies under study compared to the genetic algorithm. In addition, the coefficients obtained from the bee colony algorithm indicate more effective optimization of financial ratios in predicting the probability of fraud. Financial decision-makers can therefore use this algorithm for more accurate evaluations based on financial ratios, enabling them to identify companies with a probability of fraud and avoid purchasing their shares when forming a portfolio. ConclusionGiven the importance of fraud in financial decision-making, investors are advised to reduce the risk of predicting financial fraud in companies by improving their level of technical analysis training when forming a stock portfolio. The most significant analytical techniques are related to prediction methods based on unsupervised learning algorithms. Focusing on this set of algorithms provides decision-makers with deeper insights by enabling them to recognize the true nature of the data and, without manipulating or remapping it, identify predictable patterns, structures, and relationships of financial fraud in companies.
Accounting tools
Tayebeh Gharibi; Neamat Rostami Mazouei; Azar Moslemi; Masoud Taherinia
Abstract
The purpose of this research is to develop a framework for digital asset accounting and to evaluate the axes identified based on mutual matrices. The methodology of this study is exploratory and developmental, combining qualitative and quantitative data collection. First, it seeks to provide a theoretical ...
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The purpose of this research is to develop a framework for digital asset accounting and to evaluate the axes identified based on mutual matrices. The methodology of this study is exploratory and developmental, combining qualitative and quantitative data collection. First, it seeks to provide a theoretical framework based on Glaser's (1992) ground theory approach. Second, to determine the most effective central component of digital assets accounting implementation, the interpretive ranking process is applied. The tools used in the qualitative part are interviews with experts selected through theoretical and snowball sampling, and the tools used in the quantitative part are paired comparison checklists of row "i" and column "j". The results of the qualitative part of the study, conducted through 12 interviews, indicate the identification of 4 categories, 5 components, and 25 conceptual themes. These formed the theoretical framework of the investigated phenomenon, with reliability of the main axes confirmed through Delphi analysis. The results of the quantitative part also showed that the central component of compliance with the internal controls of digital assets ("J4") is the most important mechanism for implementing digital asset accounting in the context of capital market companies, which can strengthen the information capacities of users.IntroductionThe changing world of global trade has led to the emergence of new forms of commercial exchange in which assets are traded virtually without the need for physical presence in a contract. In other words, with the reduction of barriers to international trade due to technological developments and the shift in the nature of assets toward virtualization, digital assets have become one of the easiest means of commercial exchange between companies and investors. These assets, which are intangible in nature, not only have high potential to increase the value of companies but also generate higher profit margins because they bring lower costs to companies compared to tangible assets. 2. Literature ReviewDigital assets were initially classified as “Cryptocurrencies” in the category of intangible assets, valued by connecting to a “Blockchain” as the basis for maintaining and sharing these virtual assets among investors. The ecosystem of this type of asset, beyond the initial idea of transactions based on digital currencies, has now become part of the capital functions of companies, as increasing demand from investors has enhanced its value and nature as an intangible asset. As a result, although digital assets were initially similar to cryptocurrencies at the time of their emergence in 2008, today digital assets have a different definition from cryptocurrencies, despite a gray boundary in terms of the nature of their shares. In fact, this change was introduced by the World Bank with the aim of shaping the nature of digital assets in transparent financial reporting. In a specific definition, digital assets are considered to include content based on images, photos, videos, or any intangible content feature that can create value for its holder. By contrast, cryptocurrencies are a type of digital money in which currency production and verification of transaction authenticity are controlled using encryption algorithms. MethodologhyThe methodology of this study is considered to be of a mixed data type. In the qualitative part of the study, due to the lack of a measurable theoretical basis to describe the concept of digital asset accounting, the grounded theory analysis process is used. This provides a theoretical framework as the basic objective of the study, while the quantitative part explores the main axes identified in the theoretical framework in the context of the capital market through reciprocal and diagonal matrix processes. Philosophically, the nature of this study can be considered basic according to the matrix of methodological strategies, with this philosophical basis justified in the methodology through an inductive/deductive combination. In other words, the philosophy of research based on induction helps identify emerging aspects of digital accounting in a cognitive framework, and the deductive philosophy allows the research to examine the identified factors. ResultIn this study, due to the dispersion of digital asset disclosure standards and the indirect nature of institutional oversight, an attempt was made to identify the effective factors in the implementation of digital asset accounting based on Glaser's approach in the grounded theory analysis process. Based on 12 interviews conducted with academic experts and through three coding stages, a total of 4 main categories, 5 central components, and 25 initial conceptual themes were identified. These dimensions were an attempt to answer the first research question, which sought to identify the axes of implementing digital asset accounting in capital market companies. The study aimed to determine the central components needed to create a strategic approach to preventing structural opportunism in the emergence of digital assets in the context of capital market companies. To explain the central components, the fuzzy Delphi process was used to assess whether the axes of implementing digital accounting are feasible at the level of capital market companies. The results of this process confirmed that all 5 identified main axes can be useful in the functional evaluation of implementing digital accounting procedures. Furthermore, during the paired comparison process based on reciprocal matrices, and in response to the second research question, it was determined that compliance with internal controls of digital assets ("J4") is the most effective axis component to be considered in the implementation of accounting for these assets. DiscussionIn analyzing the results, it should be stated that internal controls in the disclosure of digital assets, due to the continuous internal monitoring of companies from a structural perspective, enable companies to, first, improve the quality of financial reporting on these assets by facilitating the process of independent auditors' reviews. Second, dynamic monitoring through internal controls provides a level of assurance in calculating the fair value of digital assets in accordance with Standard No. 17 of Intangible Assets and helps strengthen the operational efficiency of companies in using these assets. Adherence to fair value through internal control, by preventing the flow of profit or loss resulting from fluctuations in fair value in the income statement, improves the accuracy of digital asset figures from a disclosure perspective. At the same time, it enables the connection of these values with other aspects of operating profit and helps create a better balance in financial statements. ConclusionGiven the results, it is recommended that policymakers in the field of accounting standards develop a new standard under the title of digital assets, based on the separation of digital assets into intangible asset items and relying on the existing accounting standards 8, 10, 15, 17, and 21. Integrating digital assets into the intangible asset subset can contribute to the consistency and overall philosophy of the standards for these assets.
Accounting and various aspects of finance
Amin Ahmadpour; Seyedeh Mahboobeh Jafari; Fatemeh Sarraf
Abstract
This study investigates the impact of economic sanctions on tax evasion facilitated through Related-Party Transactions (RPTs) in Iran. Utilizing a novel hybrid framework that integrates graph mining, Principal Component Analysis (PCA), and advanced fuzzy metaheuristic optimization, we analyze financial ...
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This study investigates the impact of economic sanctions on tax evasion facilitated through Related-Party Transactions (RPTs) in Iran. Utilizing a novel hybrid framework that integrates graph mining, Principal Component Analysis (PCA), and advanced fuzzy metaheuristic optimization, we analyze financial data from 1,780 companies (2016-2020). Graph mining is employed to map and detect suspicious transaction networks, particularly those involving Free Trade Zones (FTZs). A sanctions intensity index is constructed using PCA from 10 macroeconomic variables. The core predictive modeling leverages a Jaguar-optimized Type-3 Sheffer-like Type-4 fuzzy logic system to handle data uncertainty and non-linear relationships. Results indicate that sanctions exacerbate RPT-based tax evasion, increasing its magnitude from 0.389% to 0.414%. The proposed Jaguar model demonstrated superior performance with 98.8% accuracy (MSFE: 0.012), significantly outperforming traditional detection methods. Post-sanctions network topology analysis revealed a marked increase in suspicious clusters and nodes, with prevalent evasion patterns including multi-layer transfer pricing and abnormal profitability in FTZ subsidiaries. This research offers a robust, scalable tool for tax authorities to prioritize audits and enhances the understanding of how macroeconomic shocks influence illicit financial behaviors within corporate networks.IntroductionEconomic sanctions are coercive measures imposed by states to restrict international activities of target nations, offering a lower-risk alternative to military conflict (Cordesman et al., 2011). Iran exemplifies this, facing escalating sanctions that incentivize tax evasion through Related-Party Transactions (RPTs). Under sanctions, firms exploit legal gaps and accrual accounting to manipulate profits (Abeysekera, 2003; Arabi et al., 2018), transforming Iran’s financial market into a complex network (Soleimani et al., 2014). Traditional analytical methods fail against such complexity, while metaheuristic models excel. Graph mining uniquely uncovers hidden dimensions in sanctioned markets by analyzing network structures and variable relationships (Hu et al., 2022), especially where information asymmetry impedes tax authorities (Iacovacci & Lacasa, 2019; Yang & Xu, 2024).RPTs occur in nested networks with non-linear relationships (e.g., shared boards, cross-ownership) (Ruan et al., 2019). Sanctions amplify complexity through layered tactics like free trade zones (FTZs) and multi-layer transfer pricing (e.g., sequential sales at non-arm’s length prices) (Chan et al., 2016; Tian et al., 2016). Non-disclosure of ~68% key RPT information (e.g., pricing logic) exacerbates tax avoidance (Barokah, 2013), enabling profit shifting to foreign affiliates and eroding tax bases (Yang & Xu, 2024).Although RPTs can be economically justified (Gordon et al., 2004a), they risk abuse for private gain (Djankov et al., 2008; Barokah, 2013). In Iran, firms use subsidiaries in FTZs (e.g., Kish, Chabahar) and transfer pricing under Article 132-T of Iran’s Direct Taxation Law to shift profits: e.g., selling goods below market to affiliates, which then export at global prices, registering profits offshore. Weak oversight and fragmented databases hinder monitoring, but Iran’s Taxpayers’ Integrated System (TIS) provides foundational data for analysis.This study proposes a novel framework combining graph mining (to detect high-risk FTZ firms) and Type-3 Sheffer-like Type-4 fuzzy logic (to model tax data uncertainty) optimized by the Jaguar metaheuristic algorithm. It identifies suspicious groups exhibiting structural (e.g., nested ownership) and behavioral (e.g., abnormal pricing) tax evasion patterns, aligning with Iran’s Comprehensive Tax Plan for risk-based audits.Research Questions:Do economic sanctions increase RPT-based tax evasion?How can advanced data analytics identify and model these hidden patterns? Theoretical Framework2.1. Related-Party Transactions (RPTs)Per Iranian Accounting Standard 12 (Audit Organization, 2020), RPTs involve entities with control/influence over financial decisions. Key groups include:Parent/subsidiary entities under shared control.Key management personnel and relatives.Entities with significant economic/management ties.Two theoretical perspectives exist:- Agency Theory:RPTs enable opportunism by insiders (Jensen & Meckling, 1976), e.g., underpriced asset sales (Cheung et al., 2006).- Efficiency View: RPTs reduce transaction costs (Gordon et al., 2004a) but require disclosure to mitigate information asymmetry (Kohlbeck & Mayhew, 2010).Empirical evidence confirms RPTs facilitate tax avoidance via transfer pricing (Harris et al., 1993; Jian & Wong, 2010), especially in low-tax jurisdictions (Barker et al., 2016).2.2. Sanctions’ Economic ImpactSanctions restrict input access, raise production costs (Parsa et al., 2013), contract import-reliant sectors (Caetano et al., 2023), and reduce total factor productivity (Nosratabadi, 2023). They incentivize shifting activities to the informal economy, causing technical inefficiency (Markus, 2024). Methodology3.1. Data & Variables- Dependent Variable: Tax evasion, measured by the tax gap (difference between declared and final tax) per OECD standards (Slemrod & Weber, 2012).- Independent Variable: RPT volume (Iranian Accounting Standard 12).- Moderator: Sanctions index (PCA-derived from 10 macroeconomic variables, Table 1).Data: 16,756 RPTs from 1,780 Iranian firms (2016–2020), including:523 firms in FTZs (zero tax rate under Article 132-T).1,257 non-FTZ firms with shared boards.Financial data (net sales, COGS, operating profit) sourced confidentially from Iran’s National Tax Administration (INTA).3.2. Integrated FrameworkGraph Mining:Construct transaction networks (nodes = firms; edges = RPTs weighted by price deviation).Identify high-risk clusters(e.g., firms in FTZs with below-market pricing).PCA for Sanctions Index:- Combine 10 macroeconomic variables (e.g., oil exports, currency volatility) into a unified index.- 2 principal components explain 85% variance (Table 1, Chart 3). Fuzzy Metaheuristic Optimization:- Apply Type-3 Sheffer-like Type-4 fuzzy logic to model data uncertainty (e.g., transfer pricing discrepancies).- Optimize via Jaguar algorithm (multi-objective: minimize prediction error [MSFE], maximize detection accuracy).- Output: Dynamic risk index (transaction volume, price deviation, geographic concentration). Results & Discussion- The analysis confirmed that sanctions significantly intensified RPT-based tax evasion, elevating its level from 0.389% (pre-sanctions) to 0.414% (post-sanctions). This 0.025% increase, though seemingly small, represents a substantial rise in hidden economic activity within the constrained environment.- The Jaguar model achieved 98.8% accuracy (error rate: 0.012), outperforming traditional methods (40% vs. 74.6% detection rate).- Graph analysis revealed post-sanctions topological shifts: increased suspicious nodes/clusters (Chart 4).- Key evasion patterns:- Multi-layer transfer pricing (e.g., mother → FTZ subsidiary → export).- Abnormal profitability in FTZ subsidiaries.- Geographic concentration in low-tax areas. Conclusion & Policy Implications5.1. Key FindingsSanctions intensify RPT-based tax evasion by incentivizing complex, hidden transaction networks. The integrated graph-fuzzy-jaguar framework proves superior to linear models in detecting evasion under data uncertainty.5.2. Innovations- First application of Type-3 fuzzy logic in taxation.- Dynamic risk index for audit prioritization.- Operational compatibility with INTA’s existing systems (e.g., TIS).5.3. Recommendations- To INTA:Integrating the model into a blockchain-based real-time monitoring platform and Develop an AI dashboard with risk-tiered visualization (green/yellow/red).- Domestic Policy: Mandating disclosure of transfer pricing logic and topological RPT networks and establishing a National Networked Data Analysis Center.- International Cooperation:Leveraging double-taxation agreements for cross-border data exchange.- Future Research: Extending the model to multinational contexts and designing "tax resilience indices" for sanction-affected economies.
stock exchange
Shokrollah Khajavi; Soraya Weysihesar
Abstract
Efficiency is one of the most important criteria that investors consider when evaluating influencing factors to identify suitable investment opportunities. Since managers play an effective role in company decisions, they may deviate from optimal investment choices. Therefore, the purpose of this research ...
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Efficiency is one of the most important criteria that investors consider when evaluating influencing factors to identify suitable investment opportunities. Since managers play an effective role in company decisions, they may deviate from optimal investment choices. Therefore, the purpose of this research is to investigate the relationship between CEO power and overinvestment. In this regard, 123 companies listed on the Tehran Stock Exchange were examined between 2016 and 2022. The results show that there is a negative and significant relationship between CEO power and investment inefficiency (overinvestment). Furthermore, this relationship is not nonlinear. The findings indicate that powerful CEOs do not engage in excessive investments that could create more personal benefits for them. Indeed, because of risk aversion and ability effects, the private benefits of powerful CEOs are aligned with shareholders’ interests, making them less likely to overinvestIntroductionEfficiency is one of the most important criteria that investors consider when evaluating influencing factors to identify suitable investment opportunities. Since managers play an effective role in company decisions, they may deviate from optimal investment choices. Therefore, the purpose of this research is to investigate the relationship between CEO power and overinvestment. To explain this relationship, three different effects are discussed: the discretion effect, the risk aversion effect, and the ability effect.Under the discretion effect, CEO power is positively related to overinvestment, because powerful CEOs have more freedom of action and may use overinvestment decisions to create personal benefits. Through empire building and expropriation, they pursue self-interest that can increase their rewards, wealth associated with stock ownership, and job security because they control capital allocation. Furthermore, CEOs can create personal bonuses through overinvestment because they influence the choice of performance measures associated with their bonuses. Under the risk aversion effect, CEO power has a negative relationship with overinvestment, because powerful CEOs are more risk-averse than shareholders who can reduce their risk through diversified portfolios. Overinvestment may increase the risk of the company. Since most of the CEO's rewards and human capital depend on their company, it is difficult for them to diversify work and wealth risks. Therefore, powerful CEOs who do not diversify and are often considered the main planners of the company's long-term strategy are more likely to make investments based on risk aversion. As a result, they are less likely to overinvest. Under the ability effect, powerful CEOs with greater management ability can make investment decisions more effectively and efficiently, and therefore are less likely to overinvest. CEOs with stronger expertise can better manage the company's external uncertainties through their experience and knowledge. Hence, powerful CEOs make more efficient investment decisions. Accordingly, the main goal of this research is to investigate the effect of CEO power on overinvestment. From the perspective of economic studies, weak supervision over CEOs, in the shadow of weak management structures and opportunities to secure personal benefits, can encourage powerful managers to choose projects with a negative net present value (NPV), thereby reducing company value. On the other hand, greater CEO power leads to more appropriate investment in valuable projects and greater investment efficiency. Factors such as risk aversion, motivation to maintain reputation and credibility, and stronger management abilities make powerful managers perform better in evaluating investment opportunities and increase investment efficiency, which aligns with organizational research. Research QuestionAccording to the research objective, this study seeks to answer the question of whether CEOs with higher decision-making power overinvest. MethodsThe current research is of an applied type; in terms of its goal, it is analytical, quasi-experimental, and correlational. From the time dimension of the data, it is retrospective and post-event. In line with the purpose of the research, 123 companies listed on the Tehran Stock Exchange were examined between 2016 and 2022. The residuals of Richardson's (2006) model were used to measure overinvestment. CEO power was measured using the principal component analysis method and the criteria of CEO duality, the percentage of independent directors on the board of directors, CEO tenure, and CEO ownership percentage. The information required to measure the variables and test the research hypotheses was extracted from the Rahavard Novin database, audited financial statements, and other reports published on company websites, Codal, and the Stock Exchange Organization. After data collection, Excel software was used for summarizing and calculations. Since the dependent variable, overinvestment, is not continuous and has only one of the two values (zero and one), the logistic regression (logit) model was used to test the research hypothesis with this variable. In addition, a multiple regression model was used to test the research hypothesis with the investment inefficiency variable. Finally, the analysis was performed using EViews software. ResultsThe results show that as CEO power increases, investment inefficiency (overinvestment) decreases. In addition, there is no significant nonlinear relationship between CEO power and investment inefficiency (overinvestment). Discussion and ConclusionThe findings of the research show that powerful CEOs, who have more authority than shareholders in making company decisions, do not engage in excessive investments that could create personal benefits for them. Indeed, because of the risk aversion and ability effects, the private benefits of powerful CEOs are naturally aligned with shareholders’ interests, making them less likely to overinvest. Under the risk aversion effect, since most of a CEO's rewards and human capital depend on their company, it is difficult for them to diversify work and wealth risks. Therefore, powerful CEOs who do not diversify and are often considered the main planners of the company's long-term strategy are more likely to make investments based on risk aversion. As a result, they are less likely to overinvest. Under the ability effect, powerful CEOs have higher management abilities and therefore make more efficient investment decisions. Because strong CEOs with greater managerial ability possess better knowledge and judgment than their peers, making them more capable of predicting future changes, they do not waste capital on negative NPV projects. Therefore, more powerful CEOs are less likely to overinvest. These results are in line with Lo and Shiah‑Hou's (2022) research and are also consistent with organizational theory. According to this theory, the greater the power of the CEO, the more appropriate the investment in valuable projects and the greater the investment efficiency. Factors such as managers' risk aversion, motivation to maintain reputation, and stronger management abilities lead powerful managers to use better strategies for the optimal use of company resources, thereby increasing transparency and securing the interests of all stakeholder groups. Therefore, powerful CEOs make more efficient investment decisions.
stock exchange
Abdolrasoul Rahmanian Koushkaki; Sohrab Vahdan Asl
Abstract
The purpose of this study is to investigate the effect of fixed asset investment and financial performance on the relationship between social responsibility and debt financing. The present study is applied and, from the methodological point of view, is a causal-correlational (post-event) study. The statistical ...
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The purpose of this study is to investigate the effect of fixed asset investment and financial performance on the relationship between social responsibility and debt financing. The present study is applied and, from the methodological point of view, is a causal-correlational (post-event) study. The statistical population includes all companies listed on the Tehran Stock Exchange, and using the systematic elimination sampling method, 141 firms were selected as the research sample and studied over a 10-year period between 2014 and 2023. The findings of hypothesis testing showed that there is a direct and significant relationship between social responsibility and debt financing. Investment in fixed assets does not affect this relationship between social responsibility and debt financing, but financial performance has an inverse and significant effect on this relationship. By adhering to social responsibilities and respecting the rights of stakeholders and society, company managers can more easily access external financing by creating a better image. In addition, obtaining a higher social rank can strengthen the company's image for investors and provide greater assurance IntroductionCompanies and economic institutions need appropriate and timely financing to invest, repay debts, and increase working capital. Financial managers are always trying to increase the value of the company by creating new financing methods. Companies do not rely on only one type of resource; they try to use multiple resources to implement their plans and address their needs. Various factors can affect access to debt financing. Corporate social responsibility is one of the important issues that can influence the company's financing process. It is described as the process of creating wealth, promoting the company's competitive advantage, and maximizing the value of wealth and benefits created for society. In general, it reflects the commitment and attention of the business to the quality of life of employees, customers, the local community, and society as a whole, with the aim of developing a sustainable economy. Literature ReviewDebt financing is a more desirable solution for financing due to tax savings and its lower rate compared to the expected returns of shareholders, but what is important for creditors is the company’s repayment ability (Ebrahimi et al., 2019). Organizations should always consider themselves a part of society and have a sense of responsibility towards society. In order to improve public welfare, employees, and related stakeholders, companies should also work beyond their direct interests. A company's social responsibility focuses on important issues such as ethics, environment, security, education, and human rights (Kordestani et al., 2018). Companies with higher social responsibility can, in fact, provide a strong guarantee for debt repayment, ensure the proper functioning of the company, reduce managers' behavioral biases, and ensure the provision of accurate information by managers to the capital market. This can increase companies’ access to financing through debt (Oyar et al., 2024). Therefore, the first hypothesis of the present study is as follows:H1: Social responsibility affects access to financing through debt.Financial performance is an objective measure of how effectively an organization has used its assets to generate revenue. It is one of the most important indicators for evaluating its performance and the degree of achievement of predetermined goals (Rahimian et al., 2013). Financial performance reflects the efficiency or inefficiency of the company and can therefore influence the opinions of investors and creditors regarding the company's performance. Accordingly, the second hypothesis of the present study is as follows:H2: Investment in fixed assets affects the relationship between social responsibility and access to financing through debt.One of the fundamental variables affecting the future performance of companies, and consequently the return on their shares, is the level of investment in fixed assets. This can pave the way for achieving the desired return in the future. However, since higher investment involves greater risk, it can weaken the company's financial position, reducing its ability to maintain current returns and achieve growth in future periods. In the long run, this can also decrease the company's efficiency and performance (Oyar et al., 2024). Therefore, the third hypothesis of the present study is as follows:H3: Financial performance affects the relationship between social responsibility and access to financing through debt. MethodologyThe present study is applied and, from a methodological point of view, is causal-correlational (post-event). The statistical population includes all companies listed on the Tehran Stock Exchange, and the study period covers 2014 to 2023. The systematic elimination method was used to determine the sample, and 141 companies were selected as the research sample. Data analysis was carried out using the combined data method and the panel data approach, and Eviews 12 software was applied to test the hypotheses. ResultsThe findings from testing the research hypotheses showed that there is a direct and significant relationship between social responsibility and financing through debt. Investment in fixed assets does not affect the relationship between social responsibility and financing through debt, but financial performance has an inverse and significant effect on this relationship. By adhering to social responsibilities and respecting the rights of stakeholders and society, company managers can more easily access external financing by creating a better image. In addition, obtaining a higher social rank can strengthen the company's image for investors and provide greater assurance. DiscussionThe results showed that corporate social responsibility directly affects financing through debt. In fact, when companies adhere to social principles and responsibilities, those who extend credit to the company operate in a more favorable environment for repayment, which simplifies companies’ access to debt financing. One of the fundamental variables affecting the future performance of companies, and consequently the return on their stocks, is the level of investment in fixed assets. Such investment can pave the way for achieving desirable returns in the future, but because of the added risk it places on the company's financial position, higher investment can reduce the company's ability to maintain its current return and achieve growth in future periods. While investing in fixed assets should theoretically affect debt financing because such assets can serve as collateral, the results showed that this feature has no effect on the relationship between social responsibility and debt financing. Financial performance reflects the overall performance of the company and the profitability derived from expenses and assets. It weakens the relationship between social responsibility and debt financing. In fact, it can be interpreted that financial performance influences the relationship between social responsibility and debt financing. ConclusionThe main limitation of the present study is the lack of a comprehensive and complete index to measure the social responsibility of companies. If the Stock Exchange Organization were to provide a general measure of social responsibility through comprehensive studies, the scope of research in this field would be greatly expanded.
