mahmoud. hematfar

In today's financial landscape, the prediction of corporate financial distress plays a crucial role in risk management and economic stability. This study aims to develop a hybrid predictive model that combines the Artificial Immune System (AIS) with the Wavelet Neural Network (WNN) to forecast financial distress in companies. The hybrid model leverages the strengths of both algorithms to improve accuracy in identifying distressed firms based on financial data. Utilizing a dataset of Tehran Stock Exchange-listed companies, this research compares the performance of the hybrid model against traditional methods like logistic regression and standalone neural networks. Results demonstrate that the AIS-WNN hybrid model outperforms other techniques in terms of prediction accuracy, sensitivity, and overall robustness. The findings indicate that the proposed model provides a powerful tool for investors, auditors, and policymakers to anticipate financial distress and make informed decisions. This approach can be further expanded to other domains of financial forecasting, contributing to the advancement of predictive analytics in the field.

Stock price crash refers to a large, negative, abnormal, and sudden change in stock returns occurring in the absence of a major economic event. As it endangers the primary objective of individual investments, which is to generate profit, its escalation can lead to investor pessimism and capital withdrawal from the stock market. Considering this, the aim of this article is to present a model of the impact of tax avoidance, discretionary accruals, and financial constraints on stock price crash risk. This research is correlational in nature, utilizing regression analysis to determine model coefficients. Furthermore, based on its purpose, this research is categorized as applied research. The statistical population of this study includes all companies listed on the Tehran Stock Exchange during the period from 2012 to 2021, comprising 1,250 firm-year observations. The results indicate that corporate governance moderates the effect of tax avoidance on the future stock price crash risk. Additionally, corporate governance also moderates the effect of discretionary accruals on future stock price crash risk. Discretionary accruals have a significant effect on future stock price crash risk, and financial constraints also have a significant effect on future stock price crash risk. The findings reveal that corporate governance, as a moderating variable, does not influence the relationship between financial constraints and stock price crash risk.

In the past, most of the financing process was to provide cash resources for the purchase of commercial goods, with the complexity of the business process and the way companies operate, the liquidity needs also changed. As a result, traditional financing methods were no longer able to respond to new needs. The expansion and increasing complexity of financing issues, as well as the introduction of new financing tools at the international level, have caused the financial system to require the introduction of new tools in order to achieve its goals. In this research, we seek to explain the pattern of implementing new methods of financing in order to increase the speed and transparency of financial reporting in private banks in the country. In this research, the fuzzy Delphi method has been used to prioritize and present the pattern of financing technologies. The statistical population consists of 25 academic experts in the field of accounting and information technology. The results showed that international money transfer technology, money transfer or remittance technology, payment technology, lending and crowdfunding technology, insurance technology, financial management technology and capital markets technology respectively have the greatest effect on increasing the speed and transparency of financial reporting.

The use of artificial intelligence has increased significantly in most jobs, and the auditing profession is no exception. Artificial intelligence systems have significantly changed the auditing process. However, opponents of the AI revolution see this development as a step backwards, as do many auditors who cannot adapt to the new changes. Meanwhile, the issue that is important in the beginning is auditors' perception of the function of artificial intelligence in audit quality, because auditors' perception of artificial intelligence plays an important role in its application by auditors. Auditors' perceptions are dependent on important variables such as perceived ease and perceived usefulness. Therefore, the main goal of this research is to analyze auditors' perception of artificial intelligence and its contribution to audit quality. This research is applied in terms of purpose and descriptive survey research in terms of method. Research data was collected using survey method. The statistical population of auditors was a member of the Iranian Auditing Association. The research sample included 84 people who completed the research questionnaires online. The standard questionnaires of Davis (1989) and Alvit and Frijat (2021) were used to collect data. To check the research hypotheses, first the normality of the data was checked and then the statistical methods of single sample t and multivariate regression analysis were used in Spss software. The results of the hypothesis analysis showed that the auditors' perception of ease of use (difference with the mean point = 0.174), perceived usefulness (difference with the mean point = 0.786) and the perceived contribution of artificial intelligence in audit quality (difference with the mean point = 0.403) are higher. They are from the average point and it shows the auditors' positive perception of artificial intelligence in auditing. Also, the results showed that both ease of use perception and usefulness perception variables play a significant role in predicting the perceived contribution of artificial intelligence in audit quality (F=60.205, P=0.000). According to the findings of the research, the auditors participating in this research consider the role of artificial intelligence in the audit quality to be positive and meaningful.

The aim of this study was to identify and prioritize new financial provision methods to increase the speed and transparency of financial reporting in private banks in Iran.

The current research method is quantitative and survey-based. The study comprises two populations. The first population consists of 95 banking and economic managers, and the second population includes 30 academic professors with master's and doctoral degrees in accounting, financial management, and information technology. Due to the small size of the first population, census sampling was employed, and for the second population, judgmental sampling with 25 participants was used. Data were collected through a researcher-made questionnaire and a pairwise comparison questionnaire.

The findings of the study revealed that all considered variables, including payment technology, financial management technology, money transfer/remittance technology, international money transfer technology, insurtech technology, lending and crowdfunding technology, and capital market technology, are effective in enhancing the speed and transparency of financial reporting. Moreover, the findings indicated that money transfer technology, insurtech technology, international money transfer technology, capital market technology, financial management technology, lending and crowdfunding technology, and payment technology, in order of importance, have the highest significance in increasing the speed and transparency of financial reporting.

Financial system planners can focus on prioritizing new methods of financial provision to enhance the speed and transparency of financial reporting.

The aim of this research is to identify financial and non-financial metrics that affect companies' sustainability performance, which can be utilized to develop current financial reporting in order to provide comprehensive information on companies' performance to assist in better decision-making.

The present study was conducted using the thematic analysis method and MAXQDA 2020 software. The research population consisted of experts (university faculty members, students, and doctoral graduates in finance, economics, accounting, and management), selected through snowball sampling. Data were collected through semi-structured interviews with experts until theoretical saturation was achieved. In this study, theoretical saturation was confirmed after conducting 26 interviews.

In these interviews, experts suggested various financial and non-financial metrics in economic, social, and environmental dimensions for measuring and reporting companies' sustainability performance. Economic metrics include sales growth, research and development, liquidity growth, financial leverage, company growth opportunities, industry competition, intangible assets, gross domestic product, company age, financial incentives, CEO duality, stock liquidity, board independence, corporate governance, ownership structure, company size, return on equity, economic value added, earnings per share, and return on assets. Social metrics include ethical conduct, job security for employees, and corporate social responsibility, while environmental metrics mentioned by most experts include waste and effluent management and clean (green) production.

It can be concluded that considering globalization and attention to social and environmental issues and responsibilities alongside corporate profitability goals, and the necessity of considering stakeholders' interests in the new corporate governance doctrine, reporting on companies' sustainability performance is not only a need but a necessity for companies in the global competitive arena and as a strategic advantage.

 The purpose of this study is to evaluate the commercialization indicators of accounting research with a fuzzy approach. The study population is experts and academics and professors of accounting. Based on purposive sampling technique, 15 people were selected as the sample. First, the criteria were identified using fuzzy Delphi technique and then the indicators will be ranked. The Demetel technique will be used to identify the pattern of relationships between the relationship criteria. According to the network of identified relationships, the fuzzy network analysis process (FANP) technique is finally used to rank the elements. Super Decision and EXCEL software were used to perform network analysis calculations. Based on the results, 8 main indicators and 52 sub-indicators were identified for the commercialization of accounting research. The main indicators are: scientific validity, applied research, organizational, cultural, individual, environmental, political and economic identified. Based on Delphi technique, 52 sub-indices were screened and confirmed. 8 main indicators were also ranked in network analysis technique. The scientific credit index has the highest rank.

Corporate social responsibility approaches are becoming increasingly widespread since environmental performance is a significant aspect of developing a firm socioemotional wealth, such as legitimacy, trustworthiness, and image. This study investigates the moderating role of managers’ emotional intelligence on the relationship between research and development costs and the social and environmental responsibility of manufacturing companies in the Tehran Stock Exchange. This research is applied and correlational. One hundred thirty-two companies were selected as sample companies that were active in the Tehran Stock Exchange during 2010-2020. The data is collected from the actual financial statements of the companies through the Kodal website, and it is compiled using Excel software. The method of testing the hypotheses is moderator regression (hierarchical), and Eviuse 12 software is used to test the hypotheses. The findings reveal that research and development costs have a meaningful relationship with the social and environmental responsibility of manufacturing companies, and the emotional intelligence of managers has a moderating role in the relationship between research and development costs and the social and environmental responsibility of manufacturing companies. The results can help all stakeholders evaluate the level of attention of companies to research and development costs and corporate social and environmental responsibility.

One of the strategies used in active portfolio management is the "network matrix model "which can be used to form different portfolios with different characteristics of stocks or companies. In this study, with the data of 156 companies listed on the Tehran Stock Exchange during the period 2011 to 2018 using the network matrix model and based on throughput accounting criteria, portfolio formation and their performance with the portfolios of the new network matrix model (Defensive, neutral and aggressive stocks) and market portfolio were compared. The results show that the proposed network matrix model portfolios based on throughput accounting criteria have higher performance than the new network matrix model in terms of Sharpe, Sortino, upside potential, and omega criteria. Also, portfolios consisting of stocks of companies with high system performance, in addition to the above criteria, have higher performance in terms of Jensen's Alpha criteria than the new network matrix model, and in terms of upside potential and omega criteria, have higher performance than the market portfolio. The performance of portfolios consisting of stocks of companies with low system performance has a stronger correlation with the market portfolio compared to the new network matrix model.

In this research, using Analytic Hierarchy Process (AHP) and TOPSIS method (TOP) based on financial criteria, earnings per share, dividend per share, operating cash flow growth, earnings per share growth, beta (systematic) risk, volatility Operating profit, stock liquidity and price-to-earnings ratio selected according to the opinions of investment experts, formed a portfolio. Then, the criteria for evaluating the performance of risk-adjusted portfolios according to modern portfolio theory (Sharp, Trainer and Alpha Jensen) were calculated based on monthly stock prices during the 5-year period from 1393 to 1397 and com-pared with the criteria for evaluating portfolio performance according to Marko-witz model. The results showed that the selection of stock portfolio using the mentioned financial criteria and using the Analytic Hierarchy Process (AHP) model leads to the acquisition of adjusted returns with more risk than the Marko-witz optimization model and the TOPSIS model (TOP).

This study with aim to designing a model for fiscal discipline of companies listed in the Tehran stock exchange using logistic regression was conducted. In this regard, in this study, 15 independent variables were considered as dependent variables to explain fiscal discipline. For this purpose we examined of data related on 129 firms that were accepted in Tehran stock exchange during 21/3/2015 to 20/03/2019 and were analyzed using Eviews9 software. The result showed that accordingly with significance level, there is a positive and significant relationship between the previous year's fiscal discipline and audit firm size separately with dependent variable. Also, there is an inverse and significant relationship between exchange rate fluctuations, earnings management, audit firm rotation and credit risk with fiscal discipline. However, for other explanatory variables, no significant relationship was observed with the dependent variable.

Banks as the largest financial intermediaries play a vital role in collecting savings and directing them toward manufacturing activities. Hence, assets and liabilities management is crucial for them and their depositors. In this study, through system dynamics approach, a dynamic model was proposed to manage assets and liabili-ties optimally. After building the model and conducting validation and sensitivity analysis, three scenarios were devised and were simulated and analyzed via the proposed model. The results revealed that taking effective decisions and actions to collect more deposits, especially time deposits as well as increasing the quality of credit assets (if allocated optimally) can be effective in improving the performance of banks. Therefore, using systems thinking and system dynamics can aid banks in managing their assets and liabilities optimally. mary of the significant items in the paper, including the results and conclusions.

The aim of the current research is to relate managers' narcissism with company value and the moderating role of corporate social responsibility performance. In terms of purpose, the research is applied and correlational. In this regard, 132 companies were selected as sample member companies that were active in the Tehran Stock Exchange during 2019-2020. In order to check managers' narcissism, managers' cash bonus index was used, to measure the company's social responsibility, the corporate social responsibility disclosure checklist in Iran was used, and to determine the company's value, Kytobin was used. The research data was collected from the real financial statements of the companies through the Kodal website and compiled using Excel software. The method of testing the hypotheses is multivariate regression using Eviuse 12 software. The findings showed that managers' narcissism has no significant relationship with company value. Corporate social responsibility performance does not have a moderating role on the relationship between managers' narcissism and company value. The results of this research add to the development of the literature related to managers' narcissism and company value.

The present study aims to examine the relationship between emotional intelligence and narcissism of managers with the firm value . In terms of its purpose, the research is an applied and correlational type of research. The research data was collected from the actual financial statements of the companies through the Kodal website and a standard questionnaire and compiled using Excel software. The method of testing the hypotheses is multivariate regression using the statistical software Evioz 12. The number of samples is 132 companies. The findings show that managers' narcissism has a negative and significant relationship with firm value. And managers' emotional intelligence has a positive and significant relationship with firm value. The findings of this research can be examined from two theoretical and practical aspects. The theoretical aspect that leads to a better understanding of the literature related to emotional intelligence and narcissism, which is one of the important dimensions of the psychological personality of managers, and the practical aspect that helps investors and other real and legal stakeholders to consider managers' narcissism when making decisions. Because narcissism can affect managers' judgment of the possibility of different outcomes.

Narcissism, which is considered as a personality structure, can affect managers' judgments and decisions regarding the possibility of various outcomes. Narcissism among managers plays a vital role in carrying out activities related to corporate social responsibility and research and development costs. Based on this, the aim of the current research is to relate managers' narcissism with research and development costs based on the moderating role of corporate social responsibility performance. In this research, two measures of managers' cash rewards and the size of managers' signatures have been used to measure managers' narcissism. In terms of purpose, the research is applied and correlational. In this regard, 132 companies were selected as sample member companies that were active in the Tehran Stock Exchange during 2019-2020. The research data was collected from the real financial statements of the companies through the Kodal website and compiled using Excel software. The hypothesis testing method is multivariate regression using Image J and Eviuse 12 software. The findings showed that managers' cash bonus and the size of managers' signatures have no significant relationship with research and development costs. The company's social responsibility performance has a positive and significant relationship with research and development costs. The performance of social responsibility of the company does not have a moderating role on the relationship between managers' cash rewards and the size of managers' signatures with research and development costs. The results of this research add to the development of the literature related to managers' narcissism and research and development costs.

Despite the past and present value of auditing, what may be of concern is the role that auditing will play in the future. The bottom line is that traditional auditing is heavily influenced by the growing power and capabilities of information technology systems. In this research, related models and variables have been identified to identify the factors affecting e-auditing in government agencies and affiliated to the Iranian government.

Content analysis method was used to identify the variable. The interviews were coded using maxqda software. The results showed that the results of defining the qualitative data collected using the interview tool, 62 open codes among 171 concepts were identified.

Then, based on the studied models on research variables, general criteria were extracted. In this study, the sample size has been considered to the extent of saturation of experts and specialists who deal directly with this issue in government and government-affiliated agencies in Lorestan province, Koohdasht city. In this research, the opinions of 10 experts have been collected.

Finally, based on the results, 10 categories have been identified, including electronic audit information, electronic audit infrastructure,

Economic agents are not rational against neoclassical theories, and do not act rationally because of their preferences or because of cognitive errors. Unreasonable factors such as personality traits, culture, religion and ideology of emotions, opinions of others and so on. Among the factors that play an important role in the behavior and reaction of individuals in different decision making situations, the purpose of this study is to explain the appropriate model of stock investor risk-taking power based on personality characteristics using exploratory factor analysis and structural equation modeling. The purpose of this study is applied research and is in the category of causal research. The research population included experts and investors who used a 35-item questionnaire to identify the indices that were validated and validated after data collection. Was used. Exploratory and confirmatory factor analysis was performed using SPSS software (PLS) for data analysis. According to the data analysis, the findings and statistical data of this study show that the four dimensions of personality sub-factors have a significant and positive effect on investor risk-taking, so it can be concluded that the personality and risk-taking of investors can be concluded. There is a strong relationship with the results of the present study.

In this study, we first calculate and estimate the efficiency of all banks listed in the Iranian Stock Exchange in the period 2012-2012. This estimation is made using the model of Eegner et al. (1977). Then, using the three-stage model presented by Shrews & Dahl (1992), Kay Van & Eisenberg (1997) and Altonbass et al (2007), using the Simultaneous Equation Path Analysis method to investigate the relationship between productivity, risk and We have capitalized and calculated the direct and indirect impact of these variables and their impact on each other. The results show that the model used is appropriate and there is a significant relationship between these three variables. The data obtained from this analysis, based on the adjusted coefficient of determination obtained from the research model, show that the impact of productivity and banking risk on capital is greater. Keywords: Banking Productivity, Banking Risk, Capital, Route Analysis

Empowerment is not the process of dividing a fixed amount of power; it is a process by which the relative power of each person increases, and a new power is created for the organization. Empowerment is a qualitative influence that must be created. Distorting financial statements involves manipulating the constituent elements by providing more than real assets, selling and earning, or offering less debt, costs, and losses. In cases where financial statements contain distortions, it is said that fraud has been committed in such a way that the constituent elements of that financial statement do not represent reality. In spite of numerous foreign investigations regarding the discovery of fraud in financial reports, this issue has not received much attention within the country. Therefore, the present study investigates the relationship between managerial capability, political communication and fraudulent financial reporting in Tehran Stock Exchange. The present research is based on the objective classification of applied research. Also, to estimate the above models, regression estimation is used by panel data. The statistical population of the study includes all companies accepted in Tehran Stock Exchange and the research period is from 2013 to 1396 for a period of 5 years. The results of the research indicate that the existence of powerful executives in companies has led to a reduction in fraudulent financial statements. It was also found that political communication reduced management ability in the event of fraudulent financial reports.

Subject and Purpose of the Article:

 Accounting knowledge has entered the field of research through research training. In this study, the commercialization factors of doctoral dissertations in accounting have been modeled. The main purpose of this research is to identify the effective factors and to present an appropriate model for commercialization of   doctoral dissertations in accounting.

This research is qualitative in terms of approach and exploratory in terms of purpose. Data were designed through a questionnaire and distributed electronically among 300 accounting professors and collected comments. On the other hand, doctoral dissertations in accounting from 1993 to 2021, including 116 relevant dissertations on the subject of commercialization were reviewed.

Individual, cultural, organizational, environmental, political and economic factors are effective in providing a conceptual model for the commercialization of accounting doctoral dissertations. level of  public sector audit quality proposition.

 Conclusion, Originality and its Contribution to the Knowledge:

The results showed that the economic factor with a weight of 5.89 in the first rank and the individual factor with a weight of 4.74 in the second rank and the environmental factor with a weight of 3.36 in the third rank and the cultural factor with a weight of 3.06 in the fourth rank and the organizational factor and Politics with an average rank of 2.83 and 1.12 are in the fifth and sixth ranks, respectively. In this research, for the first time, the commercialization of doctoral dissertations in accounting has been investigated.

Financing decisions for investment are one of the important tasks of the company in determining the best composition. On the other hand, how to finance the company’s assets for individuals and institutions is important, and how much debt and stocks the company has used to finance its assets, is important because it depends on the company’s financing decisions will be affected. This study investigates the application of nonlinear mathematical modeling in panel data analyses of the pecking order theory in capital structure using multiple regression in the Tehran stock exchange. The research period is from 2014 to 2019. In this research, panel data regression has been used to test the hypotheses. To collect information and data, the library method, and to test the research hypotheses, panel data and panel analysis using multiple regression have been used. The main hypothesis of this research is based on the fact that in order to Management decisions about the optimal capital structure of the company can be based on the theory model of the pecking order. In the results of this study, it seems that the companies in question to finance themselves, in fact, follow the mathematical model used in the theory of pecking order.

 Fiscal discipline provides a mechanism for maintaining financial health and a favorable vision for listed companies by matching revenue and expenses with goal achievement programs (GAP), which, if realized, can ensure the success of these companies. Thus, this study was carried out aimed to identify and explain the factors affecting the fiscal discipline of companies listed on the Tehran Stock Exchange. The present study is considered as an applied research in terms of purpose and as a descriptive survey research in terms of method. In this study, population is listed companies that 114 companies have been selected as a sample using systematic sampling method. Analysis of research data was done using artificial neural network (ANN) and two-layer perceptron and Matlab software. The results show that the most important factors affecting fiscal discipline include financial health, financial stability, debt growth rate, capital expenditures, profitability, and firm value and information uncertainty of companies.

Investors, shareholders, financial analysts and other stakeholders pay special attention to the figure of profit reported in financial statements as one of the main factors in decision-making. Hence the recognition of earnings management in the financial statements is very important. The main objective of this research is to investigate the effectiveness a model to specify the earnings management level by combining two data-mining techniques including a Bayesian networks and a decision tree. To do so, 24 variables have been used as the independent variables affecting earnings management and discretionary accruals as the dependent variables replacing earnings management.In this study the recommended method by Dechow et al (2012) was used to measure the earnings management. The research's statistical population included listed companies on the Tehran stock exchange, active in automotive and parts manufacturing industry and device constructions during years 88-93. The research findings indicate that the hybrid model of Bayesian networks with the C5.0 decision tree has a high capability to characterize the level of the earnings management in the automotive and parts manufacturing industry. The most important known variable by the hybrid model to identify the level of the earnings management in the automotive and parts manufacturing industry is performance threshold variable with the significance ratio of 100%.

The purpose of this study was to an investigation of financing costs factors on the auditor's qualified report in companies listed in Tehran stock exchange. The criteria considered in this study were the audit firm size, auditor's specialization in the partner level, auditor's selection tenure and audit fees. For this purpose, five hypotheses were developed and data related to 85 companies of Tehran stock exchange for the period 2009-2014 were used. To test them, the multivariate regression technique was applied to panel data. The results of the first hypothesis indicated that there was no significant relationship between the audit firm size and qualified audit report. According to the second and third hypotheses, there were significant positive and negative relationships between auditor's specialization in the partner level and audit firm with the qualified report, respectively. The fourth one regarding the relationship between the auditor's selection tenure and qualified audit report was rejected. The fifth hypothesis results also indicated that there was a significant negative relationship between audit fees and qualified audit report.