جستجوی مقالات مرتبط با کلیدواژه "مدل ها" در نشریات گروه "حسابداری"

Manipulation of information and financial statements of companies leads to the occurrence of fraud and restatement of financial statements, which causes the loss of people's capital and ultimately leads to the bankruptcy of companies. These issues have raised concerns about the quality of information in financial statements and the decision-making of companies' financial information users. Due to the importance of this issue, predicting the occurrence of these manipulations and the factors affecting them have always been the focus of analysts, investors, managers and researchers. The purpose of this research is to compare the performance of linear models and artificial intelligence in the field of predicting manipulation of financial statements. Dechow's linear model and Bayes networks artificial intelligence model were considered to compare the performance for predicting manipulation of financial statements. This research is applied in terms of purpose, post-event in terms of data, and descriptive-correlation in terms of analysis. The population of the research was all the companies listed on the Tehran Stock Exchange in the period from 2017 to 2022, and the samples were selected using the systematic elimination method with restrictions. The criteria for selecting companies with manipulation of financial statements is the presence of an unqualified audit opinion with a conditional clause subject to distortion in financial data or the existence of tax disputes with the tax area according to the income tax reserve note and tax file and the condition clause of the audit report or the existence of significant annual adjustments financial updates were provided. Research data has been collected by means of library and document mining methods and has been analyzed with Eviews software. The results showed that the Dechow model with 68.88% correctness and Bayes networks with 90% correctness have the ability to predict the manipulation of financial statements among companies listed on the Tehran Stock Exchange. Also, according to the research results, the performance of artificial intelligence models such as Bayes networks is better than linear models such as the Dechow model.

The results of the model estimation show that information transparency has a significant and positive effect with an impact factor of 0.08 at a significance level of one percent. Therefore, it can be said that information transparency as a component of corporate governance has a significant effect on the economic growth rate of listed companies. Also, the results of the model estimation show that audit quality has a significant and positive effect with an impact factor of 0.10 at a significance level of one percent. The duality variable of the CEO and the chairman of the company's board of directors has a significant effect on the economic growth rate with an impact coefficient of 0.012 at a significance level of five percent, and the concentration of ownership as a component of corporate governance has a significant effect on the economic growth rate. Examining the estimation results of the model shows that the concentration of ownership or the influence coefficient of 0.03 at the significance level of five percent has a positive and significant effect on economic growth. Also, the size of the board of directors as a component of corporate governance does not have a significant effect on the economic growth rate of companies. According to the findings of the research, the variable of institutional ownership of the percentage (ratio) of institutional ownership to the total number of shares of the company has an impact coefficient of 0.02 at a significant level of five percent.

The present study seeks to assess stakeholders’ perceptions and expectations of external accountability of certified public accountants (CPA) and its impact on the level of public trust and efficiency of reports published by this public institution. The statistical population of this study is a group of key external stakeholders that includes the government, the labor market, and the scientific community. The sample also includes 44 faculty members, 51 financial managers, and 46 government experts. The model used in the present study is the SERVQUAL model, which tries to measure the quality of services by analyzing the gap between customer expectation and perception. Also, the data collection tools in this research are three methods of interview, library studies, and questionnaire. The results show that increasing the level of external accountability improves public trust and better performance of CPAs.

The main purpose of this research is to present the maturity model of forensic accounting in Iran in order to identify and evaluate the dimensions and components affecting forensic accounting in Iran by providing a desirable and evolutionary model using the five-level maturity model of integrated maturity capability (CMMI) and the path of professional excellence and reaching higher levels will be specified with the leveling of components and finally it can be a guide for the necessary actions of professional members and trustees to reach the best status of the profession.The method of conducting the research is based on the objective of the applied type, and in terms of its nature, it is a qualitative research, and data collection was done using interviews. So that initially by studying documents and articles, the primary dimensions and components affecting the maturity of forensic accounting in Iran were identified. In the next stage, semi-structured interviews were conducted between 2023 and 2024 with twenty-one academic and professional accounting experts and official accounting justice experts who were selected using snowball sampling. By using the interviews, some of the identified dimensions and components were reviewed. After conducting interviews with experts and reaching theoretical saturation by the researcher, the data obtained from the interviews were analyzed and coded using theme analysis, and the dimensions of the forensic accounting maturity model in Iran were identified and presented to the owner. The comments were refined and approved. Based on this, the dimensions of Iran's forensic accounting maturity model include services and roles, professions and institutions, human resources, information technology, reporting, continuous improvement, service quality assurance, each of which was presented in five levels in the current research. The results of this research provide a comprehensive framework to evaluate the forensic accounting profession in Iran and will play an effective role in improving the status of the profession and can be used as a benchmark for planning the members of the profession.

Restatement of Financial Statements , which means re-presenting last year's financial information in order to correct incorrect information or increase comparability, is one of the common phenomena in Iran, which causes investors to lose confidence in the credibility and competence of management and the quality of reported profits. The purpose of this research is to present the development model of Benish fraud in companies admitted to the Tehran Stock Exchange between 2008 and 2019. The data of 265 companies were extracted using the selected and final indicators of Benish's (1999) fraud model, and neural network and genetic algorithms were also used to develop the prediction model. The results of the research indicate that based on the confusion matrix, the accuracy and efficiency of the improved Benish model with the combined algorithm of neural network and genetics in predicting unrepresented companies was 78.15%, and re-presented companies was 29.63%. . Also, the overall accuracy of the model presented with the combined algorithm of neural network and genetics was 73.21%.

Making the optimal investment and choosing the right investment project is the most important challenge facing the owners of capital in the financial markets. Examining issues such as profit management, the market situation and reaction to financial and non-financial events, studying the behavior of financial providers, the status of shareholders will lead to gaining relative knowledge of them by considering some variables and with this knowledge, the project Choose suitable for investment. In this research, in order to check the validity of methods of measuring investment opportunities in companies, independent variables: reputation, company size, profitability level, leverage level and systematic risk were evaluated. The time domain of this research is a 6-year period in which the selected companies of the Tehran Stock Exchange were studied in the years 1395 to 1400 and in this study 81 companies were considered as a statistical sample in each year. have been According to the results of the tests conducted in this research and similar researches, with the exception of the variables of leverage level and profitability level, with Spearman's correlation coefficient values ​​of 0.018 and 0.001, respectively, between other variables and investment opportunities in the territory's companies. This research has no relationship.Therefore, according to the results of the research tests, the Myers model is not a suitable model for predicting investment opportunities in the companies of the research territory or in the country of Iran.

The present research proposes a structural model of the factors influencing risk appetite in exchange-listed banks (focusing on human resources in Tehran). Therefore, a mixed-method research strategy of a sequential exploratory design (qualitative-quantitative) was employed. In the qualitative phase, using the Grounded Theory paradigm proposed by Strauss and Corbin (2018) and conducting semi-structured interviews with 15 experts in the relevant field, who were selected through purposive (in the first step) and theoretical (in the second step) sampling, the construction of a paradigmatic model was initiated. In the quantitative phase, data were collected from 384 human resources in the Tehran-based exchange-listed banks using a survey questionnaire developed by the researcher. Sampling was done through Cochran's formula and proportional stratified sampling method. The data were analyzed using SPSS version 26 and Smart PLS3 software. The results of data analysis indicated that a significant difference exists at the 0.01 level (P < 0.01) in the current and desirable status of the overall index and the six elements of the structural model of factors influencing risk appetite in exchange-listed banks among the human resources of exchange-listed banks in Tehran. This implies that the empirical structural (path) model and the reflective measurement of factors influencing risk appetite in exchange-listed banks fit and are consistent.

According to Moradi et al.'s article (1401), the auditing paradigm model of the supreme audit court in the process of granting facilities to knowledge-based companies was extracted by the qualitative method and applying the grounded theory research method. The purpose of this study is to measure and prioritize the dimensions and components of the above model by means of a questionnaire extracted from the findings of Moradi et al.'s article (1401).This research has been done using a quantitative descriptive survey method and using the structural equation model as well as Friedman's test. The statistical population of the research included all the employees of the supreme audit court, based on Cochran's formula, 342 people were selected as the sample size and it was done by simple random sampling. For data analysis, the structural equation model was used under smartpls3.3 software. The results of the findings indicated the fit of the initial model, so that the causal conditions (human resources and organization of the supreme audit court, personal and professional characteristics of the auditor), contextual factors (the position of the supreme audit court and society's demands from it, legislation and enforcement and monitoring institutions) and Intervention conditions (international conventions and standards, information technology, limits of disclosure and politicization, culture and values of society) is effective on the central phenomenon (auditing of the supreme audit court in knowledge-based companies) and the central phenomenon is on strategies (the auditing of the supreme audit court, the supporting organization of the knowledge company, examination of knowledge-based companies, internal control of the supporting organization) are effective and finally the strategies are effective on the consequences (results for the beneficiaries).

The use of traditional variables and patterns in explaining the factors affecting the management of real and accrued earnings has faced many challenges in the literature. This article tries to fill this gap by considering different variables in the context of traditional and new theories and by using Bayesian econometrics and panel data related to 131 listed companies during the period 1380-1388. First, the determinants of real and accrued earnings management are explained theoretically, then using the "Bayesian model averaging" method; The profit management model is estimated and after calculating the variables, its effect on price manipulation is determined. Based on the results, both real profit management and accrual management have a significant effect on price manipulation in both high and low price manipulation business cycles. It has an asset index.
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This study aims to uncover the factors influencing the acceptance of integrated reporting. The goal is to find how attitudes and behavioral intentions of university managers could be positively influenced and how the adoption of integrated reporting can be made easier.

To achieve the research goal, a quantitative research design was used. Questionnaires were used to gather the required data. They were filled out by the board of directors' members, including the University president, Vice president of education, Vice president of research and technology, Vice president of finance and administration, Vice president of culture, Vice president of students, and Director of monitoring and evaluation, from 30 leading public universities in Iran. The obtained data were analyzed by fitted structural equations. The criterion used to select the top universities was the most recent ranking listed in the reference database of Islamic World Sciences.

The final version of the acceptance model of integrated reporting showed that the acceptance process consists of four consecutive and path-dependent stages. The stages include knowledge; attitude (persuasion); behavioral intention (before decision); and acceptance or rejection (decision). Each stage is influenced by several innovation-specific or individual-specific variables. The specific variables of innovation include the characteristics of integrated reporting perceived by university senior managers, including perceived relative advantage, compatibility, lack of risk, and lack of complexity. The individual characteristics of these managers, such as mental norms and perceived behavior control, as well as determinants of change like perceived necessity, obligation, and guidance, are considered. Based on the presented empirical evidence, it can be claimed that the process of accepting integrated reporting in Iranian universities aligns with the Rogers decision-innovation process model. Therefore, the adoption of this new way of reporting, like many innovations, goes through the stages of knowledge, attitude, intention, and behavior. Meanwhile, the factors affecting each stage show their effects hierarchically through the mediating variables mentioned.

This research emphasizes the importance of a process approach in studying the dissemination and adoption of integrated reporting. It urges researchers to meticulously explore the hierarchy of innovation factors or specific variables, along with individual variables, understanding their impact mechanisms thoroughly. The outcomes of this research can inform the development of policies by the Iranian Ministry of Science regarding university reporting practices. The findings of this research determine how to smooth the path of acceptance of this new way of reporting. Research findings also demonstrated that decision-makers in the realm of adopting integrated reporting are primarily swayed by the perceived characteristics of this reporting method while paying minimal heed to its inherent features. The results obtained help planners to focus on trying to create a positive perception of people about the features of this innovation instead of focusing on the technical issues of integrated reporting. Therefore, it is advisable to conduct workshops, publish books and articles, and employ other methods of information dissemination and persuasion to enhance individuals' comprehension of the relative advantages and compatibility of this reporting method. This can alleviate concerns about the complexity of implementation and the risks associated with its adoption failure. Also, it is recommended that the administrators provide the necessary facilities for accepting integrated reporting and offering the necessary training to university employees. This will establish a foundation for university administrators to appraise positively the readiness of their team to accept and implement integrated reporting. In addition, By generating social pressures from both external and internal stakeholders, as well as reference groups, to develop and publish integrated reports in universities, it is feasible to reinforce the mental norms of university administrators in this direction. With the leading universities of the country taking the lead in this area, imitative mental norms can positively influence managers in other universities.

The purpose of this research is to investigate the mediating role of accounting information systems in the relationship between business strategy and company performance: a comparative study of MISSQM and ISO/IEC models. The currentresearch method is correlation. Managers of all companies admitted in Tehran Stock Exchange were selected as the study population, and among the companies admitted in Tehran Stock Exchange, a questionnaire was randomly distributed among 384 managers from non-financial companies active in 2022. For this purpose, a standardized or quantitative questionnaire was used and the survey questionnaire was distributed among senior managers, financial managers, chief accountants, quality control department managers. For the ISO/IEC model, the questionnaire was developed by the World Organization for Standardization and is provided in Haghighi Nasab and Masoumi’s (2013) research. For the MISSQM model, the scale used by Mahdavi's research (2016) was utilized to measure the quality of informationsystems services. In order to measure and evaluate the organization's business strategy in this research, a questionnaire designed by Zareimetin et al. (2009) was employed. Finally, Hersey and Goldsmith questionnaire (2003) was used to measure organizational performance. The results of hypothesis analysis showed that there is a significant positive relationship between business strategy and accounting information systems and between accounting information systems and company performance. There is also a significant positive relationship between business strategy and company performance. Accounting information systems with the MISSQM and ISO/IEC models played a mediating role in the relationship between business strategy and company performance, and the mediating role of the Iso/IEC model is more robust in this relationship.

This study aims to provide design and validation of the effective size model of internal audit department in Iranian companies. The purpose of this research is an applied-developmental research that has been done by cross-sectional survey method. The statistical population of this study includes the partners and managers of the Iranian Association of certified public accountants and the employees of auditing firms. Sampling of managers was done in a non-probabilistic and purposeful manner and staff sampling was done by random sampling method. The data collection tool is a questionnaire. The validity of the questionnaire was confirmed by construct, convergent and divergent validity. The reliability of the questionnaire was also confirmed by two methods of calculating Cronbach's alpha and combined reliability. Structural-interpretive modeling method was used to design the initial model and partial least squares method was used to validate the designed model. Data analysis was performed with MicMac and Smart PLS software. The results show that "comprehensive internal audit plan" and "corporate governance structure" have the greatest impact on determining the effective size of the internal audit department. These elements affect the "internal audit methodology approach" and the "description of internal audit tasks". Similarly, "human resource management", "risk management" and "internal audit mission" affect the "quality of the audit committee". The quality of this committee affects the "value added of the internal audit" and leads to the determination of the "size of the internal audit".

Forecasting has always been recognized as an important issue in financial markets and is considered a unique factor in estimating future unknown values. The aim of this research is to identify and forecast the conditions of the Tehran Stock Exchange(TSE) and the factors affecting them, focusing on the correlation between market prosperity and value at risk. To achieve this, in the first step of this study, the time series of the value at risk index on the capital market TSE was estimated using daily data and the first-order GARCH method from spring 2010 to June 2023. Then, the factors influencing prosperity in TSE were evaluated based on seasonal data from spring 2010 to June 2023 using the probit regression approach. In addition, value at risk index was calculated seasonally and the relationship between the probability of market prosperity and the value at risk index was examined using correlation coefficients.The research results show that the probability of market prosperity in the Iranian capital market has a significant negative relationship with the bank interest rate, liquidity growth and the occurrence of sanctions. There is also a significant positive relationship with the inflation rate and the growth of the exchange rate. Furthermore, the correlation analysis shows that market prosperity is directly related to equity value at risk. Assuming stable conditions, the research suggests that the probability of a prosperity market in the next three seasons is significantly higher than the occurrence of a recession.

This article examines the ethical challenges of using accounting systems based on artificial intelligence for decision-making and presents the correct decision-making in the framework of the four-component model of Rest. The following article contributes to the literature related to accounting as a mental act as well as the function of an intermediary in the socio-material context It does so by providing a solid base of arguments that AI alone, despite its enabling and mediating role in accounting, cannot make ethical accounting decisions because it lacks the necessary preconditions in terms of Rest’s model of antecedents What is more, as AI is bound to pre-set goals and subjected to human made conditions despite its autonomous learning and adaptive practices, it lacks true agency. The topic has been reviewed among 138 articles from 43 prestigious international accounting journals between 2015 and 2020. In the thematic coding of the selected articles, five major ethical challenges of decision-making based on artificial intelligence in accounting were identified, which are: impartiality, privacy, transparency, accountability and reliability. By using the components of the Rest model for ethical decision-making as a stable framework for the discussed structure, the challenges and their relevance for future human-machine cooperation in various offices between humans and artificial intelligence can be discussed. Therefore, in addition to understanding the appropriate decision-making process in accounting based on artificial intelligence, it is suggested that independent and internal audit processes be adapted in terms of skills and knowledge to ensure ethical decision-making based on artificial intelligence

Uncertainty can have profound consequences for both companies and individuals hoping to make optimal decisions for their benefit. Economic agents in financial markets are generally concerned about uncertainty in the political, economic and environmental spheres. When prior expectations are compromised by the increased likelihood of uncertain outcomes, agents must wait for the waves of uncertainty to dissipate before making sound financial decisions. In this research, the relationship between economic uncertainty shock and illiquidity of the stock market has been analyzed using the Time-Varying Structural Vector Auto-regressive model TVSVAR during the years 2008:4-2020:3. The obtained results indicate that the effect of the economic uncertainty shock on illiquidity was positive and increasing in most of the periods and years under investigation, and the effect of the shock of liquidity volume growth on illiquidity had a decreasing effect in most of the periods and years. The effect of inflation shock on illiquidity increased in all the studied periods and years, but in 2016 and 2020, it had a decreasing effect in the final period.

One of the major challenges faced by major firms is the risk of financial instability and ultimately financial bankruptcy. The managers of distresed and bankrupt firms are more motivated to opportunistic earnings management. , The collapse of companies like Enron, WorldCom and others have led to more research into profit manipulation and bankruptcy in developed countries. However, in the years before corporate bankruptcy, there was also sufficient pressure or incentive to create high-profit management to prevent bankruptcy through poor performance concealment Some researchers believe that earnings management variables can predict bankruptcy. Accordingly, the purpose of this research is to modeling and predict bankruptcy using accrual earnings management tools during the period 2006-2018, in manufacturing firms listed on the Tehran Stock Exchange. The research sample consisting of 1287 observations was selected based on the criteria of Article 141 of the Commercial Code of Iran. Logistic regression was used to test the research hypotheses. Findings from the hypothesis test showed that the predictive power of the Altman, Springate and Zmijewski bankruptcy models increased significantly after the addition of accrual earnings management variables to the initial models.

Gross domestic product (GDP) is one of the key indicators of macroeconomics. Predicting this index is very important in the economic planning of the country, because this variable reflects the general state of a country's economy. So far, many models have been proposed to predict this variable, but models that use accounting information have not been considered. The purpose of this paper is to examine the relationship between GDP and total corporate profits, as one of the known variables in accounting. For this purpose, the quarterly time series data of macro level companies of Tehran Stock Exchange and macroeconomics in the period 2009 to 2018 are analyzed in two stages. In the first step, the relationship between these two variables is determined by specifying a linear regression model that will be estimated using the least squares method. To evaluate the predictive power of this model, the root mean square error (RMSE) criterion is estimated in two scenarios with total corporate profit and no corporate total profit. Second, the GDP response to the shock to firms' profits is estimated through a vector auto regression (VAR) model, and the contribution of this variable to GDP fluctuation is measured. The results show that the profit of all companies improves GDP forecast in the leading horizons. Also, the shock to the profits of all companies, as much as a standard deviation, explains about 28% of GDP fluctuations.

Stock selection and optimal stock portfolio formation depends on various factors which lead to complicate making decision. Investors can maximize investment return and minimize their risk by choosing the optimal stock portfolio. Therefore always they are used to advanced financial algorithms to form the optimal stock portfolio. This study tries to find machine learning and Markowitz models ability in optimal stock portfolio formation and their efficiency comparison. The statistical sample of the present study includes 156 companies listed on the Tehran Stock Exchange during 2010 to 2019. After collecting the data, the deep learning and the Markowitz models were tested using Anaconda software and Python programming language, and then the ability of each model were determined in formation of optimal stock portfolio by portfolio return evaluation criteria, trenors and jensens index.In the ten-share portfolio of the deep learning model; Return of portfolio 0.697, trenors index of 4.541 and Jensens index of 0.480 and in ten-share portfolio of Markowitz model; Portfolio returns of 0.058, trenors index of -1.648 and Jensens index of -0.158 have been calculated. According to the results of the portfolio evaluation, it was concluded that the deep learning model has a higher ability than the Markowitz model in the formation of optimal stock portfolio.