مجید اشرفی

The desirability of the financial reporting can greatly help the users of finan-cial information in making investment decisions. The purpose of this re-search is to measure the readability of financial reporting using a multi-indicator decision-making model and the artificial neural network method and the role of information presentation time in its improvement. In this research, various indicators have been used to measure the readability of financial reporting, and the quality of reporting is obtained through the rank-ing of companies by the stock exchange. In this research, the number of 149 companies admitted to the Tehran Stock Exchange in the period of 2010-2020 was examined, and to measure the financial readability through struc-tural equations and Stata software, and to test the hypothesis of the research, the regression model and Eviews econometrics software were used. In this study, we have tried to Use machine learning techniques and optimization tools as a way to derive adaptive-robust nonlinear models that can reduce the risk of model error as much as possible. The findings of the research show that the time of providing information has an impact on the readability of financial reporting. The obtained outputs from the estimation of the artificial neural networks and results obtained from estimation, using of this method with evaluation scales concerning random amount and comparing it with adjusted R, we found that there is meaningful relation between the associated variables and return. However, such network has the least error than other networks. The results show an overall improvement in forecasting using the neural network as compared to linear regression method. In other words, our proposed system displays an extremely higher profitability potential. The obtained result can be argued that the more the company's information is provided by the managers to the company's shareholders and investors on time and at the right time, the more readable and understandable the financial reports will be.

The purpose of this article is to present the evolutionary model of loan sales using collective intelligence and meta-heuristic algorithms (bird flight algorithm). In terms of method, this research is in the category of quantitative research, and in terms of purpose, it is included in the category of applied research. The statistical population includes all active companies admitted to the Tehran Stock Exchange. This research has been investigated between 2011 and 2019 for active companies admitted to the Tehran Stock Exchange. The method of data collection is through library study and financial data of companies admitted to the stock exchange by referring to the financial statements and explanatory notes with the financial statements, and it has also been compiled using the Rahavard Novin software. Also, with the help of EViews 9 and MATLAB software, he presented a borrowing sales model, and in the next step, with the help of MATLAB software and the flight of bird's algorithm, he presented an evolutionary model of borrowing sales, in the end, by comparing the step-by-step regression model and the borrowing sales model. The findings showed that the borrowing sales model with the help of the bird flight algorithm has a higher efficiency.

The flow of information in the capital market is strategically important because it determines the path of investors' decisions. In this decision-making process, the managers of the companies can disclose timely and reliable information based on their cognitive and perceptual characteristics of capital market situations. This article aims to contribute to the capital market knowledge literature by presenting the framework of managers' inertia drivers in response to reliable disclosure of information. This study adopted mixed, both inductive and deductive approaches to develop an integrated framework, validate its practicability, and verify its effectiveness in selected firms listed on the Tehran Stock Exchange, respectively. In developing the framework and implementation procedure, the study employed a systematic screening data collection (qualitative) approach to review the managers' inertia drivers. Then, in this study's second phase, the Interpretive Rating Process (IRP) and Fuzzy Reference System are used to develop the framework of managers' inertia drivers in response to reliable disclosure of information. The study's results in the qualitative part indicate the determination of 8 driving areas of managers' inertia in the reliable disclosure of information. On the other hand, the quantitative section results showed that managers' overconfidence and excitability are the most influential fields in stimulating managers' inertia in the timely disclosure of information. Based on the results, it was determined that the excitability of managers' overconfidence in creating inertia causes managers' subjective estimates to cause exclusivity in information disclosure.

Technological orientation is one of the competitive functions in the capital market, which can be considered as a basis for evaluating the advantages of companies in achieving strategic goals. The purpose of this study is to investigate the effect of geographical location on the technology capabilities. In this study, resource based view (RBV) has been used to develop the research hypothesis. In this study, first, using data envelopment analysis (DEA) method to measure the technology capacities of companies then, considering that the dependent variable of the research was measured as 0 and 1, based on logistic regression, the research hypothesis was tested. The result of testing the research hypothesis was that the level of significance of the coefficient of variable geographical distance (DIS) has a negative and significant effect on the technical efficiency vector (TEV). This result, based on the test of the theory of resource reliance theory, indicates the fact that the existence of a geographical distance from the center can affect companies' access to competitive resources, and in this situation, reduce the capabilities of their core technology compared to competitors. This study is one of the few studies that examines the effect of technology capability on the geographical distance of petrochemical companies and its results can help strengthen the strategic decisions of companies. Therefore, based on this, this study can be considered innovative because it helps to develop theoretical literature and strategic decision-making implications.

Rising inflation in recent years has caused financial distress and many problems for companies. Most of these problems are affected by life cycle stages. One way out of these problems is to increase corporate social responsibility (CSR) performance. Therefore, our aim in this study is to investigate the effect of CSR performance on financial distress over the life cycle of the company for a period of 10 years. Data collection was done through the website of the Tehran Stock Exchange and related software for a sample of 112 companies during the period 2009 to 2019. The mathematical method (directional distance function) is used to evaluate the CSR performance, and the models of Berger et al., Almida, Campello, and Altman are used to measure financial distress. The research hypotheses are tested using panel data and fixed effects by multivariate regression statistical method. The results show that CSR performance alone does not affect financial distress. The combination of CSR and life cycle in the growth and maturity phases has a significant and negative effect on financial distress. The CSR performance and life cycle together reduce financial distress. The combination of CSR performance and life cycle in the recession phase has a positive and significant effect on financial distress and in the fall phase, does not affect it. Given that companies compete more in the phase of growth and maturity than other phases of the life cycle, they also pay more attention to CSR. Therefore, according to these results, it can be concluded that the life cycle of the company and the CSR performance together, reduce financial distress.