محمدابراهیم محمدپورزرندی

Liquidity management is one of the biggest challenges of the banking system. One of the problematic factors in liquidity management is that some loans, which are defined as non-performing loans, do not return to the liquidity cycle. The prediction of non-performing loans helps in the optimal management of banks' cash. Forecasting is possible by extracting the determining factors and using a suitable forecasting model. Therefore, this study was conducted with the aim of predicting the management of cash flow in non-performing loans of banks in three stages. In the first stage, all related factors were extracted and categorized using the meta-synthesis method and extensive background review (review of 194 articles). The categories included 10 classes of determining factors (95 factors), 11 mitigation strategies and 12 consequences. Due to the multiplicity of factors, it was not possible to include all of them in the prediction model. Therefore, in the second stage, the most important determining factors were selected by conducting three Delphi rounds and using experts' opinions. The output of this stage was the selection of 4 macroeconomic variables and 5 bank-specific variables. In the third step, the data of model variables for the years 1389 to 1400 were extracted and three machine learning algorithms, random forest, K nearest neighbor and Tobit logistic regression were used for prediction. The results showed that the prediction accuracy of random forest algorithm is higher than other used models.

This study aims to investigate the impact of the COVID-19 pandemic on stock market volatility, with a specific focus on the role of economic policies. The primary objective is to identify and analyze how the stock market responds to the COVID-19 crisis and the influence of economic policies on these responses. 

To achieve the research objectives, the Smooth Transition Regression (STR) model was used to analyze stock market data from 1991 to 2022. Initially, stock market volatility was calculated using the ARCH and GARCH models. Then, the impact of COVID-19 and other economic variables on stock market volatility was assessed using the smooth threshold model.

The findings of this study indicate that the COVID-19 crisis has had a positive and significant impact on stock market volatility. Additionally, changes in economic policies during the pandemic have led to increased market volatility. The study also revealed that during the COVID-19 period, stock market volatility was highly influenced by macroeconomic variables such as interest rates and industrial production indices. 

The study concludes that the COVID-19 crisis significantly increased stock market volatility, largely due to economic uncertainties and investors' psychological behaviors. The findings provide valuable insights for policymakers and market participants in better managing market volatility during similar economic and health crises.

This research sought to find the determinants and consequences of non-performing loans. For this purpose, meta-synthesis method was used and 7 steps of meta-synthesis proposed by Sandelowski and Barroso (2007) were implemented. The intended sample for meta-synthesis consists of selected studies based on their relationship with the research question. In the present study, the initial sample included 194 sources related to the research topic, which were extracted from databases without time limits. After screening the sources in terms of various items such as title, abstract, content and quality, 151 sources remained, whose results were examined more precisely and combined with each other. The result of this process was the extraction of 118 codes, which were categorized into 10 categories of determinants, 11 strategies to reduce and 12 consequences of non-performing loans. Determinants include international factors, macroeconomic factors, bank-specific factors, industry-related, market, borrower, and loan, political, macro-financial and institutional factors. 36% of determinants were classified in the category of macroeconomics determinants, 31% in the category of bank-specific factors, and 33% in the other 9 categories. Another result of this study is the circular causality observed among the consequences and determinants.

In this article, the goal is to design and present a model to determine the effect of macroeconomic and banking variables on the occurrence of asset freezing in the country's banking system using meta-heuristic models. The current research is applied in terms of purpose, in terms of research method, correlation analysis type and in terms of overall research design, post-event and retrospective. In order to answer the research questions, the annual data of macroeconomic and banking variables, during the period of 1399-1390, were collected and using the test of regression models in EViews, Smart PLS software and also the neural network model. It was estimated in SPSS Modeler software. The estimation results of the regression model of the first hypothesis in EViews software showed that the economic variables of GDP, unemployment rate and interest rate, consumer price index, currency strength at the error level of one percent and the economic growth rate variable at the error level of ten percent have a significant relationship. They have a dependent variable (asset freezing). Also, the estimation results of the structural model of the first hypothesis in the PLS software are significantly aligned with the output of the Eviuse software. So; The first research hypothesis is confirmed. Also, the results of the regression model estimation of the second hypothesis in EViews software showed that the intra-bank variable of the bank size ratio, return on equity, and the amount of liquidity at the error level of ten percent, and the variables of capital adequacy, return on assets, bank capital, at the error level of one percent. The percentage has a significant relationship with the dependent variable (asset freezing). Also, the estimation results of the structural model of the second hypothesis in the PLS software are significantly aligned with the output of the Eviuse software. So; The second research hypothesis is also confirmed.

Taxation is one of the main incomes of the government, and the government uses tax incentives as a key tool to improve tax compliance among taxpayers. This study aimed to understand the effects of tax incentives on tax compliance and business outcomes of taxpayers. Considering its purpose, this study is an applied research, and regarding its data collecting method, both field and secondary research methods have been used. In secondary research, we used books, national journals, and relevant articles form national and international databases, while in field research we used direct observations and interviews. Using various methods and tools for collecting the data, we investigated the agents, their interactions with each other and with the environment, and at the end, we analyzed the collected data using AnyLogic software, and the three hypotheses of the article were investigated. The results indicate that the tax incentives for any taxpayer can decrease the corresponding tax perception, which leads to tax compliance and change in the profitability and costs.

The purpose of the current research is to develop a strategy in one of the companies that produce auto parts. Considering today's complex environment, organizations need to develop a strategy to protect their position in competitive markets. The absence of such plans can increase unforeseen crises for companies. Usually, car manufacturing companies outsource the parts needed to assemble cars to parts manufacturing companies in order to reduce their production costs and increase the quality of their products. According to the environmental conditions and their current and future capabilities, component manufacturing companies should choose a suitable strategy to help the survival and growth of these companies in the highly competitive arena of the component manufacturing industry. This research is a descriptive research in terms of method. Information from library and field method has been used simultaneously. In the library method, the method of content analysis and the review of statistics and documents and the field method of questionnaires, interviews and surveys of the senior managers of this industrial plant were used, and the tools used in this research were the matrix of internal and external factors, the SWOT matrix and the QSPM matrix. Since the country's automobile industry is related to more than 60 other industries, the existence of a long-term strategy in this industry seems very necessary. One of these strategies is the existence of the manufacturing industry. To enter the auto parts manufacturing industry, there are challenges related to management, supply chain structure, technical and quality issues, and economic issues. Kosha Afarin Ideal Khodro Industries is an auto parts manufacturing company located at Iran Khodro crossroads in Danesh town. . Nowadays, changes and transformations are very fast and diverse in the automobile industry, and in order to keep pace and be present in this industry and meet the needs of customers, it is necessary to have a strategic planning management. Due to the fact that Ideal Khodro Koshaafrin Industries is one of the parts manufacturers of automobile companies in Iran, strategic planning can play an important role in the success of this company. According to the economic conditions and the factors of the external environment of organizations, especially component companies, the need for strategic planning and the use of new methods is unavoidable. Therefore, during this research, in addition to paying attention to the pathology of the supply of internal parts in the automobile industry, using the matrix of external and internal factors, SWOT has been compiled for this company, and at the end, the best strategy has been selected using the QSPM matrix. The management of the mentioned company should be carefully considered, which according to the obtained results is the best production strategy with the possibility of changing the type of production and product, paying attention to the flexible production system.

The purpose of this research is to provide a model of recognition and evaluation of factors affecting the acceptance of fintechs. The statistical population included experts and experts in the banking industry, who were selected as participants in the research using a targeted sampling approach. The data was collected by interview method with general guidance method and in a semi-structured way. In order to obtain the reliability and validity of the data, two methods of reviewing the participants and also the review of non-participating experts were used in the research. The reliability of the model was evaluated using the Kappa index. The value of Kappa index equal to 0.748 was calculated and it was placed at the level of valid agreement. Interviews and coding were analyzed using Maxqda software. Finally, based on the identified final criteria, the model derived from the foundation''s data analysis method is presented. Based on the results of open coding of qualitative data collected using the interview tool, it can be seen that 60 open codes have been identified among 434 parts of the interviews. All the created codes are reviewed again and compared with the texts so that nothing is missed. In the results of core coding, it can be seen that 60 primary codes are in the form of 15 categories of evaluation and monitoring, public trust and security, interaction and communication, human and social development, satisfaction, infrastructure, administrative and organizational health, transparency and accountability, and core justice. , financial factors, information technology, efficiency and effectiveness, quality of laws and regulations, quality of electronic services and participation are categorized.

This research is a sequential mixed study in the sense that qualitative data from the literature review is first collected through in-depth interviews and then analyzed. After collecting the data and identifying them, the coding stage was done using the Swara method using the opinion of experts. The data was collected according to the reliable information and data of large companies accepted in the stock exchange and the Kodal system, and the reports and financial statements of the aforementioned machinery and equipment industry companies were used. The examined experts are all managers and experts of machinery and equipment industry companies and university professors, who are somehow considered experts in the concepts of the current research.In general, the main goal of this research is provide a model of the financing supply chain that can identify the optimized indicators influencing the financial supply chain in order to improve its performance and introduce the degree of influence of each one.This research creates a model of the financing chain that studies the management and control of risk and obstacles and bottlenecks, as well as the effects of the financing decision, and the relationship between the management of the financing chain and finally shows what Factors can improve and upgrade the production cycle and affect the performance of the company.

One of the factors that has recently been mentioned in order to improve social capital from theeconomic aspect is the fulfillment of tax obligations through education and culture. It seems that the mostimportant result of training taxpayers is to improve the fulfillment of tax obligations, which can lead to theimprovement of social capital. The present research tries to examine one of the important aspects for thefoundation and improvement of tax implementation in the country, which is the training of the tax plan in theeffectiveness of tax implementation. To detect the effects of educational programs on taxpayers' behavior(fulfilment of tax obligations and business results), the factor-based modeling approach, which is a part-towhole approach, has been used. This research is of applied type and its statistical population consists of legalentities of Tehran city and by examining articles in foreign and domestic scientific databases in the field ofresearch, factors were identified and through the tax organization database and questionnaire during the periodof 2014 to 2019, the desired information has been collected. After identifying the factors, the relationshipbetween them and the relationship of the factors with the environment and finally modeling the basis factor andimplementing it in AniLogic software, it was concluded that the training courses held for each taxpayer canimprove the taxpayer's perception of the amount of tax that has been assigned to him. Decrease, which will leadto the fulfillment of tax obligations and improvement of social capital and changes in profitability and costlevels.

The issue of efficiency evaluation is one of the most important challenges facing managers in the dynamic and vital banking industry. Due to the very important and fundamental role of banks in most economic activities, the study of bank efficiency has a special place. Models based on data envelopment analysis had wide applications in the field of measuring and evaluating the efficiency of banks. In this study, we tried to add other assumptions to the traditional model of data envelopment analysis, using a model that is more consistent with the real conditions related to decision-making units and calculates the efficiency more accurately. In designing the data envelopment analysis model in the present study, attention has been paid to the networking and internal relations of each decision-making unit, undesirable output, involuntary input and the fuzzy nature of the variables. After developing the model with the mentioned assumptions, first, based on reviewing previous studies as well as field studies and obtaining opinions from industry experts, indicators considered as input and output. After identifying the indicators, fuzzy Delphi method used for initial screening of the identified indicators from the research literature. After the initial approval of the indices, the indices analyzed using the confirmatory factor analysis technique. Finally, the research model solved using data collected by GAMS software and with alpha-cutting approach. The results show that out of 38 branches examined, 8 branches are efficient and another 30 branches are inefficient.

Optimization of banks' foreign exchange portfolios aiming to determine an optimized combination of foreign exchange assets is in such a manner that it leads to a minimum risk and maximum yield. The approach used in this article, which is actually a priority over other methods is to use a combination of inexact mathematical models (fuzzy) and optimization. Thus, in this research, linear programming with fuzzy target coefficients has been used. The target coefficients are the same as the exchange rate. In other words, the daily rates of all currencies due to fluctuations are considered as fuzzy numbers. Therefore, in this investigation, by developing a multi-purpose mathematical model and by applying the fuzzy data relating to transaction rate of six foreign exchanges in year ended on March 20, 2020, including US dollar, Emirates Dirham, Japanese Yen, Turkish Lira, Korean Won and Euro, case by case risks related to the fluctuations of noted foreign exchanges and also their yield in the foreign exchange portfolio of Bank Mellat were measured and estimated for the future time horizon. All banks may benefit from the developed model. By determination of the optimal weight of each foreign exchange, upon describing and analyzing the existing status it specifies the optimal status, enabling banks to fulfill their foreign exchange obligations on due dates by properly and optimally making investment in foreign exchange assets meanwhile gaining a competitive advantage. "Gams Software" was used for solving the model.

Explaining the competitive strategies of supply chain management is vital. Therefore, examining supply chain risks to choose the best criteria is a new strategy to manage and control risks and reduce the vulnerability of the supply chain process in order to improve the process and productivity. The purpose of the current research is to identify and rank the risks of the  three-level supply chain (supplier, producer and distributor) with a focus on level (2) of production and operations in order to explain the new strategy in the operating company of oil and gas production. This article has been done by reviewing the studies conducted in the field of identifying and ranking the risks of lean, agile, resilient and green supply chain management, by presenting a hybrid analytical model based on fuzzy Delphi and the network analysis process in the Super-Decision software environment. The risks identified using the literature review, 32 effective components with the contexts and the real space of the supply chain and with a survey of the expert team of 17 people, have been carried out in three stages according to the fuzzy Delphi method. Finally, after refining and evaluating the extracted factors, it led to the identification of 6 criteria (environment, supply, information system, process, control and demand) consisting of 26 risks, categories and ratings. According to the findings of the research, the risks of the process criterion with the highest weight were chosen as the superior criteria and the criteria of supply, control, environment, demand and information system were placed in the next priorities. Explaining the new strategy, agile, lean, resilient and green competitive strategies were prioritized in order.

The bank’s real profitability by adsorbing the deposits, payment loans, and making investments may create cash flows different from what has been anticipated for the apportioned budgets. In line with this, the banks must predict cash flows and factors influencing their profitability. The present study tries to investigate and elucidating the effects of loan repayment losses and deposit costs on the growth in the banks’ profitability.Since there is no model for measuring the loan payment losses and deposit costs, the present study engages in designing and pretesting of models for measuring the loan payment losses and deposit costs based on Iran’s banking; then, the designed models will be used for measuring the loan payment losses and deposit costs. GMM-based multiple-regression is the method used herein along with the financial statements of Sarmayeh Bank as well as central bank’ information for a time span from 2011 to 2019.Corresponding to this research’s results, the loan payment losses and deposit costs are factors influencing the profitability of Sarmayeh Bank. In other words, the increase in the loan payment losses and the deposit costs brings about reductions in the profitability rate of Sarmayeh Bank.

The purpose of this study is to evaluate the competitive approaches of large supply chain management of the oil and gas operating company.This research is based on a multi-criteria decision-making approach using fuzzy Delphi method and network analysis process.Using literature review and a survey of a 15-member team of experts, 33 components affecting the large supply chain were extracted.It was used to refine and evaluate the extracted factors with the real contexts and space of the large supply chain, according to the fuzzy Delphi method and with the opinion of the selected team of experts.Then, the relative importance of each of the components and dimensions of the supply chain was determined based on the network analysis process method in the Super Design software environment.The results of the study, resilience strategy (0.36466) has the highest rank and then agile strategies (0.25385), lean (0.23963), green (0.14187), second,
third and fourth ranks.

Liquidity management has been one of the biggest challenges facing the banking system in Iran in the acute inflation conditions in recent years. Facilities granted by banks, regardless of inflationary conditions, usually lead to hidden losses in repayment of loans, resulting in reduced profitability and the risk of inability to meet obligations, resulting in the risk of bankruptcy. The present study aims to estimate the loan repayment loss in Sarmayeh Bank using the weed optimization meta-heuristic algorithm. In the present study, a model was designed to examine the loan repayment loss. Also, to compare the calculated results using the proposed heuristic formula and the income of the granted financial facilities in terms of loan repayment loss prediction, weed optimization meta-heuristic algorithm was used. The results showed that there is a negative correlation between loan repayment losses and the growth of Sarmayeh Bank profitability in high inflation conditions. Also, comparing the loan loss prediction between the calculated results using the proposed heuristic formula, the number predicted by the weed optimization algorithm and the income of the granted financial facilities showed that the loan repayment loss using the weed optimization meta-heuristic algorithm can be calculated.

The purpose of this study is to design a warning system for price bubble and financial crisis in the Iranian stock market. In this study, the statistical information of the seasonal data of the period 1990-2019 and the MGARHC have been used to extract and identify the variable of financial crisis and price bubble in the capital market. The results of this study showed that variables such as production, inflation rate, exchange rate, total stock market index, etc. have a significant impact on the occurrence of financial crisis and the possibility of price bubbles in financial markets. Based on the estimation, it can be stated that the effect of the shocks of the research variables on the occurrence of the price bubble in the stock market leads to an increase in the instability of the variables. This can be due to the dependence of the economic structure on its markets, and this can have heavy consequences due to a shock on the country's structure.

After-sales service can play an important role in customer satisfaction and maintaining it customers are loyal to a brand after sell to a brand make a constructive connection to it.Thus improving the quality and enhancing the performance of a business. Successful organizations are those that have the ability to consciously use customer information and provide better after-sales service. Therefore, in this research, the credit risk management model in Saipa Yadak dealer network has been designed using financial and non-financial components of after-sales serviceThe results showed that using financial and non-financial components including, service cost, performance of after-sales service agencies, good accounting of agents, the amount of collateral of agents, the quality of services of the network of agencies, the speed of services of the network of agencies Agencies, network age (or age) of agencies, and regional location of the network of after-sales service providers affect optimal credit risk management. Also, firefly algorithm and bee colony algorithm have the ability to predict the optimal management of credit risk using financial components.

Management is effective in all areas of an organization. An organization achieves the expected results when the management of the organization uses jihadi components in its approaches. An organization can achieve its planned financial and non-financial and transcendent goals, if jihadi management approaches are implemented in that organization. Jihadi management as the most logical and efficient management model for achieving the goals of organizations in a revolutionary system has been considered and emphasized in recent years. This type of executive agent management is an "Iranian-Islamic model of progress" and is based on management knowledge derived from management science and schools as well as the Islamic value system. The present study aimed to identify the dimensions and components of Jihadi management with the aim of optimal management of credit risk in the network of car manufacturers’ dealerships. Since this after-sales service network is primarily responsible for serving customers of Saipa Company, it requires having a professional and jihadist view with the aim of promoting the level of servicing.

The purpose of this study is to design and explain a model to identify the factors that create and develop entrepreneurial attitude in the capital market and to present the necessary solution for its implementation.In this study,after reviewing the research background and interviewing experts and academic professors in the field of capital market and entrepreneurship,6 main factors and 41subfactors were identified.Then the likert scale questionnaire was designed and distributed among the 384 managers and experts of financial institutions as well as investors in the capital market.Questionnaire data were analyzed by confirmatory factor analysis.At the end,the final model of the study was designed and suggestion were made to develop an entrepreneurial attitude in the capital market.

This paper focuses on the corporate governance and profitability indexes of investment in iranian commercial banks. In this paper we discuss the state of corporate governance in Iranian commercial banks and try to find a link between corporate governance mechanisms and those indexes. We found that there are some relationships between auditing quality measures, characteristics of CEO and board of directors as measures of corporate governance mechanisms and asset quality measures, efficiency measures, profitability measures, liquidity measures and capital sufficiency as measures of profitability indexesof investment in Iranian commercial banks. We report that the finding can improve the governance roles and performance evaluation of Iranian commercial Banks.

The purpose of the present study was to identify and rank business alignment challenges with Information Technology: a strategy for strategic alignment. Statistical population consisted of ten managers and experts of South Steel Company regarding strategic planning and information technologies. A paired comparisons questionnaire was used to collect and to gathering the data, which included six business alignment challenges with information technology (IT) . Hierarchical analysis process was used to analyze the data. The results showed that lack of facilities for performing activities of relative weight (0.308), Lack of board support and relative weight (0.254), Lack of a separate unit for enterprise-wide planning with relative weight (0.163), Lack of appropriate Information Technology (IT) skills and strategies with relative weight (0.134). Failure to evaluate organization readiness with relative weight (0.081). And not using information technology (IT) to gain strategic competitive advantage with a relative weight (.053) ranks first to sixth.

This analytical-descriptive article seeks to explain the impact of overall and partial of efficiency governance and residents on selected financing methods in the Javanmard Qassab neighborhood. The statistical population was all residential properties located in this neighborhood, of which 50 homogeneous license plates were selected in terms of land area by non-random sampling method. Using fuzzy data envelopment analysis model, Network Fuzzy Range Adjusted Measure Data Envelopment Analysis, overall and partial efficiency was calculated and classified into three groups by using the K-means Clustring technique. Findings from Pearson correlation coefficient and F-test & test of significance (Two-tailed) of variance in SPSS software environment show that there is a direct and positive relationship between overall efficiency and part of residents in all financing methods with an average correlation coefficient of 0.834 with a significant level of 99%. It is more prominent in the process of improvement and modernization. The findings show a direct relationship between overall efficiency and governance with a mean correlation coefficient of 0.570. The results suggest that there is no significant relationship between residents' performance efficiency and governance, which indicates a lack of correlation in financing between government and people's interests.

One of the financial institutions of the countries in the world is the Stock Exchange, which is used as indicators of economic health. As for a large volume of capital is managed through the stock market and is placed in the production and industry, the recession in this market can have important effects. In this paper, we seek to extract the cycles of prosperity and recession in the Tehran Stock Exchange using the TEPIX and the Pagan and Sossounov method. Then, using the PSO algorithm, the most important predictor variables are determined and in the next step We predict market financial cycles using ANFIS, MLP, RBF and PNN networks. The results show that according to the mean square error, the root mean square error, the accuracy of the model and the Kappa coefficient, the MLP model provides better results in predicting future market conditions.

Designing and implementing a credit risk measurement model in the country's banking system will play an effective role in increasing the productivity of the country's banks in the optimal allocation of resources. Therefore, credit has an important role in the performance of the country's banking sector. Therefore, based on this argument, the present study designs and explains a model for the contagiousness of companies' financial distress risk and credit risk in the country's banking system. For this purpose, the limit (limit) theory of Akhtar and Dali (2017) research was used to measure the contagiousness model of financial distress risk. The hypotheses were tested using the statistical method of regression analysis with combined data using the information of 23 banks listed on the Tehran Stock Exchange during the years 2014 to 2019. The findings of the first hypothesis of the study indicate that there is a significant relationship between the risk of financial helplessness of banks and the credit risk of the country's banking system. Also, the result of the second hypothesis showed that the risk of financial helplessness of banks is transmitted to the Iranian banking system in the form of credit risk.