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Showing 3 results for Hosseinzadeh
Dr Mostafa Hashemi Tilehnouei, Ms. Saba Hosseinzadeh,
Volume 9, Issue 31 (6-2020)
Abstract
Credit risk evaluation is an integral part of the lending process. Significance of credit rating is increased by the global financial crisis and banks’ capital requirement. The purpose of this research is to find a new and more accurate way to estimate corporate credit scoring. Based on Traditional statistical methods and artificial Intelligence (AI), this research following Lee, et al., (2016) is testing a hybrid model, the model is combing logistic regression and artificial neural network(ANN). Population of the study is companies listed on Tehran Stock Exchange during 2010 to 2016.sampling method is systematic eliminating method that with considering the criteria, number of 90 companies were selected for the study. The results show the hybrid model in comparison with logistic regression and artificial neural network is more efficient in credit rating of companies listed in Tehran Stock Exchange.
Mehdi Amini, Omid Ali Hosseinzadeh, Ghafar Tari,
Volume 10, Issue 36 (12-2021)
Abstract
This research was carried out with the aim of designing and validating the model to improve (enhance) the organizational capability in the northwestern national banks of the country. In terms of the data and information collection method, this research was a descriptive and survey type of research and among applied research. The statistical population of the research includes all the employees of the national banks in the northwest of the country (1820 employees of the branches of the National Bank of East Azerbaijan Province, 600 employees of the National Bank of Ardabil Province, all employees of the National Bank of West Azerbaijan Province with the number of 606 employees, employees of the National Bank of Zanjan Province 215 people). The sampling method was stratified stratified sampling, so that according to the total number of employees of national banks in the northwest of the country (3241 people) according to Morgan's table, 343 people were selected, and this ratio was for the employees of East Azarbayjan province (193 people), Ardabil province (63 people). people), West Azarbaijan province (64 people) and Zanjan province (23 people). The research tools for the factors promoting organizational capability and organizational performance were developed by researchers and Jamshidi's standard questionnaire was used for organizational capability. The results of the review from library studies, experts' opinions and confirmatory and exploratory factor analyzes led to the identification of 10 effective components on improving organizational capability. These components included customer orientation, functional coordination, knowledge creation, knowledge transfer, knowledge application, organizational learning capability, strategic planning capability, market measurement capability, information technology capability, and trust building capability. The results of Friedman's test showed that among the factors that promote organizational capability, knowledge transfer, knowledge creation, knowledge application, trust building capability, customer orientation, functional coordination, organizational learning capability, information technology capability, market measurement capability and strategic planning capability respectively have the highest amount. were ranked Also, the results of structural equation modeling showed that the path coefficients between knowledge creation (0.268), knowledge application (0.644), organizational learning capability (0.191), strategic planning capability (0.194), information technology capability (0.368), trust building capability (0.798) was at a significant level with organizational capability (p<0.05). Also, the coefficient of the path of organizational capability with organizational performance was at a significant level (p<0.05). Meanwhile, the coefficient of customer orientation path (0.11), functional coordination (0.03), knowledge transfer (0.01), market measurement ability (0.25) and organizational ability were not at a significant level (p<0.05). . On the other hand, the mediating role of organizational capability in the relationship between knowledge application (p=0.006), organizational learning capability (p=0.012), information technology capability (p=0.013) and trust building capability (p=0.001) It was significant with organizational performance.
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پانلهای کناری
Mohammad Hosseinzadeharanchei, Ali Salmanpour, D.r Davood Hagh Khoh,
Volume 13, Issue 47 (7-2024)
Abstract
The aim of this article was forming a stochastic dynamic general equilibrium model for Iran's economy in terms of the specific characteristics of the country's economy. After the experimental analysis of the model, the calibration of the model parameters was done; This means that the parameters of the model were tried to be set in such a way that the highest match between the real statistics and the simulations made by the model is achieved. For this purpose, information from previous studies or some special features of statistics were used to calibrate the parameters, and in some cases, the desired parameters were calibrated using the statistics of Iran's economy. In the next step, the presented model was simulated using Diner program. The results provided by the Diner program include a summary of the moments of the simulated variables and the instantaneous reaction functions of these variables equal to the shocks included in the model. In this study, the model was simulated in three different cases. In the first case, the policy reaction functions were not included in the central bank's decision-making, and in the next two cases, the reaction functions were included in the model, according to which the central bank is one of the two scenarios. Inflation control (through monetary base control) and exchange rate control (through intervention in the currency market) are taken as monetary policy. The obtained results indicate a high similarity between the model values and the real statistics values. Then, the behavior of the reaction functions of the variables in response to the exogenous shocks of the model (oil income shock and technology shock) was investigated.
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