درخت حوزه‌های تخصصی

INTRODUCTION: Lack of a comprehensive classification of crisis and emergency management in Helal houses has caused many losses in the Red Crescent Society of Iran. Therefore, the root of these problems can be identified and investigated with a thorough investigation. METHODS: This applied research was conducted using a hybrid design. In this research, field and library methods were used. The data were collected by using questionnaire and conducting in-depth interviews with managers, specialists, and experts of the country's crisis management organization and professionals until theoretical saturation. In the first stage, 24 interviews were conducted and we reached theoretical saturation in the 20th interview. In the second stage, relying on inferential statistics methods, 422 questionnaires were distributed. The statistical population of the research is the Red Crescent Society of Iran and its time domain is the second half of 2022. FINDINGS: After performing the three stages of open, central, and selective coding, the final research model was obtained in which, 6 general categories, 15 subcategories, and 49 main concepts are mentioned. CONCLUSION: The results demonstrated that the categories of human resources, organizational communication, and government policies are among the effective factors on crisis management in Helal houses in the Iranian Red Crescent Society in the critical condition of Covid-19 and the consequences of these categories have a significant impact. There are other problems and crises in the formation.

INTRODUCTION: Identifying and classifying hospital suppliers and choosing the right hospital supplier are based on some criteria, such as price, quality, timely product delivery, and after-sales service. METHODS: The research method was to select a suitable supplier through multi-criteria decision-making methods, including fuzzy TOPSIS and fuzzy Delphi. This research analyzed the selection criteria of hospital suppliers using fuzzy TOPSIS and fuzzy Delphi methods. The weight of the selected criteria and their importance were determined by holding interviews with hospital experts. In the next stage, the suppliers were evaluated, and finally, they were ranked using the TOPSIS fuzzy method. FINDINGS: In this research, the criteria for selecting suppliers were based on the criteria determined by Dickson. According to the fuzzy Delphi method, 7 criteria of product quality, timely delivery, final product price, after-sales service, technical ability, product position among competitors, and easy-to-use product were selected for supplier evaluation. CONCLUSION: The selection of a reliable supplier is becoming increasingly crucial given the critical role played by the healthcare sector, which includes hospitals and the Red Crescent as its constituents, the expanding development of technology, and the growing variety of medical equipment. According to the results obtained by the fuzzy Delphi method, the criterion of product quality with a score of 0.88 was chosen as the most important criterion, while the ease-to-use product index with a score of 0.7 was chosen as the least important criterion. The selection and evaluation of suppliers were accomplished through several different quantitative and qualitative indicators, such as cost, quality, timely delivery, and after-sales service. As a result, companies must choose key indicators and suitable suppliers because the right supplier leads to a reduction in purchase costs, as well as an increase in the quality of the products and ultimately the success of the organization in reaching its goals.

The present study is aimed to present a model of earnings transparency with an artificial intelligence approach in companies listed on the Tehran Stock Exchange (TSE). For this purpose, the data of 167 companies during the years 2011 to 2018 were used to test the research hypotheses. Variable selection test performed using Lasso's artificial intelligence algorithm showed that among the criteria of the audit committee's independence management system, the non-executive managers ratio, gender diversity and among the performance criteria, the ratio of cash holding in the company, operating profit margin and accounts receivable ratio had the highest effect to explain the earnings transparency of companies and also to predict the earnings transparency of the companies in the next year, the LARS algorithm method was used. The results of prediction showed the high power of Lars artificial intelligence algorithm to predict the earnings transparency of the companies listed on Tse. Keywords: Earnings Transparency, Corporate governance and performance criteria, Artificial Intelligence Approach

Due to overlap between stock markets and financial markets, this study was an attempt to examine the herding behavior in the Iranian stock market and the crude oil, foreign exchange and gold markets. For this purpose, in this research, monthly data between 2011 and 2020 for Tehran Stock Foreign exchange were used. The results of the study based on two criteria explaining herding behavior indicate the existence of herding behavior of the stock market and crude oil, gold and foreign exchange markets. The results also show that it has had different ef-fects on herding behavior in different periods. This issue has also been different in increasing and decreasing market periods. Therefore, gold is introduced as an important asset that influences herding behavior. Also, during the decreasing period of the stock market, herding behavior is not affected by the exchange and crude oil market, and in this period, the behavior of investors and investment risks in the stock market can be predicted without considering the exchange and crude oil market.

FinTech is the solution that strengthens the way of financial communication and if we apply this technology, it will provide us with new methods of performing smarter, more agile and wider financial services. The purpose of this study is to investigate and analyze the factors affecting the implementation of FinTech in Iran's banking industry using structural equation modeling to provide comprehensive solutions of removing barriers and development of this industry in the Iranian banking industry by fully understanding the current situation. The present article is of descriptive-analytical type and data collection has been done through library studies and questionnaires. The statistical sample of the study was 12147 personnel working in Iran's banks in 1400. Due to the size of the population, Cochran’s method and random sampling method were used to determine the sample size. To analyze and classify the extracted data, a questionnaire and a test of the main hypothesis and sub-hypotheses and structural equation modeling were used using smart PLS statistical software. The obtained results confirm the main hypothesis and the sub-hypotheses of the research. The results indicated that in the banking sector, there is a need for legalization and harmonization with upstream laws, as well as the need for infrastructure and tools that are very important in adopting strategies to implement FinTech in Iran's banking industry, in order to make transparency, reduce costs, provide high-speed services, and move towards a smart economy.

One of the important factors in making a profit through financial markets is a quick and correct response to market events, which is possible only by examining all aspects of the market. Today, to solve this challenge, the use of trading algo-rithms has become inevitable and can be considered as transactions made by computers that these transactions are controlled and reviewed through algorithms. Depending on their type and purpose, these algorithms examine different aspects and, according to the strategies defined for them, make decisions and signal by order registration. These trading methods are growing rapidly in the world, espe-cially in strong and developed financial markets. Proper implementation of algo-rithmic transactions reduces transaction costs and increases the accuracy of inves-tors in their investments. One of the most widely used of these strategies is the trend-following strategy, which is welcomed by many traders. This strategy can be implemented in different ways and through different trading tools. In the pre-sent study, five types of them were examined and implemented on one of the most traded symbols of the Tehran Stock Exchange. The purpose of this study is to implement some of the popular strategies in algorithmic trading along with the introduction of algorithmic trading, its strategies in the Iranian stock market, which includes the study of its advantages and disadvantages. The present study is a cross-sectional retrospective and field survey in terms of applied purpose and in terms of data collection.

Proving helpful in an efficient management of cash in order to reach optimal cash and clearly explain relevant optimization policies, this study examined the adjustment speed of cash holding using asymmetric models. The sample consisted of 117 firms listed in Tehran Stock Exchange and their financial details over the 2009-2018 period. Once the optimal level for cash holding was identified, asymmetric models such as the dummy variable approach, the quadratic model, and the threshold regression model were employed to test the adjustment speed of cash holding. The results revealed that cash-rich firms are moving toward optimal cash at a greater speed than cash-poor firms. In addition, the results from the quadratic model showed a non-linear, skewing effect of the cash holding adjustment speed in terms of the different cash levels. Therefore, there is an optimal level of cash holding that enables firms to deviate from the cash target. Should firms fall outside the optimal cash range, cash adjustment will occur at a greater speed, and it will be both partial and asymmetric.

In the field of corporate tax behavior, corporate governance mechanisms are effective for shaping and monitoring the behavior of managers. The board, which is responsible for allocating resources, improving performance and increasing shareholder wealth, plays a central role in choosing a tax management strategy. Hence, companies with different governance structures may adopt different types of tax management. Therefore, it can be argued that corporate governance mechanisms can affect corporate tax activities. In order to achieve the weight of the identified criteria, the network analysis process method was used. The purpose of this method was to structure the decision-making process, according to a scenario affected by multiple independent factors. In this method, there can be a relationship between all levels, while in the method of hierarchical analysis process, this relationship could only be from high levels to low levels. The method of the network analysis process, such as the hierarchical analysis process, calculates the inconsistency of all judgments by the conformity rate, and the calculated inconsistency rate must be less than 10%. The compatibility coefficient of the final matrix shows the validity of the questionnaire. In order to analyze the data, Super Decision 1.6.0 software developed by Thomas L. Saati, the inventor of this method, as well as MS Excel 2019 software were used. There is considerable evidence that increasing tax requirements can increase tax compliance, but typically some types of tax offenses are used as a tool to control the phenomenon of tax default.