javad einabadi

In recent years, digital currencies, as one of the emerging phenomena in financial markets, have created significant developments in the way transactions and investments are carried out. This article examines the use and acceptance of digital currencies in Iranian financial markets, focusing on the Iranian stock market. The main objective of this research is to identify the impact of various factors, including awareness, attitude, risks, and perceived benefits, on the willingness to use digital currencies in the stock market.To collect data, a questionnaire method was used and information was collected from investors and activists in the Iranian stock market. Data analysis was performed using descriptive and analytical statistical methods, including correlation and multivariate regression tests. The results show that awareness and positive attitudes towards digital currencies have a significant impact on the acceptance of these currencies, while concerns about security risks and price fluctuations can create an obstacle to their acceptance.By presenting a conceptual model and statistical analysis, this article attempts to provide a comprehensive perspective on the use and acceptance of digital currencies in the Iranian stock market and offers suggestions for policymakers and market activists.

The purpose of this research is to investigate the effect of artificial intelligence on the validation of Bank Melli customers. The present research is applied in terms of purpose and was conducted using a descriptive-survey method. The statistical population consists of technology experts from Bank Melli branches in Tehran, which are 55 people. Due to the limited statistical population, the entire statistical population was considered as a statistical sample, meaning the entire population was selected as the sample size (available sample). A questionnaire was used to collect research data. The validity of the questionnaire was confirmed by professors and the reliability of the instrument was also confirmed by measuring Cronbach's alpha. The analysis of the research data was conducted using descriptive statistical methods and inferential statistical methods. The results of the research show that the processes of pattern extraction, pattern selection, pattern adjustment, and pattern compatibility had a positive and significant effect on the validation of Bank Melli customers. Among the processes affecting the validation of Bank Melli customers, pattern selection had the greatest effect and pattern compatibility had the least effect.

In recent years, digital currencies, as one of the emerging phenomena in financial markets, have created significant developments in the way transactions and investments are carried out. This article examines the use and acceptance of digital currencies in Iranian financial markets, focusing on the Iranian stock market. The main objective of this research is to identify the impact of various factors, including awareness, attitude, risks, and perceived benefits, on the willingness to use digital currencies in the stock market. To collect data, a questionnaire method was used and information was collected from investors and activists in the Iranian stock market. Data analysis was performed using descriptive and analytical statistical methods, including correlation and multivariate regression tests. The results show that awareness and positive attitudes towards digital currencies have a significant impact on the acceptance of these currencies, while concerns about security risks and price fluctuations can create an obstacle to their acceptance. By presenting a conceptual model and statistical analysis, this article attempts to provide a comprehensive perspective on the use and acceptance of digital currencies in the Iranian stock market and offers suggestions for policymakers and market activists.

Understanding cash flows plays an important role in the study of businesses, as cash flows have a key impact on a company's economic performance. The aim of this research is to identify the factors and indicators influencing cash flows in power plant projects. This study is applied in purpose and employs a library and descriptive research methodology for data collection. Influential factors on cash flows have been identified based on a literature review, and then the relationships between these factors have been determined and analyzed integratively using Interpretive Structural Modeling (ISM) methodology. Finally, through MICMAC analysis, the factors have been assessed based on their influence and susceptibility to other factors. In relation to the factors affecting cash flows, six dimensions were identified: organizational factors, managerial factors, technological factors, economic factors, legal factors, and political factors. Eighteen indicators were recognized in relation to these dimensions. The results indicate that political and legal factors have the greatest influence over other factors, and any improvement in cash flows necessitates reforms in these two areas.

One of the important issues in global financial markets is the creation of a transparent, dynamic structure and the application of minimum rules with maximum efficiency. In order to create the aforementioned structure based on the policies and economic ideology governing the target financial community, various tools are used; among these tools, which are used to control severe price fluctuations in the stock market and reduce the emotional reaction of shareholders, are the permissible fluctuation range and automatic trading stoppage. In fact, in all stock markets in the world, in the case of abnormal fluctuations or force majeure or unforeseen events accompanied by severe shocks, either the fluctuation range limit or the trading stoppage in the form of automatic stoppages are used.A review of the empirical literature in this report shows that empirical studies critical of price limits are, if not more, no less than studies in their defense; Also, interviews with a number of capital market experts in the country indicate that the stated benefits, such as preventing the overall index from falling, creating more opportunities for decision-making, better market control by market makers, etc., assuming they are realized, are merely short-term and palliative solutions that are not only unable to solve the fundamental and fundamental problems of the capital market in the long term, but can also increase risk and create a platform for the formation of negative expectations among shareholders and generally create a negative view of the capital market, causing capital outflows or the lack of new capital inflows to the stock exchange in the future, leaving deep and inappropriate long-term effects.

The aim of the present study was to design a model of the impact of capital on operational risk in the banking industry (case study of Kerman's national banks). The research method is a descriptive correlation type and simple random sampling method. The statistical population of this study is all employees of Kerman's national banks, 210 people. The statistical sample in this study (based on the Cochran formula) was 136 people. The sampling method of the research is simple random. In order to measure these variables, the Ahangari and Saadat Mehr Capital Impact Questionnaire (2008) and the Karamzadeh Operational Risk Factors Questionnaire (2014) were used. was used. The extracted data were analyzed with a combination of descriptive and inferential statistics in the form of tables and graphs, as well as Pearson's correlation coefficient. The results of this research have shown that there is a relationship between capital and behavioral risk in the banking industry (case study of national banks in Kerman). There is a relationship between capital and regulatory risk in the banking industry (case study of national banks in Kerman). There is a relationship between capital and cyber risk in the banking industry (case study of national banks in Kerman).

The purpose of this research is to investigate replacing digital currencies instead of traditional money to overcome inflation in life insurance and investment. The proposed model includes the use of digital currencies as a tool to preserve capital value and reduce risks caused by inflation. This article is compiled based on argumentative-analytical model and contract method. the statistical population of this research is the actives in the insurance industry and financial market experts and the master's degree of the finance department of the Iranian Institute of Electronic Higher Education. The results show that the use of digital currencies can act as an effective hedge against inflation and help policyholders preserve the real value of their investments.This article also addresses the challenges and risks associated with the use of digital currencies in the insurance industry and offers suggestions for improving and developing this model.

This paper investigates the design of innovative budget optimization models in the automotive industry, with a focus on after-sales service companies. Given the increasing competition and the need to enhance efficiency and reduce costs, budget optimization has become a key factor in the success of these companies. This research examines various budget optimization models using advanced data analysis techniques and optimization algorithms.A case study of one automotive after-sales service company analyzes the impact of these models on financial performance and service quality. The results show that the implementation of optimization models can lead to cost reduction, increased efficiency, and improved operational processes. This paper also addresses the challenges and opportunities of implementing these models in the automotive industry and provides solutions for continuous improvement.Ultimately, the findings of this research can help managers and decision-makers in the automotive industry adopt more effective strategies for

Management accounting is an emerging part of accounting whose use is expanding rapidly. In the current economic conditions of our country and today's world, the use of management accounting information will play a significant role in the decision-making of managers and stakeholders. But the management accounting reports in the current situation do not represent all the realities of the organization and cannot provide the possible deviations clearly and clearly to the decision makers of the organization. Financial reports that are accompanied by non-financial information, criteria and indicators will play an important role in helping the management in the correct use of the organization's resources and funds. Lack of training to internal and external stakeholders as well as managers and accountants regarding the effects of management accounting reports, as well as the lack of clarity and certainty of the results of these reports in the eyes of the organization's managers and the possible resistance of employees in how managers deal with the results of management accounting information and data. The biggest challenge of organizations is in providing information on this part of accounting in the organization. In this regard, this research has tried with the help of the statistical community, including senior accountants, financial managers, technical and engineering managers, and the role of non-financial indicators, budget and budget reconciliation, comprehensive systems (ERP) and accounting coding, to compile management accounting reports, review and use He examined the non-financial indicators of the levels of the organization and its audit process, and finally found the presentation of these data to be a way for managers to present their performance results to the stakeholders of the organization and their decision-making

In recent decades, the frequency and intensity of extreme weather events have increased in many parts of the world, including our country, as a result of global warming. This study examines the impact of weather disasters on the stock market of Iran. A combination of accounting ratios and statistical tests are used to estimate the effects of extreme weather events on the stock market and index of different market groups. To achieve the purpose of the study, the time-series data of the period 2010-2024 have been used. The results showed that the negative impact of weather disasters on stock market returns and volatility is observed one day after the extreme weather events. This effect can be seen in most market groups. The insurance and pension group and the banks group are the most affected, while the basic metals group is the least affected by the studied weather events.

One of the most important things in decision-making and economic growth is the existence of quality, correct and reliable information. A significant amount of this information can be extracted from the accounting information system and financial statements. Financial statements provide a real and visible picture of the real business situation of a given company. It is important to pay attention to financial statements as a model for decision making. that different users should know how to benefit from this information. Managers should be proficient in accounting science so that they can make the best decision from the information collected by accountants. The contents of financial statements provide a large number of different tools and analysis, a way to understand the business. Access to financial statements and financial information is one of the important assumptions of quality and successful business.

In the last few years, artificial intelligence (AI) has brought about huge changes in many industries. The food industry is no exception to this rule, and artificial intelligence has made its impact on the world of food and beverages. Today, many organizations have realized that artificial intelligence has great potential to increase productivity, reduce food waste, and improve supply chain disruptions. As a result, many food industry activists are trying to make this industry benefit from the benefits of artificial intelligence and its subcategories as soon as possible. But what exactly is the impact of artificial intelligence on the food industry? What is the use of artificial intelligence in the food industry? Stay with us until the end of this article to answer these questions and learn more about the benefits of AI for the food industry.

According to the background of the subject of "behavioral economics" in the inter-field of economics and psychology, there is a very rich literature in this field, which, considering the relatively new nature of this field, provides a very suitable platform for further research in this field. However, the lack of specialized review studies in this field in Persian language is very evident. This research tries to review the articles written on the subject of behavioral economics and in particular the basic and new strategies that behavioral economics provides for the analysis of consumer behavior in a categorized form and by citing authoritative publications in the relevant field. . This research takes a step towards drawing a comprehensive view for the reader with a systematic review method. After searching the databases, 38 articles related to the topic were selected with certain criteria; Then the findings of the articles are categorized and presented in 9 cases. After studying this research, the researchers of economics and financial management have found a relative nobility compared to the studies done in this field and can expand the boundaries of knowledge in the subject of "explaining consumer behavior" with the tools and strategies of the science of "behavioral economics". ", identify the fields and passages of this issue and pursue their desired questions.

The present study intends to examine the level of risk-taking of individuals in different financial markets of digital currencies, stock exchanges and Forex. According to the theoretical literature, one of the most important sources influencing individuals' risk level is their financial literacy. This means that those who are more financially literate take fewer risks, and these risks are largely calculated. This research was conducted with a sample of 384 investors in the above three markets by survey method and using multi-stage sampling method. According to the research findings, the risk level of cryptocurrency market participants was higher than the other two markets, while the financial literacy of this group of people was much lower than the actors of the other two markets. On the other hand, according to the analysis of variance test, this difference is statistically significant and the results of Pearson correlation test also confirm the relationship between risk-taking and financial knowledge. With this in mind, it can be said that part of the risk-taking of cryptocurrency market participants is due to their low financial knowledge.

The purpose of this research is to design an export sales model for oil and gas futures contracts with Iran to the target countries under sanctions. This research is applied in terms of purpose, in terms of qualitative-quantitative research method and in terms of survey-exploratory data collection method, and in terms of collection, it is cross-sectional. In order to design the model using the Delphi method, the researcher identified the factors that played a role in the design by examining the background of the research, then prepared a protocol in the form of a questionnaire and questioned them among Delphi experts in three rounds to determine the indicators and sub-indices. . The qualitative part of the society consists of 6 managers and consultants of the oil and gas industry who answered Delphi questionnaires in three rounds. At the end of the third round, the output of the Delphi phase showed the sales model. Sampling in the first stage of the research, which is the design of the initial research model, is carried out by the snowball method and until the saturation stage is reached. In the quantitative part, the statistical population includes 55 employees of the oil industry who are knowledgeable about the research topic. Using Morgan's table, 48 people were collected as a sample size and data were collected using a pairwise comparison questionnaire. The said questionnaire was designed with 30 questions (index) in the format of 7 variables (sub-index). The validity of the questionnaires was confirmed by the experts. Cronbach's alpha method was used to check the reliability in the Delphi part, and the results are presented in the Delphi part. After the final approval of the indicators and the design of the paired comparison questionnaire, the inconsistency rate is lower than 1/. It was obtained, which indicates its reliability. After extracting the answers to convert the data of the questionnaires into a usable state, information was entered with the best decision software. In this section, questions from Delphi, entropy and Vicor methods were discussed for prioritizing variables. The output of the Delphi stage includes criteria such as paying attention to risk, minimizing the effects of external obstacles, internal factors, factors related to foreign investment, soft structural factors and hard structural factors. Hard structural factors, competitive advantage, internal factors, soft structural factors, attention to risk, factors related to foreign investment and minimizing the effects of external barriers were assigned the most important priority. In relation to the sub-indices, based on the Vicor ranking method, sub-indices such as increasing flexibility, mining and exploration, using expert experts in contracts, contracting with several countries and entering the energy exchange have the highest amount.

The purpose of this study is to investigate the effects of international sanctions on the international banking transactions of Iranian companies in the context of the blockchain. This research is applied and descriptive-survey type. The statistical population of this research is 10 international companies in different industries. In total, out of these 10 companies, 15 people with the conditions to answer the questionnaire questions were selected as individuals to participate in the statistical population. Due to the small number of population, the same number were selected as a statistical sample based on the counting method and answered the questions of the 20 questions of the researcher-made questionnaire. The validity and reliability of the questionnaire were assessed using cvr test and Cronbach's alpha with a value of / 788. And 792 /. Was obtained. Then k-s test was used to check for normality and then regression test and Friedman ranking test were used for prioritization using SPSS software. The results showed that international sanctions on international banking transactions of Iranian companies in the context of the Blockchain can be considered as an opportunity and by using the Blockchain, international banking transactions can be implemented and managed more effectively.

Manipulation of financial reports is influenced by behavioral and non-behavioral factors. One of the behavioral factors is the personality traits of Machiavellianism and narcissism. In psychology, these two behaviors are called dark personality traits that can affect people's honesty and good behavior. Accordingly, this study seeks to investigate the effect of managers' personality traits on the tendency to manipulate financial statements. In this research, 118 companies listed on the Tehran Stock Exchange in the period 1399-1399 have been studied. To test the hypotheses, Pold regression models were used. The results indicate that the personality traits of Machiavellianism and narcissism of managers have a positive and significant effect on the tendency to manipulate financial reports.