درخت حوزه‌های تخصصی

The purpose of this study is a new understanding behaviour and net cash flow forecasting. The data of this research contains the daily trial balance for one year, which has been received from 48 bank branches. For this purpose, the optimal model out of 4 models; Geometric Brownie, Arithmetic Brownie, Vasicek and Modified Square Root at three levels of microscopic, mesoscopic and macroscopic have been investigated and the Geometric Brownie model has been approved as the optimal model in microscopic level . The results show that Geometric Brownian Motion model can simulate the net cash flow highly accurate in accordance with the criteria of mean absolute percentage error. also forecasting net cash flow for each under study time series has been done in various forecasting horizons involved 7, 14, 21, 30, 60, 90 and 180 day time period accordance with the criteria of mean absolute percentage error. Also The other results obtained from this study is that according to 8 different prediction accuracy criteria, By increasing the forecast hori-zon, ability of the GBM model in simulation and forecasting the net cash flow de-creases.

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.

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.

The purpose of this article, extracted from the thesis, was to present the model of organizational culture based on normative and individual variables in the managers of the education staff of Tehran province. In terms of field position, and in terms of nature, it is among the foundation data research. The statistical community of the qualitative part included management experts using the principle of saturation and targeted non-random sampling method, and in the quantitative part, it also included the director general, deputies, and heads of departments of the general administration. and managers and vice presidents of education districts of Tehran province were selected as the sample size. Presentation of the organizational culture model based on normative and individual variables is considered a central category in the paradigm model of the research and other concepts in the form of categories of causal, contextual, and intervening conditions. Strategies and outcomes were included in the model and 10 categories with 57 indicators were introduced in the normative dimension and 10 categories were introduced in the individual dimension with 61 indicators. The evaluation findings based on Shannon's entropy method show; maliciousness and suspicion towards each other Self-esteem, sense of ownership over the organization, enjoyment of work, self-motivation, improvement of job skills and knowledge, personal development, and attention to positive points and job achievements, innovative decisions, and accountability are of the highest importance in realizing organizational culture.

This article aims to provide a model to explain the role of green human resource management in the resilience economy of small and medium-sized companies. The method of this research is a developmental-applied type of mixed research (qualitative-quantitative), which was used in the qualitative part of the Foundation (emerging) data method to identify components and indicators, and in the quantitative part, the descriptive-survey method was used. The statistical population in the qualitative part included experts (university faculty members) in the fields of human resource management, environment, and economics, after 28 interviews, the research reached theoretical saturation, and in a small part of the Cochran formula, there were 229 employees of the company. Industrial companies of Eshtehard town were selected. In the qualitative section, 13 codes were identified in process factors, 14 codes in prefixes, and 10 codes in suffixes. For the resistance economy, a researcher-made questionnaire with 31 indicators was used. The validity of the questionnaire was confirmed by the CVR method. Cronbach's alpha of the green human resources management questionnaire was equal to 0.761 and the resistance economy questionnaire was equal to 0.870. Two types of internal and external validity were used to validate the model. The results of the analysis of factor loadings of research components showed that there is a positive and significant linear relationship between each dimension of green human resource management. The results of the research model, it showed that among the identified factors, the antecedent dimension with a coefficient of 0.819, process factors with a coefficient of 0.797 and suffixes with a coefficient of 0.713, and finally, the coefficient of the impact of green human resources management on the resistance economy was obtained as 0.914, which shows the impact of 91 A percentage of aspects of green human resource management had resistance on the economy.

This paper sought to address the feasibility of dissecting stock price momentum in the firms listed in Tehran Stock Exchange using financial statement analysis (FSA). Different variables including those related to profitability, financial leverage and liquidity, and operating efficiency were used in this analysis. The study sample consisted of 130 firms listed in Tehran Stock Exchange over the period 2008-2019. The results showed that fundamental factors affected stock price momentum for one year in the winning portfolio and for two years in the losing one; after this period, financial information did not have a significant effect on stock price momentum. Therefore, stock price momentum performance is a function of the conformance of the past price performance to fundamentals. The results from investment strategies based on the past price performance-fundamentals conformance indicated that fundamentals cause a significant difference in stock excess returns in winning and losing portfolios.

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.

The purpose of the study is to develop and test an analytical model for resilience assessment of supply chain risks against the risks of system and its individual tiers. In this regard a multi-method research approach is adopted as follows: By using data envelopment analysis (DEA) and fuzzy set theory, a fuzzy network DEA model has been proposed to assess risk in overall supply chains and their individual tiers. The proposed model is tested by surveying of 130 people as selective petrochemical companies in Iran. The survey results show a substantial variation in resilience ratings between the overall petrochemical supply chains and their individual tiers. The research findings indicate that system resilience is not necessarily indicative of the resilience of its individual tiers. On the other hand, high efficiency scores in supply chain tiers have limited influence on overall resilience of supply chain. The proposed analytical model enables the assessment of supply chain flexibility at different levels for a wide range of supply chain risks in upstream, downstream and downstream process-es.

The research was conducted with the aim of designing a model of brand experience with the citizenship behavior of customers in the banking industry. The research method is qualitative and grounded theory, and it is considered fundamental in terms of its purpose. The statistical population of the research is Tehran banking industry managers with the highest education, experience, authorship, and ideas. In this research, unstructured and in-depth interviews were used to collect data and information. Data and information analysis were done through coding (open, axial, and selective coding) and MAXQDA software. In the end, a qualitative model is presented, which consists of causal conditions (Appropriate internet infrastructure, The emergence of new media, Creating a new form of communication, The proliferation of media, and Internet penetration rate), the main phenomenon (Branding, Brand experience, Brand personality, and Brand interest), intervening conditions (Building trust, Outsourcing, Customer behavior, Customer emotional attraction, Islamic banking, and Advertising), the contextual conditions(Customer behavior, Reproducibility of experience, Communication with customers and Notification), strategies (Accounting system, Systematic control, Low profit and help business, Electronic banking, Human Capital, Speed of service, Structure modification, Networking, Security, Creating competition and Personnel training) and consequences (Brand quality, Originality, Function, Customer satisfaction, and Customer loyalty).