taghi torabi

Iran and the member states of the Persian Gulf Cooperation Council (saudi arabia, Oman, Qatar, Kuwait, the United Arab Emirates and Bahrain) as the most important economic and political pillars in the oil-rich region of the Persian Gulf, are among the most important exporters of oil in the world market, whose economy relies on oil revenues. is Each of these countries, based on their economic structure, market requirements, internal institutions and different business conditions, have used various combinations of income sources in order to reduce the effects of oil shocks in different economic sectors. Therefore, investigating the effects of oil shocks on the macroeconomic variables of these countries separately and with a comparative approach is significant.

This article aims to analyze the impact of oil income shocks on the variables of economic growth, trade balance and inflation in Iran and the member countries of the Persian Gulf Cooperation Council and during the period from 1980 to 2017 using the shock response functions of the Structural Vector Autoregression model (SVAR). ) has investigated and compared the effect of oil income shocks on macroeconomic variables of each of the mentioned countries separately.

The result shows that oil income shocks affect economic growth, trade balance and inflation in Iran and GCC countries. By comparing the effect of the oil shock on the economy of Saudi Arabia and Iran, it can be said that the positive effect of the oil shock on the economic growth and trade balance of Saudi Arabia is shorter than that of Iran in terms of duration, but the effect of the shock on inflation in Iran is significant for longer periods than in Saudi Arabia. Also, the positive effect of the oil shock on the economic growth and trade balance of Bahrain is greater than that of Iran in terms of the duration of the effect, but the effect of the oil shock on inflation in Bahrain is significant for less periods than Iran. In the country of Kuwait, the effect of the oil shock on the economic growth and trade balance of this country is more stable and longer than that of Iran, Saudi Arabia and Bahrain, but the intensity of the impact of the oil shock on inflation in Kuwait is much less compared to Iran, Saudi Arabia and Bahrain. In Oman, the effect of the oil income shock on the economic growth and trade balance of this country has been more stable and continuous for longer periods compared to Iran, Saudi Arabia, Bahrain and Kuwait, and the shock effect on Oman's inflation has had a negligible effect. By comparing the effect of the oil shock on economic growth, the trade balance of the UAE with other countries, it can be said that the effect of the shock is somewhat similar to that of Saudi Arabia, and the positive reaction of the UAE's inflation to oil income shocks is different from the reaction of the inflation of other countries except Bahrain. Comparatively, Qatar's economy has not been affected by oil income shocks compared to other studied countries. In the country of Qatar, the oil income shock has no significant effect on economic growth, trade balance and inflation, and it behaves differently from other countries under investigation. In terms of behavioral comparison among these economic variables, Iran's inflation response to oil income shocks is significantly different from other GCC countries. Iran's inflation has shown a positive reaction to the oil income shock, which has not disappeared in the long term, but in most of the GCC countries, inflation has shown an insignificant reaction to the oil income shock (except for Saudi Arabia) that the shock effect in Long gone.

In the general conclusion, a major heterogeneity is caused by the different degree of dependence of the economy of these countries on oil revenues and the specific characteristics of their economic structure, which causes significant differences in the response of these countries' economy to oil shocks in terms of duration and intensity has been

The present study was conducted with the aim of developing a paradigm model of innovation strategy with a digital transformation approach in the banking industry. The approach used in this research is qualitative and the objective is applied. The participants includes managers and experts in the banking industry and university professors in the field of innovation strategy and digital transformation. Purposive sampling was conducted using the snowball method and theoretical saturation was achieved after interviewing 14 experts. A semi-structured interview was used to collect data. The key components of the innovation strategy have been formulated using the grounded theory in three stages of open, axial and selective coding using Maxqda. The results showed that, according to the research paradigm model, legal requirements, change in customers’ needs and expectations, the rapid development of transformative technologies and new players in the financial industry have a significant impact on the innovation strategy with a digital transformation approach. Innovation strategy includes types of innovation, levels of innovation, carrying out innovation and evaluating the effectiveness of innovation. The digital innovation culture, collaboration capability, and digital talents management constituted contextual factors. On the other hand, the level of maturity of knowledge management, the absorptive and learning capacity of banks, business intelligence, organizational barriers and macro barriers play the role of an intervening condition. Finally, customers credit scoring with Artificial intelligence, open banking, updating of policies and laws in the financial field, digital governance and intelligent supervision, Intelligent process automation, Digital Experience Management of customers and employees, data and infrastructure management, intelligent risk management, strategic renewal and ambidextrous innovation in the banking industry leads to digital value creation for stakeholders and achieving organizational and extra-organizational consequences.

Today, the research activities of knowledge-based companies are considered important sources of transformation in the fields of technology and knowledge production. The more advanced the level of these activities and the higher their technological complexity are, the more innovative and competitive products grow. The present study was conducted with the aim of providing a model for determining the level of technological complexity of research and development in knowledge-based companies. In terms of its purpose, this research is part of applied research, and regarding methodology, it is in the category of mixed research. In the qualitative section, the data was collected from the literature review and semi-structured interviews with 20 experts in the field of research and development. First, seven categories were extracted for the complexity levels of research and development, and the Frascati category (including basic research, applied research, and experimental development) was selected based on the experts’ opinions. Then, during three stages of coding (open, central and selective), the influential factors in determining the level of complexity were identified and the research model was formed. In the quantitative part, the data was collected from a sample of 290 people from the target statistical population (Golestan Science & Technology Park) through a researcher-made questionnaire. Then, the data was analyzed and model fit test using structural equation modeling method, was conducted. The data analysis was done using smart pls3 software. The results indicated a suitable fit of the data with the final model, including complexity levels and 91 effective indicators in determining complexity levels. This model can be a suitable tool for research and development departments of knowledge-based companies, in order to improve the level of research and development based on global standards and create transformation in the fields of technology and knowledge production and increase added value.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.The value of the innovation process in organizations and societies, as well as economic growth with minimal environmental disruption, is a critical and essential policy. Addressing this issue has led various organizations worldwide to adopt the circular economy approach to utilize natural resources in an innovative manner within the industry and minimize waste. Therefore, the aim of this research is to propose a framework for designing the industrial innovation process with a circular economy approach. This study was conducted using the meta-synthesis method and the seven-step model of Sandelowski and Barroso, systematically reviewing 62 relevant articles from a total of 305 articles published between 2010 and 2023. The articles were selected based on inclusion criteria, and the validity of the research was confirmed through meetings held by the research team and an audit of the entire process to achieve consensus. The reliability was also verified using the Critical Appraisal Skills Programme (CASP) and Cohen's kappa coefficient, which yielded a reliability score of 0.781. The main dimensions of the study were designed and presented in a comprehensive conceptual model based on five categories and paradigmatic themes aligned with the innovation process derived from the extracted sources. The results of this study can serve as a basis for operationalizing the industrial innovation process in alignment with circular economy strategies and categories related to sustainable development at the level of industrial organizations.

Monetary policy is a tool through which central banks manage the supply of money to achieve their goals, and it is one of the key elements of macroeconomic management, and its effectiveness is an important issue in the analysis of economic policies. The usual goals of monetary policy are to achieve or maintain full employment, to achieve or maintain a high rate of economic growth, and to stabilize prices. For this purpose, in this research, the effects of this policy on production and employment, which have been calibrated for the Iranian economy by considering frictional unemployment in the form of a monetary general equilibrium model, have been investigated. The results show that the effect of monetary growth on employment and production in a steady state may be non-linear depending on the two parameters of labor supply elasticity and elasticity of vacancies in job matches, so that the lower the labor supply elasticity and elasticity of vacancies in job matches, it is more likely that monetary growth will have adverse effects on employment and production. Also, in the framework of the model, the negative relationship between the unemployment rate and vacancies is calculated, and with the increase of the Quarterly monetary growth rate from zero to 5%, the employment and production values in a steady state, they increase by about 0.4%. In addition, considering the transition dynamic, with the reduction of the monetary growth rate from the level of the benchmark case to the level of 2.5%, the equilibrium values of the variables will converge to their new equilibrium values after 2.5 years. Therefore, it is suggested that the central bank should pay attention to the effectiveness of monetary policy on production and employment in order to achieve macroeconomic goals in recession and boom. And since monetary growth is not always unfavorable for production and employment, the effects of this reduction on production should be taken into account in inflation reduction policies.

Innovation is considered as a key factor in creating economic value and gaining a sustainable competitive advantage in the current complex environment. In this research, the effects of this approach regarding sustainable development and environmental issues are examined with regard to establishing the innovation process as a fundamental challenge in industrial societies. The present research has been carried out through the combination of previous research with the aim of providing a comprehensive picture of planning a model regarding the design of the dimensions and components of the industrial innovation process based on circular economy. Industrial and circular economy In various scientific databases, the necessary dimensions and steps were used for a comprehensive summary and then applied in two stages with the opinion of experts and according to the fuzzy Delphi technique in order to screen and confirm them.210 related articles were purposefully reviewed based on the CASP evaluation criteria, and finally 58 articles were selected for the final research. The output of the research findings obtained from the meta-combination method in the form of a comprehensive questionnaire, after screening by the fuzzy Delphi method in two stages, was confirmed to answer the main question of the research, which is the circularization of the industrial innovation process, in 4 stages and 12 dimensions. In each sector based on the circular economy as an effective framework and model to expand the results in line with the goals of sustainable development in this research.By identifying the effective factors in creating the process of industrial innovation, the present research has developed a theory and created serious insight in this field, and it can be a basis for the operationalization of circular economy strategies in the ecosystem of industrial innovation and lead to new innovation opportunities.

In this study, the effects of industrialization, economic development, financial and commercial market liberalization on environmental degradation are explained. For this purpose, in the form of the final model of the quantile panel for the period of 2000-2021, the current issue was investigated in (BRICS) countries and (OPEC) countries. The results and estimation of the quantile model show that in the first and second (bottom) quartiles; Energy consumption per capita, stock market development index, financial development, trade, gross domestic product per capita, added value of the industry sector, labor and capital have a positive effect on the potential of global warming and carbon dioxide emissions in (BRICS) and (OPEC) countries. and from the third and fourth quarters onwards, the intensity of its impact decreases in (BRICS) countries and increases in (OPEC) countries, in other words, the study indicators in the first (Q25) and second (Q50) quarters, with global warming and the emission of di Carbon dioxide has a positive time correlation in both groups of countries. Then, as the lag components move away and move towards the third (Q75) and fourth (Q95) quartiles, the correlation between the study indicators and global warming and carbon dioxide emissions increases in (OPEC) countries and decreases in (BRICS) countries. This trend expresses the warning that in OPEC countries, much effort is not made to preserve the environment by reaching a high level of production, and it is necessary for OPEC countries, like advanced countries, to spend part of their income to preserve the environment as much as possible and Or use methods that cause less pollution and destruction to the environment in the path of their economic growth.

The present study, entitled Comparison of artificial neural network method and hidden Markov model in predicting Tehran Stock Exchange index, was classified as applied, analytical-mathematical research, the local territory of those companies listed on the Tehran Stock Exchange and its time domain is from 2007 to 2017 that in terms of data collection, it is a post-event research, in order to analyze information from statistics and mathematics, the Markov model of secret-neural network model has been used. According to the MAPE index, the artificial neural network method has been able to improve the prediction power by 0.0343% compared to hidden Markov's model. Artificial neural networks with the ability to deduce meanings from complex or ambiguous data are used to extract patterns and identify methods that are very complex and difficult for humans and other computer techniques to be aware of. A trained neural network can be considered as an expert in the category of information given to it for analysis. As a result, due to the complexity and heavy calculations, as well as the long computation time and the lack of access of some researchers to advanced models and Markov's secret model is recommended for those who are looking for a simple, fast and reliable method of forecasting using the artificial neural network method to predict the price of stock indices

Tax revenues are superior to other sources of income from the domestic economy for many reasons, including the ability to control them. The current state of Iran's economy and the imposed economic sanctions, as well as the instability of oil prices and oil revenues, have led to the non-realization of government revenue programs, and if such a trend continues in the long run, the country will face an economic crisis. One of the challenges of not implementing these programs is the unexpected behaviors that the economic system manifests itself over time. In this dissertation, a system dynamics approach that is able to display a multi-loop and multi-state structure and can model nonlinear feedback and time delays has been selected as a modeling tool. The impact of tax system reform on macroeconomic variables using a dynamic system approach. The main objective of this article is to examine the variables of the tax system on macroeconomic variables such as inflation rate, unemployment rate, and gross domestic product growth rate, and to provide a model for increasing tax revenue that leads to the selection of the best strategy for improving tax revenue. To achieve this, causal loops and stock-flow diagrams were first drawn for a ten-year period (1395-1404), and then the validity of the constructed model was tested for its dynamism. After simulating the model and analyzing the applied policies, finally, 23 strategies to improve the tax system are presented, which adopt each strategy that affects the performance of the tax system and some macroeconomic variables. Economic managers, based on the country's economic conditions and their valuable human resources, can adopt appropriate strategies and provide the conditions for improving the economic situation, including the country's financial revenues.

One of the aspects of improving people's health is to pay attention to environmental mechanisms that affect people's health with their ecological effects. In the current study, the effects of industrialization and economic development on the production of greenhouse gases are discussed in line with people's health.

in the present article, following the studies; Zhao et al. (2023), Yeboa et al. (2023), Zhou et al. (2023) and Wen et al. (2022) explain the effects of industrialization, economic development, on the production of greenhouse gases in line with the sustainability of people's health in countries (G7) and OPEC countries based on the quantile panel regression model and for the time period of 2000-2022.

The estimation results confirm the relationship between financial development and environmental degradation in two groups of countries (G7) and countries (OPEC). The estimation results also show the confirmation of the effect of energy consumption on global warming potential in (G7) countries and (OPEC) countries and energy consumption has a positive effect on environmental pollution, in (OPEC) countries due to the abundance of energy and natural resources, energy prices is low, which has caused excessive and incorrect use of energy.

It can be said that the development of commercial and financial markets can lead to the improvement of human capital in countries. But this will happen better when the right context is provided for the optimal allocation of resources and the efficiency of labor and capital is increased. Financial development is an important factor in economic growth and the health status of people, which affects the health status of people not only directly but also indirectly through the environment; Also, in addition to adding physical capital in various sectors of the economy, investment in human capital should also be made. The financial sector development mechanism works in such a way that financial resources are provided from various private and government channels for the health sector of individuals; Because the efficiency of health services depends on the correct management of health system resources and its connection with the governing financial system. Investing in human resources is the education and training of human resources to acquire different skills and advance production, which can increase production and achieve economic development by raising the level of skill and expertise of the workforce and increasing its productivity. (G7) is more intuitive.

Today, the development of research and development activities that have a high level of technological complexity is considered an important and influential factor in the development and growth of the knowledge-based economy of developed countries; Therefore, the current research was conducted with the aim of identifying the effective components on the level of technological complexity of research and development activities. This research is in the category of applied research and in terms of methodology, it is in the category of qualitative research. With the approach of data-based theory, data was collected from studying documents and reviewing literature and conducting semi-structured interviews with 20 experts in the field of research and development. By analyzing the data, first 149 variables were extracted and during three stages of open, central and selective coding, the components affecting the level of technological complexity of research and development activities were identified, then the factor of obtaining advanced technology was identified as a central category. was selected and the rest of the factors were placed within the research structures (causal, background, intervening factors, strategies and consequences) and the research paradigm model was formed and five hypotheses were proposed. Based on the results of the research, 97 components (including 19 cases of causal factors, 16 cases of contextual factors, 12 cases of intervening factors, 11 cases of central subcategories, 23 cases of strategy and 16 cases of consequences) on the level of technological complexity of research activities and Development is influential.

The main issue investigated in the current research is the investigation of the impact of audit committees on the financial and economic risk of cryptocurrency demand in companies listed on the Tehran Stock Exchange. For this purpose and following Mohammad et al. (2022), at first, the relationship between financial and accounting expertise, independence and professional competence of audit committee members with (specific and systematic) risk of companies was investigated and then the moderating effect of ownership Family based on this relationship was analyzed. In this study, the financial information of the companies accepted in the Tehran Stock Exchange was used in the time interval of eleven years between 1390 and 1400, and the final sample consisted of 141 companies. The findings of the present research showed that there is a significant relationship between financial and accounting expertise, independence and professional competence of audit committee members and companies' risk. In addition, family ownership has a moderating effect on the relationship between financial and accounting expertise, independence and professional competence of audit committee members and company risk.

This research aims to develop a robust predictive model for evaluating the strategic cooperation between Iran's banking system and fintech startups. Leveraging insights from 14 experts within the banking and fintech sectors, a hybrid methodology involving the foundation's interview tool and data analysis was employed. Thirty-one indicators, categorized into six key factors influencing strategic cooperation, were identified. Using a fuzzy approach and MATLAB software, a conceptual model was crafted to assess the strategic cooperation of the banking system with fintech startups. Input from 320 industry professionals and managers further enriched the analysis. The findings underscore the pivotal dimensions shaping this cooperation, including barriers to entry, external factors, explanatory elements, varying cooperation levels, consequences of collaboration, and the motivations driving banks and fintechs. The level of strategic cooperation was determined to be in the medium to high range. Notably, the Anfis-designed model exhibited acceptable validity and predictive power. This study contributes not only by unraveling critical cooperation dimensions but also by furnishing a reliable predictive tool. The comprehensive approach, amalgamating expert insights, diverse indicators, and advanced analytical tools offers valuable insights to fortify strategic cooperation in the banking-fintech nexus.

With the passage of four generations of theoretical and experimental development of the smart city, it was expected that by relying on technologies such as the Internet of Things, artificial intelligence, cloud computing, and the like, this theory would be the way to face the problem and solve the complexities of resilience planning. But countless recent researches show the opposite. The root of the problem is not in the application of technology, but in the theoretical integration of smart city management and urban resilience. In the meantime, the resilience approach is a new point of view that instead of focusing on reducing vulnerability and looking at confrontation, it emphasizes increasing the resilience and flexibility of cities against natural and human hazards. The purpose of this research is to evaluate the feasibility of smart urban management to improve the resilience of Urmia city. To achieve this goal, a descriptive-analytical research method was used based on the analysis of a questionnaire that was completed by 30 urban experts and specialists. The results of the statistical analysis show that Urmia city is relatively favorable in terms of social and infrastructural resilience, but it does not have a favorable situation in terms of institutional-management, economic and physical-environmental resilience. In general, the overall resilience of Urmia city is lower than the optimal level according to the experts, so that the calculated value of the overall resilience of Urmia city is 2.90, which is less than the average level (3).

The purpose of this paper is to present a new technique to the portfolio selection using Genetic Algorithm and Fuzzy Synthetic Evaluation. Portfolio selection is a multi-objective/criteria decisionmaking problem in financial management. The proposed approach (Genetic Algorithm and Fuzzy Synthetic Evaluation) solves the problem in two stages. In the first stage، by using genetic algorithm and fuzzy synthetic evaluation، weight of criteria will be calculated. In second stage، using Fuzzy Synthetic Evaluation، Portfolios will be prioritized. A multi objective genetic algorithm is used to determine return and risk in the efficient frontier in Tehran stock market. In this research, we have used of firms’ performance between 1396-1400 in civil engineering, construction, investment and construction materials and tools manufacturers in order to determine portfolio selection. The main advantage of proposed approach is helping an investor to find a portfolio which have Best performance، portfolio selection doesn’t rely to expert knowledge

Today, in developed countries, the research and development department of knowledge-based companies has played a very important role in the production of new and advanced technologies and ultimately the growth of the knowledge-based economy. One of the important reasons for the success of these companies some of which have become the world's technology giants), conducting research and development activities based on global standards and having a high level of technological complexity. The current research, which is applied research, was conducted with the aim of identifying and classifying the effective factors in determining the level of technological complexity of research and development activities in knowledge-based companies. This research is a type of qualitative research that was conducted using the data-based method. The statistical population of the research was 20 research and development experts and specialists of Iranian knowledge-based companies. Data collection was done through a literature review and semi-structured interviews until theoretical saturation was achieved. By analyzing the data, the first 149 variables were extracted and during the three stages of open, central and selective coding, 98 influential factors were identified in determining the level of technological complexity of research and development activities, then, while identifying the central category, Identified factors were included in the main categories (including: causal, contextual, intervening conditions, strategies and consequences) and the research paradigm model was extracted.  In the current research, during the coding process, the identified factors were classified into 6 categories. Achieving advanced technology was considered as a central category, which includes the variables of the novelty of activity, the creativity of activity, uncertainty of result, systematicity, transferability of results, speed of development, added value of technology, distinctiveness from competitors, and credibility. The result of technology is the potential of learning, and the extent of the application of technology

Identifying related factors will provide the possibility for knowledge-based companies to help improve the level of complexity of the country's own activities.

Data Envelopment Analysis (DEA) is one of the widely used methods in measuring the technical efficiency of organizations. Data envelopment analysis is a classical non-parametric technique based on mathematical programming, which is used to compare the evaluation of the efficiency of a set of similar decision-making units. Its significant advantage is that it does not need to determine parametric specifications (such as the production function) to get performance points. Data envelopment analysis is known as a valid and stable tool used in performance evaluation, which provides a single measure of performance for each unit relative to its peers. Even though the number of data envelopment analysis models is constantly increasing and each one has a specialized aspect, the basis of all is a number of main models, among which we can refer to the "Charnes, Cooper and Rhodes" models (1978) as CCR, in which the assumption of constant returns to scale (CRS) has been used in the analysis. There are different approaches to determining the effective factors on efficiency and productivity and how to measure the productivity of production factors. Among the investigated companies in the years 2019 to 2019, it was found that the technical efficiency of the companies decreased, the technological changes of the companies increased, the managerial efficiency of the companies decreased, the efficiency of the scale of the companies decreased, and the overall productivity of the companies faced a decrease.

Today, research and development activities are considered important sources of transformation in the fields of technology and knowledge production, and research and development departments of knowledge-based companies play an important role in innovation and improvement of products and services. The more advanced and fundamental the level of research activities of knowledge-based companies and the higher the level of technological complexity of these activities, the more innovative and competitive products are available to the domestic and global markets. turns In this regard, the present research was conducted with the aim of investigating the levels of technological complexity of research and development activities in knowledge-based companies. This research is an applied-developmental research in terms of its purpose and descriptive-analytical in terms of its nature and method. The statistical population of the research was all CEOs of knowledge-based companies located in Golestan Science and Technology Park, numbering 85 people. The sample size was considered to be 80 people using Morgan's table and more cautiously, and available sampling method was used. The tool used to collect research data is a researcher-made questionnaire, whose validity was confirmed by measuring face and content validity and its reliability using Cronbach's alpha method. The results of the research indicate that 65% of research and development activities in knowledge-based companies based in Golestan Science and Technology Park are experimental development, 31.2% are applied research and only 3.8%. The percentage is the type of basic research.

Today, knowledge-based companies play a very important role in achieving advanced technologies and producing innovative products, and as a result, the growth and development of countries. The success of these companies is due to the development of advanced research and development activities that have a high level of technological complexity.

The current research is of mixed type. In the qualitative part, the grounded theory approach was used and the data was collected using interview tools and literature review. Quantitative part data was collected from the desired statistical population through a researcher-made questionnaire, then data analysis and model fitting with structural equation modeling method and using smart software pls3 done.

91 effective factors on determining the level of technological complexity in the form of six categories were identified and the presented model was confirmed.

The model for determining the level of technological complexity of research and development activities resulting from the present study can be a suitable tool for managers of research and development departments of knowledge-based companies in order to improve the level of research and development activities based on global standards and creating transformation in the fields of technology and knowledge production.

The objective of this paper is to examine the welfare cost of inflation in the context of Iran's economy, incorporating labor market frictions (search theory) within a monetary general equilibrium model. The model also features a cash-in-advance constraint. To achieve this goal, through the utilization of calibration and sensitivity analysis in the steady state, the findings indicate that both employment and production are contingent on the elasticity of labor supply and the elasticity of vacancies in job matches. Depending on these two parameters, they may exhibit an increase in response to an escalation in the inflation rate. Additionally, the three-month optimal inflation rate in a stable state is determined to be 4.66%. The welfare gains, derived from reducing the three-month inflation rate from its current level of 5.3% to the optimal rate in a steady state, is calculated to be 0.0031% of total consumption. Therefore, based on the results, it is suggested that in inflation reduction policies, the effects of this reduction on welfare are taken into consideration, and special attention should be paid to the area of business investment by giving tax incentives, especially tax credits.

The purpose of this paper is to present a new technique to the portfolio selection using Genetic Algorithm and Fuzzy Synthetic Evaluation. Portfolio selection is a multi-objective/criteria decision-making problem in financial management. The proposed approach (Genetic Algorithm and Fuzzy Synthetic Evaluation) solves the problem in two stages. In the first stage، by using genetic algorithm and fuzzy synthetic evaluation، weight of criteria will be calculated.  In second stage، using Fuzzy Synthetic Evaluation، Portfolios will be prioritized. A multi objective genetic algorithm is used to determine return and risk in the efficient frontier in Tehran stock market.  In this research, we have used of firms’ performance between 1396-1400 in chemical industries in order to determine portfolio selection. The main advantage of proposed approach is help an investor to find a portfolio which have Best performance، portfolio selection doesn’t rely to expert knowledge.  

The expansion of conventional commercial banking from 1960s and 1970s gradually gained significant pace due to the development of digital industry, the increase of innovations in the banking sector and an accumulative utilization of the capabilities of scientists in the field of information technology. Over the past three decades, Iran's banking system has recognized Fintechs and has gradually turned from confronting and competing with Fintechs to cooperation and collaboration with them. In this article, in order to achieve a solid frame work of how the interactions and cooperation of Iran's banking system and Fintech companies are related to the determination and development of a comprehensive model, contributions to detailed studies has finally concluded to the necessity of using a strategic and flexible cooperation approach, in the structuring of collaboration between the banking system and Fintech companies. In this research, which is of a qualitative type, in order to provide a paradigmatic qualitative model based on grounded theory approach, 14 of best local experts were interviewed and Atlas T software, was used to present the results. The results of this research can not only be used by experts, activists and policy makers in this field to evaluate the consequences and trace optimal strategic interactions in the country's banking system, but also clearly show the necessity of entering into strategic collaboration between banking system and Fintech companies.

Economists have always sought to discover the factors that cause poverty, because by understanding these factors, they can plan to reduce poverty. The purpose of this study is to determine the poverty line and the factors affecting it in the year 2021.

In the present study, only the line and its indicators were estimated by the data of urban and rural households' expenditure and income plan in the year 1400 and using the linear expenditure system (LES), and the determining factors of poverty were investigated. Also, the impact of the probability of poverty on the characteristics of the households was investigated using the probit model with Stata17 software.

The poverty line for a household in 2021 was calculated as 73,980,000 Rials. The highest reduction in the probability of household poverty is related to the level of education of the head of the household. With the increase of each unit of education level, the probability of facing poverty in the household will decrease by 23.1%. After that, the number of working people in the household has the highest effect in reducing the probability of household poverty with a decrease of 19.9 percent. Among these variables, in terms of the household, having health insurance has the least effect in preventing the household from becoming poor.

The gender of the head of the household is effective in reducing poverty. Also, in households where the head is younger, the probability of poverty increases. More support for young people and creating more favorable conditions for their employment is necessary to reduce poverty. Increasing the level and depth of insurance coverage will also be effective in reducing poverty.

This study endeavours to present an innovative prognostic framework and evaluate the future prospects of strategic cooperation between fin-tech startups and the banking sector in Iran. Employing a descriptive survey approach, extensive research was conducted through comprehensive literature reviews, field investigations, and insights gathered from interviews and questionnaires administered to 14 experts affiliated with both financial institutions and fin-tech companies. By identifying six key factors encompassing 31 unique indicators, including motivations for strategic cooperation, effective factors on cooperation, diverse levels of cooperation, external organizational factors, and barriers to strategic cooperation, and outcomes of strategic cooperation, a comprehensive conceptual model was developed. Employing advanced fuzzy inference techniques and MATLAB software, this model was employed to meticulously evaluate the viability and efficacy of strategic cooperation within the banking sector and fin-tech startups. The findings underscore the paramount significance of barriers to strategic cooperation while emphasizing the vital role of external organizational factors, effective factors on cooperation, diverse levels of cooperation, outcomes of strategic cooperation, and motivations for strategic cooperation of banking institutions and fin-tech startups. Additionally, the study gauges the level of strategic cooperation between the banking system and fin-tech startups, which yielded a commendable rating of 7.06, signifying a substantial medium-to-high range. Furthermore, the designed model showcases remarkable validation and predictive capabilities, rendering it an invaluable tool for forecasting future cooperation scenarios.