فواد کوهزادی

Governance of the Rial domain is one of the areas of governance that has received less attention from the country's economic policymakers in the past few decades. The purpose of Rial governance is for the government to use the capacities that the Rial payment system and the information available in bank transactions create for the administration of the country . therefore, the aim of the present study was to present a model for strengthening Rial governance with the aim of reducing capital outflow. This study was applied in terms of its purpose and descriptive-survey in terms of its data collection method and was analyzed using a mixed research method (qualitative-quantitative). The present study was conducted in three steps including qualitative, interpretive structure modeling, and quantitative. The results of the qualitative section indicate that 8 overarching themes, 25 organizing themes, and 58 basic themes were identified. The overarching themes are monetary policies, exchange rate policies, creating and strengthening transparency in banking performance, strengthening supervision and control over banking operations, creating financial attractiveness for investment in the country, gaining the trust of foreign investors, good governance, and challenges. The results from the quantitative section also showed that the dimensions obtained have a significant impact on strengthening the governance of the rial with the aim of reducing capital outflows.

The purpose of this research is to investigate the role of outbound marketing capability model design in improving the performance of state banks. The current research is of an applied type and it examines the capabilities of outbound marketing in improving banking performance. The statistical population of this research is made up of managers and experts of Sepah Bank branches. In data analysis, Cronbach's alpha test was used to measure the reliability of the questionnaire, Kolomogrov-Smirnov test to measure the normality of data distribution, and correlation test to measure the research hypotheses. In examining the effects of outbound marketing capabilities on the banking performance of Sepah Bank branches, all three hypotheses were confirmed with 95% confidence and 5% error level. The results of the research showed that there is a significant relationship between outbound marketing capabilities and banking performance. This means that the better the outbound marketing capabilities in bank branches, the better the banking performance will be.

 Today, banks have become one of the most important sectors of countries'' economies; Thus, banks provide resources for economic development and transformation, job creation, innovation and competition in any market. In this regard, the main goal of this research is to investigate the role of agility in the entrepreneurial decision-making of bank managers. The statistical population includes managers and experts of Sepe Bank branches in West Azerbaijan Province. This research is a developmental research and a type of quantitative-qualitative research. In the qualitative stage with 11 managers. Structural equation methods were used in a quantitative part. In this part, a closed-ended questionnaire with 28 primary items resulted from the qualitative stage of design and among the research community, which includes managers and experts in the administrative field of the province, according to the use of confirmatory factor analysis, the sample can be up to the limit. Acceptance continued for this exam, which included 145 people. In order to examine and confirm the validity of the entrepreneurial decision-making questionnaire based on agility based on the dimensions and items extracted from the exploratory factor analysis, the second-order factor analysis model was used. According to the findings, the most important factors were entrepreneurial decision-making and economic factors, and the most important factors were the experience of failure in management, financial resources, and business intelligence.

The increasing volume and complexity of digital data and its role as a tool to support the competitive advantage for banks, has increased the need to use new tools and techniques in data acquisition, analysis and processing, and in this context, access to Data flow in new financial transactions has become more difficult, and this has doubled the need for bank managers to use the big data strategy to solve financial challenges and take advantage of opportunities to achieve a sustainable competitive advantage. The purpose of this study is to identify the effects of big data strategy on achieving a competitive advantage in the Iranian banking industry. Present the banking industry. The hypotheses of the model were evaluated using the views of the research sample, including CEOs, managers and employees of information and communication technology, managers and marketing staff of 20 banks through a questionnaire, and the results show that banks using macro strategy Data gains a competitive advantage. In addition, ethical issues and customer privacy affect the relationship between big data strategy and gaining a competitive advantage.

The financial industry has always been a data-driven industry. Recent technological advances along with several other factors such as changing customer priorities and changing business needs have resulted in large quantities of production and consumption. Analysis of customers' behavior with Big data over the past 20 years has attracted the attention of banking marketers. Banks have used customer behavior analysis to optimally exploit opportunities, resources and avoid risks in turbulent market conditions as a powerful alternative. This concept is very dynamic and despite extensive research, it has not yet been adequately explored. The aim of this study was to develop a comprehensive model of customer analysis based on Big data by examining 156 works in nine reliable scientific databases and experts' opinions. This research has tried to develop theoretical foundations of customer behavior analysis by combining researches. To analyze the research literature, the method of transcending was used. Then, using two-stage Delphi method, the opinions of experts of the western banks of the country (Kurdistan, Kermanshah, West Azarbaijan, Hamedan) were taken and seventeen categories were classified into forty-nine concepts. The results show that customer behavior analysis model consists of five categories: factors shaping behavior, macro data, strategies, challenges and consequences.

The use of artificial intelligence in customer relationship management as the core of marketing activities has been considered by today's businesses. The researchers first extracted the concepts by reviewing the studies and previous researches, but due to the non-relevance of some of the extracted factors to the current situation of Iranian banks, they were used by experts using the interview method and Delphi. The research method is a mixture of qualitative and quantitative and is considered developmental and applied in terms of purpose. The components were first identified through interviews with 21 experts. Then a model was developed that includes 197 indicators and 21 concepts of customer relationship management based on big data. In three stages, in order to approve the initial model, experts and managers of the western banks iran (West Azerbaijan, Kurdistan, Kermanshah and Hamadan provinces) were consulted, and finally the model was approved. Based on the obtained results, banks with data and big data algorithms have used fifteen strategies in three stages of relationship start, relationship maintenance and relationship end, and consequences such as revenue increase, cost reduction, personal and dynamic pricing, advertising targeting. , Improved profitability, development of new products and services, allocation of smart resources and assisting managers in decision making. Also, management issues and challenges and ethical issues and privacy affect these consequences.

The purpose of this study was to design a model for prioritizing the factors influencing the acceptance of social responsibility using artificial neural networks. The method of this research is descriptive-survey. The statistical population of the research is all employees of the Department of Sports of Kurdistan Province, which was 240 at the time of the research. The target population is, in the first place, experts in the academic field. In the first phase, four main dimensions of social responsibility were collected by studying literature of authoritative literature (library studies) (Table 1).These factors were at the disposal of the panel of experts, including 11 university professors. The experts verified the content validity of the factors with an average above 79/0. The statistical population in the second section was the staff and managers of the Department of Sports and Youth of Kurdistan province. Based on the Klein index, 100 individuals were selected as the sample. After ensuring the initial validity, the components were based on a Likert scale-based questionnaire. Structural Validity (Confirmatory Factor Analysis) and Reliability (Cronbach's Alpha) were evaluated. Finally, validity (0.79) and structural reliability (0.891) were confirmed. Then, using artificial neural network method, the factors influencing the acceptance of social responsibility among employees were estimated and measured. The results of the research showed that, in the process of accepting social responsibility among employees, the component of ethics of business in the first priority and the component of economic needs were placed in the top priority.