محمد طالقانی

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 aim of this study is to examine, identify, and analyze the key factors influencing customer behavior patterns in the banking system. This research was conducted using a qualitative approach and thematic analysis. Data collection and extraction of relevant themes were carried out through semi-structured interviews with key experts in this field. Participants were selected using purposive sampling and the criterion of theoretical saturation, based on which 12 individuals were chosen, including university professors in the fields of marketing management and business, as well as heads, deputies, and customer relationship managers from Day Bank branches in Tehran. To ensure the validity and reliability of the data, two methods were employed: participant review and expert review by non-participating experts in the research. For data analysis, MAXQDA statistical software was used, and the data were examined through thematic analysis. The results of this study indicate that customer behavior patterns in the banking system are structured into four main categories (banking services, financial affairs, branch characteristics, and human and relational factors), 10 subcategories (electronic banking, quality and variety of banking services, foreign exchange and international activities, banking facilities and interest rates, investments, interior and exterior branch design, branch accessibility and amenities, customers, human resources, marketing and advertising), and 66 indicators.

This study aims to create a comprehensive stock price prediction model for the Tehran Stock Exchange by employing both fuzzy Delphi and interpretive structural modeling techniques. The research is innovative in that it incorporates all relevant factors from technical, fundamental, macroeconomic, and sentiment perspectives for stock price forecasting. This integration is facilitated through mathematical hierarchical modeling to pinpoint the most significant and responsive criteria for predicting stock prices.

Initially, due to potential uncertainties in expert responses, the fuzzy Delphi method was employed. Data analysis identified 54 stock price prediction criteria extracted from the literature. These were presented in two stages to experts and investors in the Tehran Stock Exchange industry as well as university professors. Accordingly, 15 criteria were selected as the most significant and influential, including five technical indicators: exponential moving average, price channel, relative strength, on-balance volume, and price. Additionally, the exchange rate from the macroeconomic component; trading volume from the behavioral component; price-to-earnings ratio, operating profit margin, gross profit margin, sales growth rate, dividend per share, earnings per share, and purchase per share from the fundamental component were chosen. Subsequently, using interpretive structural modeling, the relationships among them were examined and a hierarchical model was established. Interpretive structural modeling aids in determining the sequence and purpose of complex interrelationships among elements within a system.

The findings from the interpretive structural modeling revealed that the price-to-earnings per share ratio and the money flow index are positioned at the bottom of the hierarchy, indicating they possess a high driving force in influencing stock prices. Because the product pricing methods of organizations have a significant impact on purchases by investors, the expansionary or contractionary monetary policy plays a crucial role in pricing. The criteria at the bottom of the hierarchy include the exchange rate, a key macroeconomic factor, along with the relative strength indicator and the exponential moving average, both of which are considered significant technical indicators. The findings of this research provide organizations, investors, and active industries in the stock market with a hierarchical model of the most significant factors influencing stock prices in the Tehran Stock Exchange.

The results from interpretive structural modeling show that macroeconomic variables such as inflation rate, liquidity growth rate, and exchange rate can significantly influence stock prices. This influence occurs because individuals maintain diverse portfolios of cash, stocks, bank deposits, participatory bonds, gold, and foreign currency. Additionally, these variables impact the financial health of economic enterprises, which in turn affects their stock values.

The aim of the current research was to design an agant-based model of production cost management using internal and external organizational decisions in the marketing of industrial products. The research method is practical in terms of the goal and in terms of the research process, it is in the field of quantitative and field research of an exploratory type. The statistical population of the current research is all experts and informants on the issue of the cost of industrial products, who were selected through the snowball sampling method. In this research, 25 people were selected as a sample of experts, and data related to industrial products and their pricing were used to collect data from the companies' databases to check the research objectives. Next, three methods of theme analysis, Delphi technique and factor-based model were used to analyze the data. AnyLogic software was used to run the simulation in order to validate the model. Finally, the findings showed that in this research, two types of improvement policies have been investigated: 1. The effect of product production policies on demand and product pricing in order to make the finished price competitive 2. The effect of capacity planning policies. It is necessary to remember that this problem was designed with the approach of the foundation agent model and the behavior analysis of the research model shows that with the application of product production policies, the cost price of products increases.​

The present research was conducted with the aim of identifying the factors affecting talent management in the country's banking system. The research method is phenomenological in terms of practical purpose and in terms of collecting qualitative information, and the research community is professors and experts in the field of talent management in the banking system, which is based on the principle of theoretical saturation. 11 people were selected from among the academic staff members of universities, presidents and vice presidents of banks. The research tool is a semi-structured interview, and Lincoln and Guba's four criteria were used for the reliability of the data. The analysis of the interview texts led to the identification of 4 main categories of identification (with 3 subcategories of skills, personal characteristics and attitudes), recruitment (with 2 subcategories of external and internal organizations), development (with 2 subcategories of evaluation, retention), service compensation. with 2 external and internal subcategories), 9 subcategories and 32 concepts.

The aim of this study was to develop a comprehensive model for stock price forecasting in the Tehran Stock Exchange (TSE) using a mixed Delphi-fuzzy approach of Interpretive Structural Modeling (ISM). The model incorporated technical, fundamental, macroeconomic, and emotional factors. In this study, the fuzzy Delphi method was employed to identify key criteria from the investor’s perspective among the 54 stock price prediction criteria extracted from the existing literature. Subsequently, the interpretive structural modeling method was utilized to examine the relationships between these criteria and establish a hierarchical model. The findings of the ISM revealed that the price per share and the money flow index held significant positions at the bottom of the hierarchy and exerted a strong driving force. Among the criteria occupying lower positions in the hierarchy, the exchange rate and the power indicator relative and exponential moving averages were identified as the most influential indicators.

Financing ultimately is aimed at increasing the value of the business through planning, executing, as well as applying financial resources besides balancing profitability and risk. This is realized when financial managers make proper decision about which financing methods to adopt. This study is aimed at providing a hybrid approach based on fuzzy ISM technique and MICMAC analysis in order to design a model to help choose financing sources for Iranian industrial enterprises through overcoming the restrictions of decision-making process. To this end, the fuzzy ISM technique has been first employed to specify the interrelationships between the indicators as well as modeling their hierarchical structure; subsequently, by means of MICMAC analysis, the dominant indicators involved in the financing process have been classified in one of the four clusters based on their Driving power and Dependence. The results indicate that the index of “government fiscal policies” has the highest effect on other indicators of the system and it is a basic criterion for making fundamental decisions to choose the financing sources of Iranian industrial enterprises. Hence, in their management decisions, decision makers should pay attention to the perspective of government fiscal policies before considering any other indicators.

The aim of the current research is to provide a model to explain the effect of internal and external organizational decision components on the cost price of industrial products with a factor-based approach. The research method is applicable in terms of its purpose, and, a kind of qualitative and quantitative research of an exploratory type in terms of the process. The statistical population of the research is all experts and informants of the cost price of industrial products, and 35 people were determined as the sample size by the snowball sampling method. Companies' databases such as data related to industrial production and product pricing were used to collect data. Three methods of theme analysis, Delphi technique and factor-based model were used to analyze the data. The software used for the Delphi technique was SPSS version 25, and Netlogo software was used for the implementation and simulation of the factor-based model and its validation. The findings show that the changes in each factor during the period under review have an effect on other factors in the final price, and at the end, the validity of the model was confirmed by the experts. Therefore, the integration of the theory of constraints with factor-based modeling can be used as an effective tool in the cost price of manufactured products, and by means of it, the appropriate selling price of products can be determined and predicted in the short and long term periods.

Currently, the banking industry is of great importance due to its unique intermediary role to achieve the goals of sustainable development. The present study reviews previous studies on sustainable banking, aiming at investigating sustainable banking practices in order to improve the banking industry performance. The research method is based on a semi-systematic review. The statistical population included research articles on sustainable banking, which were obtained by the search strategy made in the period of 1995 to 2021 in scientific databases. First, 1004 articles on sustainable or green banking were identified, and finally, focusing on sustainable banking and performance, and based on the inclusion and exclusion criteria, 25 articles were selected for this study. After reviewing the literature, a conceptual framework was achieved regarding sustainable banking and improving the banking industry performance. Based on the conceptual model, it can be stated that sustainable banking should work towards increasing social responsibility so that the performance of the banking industry can be improved. In the present study, sustainable banking practices were defined by social sustainability, environmental sustainability, and ethical considerations. Therefore, in all countries, it is necessary to implement sustainable banking practices in a way that concurrently consider environmental effects and social effects in accordance with green banking and profit maximization according to traditional banking. If these actions are accompanied by social responsibility, profitability and efficiency will also increase and costs will be reduced; Finally, the improvement of the banking industry performance also depends on these three factors.

Considering the wide range of influencing factors and the complexity of relationships in the food industry, the trends do not follow linear behaviors and their analysis with nondynamic tools is challenging. In such a situation, if organizational strategies cannot be adjusted in line with the needs of the market and its environmental conditions, the resulting losses can be significant and sometimes irreparable. The purpose of this research is to identify the key effective factors in the strategic performance of production in the supply chain using a systemic approach. Due to the existence of multiple factors and the complexity of relationships between influencing variables, a systemic approach has been used to investigate behavioral dynamics in the form of cause and effect loops. Finally, in order to identify the key influencing factors, the intensity of the relationship between the variables has been ranked by experts' opinions in the form of a pairwise comparison matrix, and five key influencing factors in the field of production strategies have been introduced with the DEMATEL technique. Based on the results obtained, according to experts' opinion, having the production capacity for a fee, along with the development of factory production lines, plays a very important role in adapting manufacturing companies to demand fluctuations and managing the uncertainty of the market.

The aim of the current research is to design a marketing model for export development based on smart geomarketing based on SDI. This study has a qualitative approach. The statistical population included government experts, major exporters of kiwifruit, as well as university experts in Gilan province, and 15 people were considered as samples after theoretical saturation. The sampling method was purposeful. The data were analyzed using the database method and three-stage open, central and selective coding, and the dimensions were reflected in the form of a paradigmatic model. The results showed that management capabilities, support policies, export development marketing, environmental factors and characteristics of kiwi cultivation affect smart geomarketing. Also, smart geomarketing develops marketing capabilities and SDI infrastructure development. In addition, the development of marketing capabilities and the development of SDI infrastructure can increase the share in global markets, global reputation, brand development in foreign markets and increase foreign currency. Finally, the results showed that factors such as the weakness of the government, the environmental and competitive risks of the destination country, the lack of sufficient knowledge of producers and exporters, and the lack of sufficient facilities of producers and exporters can develop marketing capabilities and the development of SDI infrastructure and consequences such as increasing share in global markets, increase global reputation, brand development in foreign markets and increase foreign exchange.

The purpose of this research is to identify the infrastructural factors affecting the implementation of knowledge management in public companies of Gilan province. In order to carry out this research, firstly, by examining the background of the research, the infrastructural indicators of the implementation of knowledge management were extracted and adjusted using the opinions of experts, and finally it became the questionnaire of this research, and a sample of 384 experts and managers of state-owned companies in Gilan province answered it. . Using the exploratory factor analysis technique, 5 infrastructure factors were identified. Naming and how the relationships between them were analyzed based on theoretical foundations in Delphi group panels, and as a result, the conceptual model of the research was presented. To test and evaluate the model, the technique of structural equations has been used. Of the 5 identified factors, motivation factor with a coefficient of 0.13, organizational maturity factor with a coefficient of 0.25, structural factor with a coefficient of 0.32 and technical factor with a coefficient of 0.23 have a significant impact on the implementation of knowledge management. The GOF criterion is equal to 0.43, which shows that the infrastructural conceptual model of knowledge management implementation in public companies of Gilan province has been confirmed with high fit and strong fit.

The aim of the current research was to design a factor-based model to evaluate the impact of internal and external organizational decisions on the cost of industrial production based on the theory of constraints. The research method is practical in terms of the goal and in terms of the research process, it is in the field of quantitative and field research of an exploratory type. The statistical population of the current research is all experts and informants on the issue of the cost of industrial products, who were selected through the snowball sampling method. In this research, 25 people were selected as a sample of experts, and data related to industrial products and their pricing were used to collect data from the companies' databases to check the research objectives. Next, three methods of theme analysis, Delphi technique and factor-based model were used to analyze the data. AnyLogic software was used to run the simulation in order to validate the model. Finally, the findings showed that in this research, two types of improvement policies have been investigated: 1. The effect of product production policies on demand and product pricing in order to make the finished price competitive 2. The effect of capacity planning policies. It should be remembered that this problem was designed with the approach of the foundation agent model and the behavior analysis of the research model shows that with the application of product production policies, the cost price of products increases, which is in line with the competitive

The main purpose of this study is to identify and evaluate suppliers based on traditional, lean and agility criteria and rank them with the combined approach of fuzzy Delphi,SWARA and ARAS in Saipa Company.The research method is applied in terms of purpose and descriptive-survey in terms of data collection.First, key functional sub-criteria(traditional,lean and agile)were identified and then fuzzy Delphi technique,the effectiveness of these criteria was evaluated in Company.The statistical population in this part of the research is 30 experts and managers of the company, who due to the limited size of the community,all members of the community were considered as a sample.The fuzzy Delphi output showed that out of 20 sub-criteria identified after evaluating the experts,17criteria were finally approved.Then,using the new SWARA decision-making technique and applying the opinions of 30experts, the criteria and sub-criteria were evaluated and their weights were extracted.In traditional criteria,the sub-criteria"costs"with the highest weight in terms of importance in the first place and"operating capacity"in the last place;In lean criteria,the sub-criterion of"elimination of waste"as the most important and"supply of materials according to the needs of the industry"in the last rank;In the agility criteria, the sub-criteria of "flexibility"in the first place and"strong supplier communication"in the last place are extracted.In the final evaluation of the main criteria of the research,the criterion of"agility"was in the first place, the criterion of"lean"was in the second place and the criterion of"traditional"was in the last place.The proposed approach of this research provides a valuable conceptual framework to company managers to improve the status of suppliers.

Regardless of political-security issues, the South Caucasus, serves as a gateway for cultural, economic-trade, and political geography connections. Many analysts confirm to the region’s geopolitical, geoeconomic, and geostrategic significance, emphasizing that in order to reap the benefits of the region, countries must broaden their influence in many areas. This study attempted to clarify Iran’s significance in light of the wide-ranging effect of world actors and explore the nature of each actor’s role-playing in the South Caucasus strategic region. To this end, by using documentary and library research methods, 12 countries, entities, organizations, or unions among regional and extra-regional actors were identified, and the roles and actions that each of the actors play in the region were explained in accordance with numerous publications and studies. According to the findings, the 12 identified secondary and extra-regional actors’ actions are divided into three primary categories: economic-trade, military, strategic, security, and intelligence, and geopolitics. Furthermore, an analysis of South Caucasus business transactions revealed that Iran’s position as one of the regional countries with common borders with two major South Caucasus countries, namely the Republic of Azerbaijan and Armenia, has weakened and requires reinforcement in the region when compared to Russia and Turkey as regional actors, the US, China, European countries, and Israel as extra-regional actors that are mostly G20 members.

Demonstrating social responsibility in companies' business activities is equally valuable for advancing social and business goals. The aim of this study was to present the model of corporate social responsibility in the field of green marketing from the perspective of consumers of organic products. The research is qualitative and the research method is based on data. The tool used to collect the data was an interview. The statistical population of the study included managers and experts of companies producing organic products with a social responsibility and green marketing approach. The theoretical method was used for sampling until the theoretical saturation was reached and finally 14 people were interviewed. Data analysis was performed through coding in three stages open, axial, and selective coding. From the results of data coding, 83 concepts, and 26 categories were identified. The research model according to the dimensions of the data-based approach, causal conditions (acceptance of social responsibilities, social culture, public acceptance of social activities, health orientation in business, and responsibility of community members), the main phenomenon (healthy production, environmental protection, implementation of social responsibility, environment-based marketing And social marketing), contextual conditions (business environment, customer's brand image, trust in organic brands and affiliation with organic brands), intervening factors (adherence to ethics, customer payments and value of organic products), strategies (respect for stakeholders' rights, Customer relationship management, green marketing development, social action transparency, and brand equity) and outcomes (improved green and organic purchasing, customer satisfaction, sustainable business development, and business success) were presented.

The issue of employing young managers in the country’s management system has been a serious concern for many years. In the meantime, some experts believe that the country’s current management system is not ready for the presence of young people and that the current mechanism is more substitute-oriented than successor-oriented. The purpose of the present study was to design a comprehensive model of managerial succession in Iranian organizations. The current research is fundamental in terms of its purpose, and a qualitative method and a meta-synthesis approach were used to carry it out. For this purpose, all the qualitative studies conducted inside the country that dealt with the issue of surrogacy were selected as samples and then they were analyzed using the seven-step model of Sandelowski and Barroso (2006) and MAXQDA 2020 software. The results extracted from 54 chosen studies showed that the effective dimensions on the succession process include five organizational, managerial, individual, institutional and cultural dimensions, which include mechanisms, processes, policy making, evaluation, consequences, human resource management, leadership, skills, personality and job characteristics, resource conflict, legal and ethical issues have been observed in them. Also, among the approved indicators, indicators of intra-organizational support, evaluation of people's performance and capability, evaluation of the succession process, determination of key jobs, talent pool, job qualification conditions, career path, determination of policies, succession committee and competence gap analysis were the most important indicators.

While the closed-loop supply chain network was created launch, to design, and exploit the flow of materials between chain centers, supply chains face different risks, including operational ones and disruption. Each of such risks can lead to irreparable damage. Therefore, designing or redesigning supply chains to make them resilient against different risks is one of the most important programs that potentially affect the supply chain’s performance. The purpose of this research  is to design a resilient closed-loop supply chain network under the operational risks and disruption conditions by the Mulvey approach in Tehran's food industry companies with multi-products.
In this research, the problem of the resilient closed-loop supply chain is considered as a network of nodes (production sites) that are connected by arcs (paths). The model is formulated as an integer programming, the objective function of which involves maximizing the number of nodes in estimating demand and minimizing costs based on a series of scenarios developed by the Mulvey approach.
In the practical phase, first, a closed-loop supply chain consisting of 10 manufacturers, 300 distributors, and two types of products was considered for modeling. Then, three more important scenarios with probabilities of 0.3, 0.2, and 0.5 were developed to present different amounts of customer demand and facilities capacity depending on the number of disruptions. Solving the problem for the multi-product food companies, using the LP metric model showed that despite no disruption in the supply chain, the robust optimal solutions for the first and second objective functions were equal to 99.484 and 790.50, respectively. In terms of manufactured products; in the first node, the amounts of products 1 and 2 did not change for the first and second scenarios but changed by 1.4 and 2.5 units in the third scenario. In the third node, the amount of product 1 did not change for the first scenario, but for the second and third scenarios, it changed by 10.60 and 6.8, respectively. The amount of product 2 did not change for the first and third scenarios but changed by 7.7 for the second scenario. In the 10th node, the amounts of products 1 and 2 did not change for the second scenario, but the amount of product 1 changed by 2.8 and 2.3 for the first and third scenarios. In addition, the amount of product 2 changed by 10.3 and 2.8 for the first and third scenarios, respectively. In the other nodes, the amounts of the products did not change. For both of the products in different nodes, except in nodes 4, 6, 7, and 9, and product 1 in node 8, some problems had to be fixed.
According to the findings, developing the proposed model reduces operational risks and disruption as the most important causes of inefficiency in the supply chain. So, it is necessary to design robust and resilient supply chains in all industries, especially in the food industry due to its significance.

What experienced today is a huge shift from material resources to knowledge. Physical and financial assets are now necessary but insufficient to achieve the goals of the organization. Instead, knowledge, technology settings, good customer relations, information systems, etc., which constitute the intellectual capital of the organization, are recognized as the key factors of success in the information age. It believed that intellectual capital, including human capital and structural capital, has an increasing role in the performance of the company and is effective on its financial achievements such as market value, profitability, productivity, etc. The purpose of this study is to investigate the relationship between tendencies to the market is in line with the creation and development of new products on the financial performance of Iran Dairy Industries Company (Pegah). In terms of implementation method, this research is a descriptive research from the correlation branch and from the survey group and is cross-sectional in terms of time. 15 production companies and 5 sales areas of Iran Dairy Industries Company (Pegah) were considered as the research community . The results showed that the market orientation from the sub-section of innovation strategy in the direction of the tendency to create new products has an impact on the financial performance of the company and this effect is significant.

Given the agricultural potential of Iran on one hand, and the shortages in Russia's fruit and vegetable supply, along with its expanding vegetable market on the other, Russia has become a major market for Iranian exporters of fruits and vegetables. The aim of this study was to identify and rank strategies and tactics for the development of fruit and vegetable exports to the Russian market. The research followed a developmental-applied approach in terms of goals, and employed a descriptive survey using an exploratory mixed method. The statistical population consisted of experts and fruit and vegetable exporters to Russia, who were sampled using the purposive snowball technique. The qualitative phase included 20 participants, while the quantitative phase involved 100 individuals. The qualitative data were analyzed using content analysis to derive strategies and tactics, which were then ranked in the quantitative phase using the TOPSIS technique. Two strategies, namely entry and sustainable presence, were identified for the development of fruit and vegetable exports, along with 28 corresponding tactics. Finally, the top ranks were assigned to fixing regulations, establishing incentives, and stabilizing the exchange rate.

Organic products are important factors in the case of commitment to corporate social responsibility in the field of green marketing to develop the Commitment of business system to environmental issues. The study aimed at presenting and testing social responsibility of companies in the field of green marketing from the perspective of Consumers of organic products with an emphasis on brand dependence. The research was an applied research and it was of mixed and exploratory type. Statistical population of the qualitative consisted of an all customers of organic products in Tehran city which according to the Krejcie-Morgan table, 385 people were Surveyed. Data analysis was also done using structural equation modeling and PLS software According to the findings obtained in qualitative data coding, A total of 325 Concepts were extracted which were classified into 85 categories. According to the categories (22 main Categories) in the model, regarding database approach, the research model was presented. Also, quantitative analysis showed that causal conditions affect the main phenomenon, namely social responsibility in the field of green marketing of organic products. Social responsibility affects strategies in the field of green marketing, background conditions and intervener conditions. In addition, these strategies also affect the consequences of the model.

The aim of this study was to present the model of social responsibility in the field of green marketing of organic products with emphasis on brand dependence. The research is qualitative and the research method is based on grounded theory. The tool used to collect the data was an interview. The statistical population of the study included managers and experts of companies producing organic products with a social responsibility and green marketing approach. The theoretical method was used for sampling until the theoretical saturation was reached and finally 14 people were interviewed. Data analysis was performed through coding in three stages of open, axial and selective coding. From the results of data coding, 83 concepts and 26 categories were identified. Research model was presented according to the dimensions of the grounded theory approach, i.e. causal conditions (5 factors), main phenomenon (5 factors), contextual conditions (3 factors), intervention factors (3 factors), strategies (6 factors) and consequences (4 factors).