Journal of value creating in Business Management

Abstract Abstract The aim of this study is to present a model to investigate habit formation in purchasing life insurance in Iran. The present study is applicable in terms of its purpose, and descriptive in terms of its nature and method. The statistical population of it includes all the activists in the insurance industry in Iran. The method and sample size in determining the appropriate degree of the proposed model was also carried out by the available sampling method with 35 experts. The collection tool in this study includes a researcher-made questionnaire derived from the qualitative method, which includes 4 areas of economic factors, non-economic factors, factors affecting customer withdrawal, and long-term factors affecting life insurance demand. SPSS software was used to analyze the findings, and structural equations and LISREL software were used to fit the model. The research findings showed that the statistical value of the previous year's insurance demand variable was measured significantly, so it can be stated that the hypothesis of habit formation in purchasing life insurance using the conditional variance heteroscedasticity multivariate autoregression approach has a significant effect. In addition, other variables have a direct and significant relationship with life insurance demand. Introduction The three institutions of banks, insurance, and stock exchanges are of particular importance in providing financial resources for investments. The insurance industry is one of the most important pillars of the economic development of countries. By reviewing the contribution of the insurance industry in the economy of developed countries, it can be seen that insurance has a greater and more significant role and importance compared to other services (Babaei, 2020). The role of the insurance industry in financial markets appears in three ways. First, the effect that this industry can exert on other financial markets, which is usually used as a support to reduce investment risk. Its second role is to collect and provide financial resources using insurance operations, and finally, the role of the insurance industry in indirect or direct investment. Direct investment of the insurance industry in the country's economic activities is its most important role. In the role of risk coverage, insurance companies act like a cooperative fund. In other words, they act to pay for the losses incurred from the collected resources. But in the role of financial inputs, insurance acts as a capital supply fund that seeks to maximize profits like an economic enterprise (Haris et al., 2019). For this reason, it is tried to maintain an appropriate combination of insurance types in order to achieve the goals. One type of insurance policy that is significantly attractive in the composition of the insurance sales portfolio is life insurance. In selling life insurance, insurance companies use the funds of policyholders that they have in the form of technical reserves as a profitable asset and invest in appropriate economic activities. The features of this insurance policy such as low loss ratio, long-term commitments, and short-term and continuous resource provision, have made insurance companies advocate this type of insurance, unlike third-party and medical insurance. For this reason, the factors that affect its sales are of interest to insurance companies. In addition to economic variables, these factors also include non-economic ones. In fact, insurance companies are interested in developing their activities in this area by being aware of the decision-making model of life insurance buyers (Moore & Young, 2020(. Studying the effect of each of these factors will play a key role in developing life insurance sales for insurance companies. Recognizing this issue, sellers should think about developing the insurance network by understanding the psychological issues of policyholders as life insurance buyers. The development of the insurance industry, especially life insurance, as mentioned at the beginning, will play a significant role in the economic development of the country. Therefore, the researcher is trying to address the question: what is the appropriate model for examining the formation of the habit of buying life insurance in Iran? Theoretical Framework Life Insurance Insurance is a contract that transfers an imminent risk that may occur to an individual's property, activity, or life to the insurance company in order to compensate for the material loss caused by the risk (Karimi & Zaghian, 2020). Life insurance is one of the most important fields of personal insurance. Legally, life insurance is a contract under which the insurer undertakes, in return for receiving a premium, to pay an amount (capital or annuity) to the policyholder or a third party designated by him in the event of the insured's death or survival at a certain time (Ahmadi et al., 2021). Amari Allahyari et al., (2024) examined the relationships between service quality dimensions and the intention to purchase life insurance policies. The results obtained show that service quality plays a vital role in increasing customer satisfaction and improving organizational performance. The findings show that life insurance representatives with problem-solving and helpfulness skills can increase customers' willingness to purchase life insurance products. This research emphasizes that high service quality is a key competitive advantage in the life insurance market and must be aligned with organizational goals. Li et al., (2021) examined the demand for non-life insurance under habit formation by presenting a dynamic model for the optimal consumption of non-life insurance according to past weighted average consumption. In their study, habit is divided into two types: internal and external. Internal habit is influenced by the discussion of risk aversion, and external habit is influenced by the discussion of false comparison to others and the comparison of different investment options, including stocks. Research Methodology The present study is applicable in terms of purpose, and descriptive in terms of nature and method. The statistical population of the present study includes all activists in the insurance industry in Iran. The method and sample size in determining the appropriate degree of the proposed model were also carried out as a available sampling method for 35 experts. The collection tool in this study includes a researcher-made questionnaire derived from a qualitative method, which includes 4 areas of economic factors, non-economic factors, factors affecting customer withdrawal, and long-term factors affecting life insurance demand. Research Findings SPSS software was used to analyze the findings and the model was fitted using structural equations and LISREL software. The research findings showed that the statistical value of the previous year's insurance demand variable was significantly measured, so it can be stated that the hypothesis of habit formation in life insurance purchase using the conditional variance heteroscedasticity multivariate autoregression approach has a significant effect. In addition, other variables have a direct and significant relationship with life insurance demand. Conclusion The present study was conducted with the aim of providing a model to investigate habit formation in life insurance purchase in Iran. The results of this study are consistent with the results of Amari Allahyari et al., (2024), Li et al., (2021), Ahmadi et al., (2021), Ghasemi Aghdami et al., (2021), Karimi & Zaghian (2020), Abdolsalam (2021), and Tan et al., (2018). Amari Allahyari et al., (2024) showed that service quality plays a vital role in increasing customer satisfaction and improving organizational performance. The findings show that life insurance representatives with problem-solving and helpfulness skills can increase customers' willingness to purchase life insurance products. This study emphasizes that high service quality is a key competitive advantage in the life insurance market and should be aligned with organizational goals. Based on the present study, the following suggestions are made: •Reforming the organizational structure of the investment unit. •Reforming the regulations related to the investment limit of life financial resources. •Using experimental advertising by insurance companies in order to confirm the habit formation hypothesis. •Insurance companies can design optimal strategies in line with customer demand for life insurance by measuring factors related to monitoring and controlling the organization's internal processes and employing expert personnel at different levels.

Abstract Abstract
The aim of the present study was to mathematically model the forecast of iron ore prices and its by-products. The present study is applicable in terms of its purpose, and survey in terms of data. The main data collection methods in the present study are library methods. The daily price of Iranian oil was obtained by referring to the website of the Organization of the Petroleum Exporting Countries (OPEC). The daily price of iron ore stocks was extracted from the website of the Commodity Exchange, and the price of Bahar Azadi coins and the dollar rate were extracted from the Central Bank of Iran. The indices were first extracted from library studies. In this study, the statistical population includes the daily price of iron ore stocks for 2,058 working days. Given that severe fluctuations in stock prices will affect the forecast; the statistical sample used in this study includes daily iron ore stock prices during the period of companies entering the stock exchange from 20/03/2016 to 19/03/2022. Matlab and Dematel software were used for predictions made by fuzzy inference. Based on the findings of the studies, 12 variables were extracted as predictor variables to design the prediction model. Dematel results showed that 7 factors: other suppliers' prices, seasonal effect of order registration, prices of past periods, government tariff rate, exchange rate, oil price, and world iron ore price were the most influential factors. Adaptive neural fuzzy approach is one of the important approaches for comparing the effectiveness of different factors. The results showed that the exchange rate has the highest frequency among the seven available variables, followed by the world iron ore price.
Introduction
Continuous and sustainable economic growth in any economy requires the optimal mobilization and allocation of resources at the national level. In economic literature, capital is considered the lifeblood of the economic system, and its formation has been emphasized as one of the determining factors of economic growth and development. Basically, the rate of economic growth and development depends on capital accumulation on the one hand; and on the other hand, on the productivity factor in economic activities. These two basic factors depend on the nature of the investment process; therefore, one of the most important tasks of financial markets is to facilitate capital formation. Capital markets can well handle both of the aforementioned tasks of capital accumulation and increasing economic productivity (Farajian & Farajian, 2022).
The iron ore trade in the world has faced major changes with the rapid growth of developing economies in regions such as China, India, and South Korea as key growth centers in this sector, and the industrialized economies of the European Union and North America are gradually losing their dominant role in this market. Currently, the developing regions of Asia are the center of growth in steel production and consumption. Most steel-producing regions import most of their iron ore resources, and some others have insignificant or uneconomic iron ore resources. The most prominent of these are the steel industries of China and Japan. The growth in demand for iron ore imports has led to a significant increase in production in countries such as Brazil and Australia, as a combination of large, high-quality iron ore resources accessible to ports, and iron ore resources for the export market have been developed. In view of what has been said, the present study seeks to answer the question: what are the effective factors in determining the price of iron ore and how is the comparison of effective factors using the fuzzy neural network method?
Theoretical literature
The iron ore industry plays a key and influential role in the growth and development of a country. On the one hand, this industry is fundamental in development, and on the other hand, it is considered a benchmark for the industrialization of countries. Therefore, its improvement and development is of particular importance. Basic industries such as transportation, construction, machinery manufacturing, mining and other industries related to energy production and transmission are dependent on products made from iron ore. Therefore, global demand for iron ore is high and will remain stable in the future, if not increase (Hao et al, 2018). After the 2008 financial crisis, when supply and demand fell sharply, supply and demand were on an upward trajectory. Of course, so far the growth rate of supply has been greater than demand, and it is likely that the iron ore surplus will continue to grow, which could ultimately have a significant impact on iron ore prices. World crude iron ore production in 2010 reached 1.238 billion tons, with a growth of 15% compared to 2009. This number was 1.694 and 1.8 billion tons in 2013 and 2014, respectively. The apparent consumption of iron ore in 2010 was 144.8 million tons, which was an increase of 13.2% compared to the previous year. This number was 168.1 and 171.5 million tons in 2013 and 2014, respectively (Hao et al, 2018).
Factors Affecting Iron Ore Prices
Economic Factors
The economic situation of each country and the global economic situation in general have a major impact on the level of domestic and foreign demand for iron ore, and as a result, it has a significant impact on the export of iron ore in exporting countries (Azimi & Afrough, 2015).
Political Factors
Other factors affecting the trend of iron ore exports are political factors and trends. These factors are often accompanied by economic burdens. Regional and international political crises and the increasing acceleration of arms races can also be a powerful factor in increasing the production and export of iron ore (Azimi & Afrough, 2015).
Substitute goods
Although iron ore substitutes do not have an immediate impact on iron ore exports, they can have a significant impact in the long term. With the passage of time and the advancement of science and technology, new possibilities are provided for the production of new types of petrochemical products that are not only more resistant and more malleable, but also have greater relative advantages over iron ore in terms of erosion and application methods (Farajian & Farajian, 2021).
Price levels
The price level of iron ore products is also one of the factors affecting its export volume. Among the factors that have increased the export volume of iron ore products from countries such as Japan and other common market countries to the domestic markets of the United States has been the low price level of exported products compared to the price level of domestic production in the United States (Farajian & Farajian, 2021).
Exchange rate changes
The exchange rate is one of the most important variables affecting exports. It is important to examine the speed of the impact of these variables on exports. As trade between countries increases, exchange rate fluctuations are considered one of the most important sources of corporate risk (Mojdeganlou & Hosseini, 2021).
Research Methodology
The present study is applicable in terms of its purpose, and survey in terms of data. The main data collection methods in the present study are library methods. The statistical population includes elements, components, and individuals or units that share at least one attribute. In this study, the statistical population includes the daily price of iron ore stocks for 2058 business days. Given that severe stock price fluctuations will affect the forecast, the statistical sample used in this study includes the daily prices of iron ore stocks during the period of companies' entry into the stock exchange from 20/03/2016 to 19/03/2022. For the predictions made by the fuzzy inference system, MATLB and DEMATEL software were used.
Research findings
In this section, the adaptive neural fuzzy approach, which is one of the important approaches for comparing the effectiveness of different factors, is used. The important point is that in this section, 7 influential factors that are the result of the DEMATEL method are examined and explored, and their effect on the final or output variable, i.e. the price of iron ore, is examined in pairs; and finally, the factors that have the highest frequency are listed. First, the influencing factors (prices of other suppliers, seasonal effect of order registration, prices of past periods, government tariff rate, exchange rate, oil price, world price of iron ore) are introduced as a result of the DEMETL method. According to the results, the exchange rate has the highest frequency among the seven variables available, followed by the world price of iron ore. After that, the seasonal effect of order registration and the variables of government tariff rate and oil price are followed. The least frequent variable is the price of past periods, which has only been dominant once in the permutations.
Discussion and Conclusion
The aim of the present study was to predict the price of iron ore and its by-products based on time series neural networks. For this purpose, first, library studies were conducted based on which, 12 variables were extracted as predictor variables to design the prediction model. The results of DEMETL show that 7 factors: price of other suppliers, seasonal effect of order registration, prices of past periods, government tariff rate, exchange rate, Oil price and world iron ore price were the most influential factors. The results showed that the exchange rate has the highest frequency among the seven variables, followed by the world iron ore price. After that, the seasonal effect of order registration and the variables of government tariff rate and oil price are next. The least frequent variable is the price of past periods, which has only been dominant once in the permutations. The results of this finding are somewhat consistent with the results of Lee et al., (2017) and Lin & Si (2021).

Abstract Abstract The aim of the present study is to determine a pattern for identifying uncertainty and risk and increasing flexibility in capital budgeting decisions with an investment discretionary approach. The research method is applicable-developmental in terms of its purpose, and qualitative in terms of the nature of the data. The statistical population of this study included 18 power plant experts from Mejmar who had at least 10 years of teaching, research, and management experience in power plants. Purposive sampling was used in this study. The data collection method was referring to documents and semi-structured interviews. Atlas ti software was used to code the interviews for data analysis. Based on the results obtained, 6 constructive themes and 14 basic themes were identified. The 6 constructive themes include political and international factors, legal and regulatory factors, financial and budgetary factors, technological and information factors, organizational structure and culture, and economic factors. The dimensions of the organizational structure and culture factors include: the structure and organization domain, the human resources domain, and the management domain. The dimensions of the technological and information factors include: the information technology environment domain and the information sharing domain. The dimensions of the economic factors include: the economic structure and the economic environment. The dimensions of the political and international factors include: the political structure and environment and transnational and international factors. The dimensions of the legal and regulatory factors include: general legal factors and specific legal factors. The dimensions of the financial and budgetary factors include: the human factors and individual capabilities domain, the intra-organizational requirements and factors domain, and the extra-organizational factors and requirements domain. Introduction Since the late 1970s, along with the spread of advanced financial techniques such as internal rate of efficiency and net present value at the firm level, many researchers have offered criticisms regarding the use of these techniques in valuing strategic investment decisions (Dai et al., 2021). The first criticism is related to the inability of these techniques to correctly value uncertain investments, under conditions where the firm has a degree of flexibility in decision-making (Alipour and Behdadian, 2020). In particular, early proponents of the option theory of capital assets criticized the NPV method for considering decisions only in terms of whether or not they are or are not, without considering the value of flexibility (choosing between different options when receiving new information). Using the theoretical framework presented for pricing contingent claims, financial researchers have proposed the option theory of capital assets as an alternative to the NPV method to overcome its shortcomings. Since the aforementioned conditions are often related to the structure of strategic decisions, the option theory of capital assets claims to be the best method for valuing such decision-making problems (Cheong, 2021). Recent research shows that about 20 percent of industrial projects are terminated before completion, and less than a third of them are completed on time and based on budget. Effective risk management is absolutely essential to prevent these problems from occurring. In fact, flexibility is a key factor in project success (Dai et al., 2021), because by it, senior management can design and develop risk coping tools according to the requirements and conditions of the risk. The option method allows project managers to be aware of the consequences of risk, deal with it in case of adverse events and use it in the best way if conditions are favorable, select the best capital allocation option and justify it to senior management and financial stakeholders. Therefore, this research, considering the Majmar Power Plant Group, seeks to answer the question: What is a model for identifying uncertainty and risk, and increasing flexibility in capital budgeting decisions with the investment option approach? Theoretical Literature Risk In the past, people used to rely only on financial information obtained from statements prepared based on historical values ​​and analyzed by experts to make decisions about investment locations. However, since the collapse of large companies such as Enron and WorldCom due to the failure to disclose financial scandals by company managers, investors have paid more attention to the prominent role of the governance system and its principles (Komar et al, 2017). On the other hand, after the separation of the legal personality of commercial enterprises from the real personality of their owners and the development of global trade and the owners' need for financing sources, the discussion of multiple owners in companies took shape and led to the creation of joint-stock companies. In the meantime, each of the shareholders; especially those who had more influence (which was mainly due to the high volume of their capital), tried to direct the financial decisions of the companies towards their own interests (Cerchiello et al, 2016). For many years, economists assumed that all groups in a corporation work for a common goal. However, in the past 30 years, many cases of conflicts of interest between groups and how companies deal with such conflicts have been raised by economists. These cases are generally expressed under the title of “agency theory” in management accounting. According to Jensen and Meckling’s definition: an agency relationship is a contractual relationship in which a principal or owner appoints a representative or agent on his behalf and delegates decision-making authority to him (Chen et al, 2019). The greater the number of major shareholders in the company’s ownership structure, the more supervision and control is shared among the major shareholders and the conflict of interest between them decreases; therefore, the company’s efficiency on equity increases (Kou et al, 2019). Research Methodology The present study is an applied-developmental study in terms of its purpose, and a content analysis study in terms of its research implementation method. The statistical population of this study includes 18 Iranian power plant experts who have at least 10 years of teaching, research, and power plant management experience. The sampling method used in this study was purposive. Qualitative content analysis can be considered a research method for the subjective interpretation of textual data through systematic classification, coding, and theme-building processes or designing known patterns. After taking interviews from participants and writing line by line the text related to the interviews, the researcher analyzed the texts; in fact, in this method, codes, concepts, and categories were identified through a systematic classification process, and then a model of uncertainty and risk and increased flexibility in capital budgeting decisions with an investment discretionary approach was presented. The snowball technique was also used to select participants, and each interviewee was asked to provide the researcher with a list of people who were willing and specialized to participate in a study. Coding was used to analyze the data obtained from the interview and theoretical foundations. Atlas ti software was used for analysis. Research findings Based on the results obtained from thematic analysis, 6 constructive themes, 14 basic themes and 132 initial codes were identified. The 6 constructive themes include political and international factors, legal and regulatory factors, financial and budgetary factors, technological and information factors, organizational structure and culture, and economic factors. The dimensions of the organizational structure and culture factors include: structure and organization, human resources, and management. The dimensions of technological and information factors include: information technology environment and information sharing. The dimensions of economic factors include: economic structure and economic environment. The dimensions of political and international factors include: political structure and environment, and transnational and international factors. The dimensions of legal and regulatory factors include: general and general legal factors and specific legal factors. The dimensions of financial and budgetary factors include: human factors and individual capabilities, intra-organizational requirements and factors, and extra-organizational factors and requirements. Discussion and Conclusion The aim of this study was to develop a model for identifying uncertainty and risk and increasing flexibility in capital budgeting decisions with an investment discretion approach (study in the Mejmar power plant group). The coding and text analysis process of the interviews was carried out in the Atlas ti qualitative data analysis software. Based on the results obtained from thematic analysis, 6 constructive themes, 14 basic themes, and 132 primary codes were identified. The results of this study are somewhat consistent with the results of Mashhadizadeh et al, (2020) and confirm the results of this study. According to the results of the study, it is suggested: to increase flexibility in the organizational structure, a map of the current organizational structure can be prepared and factors such as organizational hierarchy, different units, and the relationships between them can be examined. Then, according to the needs and market conditions, optimization of the organizational structure can be proposed and the necessary reforms can be applied. This includes modifying hierarchies, creating matrix teams, increasing coordination, and transferring responsibilities and competencies. By planning and implementing training and professional development courses for employees, they can be improved and provided with the necessary capabilities to deal with changes and risks. By encouraging teams and employees to actively participate in decision-making and budgeting processes, the flexibility of the organization can be increased.

Abstract Abstract The purpose of this study is to provide the pattern of effective factors in the socialization of artificial intelligence technologies. The present research is applicable in terms of purpose, quantitative in terms of implementation, and of descriptive-survey type in terms of nature. The statistical population of the research included 20 board members, financial managers, accountants and auditors, as well as financial statements and engineers in the field of artificial intelligence in the hierarchical method, selected by judicial and targeted sampling method; and, 342 of all employed accountants in the structural equation sector, by random sampling. Research collection tool is a questionnaire. A hierarchy of Expert Choice software as well as structural equations (PLS) was used for data analysis. The results of the analysis showed that independent variables and dependent variables have directly a positive and significant effect. The results also showed that increasing efficiency and productivity is the first priority, creativity and innovation is the second priority, saving time and money is the third priority, analyzing financial data is the fourth priority, collaboration and cooperation is the fifth priority, matching transactions is the sixth priority, transparency is the seventh priority, determining training needs is the eighth priority, trust in financial tools is the ninth priority, ease of use is the tenth priority, user-friendly tools are the eleventh priority, automation of repetitive processes, real-time financial analysis and financial protection and security are the twelfth priority, improving financial reporting is the thirteenth priority, and awareness, technical knowledge, and the capabilities of financial tools are the fourteenth priority. Introduction The advancement and utilization of artificial intelligence technologies transforms conventional patterns of life and work, thereby creating indelible changes in the social environment to adapt to the current society in which information is rapidly evolving. All disciplines and professions are rebuilding or improving their strategies, organizations, products, and approaches. Accounting is no exception (Concept et al, 2019). Accounting can now use electronic accounting, data mining, and multidimensional data analysis. However, accounting technologies and methods are merely a subsector which is being changed by artificial intelligence, and can have a significant impact on accounting goals (Yubin et al, 2021). Artificial intelligence is an essential component for the implementation of international accounting law. Accounting rules require systems support in complex risk coverage programs, and law enforcement is one of the important advantages of artificial intelligence in the accounting profession (Cong et al, 2018). Makridakis (2017) believes that artificial intelligence will soon replace traditional accounting and auditing. This change will lead to the separation of traditional accounting and auditing and will help accounting staff to improve their work. Accounting posts, structure optimization, restructuring as well as work quality and the ability of settings are the advantages of using artificial intelligence. Accounting needs to be modified to be more reliable in the community. For example, by means of artificial intelligence, accounting uses accounting robot to build simulator models from the environment. The financial robot has an instantaneous implementation speed. Information and automation of the accounting process under instantaneous response and conditions improves the efficiency of accounting activity. Proper programming of the financial robot can ensure the decline and specifications of each link, and can effectively reduce the occurrence of errors according to the designated methods. The financial robot only executes financial employees and legal steps. It performs data entry and step by step operation, thereby reduces artificial operations in accounting, and greatly prevents artificial operations (Suleiman et al, 2020). In this regard, the main question of the research is: What is the pattern of influencing factors in the socialization of artificial intelligence technologies in accounting? Theoretical framework Artificial Intelligence Artificial intelligence is a branch of computer science that examines the computational requirements of actions such as perception of reasoning and learning, and provides a system for doing so. Its main roots and ideas should be sought in the philosophy of linguistics, mathematics, psychology, neurology and physiology, and it has various applications in computer science, engineering sciences, biology and medicine sciences and many other sciences (Han et al, 2023). Socialization The socialization stage is the stage where an individual learns social norms. This stage is the same as the assimilation stage in the psychoanalytic system of form and the learning stage according to Blumer. After socialization of the assimilation or socialized learning stage, the socialized stage begins, meaning accepting social and cultural norms and in other words, becoming in tune with them or, according to Blumer, unifying and melting into them (Arizi & Barati, 2017).  Karamipour (2023) investigated the design of artificial intelligence competencies on organizational performance, taking into account the commercial marketing capabilities. The results showed that the mechanisms of artificial intelligence competencies influence the business-to-business marketing capabilities and organizational performance, and also the artificial intelligence ​​competencies model is validated on organizational performance by considering the aspect of business-to-business marketing capabilities. Pourshahabi (2023) examined the presentation of a systematic model of employee training using artificial intelligence. The research findings show that the inputs of the model include 1- educational data, 2- personal information, 3- educational needs, 4- user feedback, and 5- workplace data. The model process also includes 1- determining needs and goals, 2- data collection, 3- data preprocessing, 4- training the artificial intelligence model, 5- model evaluation and improvement, 6- implementation and deployment, and 7- monitoring and updating. Finally, the outputs of the model include 1- individual feedback, 2- educational suggestions, 3- monitoring and follow-up, and 4- support and guidance. Research Methodology The present research is applicable in terms of purpose, quantitative in terms of implementation, and of descriptive-survey type in terms of nature. The statistical population of the research included 20 board members, financial managers, accountants and auditors, as well as financial statements and engineers in the field of artificial intelligence in the hierarchical method, selected by judicial and targeted sampling method; and, 342 of all employed accountants in the structural equation sector, by random sampling. Research collection tool is a questionnaire. Research findings A hierarchy of Expert Choice software as well as structural equations (PLS) was used for data analysis. The results of the analysis showed that independent variables and dependent variables have directly a positive and significant effect. The results also showed that increasing efficiency and productivity is the first priority, creativity and innovation is the second priority, saving time and money is the third priority, analyzing financial data is the fourth priority, collaboration and cooperation is the fifth priority, matching transactions is the sixth priority, transparency is the seventh priority, determining training needs is the eighth priority, trust in financial tools is the ninth priority, ease of use is the tenth priority, user-friendly tools are the eleventh priority, automation of repetitive processes, real-time financial analysis and financial protection and security are the twelfth priority, improving financial reporting is the thirteenth priority, and awareness, technical knowledge, and the capabilities of financial tools are the fourteenth priority. Conclusion The present study was conducted with the aim of providing a model of effective factors in the socialization of artificial intelligence technologies. The results of this study are in line with the results of Harikumar et al, (2023), Pourshahabi (2023), Karamipour (2023), Shirzad et al, (2023), Anca (2022), Noordin et al, (2022), Mahdavi (2022), and Jakob & Luciano (2021). Harikumar et al, (2023) concluded that artificial intelligence in e-commerce and financial industries has been used to achieve better customer experience, efficient supply chain management, improve operational efficiency and reduce material waste with the aim of designing standard and reliable methods of product quality control and finding new ways to reach customers and serve customers at low cost. Among the applications of artificial intelligence in e-commerce; corporate management and finance, sales growth, profit maximization, sales forecasting, inventory management, security, fraud detection and portfolio management are some of the main applications of artificial intelligence. According to the results of the research, the following suggestion is made: Accountants are advised to use artificial intelligence in the accounting and reporting process because the artificial intelligence system is completely proficient and has sufficient data in this regard. It can easily provide fast reporting and can also easily provide accurate reporting; that is, it can provide accurate reporting at any time. According to the conditions that the artificial intelligence system has, we can get from it, and it is enough to have data and it can obtain a lot of data itself; that is, it can be placed in the path of the information exchange system and exploit reports and data and it can itself provide accurate financial reporting in any style that the organization needs.

Abstract Abstract The aim of the present study is to identify and investigate the effectiveness of supply chain risk indicators of online business activities in the food industry through machine learning method using single support vector algorithm. The research method is applicable in terms of its purpose, and mixed (qualitative-quantitative) in terms of implementation method. In the qualitative part, interviews with experts active in the food industry with complete information and sufficient experience in the supply chain of this industry have been used until theoretical saturation, which were 10 people of relevant experts in large companies in this field. In the quantitative part, the field method and questionnaire were used to collect data with statistical methods, and this number was also 114 people selected as a sample from the statistical population. Considering the data conditions and the application of machine learning in the supply chain, the support vector machine algorithm, one of the most powerful algorithms in the field of artificial intelligence, was used. The results showed that customer satisfaction has a negative effect in the research model. Supply chain coordination has a positive effect in the research model. Factors affecting costs have a positive effect, but its amount is moderate. Economic and market conditions have a positive effect in the model. Internet infrastructure has limited importance in the model. Environmental risks have a positive effect. Product quality has a negative effect in the model. Introduction Today, risk management is one of the effective factors in every industry and business activity in economic enterprises around the world. Therefore, for this purpose, it is first necessary to identify the relevant risks (Rajendran & Ravindran, 2019). Companies are always looking for ways to deal with work uncertainties. In this regard, risk management has been introduced as an efficient tool for organizational managers. Risk identification and management is a new approach used to strengthen and improve the effectiveness of organizations (Ghaderi & Tariverdi, 2020). Risk management is a logical and systematic method for analyzing, assessing, and dealing with risk related to any type of activity that enables organizations to minimize losses while taking advantage of opportunities. (Rahnamaye Rudposhti & Soleimani, 2021). Increasing costs and complexities in organizations, along with increasing uncertainty and risk, have led managers to use risk management to reduce risk-taking and deviation from goals (Jalali & Moghadamnia, 2022). Identifying supply chain risks based on minimizing and managing these risks has always been an important challenge for industries and organizations. Supply chain risks increase the likelihood of unexpected events occurring in this chain that may cause significant losses to the organization (Mehrmanesh & Safavi Mirmahalleh, 2020). In this article, we decided to identify these factors in order to determine these risks in general and specifically in our country's market and in the food industry. On the other hand, by analyzing data in artificial intelligence methods such as machine learning, human error can be significantly reduced. Accordingly, the present study seeks to answer the question: What is the effectiveness of supply chain risk indicators in online business activities in the food industry through machine learning methods using the unit support vector algorithm? Theoretical framework Supply chain A supply chain is defined as a set of functional activities (transportation, inventory control, etc.) that are repeated many times along the flow channel and by which raw materials are converted into final products and value and reach the consumer. Since globalization has opened new markets and intensified competition, organizations have been able to reduce production costs by developing more complex supply chains to compete in the global market (Kamalahmad & Mrllat-Parast, 2016). Risk Management In the conventional sense, risk management means compensating for known risks by managing them. In the past, risk or danger was seen as a result of natural causes that could not be predicted. However, in a modern, managed thinking based on current science in the field of risk management, a view has been presented that risk can be measured and controlled provided that there are effective and efficient systems (Sepahvand & Vaghfi, 2021). Ahmadi et al., (2023) studied the design of a distribution channel selection system in the oil industry supply chain using a combination of adaptive neural-fuzzy network and metaheuristic algorithms (case study: National Petroleum Distribution Company of the West Azerbaijan Dual Regions). In order to analyze the data, confirmatory factor analysis, adaptive neural-fuzzy network in the basic mode, and adaptive neural-fuzzy network combined with genetic and particle swarm optimization algorithms were used. In this study, a hybrid distribution channel selection system was first designed and then evaluated based on the input scores using the system designed based on the least error, traditional distribution channel, and fuel station branding design. The results show that the best system for distribution channel selection was the adaptive neural-fuzzy network combined with the particle swarm algorithm. By comparing the performance of the branding plan and the traditional method, it was determined that the branding plan performed better and was a suitable distribution channel for the National Oil Products Distribution Company of the West Azerbaijan Dual Regions. Brusset et al., (2023) addressed this issue in a study as a dynamic method for the effects of re-understanding the supply chain during the pandemic. In this study, they created and used the dynamic method in which they redrawn the dynamic model using the optimal control model. Their model is a combination of optimal control and a pandemic model (such as Corona); and in fact, their model was a combination of these two models, which are older and more time-consuming than machine learning methods. Research Methodology The research method is applicable in terms of its purpose, and mixed (qualitative-quantitative) in terms of implementation method. In the qualitative part, interviews with experts active in the food industry with complete information and sufficient experience in the supply chain of this industry have been used until theoretical saturation, which were 10 people of relevant experts in large companies in this field. In the quantitative part, the field method and questionnaire were used to collect data with statistical methods, and this number was also 114 people selected as a sample from the statistical population. Research findings Due to the data conditions and the application of the field of machine learning in the supply chain, the support vector machine algorithm; which is one of the very strong algorithms in the field of artificial intelligence, was used. The results showed that customer satisfaction has a negative effect in the research model. Supply chain coordination has a positive effect in the research model. Factors affecting costs have a positive effect, but its amount is moderate. Economic and market conditions have a positive effect in the model. Internet infrastructure has limited importance in the model. Environmental risks have a positive effect. Product quality has a negative effect in the model. Conclusion The present study aimed to identify and investigate the effectiveness of supply chain risk indicators of online commerce activities in the food industry through machine learning method using the single support vector algorithm. The results of this study are consistent with the results of Ahmadi et al., (2023), Samiei et al., (2023), SpieskeAlexander et al., (2023), Akkerman et al., (2023), Brusset et al., (2023), Burgess et al., (2023), Ozdemir et al., (2022), Khorram Ruz., (2022), Sheydaei (2022), Pellegrino et al., (2022), and Zeng et al., (2019). Ozdemir et al., (2022) examined the effects of the pandemic on the supply chain of store goods, and finally examined and evaluated their presented model using covariance. The results indicated that in the field of supply chain vibration control, innovation can be greatly affected, so they used statistical methods for their research method. Considering the research topic, it is suggested that researchers use other machine learning algorithms, such as random forest and decision tree, and estimate the necessary evaluations. In addition, in each of these models, the accuracy of the models can be compared, and the effectiveness of each indicator in other models can also be examined. These algorithms and evaluations can also be used in industries other than the food industry.

Abstract Abstract

The aim of the present study is to design a customer relationship management model based on artificial intelligence in digital marketing of services in the health tourism industry. The research method is applicable in terms of its purpose, and mixed (qualitative-quantitative) in terms of its implementation method. The statistical population of the qualitative part of the study includes 14 experts and scholars in the field of marketing and artificial intelligence selected by the snowball sampling method. The statistical population in the quantitative part includes experts and marketing managers related to health tourism in Tehran. Given that their exact number cannot be calculated, a maximum number of 384 people was considered based on the Morgan and Cergesi table. Data collection in the qualitative part was carried out through semi-structured interviews, and in the quantitative part through questionnaires. The coding method was used in the qualitative part data analysis, and SPSS and Lisrel software were used in the quantitative part. The results of the study showed that the causal conditions in the study include improving market competition, improving relationships, automated data analysis, and empowerment; and the background conditions include customer data management and intelligent services. Also, the intervening conditions include efficient planning, saving resources, and managing customer behavior. The strategies in the study include solving the integration problem, solving the information management problem, and solving planning problems; and the outcomes include increasing customer satisfaction, increasing financial strength, customer loyalty, and saving time. The results of the structural equations show that the dimensions are well loaded on the research variables and can provide a suitable description of the variables.

Introduction

The activity of customer relationship management includes collecting, managing, and intelligently using data with the support of technology solutions to develop long-term customer relationships. Data obtained from all customer touchpoints, if managed well, can support companies in creating personalized marketing responses, generating new ideas, tailoring products and services, and thus delivering high customer value and gaining competitive advantage (Agarwal et al., 2021). In the digital age, the increase in the volume, velocity, and variety of data, as well as its processing capacity, has led to new technological solutions, including the advancement of artificial intelligence techniques, which refers to the ability of a system to correctly interpret large amounts of data, learn from this data, and use this learning to achieve specific goals and tasks (Ahmed et al., 2020). Artificial intelligence seems to be the future of the industry, and the focus of this technology on putting consumers at the center of health and well-being and ensuring that patients’ daily patterns and healthcare professionals’ needs are observed to provide improved guidance, support, and feedback, and ultimately customer relationship management in the health tourism industry will be of great importance in the future (Al Sayed, 2024).

A review of the role of data in the health tourism sector shows that the data required for the impact of AI on service delivery, especially in health tourism, is still limited (Dalkıran, 2023). Artificial intelligence can provide opportunities for health tourism service providers (Cubric, 2020). New customer relationship management features, such as personality insight services, website formation, chatbot services, programmatic advertising, and facial, image, and face recognition technologies, require significant data to be collected in real time, which is almost impossible to implement without advances in AI. Along with the relevance of AI in the business world, universities also claim that AI is the next step towards a new and more powerful customer relationship management (Rabbi, 2024).

Therefore, this research seeks to answer the question: How does the design of an AI-based customer relationship management model in digital marketing of services in the health tourism industry look like?

Theoretical Framework

Digital Marketing

Digital marketing means using the Internet, mobile devices, social media, search engines and other channels to reach customers. Some marketing experts consider digital marketing to be a completely new endeavor that requires a new way of approaching customers and new ways of understanding how customers behave compared to traditional marketing (Barone, 2021(.

Customer Relationship Management

Customer relationship management involves the intelligent collection, management and use of data supported by technology solutions to develop long-term customer relationships and exceptional customer experiences (Ledro et al., 2022).

Artificial Intelligence on Customer Relationship Management

Artificial intelligence is impacting customer relationship management. Artificial intelligence has revolutionized customer relationship management by automating tasks, providing deeper insights, and creating more personalized experiences for customers. Artificial intelligence enhances the automation process in customer relationship management, freeing up human resources to focus on more complex issues in the work (Ahmed, 2025).

Ponomarenko et al. (2024) in their research on the topic “Application of Artificial Intelligence in Digital Marketing” reported that it is important to identify the main directions of using artificial intelligence to optimize marketing strategies of companies in the digital environment in conditions of intensifying competition on the Internet. Artificial intelligence is considered as a tool for qualitative transformations in the use of digital marketing tools based on various information generated in the global network. The methodological basis of this study is a comprehensive analysis of scientific approaches to the implementation of artificial intelligence in the field of digital marketing, the formation of a database for modeling and identifying optimal machine learning algorithms to ensure the competitiveness of brands. A scheme of the main sources of information that should be used by the company to implement artificial intelligence algorithms in the process of increasing the effectiveness of the use of digital marketing tools is developed on the Internet. Digital marketing tools are presented to be utilized to communicate with the target audience in the long term and ensure the economically feasible level of conversion. The main stages of interaction of companies with audiences on the Internet using modern machine learning algorithms are presented. The main directions of using artificial intelligence in digital marketing have been identified, which enables the company to achieve a high level of loyalty among users based on personalized interaction models.

Baran et al. (2023) in their research on “Next Generation Technologies in Health Tourism” reported that the developments in the field of digitalization in health tourism were initially focused on e-health technologies and suggested that managers and employees should be prepared for the profound transformation created by technology.

Research Methodology

The research method is applicable in terms of its purpose, and mixed (qualitative-quantitative) in terms of its implementation method. The statistical population of the research in the qualitative section includes 14 experts and specialists in the field of marketing and artificial intelligence, selected by the snowball sampling method. The statistical population in the quantitative section includes experts and marketing managers related to health tourism in Tehran, and given that their exact number cannot be calculated, the maximum number was considered to be 384 people according to the Morgan and Gergesi table. Data collection in the qualitative part was done through semi-structured interviews, and in the quantitative part through questionnaires.

Research findings

Coding method was used in the qualitative part data analysis, and SPSS and Lisrel software were used in the quantitative part. The research results showed that the causal conditions in the research include improving market competition, improving relationships, automatic data analysis, and empowerment; and the background conditions include customer data management and intelligent services. Also, the intervening conditions include efficient planning, saving resources, and managing customer behavior. The strategies in the research include solving the integration problem, solving the information management problem, and solving planning problems; and the outcomes include increasing customer satisfaction, increasing financial strength, customer loyalty, and saving time. The results of structural equations show that the dimensions are well loaded on the research variables and can provide a suitable description of the variables.

Conclusion

The present study aimed to design an AI-based customer relationship management model in digital marketing of services in the health tourism industry. The results of this part of the study are consistent with the findings of Abdollahi (2021), Ghasemi (2019), Ribeiro et al. (2021), Ramon Saura et al. (2021), Al Sayed (2024), and Ponomarenko et al. (2024). AI in customer relationship management involves the integration of intelligent technologies to analyze customer data, predict behaviors, and automate interactions. This integration enhances the capabilities of traditional customer relationship management systems, making them more efficient and responsive to customer needs. AI-based customer relationship management systems provide the tools needed to achieve these goals and provide insights and automation that were previously unavailable.

According to the research results, the following suggestion was made:

Based on the role of artificial intelligence in customer data management and automated data analysis, it can be suggested to develop artificial intelligence in tourism service marketing because with artificial intelligence, businesses can use historical data to predict customer behavior and anticipate customer needs.

Abstract Abstract The aim of this study is to present a tourism industry development model in Iran. The research method is fundamental in terms of its purpose, and mixed in terms of its implementation (qualitative-quantitative), with an approach based on grounded theory. The statistical population in the qualitative section includes 23 experts in the field of theoretical and practical foundations of the tourism industry; including university faculty members and tourism managers selected in a snowball method; and in the quantitative section includes 374 experts in the field of tourism. The tool for collecting findings is a semi-structured interview in the qualitative section, and a researcher-made questionnaire in the quantitative section. Data analysis in the qualitative section carried out based on the grounded method by MAXQDA software, and in the quantitative section by SPSS software. The results of the study showed that, according to the determined goal; tourism infrastructure, international relations, social factors, and governance attitudes are among the effective factors that must be managed. Factors such as presence in the global tourism scene, facilities and infrastructure, tourist attraction policies, and existing potentials are considered as the basis and context for the development of the tourism industry in Iran and need to be improved. Introduction Tourism is an expanding industry and its importance is constantly increasing, and more and more people are getting involved with it. The United Nations World Tourism Organization states in its report that the tourism industry is the world's largest service industry in the 21st century and will maintain this position in the future (Amini et al., 2018). Tourism is a set of activities of people who travel to places outside their usual community environment for leisure, entertainment, business, or any other purpose and stay there for a while. The importance of tourism is that this field is considered a dynamic, competitive, and income-generating industry. A significant part of the budget of developed and developing countries is provided by the tourism industry. Many tourist countries adopt written strategic plans to improve their performance in this industry (Yahya Zadeh et al., 2023). Tourism is vital to the success of many economies around the world. The experience of the last two decades has shown that some countries, despite the lack of natural resources, have been able to achieve very high incomes by investing in the tourism industry (Qiu et al., 2020). Since Iran is a country with pristine nature and great potential in the health, trade, and historical-cultural sectors of the Middle East, the present study tries to minimize the gap in expectations between tourists and legislative institutions, and in this regard, using a data-based approach based on the opinions of relevant experts, an attempt was made to present a paradigmatic model for the development of the tourism industry. In the second stage of the study, using the opinions of experts, the executive factors in the development of the tourism industry were examined, and the results are presented in the following description of the findings so that it can be effective in the socio-economic development of the country in accordance with the national development plan and related perspectives. Accordingly, the present study seeks to answer this question: What is the development pattern of the tourism industry in Iran? Theoretical Framework Tourism Industry The tourism industry is one of the important socio-economic phenomena with cultural, political and environmental impacts. In recent decades, tourism has been growing and diversifying and has been one of the largest economic sectors in the world (Veicy, 2018). The tourism industry is an important source of income and an effective factor in cultural exchanges between nations and societie; and as the world's largest service industry, it has a special economic position (Hoseini & Mosavi, 2024(. Fani (2025) examined the influential and effective factors of marketing to tourism industry customers in Iran using the fuzzy DEMATEL technique approach. The findings showed that 3 dimensions, 8 components, and 41 indicators were identified. The extracted dimensions consist of the service quality dimension, including the components of satisfaction with tourism services, infrastructure facilities, tourism costs; the marketing policy dimension including the components of macro-policy, planning and management; and the tourism experience dimension including the components of tourists' feedback, tourism culture, and advertising and marketing. Momeni et al. (2025) examined the design of a smart tourism model with a meta-synthesis approach. The present study evaluated 128 articles and sources in the field of smart tourism using the meta-synthesis method. During the stages, 34 sources and articles were consistent with the accepted criteria. As a result of combining the findings, 8 subcategories were extracted, including improving cost management in tourism, providing smart tourism services, smart cloud services, an online service system for tourists, quality of services and facilities, the Internet of Things, identifying customer needs in a smart way, and dynamic pricing. Finally, for the development of smart tourism in Iran, it is recommended to adopt a comprehensive perspective considering both the micro and macro levels. At the macro level, more attention should be paid to raising the priority of smart tourism development in the long term, national development policies, paying more attention to planning, coordination, and monitoring, and improving the infrastructure required for the development of smart tourism. Research Methodology The research method is fundamental in terms of its purpose, and mixed (qualitative-quantitative) in terms of its implementation method, with an approach based on grounded theory. The statistical population in the qualitative section includes 23 experts in the field of theoretical and practical foundations of the tourism industry; including university faculty members and tourism managers selected in a snowball method; and in the quantitative section includes 374 experts in the field of tourism. The tool for collecting findings is a semi-structured interview in the qualitative section, and a researcher-made questionnaire in the quantitative section. Research findings Data analysis in the qualitative section is based on the grounded theory method and MAXQDA software was used, and in the quantitative section, SPSS software was used. The research results showed that, according to the determined goal; tourism infrastructure, international relations, social factors, and governance attitudes are among the effective factors that must be managed. Factors such as presence in the global tourism scene, facilities and infrastructure, tourist attraction policies, and existing potentials are considered as the basis and context for the development of the tourism industry in Iran and need to be improved. Conclusion The present study was conducted with the aim of providing a model for the development of the tourism industry in Iran. The results of this study are consistent with the results of Fani (2025), Momeni et al. (2025). Mansoori et al. (2024), Ghodrati et al. (2024), Rajabi et al. (2024), ,Kwabi et al. (2023), Yahya Zadeh et al. (2023), Al Fahmawee & Jawabreh (2023), and Asadpour Kordi et al. (2022). Mansoori et al. (2024) showed that the nine main factors affecting the formation of higher education tourism in Iran, in order of influence, are: dynamic political exchanges with the world at the national level, the existence of national macro-policies in the field of academic interaction, facilitating the admission process in political and administrative dimensions, the existence of economic and technical infrastructure for foreign students, the international language level of faculty members and staff and a dynamic and receptive higher education structure, the existence of a sense of security in social, security and political dimensions for foreign students, and the factors of being a brand of universities and introducing and presenting historical, cultural and religious attractions to the world. According to the results obtained, it is suggested that the development of the tourism sector in both categories through changes in infrastructure and extensive advertising at the national and international levels should be a priority for the authorities, and the authorities should pay special attention to the foreign tourism sector to generate foreign exchange, growth, and development of the tourism sector. It is suggested to the government, ministries and relevant institutions, considering the experiences of neighboring and similar Islamic countries such as Turkey and Malaysia, to try to see the tourism sector as one of the most important sources of income in order to move away from budgeting based on oil and taxes and pressure on domestic factors.

Abstract The present study aims to identify and explain the dimensions and components of crisis communication in the context of social media (case study: the Tax Administration Organization). In terms of purpose, the research is applied–developmental, and methodologically it is a mixed-method (qualitative–quantitative) exploratory study.The statistical population in the qualitative phase consisted of 25 university professors and experts from the Tax Administration Organization who were selected through purposive sampling. The statistical population in the quantitative phase included 131 managers and specialists of the Tax Administration Organization. The sample size was determined using Cochran’s formula and selected through simple random sampling.Data were collected using semi-structured interviews and a questionnaire. In the qualitative phase, thematic analysis was employed to identify the dimensions and components. In the quantitative phase, confirmatory factor analysis using SmartPLS software was applied to test and validate the findings obtained from the qualitative stage.Based on the findings, all identified variables were confirmed. The results indicate that the development of crisis communication through the capacities of social media is a complex and multidimensional phenomenon which, if implemented in a scientific and systematic manner, can provide numerous benefits and advantages for governmental organizations.

Abstract Abstract
The purpose of this research is sociological analysis of the scenarios of the business environment of Isfahan province with the future research approach of 2029 horizon. This research is applicable in terms of purpose, and mixed (qualitative-quantitative) in terms of method. The statistical population of the research includes 17 experts consisting of Isfahan province specialists selected by purposeful sampling. The tools of data collection are interviews and questionnaires. Data analysis was done using Delphi method as well as Scenario Wizard-MICMAC software. Using the mik-mak method, 8 key factors affecting the business environment of Isfahan province up to the horizon of 2029 were extracted, including good governance, stability of laws, international political and non-political interactions, expected inflation, priority of politics over economy, tax system, banking system, expansion and development of virtual space; based on which, 5 scenarios (from the most optimistic to the most pessimistic) have been compiled. The results show that sociological components, along with economic elements, play a decisive role in the future of the business environment in Isfahan province and the decision-making of national and provincial officials. Based on this, it is recommended to rely on good governance, stability of laws, international political and non-political interactions, etc. to provide the necessary platform for improving the business environment of the province. Also, there should be mutual trust in the relations between them. In the field of improving the business environment, it is possible to benefit from educational programs or to use environmentally stimulating advertisements, and the management in different sectors should be based on people's demands.
Introduction
The business environment is one of the indicators that determine the economic status of each country, which can be used to analyze the economic conditions of each country. The more transparent and competitive the business environment in the countries, the more increase in the economic health of the countries and the adoption of favorable policies, which will lead to the improvement of economic indicators. In this regard, examining the status of business indicators, both micro and macro, and explaining the existing challenges can be fruitful in creating and developing the business environment in the country (Nozari, 2017). What is certain is that reforming the business climate and improving the aforementioned indicators in the global arena is not only a positive and fundamental step in the direction of strengthening the private sector's participation in the economy and improving the level of employment and production, but also, definitely, from the perspective of foreign investors are among the most important indicators for entering the host country and a necessary condition for promoting and facilitating the flow of technology entering the country (Masovic, 2018).
Businesses have both economic and social goals. The business environment, development of plans and scenarios related to it, innovation in the production and sale of products or services cause a lot of diversity and transformation in the society and economy of any country, so sociological investigation of the subject is important. And Weber was the first sociologist who answered the question of why successful and innovative businesses flourished in the areas where Protestant ethics and Calvinist spirit prevailed in the book "Protestant Ethics and Spirit of Capitalism" (Nozari, 2017). According to Weber, the success of people in new businesses is the product of specific cultural and social conditions. According to him, social characteristics are the determining factor of entrepreneurial spirit. In other words, the issues and problems of economic development are non-economic.
What can be imagined for the future is that the society will change from a managerial state to an entrepreneurial state. In other words, in future societies, people will make an unprecedented effort to control many educational, economic, cultural and etc. variables (Nazari Sheikh, 2022). Therefore, in this research, the researcher intends to answer the basic question: what is the sociological analysis of the scenarios of the business environment of Isfahan province with the future research approach of 2029 horizon?
Theoretical Framework
Business space
Business environment is a set of policies, legal conditions, institutions, and regulations that govern business activities. Macroeconomic stability, the quality of the country's infrastructure, the quality of executive bodies, the system of making laws and regulations, the cost and the possibility of accessing information and statistics, work culture, and other such factors are among the factors that affect the performance of economic units, while managers of economic units cannot have much influence on them. Inappropriate business environment increases the cost of economic enterprises and causes the loss of investment motivation and also the country's producers lag behind global competitors (Bakhtiari & Shayesteh, 2012).
 Futurology
Futurology is a systematic and collaborative process that provides information about the future and creates medium-term to long-term perspectives, in a way that aims to make decisions and mobilize joint actions. In other words, in future studies, a picture of the future is depicted so that planners can design the way to reach it (Fazli & Gholizadeh, 2020).
Shafaei et al, (2024) investigated the effect of knowledge management on organizational performance considering the mediating variable of business process management. The findings of the research showed that all three hypotheses were confirmed based on the significant values ​​related to the hypotheses. The effect of knowledge management on business process management was 0.742, the effect of knowledge management on organizational performance was 0.422, and the effect of business process management on organizational performance was 0.652. Therefore, the most important proposal of the research is to pay attention to the preservation, sharing and application of knowledge, which is effective both in managing business processes and in increasing the level of organizational performance.
Nazari Sheikh et al, (2022) in his research entitled "Sociological analysis of the effect of cultural components of business on the production-commercial performance of industrial units (Ardebil province)"; which was conducted with the participation of 184 entrepreneurs active in the industrial sector, came to the conclusion that cultural-social components have a positive effect on the production-commercial performance of industrial units. Also, the findings of the research indicated that the components of low power distance, individualism, low uncertainty avoidance, long-term orientation, and masculinity have a positive effect on the production-commercial performance of industrial units.
Research methodology
This research is applicable in terms of purpose, and mixed (qualitative-quantitative) in terms of method. The statistical population of the research includes 17 experts consisting of Isfahan province specialists selected by purposeful sampling. The tools of data collection are interviews and questionnaires.
Research findings
Data analysis was done using Delphi method as well as Scenario Wizard-MICMAC software. Using the mik-mak method, 8 key factors affecting the business environment of Isfahan province up to the horizon of 2029 were extracted, including good governance, stability of laws, international political and non-political interactions, expected inflation, priority of politics over economy, tax system, banking system, expansion and development of virtual space; based on which, 5 scenarios (from the most optimistic to the most pessimistic) have been compiled. The results show that sociological components, along with economic elements, play a decisive role in the future of the business environment in Isfahan province and the decision-making of national and provincial officials. Based on this, it is recommended to rely on good governance, stability of laws, international political and non-political interactions, etc. to provide the necessary platform for improving the business environment of the province. Also, there should be mutual trust in the relations between them. In the field of improving the business environment, it is possible to benefit from educational programs or to use environmentally stimulating advertisements, and the management in different sectors should be based on people's demands.
Conclusion
The current research was carried out with the aim of sociological analysis of the scenarios of the business environment of Isfahan province with the future research approach of 2029 horizon. The results of this research are in agreement with the results of Shafaei et al, (2024), Sahraei & Mafibalani (2023), Nazari Sheikh et al, (2022), Dvorský & Petráková (2021), Soni et al, (2021), Farzin et al, (2020), Safar & Bahram (2019), Shams et al, (2019), Nozari (2017), Zabetpour & Aghajani (2016), Ritter & Pedersen (2019), and Masovic (2018). Shams et al, (2019) showed that elements including the growth of the urban middle class, the large and attractive market of the service sector, the government's support for start-up businesses, the change in lifestyle in Iran and the world, the organizational culture of start-up businesses, and transformation of social problems were identified as social factors (environmental culture or ecology) affecting future businesses.
According to the results of the research, the following suggestions were presented:
 According to the results of the study, 8 factors have been identified as key factors affecting the business environment of the province, based which, 4 scenarios explain the business environment of the province until the horizon of 2029 in a storytelling method.
It is obvious that in the wide range of challenges faced by the rulers and the multitude of possible solutions to improve the business environment, identifying the main factors of changing the business environment will prevent wasting time and national funds.

Abstract Abstract The aim of the present study is to design a model for attracting sports investors with a socio-economic security approach. The research method is applicable in accordance with its purpose and of descriptive-correlational type. The statistical population of the present study is faculty members sports management and economics who are experts in the field of socio-economic security, and experts and specialists in the field of sports economics; the sampling was carried out purposefully, and was 16 times the number of questions of the variable with the highest number of questions (9 questions in the contextual factors variable) estimated at 144 people. 160 questionnaires were distributed in order to ensure the receiving of the appropriate number of responses; and out of the 154 received questionnaires, 150 fully answered questionnaires were entered into the analysis process. The data collection method is a questionnaire. SPSS and PLS software were used in data analysis. The results of the factor analysis of the structures of each of the six main variables (causal factors, background factors, intervening factors, pivotal phenomenon, strategies, and consequences) showed that all components have a significant explanatory role. Path analysis also showed that the relationships between the six main variables in the sequence of five levels (causal conditions, background factors, intervening factors, pivotal phenomenon, strategies, and consequences) from independent variables to dependent variables are positive and significant, and the conceptual model has a good fit. Based on the research findings, it can be said that if investors are assured of the security of their investment, they will be more eager to invest in the field of sports; and in order to make investments, they should pay attention to strategies such as providing the necessary legal support for investment, and e-commerce investment security allowed for investors. Introduction The sports industry has become one of the largest global industries due to its positive social, cultural and economic impacts; and for most countries this industry is an important source of economic activities, income generation, job creation and international trade (Rezaei, 2021). This industry is a global phenomenon and one of the largest and most important industries in the world, accounting for 2.5% of international trade (Emami et al, 2022). Today, sports is an extremely attractive industry. A billion-dollar industry with high growth over a decade, which is growing rapidly as one of the world's leading industries (Bayarslan, 2023). In this regard, the sports industry has become doubly important for all governments because various goals are pursued through sports in the direction of economic, political, social and health improvement; and if there is proper management and structure, these goals can be achieved. In other words, today, the widespread use of the sports industry is considered as a tool for development in economic, social, political and other dimensions. Therefore, the need to explain the factors affecting economic growth and development can be effective in achieving the strategic goals and policies of countries (Sajadi et al, 2017). There are different paths to achieving economic growth, one of which is the field of sports and subsequently attracting sports investors and ultimately the country's economic growth with the inflow of capital (Wikner & Backstrand, 2018). In this regard, various factors are effective in attracting sports investors; and identifying their role and position helps the country's sports policymaking system to use appropriate policy solutions to attract capital and compensate for the lack of domestic resources necessary for the growth and development of national sports (Gholamian et al, 2023). However, what encourages domestic investors to stay and invest more and attracts foreign investors is investment security, which has become one of the main concerns in the international economic system. Investment security is defined as the availability of a set of legal, administrative, social, political and economic factors that create reassuring conditions for starting, operating and continuing investment activities and prevent the occurrence of factors that disrupt peace of mind during the above stages (Ghasemian, 2001). Therefore, considering the importance of investing in sports and its numerous benefits in terms of the health of individuals in society, participation in competitions and medal winning, contributing to economic growth, etc.; as well as the lack of domestic studies in the field of examining the impact of various aspects of security on attracting sports investors and in general the security of investment in sports in the country, it seems necessary to present an applicable model based on scientific findings in order to improve the current state of investment in national sports and help in the process of attracting sports investors. Therefore, the basic question in this study is: What is the applicable model for attracting sports investors with an economic-social security approach? Theoretical Framework of Investment in Sports Investment in the sports industry also brings benefits to society in terms of social, cultural and political aspects. Perhaps what prevents investors from investing in this profitable industry is that the benefits of investing in sports remain unknown; it is hoped that the authorities will make more efforts to introduce the benefits of investing in the sports industry through various programs so that they can direct stray capital towards this industry (Wang, 2021). Investment Security Investment security is essentially a public good created by the government and its dimensions go far beyond reducing risk or uncertainty. Its realization requires an institutional framework of economic, social, political, legal and administrative conditions that attract the trust of savers and investors, and ensure the safety of individuals and the legal security of transactions (Kwilinski et al, 2020). Ocholi (2023) examined foreign direct investment and national security: An analysis of economic relations between Nigeria and China. It showed that China and Nigeria benefit from foreign direct investment and its effects on economic security. Dougblay et al, (2023) examined the factors limiting investment activity in the sports industry, for example international football competitions in Russia. They stated that for systematic and rational investment activities in sports, it is necessary to resort to a larger scale implementation of mechanisms regulated for a specific sport because when training centers are established on the basis of professional sports clubs, they can not only play a role in national sports education, but also improve the state of sports management in the country and promote sports coaches and referees. Research Methodology The research method is applicable in accordance with its purpose and of descriptive-correlational type. The statistical population of the present study is faculty members sports management and economics who are experts in the field of socio-economic security, and experts and specialists in the field of sports economics; the sampling was carried out purposefully, and was 16 times the number of questions of the variable with the highest number of questions (9 questions in the contextual factors variable) estimated at 144 people. 160 questionnaires were distributed in order to ensure the receiving of the appropriate number of responses; and out of the 154 received questionnaires, 150 fully answered questionnaires were entered into the analysis process. The data collection method is a questionnaire. Research findings SPSS and PLS software were used in data analysis. The results of the factor analysis of the structures of each of the six main variables (causal factors, background factors, intervening factors, pivotal phenomenon, strategies, and consequences) showed that all components have a significant explanatory role. Path analysis also showed that the relationships between the six main variables in the sequence of five levels (causal conditions, background factors, intervening factors, pivotal phenomenon, strategies, and consequences) from independent variables to dependent variables are positive and significant, and the conceptual model has a good fit. Based on the research findings, it can be said that if investors are assured of the security of their investment, they will be more eager to invest in the field of sports; and in order to make investments, they should pay attention to strategies such as providing the necessary legal support for investment, and e-commerce investment security allowed for investors. Conclusion The present study was conducted with the aim of designing a sports investor attraction strategy with a socio-economic security approach. The results of this study were consistent with the results of Ocholi (2023), Dougblay et al, (2023), Mohammed (2023), Gholamian et al, (2023), Aliyari & Savadi (2022), Emami et al, (2022), Del Pisheh & Saki (2021), Jaferi & Hemmati Nezhad (2021), Zakharova (2020), Siemińska (2020), and Letiagina et al, (2019). Del Pisheh & Saki (2021) showed that the priority of policymaking should be based on attracting private sector investment in the development of sports spaces and venues, such as the impact of regulations and legal and financial laws, social management issues, and the impact of the media on attracting capital. According to the results of this research, the following suggestions are made: The way should be open for the private sector and sports investors so that they can attract maximum participation of the community in sports, use the necessary capacities, and easily operate for marketing and sales, as well as club ownership and export and import of goods and athletes. Financial corruption in the field of sports should be prevented and a safe and low-risk investment should be made for investors, and e-commerce should be allowed and the legal support for investment guarantees should be improved, and the information and communication system of the country's economy and sports industry should be issued for them so that they can invest with greater interest.

Abstract Abstract The aim of this research is to model the factors affecting the profit response coefficient of companies by combining behavioral finance components using the structural equation method. This research is applicable in terms of its purpose, descriptive-correlational in terms of collecting data, and with a survey method. Using data from 153 companies listed on the Tehran Stock Exchange during the period 2013 to 2022 and through the structural equation modeling method, the factors affecting the profit response coefficient were identified and ranked. The results of the research showed that the financial condition and performance factor with a path coefficient of -0.19, the capital market condition and performance factor with a path coefficient of 0.167, and the investment environment factor with a path coefficient of 0.12 have a significant effect on the profit response coefficient at the 0.05 error level. Accordingly, the structures of earnings per share, financial leverage, information asymmetry, market index return, inflation rate, free float shares, stock turnover rate and stock trading frequency were identified as structures affecting the profit response coefficient. Among the aforementioned structures, the absolute value of the coefficients of the structures showed that the inflation rate has the highest, and earnings per share has the lowest impact on the profit response coefficient. Introduction In investment activity, investors need information to make decisions. The required information can be seen in the company's published financial reports. Financial reports are an excellent tool for obtaining information about the company's financial status and performance. One of the financial statement information used in decision-making is the company's profit. Profit is a comprehensive element for evaluating the overall performance of the business unit (Azizi et al, 2016). Agency theory (Jensen & Meckling, 1976) states a relationship between the owner (the principal) and the delegation of authority and decision-making to management (the agent) to optimize profits. There are opportunities for disagreement between the two sides of this relationship, which leads to information asymmetry. Information asymmetry occurs when a management (agent) has more information about the company's situation and prospects than the owner (principal) (Baroroh et al, 2022). Therefore, information asymmetry occurs when two parties to a contract or transaction have access to different information. Signaling theory is generally useful for explaining the behavior of individuals when two parties have different access to information. According to signaling theory, information asymmetry can be reduced when one party (the sender) chooses what information to send and how to send it (signal), and the other party (the receiver) must choose how to interpret the signal (information) (Nurfadilah et al, 2023). One tool that can be used to measure investor reaction to accounting earnings information is the earnings response coefficient. The earnings response coefficient is an estimate of the changes in a company's stock price as a result of the company's earnings announcement to the market. The earnings response coefficient is another measure of abnormal returns observed in response to unexpected elements of earnings reported by the company. In other words, the earnings response coefficient measures the sensitivity of stock markets to earnings reports through the regression slope coefficient between abnormal returns and unexpected earnings (ViDiat Moko & Indarti, 2018). The importance of research on the earnings response coefficient primarily stems from the need to increase the trust of company shareholders in the disclosure of accounting information, which allows them to make informed decisions about investing in stocks. Therefore, the main goal of this research is to model the factors affecting the earnings response coefficient of companies by combining behavioral finance components in the Iranian stock market. Considering the above, the researcher tries to address the main question of how to model the factors affecting the earnings response coefficient of companies by combining behavioral finance components using the structural equation model. Theoretical Framework Corporate Earnings Response Coefficient One of the tools that evaluate the quality of earnings is the earnings response coefficient. The earnings response coefficient is significantly related to earnings or the responsiveness of the information interpreted or contained in earnings. The earnings response coefficient is another measure of abnormal returns observed in response to unexpected elements of earnings announced by a company that publishes its earnings report. In other words, the earnings response coefficient measures the sensitivity of stock markets to earnings reports through a regression slope coefficient between abnormal returns and unexpected earnings (Nurfadilah et al, 2023). Behavioral Finance Components Investor behavior to buy stocks is influenced by the availability of information that can be used in stock valuation. However, there is still doubt whether the availability of this information, namely earnings information, has been well received by investors. Earnings quality can be shown as the ability of earnings information to respond to the market. In other words, reported earnings have the power to respond. Strong market reaction to earnings information is reflected in a high earnings response coefficient, which indicates that the earnings are reported with quality (Paramita, 2020). Adib Fard & Khan Mohammadi (2024) investigated the effect of management ability on earnings response coefficient considering the role of information asymmetry. The research hypotheses were tested based on a statistical sample of 164 companies over a 10-year period from 2012 to 2021 using multivariate regression models with mixed data. The results indicate a positive effect of management ability on earnings response coefficient; However, the results showed that increasing the difference between the bid and ask price as a measure of information asymmetry leads to the adjustment of this relationship, in a way that weakens the effect of management ability on the real profit response coefficient. Ramineh (2024) examined the effect of conditional conservatism and comparability of financial statements on the profit response coefficient. The statistical population of the study is companies listed on the Tehran Stock Exchange and the sample under study includes 152 companies listed during the years 2018 to 2022. The results obtained from data analysis show that the comparability of financial statements has a positive and significant effect on the profit response coefficient, and conditional conservatism has a positive and significant effect on the profit response coefficient. Research Methodology This research is applicable in terms of purpose, descriptive-correlational in terms of data collection, and with survey method. Using data from 153 companies listed on the Tehran Stock Exchange during the period 2013 to 2022, and through the structural equation modeling method, the factors affecting the earnings response coefficient were identified and ranked. Research findings SPSS software and structural equations were used to analyze the data. The results of the research showed that the financial condition and performance factor with a path coefficient of -0.19, the capital market condition and performance factor with a path coefficient of 0.167, and the investment environment factor with a path coefficient of 0.12 have a significant effect on the earnings response coefficient at the 0.05 error level. Accordingly, the structures of earnings per share, financial leverage, information asymmetry, market index return, inflation rate, free float shares, stock turnover rate, and stock trading frequency were identified as structures affecting the earnings response coefficient. Among the aforementioned structures, the absolute value of the coefficients of the structures showed that the inflation rate has the highest and earnings per share has the lowest effect on the earnings response coefficient. Conclusion The present study aimed to model the factors affecting the profit response coefficient of companies by combining behavioral finance components using the structural equation model. The results of this study are consistent with the results of Adib Fard & Khan Mohammadi (2024), Ramineh (2024), Ahmadi Olyaee (2023), Zareian Kalkhouran & Zareian Kalkhouran (2023), Hajannejad et al, (2022), Kordestani & Abdoli (2022), Bahaghighat & Rezaei (2018), Sandy & Mulya (2024), Kim et al, (2023), Elviani et al, (2022), Niswah et al, (2022), Sun et al, (2021), Awawdeh et al, (2020), and Wijaya et al, (2022). Sandy & Mulya (2024) showed that high earnings quality attracts high investor sentiment in stock trading; good news is quickly processed in the price and the price increases in a short period, while bad news can also lead to price corrections and investor sentiment. Also, a positive relationship was observed between return on equity and earnings reaction coefficient, which strengthens investor sentiment in this relationship. According to the research results, the following suggestions are made: It is suggested that actual and potential investors pay attention to earnings per share and financial leverage as indicators of company performance results at the time of earnings announcement, in order to predict the market reaction to unexpected earnings, as well as the percentage of free float shares and the stock turnover rate and the frequency of stock trading as indicators of the atmosphere prevailing in stock trading in the market, as factors affecting the earnings reaction coefficient.

Abstract Abstract The aim of this study is to present a model of the influence of psychological ownership and risk with the mediating role of organizational justice, organizational commitment and job satisfaction. This research is applicable in terms of its purpose, descriptive-analytical in terms of data collection, and is a survey-based, correlational research. The statistical population of the study includes 400 accountants, managers and auditors selected through a random sampling method. A researcher-made questionnaire was used to collect research data. SPSS software was used to analyze the data; LISREL software was used to model the structural equations of the research; and Stata software, bootstrap, and Sobel methods were used in the part of the mediator role test. The results showed that there is no significant relationship between psychological ownership and risk. There is no significant relationship between organizational commitment and risk. There is a positive and significant relationship between organizational justice and risk. There is no significant relationship between job satisfaction and risk. There is a positive and significant relationship between psychological ownership and risk with the mediating role of organizational justice; there is no significant relationship between psychological ownership and risk with the mediating role of organizational commitment. There is a positive and significant relationship between psychological ownership and risk with the mediating role of job satisfaction. Introduction Recent psychological theories show that having authority in the workplace can play an important role in relationships between individuals in the organization. With increasing authority, employees' expectations from the organization increase. Increased wages and legal benefits, increased access to information, decision-making, and increased responsibilities are among these expectations (Soltanzadeh et al, 2016). Some researchers claim that employees' financial ownership of part of the organization as a shareholder can affect important factors such as employee behavior and motivation, as well as the planning of the organization's owners. Among the topics entered the realm of organizational behavior, management and psychology is psychological ownership, which has become increasingly important after new theories and research in industrial and organizational psychology and management and has become one of the main topics of management (Farzinfar et al, 2022). Psychological ownership is a state in which an individual attributes his or her sense of ownership to any of various fields such as the organization, job, and work tasks, work tools and equipment, ideas, suggestions, and members of his or her group. In addition to being defined from a traditional and real, formal, and legal perspective; the concept of ownership also has a psychological or mental state. The concept of psychological ownership is initially motivated by the motivation of establishing a connection between employee attitudes and behaviors by modeling the concept of ownership and its effects, claiming that creating a sense of belonging creates constructive organizational, group, and individual effects (Preston & Gelman, 2020). On the other hand, injustice causes damage to human dignity, the outflow of social capital, and a decrease in national determination to act, and threatens the health of society. The perception of organizational justice is a fundamental requirement for the effective functioning of organizations, the personal satisfaction of employees, and plays a very important role in shaping their attitudes and behaviors (Barimani & Abbaszadeh, 2019). Organizational justice is an important determinant of the attitudes, decisions, and behaviors of individuals in the workplace. Organizational justice is a multidimensional social construct that explains how individuals perceive fairness in their workplace (Shahi et al, 2017). In this type of ownership, emotional components play a very prominent role, and perhaps the most important aspect of this ownership is its emotional sense. Considering the above, the researcher tries to address the main question: What is the model of the influence of psychological ownership and risk on the mediating role of organizational justice, organizational commitment, and job satisfaction? Theoretical Framework Psychological Ownership Psychological ownership is the emotional and cognitive attachment between an individual and property that affects the individual's behavior and self-perception. Therefore, psychological ownership has emotional, cognitive, and behavioral dimensions that manifest at the individual or group level. Thus, the semantic core of psychological ownership is the feeling of ownership about an object (Farzinfar et al, 2022). Risk Risk is considered an integral part of all business activities, and its effective management helps organizations in preventing financial problems and carrying out capital budgeting, and also improves the decision-making process (Mahmoudi & Pourshahabi, 2023). Organizational Justice Accordingly, organizational justice is defined as the perception of employees about the fairness of the workplace. In other words, the perception of fairness in the workplace by employees is called organizational justice, which has a direct impact on their attitude and performance (Parven & Awan, 2018). Organizational Commitment Organizational commitment is a condition in which employees show a strong interest in the values ​​and goals of the organization. In addition, organizational commitment means more than formal membership of employees because it includes liking the organization and the willingness to perform a high level of voluntary, collaborative, and supportive efforts for the benefit of the organization in order to achieve its goals (Nahak & Ellitan, 2022). Job Satisfaction Job satisfaction is the internal state of employees regarding the degree of favorable or unfavorable feelings about the effective or cognitive evaluation of the job experience. In other words, the extent to which employees like their job is called satisfaction, and the extent to which they hate their job is called dissatisfaction. Job satisfaction indicates the extent to which people are satisfied with and love their job. Some people enjoy their job and consider it the main focus of their lives, and some hate their job and do it only because they have to (Farhani, 2023). Darvishi & Ashrafi (2024) studied the effect of talent management on organizational commitment with the mediating role of organizational justice among employees of Farhangian University of West Azerbaijan Province. Analysis of the collected data showed that talent management is effective by 83% on organizational justice and by 42% on organizational commitment of employees. Organizational justice also affects organizational commitment by 48%. Also, talent management has a mediating role. Organizational justice has a mediating role on employee organizational commitment by 4.21 using the Sobel test. Therefore, according to the statistical results, all research hypotheses were confirmed and the overall conclusion of the research was that organizational justice has a mediating role between the relationship of talent management and employee organizational commitment. Brundin et al, (2023) studied leaving the family business: the dynamics of psychological ownership. They concluded that, contrary to the prevailing and common belief that psychological ownership is static, psych it will have different meanings for different people at different times and has a dynamic nature. Research Methodology This research is applicable in terms of its purpose, descriptive-analytical in terms of data collection, and is a survey-based, correlational research. The statistical population of the study includes 400 accountants, managers and auditors selected through a random sampling method. A researcher-made questionnaire was used to collect research data. Research findings SPSS software was used to analyze the data; LISREL software was used to model the structural equations of the research; and Stata software, bootstrap, and Sobel methods were used in the part of the mediator role test. The results showed that there is no significant relationship between psychological ownership and risk. There is no significant relationship between organizational commitment and risk. There is a positive and significant relationship between organizational justice and risk. There is no significant relationship between job satisfaction and risk. There is a positive and significant relationship between psychological ownership and risk with the mediating role of organizational justice; there is no significant relationship between psychological ownership and risk with the mediating role of organizational commitment. There is a positive and significant relationship between psychological ownership and risk with the mediating role of job satisfaction. Conclusion The present study was conducted with the aim of presenting a model of the influence of psychological ownership and risk with the mediating role of organizational justice, organizational commitment and job satisfaction. The results of this study are consistent with the results of Darvishi & Ashrafi (2024), Brundin et al, (2023), Aslani (2023), Enver et al, (2022), Alikarami et al, (2022), Jakada et al, (2021), Hasiri et al, (2020), Nooraee (2019), and Trop et al, (2018). Aslani (2023) showed that psychological ownership had a positive and significant effect on employee retention with the mediating role of commitment. The following suggestions are for future research: Psychological ownership of managers may cause the selection of methods from accepted accounting standards that create more appropriate profits and insufficient disclosure of financial information. As a result, it is suggested that the relationship between psychological ownership of managers and profit distortion be investigated. It is suggested to examine the effect of ownership concentration, number of shareholders and owners on psychological ownership, and financing methods (equity or debt based).

Abstract Abstract The aim of this study is to study the antecedents and consequences of brand revival with a meta-synthesis approach. For this purpose, the seven-step method of Sandievsky and Barroso was used to extract data from scientific and research articles over a 23-year period (1990-2023). After initial studies, 32 articles were selected for a more detailed study. Using the conceptual model and inference from the results, the MAXQDA 2020 software was used to analyze the data. The results showed that 44 indicators and 4 dimensions were extracted and presented in two general concept factors. Finally, considering the frequency and intensity of the indicators of each dimension, a comprehensive conceptual model of Iranian brand revival was designed. In examining the factors affecting the revival of lost brands, from the aspect of brand re-creation; indicators such as nostalgic feeling, authenticity, heritage, story, and the attractive past of the brand have had the greatest impact. In terms of brand modernization, indicators such as innovation, excellence, advertising appeal, and adaptability to consumer expectations have been assigned the most frequent. In terms of the consequences of reviving extinct brands, in terms of consumer minds and emotions; brand awareness and image indicators have been the most important, and in terms of consumer behavior; loyalty, market share, and brand value indicators have been the most important. Introduction Brands, like living organisms, have their own life cycle, which consists of various stages such as introduction, growth, maturity, and decline. If the brand cannot adapt to market conditions, it enters the decline stage and is eventually removed from the market. It is important to note that not all brands go through this complete cycle. Some brands may disappear quickly after the introduction stage, while others may remain in the maturity stage for years. Brand revitalization is a process that seeks to restore the lost value and credibility of a brand that is in decline (Jin, 2013). Brand revitalization is a concept that gives a new life to a brand. Brand revitalization injects energy into the brand life cycle because it is different from a total brand change of the company. More than 80% of brands commercialized fail, requiring strategic considerations for revival. (Akbar et al, 2017). Brand revitalization can be necessary for various reasons, such as changing consumer tastes, the entry of new competitors, or public scandals. Even well-known brands are at risk of decline over time (Gilal et al, 2021). In other words, brand revitalization is a strategic process to return a brand to the path of success after a decline or recession. Its ultimate goal is to prevent further decline in brand value and achieve its previous or even stronger position in the market. Brand revitalization can help to renew brand value or improve brand image. The survival of companies in a competitive market depends on their ability to adapt to changes. Brand revitalization can help companies to remain in this market (Toivola, 2016). Ultimate increasing sales and brand awareness and attracting new generations and new target markets (Beckers et al, 2017) are some of the key benefits of brand revitalization. However, brand revitalization can be challenging, especially for brands that are weak or damaged and may take years to revive. Despite these challenges, brand revitalization can be very beneficial. Given the increasing importance of brand revitalization in practice, it is surprising that scientific research in this area is limited (Brown et al, 2017). Researchers and practitioners have recognized the importance of reviving dead brands and are calling for innovative and practical concepts in this area (Gilal et al, 2021). Understanding the variables that lead to brand revival is important because these brands often have lasting value, such as a high level of brand awareness and a positive brand image among customers (Handique & Sarkar, 2020). Given the above, the question can be asked: What is the pattern of antecedents and consequences of brand revival with a meta-synthesis approach? Theoretical Framework Brand Revival Brand revival is a complex and arduous process of returning a declining brand to its previous position or promoting it to a higher level. It is like rising from the ashes like a phoenix and brings with it numerous challenges, as Stratton et al, (2023) point out that reversing the decline of a brand is difficult and there are few solutions for it, let alone a definitive solution. Brand revival is a complex process with numerous obstacles. Molazadeh Shirepezi et al, (2023) investigated the identification of dimensions and components of brand revival in the textile industry. The findings showed that in the qualitative section, after coding the data obtained from interviews and reviewing library resources, 166 concepts and 114 components were categorized into 16 dimensions, and in the quantitative section, the extracted model was tested in the qualitative section, which showed that the concepts and components obtained from coding are fully compatible with the dimensions. In this study, for the first time, the brand revival structure in the textile industry was designed and tested, which is completely different from previous studies designed to identify the prerequisites and dimensions of the brand. Finally, a fourteen-factor model was presented in the form of 114 components for brand revival in the textile industry, which can be an effective framework in the growth and development of textile industry brands. Stratton et al, (2023), examined the revival of declining brands using the leverage of the brand's obsolescence. They stated that in order to revive the brand and maintain its position in the market, it is essential to address the problem of brand obsolescence. In fact, brands must meet the needs and expectations of the new generation of consumers with their innovation and updating and be at the forefront of competition with emerging brands. Research Methodology For this purpose, the seven-step method of Sandievsky and Barroso was used to extract data from scientific and research articles over a 23-year period (1990-2023). By initial reviews, 32 articles were selected for a more detailed study. Research Findings Using the conceptual model and inference from the results, MAXQDA 2020 software was used to analyze the data. The results showed that 44 indicators and 4 dimensions were extracted and presented in two general concept factors. Finally, considering the frequency and intensity of the indicators of each dimension, a comprehensive conceptual model of the revival of Iranian brands was designed. In examining the factors affecting the revival of lost brands, from the aspect of brand re-creation, indicators such as nostalgic feeling, originality, heritage, story and attractive past of the brand have had the most impact. From the aspect of brand modernization, indicators such as innovation, excellence, advertising attractiveness and adaptability to consumer expectations have had the most frequency. In the context of the consequences of the revival of lost brands, from the aspect of consumers' minds and emotions, brand awareness and image indicators and from the aspect of consumer behavior, loyalty, market share and brand value indicators have had the most importance. Conclusion The present study was conducted with the aim of examining the pattern of antecedents and consequences of brand revival with a meta-synthesis approach. The results of this study are in line with the results of Molazadeh Shirepezi et al, (2023), Stratton et al, (2023), Almazyad et al, (2023), Zhu (2023), Xiang (2023), Asgarnejad Nouri et al, (2022), and Tripathi et al, (2020). Stratton et al, 2023) stated that in order to revive the brand and maintain its position in the market, it is necessary to address the problem of brand obsolescence. In fact, brands must innovate and update themselves to meet the needs and expectations of the new generation of consumers and be at the forefront of competition with emerging brands. Revival of extinct brands can be challenging, but it is possible with the right strategies. One important strategy is to focus on nostalgia, by evoking emotions through advertising and content marketing, using old brand elements, and telling compelling and authentic stories from the brand’s past. Also, adhering to brand authenticity by rediscovering core values ​​and offering products and services that align with these values ​​is very effective.

Abstract Abstract The aim of the current research is to identify the factors affecting the commercialization of the products of knowledge-based companies located in science and technology parks and growth centers. The research method is applicable according to its purpose, and qualitative in terms of its implementation. The statistical population of the research includes 12 experts and specialists in the field of knowledge-based centers in West Azarbaijan province, and the samples were selected using a purposeful sampling method. Data collection was done through semi-structured interviews. To analyze the data through data-based and coding, MAXQDA software was used. The results of the research showed that the model designed was identified by 14 indicators that includes causal conditions (management factors, information factors, financial factors), background conditions (laws and regulations, technological capabilities), core category (market factors, product factors), strategies (strengthening interactions, marketing and sales capabilities), consequences (economic development, knowledge-based economy, entrepreneurship development), intervening conditions (individual factors, cultural-social factors); explaining the components of commercialization of products of knowledge-based companies. Extended Abstract                                           Introduction Ideation, research, innovation and technology based on it are valuable when they lead to wealth creation. Based on this, the industrial and economic improvement of any society depends on scientific and organized researches and the application of the results of these researches practically in order to meet the various needs of the society and improve the standard of living and well-being. Recognizing the needs of the consumer market, creating ideas, conducting research and studying for the development of technology and finally its commercialization are the inevitable stages of the birth and creation of a new technology (Cooper, 2019). Commercialization is an important part of the innovation process without which no product will successfully enter the market. Creating platforms for the supply of knowledge and technology, in addition to providing significant economic values ​​for organizations, leads to the economic and technological growth of society. One of the main reasons for the speed of technological progress and development in industrialized countries has been the attention to the commercialization process of those countries (Safari, 2018). On the other hand, the lack of necessary ability to commercialize and implement research achievements in new products and processes and supply them to the market is one of the major weaknesses of developing countries in the process of industrialization. Studies show that out of about 1000 raw ideas, only 1 or 2 ideas succeed in the market. Ideas must be commercialized to become a successful and profitable business, and commercialization as a non-linear and complex process requires the role of different actors with different capabilities (Shamsi & Sadeghi, 2015). Knowledge-based companies are private or cooperative institutions engaged in activities in order to synergize science and wealth, develop a knowledge-based economy, realize scientific and economic goals, and commercialize the results of research and development in the field of superior technologies with great added value. In these companies, research and development is the core of activities, and the main advantage of these companies is the technical knowledge and scientific abilities of their personnel. In knowledge-based companies, economic growth and job creation are realized in proportion to the innovation capacity. This means that research and development achievements are continuously transformed into new products, processes or systems through investment; and access to investment capacities for entrepreneurs and researchers is an important factor in creating innovation and exploiting the power of technology in the national economy. Also, knowledge, innovation, skills and continuous learning play an important role in these companies (Karimi Yazdi et al, 2018). Therefore, in this research, we are looking for an answer to the question of how to identify the factors affecting the commercialization of the products of knowledge-based companies based in science and technology parks and growth centers. Theoretical Framework Commercialization Commercialization includes all the activities required to convert an idea, technical knowledge, work method, practice, process, product, service, organizational form, technology or a combination of any of these capitals into value-creating opportunities (Asadi et al. 2021). Commercialization is a process that uses all possible potentials so that those who invest in technological innovation can obtain the benefits created by the innovation; in other words, technology commercialization is a part of technological innovation, and if we consider innovation from addressing the idea to entering the market, without commercialization; innovation and therefore technology will not exist. Technology commercialization is the process of creating the right product at the right price to meet the demand of a market. In another definition of technology commercialization, technology and commercialization are separated from each other. In this definition, technology includes the product, and commercialization emphasizes creating a market, a brand name, and maximizing the profit from this market (Cooper, 2019). Aghababayi et al, (2023) conducted a research entitled "Identification of factors of commercialization of technological projects in new knowledge-based companies". The findings of the research show that it is important to pay attention to the 5 criteria of technology, skill, knowledge, market, and policy and law for the commercialization of technological projects in new knowledge-based companies. Van Doren et al, (2022) investigated the external commercialization of technology in emerging fields. From a study of 84 synthetic biology organizations, they found that disposal capacity mediates the relationship between management innovation and foreign technology commercialization. This study provides empirical evidence of the interdependence of various managerial and organizational processes required for foreign technology commercialization. Research methodology The research method is applicable according to its purpose, and qualitative in terms of its implementation. The statistical population of the research includes 12 experts and specialists in the field of knowledge-based centers in West Azarbaijan province, and the samples were selected using a purposeful sampling method. Data collection was done through semi-structured interviews. Research findings To analyze the data through data-based and coding, MAXQDA software was used. The results of the research showed that the model designed was identified by 14 indicators that includes causal conditions (management factors, information factors, financial factors), background conditions (laws and regulations, technological capabilities), core category (market factors, product factors), strategies (strengthening interactions, marketing and sales capabilities), consequences (economic development, knowledge-based economy, entrepreneurship development), intervening conditions (individual factors, cultural-social factors); explaining the components of commercialization of products of knowledge-based companies. Conclusion The present research was conducted with the aim of identifying the factors affecting the commercialization of the products of knowledge-based companies located in science and technology parks and growth centers. The results of this research are in agreement with the results of Aghababayi et al, (2023), Asadi et al, (2023), Van Doren et al, (2022), Stiri & Mehraayin (2022), Hoang (2022), Shan et al, (2021), Da Silva (2021), Assari & Niasti (2021), Deresihan et al, (2022), Azma et al, (2022), Alikhani et al, (2021), Tam et al, (2019), and Ho & Chuah (2019). Da Silva (2021) showed that there are other types of motivations for starting new investments for university students' entrepreneurship, such as financial, organizational, and technological factors. It also gathers information about the target market of the new investment, such as why startups choose certain markets, and also identified the main players competing with the startups. According to the results of the research, the following suggestions are presented: It is suggested that growth and technology centers hold management courses and workshops to familiarize managers with the concepts of managing business affairs in the field of finance, marketing, etc. It is suggested that in the field of information, research and development units should be active in companies, and research should be done continuously. It is suggested that the government allocate financial funds to knowledge-based companies so that they can solve their problems in the field of risks associated with a sharp decrease in demand and market information.

Abstract Abstract The purpose of this research is to design a model to evaluate the level of digitization of the innovation process centered on artificial intelligence in knowledge-based companies, so that the digital maturity of the innovation process in an organization can be measured. The results of 188 indicators were distributed in the form of a 5-point Likert questionnaire and by Delphi method in two times among 18 experts in this field. The result of the work was 5 components as input to the model, which was sent in the form of a questionnaire to 230 knowledge-based companies of Pardis Technology Park. 198 companies completed it and sent it back. From this number of samples, 150 data were separated for training data and 48 data as model test based on a random function. In the last stage, i.e. modeling, the adaptive neural-fuzzy inference method was used for the model. The method of grid separation or lookup table (PG) in MATLAB 2023 software was used to evaluate the performance of the model using root mean square, error (RMSE) and relative error (E). This research was able to provide an intelligent model with a very low error. As a result, it was able to achieve effective indicators in the degree of digitization of the innovation process. Extended Abstract                                           Introduction An innovation process, whether in its general form from the stage of idea formation to the stage of entering the market and commercialization, or in each of the parts separately, must be in such a way that it has the most productivity (efficiency and effectiveness combined during the process). Moving in this direction reduces financial, time and human costs. The relevance of innovation to ensure the competitiveness of companies has been confirmed among researchers and professionals (Schiuma, 2012). Also, innovation is a risky process that requires resources, competence, culture and attitudes that cannot even be promoted and managed easily (D'Este et al., 2012). Due to the mismatch in digital skills and awareness, employees are not able to understand the reasons and potential of implementing new technology and displacement. Therefore, the next challenge in the digital ecosystem is to promote and define conditions, roadmaps and management models for implementing digital innovation strategies, for managing digital knowledge and fostering continuous innovation (Nonaka & Takeuch, 2019). Innovation processes rely on external institutions, i.e. innovation intermediaries, research and development laboratories, or innovation centers (Corre & Mischke, 2005). Global and virtual competition, as well as the rapid development of digital technologies and solutions, raise efficiency standards, increase the speed of market dynamics, and reduce product life cycles (Schiuma, 2012). Each actor involved in innovation must be aware of the organization's vision, goals, and strategies in order to effectively contribute and generate value (Lianto et al., 2018; Nonaka & Takeuchi, 2019). To understand and effectively manage technology, codification and exploitation of generated knowledge, specialized skills and new governance models are required (Joshi et al., 2010). Theoretical framework Digital innovation process Completely rebuilding business around new opportunities and new demands is possible through digital technology. Eyring et al., (2022) in an article, mentioned these processes under the title of digitization. Digitization is a useful and effective necessity. It provides a vision of digital assets that offer opportunities to business or even to industry. Digitization sometimes reconceptualizes their products by serving a business model through their artifacts. Digital transformation describes a sometimes broad process of change that may have multiple goals, while innovation focuses on the moment of invention and the implementation of that invention. Innovation may cause fundamental changes and vice versa, but both are not synonymous. Advancement of digitization and digital changes may be started as an innovation action. This may be catalyzed by new business opportunities, but ultimately must reach beyond the innovation function to reshape the entire organization (Globe, 2018). Businesses need a dynamic tool to support their digital innovation management efforts. Artificial intelligence Artificial intelligence is sometimes called machine intelligence, refers to the intelligence shown by machines in various situations, which is in contrast to the natural intelligence in humans; in other words, artificial intelligence refers to systems that can react similar to human intelligent behavior, including understanding complex situations, simulating human thinking processes and reasoning methods and successfully responding to them, learning and having the ability to acquire knowledge and reason to solve problems (Teece et al., 1997). The scientific study of algorithms and statistical models are used by computer systems that use patterns and inference to perform tasks rather than using clear instructions. Machine learning is the science of making computers learn about a specific subject without the need for an explicit program. As a subset of artificial intelligence, machine learning algorithms create a mathematical model based on sample data or "training data" in order to predict or make decisions without overt planning (Du et al., 2019). Research methodology The sampling method was carried out in the form of theoretical saturation at the stage that no new material was obtained from the articles as a new index, and other indices were common in meaning and concept. In this study, Pardis Technology Park companies and its branches, including Azadi Factory and Hi-Wi centers were considered. Because these companies are active within the innovation ecosystem, they are familiar with the literature in this field, which facilitated the completion of the questionnaires. Questionnaires were sent through the Press Line program and within social network groups, and for some through phone and email. All these companies had the approval of knowledge-based company level 1 to 3 and the completers had educational qualifications of at least bachelor's degree to doctorate. After examining the opinions of the experts, it was determined that a consensus was reached by having an average above 4 for all indicators. In adaptive neural fuzzy inference, the network separation method or lookup table (PG) was used in MATLAB 2023 software. In this method, the number of membership functions is 5 functions representing very low, low, medium, high and very high. Research findings A number of 290 articles were selected among the whole, which had the citation higher than 1. The texts of these 290 articles were studied, and finally 149 articles related to the selected topic and the literature and background of this research were used. In fact, the general goal and main question of this research was to model the innovation process centered on artificial intelligence, was carried out successfully with a very low model error during the test. As a result of reviewing these 149 articles and specialized texts, 189 indicators related to the issue of digital innovation were extracted. As the next goal, 42 main and effective indicators were obtained from this literature Conclusion In addition to the main goal and special goals of the research that were achieved through the presentation of the model, by examining the relationships obtained according to the surface diagrams, the sensitivity and impact of each component can be determined. "Variables" in the output, i.e. the degree of digitalization of the innovation process were analyzed. According to the findings and comparing them with the background and findings of previous researches, it can be stated that the sensitivity rate and impact of input 1, that is, the benefit of digital technologies based on artificial intelligence, is more than the other 4 inputs on the digital level of innovation process, in the sense that having these technologies is the main axis. It is less effective to benefit from the output; and if it is not present in the laboratory, from other components. The lowest sensitivity and impact on the output in the model belonging to the third and fourth components, i.e. network and smart learning, were identified next to the component of benefiting from technologies, and this could mean that in the conditions of benefiting from digital technologies, according to the findings of the research, it is suggested to design the intelligent model of innovation in different industries and for each industry separately for future research. In the literature, researchers encountered a wide range of these digital innovation models such as banking, schools and institutions of higher education, health, etc. The second suggestion is that future researches can design a separate model for each of the input components so that the input component of this research is placed in the output position and the indicators determined in this research are used as their input. It is possible to design 5 other models according to the five components of this research, and connecting these models to develop a final and macro model can bring new achievements.

Abstract Abstract The purpose of this research is to investigate the presentation of the organizational team performance model with the approach of non-economic motives of organizational citizenship behavior in the municipalities of Tehran province. The current research is applicable in terms of purpose, and descriptive-analytical in terms of nature and method. The statistical population of the present study includes 100,000 employees of the municipality of Tehran province, which was determined 384 people due to the large sample size using the Morgan Karjesi table. Sampling was done by simple random sampling. The collection tool in this research includes a researcher-made questionnaire derived from the qualitative method. The reliability of the research was checked and confirmed using Cronbach's alpha criterion in SPSS software. PLS software was used to fit the conceptual model of the research. The findings of the research showed that the skills, expertise and resources of the organization along with the relevant components have an impact on the competitive environment of the organization. The findings also showed that the role of skill and expertise with a coefficient of 0.462 in the competitive environment of the organization is stronger than the role of organizational resources with a coefficient of 0.390, and the model has a good fit. Extended Abstract                                           Introduction Employee performance has always been considered as one of the main organizational resources by organizations due to the importance of human resources. A work team will be formed by putting the employees together. Work teams act based on the opinions of team's members; as a result, work teams will perform differently in different situations (Eskandar et al, 2020). Teamwork role in advancing the organization's goals of team building and work of the team helps to clearly outline the vision and common goals, and by creating a spirit of trust among human resources, the organization evokes a sense of commitment and responsibility. By emphasizing teamwork, the organization not only provides the spirit of cooperation and accountability, but also educates people who continuously seek to participate in decision-making, problem solving, and applying acquired knowledge and skills. Teamwork is the best method to provide high performance and team performance is evaluated through various criteria such as reducing errors, continuous quality improvement, increasing efficiency, and customer satisfaction (Abediyan et al, 2018). Based on the research, it is possible to examine the indicators of trust between team members, members' trust in the leader, participation and cooperation as effective factors on team performance. One of the issues raised regarding human resources is organizational citizenship behavior (Akbarimehr et al, 2020). Organizational citizenship behavior is a trans-role performance that includes more than the official roles of employees, i.e. voluntary and often unrewarded behaviors. A good citizen of the organization has a variety of behaviors such as accepting and assuming additional duties, following the regulations and procedures of the organization, maintaining and developing a positive attitude, and tolerating dissatisfaction and problems of the organization (Shamsi, 2020). Therefore, the researcher tries to answer the question: what is the model of organizational team performance with the approach of non-economic motives of organizational citizenship behavior in the municipalities of Tehran province? Theoretical Framework Team performance of the organization One of the most important characteristics of successful organizations is the tendency to team work and to revive the spirit of participation and constructive cooperation. Meanwhile, what helps organizations to increase their ability and face challenges is the formation of appropriate and effective teams. Team work is one of the most important facilitators in achieving positive and cost-effective results in the field of organization. Also, teams and working groups are a pleasant and acceptable mechanism for everyone to perform and complete tasks with more speed and efficiency in organizations (Makandi et al, 2021). By emphasizing on team building, the organizations can not only create and exploit multiple skills and spread the spirit of cooperation and responsibility, but also cultivate people who continuously seek to participate in decision-making and problem solving, and applying the acquired knowledge and skills (Nadi et al, 2017). Organizational citizenship behavior The study of people's behavior in work environments has been of interest to management science thinkers for a long time, and many studies have tried to classify behaviors and their causes. But a topic that has been raised in the last two decades and has attracted the attention of psychologists and sociologists in addition to behaviorists is organizational citizenship behavior (Ho& Li, 2020). Organizational citizenship behavior is a kind of valuable and useful behavior (Sadeghi ajeh, 2014) which includes diverse behaviors of employees such as accepting and assuming additional responsibilities, following the rules and procedures of the organization, maintaining and developing a positive attitude, patience and tolerating dissatisfaction and problems in the workplace (Qiu et al, 2019). Ghanbari & Ahmadi (2022) investigated the role of individual citizenship behavior in the organizational innovation of schools with the mediating role of knowledge sharing in primary school teachers. The results showed that individual citizenship behavior and knowledge sharing of teachers have a significant effect on the organizational innovation of schools at the level of 0.05. Individual citizenship behavior through knowledge sharing has a significant effect on the organizational innovation of schools at the level of 0.05. Also, individual citizenship behavior and knowledge sharing can explain 47% of the variance of schools' organizational innovation. Jafari & Jafari (2022) analyzed the effect of human capital on competitiveness in an article titled "Analysis of the effect of human capital on competitiveness in the insurance industry" (case study: Dana Insurance Company, Khorram Abad branch) with the structural equation modeling method. The results showed that human capital has a positive and significant effect on the competitiveness of Dana Insurance Company. On the other hand, by testing the hypotheses of the research, it was found that among the dimensions of human capital, the ability dimension of employees has a more positive and significant impact on competitiveness; therefore, human capital can be considered as a fundamental factor affecting the competitiveness of Dana Insurance Company, which increases its competitiveness. Research methodology The current research is applicable in terms of purpose, and descriptive-survey in terms of nature and method. The statistical population of the present study includes all the employees of the municipality of Tehran province, which has more than 100,000 employees. In order to estimate the appropriate sample size, the Morgan table was used, based on which, since the number of the statistical population is 100 thousand, the sample size was considered to be 384 people using the Morgan Karjesi table, and simple random sampling method was used. The research data collection tool includes a researcher-made questionnaire derived from the qualitative method Research findings SPSS and PLS software were used for data analysis. The findings of the research showed that the skills, expertise and resources of the organization along with the relevant components have an impact on the competitive environment of the organization. The findings also showed that the role of skill and expertise with a coefficient of 0.462 in the competitive environment of the organization is stronger than the role of organizational resources with a coefficient of 0.390, and the model has a good fit. Conclusion The current research was conducted with the aim of presenting the model of organizational team performance with the approach of non-economic motivations of organizational citizenship behavior in the municipalities of Tehran province. The results of this research corresponds with the results of SUKRESNA et al, (2021), Azila-Gbettor et al, (2021), Aghighi et al, (2020), Alfawaire & Atan (2021), Motiei et al, (2021), and Emeagwal & Ogbonmwan (2018). SUKRESNA et al, (2021) showed in a research that organizational citizenship behavior can mediate the relationship between the mental structures of organizational performance and employees' perceptions of their leaders, as well as their motivation to serve in the public sector. According to the present research, the following suggestions are presented: - Training employees to communicate well with others; - Skill training in using modern technologies and acquiring job skills and expertise; - The skill of employees in changing their role and giving energy to others and improving individual ability to influence decision-making; - Employees are employed as productive tools with motivation and talent in the organization; - Give importance to the team resources of employees in the organization;  

Abstract The purpose of this research is to examine the components of stakeholder participation to create value in the banking industry (the case study of East Azerbaijan Agricultural Bank). This research is developmental in terms of the goal, descriptive-exploratory in terms of the type of method, qualitative in terms of the method of collecting data, and meta-synthesis approach in terms of the method of conducting the research. The statistical population of the research includes 20 experts in the field of banking and stakeholder behavior analysis. The results showed that by using the scientific method of meta-synthesis and by reviewing published articles, the articles that dealt with the topic of business process integration were analyzed, and based on 27 selected articles, 37 indicators were extracted. In this study, 1009 articles and related researches in reputable journals were selected from citation profiles in the period before 2020. Finally, 11 cases were evaluated and identified, and the final framework was confirmed and identified by applying the total opinions of the experts, the components and indicators of the stakeholders' participation as 1- activity 2- resources 3- input/output 4- goal 5- time 6- technology 7- Laws 8- Beneficiaries (owner, executive, customer, and supplier). Extended Abstract                                           Introduction If organizations want to be successful in the long term, they should prioritize the needs and expectations of stakeholders. Stakeholders have right expectations and demands that should be taken into account. Therefore, the interaction and proper management of stakeholders should be an essential part of the management tasks of organizations, so that the management of public issues is defined as responding to the diverse stakeholders of organizations (Goldar et al, 2017). The need for stakeholder theory has been widely highlighted to develop sound strategies for a large organization. However, there is still a lack of popular visualization and application tools, and no unique approach is available to identifying and engaging stakeholders (Regge et al, 2018). In the complex and turbulent environment of the competitive market, organizations try to create a suitable position in the eyes of customers by providing distinct value propositions to customers. Meanwhile, an organization that is able to create a special value in the minds of customers will have a competitive advantage. This has prompted organizations to focus on the needs and demands of customers to supply special and distinctive products and services. No organization in the current era can satisfy customers by only using its special capabilities and facilities. Organizations are seeking to provide different products and services to customers by cooperating and participating with each other. In addition, organizations consider themselves responsible for their stakeholders and try to provide their desired value (Rahman Sarasht & Sheykhi, 2019). About the main nature of value creation in different stages of the value creation process, according to some researchers, potential value is hidden in the customer value statement of companies and organizations, and companies and organizations present to customers (Kikha et al, 2022). This hidden value is hidden in the essence of stakeholders' resources, which is used in the design of customer value options because it is not yet presented to customers in the real market environment and in the offers of companies and organizations. This is despite the fact that the scope of the customer's point of view is located where the hidden value of the company's and organization's market offers are objectified (Milles, 2017). Therefore, according to the issues raised, the present study intends to answer the question: what are the components of stakeholders' participation to create value in the banking industry in East Azerbaijan Keshavarzi Bank? Theoretical Framework Stakeholder The word "stakeholder" was used for the first time by the Stanford Research Institute. After the emergence of stakeholder thinking in this institution, for the first time in a report presented on planning in 1963 (Slinger, 1997), the Stanford Research Institute defines stakeholders as "people without whose support the organization would cease to exist." (Mainardes, 2011). Creating value The old view states that suppliers sell products or provide services; and customers buy them (Carroll & Buchholtz, 2006). But now, customers have the ability to communicate with manufacturers in each of the production stages, from design to its supply. This type of communication, as a mutual process, should result learning in both parties. In the other word, based on new approaches, customers and suppliers will have the possibility to create common value by cooperating with each other. Creating shared value is a type of marketing plan or business plan that emphasizes the creation and successive recognition of shared values ​​of the organization and the company and customers. Sheykh Beglu et al, (2021) reviewed the presentation of the stakeholder participation model in public policy making in the health system. The findings showed that by means of the theme analysis method, the theme network of factors affecting the participation of stakeholders was extracted with 103 basic themes, 20 organizing themes, and 5 inclusive themes. Then, by applying structural-interpretive modeling and establishing pairwise relationships, relationships between overarching themes were discovered and prioritized in four levels. As a result, the final model represents the levels of the framework of stakeholder participation in public policy, including the factors that form the basis of stakeholder participation, the conditions of interaction with stakeholders, the influencing factors of stakeholders, the operational conditions of stakeholder participation, and the results and consequences of stakeholder participation. Kajuri et al, (2021) examined the presentation of the value creation model for bank customers in the process of co-creation of brand value by bank customers (the case study of Shahr Bank). The results showed that the dimensions of the model include customer motivation, customer value, organizational factors, customer experience, customer loyalty and customer mental image; and the model has a good fit. Research methodology This research is developmental in terms of the goal, descriptive-exploratory in terms of the type of method, qualitative in terms of the method of collecting data, and meta-synthesis approach in terms of the method of conducting the research. The statistical population of the research includes 20 experts in the field of banking and stakeholder behavior analysis. Research findings Using the scientific method of metasynthesis and reviewing the published articles, the articles that dealt with the topic of business process integration were analyzed; and 37 indicators were extracted based on 27 selected articles. In this study, 1009 articles and related researches in reputable journals were selected from citation profiles in the period before 2020. Finally, 11 cases were evaluated and identified, and the final framework was confirmed and identified by applying the total opinions of experts, components and indicators of stakeholder participation as 1- activity 2- resources 3- input / output 4- goal 5- time 6- technology 7- rules 8- stakeholders (owner, (executor, customer, supplier). Conclusion The current research was conducted with the aim of investigating the components of stakeholders' participation to create value in the banking industry (the case study of East Azerbaijan Keshavarzi Bank). According to the obtained results, the current research is in line with the results of Sheykh Beglu et al, (2021), Kajuri et al, (2021), Fattahi & Rasulizad (2020), Seddigh et al, (2020), Bernadette et al, (2019), Shahmandi & Purajam (2019), Barzwar (2019), Esser & McNeill (2018), and Rukman (2017). Sheykh Beglu et al, (2021) investigated the presentation of the stakeholder participation model in public policy making in the health system. The findings showed that by means of the theme analysis method, the theme network of factors affecting the participation of stakeholders was extracted with 103 basic themes, 20 organizing themes, and 5 inclusive themes. Then, by applying structural-interpretive modeling and establishing pairwise connections, relationships between overarching themes were discovered and prioritized in four levels. As a result, the final model represents the levels of the framework of stakeholder participation in public policy, including the factors that form the basis of stakeholder participation, the conditions of interaction with stakeholders, the influencing factors of stakeholders, the operational conditions of stakeholder participation, and the results and consequences of stakeholder participation. According to the obtained results, the following suggestions were presented: - Organizations should try to adjust the output of processes as much as possible for the formation of other processes, and this will be the basis for integration between processes as much as possible. - Organizations should act towards the integration of goals by having missions, goals, plans and strategies aligned in all processes. - Regarding the time component, as a component that has a special effect on processes and their implementation, as well as their integration, especially in today's fast-paced world, paying attention to the time required to implement processes, the time required to change business processes and the implemented work, the time that the business process works without errors and the time required to communicate between the processes should be taken into consideration. - Based on the indicators of process automation level and the amount of attention to technology integration management, it is possible to help the integration of business processes to a great extent.

Abstract Abstract
The aim of the current research is to design a model for the development of women's employability capacity with an emphasis on the seventh development plan. This qualitative research was compiled using thematic analysis; in this research, using semi-structured interviews with 23 experts in the field of policy making, entrepreneurship and management, the findings were combined and the present model was designed. Based on this, by analyzing the content of the interviews using the Maxqda 2020software, the relevant dimensions and codes were extracted and the importance and priority of each was determined using Shannon's entropy technique. Based on the research approach, 34 concepts and 109 codes were extracted. Supportive policies, territorial development, skill capacities, entrepreneurship platform, explanation of women's employment document and educational system gained the highest importance coefficient. In this research, the development model of women's employability capacity was presented with an emphasis on the 7th development plan. Since a comprehensive model for women's employability with emphasis on the 7th Development Plan has not been presented so far, this research can be useful in promoting women's employment, social development, and job equality.
Extended Abstract                                          
Introduction
Employability is a measure that shows how desirable a person is among the workforce based on his skills and knowledge (van Harten et al, 2022). Employability skills are important because they make easier the people's recruitment for employers and increase their chances of getting and keeping a job (Chang, 2016; Abelha et al, 2020). According to the vision document of 2025, obtaining qualified and expert human resources is necessary to improve the country's position in the global economy. One of the most important criteria for measuring the degree of development of a country is the importance and prestige that women have in that country. The human development index for women in developed countries is 80%, in underdeveloped countries it is 60% for men, and in Iran, the index is 61% for men. Examining the causes of this difference in underdeveloped countries shows that in developed countries, most of this difference is caused by the level of employment and wages, while in underdeveloped countries, in addition to the differences related to the labor market, differences in education, health and Nutrition is also observed (Najirad et al, 2003). The general policies of the 7th Development Plan are priority of economic progress combined with justice. The goal of the 7th development plan in Iran is to achieve a fair economic progress with an average growth rate of 8% during the duration of the plan. The challenge of investigating the development of women's employment capacity with emphasis on the seventh development plan lies in the existing gender inequalities in the workforce. Women often face barriers to employment and career advancement, including limited access to education and training, discriminatory hiring practices, and unequal payment. The problem is that these barriers lead to underrepresentation of women in some industries and leadership positions, causing a loss of talent and potential economic growth.
The current research will be done with the aim of designing and explaining the development model of women's employability capacity with emphasis on the seventh development plan; a research that covers the existing research gap and will be useful in the development of literature in the research field. The main question of the research is raised as follows: What is the development pattern of women's employability capacity with emphasis on the 7th development plan?
Research literature
Employability is the ability of people to get a suitable job. The measurement of employability should be done by considering all dimensions (Delva et al, 2021). Lee argues that despite the existing notions, employability is not defined in terms of skills, rather learning plays an important role in this process and creates constructive experiences, so employability is defined as a learning process. Continuous learning continues even after employment. With this statement, Harvey aims to differentiate employability and how to measure it. Other definitions of employability are: 1. The ability to obtain primary employment; hence the interest in ensuring that 'key competences', career advice and understanding about the world of work are embedded in the education system. 2. The ability to maintain employment and "transition" between jobs and roles within the same organization to meet new job requirements. 3. The ability to obtain a new job if necessary, that is, to be independent in the labor market with the desire and ability to manage one's job transfer between and within work organizations using optimal effort. 4. A person's capacity to continuously develop and improve their skills to maintain relevance and attractiveness in the labor market (Gürbüz et al, 2022). Based on business strategies in sharing economies, learning job techniques and acquiring qualifications have a significant impact on the employability process. McQuaid and Lindsay (2005) have introduced two alternative views in the discussions related to employability. The first point of view is expressed based on the individual's personal abilities and talents. Another point of view considers the external factors of labor market organizations, economic and social conditions; and states that these factors may affect the probability of a person's success in getting a job and promoting his career. Employability is highly dependent on the analysis of job elements and describes people's attitude and perception of jobs and peers. Therefore, employability is the opportunity to obtain and maintain a job (Reilly et al, 2016).
Research methodology
The current research is based on qualitative research in the inductive paradigm and is applicable in terms of purpose. The statistical population of this research was experts and professors in the field of policy making, entrepreneurship and management; according to the purpose of the research, sampling was done in a purposeful way using the snowball technique and with the number of 23 people. The sample size was determined using the principle of theoretical saturation in such a way that no new factor was identified after interviewing the 21st and 22nd people, and the interview process ended with the 23rd person. The interviews were conducted face-to-face with open questions, and then, using the coding process, the components of the women's employability capacity development model were identified with an emphasis on the seventh program. Based on this, by analyzing the content of the interviews using the 2020 Maxqda software, the relevant dimensions and codes were extracted and the importance and priority of each was determined using Shannon's entropy technique.
Research findings
According to the analysis of the interviews, the categories were written in the form of references. Based on the analyzes conducted with the help of the theme analysis method, a total of 34 concepts and 109 codes were discovered and labeled for the components of the development of women's employability capacity with emphasis on the seventh program in this research. Based on this, the policy makers and those in charge of employment in the country should acquire recognition and detailed knowledge of the components of the development model of women's employability capacity with emphasis on the 7th development plan, such as support policies, challenges related to gender discrimination, territorial development, need assessment, value chain analysis, strategic alignment, dealing with island thinking, talent management, skill capacities, strategic balance, entrepreneurial platform, governing management structure, formation of think chambers, explanation of women's employment document, cognitive complexity, synergy, policymakers' attitude, knowledge sharing culture, empowerment, integration mechanisms, focus on core issues, community employability culture, networking, honoring the status of women, professionalization, decentralization, job-employee fit, cultural enrichment, information platforms, educational system, financial support, cognitive flexibility, control and supervision system and economic infrastructure. Supportive policies, territorial development, skill capacities, entrepreneurship platform, explanation of women's employment document and educational system gained the highest importance coefficient.
Conclusion
The seventh program is the development of the fourth paragraph of Iran's 20-year vision document; it is the first program in line with the realization of the declaration of the second step of the Islamic Revolution, and the first program that, for the realization of justice in the area of ​​the land, has made the approved documents the basis of an integrated approach to the land, and paid serious attention to and focus on the key issues with a problem-oriented approach; and in this program, the government's priority programs are clear and can be cited in the program due to the existence of the People's Government Transformation Document. The axes of public culture enhancement in consolidating Iranian Islamic lifestyle, national identity promotion, national solidarity and trust, women's growth and prosperity, family institution consolidation, social health promotion and social damage prevention are emphasized in this program in order to be properly introduced into macro policies. In this program, emphasizing the need to create platforms for women's employability, the undeniable role of women in the development of knowledge-based economy and job creation has been emphasized. Therefore, the existence of a model in order to improve the employability capacity of women can reveal various aspects of this matter and be an important step in achieving the planned goals. The findings of the research, such as communication skills and technical skills as the codes of the category of skill capacities, are in line with the research results of Movahedi et al (2019). Also, the educational system is consistent with the research results of Ricci et al (2021), Hassan et al (2020), Wu (2019), Faulkner et al (2019). The research findings in the field of information platforms are consistent with the research results of Hassan et al (2020), Pappas et al (2018) and Movahedi et al (2019). The findings of the research in the field of the ruling management structure are consistent and compatible with the research results of Movahedi et al (2019). The development of employability capacity should be done at the local level first and according to geographical needs. It is suggested that the coordination deputy of economic affairs of the governorates conducts a detailed analysis of the local conditions and uses the capacities of the employment trustees of the provinces, such as agricultural jihad, industrial towns, industry and mining organization, and banks. Obviously, due to the requirement of economic institutions to respond to this deputy at the provincial level, the approvals of this deputy are mandatory. The Supreme Council of Employment, as the official authority for dealing with employment challenges, should place the issue of women's employability among its work priorities.
 

Abstract Abstract The purpose of this research is to design a strategic model of online banking relational marketing in the fourth industrial revolution with a data-based approach. The research method is applicable-developmental in terms of its purpose, and exploratory in terms of its nature. The statistical population of the research included 11 experts from the banking industry, and the sampling was done in a purposeful and snowball type. Data-based theory was used to collect and analyze data. The data collection tool is a semi-structured interview. Data analysis and model design were done in three stages of open, central and selective coding. The findings showed that emerging behaviors and new developments in relational marketing are key causal conditions, while the development of relational marketing components, customer behavior changing, and the fourth industrial revolution were identified as ground conditions. This study also showed the need for banking transformations, external disruptions, relationship management and human capital transformation, and barriers to online banking as intervener factors. Tactical transformative programs in the open banking system, using customer data for banking strategy, opportunism and loyalty with a constructivist perspective were identified as effective strategies. The consequences of this model include the transformation of the banking system and new banking, investing in new forms, increasing income by aligning online services, and managing relationships with virtual customers. Extended Abstract                                           Introduction The first industrial revolution changed life and economy in general and changed the agricultural economy to an economy in which industry and machines are dominated by humans. Oil and electricity facilitated mass production in the second industrial revolution, and information technology was used to automate production in the third industrial revolution. Finally, in the fourth industrial revolution, attention was paid to increasing the cognitive power of human productions and this power was strengthened (Xu et al., 2018). Considering the fourth industrial revolution and the decline of traditional marketing and the emergence of relational marketing, organizations are determined to create strong links with their customers by using relational marketing strategies. Relational marketing is today's business art (Talari & Khoshroo, 2022). Online banking relational marketing is one of the important factors in the fourth industrial revolution. Due to the advancement of information and communication technology, banks need to find new ways to attract and retain their customers. In this regard, the use of online relational marketing methods can be effective in providing customers with a positive banking experience. Currently, the business environment is witnessing deep and fundamental changes, and many experts in the field of business and economics believe that this evidence indicates the beginning of a new era, the fourth industrial revolution (Basyazicioglu & Karamostafa, 2018). The first industrial revolution changed life and economy in general and changed the agricultural economy to an economy in which industry and machines are dominated by humans. Oil and electricity facilitated mass production in the second industrial revolution, and information technology was used to automate production in the third industrial revolution. Finally, in the fourth industrial revolution, attention was paid to increasing the cognitive power of human productions and this power was strengthened (Xu et al, 2018). Based on this, the current research is looking for an answer to this question: What is the strategic model of online banking relational marketing in the fourth industrial revolution with the data-based approach?  Theoretical Framework Relational marketing Relational marketing consists of Creating, maintaining, and promoting relationships with customers and stakeholders of the company, which is achieved through building trust as a result of fulfilling obligations. In fact, relational marketing is defined as a type of marketing that attracts, develops, maintains, and promotes relationships with customers. The rationale for using relational marketing is that it forces the company to focus on the long-term financial benefits that can occur when a customer first enters the organization, and this is because acquiring new customers for the company is 5 to 10 times more expensive than retaining existing customers (Ghosal et al, 2020). Principles of marketing in the fourth industrial revolution Apart from the design principles of the fourth industrial revolution, marketing throughout the new industrial revolution has been accompanied by redefined marketing principles based on connectivity, communication, and collaboration in the digital ecosystem. Unlike traditional marketing, where marketers and organizations are in control, Industry 4.0 requires that all stakeholders—including customers, business partners, and suppliers—in the digital ecosystem be treated equally (Ramadhani et al, 2019). The main empowering technologies of the fourth industrial revolution in marketing Emerging technologies provide opportunities for companies to change their practices and adapt them to customer demands and expectations. Therefore, with new technologies in Industry 4.0, companies can achieve the sustainable competitive advantage needed for better market positioning and performance (Jančíková et al, 2019). Pfajfar et al, (2022) conducted a research entitled the value of corporate social responsibility for multiple stakeholders and social impact - relationship marketing perspective. The results confirm a positive relationship between employee-oriented CSR and the perceived usefulness of CSR actions for society, customers, and employees (but not suppliers). Differences between small and medium-sized companies and large B2B companies are observed with contrasting perceptions of relationship quality antecedents and outcomes. Rosário et al, (2022) conducted a research titled Industry 4.0 and Marketing: Towards an Integrated Future Research Agenda. This paper shows that there are several research avenues for marketing researchers to conduct research in, but the most important areas are the five principles of marketing in Industry 4.0: collaboration, dialogue, co-creation, recognition, and connection. Future research should focus on the quantitative study of these five principles. Research methodology The research method is applicable-developmental in terms of its purpose, and exploratory in terms of its nature. The statistical population of the research included 11 experts from the banking industry, and the sampling was done in a purposeful and snowball type. Data-based theory was used to collect and analyze data. The data collection tool is a semi-structured interview. Research findings Data analysis and model design were done in three stages of open, central and selective coding. The findings showed that emerging behaviors and new developments in relational marketing are key causal conditions, while the development of relational marketing components, customer behavior changing, and the fourth industrial revolution were identified as ground conditions. This study also showed the need for banking transformations, external disruptions, relationship management and human capital transformation, and barriers to online banking as intervenor factors. Tactical transformative programs in the open banking system, using customer data for banking strategy, opportunism and loyalty with a constructivist perspective were identified as effective strategies. The consequences of this model include the transformation of the banking system and new banking, investing in new forms, increasing income by aligning online services and managing relationships with virtual customers. Conclusion The current research was conducted with the aim of designing a strategic model of online banking relational marketing in the fourth industrial revolution with the data-based approach. The results of this research are in agreement with the results of Pfajfar et al, (2022), Rosário et al, (2022), Talari & Khoshroo (2022), Adetyoa et al., (2021), Zalkani Andarvar (2021), Mohammadi fateh et al, (2022), Najafzadeh Ziaodin et al, (2021), Mosavi et al, (2020), Vazifehdoust et al, (2017), and Kosiba et al, (2018). Mohammadi fateh et al, (2022) showed that the technologies of the fourth industrial revolution are big data, biological identification system, fraud detection technologies, contactless ATM, data mining, cloud computing, marketing, versatile channel, artificial intelligence, fintech, biometrics, blockchain, intelligent social networks, artificial neural networks, remote monitoring technologies, commercial Internet of Things, and digital account, respectively. Then, by these experts, the application rate of these technologies is specified in four areas of banking, i.e. marketing, human resource, risk management, and customer orientation in a three-level spectrum (low, medium and high). According to the opinion of experts, all the identified technologies have medium to high application in four areas of banking. According to the results of the research, the following suggestions are presented: It is suggested that online relational marketing is one of the important aspects of banking in the fourth industrial revolution. Online relational marketing can improve customer loyalty. To manage relationships with virtual customers, banks must use the principles of marketing in the fourth industrial revolution, including collaboration, dialogue, co-creation, recognition and connection. These principles create an innovative approach to the marketing mix under new conditions in the fourth industrial revolution.  

Abstract Abstract
The purpose of this research is to present a model of portfolio management in investment funds based on behavioral financial variables. The method of this research was applicable in terms of purpose, and of descriptive-survey type. The statistical population of the research includes 10 experts who have a PhD. degree in financial management or accounting and university professors. The method of data collection was a researcher-made questionnaire and analyzed using structural and interpretive modeling. The results showed that in the first level, the most effective components included: control of the fear of surviving profit, normalization of conservative behaviors, and control of regret-avoidance behaviors. In the second level, the components influencing the first level, i.e. paying attention to self-control behaviors, having a written investment strategy, paying attention to the principles of mental accounting; and in the third level, the components influencing the second level, which include behavioral optimism and pessimism, Paying attention to risk-averse and risk-taking behaviors and, controlling mass behaviors; and the most effective component at the fourth level includes the effect of inclination. In the Mik Mak model, most of the variables were also included in the linked variables, which have a strong influence and also a strong dependence force.
Extended Abstract                                          
Introduction
The behavior of investors as those who seek to optimize profit, omniscient, and infinitely rational, is difficult to understand in the real world. Even assuming that investors are aware of everything, the fact that they may have to interact in information search processes and that they may have rational limitations has been ignored (Barasud & Zamardian, 2019). The uncertainty in analyzing investment risk against expected market returns means that portfolio management has been a thoughtful challenge for portfolio managers. Fund managers should change their portfolios at regular intervals and should add a tendency style. Portfolio management is the allocation of assets, diversification and rebalancing of assets up to higher than the limit set. Asset allocation is the division of assets in the portfolio between risky and risk-free asset classes. Typically, investing requires the careful design of an investment policy statement that appeals to the unique needs of investors. Diversification is sharing risk and reward across asset classes because it is difficult to determine which particular subset of assets is likely to perform better than another. Therefore, diversification is a process of expanding the number of assets in a portfolio in order to minimize investment risk (Doeh Agblobi et al, 2020). Thus, in this research, the researcher intends to answer the basic question: what is the model of portfolio management in investment funds based on behavioral financial variables?
Theoretical Framework
Portfolio management
Portfolio management is the art and science of deciding on investment texture and strategy, matching investments with objectives, allocating assets to individuals and institutions, and balancing risk against performance (Bkhit, 2019).
Behavioral finance
Behavioral finance studies how psychological phenomena affect financial behavior. Financial behavior studies how people behave in determining financial matters. Behavioral finance is a new theoretical branch in finance that is defined by combining the knowledge of psychology, sociology and other social sciences (Meisa Dai et al, 2021).
Investment funds
On the other hand, in most of the developed countries, investment funds are considered as the central core of the capital market and they direct huge amounts of wandering capital to the productive and active sectors of the society every month. By adopting appropriate policies, these funds can play an essential role in reducing inflation, increasing production, and improving the efficiency of managers. Fortunately, the investment funds industry in Iran was established in 2007 with a delay of several decades, but with a lot of acceptance from the investors. Considering the irreplaceable role of these funds in allocating optimal financial resources in the capital market, evaluating the type of transactions in these companies and the effect of their type of ownership on the type of transactions of these financial intermediaries can provide valuable information to investors (Shams & Esfandiari Moghadam, 2016).
Bennett et al, (2023) mentioned that it was implemented as a behavioral finance approach for pricing decentralized financial assets. They found that decentralized finance provides a better explanation of asset pricing in rapidly evolving markets than traditional financial theory. Investor attention, sentiment, discoveries and biases, and network effects interact to form a highly volatile and dynamic market.
Keshavarz et al, (2021) in a research on investment strategies based on technical indicators: evidence of behavioral reactions of investors in the Tehran Stock Exchange. The results showed that according to the coefficient of variation and the correlation test, the results indicate that the indicators of moving average, exponential moving average, and relative power, compared to other indicators, are more indicative of the behavioral reactions of investors.
Research methodology
The method of this research was applicable in terms of purpose, and of descriptive-survey type. The statistical population of the research includes 10 experts who have a PhD. degree in financial management or accounting and university professors. The method of data collection was a researcher-made questionnaire.
Research findings
Data analysis using structural and interpretive modeling. The results showed that in the first level, the most effective components included: control of the fear of surviving profit, normalization of conservative behaviors, and control of regret-avoidance behaviors. In the second level, the components influencing the first level, i.e. paying attention to self-control behaviors, having a written investment strategy, paying attention to the principles of mental accounting; and in the third level, the components influencing the second level, which include behavioral optimism and pessimism, Paying attention to risk-averse and risk-taking behaviors and, controlling mass behaviors; and the most effective component at the fourth level includes the effect of inclination. In the Mik Mak model, most of the variables were also included in the linked variables, which have a strong influence and also a strong dependence force.
Conclusion
The present research was conducted by presenting the model of portfolio management in investment funds based on behavioral financial variables. The results obtained in this research is aligned and in the same direction with the results of Bennett et al, (2023), Fuladi et al, (2021), Keshavarz et al, (2021), Sajid (2021), Leković (2020), Lotfolah Hamdani (2020) and Asadi Qarajalo & Abdo Tabrizi (2019). Bennett et al, (2023) mentioned that it was implemented as a behavioral finance approach for pricing decentralized financial assets. They found that decentralized finance provides a better explanation of asset pricing in rapidly evolving markets than traditional financial theory. Investor attention, sentiment, discoveries and biases, and network effects interact to form a highly volatile and dynamic market.
Therefore, it is suggested to investigate the effects between these variables using structural equation models in future researches. Also, other methods of uncertainty modeling, including fuzzy DEA, should be used to model these indicators.
 

Abstract Abstract
The purpose of this research is to investigate the communication model of customer participation and competitive business with social media based on brand in manufacturing and trading companies of Ahvaz city. In terms of purpose, the current research is applicable, and of the survey research type. The statistical population of the research includes the customers of the food manufacturing and trading companies in the industrial towns of Ahvaz city. Due to the unlimited population, the statistical sample was considered to be 384 people using Cochran's formula, and finally 312 questionnaires were analyzed. Sampling in this research is available randomly. The collection tool in this research is a questionnaire. Data analysis was done using SPSS and PLS software. The findings showed that the identified factors had a significant effect, and the overall index of fit (GOF) was obtained as 0.661, which is a strong index and shows the overall high quality of the model.
Extended Abstract                                          
Introduction
Virtual social networks are a new generation of Internet websites. Internet users in these websites gather together virtually around a shared axis and form online communities (Torki et al, 2023). With the spread of the Internet and the spread of social media, customers' buying patterns have changed and their shopping habits have been affected by business based on social networks. In addition to using search engines, customers also search for desired products and brands on social media such as Instagram. The growth of Instagram has attracted the interest of many large companies that are looking for new ways to strengthen their relationships with their customers. Instagram is one of the fastest programs in growing social media (Anderson Jiang, 2018).
Consumer interactions on social media are generally important. The evolution of social media and technologies now allow consumers to easily share their opinions through the online environment. Written and visual content sharing programs allow users to share information resulting from the hedonistic activities resulting from the use of various products and services (Fox et al, 2018).
Online branding is becoming increasingly popular in modern society, as marketing is largely developed through social media platforms, blogs, websites, and other online channels. Companies should also have an active digital presence and show themselves in the digital field by using different digital channels to develop the brand (Bamm et al, 2018). These activities usually require high or moderate participation from consumers, which creates a positive psychological state when experiencing their participation or cooperation with the brand, and includes aspects of cognitive effort, emotional involvement, and behavioral diversity (Lu et al, 2015).
For this purpose, the current research aims to answer this question: What is the communication model of customer participation and competitive business with social media based on brand in manufacturing and trading companies of Ahvaz?
Theoretical Framework
brand
A brand is not only a symbol that distinguishes a product from others, but also includes all the features that come to mind when a buyer thinks of that brand. These characteristics are the concrete, abstract, psychological, and social characteristics of that product (Meysamiazad et al, 2024).
social media
Social media is a group of online user programs whose purpose is to facilitate interactions and content sharing. Social media is a group of Internet-based applications that are built on the ideological basis of Web 2 technology and allow users to create and share their own content. People increasingly consider social media programs to be an important part of their daily lives and are more likely to move their interactions to virtual programs (Alalwan et al, 2017).
Competitive advantage and customer engagement
The brand can create a competitive advantage for the company and maintain loyal customers. Creating a positive brand image is a strategy. This brand image can be considered as a cultural heritage, service quality, and trust; and can affect customer satisfaction (Araujo et al, 2023). Wang & Kim (2017) showed that functional advantages in products, service advantage in providing services, analytical advantage in CRM, multi-channel advantage in communication, symbolic advantage in advertising, and network advantage in sharing resources have a significant impact on customer value and brand loyalty.
Competitive advantage of online businesses
Companies in the market look for mistakes of competitors and use opportunities. One of the ways to increase the power of competition in this market is to use strategic management in order to achieve a competitive advantage. In the most basic concept of competitive advantage, in a way, it refers to the company's exploitation of resources in order to achieve superior performance in which three main factors can lead to differentiation and difference from other competitors. These three factors include sources of competitive advantage, competitive advantage, and company performance. Competitive advantage is the basis of strategic planning in companies, which broadly refers to using opportunities and neutralizing competitive threats (Tong, 2023).
Torki et al, (2023) investigated the impact of social media participation on green management (case study of employees of Shahrekord industrial companies). The results showed that the amount of use of social media, the type of use of social media, and the amount of trust in users in social media have a positive effect on green management. This means that with people's easy access to virtual space and social networks, the Internet has become an inseparable part of life. In order to make optimal use of the created space, companies are trying to use this opportunity optimally and to their advantage, and improve the green management.
Rahimi et al, (2023) investigated the impact of digital content marketing on brand awareness through social media and customer interaction. The results showed that there is a positive and significant relationship between digital content marketing and brand awareness. Also, social media and customer interaction play a significant mediating role in the relationship between digital content marketing and brand awareness. It is obvious that digital content marketing as a new phenomenon plays a vital role in displaying brand name, strengthening customer relationship and increasing brand awareness, customer loyalty, and sales.
Research methodology
In terms of purpose, the current research is applicable, and of the survey research type. The statistical population of the research includes the customers of the food manufacturing and trading companies in the industrial towns of Ahvaz city. Due to the unlimited population, the statistical sample was considered to be 384 people using Cochran's formula, and finally 312 questionnaires were analyzed. Sampling in this research is available randomly. The collection tool in this research is a questionnaire.
Research findings
Data analysis was done using SPSS and PLS software. The findings showed that the identified factors had a significant effect, and the overall index of fit (GOF) was obtained as 0.661, which is a strong index and shows the overall high quality of the model.
Conclusion
The present research was conducted with the aim of investigating the communication model of customer participation and competitive business with social media based on brand in manufacturing and trading companies. The results of this research is aligned with the results of Torki et al, (2023), Rahimi et al, (2023), Tang (2022), Shekarchizadeh & Hakim Akif Esfahani (2021), Dedeoglu (2019), Lee et al, (2019), Maia (2018), Taheri et al, (2017), Madrasi Tehrani & Saidi (2017), Esfandiari & Imankhan (2019). Rahimi et al, (2023) investigated the impact of digital content marketing on brand awareness through social media and customer interaction. The results showed that there is a positive and significant relationship between digital content marketing and brand awareness. Also, social media and customer interaction play a significant mediating role in the relationship between digital content marketing and brand awareness. It is obvious that digital content marketing as a new phenomenon plays a vital role in displaying brand name, strengthening customer relationship and increasing brand awareness, customer loyalty, and sales.
In line with the obtained results, it is suggested:
⮚ to improve the online activities of the company, the managers well provide the possibility of access to personal information for the customers and ensure the security of the customers' information.
⮚ the managers provide the best information about products and services to customers through the company's websites.
 

Abstract Abstract
The purpose of this research is to investigate and explain the effective variables in measuring intellectual capital and to provide an optimal model. This research is developmental in terms of its purpose, analytical-correlational in terms of the type of method, qualitative in terms of the method of collecting data, and with a meta-composite approach in terms of the method of conducting the research. The statistical population of the research includes all studies and researches done in the past in the field of intellectual capital. In two parts in this research; descriptive and inferential meta-analysis, the analysis of the intellectual capital of the researches published in the period of 1366 to 1399, extracted from the Irandoc database, in the number of 51 studies (102 variables - including repeated variables, finally 53 variables) was analyzed. Based on the descriptive meta-analysis, the classification of intellectual capital research were categorized into three categories of organizational focus, the focus of intellectual capital accounting literature, and the research methods used in the research. Also, based on the criteria of concentration of accounting literature, intellectual capital research was divided into five categories: audit, accountability and governance, management control/strategy, performance measurement, and others (including the public). Inferential meta-analysis was performed using stata software. Based on the results of inferential meta-analysis, the relationship between intellectual capital components and financial performance components was examined. The results showed that based on the pattern of random effects, the average effect size extracted from the research is equal to 0.269.
Extended Abstract                                          
Introduction
Intellectual capital is the most important source for sustainable competitive advantages of organizations, and today one of the important responsibilities of managers is better management of intellectual capital (Bani Asadi et al, 2021). Intellectual capital is the most basic asset of an organization, and in a knowledge-oriented society, intellectual capital is used to create value for the organization, and organizational success depends on the ability to manage these assets. Intellectual capital is defined as a set of intangible assets, resources, and competitive abilities that are obtained from organizational performance and value creation (Montazeri et al, 2022). Intellectual capital includes all processes and assets that are not usually shown on the balance sheet, and also includes all intangible assets (such as trademarks, product patents and business names) that are considered in modern accounting methods (Nowrouzi et al., 2017). Intellectual capital is a capital beyond physical and tangible assets. Today, intellectual capital can play an important role in creating added value due to the production of knowledge and information and as a result the production of wealth in the knowledge-based economy (Asgarnezhad Nouri & Emkani, 2017). Intellectual capital is a language for thinking, speaking, and taking actions related to the organization's future revenue drivers, which include relationships with customers and partners, innovation efforts, organizational infrastructure, and knowledge and skills of the organization's employees. As a concept, intellectual capital is associated with techniques that empower managers to strengthen management (Zareian Moradabadi et al, 2022). Therefore, according to the issues raised, the current research intends to answer the question: how to explain the effective variables in measuring intellectual capital and provide the optimal model?
Theoretical Framework
Intellectual Capital
Intellectual capital is capabilities, knowledge, culture, process strategy, intellectual assets, and communication networks that create value and competitive advantage for the organization, and help the organization achieve its goals (Mahmoudi et al, 2021). Intellectual capital is defined as a general set of abilities, information, culture, strategy, trends, and relational networks of an organization that have created a value or competitive improvements and help the organization to achieve its goals. Broking defines intellectual capital as the market assets of human assets, the axis of intellectual assets and sub-structural assets, and believes that when these assets are combined with other production resources of the organization, it leads to the creation of value. Most of the studies conducted on intellectual capital have concluded that intellectual capital consists of three types of capital, which include: human capital, structural capital, and relational (customer) capital (Farazmand et al, 2019).
Zareian Moradabadi et al, (2022) investigated the model of intellectual capital evaluation in the state banks of the Islamic Republic of Iran. The results showed that intellectual capital has 4 components and 48 sub-components. The results of structural equation modeling showed that the effect coefficients of all sub-factors and variables (the four dimensions of the intellectual capital evaluation model, including human, structural, relational, and innovation capital) are significant and higher than 5.00, and also their significance levels are higher than 96.1. Therefore, the evaluation model of intellectual capital as a valid and reliable tool has the ability to be used for better management of intellectual capital.
Olarewaju & Msomi (2021) investigated the intellectual capital and financial performance of the development of South African public insurance companies, the impact of intellectual capital on financial performance for the period 2008 to 2019. The findings showed that there is a significant and direct relationship between asset yields of the previous period, intellectual capital, and the financial performance of insurers in the South African Development Association. Except for intellectual capital components; human capital components and structural capital have a direct and significant relationship with the asset yields, while capital employed has an inverse and non-significant relationship with asset yields. The risk-control variables are policy issue, insurer size, and leverage; all of which inversely and significantly affect asset yields. Therefore, there is a U-shaped relationship between intellectual capital and financial performance in public insurance companies in the South African Development Association. Therefore, policy makers and insurance managers should maximize their intellectual capital because it creates a competitive advantage that leads to improved financial performance and wealth generation.
Research methodology
This research is developmental in terms of its purpose, analytical-correlational in terms of the type of method, qualitative in terms of the method of collecting data, and with a meta-composite approach in terms of the method of conducting the research. The statistical population of the research includes all studies and researches done in the past in the field of intellectual capital. In two parts in this research; descriptive and inferential meta-analysis, the analysis of the intellectual capital of the researches published in the period of 1366 to 1399, extracted from the Irandoc database, in the number of 51 studies (102 variables - including repeated variables, finally 53 variables) was analyzed.
Research findings
Based on the descriptive meta-analysis, the classification of intellectual capital research were categorized into three categories of organizational focus, the focus of intellectual capital accounting literature, and the research methods used in the research. Also, based on the criteria of concentration of accounting literature, intellectual capital research was divided into five categories: audit, accountability and governance, management control/strategy, performance measurement, and others (including the public). Inferential meta-analysis was performed using stata software. Based on the results of inferential meta-analysis, the relationship between intellectual capital components and financial performance components was examined. The results showed that based on the pattern of random effects, the average effect size extracted from the research is equal to 0.269.
Conclusion
The current research was conducted with the aim of investigating and explaining the effective variables in measuring intellectual capital and providing an optimal model. According to the obtained results, the current research is in line with the results of Zareian Moradabadi et al, (2022), Olarewaju & Msomi (2021), Bani Asadi et al, (2021), Farazmand et al, (2019), Kamath (2019), Francesco Gangi et al, (2019), Ghadir & Shihap Mohammad (2019), Hapsah & Imbarine et al, (2019), and Soetanto & Liem (2019). Bani Asadi et al, (2021) showed that there are 863 researches in the field of intellectual capital, at the end of which 112 researches were selected and by analyzing their content, the relevant dimensions and codes were extracted and the importance and priority of each was determined using Shannon's entropy method. Based on the findings of the research, the organization's image and reputation codes, organizational procedures, patents, customer loyalty, employee creativity, and the organization's training programs for employees have the highest coefficient of importance among the three dimensions of intellectual capital. Finally, after going through the research steps, a comprehensive model of intellectual capital was presented in three dimensions of human capital, structural capital, and relational capital.
In relation to the factors related to corporate governance, there are factors related to intellectual capital, managerial ownership, institutional investors, independence of the board of directors, corporate ownership, and board of directors' compensation. Therefore, it is suggested to improve the intellectual capital by choosing optimal approaches from each of the above factors, for example, by increasing the amount of the board of directors' bonus, the motivation of the managers can be increased, or by increasing the independence of the board of directors, or by increasing the institutional ownership etc. improved intellectual capital. It is important to mention that the above factors are important in measuring intellectual capital and the intellectual capital of any organization can be measured using all these factors.

Abstract In order to calculate the employment trend in Iran, the aim of the article is to optimize the employment trend in Iran for the years of implementation of the sixth economic, social and cultural development program (2017-2021). For this purpose, first, using the Gauss-Seidel algorithm, the system of dynamic and non-linear macrometric equations and the quantitative goals of the sixth development program; the employment process in the country was simulated. Then, the optimal trend of the working population was calculated from the minimization of the welfare loss function of the policymaker by programming and implementing an open cycle algorithm and solving the Bellman equations. The obtained results showed that achieving higher employment requires controlling inflation at lower rates as well as achieving a higher economic growth rate. The findings of this research are compatible with the theory of new Keynesians such as Gerish, Clarida, Gertler, Menkiu, Walsh and Taylor regarding the necessity of simultaneously reducing inflation and increasing production. Hence, the jump in production and curbing inflation can make possible the optimal control of employment and business at the targeted level. Based on this, the targeting of macroeconomic indicators in the available (possible) territory, complete monetary and financial discipline, independence of the central bank, and the use of stochastic optimal control theory in the targeting of development programs are among the policy recommendations of this article. Extended Abstract                                           Introduction "Inflation" and "Production" have a privileged position among the economic variables that are used as indicators in evaluating the performance of the economy. In a theoretical approach, Keynesian economics after the Great Depression of 1929 establishes an alternative relationship between inflation and production within the framework of demand-oriented economics. This theoretical achievement was confirmed by Fisher in 1926 using statistical data (Fisher, 1926). After Keynes and in the 1950s, Phillips, using statistical data from England, showed that in the short run Keynes's idea about the substitution between inflation and unemployment is valid (Phillips, 1958). In the early 1960s, Friedman and Phelps showed, based on the model of adaptive expectations, that there is no relationship between inflation and unemployment in the long run, and that there is a substitution relationship only in the short run (Fredman, 1968; Phelps, 1967). In a situation where Keynes' views were involved in a theoretical challenge by the traditional Chicago monetarist school led by Friedman and his followers such as Schwartz and Phelps, Lucas' criticism of econometric models and emphasis on the importance of deep coefficients and relationships resulting from rational optimization, along with scientific efforts by Svensson and Woodford on the need to provide models with time consistency in the 1970s led to the definition of a new monetary rule by Taylor in the early 1990s (Svensson, 1997; Woodford, 2001; Taylor, 2000). Gali, Clarida, Gertler and Walsh derived the monetary rule from the minimization of a welfare loss function for the policymaker with respect to the constraint functions (Gali & Gertler, 1999; Clarida et al, 1999). Observing the inability of the monetary policy of inflation targeting and market fundamentalism to deal with the economic consequences of the 2008 financial crisis and the "resumption of Covid-19", as well as the failure of economic neoliberalism to automatically achieve the economic growth rate to goals such as a significant reduction in inequality and poverty has proposed the new economic policy called employment targeting as a solution in early 2019 (Ghate & Mazumder, 2019). As examples to be mentioned in this article, we can mention the active inclusion policy by the European Union that has started in the last few years. In this way, which is known as active labor market policy, the government tries to increase the employability of citizens and help increase the number of employees (Fredriksson, 2020). In the country of Iran, a 10-year strategy for the period of 2021-2031 has been designed and implemented so that people with different degrees of desirability are employed. Theoretical Framework In researches related to the relationship between inflation and unemployment, Phillips theory is mentioned as one of the leading theories. His research showed that there is an indirect relationship from inflation to unemployment (Fisher, 1926). In 1958, Phillips reached results that show that there is an indirect relationship between these two variables in the short term (Phillips, 1958). In 1960, Lipsey conducted his empirical research during the period 1857 to 1962 for England and used the traditional theory of "price behavior in the market" for this purpose. According to this theory, in the conditions of excess demand, prices increase; and in conditions of excess supply, prices decrease. (Lipsey, 1960). In 1960, Samuelson and Solow hypothesized that firms set their pricing based on a fixed law (average cost of production) in which price is calculated based on unit labor cost plus profit. In the 1960s, the Phillips curve theory was developed by Friedman and Phelps with an emphasis on expectations. One of the important steps in the development of Phillips' relationship was the addition of expectation factors to the initial relationship by Friedman and Phelps (Fredman, 1968; Phelps, 1967). Phillips' goal in the late 1960s was to explain the relationship between inflation and unemployment through the behavior of prices and wages. In the 1970s, by combining the Phillips curve and expectations with the learning-by-error process, the famous hypothesis of accelerated inflation was formed, which influenced policy debates. In the 1960s, the research results of Thomas Sargent and Neil Wallace showed that monetary policy is not directly related to the production and employment trends (Sargent & Wallace, 1973). Taylor (1979) was the first person who, using dynamic optimization methods, presented an optimal monetary rule in the direction of optimal control of the amount of money, which is considered a simple instrumental rule (Taylor, 2000). Svensson and Woodford (1997) expanded the discussion of the optimal monetary rule and use an inter-period optimization process to find the optimal monetary rule (Svensson, 1997; Woodford, 2001). Galli, Clarida, Gertler and Walsh in 1999 derived the monetary rule from the minimization of a welfare loss function for the policymaker with respect to constraint functions. They found that the inflation rate is related to its lag, inflationary expectations, and excess demand, suggesting that there is a rate of unemployment that, if maintained, would correspond to a sustainable rate of inflation (Gali & Gertler, 1999; Clarida et al., 1999). Since 2019, targeted programs have been created, including the Australian Disability Strategy (2021-2031), designed to advance the employment and financial security of people with disabilities. In Latin America, Africa and Asia, employment guarantee schemes have been proposed for anti-poverty policies. In India, there is a so-called twin problem in the labor market; one of which is job loss and the other is that employees change contracts from permanent to temporary. Research methodology In this article, to calculate the optimal trend of employment in Iran, the combined approach of simulation based on stochastic dynamic optimization is used. For this purpose, a policymaker's welfare loss function of linear quadratic and inter-period type including the deviation of inflation rate and economic growth from their targeted and approved values ​​in the country's sixth plan of economic, social and cultural development, with regard to the system of dynamic and non-linear equations of Keynesian macrometrics, is minimized by stochastic dynamic programming method. The system of dynamic and stochastic macrometric equations includes behavioral equations and defining equations. These equations have been estimated using the statistical data related to the years 2017-2021 of the Central Bank of the Islamic Republic of Iran and based on the maximum available information using the ordinary least squares regression method. Research findings EViews software was used for data analysis. First, the employment process in the country was simulated by using the Gauss-Seidel algorithm, the system of dynamic and non-linear macrometric equations and the quantitative goals of the sixth development program,. Then, the optimal trend of the working population was calculated from the minimization of the welfare loss function of the policymaker by programming and implementing an open cycle algorithm and solving the Bellman equations. The results of this research showed that achieving the optimal and planned growth rate requires curbing inflation and growth with economic stability. Conclusion The obtained results showed that achieving higher employment requires controlling inflation at lower rates as well as achieving a higher economic growth rate. The findings of this research are compatible with the theory of new Keynesians such as Gerish, Clarida, Gertler, Menkiu, Walsh, and Taylor regarding the necessity of simultaneously reducing inflation and increasing production. Hence, the jump in production and curbing inflation can make possible the optimal control of employment and business at the targeted level. According to the results of the research, the following suggestions were made: Targeting macroeconomic indicators in the available (possible) territory, complete monetary and financial discipline, independence of the central bank, and the use of stochastic optimal control theory in targeting development programs are among the policy recommendations of this article.

Abstract The current research has been conducted with the aim of investigating the factors affecting the financial recovery of businesses admitted to the stock exchange. This research is an interdisciplinary study; a combination of legal and financial topics with qualitative and quantitative data. In this regard, 144 companies were studied as a statistical sample of the research in the 12-year period of 2010-2021 based on the screening process. The findings of the research showed that, in the examination of the goodness of fit indices of the model, it can be seen that, based on the McFadden coefficient of determination index, the use of predictor variables in the final model of the financial recovery of companies has been able to improve the likelihood function by 71.25%. That is, it can be concluded that the main forecasting components in the final model have been able to be effective up to 71.25% in the accuracy of detecting the financial recovery of companies. Finally, the analysis of multilayer artificial neural networks in order to evaluate the reliability of the results in diagnosing and prioritizing the financial recovery of companies shows that, therefore, considering that the tenth principal component is the most important factor in the financial recovery of companies, and citing the magnitude (absolute value) of the coefficients of each variable in the formation of this component, the order of the importance of financial variables in the financial recovery of companies and their exit from bankruptcy can be determined.
Extended Abstract                                          
Introduction
Financial helplessness refers to a situation in which the company cannot fully fulfill its obligations to financial providers, and faces difficulties in fulfilling them. Financial helplessness does not necessarily lead to bankruptcy, and a set of management measures to get out of helplessness or rehabilitation can save the company from the risk of entering the bankruptcy stage (Mherani et al, 2021). The growth and revival of the company is the result of exploiting the opportunities. In fact, a company has limited resources that it uses as necessary tools to achieve growth in facing upcoming opportunities (Hussain & Waseer, 2018). Company growth has been studied by many researchers and different terms have been used to define its stages. But most researchers agree that the growth and revitalization of the company is a process. In other words, every company is born like a child, then it starts to grow and in this way it faces various challenges and crises until it finally matures and then dissolves. In this path, there are several factors that help the company's success and allow it to move from one stage to another. Of course, there are two different thoughts among researchers in this regard; some of them believe that the company's economic growth path is linear and predictable. But some others believe that the company's growth is the result of taking advantage of opportunities and is unpredictable (Guha et al, 2013).
Manufacturing companies active in the stock market, which are considered as the main players in the economy of any country, play an important role in increasing the national income. Regardless of paying taxes to the government, companies create many job opportunities and provide them with the opportunity to pay taxes to the government by hiring and paying jobseekers. Also, companies play an important role in improving the foreign balance of the country by exporting their goods to other countries. On the other hand, bankrupt companies lose the ability to pay taxes to the government and are forced to fire their employees; which brings many social and political problems. Also, since bankrupt companies are unable to pay their loans, they create problems for lending institutions (Yan & Vedoud, 2019). Therefore, this research, referring to the concept of asset pricing models of Black and Schulz; which emphasizes on the intrinsic value of debts and assets, paying attention to the importance of bankruptcy and exit and in the continuation of rehabilitation, has examined the factors affecting financial rehabilitation of businesses accepted in the stock exchange, and in fact, the main question of the research is: what factors are effective on the financial recovery of bankrupt companies in the stock exchange?
 
Theoretical Framework
Financial rehabilitation (exit from bankruptcy)
Company rehabilitation is a process in which the weak performance status of the company changes and its performance indicators improve (Berandez & Berg, 2020). When some organizations experience a financial crisis and face challenging and deteriorating operating margins, financial revival means a significant improvement in operational margins and financial health of the organization (Ghazavi, 2018). The financial recovery of the business unit is a process based on which the weak performance status of the company is changed and the performance indicators are improved (Brandes & Brege, 2012).
 
Financial recovery strategies
The increase in the bankruptcy of business units due to the economic situation attracted the attention of researchers to this field and caused research to be found to provide a model to predict the exit from helplessness of helpless companies. With the increase in the scope of the financial crisis, managers of companies in crisis have increased their efforts to implement strategies that will save them from bankruptcy and stop their decline. In this regard, some of them use the strategy of cost reduction (Bruton & Rubanik, 2016) and asset restructuring (Sudarsanam & Lai, 2017; Hambrick & Schecter, 2014) for revival, and others consider the reorganization of the company's debts.
Dzingirai & Baporikar (2022) in a research titled "Trends and patterns in revitalization strategies" state that the most important aspect of strategic management should be the ability to respond to a world that is changing rapidly and with an increasing trend. The purpose of implementing this strategy is to take measures aimed at reducing the effects of change among organizations. As a result, it seems that the present time is the most ideal time to analyze the existing articles in this field from the perspective of bibliography. The role of revitalization strategies in strategic management articles cannot be underestimated. Three revitalization strategies, i.e. retrenchment, restructuring, and reorganization have led to the spread of articles related to the mainstream revitalization.
Ramalho & Diogo (2021) found that operational structure restructuring measures play an important role in the revitalization process of any company. In addition, this study shows that the managers of American companies during the considered time period, regardless of the effectiveness of the strategies, give more importance to financial restructuring measures.
 
Research methodology
This research is an interdisciplinary study; a combination of legal and financial topics with qualitative and quantitative data. In this regard, 144 companies were studied as a statistical sample of the research in the 12-year period of 2010-2021 based on the screening process.
 
Research findings
The findings of the research showed that, in the examination of the goodness of fit indices of the model, it can be seen that, based on the McFadden coefficient of determination index, the use of predictor variables in the final model of the financial recovery of companies has been able to improve the likelihood function by 71.25%. That is, it can be concluded that the main forecasting components in the final model have been able to be effective up to 71.25% in the accuracy of detecting the financial recovery of companies. Finally, the analysis of multilayer artificial neural networks in order to evaluate the reliability of the results in diagnosing and prioritizing the financial recovery of companies shows that, therefore, considering that the tenth principal component is the most important factor in the financial recovery of companies, and citing the magnitude (absolute value) of the coefficients of each variable in the formation of this component, the order of the importance of financial variables in the financial recovery of companies and their exit from bankruptcy can be determined.
 
Conclusion
The current research was conducted with the aim of investigating the factors affecting the financial recovery of businesses admitted to the stock exchange. The findings of the Ramalho, Diogo Miguel Pacífico (2021), Kazemzadeh & Moazami (2019), and Dzingirai & Baporikar (2022) also identified and introduced factors for the revival of companies in line with the results of this research. The artificial neural network composed of the main components in this research can correctly predict 90.9% of the bankruptcy or non-bankruptcy situations of companies, which can be confirmed by the research results of Lee (2021), Barzegar & Haedari (2017), and Wanita & Grace (2021) based on the acceptable and high power of the artificial neural network in the detection of aligned bankruptcy. Finally, for the revival of bankrupt companies in the stock exchange, suggestions for officials and legislators with regard to the research findings are presented:
- It is suggested to the Ministry of Security to make the necessary inquiries from the bankruptcy liquidation department of the provincial judiciary before issuing a license for production units that have been closed down or bankrupted, and provide the necessary background within the framework of laws and regulations for the activation of closed or semi-closed production units, with the least capital and the least cost, to activate the huge capital stagnant in them.
 

Abstract Abstract The aim of the current research is to analyze the discourse of tourism development with a justice-oriented and moderate approach. The present research method was discourse analysis and applicable in terms of purpose. The statistical sample in this research was a total of 60 texts, including all texts expressed by government managers in the tourism sector in two historical periods of governance in the Islamic Republic of Iran, with justice-oriented discourse and moderation discourse in 8-year periods. The library method was also used to collect data. The findings showed that the characteristics of traditional public administration included: applying the authority of the government over all departments, intense hierarchical structures, integrity of regulations and working procedures, separation of administration from politics, and strict controls. Also, the characteristics of modern public administration included: deregulation, privatization, adjustment of manpower, and market competition. Justice-oriented discourse management is close to modern public administration and includes features of good governance. Also, moderation discourse management is closer to modern public administration and includes features of traditional public administration. Extended Abstract Introduction Tourism is an ancient phenomenon that has existed in human societies for a long time and has gradually reached its current technical, economic and social position during different historical stages (Razvani, 2007). In addition, due to its special geographical location and the existence of its culture and customs, historical works, art and cultural heritage, Iran has definitely been considered the best destination for travelers and tourists of the ancient era (Hasanpour et al., 2012). The tourism industry in Iran was officially formed half a century ago in order to introduce the greatness of Iran and the civilization of this ancient land, and for the first time since 1314, an office was established in the Ministry of Interior called the Department of Tourism Affairs. In 1385, with the approval of the Supreme Administrative Council, the Handicrafts Organization was merged with the Cultural Heritage and Tourism Organization. According to the above, it can be generally said that the tourism industry is a nascent industry in the country, which is still at the beginning of its work (Nemati, et al., 2014). Although in recent years various political, social, economic events and even natural disasters have brought many sudden shocks to the world tourism industry, this industry has shown that it has a lot of resistance and can continue to grow despite all these conditions and make more progress every day than yesterday (Bakar & Rosbi, 2020). Since Iran has been experiencing climate change and drought in the last few years, agriculture is not in a very favorable situation, and this is where the tourism industry becomes an important issue for employment. When we pay attention to the priority of the tourism sector, we see Iran at the 117th rank, a position that shows that even though everyone knows the colorful role of the tourism industry in economic prosperity and employment, little effort is being made to grow this industry in Iran. (Research Institute of Cultural Heritage and Tourism, 2016). Based on the mentioned materials, the purpose of this research is to answer the question: what is the analysis of the discourse of tourism development with a justice-oriented approach and moderation in Iran? Theoretical Framework Justice-oriented discourse: The election of the ninth presidential term with the inauguration of the Ahmadinejad government represented a fundamental change in the country. Ahmadinejad was the head of the government of the Islamic Republic of Iran in the years 1384 to 1392. The main orientation of Ahmadinejad's positions was around topics such as justice, self-belief, religiosity, reformism, fight against corruption, centralism, fight against the welfarism and luxury of managers, paying attention to the deprived and oppressed groups and the marginalized. The discursive approach of his government is on the way to return to the foundations of the Islamic Revolution, but in practice, the populist approach of the government presents a vulgar interpretation of the ideals of the revolution. In terms of basics, the discourse of the Ahmadinejad government should be understood in its mass nature and the tendency to see things in a mass way; hence, this discourse has been introduced as the duty-oriented mass discourse (Darabi, 2009). Moderation Discourse: After winning the elections of the 11th and 12th periods from 1382 to 1400, Rouhani assumed the presidency of the government of the Islamic Republic of Iran in this period, and according to himself and his colleagues in the government, he formed the moderation discourse. Rouhani tried to instill hope and peace and win the voters' opinion by using descriptive combinations as well as hopeful terms such as Alhamdulillah and Ansha'Allah. He considered his discourse of moderation different from other previous discourses and even his election rivals. Rouhani believed that the 11th government is the government needed by the Islamic Republic of Iran because progress in the economy, prosperity of business and creation of employment in the country requires the normalization of relations with neighbors and international forums, and the government has a very high ability in foreign and international relations (Mirzaei & Rabbani Khorasghani, 2015). Tourism is an important part of economic services. According to studies by the World Tourism Organization and the World Travel and Tourism Council in 2013, the total share of travel and tourism in the global economy has increased to 9.5% of the global GDP ($7 trillion), which not only produces wider economy, but also is growing faster than other important sectors such as financial and commercial services, transportation and construction; and in total, in 2013, it created nearly 266 million jobs (Pratt & Tolkach, 2018). The participation of indigenous people in the development of tourism is one of the main criteria of social power. It is obvious that if the natives do not have a correct view of the tourism industry, they will not provide proper services to tourists or even in some cases they may consider tourists as invaders and usurpers. In these conditions, the development of the tourism industry in the region will face serious problems (Iqbal et al., 2022). The received positive effects, as a result of tourism, encourage the society to support the development of the tourism industry and especially the activity in this industry. But the perceived negative impacts prevent residents from supporting tourism development (Shokohi et al., 2012). The cultural point of view of the people of the region in the field of tourism has a significant impact on the development of the tourism industry in tourism areas. Culture is an influencing factor that must be formed and promoted bilaterally. Cultivation and cultural acceptance are two important categories in the development of the tourism industry, which must be done by both the host and the guest (Hezarjaribi & Najafi, 2011). Research methodology The current research is among the qualitative researches and seeks to analyze the discourse of government management in the tourism development sector. Discourse analysis is a new method for research in communication texts that has been used to understand the message and meaning used in communication messages. In the beginning, this method was largely indebted to linguistics (Altamirano, 2022). The statistical population of this research includes all the texts expressed by government managers in the tourism sector in two historical periods of governance in the Islamic Republic of Iran, including the justice-oriented discourse (1384 to 1392), and the moderation discourse (1392 to 1400) in 8-year periods, published in newspapers, magazines and the website of the presidency etc. The sample size of the research was a total of 60 texts that were interpreted and analyzed. Finally, with the results of the investigations, it was concluded that all 60 are basic texts. Thematic analysis method was also used to analyze the data. Research findings Based on the analysis of the texts of each of the justice-oriented and moderation-oriented discourses and the statistics of the characteristics of each, the findings showed that the characteristics of traditional public administration include: applying the authority of the government to all sectors, intense hierarchical structures, the integrity of regulations and work procedures, Separation of administration from politics, and strict controls. Also, the characteristics of modern public administration included: deregulation, privatization, adjustment of manpower and, market competition. Justice-oriented discourse management is close to modern public administration and includes features of good governance. Also, moderation discourse management is closer to modern public administration and includes features of traditional public administration. Discussion In the justice-oriented period, modal constructions of coercion and obligation are almost at the level of the reform period, which indicates the democratic management style of delegation. During this period, Mr. Ahmadinejad delegated the affairs to the managers of the tourism department, Mr. Mashai and Baghai. In this period, the definite cognitive aspects have the highest rank, which indicates the high efficiency and performance in the development of the tourism sector. It should be noted that this research is based on the texts expressed by the discourse analysis method and only the literary aspect of the discourse has been examined. For this reason, since the intervening variables have not been examined in the research, the researcher's publication believes that according to the various influential variables, the efficiency and performance in all four periods in the tourism development sector was low, but considering the improvement of the country's conditions compared to the beginning of the Islamic Revolution, the justice-oriented period had better conditions and grounds for the development of the tourism sector. In this period, modal doubtful constructions are more than the period of moderation and less than the period of construction and reforms, and this is where the inefficiency of the managers of the tourism development sector is seen, because in this period, due to the improvement of the country's conditions compared to the previous periods and the absence of Corona and the increase in oil prices, this doubt is a sign of extreme weakness of the relevant managers. In the period of moderation, non-modal constructions of compulsion and obligation are at a higher level than average and indicate the existence of command management style and pressure from top to bottom. In this period, definite cognitive constructions are less than the justice-oriented period and more from the period of construction and reforms, which can, considering the increase in the number of tourists in this period and the existence of the corona crisis, sanctions and the reduction of oil prices, etc., the performance and efficiency of the government in this field considered high or relatively acceptable. In this period, the constructions of the doubt have the lowest level compared to other periods, and this indicates the sufficient knowledge and expertise of the government managers of the tourism sector. In this period of doubtful cognitive constructions are more than the justice-oriented period and less than the period of construction and reforms, which indicates an average level of transparency of government affairs in the tourism development sector in this period. Looking at the data in the table, it can be said that almost the level of expertise of the managers of all four periods is in the average level and it has affected the efficiency and effectiveness.