کیامرث فتحی هفشجانی

The purpose of this research is the relationship between the factors affecting the development of industrial startups using fuzzy cognitive mapping methodology. According to its purpose, the research method is applicable, and in terms of implementation, it is …. The statistical population of the research includes 19 professional experts in industrial startups, including senior managers and their collections, and the sampling was done in a targeted manner, and the interviews continued until reaching theoretical saturation. The data collection tool is a semi-structured interview. To collect data, fuzzy Delphi technique was used to identify the components, and fuzzy cognitive mapping method was used to present the model. The results of the analysis showed that the main factors affecting the development of industrial startups include eleven variables: development competencies, human resources competencies, the organization's needs for development, attracting and retaining elites, startup brand, creating suitable opportunities, the development of elite skills, economic conditions, customer satisfaction, startup progress, and development culture. Then using the methodology of fuzzy cognitive maps, the way of relationship between these factors was explained accordingly.

The increasing use of information technology in financial and banking services continues, and the challenge of better managing information technology projects to maximize their economic benefits remains unresolved. Therefore, this study aimed to identify and prioritize the criteria for selecting the optimal portfolio of information technology projects in Iran’s banking industry using both quantitative and qualitative methods. For this purpose, the research sample included experts (university professors and senior managers in the information technology management sector of the banking industry), selected through the snowball sampling method (n=12). In addition, for data analysis, first, the final criteria of the model were determined using the fuzzy Delphi technique, and then the criteria were prioritized using the DEMATEL technique. The results of the fuzzy Delphi technique indicated that the criteria for selecting the portfolio of information technology projects in Iran’s banking industry consist of 5 main criteria (organizational, environmental, economic, technical, and risk-related) and 18 sub-criteria. The results of the DEMATEL technique further revealed that among the main criteria, the risk criterion, and among the sub-criteria, low security risk, hold the highest importance.

 

 

With the emergence of Industry 4, the world is increasingly considered as a volatile, uncertain, complex and ambiguous environment, and leaders must be agile and ready to lead the digital transformation of their organization. The purpose of this article is to present the development model of the agility of production processes with the approach of industry 4 intelligence and its effects in the economy.

This article is applied and part of mixed research (qualitative-quantitative). The tools of data collection were interviews and researcher-made questionnaires. The validity and reliability of the questionnaire was confirmed.

Ethical Considerations: 

In this article, the originality of the text, honesty and trustworthiness are observed.

The results led to the identification of 30 components and 119 indicators, with employees, supply chain, production and smart products as the main category; Internet of things, big data and data analysis as causal conditions; Competency of employees, flexibility of employees, knowledge management of employees and intelligence and awareness of employees are also background conditions; Mandatory, normative and imitative stimuli as intervention conditions; Employee empowerment, downsizing and integration and strategy based on information technology as strategies; Variables of process performance, economic performance, gaining competitive advantage and agility and flexibility were considered as outcomes.

The agility of the food industry will lead to the development of production and economic growth of the country.

The present study aims to identify the most important variables affecting the fluctuations of gold prices. It is the first Iranian research in which the fluctuations in this market are modeled using non-linear Bayesian Model Averaging (BMA) and deep neural network approaches.

It is applied research where monthly data collected from 2010 to 2022 were used. It evaluates 35 factors playing a role in gold price fluctuations. GARCH and random fluctuation models are used to extract gold price fluctuations. TVPDMA, TVPDMS, and BMA models are used to identify the most important variables causing gold price fluctuations. Furthermore, the deep learning approach is used to investigate how effective the selected variables are in gold price fluctuations.

The results indicated that Support Vector (SV) models were more accurate than GARCH models in capturing fluctuations and that BMA outperformed TVPDMA and TVPDMS. Additionally, 12 variables were identified as influential in gold price fluctuations, with in-market factors playing a more significant role than out-of-market factors. The study also employed Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Multi-Layer Perceptron (MLP) neural network models in deep learning mode to predict gold price fluctuations. It was concluded that global interest rates had the most significant impact on fluctuations in the gold price, with the Pivot Point DeMark's Index making the greatest contribution.

Originality/Value: 

The gold market is known for its volatility, and accurate predictions about its future can significantly impact decision-making. Understanding the gold price and making correct forecasts can help inform decisions about buying and selling gold in global markets, and determine the most favorable times for transactions and investments. Therefore, it is crucial to accurately predict the gold price from various perspectives. This research attempted to develop an intelligent model for forecasting fluctuations in the gold price.

In today's world, many decision-making problems are uncertain. The main source of these conditions is the lack and sometimes the absence of information for decision-making, which makes it one of the most challenging and at the same time the most important issues in supply chain management. Therefore, the present study aims to provide a Bi-objective mathematical model of a sustainable supply chain based on uncertain parameters, with a focus on minimizing costs and environmental pollutants. The proposed model can be an efficient tool for designing a sustainable and flexible supply chain network.

This research is descriptive-analytical. Furthermore, in terms of its objectives, it is considered an applied type of research. This study developed the Malvey scenario-based method, focusing on the parameters of the two-objective mathematical model, while considering shipping costs, demand, and capacity reduction due to disruptions as uncertainty parameters. In study utilized software tools GAMS, Excel, and Microsoft Visio for data analysis.

The results indicate that using the mathematical model based on the Malvey scenario in uncertain conditions in a sustainable supply chain can lead to achieving favorable and fruitful results. The mathematical model was able to effectively address demand uncertainty, shipping costs, and capacity reduction due to disruptions, although its performance decreased in scenarios with larger aggregates.

The aim of this study is to analyze the factors influencing the financing of renewable energy projects to achieve sustainable development goals using a fuzzy cognitive map approach.

This applied research was conducted in both qualitative and quantitative sections. In the qualitative section, content analysis with a conventional and directed approach was employed, and in the quantitative section, a causal method was used. Data were collected through semi-structured interviews in the qualitative phase and pairwise comparison questionnaires in the quantitative phase. The participants were senior managers and experts from the Renewable Energy and Energy Efficiency Organization (SATBA), selected using purposive and theoretical sampling (a total of 21 participants).

The qualitative findings revealed key influencing factors, including "social responsibility," "direct and indirect government support," "sustainable economic development," "environmental sustainability," "support from financial funds," "commercial creditworthiness of financial suppliers," "foresight and capital planning," "financial capacities," "investment return policies," "empowerment of financial institutions," "renewable energy development policies," "investment culture in renewable energy," and "optimal management of investment risks." The fuzzy cognitive map results showed that "direct and indirect government support for the energy industry" had the highest output and influence, while "commercial creditworthiness of financial suppliers" had the highest input power and susceptibility to influence.

This study provides a comprehensive analysis of the factors affecting the financing of renewable energy projects. It highlights the critical roles of government support policies and the commercial creditworthiness of financial suppliers in the success of these projects, suggesting that improvements in these areas can contribute to achieving sustainable development goals.

In recent years, the rapid development of knowledge-based organizations and companies and the need to pay attention to all kinds of threats, attacks are considered as the most important factor in their development. Therefore, the survival of these organizations depends on the principle of leveling all types of threats and presenting a comprehensive conceptual model in these organizations. The main purpose of the research is to present a conceptual model of the leveling of various threats in the security and cyber defense of knowledge-based organizations in the country. The methodology of the above research is based on the type of research to provide a conceptual model, it has a practical aspect, according to the purpose, it is of a developmental-applicative type, considering the dimensions of the research that It deals with theoretical, functional and operational areas. This research is divided in terms of purpose (type of research in the    category of applied-developmental research and in terms of research approach in the category of mixed quantitative and qualitative research). In the qualitative section, by referring to articles, books and  research reports, upstream documents using the metacomposition method, dimensions, components and indicators of the conceptual model of leveling various types of cyber threats in cyber security and defense in knowledge-based organizations, the extraction and qualitative control of findings was carried out, based on the findings of the model An initial concept was formed and after evaluation with scientific methods and based on structural equation modeling, the proposed validation framework and the final conceptual model were presented. To identify the dimensions and components of the model by studying previous researches, theoretical literature as well as interviews with specialists and experts in this field, the dimensions and  components were extracted, then to validate the dimensions and components from the survey method (a field from the statistical population of experts, experts) with tools The questionnaire was asked. After      performing valid tests (factor analysis test), the dimensions and components of the model were confirmed. The results of the research findings showed that all the considered factors for each of the components have a factor load greater than 0.4; Therefore, they load well on the relevant dimensions, or in other words, the components of the subset of dimensions are related and form part of the model structures; Therefore, the components are interdependent with the dimensions and have a meaningful relationship. The presented conceptual model explained well the relationship between dimensions, components, and variables in order to stratify the types of threats in security and cyber defense of knowledge-based organizations. The  calculation and analysis of the fit indices with the software Smart-PLS(4) also confirmed the conformity of the conceptual framework and the experimental background with the reality.

Since supply chain risks are intertwined, a resilient approach to reduce risk can moderate supply chain risks. The current research was conducted with the aim of determining the causal and structural relationships between the factors influencing the supply chain risk management based on resilience using a mixed (qualitative-quantitative) approach. For this purpose, we used the multi-grounded theory method to identify the influencing factors, the interpretive structural modeling method to determine the relationships, and the structural equation modeling method to test the significance of the relationships. In the first part, the relationships between the influential factors were identified with the judgment of 17 experts and a structural interpretative model was obtained.then, with the data obtained from the number of 350 managers and experts of Iran's National Oil Products Distribution Company, the validity of the relationships determined in the ISM model was evaluated using the SEM method.the findings showed that supply chain risks, while influencing each other, affect resilience factors in the second level of the model. Therefore, resilience factors are affected by risks and react to control them, and this issue can lead to the achievement of supply chain risk management goals at the first level of the model.

 Today, the most important issue is the cyberspace challenge in intelligence-oriented organizations, the increase in cyber damages, threats and cyberspace security issues. The main goal of the research is to explain the relationship and effectiveness of the cyber security and defense components of small and medium-sized intelligence-oriented organizations in the country.

 The research method is structural-functional in terms of descriptive-survey data collection method according to the practical purpose. The statistical population of the research is managers, experts, security officials and… organizations. The obtained sample size was 157, only 88 of these organizations agreed to participate in the research. Interviews with experts, library sources, articles, and questionnaire tools were used to collect data and to measure validity, form-content validity and Cronbach's alpha coefficient were used for reliability, and SPSS software (25) was used to analyze data and test hypotheses. In the descriptive statistics section, dispersion indices were used, and in the inferential statistics section, Kolmogorov-Smirnov tests were used to evaluate the normality of the data, and Pearson's correlation coefficient was used to check the relationship between the variables.

 The analysis of the research data showed that there is a significant relationship between the research factors and components; Also, acceptable correlation between the variables; There is a security policy, organizational security, etc. The relationship between the variables and effective scales of the research has been measured. The results in the first part showed the components of cyber security and defense; Security policy, asset classification and management, etc. have a meaningful relationship and have a direct impact on the performance of all intelligence-oriented organizations. After reviewing the results, it was determined that the relationship between components such as employee security, physical security, and scales such as the year of organization, annual transaction, etc., has a direct effect on improving the security and cyber defense of these organizations; It was also found that there is no relationship between variables such as the number of security staff and security policy, and the relationship between the variables of security staff and system maintenance and support is in the opposite direction; Therefore, this issue reduces the productivity of security department employees in information-oriented organizations

The spread of attacks and various threats in the cyber space in data-oriented and knowledge-based organizations has caused attention to the issue of cyber security and defense in knowledge-based organizations as very important and strategic issue. This issue requires the explanation of comprehensive roadmap to achieve the goals through the optimal performance of the organization's main processes. The present research deals with the structured analysis of the safety index in security and cyber defense of knowledge-based organizations.After determining the sub-indicators and main influencing factors using scientific methods (Delphi method),their importance was determined by experts. Effective components are combination of security and cyber defense components.The existence of various threats and conditions in the country caused three knowledge-based organizations, "Islamic Azad University,South Tehran Branch, University Research Sciences Unit,and University of Tehran, which they are important in terms of strategic and cyber issues, to be studied. The importance of the influencing factors With the opinions of determined experts, the geometric mean was obtained, and after weighting the components, all values were normalized, using the evolutionary algorithm of Prometheus as one of the new decision-making methods,intra-group comparison of the components was carried out, and then the priority It was done based on the type of intergroup security and cyber defense components. The organizations were ranked based on priority and the amount of points and it was decided to increase the level of security and cyber defense within the organization in accordance with the strategic principles to achieve maximum security and efficiency of the system.

Project financing has emerged as a critical mechanism for funding infrastructure and capital-intensive projects across various sectors, both in the public and private domains. Its significance has grown notably in recent decades within the financial market, reflecting its pivotal role in facilitating economic development. Notably, in developing countries, the establishment of robust economic infrastructure is a pressing priority, serving as a cornerstone for overall growth and advancement across multiple economic sectors. However, the insufficient attention given to meeting financing requirements in this domain poses substantial challenges to economic progress. Diving deeper into the realm of project financing, one finds a diverse array of financing mechanisms, each characterized by its unique set of risks and complex capital structures. These risks, if not effectively managed, can exert considerable influence on project outcomes, impacting crucial objectives such as project timelines, cost management, safety protocols, quality standards, and long-term sustainability goals. Understanding these risk factors and their interplay is paramount for stakeholders involved in project financing endeavors.
 
To explore these dynamics, this study employs an objective-oriented approach, leveraging a descriptive-correlational method for data collection. Central to this methodology is the utilization of Structural Equation Modeling (SEM), a powerful analytical tool that allows for the examination of complex relationships among variables. The study's statistical population comprises a diverse range of professionals, including experts, senior experts, supervisors, and managers from mining companies within the country under study. From this pool, a sample of 220 individuals was randomly selected to ensure robustness and representativeness in the analysis.
 
The study's findings shed light on the intricate relationships between various factors and project financing risk. Notably, the analysis unveils the significant impact of financing methods on political risk, with an observed effect intensity of 0.462 and a probability statistic of 0.686. This surpasses the critical t-value at the 5% error level, underscoring the statistically significant influence of financing methods on political risk. This underscores the importance of considering the choice of financing mechanisms in mitigating or exacerbating political risk factors, thereby enhancing the overall risk management strategy of project financing endeavors. Moreover, the study delves into the relationship between customer and management risks. While the overall effect of customer risk on management risk was determined to be 0.046, the calculated significance value of 0.851 fell below the critical t-value at the 5% error level. This indicates a lack of significant observed effect, suggesting that customer risk may not exert a substantial impact on management risk. Nevertheless, understanding these nuanced relationships contributes to a more comprehensive understanding of the multifaceted nature of project financing risk. Beyond these specific findings, the study highlights a myriad of factors that influence project financing risk, including social risk, contractor risk, construction risk, design risk, legal risk, financial risk, and subsidiary contracts, among others. Each of these factors contributes to the overall risk profile of project financing endeavors, necessitating a holistic approach to risk management and mitigation strategies.
 
In conclusion, the study underscores the critical importance of focusing on project organization and management capability, particularly in the context of developing countries. Inadequacies in these areas often result in suboptimal utilization of resources and capital, leading to delays in project commencement, implementation, and operation, ultimately yielding uneconomical outcomes. In light of the prevalent project-oriented approach adopted by organizations, there exists a heightened imperative to design and enhance project organizations to effectively navigate the complexities of project financing endeavors and achieve desired outcomes.

Commodity smuggling is a complex phenomenon with multiple dimensions, which is related to the hidden and underground economy on the one hand, and to social order, cultures, and attitudes on the other hand. In the conditions of the spread of Covid-19 as a global crisis, the complexity of the situation of goods smuggling has increased. Getting out of the situation of smuggling as an economic disease and a critical situation that is considered as one of the country's development challenges, requires coordinated and integrated measures, and the approach of integrated marketing communications can be used to deal with such challenges. Therefore, planning a systematic way out of commodity smuggling with the integrated marketing communication management approach (case study: Covid-19  outbreak crisis) was proposed for the first time.The present exploratory research was presented through semi-structured interviews of 12 experts and using the database theory and the Delphi method, conceptual model and appropriate theory, extracting 18 categories and 82 sub-components, content validity (0.71), retest reliability (77%), and reliability two coders (65%) were evaluated favorably and practical suggestions were presented by documenting organizational knowledge.It seems that in the crisis of the Covid-19 outbreak, planning through the management of integrated marketing communications can be used to prevent and get out of the situation of smuggling of goods towards the health of the business environment and economic development.Therefore, planning a systematic way out of commodity smuggling with the integrated marketing communication management approach (case study: Corona outbreak crisis) was proposed for the first time.The present exploratory research was presented through semi-structured interviews of 12 experts and using the data base theory and the Delphi method, conceptual model and appropriate theory, while extracting 18 categories and 82 sub-components, content validity (0.71), retest reliability (77%) and reliability Two coders (65%) were evaluated favorably and practical suggestions were presented by documenting organizational knowledge.Among the categories, "supporting legal trade while modifying and completing the business model" and "supporting production while modifying and completing the production and employment model" had the highest frequency. It seems that in the crisis of corona outbreak, planning through the management of integrated marketing communications can be used to prevent and get out of the situation of smuggling of goods towards the health of the business environment and economic development.

There is a kind of supply chain services that the products are not considered as a commodity, and a combination of products and service or only service is exchanged in these chains. Despite the importance of these supply chains, the research literature is not very rich and the need for further strengthening in this area is quite evident. Hospital service supply chains are also the type of service supply chains that should be taken into consideration. The aim of the current research was to optimize the supply chain of hospital services. For this purpose, library studies were first conducted and the research gap was extracted. Then, a multi-objective mathematical planning model was designed based on research innovation and its assumptions, the first objective was to minimize the cost, the second objective was to minimize the unrealized demand, and the third objective was to maximize the commitment of suppliers. After the solution, the model was validated based on fast-moving and non-moving goods, and the results showed that the parameters of the model all lead to a worsening of the solution, causing an increase in cost and unfulfilled demand and a decrease in employee commitment. But the goal of employee commitment has changed more than other goals due to the increase in parameters, and sometimes this commitment is reduced by 70%. The parameter of demand for fast-moving consumer goods has the greatest effect on cost and unrealized demand.

The government in Iran, similar to other developing countries after the Second World War, considered itself responsible for eliminating the backwardness of the country and tried to eliminate it by designing development plans and implementing construction projects. The huge volume of half-finished construction projects is one of the realities of public sector management in the country. Parliamentarians consider the approval of the public-private partnership bill as a solution to half-finished plans. This research, conducted in a qualitative method, tries to answer two questions by analyzing the opinions of experts: first, can all half-finished projects be transferred, and second, what are the methods of economization of projects for transfer? In this article, the text of the interviews has been coded with open coding software. The analysis results are that there is no general solution for all plans, and in each case according to the background conditions (classification of unfinished plans, the possibility of their economization, etc.), causal conditions (control of the plan's approval), intervention conditions (use of capacities transfer laws, the entry of the privatization organization into this issue, etc.), strategies (preparation of legal prerequisites, preparation of regulations, etc.) and consequences (creating incentives for project managers by creating a method of returning saved resources, etc.) a convenient method for economization and transfer should be designed.

Supply chain management is a modern organizational management mode that organizes and plans information, capital flow, and business partnerships in the supply chain and requires complete business and market information (Quinn et al., 2012). However, the cost of acquiring supply chain companies and product information by traditional methods is very high. Information technology provides the power for companies to implement supply chain management and share the supply chain easily, and all companies in the supply chain can create value through information management (Shawaki et al., 2023). The utilization of intelligent approaches to predict prices and demand quantities enhances supplier delivery performance. It also refines demand forecasting accuracy, improves factory planning precision, forecasts demand for new products, and minimizes supplier risks, transportation costs, inventory, operational expenses, and time (Tirklai et al., 2021). In supply chain management, accurate forecasting of demand reflects the price. It is a critical issue that can reduce inventory costs and achieve the desired service level (Zouqaq et al., 2020). Intelligent supply chain pricing approaches can help supply chain companies to adapt the quality of their product offerings in supply chain management according to the knowledge gained (Kotsiopoulos et al., 2021). Identifying and modeling steel market fluctuations is very important in the steel industry and supply chain management. Considering the vertical chain in this industry and the interaction between the players of this industry, game theory has been used to model the optimal price. Neural network models were employed to replicate the game, as interaction and repeated gameplay are required for achieving balance among players. Taking into account Iran's unique circumstances, notably its confrontations with substantial sanctions in the metal industry, the sanctions variable was integrated as an adjusting factor in the pricing model for this sector.

This is a practical study. The research time frame for predicting steel prices and calculating the sanctions index spans from 2011 to 2020, with quarterly data. The MATLAB software was used.

Three Bayesian neural networks, support vectors, and Grassberg's anti-diffusion were used to predict the price of steel. The results showed that the Grossberg anti-diffusion model is more accurate in predicting steel prices. Next, the predicted price entered the game theory process and the Nash equilibrium point of the model was determined. According to the country's specific conditions, the sanctions variable was introduced in the game theory model. The results showed that the inclusion of sanctions in the model led to price increases and production reductions within the steel industry. The present study delved into price fluctuations resulting from shifts in supply and demand, particularly in the context of sanctions. The findings reveal that a reduction in supply coupled with escalated sanctions led to substantial price hikes, surpassing the impact of supply changes. Consequently, steel exhibits a heightened susceptibility to input constraints, where any disruption in its supply chain triggers significant price spikes, thus unsettling the market. This amplifies the sensitivity of supply chain management for steel. Consequently, a systemic and dynamic approach is essential for market regulation policies, raw material supply, transportation strategies, and warehousing considerations. It should be noted that the use of intelligent approaches and machine learning can play a significant role in coordinating such issues.

Considering that Stackelberg's approach was used in the current research, the sequence of players' entry into the game holds significance with respect to the Nash equilibrium. The development of market entry monitoring rules and regulations in this industry should be investigated because the steel industry is one of the industries that face high entry and exit costs. As a result, Policymakers and industry managers should monitor the entry and exit of players within this sector. They should endeavor to establish norms and regulations governing interactions among market participants to foster a structured and well-defined competitive environment.

The importance of mass biology has increased due to pollution caused by biomass burial, the profitability of biomass energy, and the demand for energy in the supply chain network. The goal of this research is to design a model for the biomass supply chain network with an economic and ecological approach to reduce costs and carbon emissions. Research gaps have been addressed, which include determining desired and undesired process outputs, along with simultaneously examining material supply disruptions and final product demand. The mathematical model used is a mixed-integer linear programming model. The primary objective is to minimize costs, and the secondary objective is to minimize carbon emissions. To address this in a single-target function under uncertainty, the fuzzy TH mathematical model has been employed. Uncertainty and disruptions have been studied through scenario building. The model's validation includes a case study in Fars province, where the findings justify the construction of four power plants. The proposed model improved the accuracy of electricity production predictions by 2.1 percent. An analysis and sensitivity study was performed on the TH method's parameters and changes in customer demand values according to predictions. The results show that the proposed model performs well, achieving cost-effectiveness through the integration of economic and ecological approaches. It also successfully reduces greenhouse gas emissions, enhances energy security and stability, and demonstrates a positive impact.

he technology roadmap is one of the most effective approaches to align the organization's strategies with planning in the field of technology, from a strategic point of view and its integration with the new technologies of the fourth industrial revolution, the technology roadmap of the fourth industrial revolution leads organizations to new smart and digital technologies in order to achieve the organization's goals. And it leads to increase in productivity in production. This research aims to analyze the effective smart and digital factors of the fourth industrial revolution with a strategic management approach in developing a technology roadmap for power equipment manufacturing and energy supply industries.This research aims to analyze the effective factors of the fourth industrial revolution on the development of a technology roadmap for power plant equipment manufacturing and energy supply industries.In this regard, first by using the literature and interviews with a number of relevant experts in the power plant equipment manufacturing and energy supply industries, several factors were extracted, and then the factors were finalized using the fuzzy Delphi method and ranked using the TOPSIS technique. The results show that the criterion of intelligent design and production has the highest rank, and the component of defining and balancing the research and development portfolio has the first rank, the technology evaluation component has the second rank, and the market changes evaluation component has the third rank.

During project management, certain risks need to be effectively mitigated. While risks are an inevitable part of every project, their perception, analysis, and management help organizations achieve goals. Risk management is now an important part of project management and has a specific function for improving the efficiency of implementing the project, saving prices, and improving the profitability of projects. Theories have demonstrated risk management as an influential and scientific management instrument to decrease risk levels. Accordingly, investigating the new methods of eliminating financial risk and financial risk management of projects is necessary to develop and improve risk management.
 
In this study, the related models and variables were introduced to identify the factors influencing project financing risk. Subsequently, general criteria were derived from the examined models and their associated variables. The study samples were drawn from experts and professionals within Iranian mining companies who had direct involvement in the subject matter. Variables were identified using the content analysis method, which involved utilizing MAXQDA software for theoretical and qualitative data analysis.
 
Financing methods, social risk, contractor risk, construction risk, political risk, design risk, legal risk, financial risk, management risk, customer risk, and sub-contracts are the categories governing the current research. Each item is composed of one or several concepts that represent “features,” “conditions,” and the current or desirable “situation” of the item in the country. Another important point is the synchronicity of “description” and “prescription” in secondary or pivotal items of the research. It means that the constituted items not only represent the descriptive meaning that reflects the description of the current or the desirable situation but also represent the prescriptive meaning. The highest-ranking item is "financing methods," with 99 allocated codes. Following that is "financial risk" in the second rank, with 86 codes, and "management risk" secures the third rank with 26 codes. Ultimately, the categorized items can be approached through a model. Therefore, one of the most important results of the country's economic enterprise challenges is the lack of proper modeling for the financing method. A specific model should be created for financing, based on the risk and return of financing. In addition, it should be noted that the structure used to finance the project in one country may not be effective due to the differences in its laws and conditions, while it is used effectively in another country. according to the conditions of each project and the host country of the project.
 
In this study, the influential items or factors affecting project financing risk are investigated. The results of the study showed that financing methods, social risks, contractor risks, construction risks, political risks, designing risks, legal risks, financial risks, management risks, customer risks, and secondary contracts have influential impacts on project financing risk. After project formation and establishment, project financing emerges as a key determinant. Effectively managing a project to successfully achieve its goals within defined time, cost, and quality parameters demands a holistic understanding of the project's stakeholders and its environmental context. Contract frameworks dictate how foreign companies can leverage their financial capabilities to execute operations within different countries.

Pollution due to biomass burial, the possibility of producing clean energy from biomass and the high demand for ‎energy have made the optimization of the biomass supply chain network important and necessary. The purpose of ‎this article is to optimize biomass supply chain network at four levels in order to reduce economic and ‎environmental costs. The most important gap in research, resolved in this article, is the determination of the ‎desirable and undesirable outputs of the masses in the centers. Separating and considering the multi-period, multi-‎product mode with heterogeneous transport means. The research model is a two-objective linear programming of a ‎correct number mixed with uncertainty and disturbance, four scenarios were designed for this purpose. The model ‎was solved with genetic algorithm and MOPSO method and with Python software. Validation of the model was ‎investigated in a real case study in Fars province has been The proposed model has been able to implement ‎sustainability and resilience at the same time, which has reduced costs, reduced carbon emissions, and increased the ‎commercialization of energy production from biomass, thus increasing the willingness of investors to invest in this ‎network. It is supplied from the supply chain. The proposed model makes the amount of energy production 2.1% ‎lower than when the favorable and unfavorable outputs are not considered, which means it is much closer to reality. ‎By performing sensitivity analysis on real data, the efficiency of the model was proved

The present research has analyzed the dynamic risks of the stability of the supply chain of banking services using social network analysis (SNA) and system dynamics (SD) in order to policy the stability of the supply chain of banking services. According to the results of SNA; Corruption risks of receiving facilities, customer dissatisfaction, shareholder dissatisfaction, bank service costs, the cost of establishing a new bank branch, demand for facilities, payment claims to customers and the bank's supervisory weakness as critical risks and risks of paper waste, urban traffic, cyber security, supervisory weakness and Lack of human resources were identified as the most causal risks . Next, the SD model was designed based on the interactions of critical risks and its effects on the stability of the supply chain of banking services using the data of Iran's Mehr Bank. According to the sensitivity analysis, the sustainability policies of the bank service supply chain, including financial, social and environmental sustainability, were identified and the results were compared and analyzed, finally, the selected combined policies included:1-Managing 5% reduction in bank costs through agility processes and expenditure monitoring; 2-Increasing the efficiency of the validation process by 4 times; 3-Increasing the fee income of banking services by increasing the allocation 3 times to the development of electronic banking infrastructure; 4-Implementation of employee empowerment training programs;5-Proportionalization of the number of employees; 6-Increasing electronic services in order to increase access to the bank; 7-Appropriate location of branches and ATMs; 8-Awareness and promotion of electronic services were provided

Fourth industrial revolution is rapidly changing technology, industry and patterns through increased communications and intelligent automation in the current century. It is crucial to conduct thorough research to determine the importance of dimensions and indicators in assessing the preparedness of Iran's industries for sustainability in Industry 4.0. The goal of this paper is to identify and determine the importance of the influential components on the organization's readiness to move towards the fourth-generation industry. This model should help the organizations and industries understand their industry 4.0 readiness status. In qualitative part of the study, we categorized the data to produce the initial codes, themes and axial codes by examining the theoretical foundations and receiving experts' comments. The result was extracting 60 initial codes and 6 themes. We then used the fuzzy Delphi method on the result of the poll. Experts unanimously voted in favor of 17 sub-criteria. Finally, we used fuzzy DEMATEL method to study the relationships between criteria and sub-criteria. According to this study, ‘functional readiness’ was the most effectible and ‘information technology readiness’ was the most affecting criteria. Among sub-criteria, ‘governmental and institutional laws’ and ‘workplace dynamics’ were identified as the most effectible cause and most affecting effect respectively.

This article seeks to provide a flexible structure for the learning organization tailored to the conditions of Iranian schools. Using this structure, schools, as an educational organization, facilitate innovation and effectiveness in the face of an ever-changing environment. Also, teaching human values and principles of education help students become people who live in a healthy and civilized way in a world rich in future technologies.

This paper uses multi-criteria decision-making methods and fuzzy techniques such as fuzzy Delphi and DEMATEL and ANP techniques to provide an executive and operational framework in school learning organizations.

The results show the structures of the learning organization, the skills of the learning organization, and the technologies of the learning organization as the main criteria of the learning organization in Iranian schools, respectively. Also, reinforcing leadership sub-criteria, knowledge management technology, personal abilities, and subjective models with the nature of cause play a crucial role in forming learning organizations in schools.

Originality/Value:

 Researchers have identified the way for Iran to achieve the economic goals envisaged in the Iran Vision 2025 document, the transformation of Iranian organizations into learning organizations. However, the study of databases such as Irandak, scientific information of Jihad Daneshgahi, and the citation database of sciences of the Islamic world shows that limited efforts have been made in this direction, especially in schools in Iran. Without focusing on why and what the learning organization is, this article, using the dimensions and criteria introduced for the learning organization, points out how to provide a flexible structure for the learning organization appropriate to the conditions of Iranian schools.

One of the country's issues in the renewable energy sector for sustainable development is their financing. The current research was carried out with the aim of deeply understanding the dimensions, components and indicators of renewable energy financing and explaining the causal relationships between them in order to design a suitable model using a mixed (qualitative-quantitative) approach. In the qualitative part, the dimensions, components, and indicators were identified through semi-structured interviews and extracted using content analysis and coding techniques. then, in the quantitative part, the extracted dimensions were confirmed by the fuzzy Delphi method and the model was designed by the comprehensive structural-interpretive modeling method. The research community consists of 21 experts, including managers and senior experts in the field of renewable energy, who were selected by targeted non-probability sampling and snowball technique. The findings of the qualitative section showed that the model has 13 dimensions with 39 components and 82 indicators. In the quantitative part, the findings showed that the model has seven levels in such a way that "direct and indirect support of the government to the energy industry" dimension are the most effective in improving the financing of renewable energy.

One of the challenges faced by the steel industry is supply chain management. Based on this, inthe present research, based on the three scenarios of non-cooperation and simultaneousmovement (Cournot), non-cooperation and sequential movement (Stackelberg) and cooperativebehavior (collusion) will be discussed in the steel supply chain.The research method is applied in terms of purpose. The research period is seasonal data from2011 to 2020 and the software used MATLAB softwareIn this paper, a hybrid model based on artificial neural networks and game theory was presentedto help steel industry activists in determining the price level and optimal production. To predictsteel prices, three Bayesian neural networks, support vectors and cross-emission anti-emissionwere used. The results indicate that the cross-emission model of Grossberg is more accurate inpredicting steel prices. Also, the results show that by moving from the Cournot game to theStackelberg game and from the Stackelberg game to the Collusion game In the supply chain, itwill increase the price in the steel industry by 6 dollars per ton and the amount of product supplywill be in the range of 1500 to 4000 tons In other words, with the increase in the level ofcollusion in the steel market, more products have been offered in the market and at the sametime, the price level of the product will also increase, which will reduce the welfare of steelconsumers in the market.

In this research, by studying the research background and using the latest version of SCOR model and experts' opinion, while identifying the factors affecting supply chain stability and determining the weight of each factor by IVHF-DANP method, the priority of SSCM rings has been determined using EHFL-VIKOR method in cement industry with the aim of improving supply chain performance. Consequently, in addition to six criteria of SCOR model and three dimensions of sustainability approach, ten other factors have been determined by experts and in total, the weight of nineteen factors has been determined and the customer's interest ring has the most preference. Then, the relevant mathematical model was presented and solved in GAMS software using NSGA-II method in MATLAB software. The combined integrated model of sustainable supply chain has been dealt with in this research since the whole supply chain -from the primary supplier to the final customer- is considered in forming and solving the model and each of the objective functions has been realized by assigning the characteristics of the SCOR model to the three dimensions of the sustainability approach formed accordingly.