محمدرضا معتدل

Considering the extent of oil and gas industries and the effective role of these industries in causing environmental pollution, it is necessary to formulate a strategic plan for managing the performance of environmental improvement. In this article, the formulation of the performance management system and environmental improvement by presenting the best combination of oil and gas holding strategy based on BSC, fuzzy AHP, game theory, and in fact the purpose of this article is to present a model that utilizes the capabilities of The goals of the balanced scorecard landscape and game theory are to allow organizational planners to make changes due to economic, political and critical policies in their organization's strategic and executive planning.

considering that this researcher investigates a scientific problem using the theoretical and fundamental research of others to apply it in the real world, therefore, the current research is qualitative and practical in terms of purpose. In terms of the nature of data collection, it is also a case study and falls within the scope of descriptive research. The statistical population of this research is all senior managers of Nagar Sanat Petrochemical Oil and Gas Holding and CEOs of its subsidiaries. After determining the key objectives of evaluating the performance of balanced scorecard landscapes based on previous research literature, the fuzzy AHP method, the Likert spectrum tool and also determining the map of related objectives in each landscape, the proposed strategies and different combinations of its different aspects are available to a working group 5. Some of the experts of oil, gas and petrochemical holdings have been appointed and based on their valuable experiences in that industry and on the basis of the final strategy map and beta coefficients of the path obtained in the estimation of the model, the amount of usefulness resulting from the implementation of each strategy and the combination of several strategies numerically assigned between 0 and 5.

Based on the possible results of each strategy proposal in the landscape of the balanced score card and the application of the theory of cooperative games and the Shepley value obtained for the players, the order of their strength and sensitivity in coalitions is obtained as C>L>I>F, the best strategy combination with The highest coefficient of desirability in order to achieve the ultimate goals of the organization reached the combination of the C3L3I2F2 strategy, which is the customer perspective (focusing on the methods of obtaining customer satisfaction), the growth and learning perspective (focusing on acquiring knowledge in the field of improving activities through increasing the technical knowledge of specialists) and the internal process perspective. The establishment of order management systems in order to increase the efficiency of ordering processes (internal process) (planning to increase revenues by reducing overhead costs) showed the best benefit. Among the goals identified from the customer's point of view in this research is penetration in new markets, which has the most direct effect on increasing revenue with a beta coefficient of 0.774.

The environmental performance management system is a part of a management system that includes the required structure, planning, activities, responsibilities, methods, processes and resources for the purpose of developing, implementing, reviewing and maintaining the policy. environment are used.

The purpose of customer relationship management is to develop profitable customer relationships and increase company value. Based on this, this research identifies factors affecting competitive advantage. The current research is applied in terms of purpose and in terms of survey method with model development approach. The time frame of the research is five years (2016-2016). For this purpose, information on the indices of 33 factors affecting competitive advantage in Tejarat Bank were entered into Bayesian averaging models (BMA), (TVP-DMA) and (TVP -DMS) Based on the error rate, the BMA model had the highest accuracy. After estimating the model, 8 main variables were identified. which includes the long-term account balance; the amount of use of mobile bank; the amount of internet bank usage; real customers; legal clients; special or normality of the customer; The type of job and education. In the next step, customers are entered into the LRFM model and categorized based on these variables, finally, the effect of non-fragile variables in the Markov switching model on profitability was analyzed. The results indicated that the majority of the variables have a positive and significant effect on the level of profitability, and by moving from the high prosperity to the deep recession, the impact of the variables has increased. As a result, it can be said that profitability in the state of economic recession has a higher sensitivity to explanatory variables.

Efficient and effective customer relationship management increases customer satisfaction and retention. Customer relationship management helps organizations evaluate profitability and customer loyalty using criteria such as repeat purchases, money spent, and durability. The main goal of this research was the dynamic modeling of communication with customers and the dynamic analysis of this model. The current research is applied in terms of purpose and in terms of survey method with model development approach. The time frame of the research is five years (2017-2021). For this purpose, information on the indices of 33 factors affecting competitive advantage in Tejarat Bank were entered into Bayesian averaging models (BMA), dynamic moving average model with parameters that can be changed over time (TVP-DMA) and dynamic selection model with parameters that can be changed over time (TVP). -DMS) Based on the error rate, the BMA model had the highest accuracy. After estimating the model, 8 main variables were identified. which consists of: long-term account balance; the amount of use of mobile bank; the amount of internet bank usage; real customers; legal clients; special or normality of the customer; Type of job and education. These 8 main identified variables were entered into the dynamic model and then the model was validated based on boundary adequacy tests, structure evaluation, integration error and sensitivity analysis.

Air transportation has always been of interest to national managers and planners due to its positive features, including high speed, safety, and large capacity. However, various constraints affect the efficiency of this system. In this research, the resilience of the air transportation network is examined. Constraints are divided into two categories: natural events and sabotage events. In this study, data from domestic flights in Iran were used to analyze the resilience of the air transportation network. For this purpose, the number of serviced flights was considered as an indicator of network performance, and the cascade failure diagram method was used to analyze resilience. The results show that in the most pessimistic scenario, with the removal of three airports, network performance drops below 10%, as indicated by the cascade failure diagram. Additionally, the ideal scenario of network performance decline was examined, and the results show that in this scenario, with the removal of 90% of airports, network performance remains above 45%. Based on the conducted analysis, the biggest problem in Iran's air network is the excessive concentration of flights in a few specific and high-demand airports, which greatly affects network resilience in case of any issues occurring for them.

The current research sought to design a model for evaluating technological innovation capabilities with a dynamic modeling approach. The nature of the research was quantitative and qualitative, and in the qualitative part, technological innovation capabilities were extracted using interviews with experts and then refined using the Delphi technique. In the quantitative part, the designed model was simulated using the system dynamics approach. The effect of 18 factors on innovative capabilities was shown to be completely positive and effective. In other words, it can be said that the 18 determined factors can lead to innovation in technology in the automobile industry, and it is definitely effective in this industry. But in addition to the general effect, if we want to go into details, we can see that the 18 factors have an effect on the six state variables, namely profitability, customer satisfaction, innovation improvement, human resource management, productivity and quality. The shape of this effect varies from one variable to another. The shape of the work was meant to be linear or exponential. The effect of the model on profitability and customer satisfaction variables was completely significant and exponential. In this way, at the end of the period, cumulative effects and growth of profitability or customer satisfaction were witnessed, and this effect was not clear at the beginning of the period.

The main problem in the steel industry and value chain management is identifying and modeling fluctuations in this market. Considering the vertical chain in this industry and the interaction between players, we will use game theory to model the optimal price. On the other hand, considering that to achieve equilibrium, player interaction, and game repetition are needed, deep learning models were used to repeat the game. The research method is quantitative, descriptive in terms of philosophy, positivism, in terms of nature, and applied in terms of results. The data collection method is the library. The research period is seasonal data from 2011 to 2020 and the software used is MATLAB software. This research presents a hybrid model based on deep learning networks and game theory to help steel industry activists determine the optimal price level and production. To predict the price of steel, CNN, LST, and RNN algorithms were used in deep mode. The results show the fact that by moving from the Cornot game to the Stackelberg game and from the Stackelberg game to the collusion game in the supply chain, it increases the price and production in the steel industry. The exclusivity of the steel market in Iran assures the producers that the price will not decrease with the increase in supply.

The purpose of this study is to investigate the factors influencing customer behavior in the use of electronic services of Shahr Bank. 

This study employed a quantitative research method. A total of 77 components were extracted from the literature and categorized into four dimensions: sociological, psychological, demographic, and technical services. Additionally, 10 indicators, including culture and norms, social class, social pressure, demographics, quality of technical services, ease of technical services, and behavioral, emotional, perceptual, and personality factors, were determined. After content validation, the initial research model was examined. A questionnaire was designed for data collection and distributed among the bank's customers. 

The findings, using exploratory factor analysis, revealed that the dimensions and indicators identified in the first phase of the study were sufficiently valid. Results indicate that psychological, demographic, and technical service factors have significant effects on customer behavior in utilizing electronic services. 

The final model of the study was developed based on the internal relationships between variables and statistical analyses. This model can serve as a framework for improving the acceptance of electronic technologies in banking. Based on the findings, recommendations were provided to increase the adoption of electronic services at Shahr Bank.

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

The present research purpose has been dynamic modeling of customer relationship management in e-banking in Sepeh Bank and merged banks, and the conceptual framework identified in the case study was used. The statistical population is the experts in Sepah Bank's customer affairs, and a sample of 14 people has been selected through theoretical sampling method utilizing purposeful techniques. To measure the relationship between dimensions and indicators, fuzzy cognitive map was used in the form of pairwise comparison matrix questionnaire, and the reliability and validity of the questionnaires were confirmed by the test-retest method and the content validity with Lawshe method. For simulation in a certain period of time and measuring the validity of the model, Bidirectional Associative Memory(BAM) Neural Networks have been used in the FCM Expert software. The research findings show that "Customer Relationship Development" is the most central and influential and "Customer Retention" is the most affected dimension, and the mutual influence between "Customer Identification" and "Customer Relationship Development" is significant. Also, the "Customer Attraction" has the greatest impact on the "Customer Retention & Customer Relationship Development" and the "Customer Reach and Acquisition" has the greatest impact on the "Customer Attraction & Customer Retention". Based on these results, it is recommended that Sepah Bank managers pay special attention to customer attraction through branding and the implementation of advertising campaigns at contact points, and despite the low impact of the "Customer Relationship Review", its significant impact on the most central dimension, i.e. "Customer Relationship Development" should not be neglected.

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

This research adopts an approach that conceptualizes security and develops a comprehensive security model using knowledge representation technologies. It aligns with sustainability and organizational resilience within the context of the fifth industrial revolution, aiming to provide a complete overview of the conceptual components of security.

The objectives of this applied research are pursued through a conceptualization approach. To achieve this, the latest version of Protégé software was used to develop the ontology. Additionally, a life cycle process for ontology creation was designed to align with international methods and design science. Furthermore, to create a comprehensive representation, the OntoGraf tool was employed with a focus on organizational resilience.

The design of a conceptual model for organizational security requirements, controls, and assets was achieved through ontology engineering using the Protégé tool. This process was based on standards, international frameworks, and the specific conditions and needs of the country. The approach aimed to establish sustainability and resilience within the organization while also creating a comprehensive representation of the conceptual components of security in organizations.

In today’s complex environment, smart action is essential. In a large organization like a university, acting intelligently is the most important factor in enhancing competitiveness. Security plays a crucial role across various dimensions of organizations that adopt a smart approach. The field of security is highly dynamic, with new threats constantly emerging. To address these rapidly growing threats, conceptual solutions are needed to enhance organizational security, resilience, and continuity. This research presents the conceptualization and organization of knowledge in security, as well as the creation of a platform for the development and use of common concepts

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

The architecture and implementation of security processes in smart projects, due to their complex nature and extent, is not possible using traditional security methods and requires innovative solutions based on artificial intelligence. One of the hybrids of artificial intelligence is CTI, which provides a better understanding for people in the field of security to analyze the situation and position, and with analyzes based on understandable intellectual patterns, next to the metadata, an analytical view of the situation. depicts, therefore, the necessity of having suitable services of SOC and the effective use of CTI in organizations is very necessary.The methodological framework used in this research is based on the combination of the matrix models of design science, the rotational attitude model and the process model, which are all three of the main models of design science. In the quantitative part, the data was collected through a questionnaire and the model was tested using the structural equation modeling technique and Smart-PLS software. the method of assessing the maturity of cyber threat intelligence capability was designed according to C2M2 and SOC2M2 standard in six specific phases and a questionnaire was designed according to them including twenty eight questions. The results showed that, in smart police, the definition and application of CTI in the security operation center has started and is at the maturity level of one. The focus of the organization is the aspect of CTI tools and it is necessary to develop management, process and automation funds according to them. .

Efficient supply chain as well as the proper management of its components play an important role in supply chain productivity. The steel industry is one of the mother industries and needs to further enhance its chain productivity. The purpose of the present study is to identify key factors affecting the productivity of national steel supply chain. In order to identify the factors affecting steel supply chain productivity, the SCOR model has been used and its indices have been validated by CVR and CVI forms as well as by steel industry experts, based on which the designed questionnaire was distributed among the managers and experts of the steel industry and the data were collected. Finally, the data analysis was performed using confirmatory factor analysis with structural equations and PLS software. The factors affecting supply chain productivity were confirmed by 30 indices and 6 factors.The results revealed that all 6 factors influence steel supply chain efficiency, however, among these factors, the enabler’s factor

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.

Increasing operating profit is a challenge faced by pharmaceutical distribution companies. Most of the researches conducted in this field have a cost reduction approach. The online monitoring system is one of the effective methods that can be used for managers' decision-making and improving the performance of the pharmaceutical distribution chain with the approach of reducing costs and increasing revenues. To create this system, conceptual, mathematical and computer modeling is needed. The aim of this research is to develop a mathematical model of the online monitoring system to improve the pharmaceutical distribution system based on a conceptual model using a reinforcement learning approach. The mathematical model was derived based on the factor-based conceptual model and using the multi-factorial reinforcement learning approach. After extracting the mathematical model, the effectiveness of the model was validated by comparing the results obtained from the output of the mathematical model and the actual results in a pharmaceutical distribution company. The findings of the research showed that the developed mathematical model has the ability to continuously improve the goals, decisions and performance of the pharmaceutical distribution chain processes, according to the interactions and changes in the behavior of agents and the state of the environment.

The significant growth in the amount of use of management information systems in different work departments of organizations has caused researchers in the field of information technology management to pay more attention to improving productivity in these systems. The purpose of this research is to identify the cause and effect (causal) mathematical model of the productivity of management information systems in the field of human resources.

This research has used a mixed exploratory approach. First, the conceptual model was calculated using the previous sources, and then the mathematical model of cause and effect was created using the quantitative method of Fuzzy DEMATEL (in six steps). The reliability and validity of the questionnaires of fuzzy DEMATEL pairwise comparisons have been confirmed by using the test-retest method and the content validity method of Lawshe, respectively.

Among the main productivity dimensions of the human resources management information system, the dimension of "intelligence" is the most effective dimension. The "innovation" dimension is the most effective dimension. The dimension of "innovation" has the highest degree of interaction with other dimensions and the dimension of "intelligence" has the highest degree of causality.

Since "effectiveness" is the main problem and "intelligence" is the main solution to the problem, placing the dimension of "intelligence" and the components of "organizational effect" and "individual effect" and "user satisfaction" in the focus of attention; The main priority of the management information system maintenance and development team in Naja's human resources department is to improve productivity.

The risks5 of buyer-supplier relationships cause the decreased performance and disruption in supply, but they can be managed by providing a suitable strategy. Despite the importance of these risks, a risk management model that determines the appropriate strategy for each supplier has not been developed so far. The purpose of this research is to provide a model for determining the strategy of buyer-supplier relationships risks for oil rotary equipment manufactures.

In the first stage, relationship risks and strategies were identified based on the research literature, and then experts' opinions about risks were collected to determine relationship risks in the studied industry. In the second stage, using the interpretive structural modeling method developed with fuzzy logic, the relationships between risks and those levels were examined and the most effective risks were determined by MICMAC analysis. The third stage is determined strategies by experts' opinions. Then fuzzy risk matrix with the dimensions of probability and intensity of impact is designed. Based on the risk priority (based on risk position in the matrix and its level based on interpretive structural model), a suitable strategy was determined for each supplier. In the last step, this model was validated by calculating the percentage of agreement.

The most effective risks of buyer-supplier relationships in this research include loss of objectivity, lack of trust and confidence, supplier's unwillingness to cooperate, Limited number of suppliers, supplier's opportunism, collusion and conflict of goals, which Their priority and relationships have been determined. Based on the priority of risk for each supplier, strategies for risk management have been determined.

The results of comparing the output of the model and the opinions of experts show the validity of the designed model and this model can be used for all industrial equipment manufacturer companies.

The scope of activities and strategic goals in modern organizations has led to the development of organizational structure and increase their utilization of various IT-based systems. Inadequate bureaucracy and administrative hierarchies in public organizations such as ministries make them difficult to manage. The diversity of policy units, the weakness of management power in achieving organizational goals, and as a result, poor monitoring and evaluation of programs in these organizations, making them smart is essential. But considering the structural and functional complexities of these organizations, how can one measure their smartness and organizational structure. Therefore, this study was conducted with the aim of providing a strategy for measuring the status of smartness and the structure of public organizations. The method of work includes designing a fuzzy expert system; First, effective indicators were identified. Then, using fuzzy theory and expert opinion, a fuzzy expert system was designed. In the designed system, 13 quality indicators were used that can determine the status of the structure and the level of smartness of the organization in 5 categories. In order to collect research data, a questionnaire was designed and provided to managers and senior experts of the Ministry of Health and Medical Education and then technology radar is used to display the system output results. Finally, the system sensitivity is analyzed. Based on the research results, the studied organization is in an unfavorable situation in terms of smartness and organizational structure.

Today, agility is recognized as a characteristic of competition, so its use in the supply chain of many companies has expanded, but these companies need a way to adapt to the dynamic needs in the least Time consolidates a large amount of information and delivers it to different parts of the supply chain. E-marketing can be effective in solving this problem.The purpose of this research is to"develop a comprehensive model for evaluating the factors of electronic marketing that affect the agile supply chain". This research is applicational and descriptive-surveying with the modeling approach. The statistical population of this research consists of experts with common expertise in the field of IT and marketing in Hamrah Aval operator. The number of these people is 133, which was randomly selected.The questionnaire is used to collect the information, and the structural equation modeling approach, the one-sample t test, (AHP) approach and Quality Function Deployment approach,were used to analyse the data. The research results show e-marketing has an effect on supply chain agility and 7 factors, as the most effective e-marketing agents to respond to agility enablers and 7 tools the most effective e-marketing tools for budget allocation were identified and prioritized in order of weight. According to studies conducted in this field, no study has been conducted in relation to the present study. As a result, the proposed structure is presented as the first model that has the ability to be formulated and implemented according to the current variable situation.

Making more profit in organizations requires accurate tools to strengthen the business for proper financial planning. Therefore, the purpose of this study was to demonstrate knowledge of the neural network to provide a framework for achieving the desired profit in the organization's financial planning. This research was of the applied type and was performed by the analytical survey method. The study population was the organizations present in the Exchange and Securities Organization, and the data extracted from the official system of the Exchange and Securities Organization of Iran (Cadal) were used. This research was conducted using the neural network method in a MATLAB program environment. Findings The range of changes of factors affecting the main index in the organization's financial planning (profit) and the most important factors affecting it were determined. The proposed framework was reviewed in three different sets of three various industries and had acceptable results. Therefore, the study results indicated that the proposed framework in this study could be used for other organizations present in the stock exchange and securities.

The complexity and inconsistency in the environment is increasing strongly, and smart organizations need to adapt to the environment in order to perform smart and timely actions, in other words, acting smart is an integral part of increasing their competitiveness and survival. In order to achieve goals and missions in such organizations, information security is of high importance. In order to deal with advanced threats, appropriate solutions are needed for prevention, detection and response in an effective time frame. Meanwhile, the organization of knowledge and the use of common concepts by humans and computer agents has become an important issue in the field of security, and ontology is presented as the key to this issue. Considering the nature and capabilities hidden in ontology, new and innovative applications are envisioned in the field of intelligent organization security, which has made it a suitable tool for security knowledge modeling. In this research, by studying the world's successful achievements and experiences in this field and research in the field of strategic documents in terms of requirements, the network ontology design was done in the Protégé software environment and the model was presented using Onto Graf, and then the application software as The semantic infrastructure of the network was designed with Python language.Therefore, it is possible to continuously develop the ontological model and provide a common understanding in the organization, and based on the conclusions obtained from the model and the designed software, provide suitable solutions to increase the security of the intelligent organization

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.

The purpose of this paper is to provide data quality model of a university portal with an integrated approach of system dynamics and quality function deployment. The present study is applied in terms of descriptive – survey method research. Following paper aims to provide a model and identify the concept and its dimensions for an academic portal and through using library study methods as well as field methods such as questionnaires, content analysis methods and Fuzzy Delphi method simultaneously, collect the voices of different users regarding data quality and finally, with the formation of four quality house matrices, it led to design requirements. Based on Quality Deployment Function analysis, found out that Extensible Markup Language (XML) could be more proper programming language to achieve flexibility as one of the most important engineering characteristics to fulfill user’s requirements. The important ambiguous issue in this context was how the internal communication between the requirements was; As a result of simulating these relationships, it was found that the way of communication overshadows the whole results. At the time of planning in the field of data quality and presenting a model in this regard, it should be considered that the factors may have conflicting relationships and unilaterally addressing a requirement or characteristic without considering its relationship with other cases could have the opposite result and efforts related to it will be fruitless.

Due to the increasing number of competitors, organizations are increasingly looking for aperformance evaluation system that is effective and dynamic In addition to clarifying an organization's current situation, performance evaluation and management can be an organization's strategic plan that could also determine the organization's future. The purpose of this article is to provide a model for evaluating the performance management of oil and gas companies with a game theory approach. The present research is applied and descriptive research, and its branch of survey. The study population of this research includes all companies which act in the field of oil and gas. The statistical sample of this study consists of 280 people who were randomly selected. In the Recent study, multirariate statistical analysis software was used for analysis in to part: descriptive and inferential, mathematical modeling and shapley value. The results showed that paying attention to the customer's perspective will create the most desirability to achieve the vision, and penetration in new markets with a beta of 0.774 directly affects revenue growth.