محمدعلی افشار کاظمی

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.

Personalized Digital Marketing is one of the key and thriving trends in the world of digital marketing, developed with the aim of delivering unique and tailored experiences to each customer. In this approach, marketers strive to understand the needs, preferences, and behaviors of users by collecting and analyzing their data. Based on these insights, they design marketing content, advertisements, and offers that align specifically with each individual. The goal of this research is to identify the dimensions and components of personalized digital marketing through a recommendation engine using a thematic analysis approach. To achieve this, after reviewing the literature and research background, basic and organizing themes were identified. Then, through surveys and interviews with 25 experts and university professors familiar with the concepts of personalized digital marketing, a conceptual model of the research was introduced. In conclusion, practical suggestions were provided to IT and marketing managers in online stores, including Digikala.

This article analyzes how to develop a step-by-step business strategy based on dynamic, agile, and self-organizing approaches. The present study examines the four main stages of platform business (entry, growth, development, and maturity) and investigates the key elements and various strategies for each stage. These elements serve as a conceptual framework and ultimately lead to the creation of a platform business model. The current research is qualitative in nature, with the target population consisting of university professors and experts in the field of platform businesses, selected using purposive sampling and the snowball method. Data collection tool includes in-depth interviews. A multi-faceted approach based on thematic analysis (themes) is employed to analyze the data. This study provides a rich and diverse set of strategic concepts for designing a platform, enabling platform companies to reduce the risk of failure and survive in uncertain and complex market environments. Additionally, it empowers platform providers to establish a successful business ecosystem.

Today, knowledge-based businesses are important in the two dimensions of science production and knowledge-based economy development. The special conditions of these businesses, such as being new, focused on creativity, communication with other organizations, and the use of various capacities, have caused the challenges related to this category to be given more attention. The purpose of this article is to provide an interpretative structural model for the challenges of marine knowledge-based businesses that are not in the formation stage but in the structural and communication maturity stage. In this research, library studies and literature review were used to calculate the criteria related to maritime knowledge-based trans-bureaucratic organization, and in order to identify the obstacles and challenges that are the main variables of the research, the questionnaire tool and the content analysis approach were used. . The statistical population of the research is 11 specialists and experts in the field of marine technologies, whose opinions have been collected using the Delphi technique and analyzed by combining the research approach in soft operations and fuzzy logic. Fuzzy logic pays attention to the degree and intensity of the relationship between elements according to the opinions of experts and makes the final model more valid. Based on the results of the research, the challenges of "management based on open relationships and high trust" and "success-seeking spirit, idealism and excellence-seeking human capital" have been placed at the level of a model and are always influential and influential. are high "Financial, technical, business and commercial risks",

Timely delivery of medications, medical equipment, and other essential supplies is critical to patient care and can often be life-saving. Delivery delays in the healthcare supply chain can lead to increased costs and operational challenges for healthcare organizations and affect patient care and financial stability. Efficient and reliable supply chain management is critical to reduce these risks and ensure integrated performance in the health industry. This research addresses the delay in the delivery of health commodities in the global health supply chain of the United States Agency for International Development. It presents a framework based on the support vector machine technique and Bayesian optimization to predict the delivery status of health commodities. It also determines the features that have had the greatest impact in predicting the status of commodities delivery for data-driven health supply chain management.

The study's research method is design science, which presents a framework based on the support vector machine technique and Bayesian optimization to predict the delivery status of health commodities. It also compares the performance of different classification algorithms to predict the transportation status.

The results indicate that the presented framework based on the support vector machine technique and Bayesian optimization leads to a classification accuracy of 95%, outperforming other techniques to predict delivery delay. The results showed that the features of the destination country, shipping method, supplier, and production location are the most influential features in predicting the delivery status.

Optimizing camera placement is a two-decade-old research problem. Many researches have solved the problem with different approaches. Some different methods such as genetic algorithm, reinforcement learning, and greedy algorithm have been developed to obtain the maximum surface coverage. Some researchers have considered specific applications in order to optimally cover a certain area such as a coastal area or a protected area under the coverage of CCTV cameras. Some researchers have also considered the camera's capabilities of vertical rotation or horizontal rotation or zooming in order to use these capabilities for optimization. With the development of drone manufacturing technology, this tool is also proposed for specific applications. But what is less discussed is the optimization of the placement of urban surveillance cameras in a real city map. Usually, due to the high cost, all city cameras are not installed at once, and cameras are added annually to develop the city traffic monitoring system. Therefore, it is necessary to prioritize the selection of the route and a very important factor in prioritization is traffic. Traffic is the most important factor in choosing the route for the placement of urban surveillance cameras because the streets with more traffic are exposed to more traffic accidents and should be the priority for video monitoring. Traffic data is usually big data, not available for all cities, and on the other hand, providing traffic data may violate citizens' privacy. Therefore, there are many methods for creating virtual traffic, which are classified into two categories: macro and micro. Macro methods model traffic as a physical phenomenon such as fluid or gas, but micro models, which are mostly used in artificial intelligence methods, consider traffic as a set of individual trips. In this work, we use the second method to create virtual traffic so that routes with more traffic are prioritized for installation. Citizens usually make a lot of intra-city trips, and the function of city monitoring systems is to monitor these routes. Therefore, the placement of surveillance cameras should also be in such a way that it considers the observation of these routes. In the proposed method, the real map of the city is selected as a model. Then, by separating the main paths and obtaining the skeleton of the path, a graph of the paths is obtained, the intersection point of the paths will be its vertex and the distance between the vertices will be the weight of the connecting edges. Now by randomly selecting two vertices from the graph as the origin and destination of an intra-city trip and routing between them with Dijkstra's algorithm, a trip is made. By repeating this process, virtual traffic is simulated. To create virtual traffic similar to real traffic, the probability of choosing high-traffic points is considered more than other points. Therefore, the probability of selecting vertices in the graph is different according to their location in the city. By creating one hundred thousand paths for the studied model, the edges with the highest repetition can be found as the final results and suggested for camera installation. The evaluation of the final results is done by repeating random experiments and using the Jaccard similarity coefficient, and the degree of similarity of the output results is checked. The reliability of the proposed method is expressed by mathematical analysis and by drawing graphs, and the impact of influential parameters such as the number of city trips, the probability of choosing points, the impact of city topology, and the number of output results are expressed analytically, and the similarity of the results is 98%. The advantage of the proposed method is not depending on special tools such as special cameras for traffic measurement, as well as not depending on a specific location and topology.

Granting facilities is an important part of every bank's operations. This part of banking activities is economically important. With its operations, banks can provide the transfer of resources from those that have directly invested to those who need money, this repayment makes another people use these resources. Failure to repay facilities on time will cause the bank's resources to stagnate and in the long will cause the country's economic recession. It is important to monitor the correct allocation of resources because if bank resources are used and unfounded payments are made, the banks will not be able to pay the depositors and will become bankrupt. By examining the researches in the field of banking, it was found that most of the researches have focused on the optimal combination of the investment portfolio in the capital market, and less researchers have paid attention to the discussion of the optimal combination in the money market. Most of the researches that used operational and statistical research methods were related to industrial issues, and less in financial issues and operational research discussions were used. In the optimal portfolio of the combination of facilities or investments, mostly the genetic algorithm has been used and less than other fuzzy methods have been used in the conditions of uncertainty. Therefore, in this research, the improvement of facility payment modeling has been addressed by using convolutional neural networks and CNN-LSTM modeling.

The increase in industrial activities and the dispersion of interdependent industries in unfavorable climatic situations have caused environmental problems and issues on the other hand, it can be considered a serious obstacle to sustainable production in industries. The purpose of this research is Interpretive ranking appraisal of ecological drivers of sustainable production in the oil industry.  

This research, which is considered developmental and mixed in terms of methodology, tried to identify the ecological drivers of sustainable production in the oil industry by relying on Meta-synthesis analysis and Delphi processes in the qualitative part of the research. Then, in the quantitative part, interpretive ranking analysis will be used to identify the most effective ecological driver of sustainable production in oil industry. The participant in the qualitative section was 14 specialists and experts in the field of industrial management at the university level and in the quantitative part, the participation of 23 managers and the experts was used from the management level of the development center in the National Iranian Oil Company, who had experience both in terms of knowledge and experience. The results of the research in the qualitative part after the content screening of 14 confirmed studies indicated the existence of 6 ecological drivers of sustainable production in the oil industry.

The results in the quantitative part of the research showed that, from the sum of the overall effectiveness based on the paired scale between the research components, it was determined that the percentage of influence of the stimulus, ecological, climatic and environmental positioning is higher than the rest of the ecological stimuli of sustainable production in the oil industry.

The obtained result expresses the fact that ecological positioning in terms of climate and environment helps the oil industry by bringing together companies active in this field, while preventing the dispersion of industrial companies, at the same time can by evaluating the soil; Plant and animal diversity and other environmental aspects prevent the erosion of natural resources and environmental pollution.

facilitating the business environment depends on the participation and role-playing of different parts of the society in improving the conditions.

this research has been carried out with the aim of designing an interpretive structural model of governance of ease of business.

The research is applied in terms of purpose and survey in terms of data collection and has a quantitative approach. The community studied in this research is the country's business system, and 15 experts were selected to form an expert panel. After extracting the dimensions and components from the literature and research background, fuzzy Delphi technique was used to refine the components. Finally, Interpretive Structural Modeling (ISM) method was used for modeling.

The findings of the research showed the factors of correcting the deficiencies of relevant laws, implementing electronic government, transparent and carefree access to financial resources, familiarity with relevant laws, privatization of organizations and institutions. Trustee and reform of the tax system are linked variables.

Since the linked variables have a great power of influence, any action on these variables causes changes in other variables. Therefore, in order to facilitate business, in the first step, all efforts should be focused on improving these factors.

The scarcity of water resources can be considered one of the most important problems that has impacted all aspects of people's lives in Iran today. Given the significance of the issue, in this study, the dynamic hypotheses within the water resource supply system were initially illustrated through a causal loop diagram. This was done using the tool of system dynamics, which has proven its utility in analyzing and simulating various socio-economic systems. Subsequently, a Stock Flow Diagram was developed, and after model simulation and validation, scenarios involving tariff and governance in relation to water resources up to the year 1420 were analyzed. The results showed that changing household water consumption tariffs will not have much impact on water resource stocks. However, as the agricultural and industrial water consumption patterns are expected to be modified in the long term, increasing tariffs for these sectors will have a significantly better effect on water resource management over a 20-year horizon. If government regulations regarding water-intensive industries, cultivated land expansion, and agricultural water consumption become 20% more stringent, assuming stability in other model parameters, underground water resources and reservoir water resources are projected to increase by 17% and 20% respectively by the year 1420.

In recent years, the world has been engulfed in a crisis caused by a contagious disease called the coronavirus. The impact of this crisis is so significant that some researchers have also paid special attention to the post-coronavirus world. Therefore, the aim of this research is to identify the factors of sustainable value in using information technology for managing acute viral diseases.

The research method is mixed. In the qualitative section, the thematic analysis method has been employed. The reliability assessment of this section is also conducted using the method of comparison by two coders, resulting in a coefficient of 83%. In this section, interviews continued until theoretical saturation was reached, and 23 interviews were collected. In the quantitative section, structural equation modeling with a partial least squares approach using SmartPLS_3 software was employed to analyze the data, and a semi-structured questionnaire with a five-option Likert spectrum was distributed among 241 individuals. The research population includes healthcare professionals in medical sciences, faculty members in management and technology fields, as well as managers of knowledge-based companies active in medical technology in Tehran province. Simple random sampling using the Cochran formula is also employed in this section.

The results showed that in the area of pandemic management and control, organizational factors (with a coefficient of 0.41), control and supervision (with a coefficient of 0.28), and planning (with a coefficient of 0.43) were confirmed. In the sustainable value section, environmental factors (with a coefficient of 0.29), social factors (with a coefficient of 0.37), and economic factors (with a coefficient of 0.47) were confirmed.

Thus, the sustainable use of information technology can not only control pandemics but also prevent their consequences for future generations.

The aim of the research is predicting critical risks of the gas transmision network and choosing optimal corrective action in optimal time and cost. Risks were predicted with data-mining algorithms based on the CRISP methodology. K-Means, Kohnen, Two Step algorithm and Neural Network Algorithms, C.5 Tree, Nearest Neighbor and Support Vector have been used for clsutering and classification. Markov decision process is also used to select the optimal control action.Decision making problem is based on back down induction in stochastic dynamic programming in the limited time of modeling and simulation and sensitivity analysis and model validation. Based on results, in 97.56% of the agreed data, learning was created and the accuracy and validity of the data mining model was estimated at 86.92%. Also, 13 risks have been identified as critical, and the simulation results show a 92% improvement rate in the cost and 77% in the control action implementation time.

Today, considering technology development, increased use of Internet in businesses, and movement of business types from physical to virtual and internet, attacks and anomalies have also changed from physical to virtual. That is, instead of thieving a store or market, the individuals intrude the websites and virtual markets through cyberattacks and disrupt them. Detection of attacks and anomalies is one of the new challenges in promoting e-commerce technologies. Detecting anomalies of a network and the process of detecting destructive activities in e-commerce can be executed by analyzing the behavior of network traffic. Data mining systems/techniques are used extensively in intrusion detection systems (IDS) in order to detect anomalies. Reducing the size/dimensions of features plays an important role in intrusion detection since detecting anomalies, which are features of network traffic with high dimensions, is a time-consuming process. Choosing suitable and accurate features influences the speed of the proposed task/work analysis, resulting in an improved speed of detection. In this article, by using data mining algorithms such as J48 and PSO, we were able to significantly improve the accuracy of detecting anomalies and attacks.

The use of new approaches and technologies in the design of maintenance plans and policies, taking into account the changes and growth of technology, is one of the factors that are increasingly considered by experts today, and in addition to reducing costs Repair, reducing downtime of machines and increasing the useful life of machinery and equipment, create a competitive advantage in production systems. The purpose of this study is to provide a model for realizing a proactive maintenance approach. In this regard, the decision-making problem for "selecting maintenance policies and programs at the optimal time with the lowest cost" has been modeled. For conducting research, historical data related to the implementation of maintenance programs and risk assessment in the gas pipeline network have been used, and based on recursive induction in stochastic dynamic planning with Markov decision-making process in finite time, mathematical model is designed. In this research, to assign each of the specified policies and actions related to the maintenance program to the identified risks and defects, simulations and optimizations based on time and cost have been performed and sensitivity analysis and validation of the model are performed. The rate of improvement and the rate of optimization in the cost of implementing maintenance policies and the time of its implementation, indicate the efficiency of the proposed model.

The main challenge of companies is to fulfill services and meet customer expectations. Quality Function Deployment (QFD) helps to extract service features from customer requirements.

Due to the use of the Internet of Things in telemedicine, this research has two objectives, the first purpose is to identify the parameters affecting the integration of IoT and telemedicine systems with the view of improving quality performance and the second purpose is to investigate the possibility of using artificial neural networks to predict the behavior of the QFD matrix.

For the first purpose, value-oriented engineering analysis method and customer-oriented Function Analysis System Technique (FAST) diagram were used, and after obtaining the parameters, including customer call, service characteristics and operation requirements, for the second purpose, Fuzzy Back-Propagation Network was used.

After obtaining identify the parameters affecting the integration of IoT and telemedicine systems with the view of improving quality performance, a total of 50 QFD matrices were collected and their data were introduced in a Fuzzy Back-Propagation Network. 80% of this amount has been used for network training, 15% for testing and 5% for validation of predicted results. The mean square error (MSE) for the validation section is MSE = 0.015584.

the results showed that the Fuzzy Back-Propagation Network method is suitable for predicting the expansion of QFD in the integration of IoT and telemedicine systems.

The purpose of this research is to combine the genetic algorithm in the optimization of the stock portfolio in the financial decision making of investors; in a simulation project, the final use of the input data is to build the simulation model. This process includes collecting input data, analyzing the input data, and using these analyzed input data in the simulation model. The statistical population of the research includes 20 symbols (companies) from among the industries (Vabsadar, Vetjarat, Akhaber, Fakhuz, Fars, Balbar, Tapampi, Khasapa, Khodro, Sasharq, Sosofi, Shobhorn, Shapna, Ghopino, Fould, Ghasabat, Kesra, Vanbank, Vanneft, Veniki) and the information related to the daily stock price and the daily index value from Decembre 22, 2008 to January 16, 2020 was considered as a sample. The tool for collecting information and data is using the Phipiran site, and the amount of beta (risk) of stocks is calculated monthly using Excel software, and the frequency of return and beta (risk) calculated using Spss software, and distribution functions were discussed using Easy fit software; the results showed that if the agents are beginners to earn more profit than normal behavior and accept 40% risk, the amount of profit obtained after optimizing the model with genetic algorithm is more than the initial model. If the agents are professionals to earn more profit than risk-averse behavior and accept 80% risk, the amount of profit obtained after optimizing the model with genetic algorithm is more than the initial model.

Recently, the supply chain of perishable goods, have been considered due to their impact on human life. On the other hand, in the packaging industry, considering paper as a primary and perishable material due to the nature of water absorption, severe rotting in front of sunlight, flammability and turning to ash and finally affecting the final quality of the product produced from this issue. It is not excluded, it has attracted more attention. The high level of speed of changes and ambiguity in decisions has made it impossible to predict the future conditions of supply chains. Therefore, the design and use of a mathematical model for the design of the closed-loop supply chain network, taking into account the optimal pricing of products, the return rate and demand, along with taking into account the wastage of materials in the system, is strongly needed. At first, the supply chain of the paper-cardboard industry was designed and modeled with mixed integer programming, then due to the high volume of calculations and data of the problem, we can't receive exact solution approaches, the innovative approach of searching for harmony was used for the solution. . The problem is a single-objective model that minimizes system costs by considering environmental considerations. The present research shows that the price increase has a positive effect on the product return rate and reducing the level of product corruption. Finally, to validate the model, the numerical solution of a closed loop network has been done in this industry.

The use of shock absorbers in various industries in order to reduce the fluctuations of equipment and air from premature depreciation and increase the useful life of parts has a special feature. In this research, the design and construction of the hydraulic shock absorber and the analysis of the characteristics and components of the parts and the impact of the working fluid used in the shock absorber have been discussed. In common shock absorbers used in the industry, hydraulic oil with a constant viscosity (Newtonian fluid) is used, and in this condition, due to the constant viscosity of the fluid, the stopping acceleration of the shock impacting the shock absorber is initially high, and with the passage of time, the acceleration . The stop is reduced, and this issue causes motion shock and hitting the body, and may cause injury or death. In this research, researchers and decision makers have investigated the rheological properties of the working fluid used in shock absorbers by applying the science of rheology, which has been highly regarded over the years. In fact, by using fluids whose viscosity is not constant (non-Newtonian) and whose viscosity changes due to various reasons such as shear stress change, the intelligent function of the receiver is affected. The use of these fluids is such that when the body collides with the bumper, due to the impact and the high cutting rate, the viscosity of the fluid is reduced and causes the body to experience less acceleration and stop. decrease with The shear rate and consequently the increase in viscosity of the fluid, the acceleration of the stop is increased until it finally becomes an object. It should be noted that the construction of such shocks is of interest in the world, and this is the first experience of industrial use of this shock in the world, which can confirm the laboratory results of improving the damping conditions. These shock absorbers are used in various industries, such as automotive industry, aviation, strengthening of buildings against earthquakes, as well as the elevator industry.

This paper aims to present the key research trends in the healthcare supply chain,critically analyze the research characteristics of these areas, define the main elements of thehealthcare supply chain and the effects of the COVID-19 pandemic on the healthcare supply chain,and present responses to overcome these impacts based on literature review.

Design/methodology/approach:

 A systematic literature review is conducted on the healthcaresupply chain research papers covering ten years of research (2010-2020) in peer-reviewed journalspublished in English. To achieve this goal, we performed a critical analysis of key research trendsin the healthcare supply chain, assessing the significant characteristics of the articles, such as issue,solution, research method, outcomes, and concerns,

We found 13 key research trends in the healthcare supply chain; healthcare supply chaincollaboration, performance measurement, and model/framework were the most significant areasaddressed in the papers reviewed in this study. The reviewed studies did not investigate therelationship between different entities in the healthcare supply chain in detail, and most hadlimitations in generalizing the findings to diverse companies/countries. The primary outcomes ofthe assessed studies were cost reductions and performance enhancements.

Originality/value: 

The analysis of the healthcare supply chain studies in diverse research trendsresulted in insights that help understand concerns in different trends and outcomes of the proposedsolutions. In addition, this study addressed the impact of the COVID-19 pandemic on thehealthcare supply chain and the responses to overcome them in particular.

The purpose of this research is to model scenarios for the protection of underground water resources in South Khorasan province in drought conditions.

In this regard, this problem was followed using the system dynamics approach and the behavior of the reference variable "Volume of underground water resources of South Khorasan Province" was simulated against different scenarios during the years 2013 to 2014 through the use of Vensim software. The required information was collected by referring to relevant organizations such as South Khorasan Regional Water Organization, South Khorasan Agricultural Jihad Organization and Iran Statistics Center, and the input data of the model was called into the model in the form of an Excel file.

The results of the research showed that applying the control scenario of water resources exploitation in normal drought conditions and drought with low intensity is useful, but applying this scenario in drought conditions of more than 20% will have negative effects on the economic indicators of the agricultural sector. Also, the fourth scenario of the cultivation pattern (emphasis on strategic crops) along with the fifth scenario of the cultivation pattern (drought-resistant crops) have brought the least pressure on underground water resources. Nevertheless, considering that cultivation pattern No. 4 has created the least added value, it cannot be an efficient pattern.

According to the results of the research, if the severity of droughts increases in the coming years, but the current agricultural conditions of South Khorasan province continue in terms of cropping patterns, droughts will not have an effect on economic indicators, because in these conditions, farmers By breaking the ground and extracting more from underground water sources, they will compensate for the lack of rainfall and will show the negative effects of drought on the stock of underground water resources. Considering the effect of the cultivation pattern on underground water resources and economic indicators, it is necessary to think of measures to change the cultivation pattern.

In this study, a comprehensive classification for supply chain risks in the pharmaceutical industry is presented using the Bailey’s classical strategy method and the four-stage Collier method. Initially, through the examination of texts related to the main hazard groups, supply chain elements, considering resources and functions, and categorizing upstream supply chain organizations, primary industry, and downstream supply chain organizations within the industrial and market environment, infrastructural environment, and external macro environment were modeled. In the next stage, criteria related to the security and safety of the supply chain were identified. In the final stage, a two-dimensional matrix classification for the identification of supply chain risk factors was proposed through the cross-tabulation of supply chain elements with security and safety criteria. Based on this classification and utilizing the exemplification method through a synthetic framework, a detailed list of risk factors was compiled. The aim of this study is to propose a comprehensive risk classification for pharmaceutical industries.

Bailey’s classical strategy method has been used to develop a comprehensive classification of supply chain risks in pharmaceutical industries. In order to review the existing knowledge about supply chain risk groups, a systematic review of literature was performed. In the first stage, to find articles related to supply chain risks in the pharmaceutical industry, different combinations of related keywords have been used to search for articles in relevant databases. The selected articles were examined in three stages: extracting and classifying the main risk groups of the supply chain (the first dimension of the conceptual framework of classification), extracting and classifying criteria for a low-risk supply chain (the second dimension of the conceptual framework of classification), and applying the two-dimensional framework of classification to identify and classify risk factors of the supply chain.

A total of 77 articles were selected for review. Based on the analysis of these articles, 83 risk groups were identified. These risk groups were arranged into a model including upstream supply organizations, the main industry, and downstream supply organizations, considering the relationships between supply chain’s resources, functions, and outcomes in the industry and market environment, infrastructural environment, and external macro environment. In the next step, 30 criteria for a safe and secure supply chain were identified. These criteria are divided into two general categories: criteria for the security of the internal supply chain environment (criteria of resistant supply chain resources and criteria of resilient supply chain functions) and criteria for the safety of the external supply chain environment (criteria of safety of market and industry, criteria of safety of infrastructural environment, and criteria of safety of external macro environment). In the last stage, through cross-tabulation of resource groups with resource resistance criteria, function groups with function resilience criteria, and peripheral environment elements with peripheral environment safety criteria, a model for identifying risk factors in the industrial environment was proposed. Based on this model, 372 risk factors of the supply chain of the pharmaceutical industry were identified.

In this study, a new classification for supply chain risks of the pharmaceutical industry has been presented. The proposed classification is highly comprehensive, and the number of risk groups counted in this study is more than all the studies that have been done in this field so far. Most existing risk taxonomies are incomplete and do not follow a specific theoretical model. The classification of risk groups identified in this study has been done based on a model that considers the relationship between assets, functions, and outcomes of the supply chain. The risk groups identified in this study cover from the upstream of the supply chain to the main industry and the downstream of the supply chain. Many risk taxonomies focus on the pharmaceutical industry and do not cover the entire supply chain from raw material production to customers. In this study, cross-tabulation of resource groups with resource resistance criteria, function groups with function resilience criteria, and peripheral environment elements with peripheral safety criteria create an ideal model for identifying risk factors in the industrial environment. The classification proposed in this study can be used to evaluate the resistance and resilience of the supply chain. This model can also provide a suitable basis for identifying and evaluating risks in the supply chain environment. In addition, results of this study provide a very practical guide for choosing supply chain risk management strategies.

This article presents a new model for optimizing the safety risk of take-off, as the most important and dangerous flight process, using a combination of BI algorithm and recurrent neural network LSTM. The goal is to train an effective neural network with past data records of air accidents to predict safety risk parameters. For this purpose, 17 safety features, such as weather conditions, aircraft configuration and preparation, flight information and air traffic were obtained. The data related to 2019 to 2020 was selected after performing exploration, summarization, cleaning, normalization operations with 28813 data records. Due to the dependence of flight data on their previous inputs and the need for a kind of memory, training was performed by deep learning algorithm (LSTM) in Python environment. After learning, the learning error was about 6 percent and the mean square error was about 116/0. It shows that the error percentage is negligible and the proposed model has high validity. Also, this model solved the problem of exploration and cleaning of bulk flight data by having advanced tools such as ETL, metadata and real-time monitoring and was able to predict the most important safety risk factor (speed V1) with high accuracy. This pattern helps the flight service in controlling the important parameters of safety risk, such as the speed of aircraft taking off from the runway, controlling the safe take-off speed and most importantly controlling the loss of flight with a reliable strategy.

In general, information technology has a sustainable nature, and in line with preserving the environment, it can advance programs that protect the interests of future generations. On the other hand, the presence of acute viral diseases in different periods has caused many human and financial losses in the world. Sustainable information technology can have a great impact on the management and control of acute viral diseases, which human power alone seems to be insufficient. Therefore, the purpose of this research is to design a management and control model using sustainable information technology for acute viral diseases. In the current research, it is an applied research that developed a conceptual and process model by using the qualitative method of theme analysis and the formation of a panel of experts. The data collection tool is an unstructured questionnaire for interviewing experts who include the medical community, university faculty members, and knowledge-based managers. Sampling continued using the targeted method until reaching theoretical saturation with the number of 26 interviews. The results presented a model with four sub-themes including: sustainable value (social, economic, environmental), management and control of viral diseases (planning, organization, control and monitoring), information management (data collection, information dissemination, reporting and data analysis). ) and finally led to sustainable information technology factors (sustainable performance, attitude, technology, policy and implementation). In the process model, the main components of the algorithmic model include identifying, designing, organizing and storing information. Therefore, it can be said that by using the management and control model implementation during

Despite the alternative methods of financing municipal projects and plans, crowdfunding by attracting the dormant capital of small investors and new investment methods can create new investment opportunities for ordinary lenders, people. The main goal of the current research was to investigate the methods of financing in Tehran municipality, according to the role of social capital in this process. The research method of the current study is quantitative, survey, cross-sectional, retrospective and applied. In order to collect information, library sources and comparative studies between different municipalities in the world were used in the field of providing income as well as field study. The statistical population of the present study was made up of senior financial managers and assistants, consultants, financial experts and experts, expert professors, revenue managers and diagnostic experts, and data analysis was used using decision making with multiple criteria. The participation factor with a relative weight of 0.435 has the most importance, which has the highest priority among financing methods; And the investment factor with a relative weight of 0.28 is the next priority, the paper and legal factors are ranked third to fourth with the weights of 0.138 and 0.088 respectively, and finally the contract factor is the last priority with a relative weight of 0.059. The inconsistency rate of pairwise comparisons is 0.04, which is less than 0.10, so these comparisons are acceptable. While reducing costs, social capital promotes interaction between citizens and municipalities or public service institutions, and it can be used to achieve development goals. Achieved purposefully and efficiently.

Given the complexity of tools as well as the variety of banking activities and intra-system communications, maintaining the banking system’s health and stability refers to one of the key reasons for monitoring banks and credit institutions in today’s banking industry; on the other hand, cybercriminals may cause serious harm. This is a descriptive-quantitative research employing two of deep thinking and survey study methods and different tools (interview, observation, questionnaire, and document review) for data collection. Its statistical population includes the investigation of cyber incident logs over the recent year, and no special sampling has been carried out. After presenting the model, the usual simulators, particularly MATLAB, are utilized based on the project needs and the results are reviewed according to the execution speed. The system designed to detect various criminology types caused by cyber incidents on the Internet is expected to have high flexibility and to be applied to other types of websites.