abbas toloieashlaghi

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.

In this article, a sustainable network of distribution of agricultural items with suppliers, distribution centers, and retailers is considered. The main purpose of presenting the mathematical model in this article is to determine the optimal number and location of suppliers, assigning suppliers to distribution centers and optimal routing for the distribution of agricultural items to retailers in a predefined time window. Also, determining the optimal amount of inventory and the reorder point in retailers and distribution centers is another problem decision. To model the problem, some parameters of the model were considered non-deterministic and were controlled by the probabilistic fuzzy method. The results of solving numerical examples in different sizes showed that with the increase of the total costs of the distribution network of agricultural items, the amount of greenhouse gas emissions decreases, and the employment rate increases. Also, with the increase of the uncertainty rate, due to the increase of the real demand and the change in the optimal amount of production, distribution, storage and reorder point, the values of all the objective functions also increase. It was also observed by solving different numerical examples with NSGA II and MOGWO algorithms, these algorithms have been able to solve the problem in a much shorter period than the epsilon constraint method, and comparison indicators such as NPF, MSI, SM, and computing time show These algorithms have a high efficiency in solving numerical examples of the problem of the distribution network of agricultural items.

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.

due to the heterogeneity of the behavioral factors in shareholders' decision-making, the most important concern of shareholders is choosing the stock portfolio that can get the highest return.Iran's stock market has always faced severe fluctuations, and this is the most important factor in the decision of shareholders in choosing stocks. Being aware of the effects and predicting the price trend of stocks before choosing a stock portfolio helps shareholders to reduce losses or increase returns.

The main objective of this research was to create a stock portfolio in accordance with the Iranian stock market in such a way as to be able to simulate different scenarios.

stock portfolio selection is one of the areas that can help shareholders better with factor-based modeling tools.In this research, focusing on modeling capabilities based on factors, shareholders, tradable securities including 20 symbols from different industries have been modeled.

Agents sell in this artificial market in each trading period in accordance with the trading strategy and the accepted learnings.In order to check the validity of the model, the statistical output of this market was approved by experts, professors and managers of the capital market and its validity was confirmed.

Despite the factors with variable behaviors, it is possible to form a stock portfolio for each group that leads to the relative satisfaction of the shareholders.

Developing a robust platform architecture can give companies a competitive edge and enhance product future generations and customer satisfaction. However, in order to develop a product platform architecture, there is a need for some kind a product variety design that concurrently manages costs and the supply chain process, and focuses on ease of use and improved availability to components. In this research, the design for variety (DFV) approach and two indices, generational variety index (GVI) and coupling index (CI) are used to measure a product architecture. Using the quality function deployment (QFD) and design structure matrix (DSM), design indices for product diversity are identified and ranked. Additionally, the design for variety approach is modeled simultaneously with the concepts of design for cost (DFC), design for availability (DFAv), and design for supply chain (DFSC) to yield a practical mathematical model for the development of the product platform architecture, which aims for product diversity, improved availability, reduced costs, and supply chain management. The case study of the current research is a phased array radar, which is optimized using the latest techniques (genetic algorithm) and MATLAB software to solve the problem. After implementing the model, considering four objectives including total cost, availability, supplier evaluation score (competency) and replaceability (variety), and seven main parameters of the model, sensitivity analysis and other comparisons and results are presented, which analyzes the relationships between objectives, the impressment and affectability of objectives and model parameters on each other. Regarding the comparison of objectives, the results generally show the inverse relationship between the total cost objective and the other objectives, and the direct relationship between the other objectives with each other. Additionally, the results of the sensitivity analysis performed indicate that the availability objective had the highest effect and replaceability (variety) and the evaluation score of suppliers (competency) and total cost also took next place.

Driving behavior refers to a set of relatively stable, observable, evaluation and prediction actions and reactions of humans in the field of traffic and the use of transportation devices, which, due to external stimuli, affect how they and other road users travel and can have positive or destructive effects on have traffic flow. In this research, attention has been turned from a linear view of the problem to a non-linear and multifactorial view. This research seeks to investigate driving behavior using simulation based on system dynamics approach. The main goal of the article is to present the practical model resulting from the design of driving behavior in Tehran. In order to achieve this goal, by reviewing the literature and reviewing the documents, the key variables of driving behavior were identified and based on this, the dynamic hypotheses of the model were formulated. In the following, the cause and effect and state-flow diagrams were drawn and the equations related to the relationships of the model variables were extracted. In this research, the opinions of experts in different executive departments were used in the form of semi-open or closed interviews. The main part of the required data has been collected and analyzed from the existing data banks in the traffic-related units of Tehran. In the end, after testing the dynamic model using software and wind, different scenarios were proposed to apply the model. The results of the selected scenarios show improvement in variables related to driving behavior.

Today, many fields of research and business deal with the thoughts, images and mental patterns of their users and audiences. Knowing and being aware of the way of thinking of people, customers and audiences of a collection has a great impact on making appropriate decisions by the managers of that collection, in order to advance the goals and solve various problems. One of the important requirements of managers in any collection is to have sufficient knowledge of how they think about the collection and its performance. This helps them guide the group properly and make appropriate decisions in the way of advancing its goals. Therefore, collecting data from customers should be done with measured and accurate methods to achieve high quality information and obtain valid results. This research, by raising the question of "how can you use the analysis of people's feelings to find out how they think about a certain issue?", tries to provide a new approach on the platform of the Twitter social network to obtain reliable and high-quality information from people in relation to a certain topic. The purpose of the current research is to provide a new approach to collect data from people, in order to measure their perception about a specific issue. It will also examine the impact of the presented method on the speed, quality and cost of collecting data from people using a case study approach.

In this research, their comments on the social network Twitter were used to check the satisfaction of users of three internet taxi applications in Iran, namely Snap, Tapsi, and Carpino. The data collection approach used in this research was descriptive, with results used by users, managers, and researchers. The research population consisted of all users of the three applications and members of the Twitter social network who had published their thoughts about these applications. The research collected and analyzed a total of 682 relevant tweets cross-sectionally during the summer of 1400 using the Twitter application interface and related hashtags. The analysis steps included data collection, pre-processing of tweets - including linguistic, sentiment, and thematic analysis, followed by sentiment analysis.Discussion and

The comparison of the analysis results from this research to the face-to-face interview method showed that the participation of respondents was challenging, and the traditional field method came with its own disadvantages. However, this method is able to overcome those issues and provide reliable results at a lower cost and time. Moreover, the results obtained from analyzing the data collected were similar to the results obtained through the face-to-face interview method, which speaks to the accuracy and quality of the data. Overall, the proposed method can provide valuable insights into people's thoughts and opinions on a particular topic, at a lower cost and time.

The proposed method can be widely applicable to various fields, including business, research, and even everyday life. Managers, researchers, and business owners can use it to collect data and insights from their target audience, which can be analyzed to make informed decisions. Further development of the method can lead to even more useful and accurate reports, helping individuals and businesses stay ahead of their competitors. All students and researchers dealing with data collection can use this method to conduct their studies more effectively. Additionally, market research companies can use it to gain valuable feedback from consumers, informing their next steps in providing products and services.Overall, the applications of this research are far-reaching, and it provides a valuable resource for individuals and organizations looking to better understand their audience.Keywords: Sentiment analysis, text mining, how people think, Twitter, Internet taxi.

The current article examines the trends and performance of research on the types of effects of the COVID-19 epidemic and the different management strategies of perishable goods supply chain disruptions during 2 years (2020-2022) using bibliometric and network analysis based on the data set from the Scopus database using VOSviewer software. The analysis designates that Kumar A. has been the most influential author in perishable goods supply chain research during the COVID-19 pandemic, and India has contributed the most in this field. The most repeated keywords were resilience, food supply, and perishable food supply chain. Citation analysis indicated that resilience and sustainability are the mainstream of research in articles with high citations. The network analysis also disclosed that resilience and sustainability are the key themes in the clusters. Furthermore, strategies for managing disruption during the COVID-19 pandemic were extracted from the highly-cited articles, which are presented in this article.

Collecting data from users using conventional traditional methods, in order to achieve a specific purpose, is often expensive, time-consuming, and accompanied by disadvantages affecting the research results, the aim of the current research is to provide a model based on gamification in order to obtain the way of thinking of people through a case study of internet taxi applications in Iran (Snapp, Tapsi, and Carpino).

Research is applied in terms of aim and descriptive in terms of nature. Data collection was done by a researcher-made questionnaire, whose validity and reliability were confirmed based on expert opinion and Cronbach's alpha coefficient. The statistical population was all the users of the mentioned applications and members of Telegram, which was 180 people as a statistical sample.

Comparing the results to determine the popularity of brands in the two methods was almost the same, in addition, the cost and time of using the proposed method was significantly less and the percentage of audience participation was higher.

By presenting the proposed framework, the limitations of common data collection methods were removed and more accurate and higher quality data were used to understand people's thinking, it is also possible to use this method for all researchers.

The purpose of this study is to identify the key success factors of the BOT method in financing the country's service projects and to present an operational model. This research is applied in terms of purpose and survey in terms of explanatory nature. The research sample is 220 individuals and legal entities related to carrying out projects in this way. The required information was collected through a researcher-made questionnaire, considering the census method, and analyzed by modeling structural studies. The dependent variable "Success of BOT method" is measured using three indicators and the independent variable "Key factors" is measured through forty-one indicators. The results showed that the key effective factors in order of effectiveness are; Financial, public, market, technical, legal and institutional factors. Finally, by using the obtained results and the extractive operational model, suggestions have been presented in order to remove the existing obstacles and increase the success of applying this approach in the service-oriented sectors, especially in the field of sports in Iran.

The purpose of this study is to combine two methods of data envelopment analysis and neural network in order to provide an optimal model for ranking inefficiency factors in the Iranian banking industry. First, through the study of theoretical foundations and interviews with banking experts, efficiency evaluation indicators in the banking industry were identified and finalized. In order to evaluate the efficiency of the units in the statistical population of the study, data envelopment analysis technique was used, especially the modified goal programming data envelopment analysis model, which was identified from 32 managements, 3 efficient managements and 29 inefficient managements. Then, the branches of inefficient management were evaluated and using the information of inefficient branches, the neural network matrix was prepared to identify the causes of inefficiency and the results were analyzed with different neural network models. The model with the lowest mean square error will be selected as the optimal model to determine the inefficiency factors. As a result, the self-organized mapping model with hyperbolic tangent transfer function and 0.9 momentum training rule was selected. By analyzing the sensitivity of this method, the indicators of provincial liquidity share, personnel distribution and operating costs were selected as the most important factors of inefficiency.

Nowadays, organizations need an efficient supply chain and proper supply chain management to face global competition. The steel industry is considered the most strategic industrial good in the world because of its large impact on the economic and industrial development of countries. Paying attention to the supply chain of this industry, as the fundamental industry is crucial because of its key role in the national economy and the welfare of communities. This research aims to provide a dynamic system model for the country's steel supply chain to help policymakers and managers to have more effective management in the industry. To present the model, causal rings are drawn by the association of steel industry experts and then modeled by VENSIM. Following are the required tests for model validation. Scenario-based simulation results show that a ±20% change in the two model parameters that reflect technology growth and investment coefficient will have a significant impact on the achievement of the goals.

The ability of ambulance centers to respond to emergency calls is an important factor in the recovery of patients' health. This study aimed to provide a model for the establishment of emergency relief in the road network in 2020 in East Azerbaijan province.

This applied-descriptive and experimental research with an explanatory modelling approach used the comments of 70 experts to run a model, which was based on the use of a metaheuristic (genetic) algorithm ,Simulation for the number of ambulances and the composition of the monitoring list simultaneously , objective and subjective data combined ,the agent and environmental variables, were determined and modelled through a meta-hybrid approach during the agent-based simulation and the metaheuristic algorithm.

To travel the initial structure for 40 dangerous points and five stations, the initial time was equal to 7860 Minutes, which reached a number between 2700 and 4000 Minutes after genetic optimization, production of a new list, and the mutation of ambulances from one station to another.

This type of optimization can be used to accelerate activities and reduce costs. Due to the dissimilar traffic of the areas, the ambulance does not arrive at dangerous points at equal times. The travel time of all dangerous points can be reduced by changing the location of points, moving forward or backwards depending on the conditions, customizing the features of ambulances and dangerous points, and combining the list of areas to find the best location for emergencies according to the interaction between agents, environmental constraints, and different behavioral features.

"Choice" is the key feature of life in the modern era, and people make their own lives with their choices, which makes them and their ways of life different. Humans make their own lifestyles with their choices, and each person shows their unique identity to others through their lifestyle. An important factor manifesting the lifestyle of an individual or family is "consumption". This article attempts to understand the dynamic mechanism of the household and community consumption lifestyle through its conceptual modelingresearch.

. For this purpose, it divided Iranian households' consumption into educational, biological, media and cultural categories, described the dynamic mechanism of each of these four types of consumption  (with an emphasis on educational consumption) as the subsystems of the household consumption lifestyle pattern, and finally presented its dynamic conceptual model and explained its mechanism through the dynamic system approach.

Finally, it came to the conclusion that household consumption follows a dynamic mechanism and different consumption types combine differently at different income levels. The composition and position of the consumption types indicates the dominant approach to consumption, its importance, and household consumption tendency.

This model can be used in cultural policy making affairs in order to create a cultural community.

The purpose of this study is to provide a model for the sale of new goods through the one-to-one marketing method. Since in applied research, the main goal is not only scientific discovery, but also to test and study the application of knowledge, so the method of this research is applied in terms of purpose and has been done by exploratory method. The data collection method is mixed (quantitative and qualitative) and the data collection tool is interviews with experts by conducting specialized interviews in Delphi method and a questionnaire. Therefore, 375 people from the market of selling new goods by one-to-one marketing method (in the quantitative section) and 17 experts and specialists in this field (in the qualitative section) participated in this research. The collected data were analyzed by descriptive and inferential methods through SPSS 16 and Smart PLS software. The results showed that the components of the model of selling new goods through one-to-one marketing include method systematicity, technology orientation, design orientation, market orientation, resources use, the basis of efforts for new goods, conceptualization of new goods, and finally new product management; the model has a good fit and all its relationships are significant. Therefore, it can be concluded that this model is valid.

In this paper, risks in oil construction projects are identified, analyzed and considered for buffers in system dynamics modeling. To do so, all important and effective variables and risks within an oil construction project are determined, including internal and external variables and then, conceptual model is developed using system thinking approach. Based on the conceptual model, state and flow model is obtained and the relations between variables are established. In order to show efficiency and effectiveness of the proposed method, a real case study is considered and solved. Moreover, sensitivity analysis is provided, by using real data and this model. The primary goal of this research is to investigate the impact of different risks that exist in oil construction risks on key variables; these key variables include human resources, facilities and materials. The results demonstrate that the initial plan of each resource is not consistent with the actual need of them. In other words, based on the existing risks in the model, the proposed approach determines what level the actual resources requirement would be placed at and given existing risks, which buffer should be considered for each resource. Furthermore, the impact of risks in performing activities is forecasted and the model shows what impact the risks have on the delay in initial progress of the project as time passes. Finally, it is studied how changes in key and input variables affect the all project.

Due to the separation of teachers and students in the online teaching system and not receiving the moods of learners and applying appropriate feedback, this study seeks to design an intelligent system that can first detect learners' emotions remotely and then suggest educational scenarios to the teacher. Increases positive emotions and reduces negative emotions in learners. This research was conducted in 1998. The study population is the tenth grade mathematics students of Farzanegan 7 High School in Tehran. The students were divided into 5 groups of 15 people, each of whom was exposed to one of the situations of happiness, anger, fear, despair and sadness, and their facial information was received and recorded through a webcam. Data analysis in this study was performed by data mining method by Clementine software. By comparing the change in the range of emotions recorded before the implementation of the training scenario and then by data mining method with the help of Cummins algorithm that first clustering and then classification The results show that after the implementation of educational scenarios, changes were made in the ranges and increased the mean of positive emotions and decreased the mean of negative emotions.

Data envelopment analysis is used as a suitable tool to estimate the efficiency of companies that use production technologies with multiple inputs and multiple outputs. Classical data envelopment analysis models often do not provide accurate information about the status of units to managers and organizational policymakers due to the low resolution of units. In this research, the basis of the BCC model is the output oriented of data envelopment analysis and in order to increase the discriminate of efficient decision-making units from inefficient, the ideal data envelopment analysis model based on BCC was used and then to increase the resolution Decision Making Units A new model called the Modified goal Programming Model of Data Envelopment Analysis based on output-oriented BCC was used to measure performance. In this study, the management of Ghavamin Bank branches across the country was evaluated. The results of the research show the discriminate power of the modified goal programming model of data envelopment analysis based on output-oriented BCC compared to other data envelopment analysis models. So that out of 32 managements under review in Ghavamin Bank, the management of branches in the west of Tehran was identified as efficient using this model and the rest of the managements were found to be inefficient.

Innovation is the corporate vitality and strategic pivot that plays an important role in the survival and prosperity of companies. Small and medium-sized enterprises are less active than large companies in open innovation due to their specific characteristics. The purpose of this article is to present a model of partnership structure for open innovation in small and medium-sized enterprises.

The present study is an exploratory study and in terms of type of use, is functional and the questionnaire has been used to collect data. In order to conduct research, 57 questionnaires were completed by experts working in small and medium-sized enterprises producing goods and services of ICT students. And by using the dynamics of the system, the design of the model has been addressed. The horizons of the research are from 1392 to 1397.

In this research, by designing an appropriate partnership structure, we seek to increase the aggregate profit of the network and the new small and medium-sized enterprise. In different scenarios, the behavior of the main variables of the model and the variables controlled by the partners and the network are discussed and their results are presented in the form of diagrams.

Research results make it possible for companies that create a collaborative structure for innovation by studying the investment in each of the cases affecting the model, analyze the changing trend of network profits.

Today, the important role of transportation in sustainable development programs is undeniable. Many experts believe that the more efficient the transportation is, the more inclusive it is. In contrast, inefficiencies in the transportation system will have serious environmental consequences, such as air pollution and adverse social and economic consequences. In this regard, the purpose of this study was to design and simulate a dynamic suburban public transport system using anfis and Dijckstar's algorithm. The method of this research is from the point of view of purpose, developmental - applied, and from the point of view, analytical - descriptive. Both library and field methods have been used to collect data and research information. In present study, using simulink software and using matlab functions, two simulation models of the current system and the proposed system of public transportation were designed and implemented for a week. With the goal of more closely related reality simulator, the network-based fuzzy inference system to estimate traffic volume,the c-mean fuzzy clustering algorithm to determine the number of passengers referring to the terminal of each city, and finally the Dijckstar's algorithm for routing Travelers are optimized from origin to destination. In the following, the results of the two simulation models were compared. According to the results in the proposed system, the amount of passengers used by the bus from the bus increased by 8.2%, the use of bus capacity increased by 12.66%, and the total amount of fares paid by passengers decreased by 17510 USD.

This study provides a dynamic behavior analysis of roadmap development for enhanced oil recovery (EOR) technologies based on system dynamics in order to reduce domestic R&D costs. The key variables and causal-loop diagram were identified via expert opinion and data. The mathematical relationships amongst variables were identified based on background research and in approximately two years, a mathematical model of the system was developed using computer simulations in VENSIM. The results indicated two types of damped oscillation and goal-seeking dynamic behaviors for model variables. Further, the dynamic hypotheses testing indicated that increased technological maturity and education reduces costs while increased technologic complexity would increase the costs. The best scenario was identified as a combination of highly-mature technology, high complexity, and high education level as it leads to minimum costs.

Today supply chain network is recognized as the main bases in economic activity. Their significance is due to just in time delivery and the efficiency of different commodities including food, clothing, energy, computer hardware. This has stimulated researchers and experts to analyze supply chain problems. Meanwhile, uncertainty has penetrated every level of our lives and we encounter it every day. The present paper focuses on green supply chain that consider uncertainty conditions to solve a model for designing a forward green supply network (environmental)under uncertainty of future economic conditions in Iran Khodro Company. The problem of designing the aforementioned network includes hypotheses including multi-commodity, multi-layer and one-period. Due to inconsistent economic conditions, uncertainty has been differently tackled here as compared with previous literature. In this problem, several important parameters have been considered as indefinite including customers’ demands, operating expenses, the productive capacity and relocating capacity of facilities. The proposed model also considers the contamination of production section and the transportation system of the chain and tries to reduce it by suggesting an objective function and Eco-indicator 99 method. As well, production and distribution centers operate in a dual-purpose manner. Saving costs and reducing contamination due to applying transportation supplies and common infrastructures are among the benefits of this method. Considering the complexity of solving this problem and its NP-hard nature, the meta heuristic method of genetic algorithm with non-dominated sorting (NSGAII) was analyzed and finally model performance was examined with a numerical example and solving it with MATLAB and GAMS software.

In this research, production planning and the amount controlling of inventory have been as effective factors in the process of reverse supply chain in flow returned products from customers to producers. Also, as the amount of recoverable as well as recycling returned products factors are in uncertainty and probability condition; therefore, a model which is enable to meet customers ‘needs in terms of least delay time, high flexibility and low cost of supply chain is necessary. The results of multi objective mathematic model is to meet and optimize different objectives as increasing profitability, decreasing cost, decreasing the environment pollution, scrap and processing time. Considering that the reverse supply chain problem is categorized in NP-Hard problems which are not easily solvable by Gradient methods thus other methods like Genetic Algorithm for optimizing production planning and inventory control in reverse supply chain was used.

One of the difficult tasks in management is decision making. To accomplish all phases of decision making process, all criteria must be measurable and quantitatively available. Because information technology, according to its intangible nature, has a broad range of definitions and generally undetermined indicators some of which are qualitative, there is no certain criterion to measure it. This paper aimed to consider all aspects of information technology. Indicators of information technology have been set in four main groups and in each of them, themain criteria and related sub-criteria are defined. As qualitative and quantitative criteria cannot be measured certainly and accurately, the fuzzy systems (FS) are utilized to assess the magnitude of any indicator. To do so, after creating the matrix of decision-making, weights assessment techniques in multi criteria-decision making (MCDM) have been used and then a model for measuring in order to gain points for a unique level of information technology is provided. The method used to assess the weights is “grouping” that is one of the decision-making techniques and the method of measurement is fuzzy simple addition weight (FSAW). Points earned, indicate the level of information technology in the organization. According to the implementation of the model and examination by experts in this field, designed model was approved and is applicable in all organizations that have IT units.