جستجوی مقالات مرتبط با کلیدواژه "زنجیره تامین" در نشریات گروه "علوم انسانی"

The purpose of this study is to identify the threshold of systematic and non-systematic risks to the supply chain of oil, petrochemical, and chemical industries. The period of this research is 2011-2021. This research has two communities. The first society is the experts in the petrochemical and chemical industries, and the second society is the active firms in the petrochemical and chemical industries on the Tehran Stock Exchange. In this research, 99 risks affecting the supply chain of oil, petrochemical and chemical industries were investigated in the form of two categories: unsystematic risk factors (77 indicators) and systematic risk (22 indicators). Based on the expert’s opinion, using the Delphi-fuzzy type 3 approach, 23 unsystematic risk indicators and 13 systematic risk indicators were selected. Based on the principal component analysis approach, systematic and unsystematic risk components were extracted from the selected variables. The results of the PSTR model between the supply chain and systematic risk (0.353 negative impact above the threshold; 0.218 positive impact below the threshold) and unsystematic risk (0.413 negative impact above the threshold; 0.237 positive impact below the threshold) confirmed the behavior of the threshold.

The purpose of this research is the value-added model of the supply chain of petrochemical industries with a sustainable development approach. According to its purpose, the research method is practical, qualitative-quantitative in terms of implementation, and survey in nature. The statistical population of the research includes 25 managers and experts in the petrochemical industry, and the sampling was done as available judgment, and the interviews continued until theoretical saturation was reached. The tool for gathering information is an interview. To collect and analyze data, Delphi technique was used to identify components. MATLAB software was used for data analysis. In the library analysis, 16 main components were identified and entered into the Delphi technique, and finally all were confirmed. These sixteen criteria are political factors, cultural factors, legal factors, financial factors, individual factors, management factors, information sources, implementation, review, feedback analysis, performance evaluation factors, risk concepts, identification of environmental issues, identification of health issues, learning Issues of safety and added value in the supply chain of petrochemical industries with a sustainable development approach. Based on interpretive structural technique, these components were leveled. And they formed a model in 7 levels. The proposed model leads to the improvement of the economic and commercial performance of companies due to optimization of processes, reduction of wastage, improvement of product quality and reduction of costs. Considering the variety of issues such as safety, health, environment and social standards, this value-added model of the supply chain helps to realize sustainability and continuity.

The supply chain of machine-made carpets has faced several fluctuations in recent years. One of the most important fluctuations is the bullwhip effect. Future study of bullwhip effect in the supply chain can prepare decision makers to deal with possible scenarios. This research has been carried out in the Iranian machine-made carpet industry.

Future study of the bullwhip effect in the supply chain of Iran's machine-made carpet industry

The statistical population of this research is the experts of Iranian machine carpet industry who have been selected by judgment and snowball method. Theme analysis was used to analyze the interviews and Micmac and Scenariowizard software were used for future study.

The results of the interview showed that there are 10 drivers for bullwhip effect in the supply chain, 9 of which were selected as important drivers by Micmac software. Out of 1152 possible scenarios, 3 scenarios were consistent, which are a favorable scenario, an unfavorable scenario and a median scenario.

Finally, suggestions such as reducing start-up time, improving demand forecasting methods, changing the replenishment policy, volume-based discounts instead of batch-based discounts, and vendor inventory management were presented to achieve the desired scenario and avoid the unfavorable scenario.

The primary objective of this research is to design a sustainable supply chain agility model in the oil and gas industry of Bushehr Province. This study employs a mixed-method approach (qualitative-quantitative), content analysis, the fuzzy DEMATEL technique, and the Analytic Network Process (ANP). The statistical population consists of managers, officials, and mid- to senior-level experts from companies operating in the oil and gas industry of Bushehr Province. A sample size of 10 managers, experts, and industry specialists was selected for each stage. The qualitative findings revealed that sustainable supply chain agility indicators are comprised of environmental factors (green purchasing, eco-friendly and economic design and packaging, environmental preservation), economic factors (adoption of information technology, responsiveness, speed, competence, flexibility), and social factors (customer collaboration, ethical purchasing, social responsibility, compliance with laws, integration of relationships, and supplier collaboration). In the quantitative section, the first stage using the fuzzy DEMATEL approach showed that environmental factors fall under the category of effect criteria, while economic and social factors fall under the category of cause variables. ANP findings indicated that among the environmental factors, the green purchasing indicator holds the highest weight (0.33), followed by the environmental preservation indicator (0.087) and eco-friendly and economic design and packaging (0.086). Among the economic factors, the speed indicator has the highest weight (0.0524), followed by flexibility (0.0513) and competence (0.0505). Among the social factors, the customer collaboration indicator (0.0439) and compliance with laws (0.0438) have the highest weight.

The enhancement of defensive deterrence requires the improvement of the methods, tools and processes utilized by defense industries. This in turn, is contingent upon the engagement of new and diverse economic-industrial capacities, capabilities, and methods nascent in the defense ecosystem of the country. The scope and breadth concepts developed in the field of defense economics has rendered improving the performance of the supply chains of the defense industry a topic of discussion among theorists in this field.  Currently, the expansion of the supply chain of organizations has encouraged theorists to turn towards new methods and technologies for improving performance. The block chain technology has recently received attention due to some of the features that it possesses. Therefore, the objective of the present article is to assess the feasibility of utilizing blockchain technology for managing the supply chain defense industry. Additionally, the study purports to assess the feasibility of developing the capabilities of this technology based on the needs of Iranian defense industry. For this purpose, the modus operandi of this paper first relied on employing the Delphi method for identifying the relevant performance criteria with regard to the utilization of the blockchain technology for the defense industry supply chain. Subsequently, semi-structured interviews with experts in the field were held to assess the feasibility of their usage with regard to each of the key criteria identified.The results of the surveys showed that the key main features of a suitable supply chain for the defense industry are quality, speed, cost, flexibility and innovation indicators. Importantly, the study finds that the application of this technology can play a role towards improving the indicators of the aforementioned criteria. Finally, the paper concludes that it is possible to utilize blockchain technology in the defense industry of Iran.

Considering the necessity of flexibility in the supply chain to manage uncertainties, this research aims to design and explain a flexibility process model for the financial supply chain in Iran's car leasing industry. 

The research method is a mixed-methods exploratory approach. First, 21 qualitative interviews were conducted. Using grounded theory, a financial supply chain flexibility model for Iran's automotive leasing industry was developed, comprising 24 sub-categories within six main categories. Next, 260 questionnaires were distributed and completed in automotive leasing companies in Iran. Structural equation modeling was then employed to conduct a path analysis of the hypotheses concerning the relationships among the model dimensions, and the validation of the model was assessed in the study.

Based on the data analysis, the causal conditions of flexibility include "expectations related to customers," "factors related to suppliers," and "motivations related to financing." The contextual factors contain "legal-regulatory factors," "financial-economic factors," "environmental factors," and "cultural-social factors." The intervening factors of financial supply chain flexibility include "ownership and shareholders of leasing companies," "communication and IT-related factors," "industry systems and infrastructure," and "transportation and logistics." The phenomenon of financial flexibility in the supply chain was defined as "financing solutions," "effective communication of supply chain elements," "factors related to the ability to credit," and "proper risk management." Additionally, the strategies for the flexibility of the financial supply chain cover "innovation and development of new products," "development of sales network and after-sales services," "development of training and service skills," and "development of cooperation between supply chains." The consequences of financial flexibility in the supply chain of leasing companies encompass "increasing the production of automotive products," "increasing the level of access to services," "easier access to financial resources," "improving the circulation of financial information," and "increasing the efficiency of the supply chain." In the quantitative part of the research, based on the results of structural equation modeling and path analysis, it was found that intervening factors affect the antecedents and strategies of flexibility. The antecedents of flexibility have an impact on attention to flexibility. Besides, dimensions such as contextual factors, attention to flexibility, and intervening factors significantly affect strategies for financial flexibility in the supply chain, which ultimately affect the consequences of financial flexibility.

To enhance the flexibility of the financial supply chain, it is advisable for companies to draw insights from successful product development experiences. Additionally, efficient management of after-sales services, building trust and establishing effective communication with customers, and upgrading employees' knowledge, experience, and skills to align with industry developments are essential factors for fostering financial flexibility in the leasing industry.

Improving the financial and operational performance of supply chains requires a strong focus on inventory management. Additionally, implementing financial measures at the operational level is crucial for enhancing overall performance. By establishing effective financial strategies at this level, the efficiency and profitability of the supply chain can be significantly increased. This article aims to apply the Atride-Sterling approach to enhance the financial and operational performance of supply chains.

The participants in this research were supply chain managers with a minimum of 15 years of teaching experience and a master's degree or higher. Participants were selected through purposive sampling, focusing on individuals with teaching experience at the elementary school level. A total of 22 experts participated in the study. Data collection was conducted using semi-structured interviews, which continued until theoretical saturation was reached. Thematic analysis, based on the Atride-Sterling model, was employed to analyze the qualitative data. To ensure validity, Holstein's coefficient, Scott's Pi coefficient, Cohen's kappa index, and Krippendorff's alpha were utilized, all of which were confirmed. Atlas.ti software was used for the thematic analysis.

The results of the thematic analysis indicate that from the 54 available indicators, 13 fundamental themes can be identified, leading to the emergence of two categories of constructive themes: financial performance and supply chain operations. The identified model encompasses these two constructive themes, which include 13 primary themes: inventory management, financial reporting, operational financial measures, coordination, risk management, supply strategy, demand planning, technology management, logistics strategy, customer engagement, flexibility, supplier relationship management, and quality assurance on a global scale. Given the critical importance of the supply chain to organizational success, enhancing the financial and operational performance of this supply chain is essential.

Optimizing coordination between internal and external stakeholders, along with timely logistics management and the sharing of financial information, will enhance productivity, reduce costs, and improve competitiveness. Also, recognizing and managing various risks such as price risk, supplier risk, and market risk, are crucial measures for effectively addressing environmental challenges and seizing opportunities.

In the current era, the competition between organizations has also been transferred to the supply chain. The stability of the supply chain is a necessary and sufficient condition for the stability of companies. The most basic condition for the sustainability of an organization is its profitability. Therefore, the aim of this research is to present a mathematical model based on game theory in order to maximize profit in the closed loop supply chain. The main goal in the closed loop supply chain is to eliminate waste and optimize the consumption of products in such a way that the products are separated into two groups, new product and used product, and there is the possibility of returning used product and reproduced products in the consumption cycle. has it. However, all members of the chain benefit. But the fact is that it is not clear which factors can maximize the benefits of the closed loop supply chain members. For this purpose, in the current research, a mathematical model based on game theory is designed in which cooperation between upstream and downstream members occurs. Finally, it is clear what effective factors such as demand, returned products, recycled products and remanufactured products have on the profit of the chain members. In other words, how can the total profit of chain members and the share of individual members be increased and under what conditions this increase is achieved.
The general results from the analysis of this research show that demand is a factor that can increase the profit of all members of the chain, and returned products have a positive effect on the profit of all members, while recycled products and remanufactured products, in If it increases, it only increases the profit of the reproducer and recycler and reduces the profit of other members significantly at different levels.
In this research, the profitability of the closed loop supply chain has been investigated using game theory and the parameters of demand, returned products, recycled products and remanufactured products affecting the profitability of the closed loop supply chain have been simultaneously investigated. Therefore, the innovation of this research includes the simultaneous examination of demand, returned products, recycled products and remanufactured products affecting the profitability of the closed loop supply chain.

This research was conducted with the aim of investigating the effect of supply chain correlation on sustainable management innovations with the presence of information sharing as a moderating variable and investigating the impact of customer orientation on sustainable management innovations with the presence of information sharing as a moderating variable. This article is a descriptive survey and correlation type in terms of its practical purpose and how to collect the required information. The statistical population of this research is the managers of some companies working in the industrial towns of Zanjan province. The statistical sample based on Morgan's table will be 297 people. Also, random sampling method is available in this research. The relationships between the variables and the investigated components have been modeled using SPSS software and Smart PLS structural equations, and T-test has been used to check the effect of the variables. The results showed that supply chain integration has a significant effect on managerial innovations. Also, customer orientation has a significant impact on sustainable management innovations. Supply chain integration has a significant impact on sustainable management innovations with the presence of information sharing as a moderating variable. Customer orientation has a significant effect on sustainable management innovations with the presence of information sharing as a moderating variable.

LARG supply chain methods consist of lean, agile, resilient and green methods, which are among the most widely used supply chain management approaches in today's world. These methods are used in order to improve performance and increase the efficiency and effectiveness of an organization. Therefore, the purpose of this research is to present a LARG supply chain model in defense organizations.

This research is applied in terms of purpose and exploratory in terms of qualitative method. The information sources of the research are the published scientific articles and documents, as well as interviews with experts of defense organizations, which have been analyzed using the database method (Glaser's Emerging Approach) and with the help of MAXQDA software. The statistical population of the research in the interview phase was 􀀔􀀘 individuals among experts in Logistics and Support Deputy who were selected purposefully and judiciously using the snowball method.

From the analysis of related articles, documents and interviews, 􀀕􀀕􀀖 primary codes were extracted, which were identified in a multi-step process of coding, indicators, components and model dimensions.

The most important factors of the lean, agile, resilient and green supply chain are managerial factors, human resources, resources and equipment, process factors, organizational factors, technical and technological capabilities, in order of priority.

The current research aims at the possible scenarios of the sustainable supply chain in the dairy industry with a future research approach. The method of qualitative and applied research and in terms of data collection is a descriptive-survey research. The statistical population of the research includes 11 expert professors (academic experts), experts and specialists working in the country's dairy industries (industry experts), and independent customers and researchers (public stakeholders). The non-probability sampling method is purposeful (judgmental) and snowball. Effective factors and key uncertainties in the dairy industry were identified by the fuzzy Delphi method, then three compatible scenarios were identified with the help of Wizard Scenario software. According to the findings of the research, the factors influencing the driving forces and key uncertainties on the future of the sustainable supply chain in the dairy industry were identified, which include: foreign trade and communication regulations, the state of competition laws, attention to health and safety issues and standards, attention to Inventory maintenance for each product unit, foreign exchange rate fluctuations, inflation rate fluctuations, the cost of raw material production, the cost of spoilage of dairy products, and the motivation and willingness of private investors to invest in the dairy industry. The results of the research showed that after the possible states for each of the key uncertainties were identified with the help of the Wizard Scenario software, three compatible scenarios were obtained with the titles "prosperous", "realistic" and "incurable". . On the other hand, it was determined that the foreign exchange rate and inflation have the greatest impact on other factors and the future of the dairy industry.

China and the United States, the two economic superpowers accounting for nearly 43% of the global economy, are engaged in a mutually interdependent economic relationship, despite their distinct levels of development and positions within the global supply chain. This interconnectedness has fostered numerous opportunities for the international economy and contributed to the dynamism of the global market. Employing the theory of comparative advantage, this paper examines the nature of this relationship and the positioning of each country within the supply chain. Findings indicate that the mutual economic dependence between these two nations has been shaped by their comparative advantages and has intensified over the past two decades, driven by China's rapid economic growth and increased joint ventures. China is primarily positioned at the beginning of the supply chain, focusing on the production of consumer goods and industrial products, while the United States has solidified its place at the end of the chain, emphasizing design, research and development, and advanced technologies.

Supply chain integration is essential for the efficiency, growth, and economic development of countriestowards gaining a competitive advantage. Over the past decade, there has been a growing consensus onthe importance of establishing integration throughout the supply chain. Discussions related to supplychain management have also been considered one of the most powerful operational paradigms forenhancing the competitive advantage of manufacturing and service organizations (Ebrahim Pour et al.,2015). The literature on product development continues to grow. Product development refers to theprocess of transforming a market opportunity and a set of assumptions about product technology into amarket-available product (Rubera et al., 2016). Acquiring knowledge management entails setting upsystems to obtain internal and external knowledge, such as utilizing raw data or examining new productsof a competitor (Pashaie & Abdavi, 2016). Based on the provided information, sports companies needto preserve their employees' knowledge and should proactively acquire and transfer senior staff'sknowledge to other employees while continuously updating their learning over time. With theincreasing knowledge of citizens, companies are obliged to observe and utilize updated and newlycreated knowledge to compete against rivals. In the current competitive environment, knowledge isconsidered the primary source for producing goods, and their profitability heavily depends on theknowledge applied. Therefore, evaluating the investment value in knowledge is very complex as it mayresult in both disappointment and growth and profit. However, so far, no research has been conductedon the integration of supply chains and the use of knowledge capacities in sports companies. For thisreason, conducting research in this area can help fill this gap and provide suitable suggestions fordeveloping sports products based on supply chain integration and knowledge capacities. Therefore, theaim of this research is to answer the question of what impact supply chain integration and knowledgeabsorption capacity have on the performance of sports product development. The research method isapplied in terms of objectives and descriptive in terms of execution, employing a survey approach. Thestatistical population of the research consists of managers and employees of sports productioncompanies in Iran. To evaluate the model fit and test research hypotheses, 385 individuals wereexamined. Field research and questionnaire tools with random sampling were used to collect data.Structural equation modeling with a partial least squares approach and PLS software were used for dataanalysis. The findings indicate that deep coordination and integration in the supply chain and knowledge  absorption capacity positively and significantly affect the performance of product development. Thesefindings confirm that knowledge-absorption-based integration is essential for achieving the goals ofsports product development. Therefore, we conclude that the absorption capacity of knowledge can beconsidered as a multi-level structure. At the lowest level, the individual level of knowledge absorptioncapacity is situated. At this level, the relationship between knowledge absorption capacity and learningis entirely intuitive. In this context, memory has been mentioned, where previously accumulatedknowledge, the ability to store knowledge, and its retrieval are facilitated. This dynamic process reflectsthe concept of knowledge absorption capacity, where previous relevant knowledge facilitates learningor absorption of new relevant knowledge. Considering the role of information, its search is also ofparticular importance for knowledge management systems. Effective search increases the speed ofinformation retrieval and sharing, enhancing productivity. In other words, employees only utilizeknowledge management systems when they offer excellent performance for searching neededknowledge content. With the development of advanced search capabilities, access to individuals'knowledge doubles. Thus, by using knowledge management systems, the detection of unknownknowledge within the company becomes feasible. Undoubtedly, establishing a customer knowledgebase with the ability to monitor and analyze experiences, opinions, and suggestions recorded in productrecords provides a foundation for product improvement and development. In other words, by enablingfeedback and experience recording for products, product strengths and weaknesses become visible tocustomers for free, and improvement and development solutions are registered in the company'sknowledge base. Given the findings of this research, attention to creating integration among differentelements of the supply chain, along with policies and programs to increase knowledge absorptioncapacity in organizations and sports companies, is crucial. These actions include developingcoordination processes in the supply of raw materials, improving production processes, and increasingthe ability to absorb and utilize technical and managerial knowledge. These efforts can significantlyimprove the efficiency and performance of the sports industry, especially in the development ofproducts and the provision of sports services.

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

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

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

This article was done with the aim of presenting a pattern of analysis of disruptions and resilience of the food supply chain. This study is a cross-sectional survey in terms of its practical-developmental purpose and in terms of the method and time frame of data collection. In order to achieve the goal of the research, an exploratory mixed research design was used. The community of participants of the qualitative section includes the managers of Amad and IRGC support, 17 of whom were selected in a purposeful manner until theoretical saturation was achieved. In the quantitative part, the point of view of 148 managers and experts of food prepared and supported by the IRGC was used. Quantitative sampling was done by cluster-random method. The data collection tools were semi-structured interviews and researcher-made questionnaires, which were validated by construct validity, convergent validity and divergent validity methods. Using Cronbach's alpha and composite reliability, the reliability of the questionnaire was also evaluated. In order to identify the dimensions and components of food supply chain disruptions and resilience analysis, qualitative thematic analysis method, structural-interpretive modeling method was used to determine the relationships of elements, and partial least squares method was used to validate the resilient supply chain model. The findings showed that human resource management, natural disturbance, awareness and economic disturbance affect security and operational disturbance. Security and operational disruption affect robustness, transparency and dummy disruption, and in the same way affect redundancy and cooperation. Redundancy and cooperation also affect agility and flexibility,

Determining supply chain priorities in smart industries with data-driven analysis and modeling methods is essential to achieve sufficient accuracy and identify key factors affecting supply chain efficiency. The use of this information improves the effectiveness of supply chain management. This article investigates and presents a quantitative approach for evaluating the priorities of the smart supply chain using data-driven prediction methods. The main objective of this paper is to provide a systematic and efficient method for determining priorities in the supply chain. In this approach, first, the key efficiency indicators in the supply chain are identified. Then, using data-driven prediction methods based on machine learning, the efficiency of each indicator is calculated for each element of the supply chain. The proposed approach has advantages such as systematicity, flexibility, practicality, and high accuracy. This method helps companies and organizations improve their management decisions by evaluating and determining supply chain priorities, optimizing performance, and enhancing processes.
The innovation dimensions of this research include two main aspects. The first aspect focuses on two widely used industries equipped with Internet of Things (IoT) technology. The second aspect combines traditional supply chain analysis methods with machine learning algorithms. Initially, key performance indicators in the supply chain were identified. These indicators were extracted through a comprehensive search of articles in reputable scientific databases using keywords related to the smart supply chain. Then, using data-driven prediction methods, the efficiency of each indicator for each element of the supply chain was calculated. In this study, the DEMATEL matrix was used to analyze the interrelationships between indicators, and the prediction method using Support Vector Machines (SVM) was applied to assess the relationships between the criteria. Finally, the final weight of each indicator was determined by combining the results of DEMATEL and SVM, and the indicators in the supply chain were prioritized accordingly.
The results of this article show that flexibility is the most important criterion in the supply chain due to its ability to respond to changes and fluctuations in demand. The quality of the products and services provided ranks second, as higher quality increases customer satisfaction and trust in the brand. The total cost of the supply chain is third, and reducing costs improves profitability and competitiveness. Product delivery time is fourth, as fast and accurate delivery significantly impacts customer satisfaction. Finally, supply chain-related risks are ranked fifth, and effective risk management can mitigate potential issues. This prioritization helps organizations better allocate resources and improve supply chain performance.
Using systematic and precise approaches to prioritize supply chain criteria can serve as a practical guide for selecting and determining suppliers, implementing supply chain optimization strategies, and allocating resources. This research demonstrated that combining traditional supply chain analysis methods with machine learning algorithms such as SVM can improve the accuracy and efficiency of forecasting and decision-making. By enhancing the supply chain, organizations can improve their performance and optimize processes. Moreover, approaches such as Just-In-Time (JIT) strategy, Total Quality Management, and the use of new technologies can contribute to supply chain improvements. Building relationships with suppliers, analyzing data, and forecasting supply chain needs and challenges are also useful strategies.

Customer satisfaction is the most decisive factor in marketing success; therefore, companies and organizations must correctly identify and understand the needs, tastes and expectations of their customers so that they can produce a product with maximum value and deliver it to Effectively price, distribute and promote. In general, accurate understanding of consumer behavior, especially at the moment of final selection of products, can help companies in making major decisions and achieve the organization's high goals. The purpose that led to this research was to design some patters through which the factors and how to persuade buyers in industrial marketing can be achieved. These patterns obtained by conducting research on small and medium-sized companies that buy food machinery in Afghanistan. In order to be able to provide the most appropriate machines to this target market by using that pattern, in order to satisfy these buyers, it is possible to penetrate this market as much as possible for the manufacturers of food production machines in the country of origin (Iran) to be provided.

This research was conducted qualitatively and using the data method of the Glazer Foundation. The reason why the foundation data method was used in this research was that there was no appropriate pattern for the target community that was addressed and that there were not many patterns in the field of persuasion in general in industrial marketing. Therefore, it seems that there is a need to present three patterns in this field. Based on this, first the interview questions were designed in line with the main research questions. Then the statistical sample was selected in a selective way and according to different branches of food industry. By identifying the communication channels, the interview with these producers was provided, and the interviews continued until theoretical saturation was reached.

By analyzing the data obtained from these interviews, it became clear that six main factors have a key influence on persuading buyers in the food industry machinery market in Afghanistan. These six factors include; The first factor is the cost, which includes all the costs that a person has to identify, choose, compare products to purchase and use, repairs and parts. This factor is mentioned by all the activists as an important factor. The second factor is reliability. This factor represents the things that make the machinery supplier a trusted image in the minds of the users of these products. The third factor is the technology used in these machines and the simplicity of its use. Ease of use and no need for foreign experts are important factors in this factor. The fourth factor is expertise, that the supplier of the machines in question has sufficient expertise in all fields related to the production of these machines. The fifth factor is the complete elimination of the need. in such a way that it can provide a complete set of machines needed to produce the desired food. It means that the company can meet its zero to hundred needs for machines from one supplier. The sixth and last factor is geographical distance. This factor was more common in food producers who were engaged in production in Herat city. Ease of access to machinery suppliers and communication has been one of the important factors in this factor.

This research can claim to add to the scope of knowledge in two major areas; The first field of research is about persuasion in industrial marketing. This can have various reasons, but it seems that there are stronger reasons to pay more attention to industrial marketing. The size of the market, the amount of expertise required for better performance in this sector, much bigger results in case of success, high costs in case of failure, etc., these are all reasons that make it reasonable for researchers to pay attention to industrial marketing. The second area that makes our research valuable is working on the target society, which has been less worked on, and on the other hand, because it is one of the important markets for the export of Iranian goods, the information obtained from it is also scientific. And it will be very valuable in terms of market needs. In general, industrial marketing has received less attention than consumer marketing. The results of this research can be useful both for the buyers of these machines in Afghanistan and for the manufacturers of food industry machines in any country that intends to export these goods to Afghanistan.

EXTENDED ABSTRACT
In the bargaining process, most people follow their usual procedures when faced with issues and disputes and seek to find a solution that satisfies the interests of the parties. But in this process, problems such as lack of effective interaction, instability of decisions, lack of clarity in the understanding of parties and specialties are often seen. Bargaining and negotiation in the supply chain are essential components of decision-making processes that have wide-ranging implications for various individuals engaged in the global business landscape. With increasing emphasis on achieving fair outcomes and efficient allocation of resources, the application of game theory, especially the Nash negotiation solution, has attracted more attention in the field of supply chain negotiations. As global markets become more complex and intertwined, understanding the dynamics of supply chain negotiations is essential for organizations to optimize their operations. In dealing with complex issues and a large number of people and different aspects, Nash negotiations allow the parties to reach agreements that satisfy all parties in the shortest possible time. The Nash negotiation solution developed by Nash (1950) provides a powerful framework for analyzing negotiations and incorporates the concept of "fair sharing" between the parties involved. This tool has proven to be valuable for modeling and understanding negotiation processes in supply chains. By considering individual preferences, relative negotiation power and feasible agreements, Nash's negotiation solution tries to establish optimal and fair results. Understanding the application and implications of the Nash negotiation solution in supply chain negotiations can provide valuable insights in reaching mutually beneficial agreements and enhancing cooperation between supply chain partners. However, in the field of negotiations and bargaining, there have not been enough studies and researches regarding the use of the "Nash" negotiation solution; Therefore, the main purpose of this research is to use the solution of "Nash" negotiations to improve the bargaining process, so that by examining the effects of "Nash" negotiations on the quality of decision-making, the psychology of people and the agreements reached, a pattern of improvement and improvement in the bargaining process in the supply chain can be obtained.
From the perspective of the research strategy, this research is a qualitative method, and from the perspective of the paradigm, it is classified as an interpretive paradigm. In this method, the researcher uses the method of qualitative data analysis, which is specifically used in this research, to make patterns. The meta-synthesis research method is one of the types of meta-study methods and is considered a qualitative research method. In fact, meta-synthesis is a type of qualitative study that uses the information of findings extracted from other studies in the field of a related topic. In the meta-synthesis method, the researcher combines the secondary data of the results of other studies to respond to the results of his study and obtains new results. The current research includes two primary stages: initial planning and implementation of a systematic review, followed by reporting and publication of findings, and finally a model that shows the improvements that can be made in the supply chain bargaining process by adopting Nash's approaches with the meta-synthesis is presented. In order to achieve the goal of the research, the seven-step method of Sandelowski and Barroso was used. Sandelowski and Barroso's method is a structured model for qualitative text analysis and extracting concepts. This method uses a seven-step model for document analysis. The main method of data collection is also library studies.
 In order to evaluate the reliability of the interview, the within-subject agreement method was used with a two-pass code, in which a researcher colleague (coder) who was a PhD student registered. Collaboratively, the researcher and research associate coded the four articles and subsequently calculated the percentage of within-theme agreement, indicating the agreement between the two transfer codes. To facilitate the coding process and save time, a checklist containing two values (yes/no) was used to cover the entire task or all necessary items. When the opinions were obtained through the formula presented below, the kappa coefficient of agreement was calculated, a numerical value between 1 and +1. A rate close to 1 indicates high reliability, while a rate close to -1 indicates disagreement and a rate close to zero indicates no reliability. A kappa coefficient between 0.6 and 0.8 indicates good reliability. In the context of the current research, a part of the article was presented to two professors and based on their evaluation and comments, the kappa coefficient (K) was calculated using the P0-PE formula divided by P0-1, and its value was 0.84. The results showed that there was a total of 6 dimensions, 18 components and 90 indicators that showed changes in terms of repetition and frequency.
The findings of this study showed that Nash negotiations are effectively able to form agreements that support a fair balance between the negotiating parties. This equality resulting from Nash solutions, in addition to strengthening long-term cooperation, also plays a role in reducing potential negotiation tensions. Structuring the negotiation based on the theoretical framework of Nash negotiations paves the way for the development of more favorable and insightful relations between the parties. Psychologically, Nash techniques can help reduce negative emotions and increase mutual trust. Negotiators who feel their interests are properly understood and established are more willing to cooperate and enter into long-term contracts. This issue not only affects the individual relationships between experts, but also has an effect on the entire structure and performance of the supply chain. Nash solutions also improve the quality of decisions. By focusing on sustainable and win-win outcomes, parties are more motivated to explore innovative and progressive solutions. Innovative perspectives can lead to improved processes, reduced costs, and increased efficiency and effectiveness. At the theoretical level, the application of Nash solutions in this study has benefited from the realistic simulated dynamics that we have achieved a more accurate understanding of the complex dynamics of supply chains. Understanding these complexities has enabled researchers and managers to implement more insightful strategies to guide negotiations and find efficient and successful agreements

The purpose of this study is to design a quality risk management model in the supply chain of the automotive industry. This research was conducted with a mixed approach. In the qualitative part, Delphi method was used to identify effective factors and derive a conceptual model. In the quantitative part, hierarchical data analysis was used to prioritize the indicators. The statistical sample includes 16 academic and automotive industry experts who were selected by judgmental sampling and snowball sampling. The data collection tool includes a questionnaire According to the results of the Delphi, the 70 sub-indices finalized in the research are divided into 14 main branches and 3 main fields including quality risk based on: supply chain capabilities, different parts of the supply chain and work stages. After performing the process of hierarchical analysis of data at three levels, the first 14 indicators of the research, which obtained the most weights, were identified as the most important indicators.By identifying the types of quality risks during the process and supply chain in the automotive industry, this research helps the managers of the automotive industry in developing the correct strategies for risk management and quality management of the supply chain.

The current research was conducted with the aim of providing a supply chain logistics dynamic model based on the Internet of Things with an emphasis on online marketing. The participants of this research were supply chain managers with at least 15 years of teaching experience and a master's degree or higher. The selection of people was done by purposive sampling with the criterion of teaching experience in the elementary education period. Sampling was done with the participation of 18 experts. The data collection tool included two parts, 1- examination and exploration of upstream documents, documents related to the supply chain, logistics and Internet of Things in the library part, 2- semi-structured interview in the field part, where the semi-structured interview with the participants continued until the theoretical saturation stage. Found. To analyze the qualitative data, the theme analysis method based on the Atreide-Sterling model was used. In order to measure reliability, Holstein's coefficient, P-Scott's coefficient, Cohen's kappa index and Kruppendorf's alpha were used, which were confirmed. ATLASTI software was used in the theme analysis section. According to the results, four quantitative criteria were used to check the validity, transferability, verifiability and reliability: Holstein coefficient, Scott P coefficient, Cohen's kappa index and Krepinderoff's alpha. The degree of correlation of the experts' opinion was obtained by calculating the Holstein coefficient (PAO) or "observed agreement percentage" of 0.810, which is a significant value. According to the flaws in the Holstein method, the P-Scott index was also calculated, and its value was 0.799. The fourth indicator of validity of qualitative research is Cohen's Kappa index. Cohen's kappa index is 0.746 in this study. Finally, Kerpinderoff's alpha was used and its value was estimated at 0.834 in this study.