زنجیره تامین سبز

Due to the specific characteristics of pharmaceutical products such as the specific half-life, the need to observe temperature controls; maintaining the safety of medicines at all stages, complying with international regulations and standards and providing the best level of service to consumers; The pharmaceutical supply chain is very important. Today, in developing countries, the chalenges that exist in the production, storage, import and distribution of pharmaceutical products have reduced the sustainability and increased costs of the pharmaceutical supply and distribution chain network. Sustainability, which seeks to meet today's economic and social needs without jeopardizing the environment and the needs of future generations, is defined as a concept consisting of three economic, social and ecological dimensions. This study by developing an integer bi-objective optimization model; while integrating import factors, time value of money (TVM) and temperature control requirements; It guarantees operational efficiency and economic and environmental sustainability of the pharmaceutical network. In other words, with synergy between cold chain logistics and green principles, while maintaining the quality and integrity of temperature-sensitive pharmaceutical products, it seeks to minimize costs and environmental effects. Also, taking into account the economic consequences of TVM, the inherent challenges and complexities of the international import of pharmaceutical products, it helps to make more cost-effective decisions and more accurate financial feasibility over time. In fact, the present study aims to achieve a harmonious balance between operational excellence, economic viability and sustainable practices, and helps the managers and stakeholders of this industry in navigating the multifaceted challenges of global drug distribution. After solving the model with the help of GAMS and the comprehensive benchmarking method, it has been determined by using numerical examples that (a) pharmaceutical import plays the biggest role in creating costs for its cold and green network. In this regard, it is important to pay attention to the fact that although domestically produced drugs have a lower price than the imported ones, their quality and effect on treatment is also much lower, and this issue makes imported pharmaceutical products more popular among people. In addition, since even the production of pharmaceutical products is dependent on the import of raw materials and legal requirements such as price restrictions are an obstacle for producers, it seems that revision of existing requirements and regulations and Such improvement of production technologies in the long term can reduce the costs of the chain to a great extent, although it may bring costs to the network in the short term; (b) Compliance with temperature controls, which is inevitable during the operation of a strategic product chain such as medicine, will definitely lead to an increase in its costs and a warming of the earth, and it is necessary for the decision-makers of this industry, in short spend enough time and take appropriate measures to improve maintenance technologies and continuously monitor the health and quality of refrigerated items in order to enjoy more benefits in the long term; (c) Transportation, while constituting the smallest part of the costs, is considered the most effective operation of the network in warming the earth. This issue, rather than being affected by the quality, health and capacity of vehicles, is a result of the lack of proper management of supply and demand and improper management of inventory; (d) The time value of money and issues such as inflation, exchange rate fluctuations, and sanctions, although in the short-term and medium-term it will cost more for the chain, but it will not play a decisive role in the long term. In fact, the above two-objective model shows that the improvement of economic and environmental performance in the long term and the realization of sustainable management of the pharmaceutical supply chain can be achieved by revising the legal requirements and production strategies, correct supply and demand management, and proper inventory management.

This study aimed to model the key success factors in establishing green supply chain management within Iran's construction industry. 

This study employed a descriptive-correlation design and variance-covariance matrix analysis, incorporating both library and field research methodologies. Initially, relevant literature was reviewed, followed by the extraction and analysis of selected articles using meta-synthesis and content validity methods. The finalized research model was developed based on data obtained from Iran’s construction industry and examined through structural equation modeling to measure the relationships between identified variables and validate the proposed model. 

The analysis identified several critical success factors associated with the establishment of green supply chain management. Key factors included structural equation modeling, management support systems, improved environmental and financial performance, environmentally compatible design and production, supportive legislation, and integration of environmental processes. Additional influential factors were government policies, green human resources, environmental education, green packaging and transportation, water, energy, and waste management, green purchasing and marketing, cultural elements, supplier collaboration, and social performance of the green supply chain. Each of these factors demonstrated a positive and significant relationship with the successful implementation of green supply chain management. 

The research provides a comprehensive model outlining the key success factors essential for the successful establishment of green supply chain management within Iran’s construction sector. This model offers actionable insights for industry professionals and researchers, highlighting the necessary components for aligning organizational supply chain practices with environmental sustainability goals.

The aim of the current research is to provide a model of factors affecting the implementation of green supply chain management in the construction industry. This research was conducted using a mixed approach. The current research design is the analysis of hidden content and the target community, managers and contractors active in the construction industry and familiar with the supply chain of this industry, and the purposeful sampling method was used. For modeling, the structural-interpretive method was used, and finally, the power of penetration and the degree of dependence of the factors were determined by using Mick-Mac analysis. In order to identify the components of the research, first, a meta-combination approach and a systematic search of sources were used in the period between 1392 and 1402 for internal research and between 2013 and 2023 for external research, and then semi-structured interviews with 14 experts were used. Based on the findings of the research, 101 primary codes were extracted in 14 categories including: internal environmental management, green technology, reverse logistics, green purchasing, green design, green construction, green transportation, green human resources management, green marketing management, internal and external obstacles and drivers. and green supply chain management performance were classified. Also, the modeling results have shown a five-level model in which internal and external drivers and obstacles were placed as the most influential variables in the fifth level and the green supply chain management performance variable as the most influential variable in the first level.

e automotive industry is widely recognized as one of the most productive sectors in many countries and has consistently garnered the attention of governments worldwide. In recent times, environmental concerns and the potential risks to the natural world and human health have gained global prominence. Given the inherent environmental impact of the automotive industry, considerable efforts are underway to mitigate its adverse effects. This research aimed to present a model for analyzing the enablers of the green supply chain in the Iranian automotive industry. A structural-interpretive modeling approach was employed to determine the relationships between enablers. The study focused on active companies in the automobile and automotive parts manufacturing sectors. The statistical population of this research consisted of supply chain operations experts in automotive companies, and a sample of 16 managers from the mentioned companies was selected. MATLAB software was utilized for calculations and model presentation in this research. Based on the results derived from the structural-interpretive modeling approach, several significant components were identified at different levels of the model. At the initial level, the analysis focused on components related to the organization's social and environmental responsibilities, as well as its efforts in recycling and reuse. Moving to the seventh and final level of the model, the research emphasized the critical role of supplier relationship management

The aim of this research is to present a model of green supply chain drivers on companies' competitiveness. In this research, the interrelationships of the effective drivers of the green supply chain in the competitiveness of companies active in the field of food industry have been determined. For this purpose, with library studies and research literature, drivers of green supply chain in the competitiveness of companies have been extracted and by distributing questionnaires and experts' opinions, the final drivers of choice and relationships between them have been determined. These stimuli are presented at different levels and according to their strength and dependence in 4 levels and 8 classification and leveling stimuli and relationships between elements at different levels. The findings of the research indicate that the drivers of the green supply chain in the competitiveness of food companies depend on the factors of trust and satisfaction, market responsiveness, management commitment and technology improvement, and these indicators are highly dependent on other indicators to provide the necessary facilities to be green in the competition. . In order to test and confirm the model, the Mic Mak method has been used, which confirms the results of the research. The results of the Mick Mick analysis show that the fourth factor of competence and skill development has a high power of influence and less dependence; Therefore, it is an intrusive factor. Also, since the fifth factor, i.e., trust and satisfaction, has little influence and dependence, it is considered an autonomous factor.

Analyzing and predicting efficiency in industries is very important in order to evaluate the performance of units and plan to improve their performance. Poultry industry, as one of the strategic and complex industries, has taken an important part of the food chain basket of the societies, and from this point of view, the analysis of its supply network is very important.In this research, using the network data coverage analysis model and data mining, research gaps in the field of measuring and predicting the efficiency of the green supply chain in the poultry industry have been covered. This research is descriptive and survey in terms of its practical purpose and in terms of the nature of implementation, which is done by developing mathematical models in the field of data coverage analysis.First, using the Delphi approach, the effective indicators were identified and screened based on the opinion of experts, and then a new mathematical model was presented based on the coverage analysis of network data. In the following, the efficiency of 9 chains was evaluated in five years using the alpha cut method based on the enveloping analysis method of fuzzy data. The results showed that the presented model is able to evaluate the efficiency of the green and multi-level supply chain of the poultry industry in consecutive years.

Numerous variables are involved in green supply chain management and investigating any intervening variable can influence a diverse set of others. Blockchain, as an emerging technology of the fourth generation of the industry, comes with a variety of distinctive characteristics. The analysis of the integration between blockchain and green supply chain management will be highly intricate. Therefore, it is essential to establish a model to comprehend it effectively.
This study was carried out in two phases. In the first phase, the required information was collected, extracted, analyzed, and combined through a systematic review with a focus on the key questions. After identifying the primary existing sources, based on the entry conditions, some items were removed according to the determined conditions. Finally, 18 articles were thoroughly reviewed, and the variables were extracted. In the second phase, the validation, refinement, and examination of the relationship among variables were discussed through questionnaires. The combined method of DEMATEL and Interpretive Structural Modeling (ISM) were used.
Variables from the green supply chain, likely to be influenced by blockchain were extracted, refined, and modeled in 10 levels, ranging from the most influential to the least influential ones. Environment-related variables, along with business viability, are the most influential.
According to the achieved model and the degree of influence and impact of the variables, the main driver for moving towards green practices and utilizing blockchain include "the need to obtain environmental certification (government pressure)," "buying green products (inclination)," and "giving importance to the social responsibility of the green company." The outcome also depends on "business continuity" and environmental variables. An important aspect regarding the relationship between blockchain and the green supply chain is the location of the variables influenced by blockchain in the interpretive structural model. These variables were placed in the middle levels of the model, indicating that before implementing blockchain technology, it is crucial to assess the influencing variables and determine their value. The assessment can determine whether the establishment or non-establishment of blockchain technology is justified. If these variables indicate the need for changes in the intermediate variables of the model, blockchain technology can be used as a tool or enabler in the supply chain to drive the desired changes based on the specified influencing variables. Ultimately, as the intermediate variables in the model change, the dependent or influencing variables in the model can also be affected.

This research aims to identify key components and indicators for managing green supply chains utilizing the Internet of Things (IoT). The methodology employed is a mixed approach consisting of two stages. First, through qualitative content analysis, this study reviews theoretical foundations and previous research to identify indicators associated with drivers for green supply chain management based on IoT. Subsequently, these indicators were presented to 22 experts in management and information technology to validate and verify them. The research findings reveal that the IoT-based green supply chain model encompasses nine components and 66 indicators. These components include intelligent supply chain management, real-time monitoring of object statuses in the supply chain, intelligent object transfer along the supply chain, intelligent object location in the supply chain, information transparency within the supply chain, corruption reduction, intelligent quality management within the supply chain, intelligent sourcing in the supply chain, intelligent distribution management, and intelligent inventory management. The comprehensive drivers in the proposed model emphasize the importance of incorporating IoT in supply chain management to enhance overall supply chain performance while addressing environmental concerns.IntroductionAs technology continues to advance rapidly across various industries, mankind has enjoyed an improved quality of life. However, the environmental toll of recent decades, such as global warming, water scarcity, polar ice melting, habitat destruction, and deforestation, has raised significant environmental concerns. Modern human activities have contributed to these environmental issues. Consequently, there is mounting pressure on companies to integrate environmentally responsible practices into their operations and supply chains. Recognizing the pivotal role of green supply chain management in sustainable job creation, environmental problem reduction, improved public health through safer food consumption, and enhanced agricultural land productivity, recent years have witnessed increased interest and research into the determinants of green supply chain management.MethodologyThis research adopts a mixed-method approach conducted in two stages. Firstly, qualitative content analysis is employed to review theoretical foundations and prior studies, facilitating the identification of indicators associated with drivers for green supply chain management using IoT. Subsequently, these identified indicators are validated and verified by 22 experts specializing in management and information technology.ResultsThe research findings indicate that green supply chain management, with an IoT approach, comprises nine components: intelligent supply chain management, real-time monitoring of object statuses, intelligent object transfer, intelligent object location, information transparency, corruption reduction, intelligent quality management, intelligent sourcing, intelligent distribution management, and intelligent inventory management.ConclusionsThis study highlights the presence of nine components and 66 indicators within the IoT-based green supply chain model. These components encompass various aspects of supply chain management, emphasizing the importance of incorporating IoT technology to enhance overall supply chain performance while addressing environmental considerations. Due to the growing concerns surrounding environmental issues and the emission of harmful substances by companies, it is highly recommended to incorporate the IoT into supply chain management. This integration serves to monitor and control the quantity of waste generated, and encourages the use of environmentally-friendly 3D printing for creating IoT sensors instead of traditional plastic materials. Furthermore, it is advisable to optimize waste collection schedules and routes for garbage trucks, as these measures can significantly reduce the time and resources spent on waste management. To facilitate this transition, managers should organize in-service training programs to educate employees about IoT technology and communication equipment, emphasizing the positive impact of these advancements on green supply chain management. Additionally, adopting state-of-the-art technologies like Radio-Frequency Identification (RFID) in supply chain systems can contribute to the development of a sustainable and environmentally-conscious supply chain. Legislative bodies should also play a crucial role in promoting green supply chain practices by identifying and addressing legal loopholes in existing supply chain-related laws. This can be achieved through the implementation of incentives, such as tax reductions for eco-friendly companies, or penalties, including tax hikes, financial fines, and even legal repercussions, to encourage the adoption of smoother and more environmentally responsible supply chain management practices. It's worth noting that this research has certain limitations. It primarily relied on articles within specific databases during a defined timeframe, excluding other valuable sources like foreign books and theses due to accessibility constraints. Furthermore, qualitative research inherently depends on the researcher's interpretation and perspective, potentially affecting the reliability of the results. Lastly, challenges related to the COVID-19 pandemic and respondent reluctance posed difficulties during the research process.

The construction industry has always had significant destructive effects on the environment. Using green supply chain management strategies to achieve sustainable construction is an effective approach to reduce environmental damage. Due to the vagueness of the dimensions, in this research, relying on the qualitative approach and the interpretive paradigm and the seven-step meta-synthesis method, the effective components on the establishment of green supply chain management in the construction industry were explained. For this purpose, 728 related studies in the field of supply chain management, especially with sustainable, green, and reverse, were identified, reviewed, evaluated, and screened, and finally, based on the entry and exit protocol, 37 studies were coded in the research portfolio, which in total 73 primary codes were extracted and categorized into 13 concepts and 4 categories. Classification reliability was confirmed based on Kappa coefficient. The findings of the research showed that the components affecting the green supply chain management were identified based on four main categories including: the main factors of green supply chain management, facilitating factors, internal and external drivers and barriers, and finally, suggestions based on the extracted results From this research, it was presented to future researchers

Nowadays, due to the pollution that businesses and various industries impose to the environment, the adoption of strategies and policies by governments to improve the environmental performance of the supply chain has received more attention. The green supply chain will have many benefits, such as saving energy resources, reducing pollutants, and so on. Government intervention to develop these chains takes various forms, such as subsidies, taxes, licensing, and advertising. In this study, two manufacturers with green and non-green supply chains compete in a competitive market and sell their products through a joint retailer, and the government intervenes as a leader in the stackelberg game. These chains are designed based on the selection of agent-based pricing and wholesale pricing methods in four different models. In these models, the government advertises for green products in the first and second models and imposes taxes on the producer of non-green products in the third and fourth models, seeking to maximize social welfare and improving the environment. In order to analyze and compare the models, the game theory approach was used. The results show that in general, government intervention improves the environmental situation and social welfare, and in the case of advertising has a better effect on the overall market trend and also on social welfare than the tax imposing strategy.

Supply Chain is a network of facilities and distribution centers that performs operation of preparation, conversion of raw materials into products and distribution of the final product to the customer. Recent technological, organizational and economic advances in comprehensive health systems have provided patients with more access to treatment. Despite this progress, improvements in health infrastructure and supply chain management are inevitable. Therefore, proper use of appropriate drugs with the right combination for the right patient at the right amount at the right time is essential for the safety and recovery of the disease. Therefore, in this paper, a drug supply chain network with considering discount on the green supply chain, including a pharmacy, a distribution center and a recycling center with a number of drugstores is studied, consisting of two homogeneous vehicle routing sections. A distribution center for medicines and a recycling center for pharmaceutical waste are set up. This research is solved by using the Epsilon constraint method with software of GAMs and after sensitivity analysis it is determined that the most important parameters are demand and then lost unit cost and unit hold cost. In other words, GAMs can solve this model for up to 5 nodes and 11 periods.

The purpose of this study is to investigate the effect of green supply chain on foreign trade performance with regard to the mediating role of environmental performance among small and medium businesses active in the field of cellulose industries in industrial areas of Golestan province. This research is descriptive-survey research in terms of method, and is correlation in terms of how to collect information and is applied in terms of purpose. In this research, a questionnaire was used to collect data. The reliability coefficient for the questionnaires used had the required reliability. The statistical population of this study consists of all managers and supervisors working in small and medium businesses active in the field of cellulose industries in industrial areas of Golestan province, whose number was170 people during the study period. A total of 125 people were considered as the study samples that were selected using purposive sampling method. According to the results of KMO and Bartlett tests, the research data is sufficient and for this reason, to analyze the research hypotheses, factor analysis technique and structural equation model test were used and PLS software was used. Findings show that green supply chain has a significant effect on foreign trade performance and environmental performance; environmental performance has a significant effect on foreign trade performance. The results also showed that the mediating role of environmental performance is played between the studied relationships.

Nowadays with increasing environmental pollution government's attention to the concept of the green supply chain has increased. The green supply chain produces a green product that is highly environmentally friendly. The purpose is to examine the impact of government intervention on competition between chains, the environment and social welfare. This article presents three different models. In the first model the two green and non-green supply chains are competing with each other and the government is not present. In the second model, the government creates a culture to use the green supply chain and in the third model, is taxing the non-green supply chain. The objective of government is social welfare. In both models of government intervention, the game is in the form of a Stackelberg. Backward analysis method is used to solve the model. This method is a backward inference process in problems with limited steps, with the aim of obtaining optimal action in each step. MATLAB and Maple software are used for mathematical calculations and obtaining decision variables. The results show that if the government intervenes in a cultural way, environmental damage will decrease. Another result is that the conditions for increasing social welfare in the state of culture are determined. It is also possible for the green supply chain to increase its price if certain relationships are established between the parameters. In the tax collection model, if the government aims to maximize social welfare, social welfare will increase under any circumstances compared to the absence of the government.

One of the most important industries that cause environmental pollution is the cement industry and companies active in this industry. Cement industry in terms of importance, such as steel and petrochemical industries, and always in accordance with national economic and development plans and policies contributed to the performance is satisfactory. The present study aimed to identify barriers to GSC implementation by FD, weight and prioritize them through the FBWM and evaluation, ranking of Abeyek Cement Industries, Isfahan and Tehran regarding the performance of using the GSC with MAPPAC technique. The present study is a field research in terms of applied purpose and in terms of data collection. The present article is exploratory because it seeks to identify barriers to the implementation of green supply chain in the country's cement industry.The present statistical sample and population consisted of 12 logistics senior managers in cement companies. Results of screening by a FD indicated that a native model had five dimensions and thirty four indices. According to results of weighting barriers to GSC implementation dimensions by the FBWM, the support & covering was the most important dimension of the GSC, then the Technological was put in the second place, dimensions the economic, knowledge and environmental were ranked third to fiveth respectively.The cement companies were then evaluated by the proposed model through MAPPAC technique. In the present study, the native model of barriers to the implementation of green supply chain in cement manufacturing industries has been designed.

This article aims to develop an integrated production-inventory-vehicle routing model for deteriorating products in a green supply chain considering environmental impacts. The objective is to maximize the profit of selling products considering the costs of production, setup, inventory holding, distribution, vehicle routing, transportation, fuel, and environmental pollutants.

 Intending to integrate the supply chain policies, the developed model aims to maximize the total profit of producers and wholesalers in a horizontal collaboration. The model is formulated to mixed-integer linear programming (MILP). A set of deteriorating products with a shelf life is assumed. The quality of the products decreases over time, and therefore, there is a fixed deterioration rate in each period. A discounting policy is considered for producers and wholesalers. The model is coded using IBM ILOG CPLEX. Three examples with different dimensions are solved in two centralized and decentralized versions. The sensitivity of demand and holding cost parameters are analyzed. 

The solving results of the model in both centralized and decentralized cases underlined increasing profits by integrating the supply chain decisions. By comparing the model’s solving results in both centralized and decentralized cases, the sales revenue of the wholesalers in the decentralized case increased by more than 30% in all three samples when a price discount was possible. However, the revenue from the wholesalers' regular sales was more concentrated than those of decentralized case. Compared to the decentralized case, the manufacturers' revenues from discounted and regular sales in the centralized case also increased by more than 10% and 70%, respectively.

Although the demand and many other parameters such as cost and production rate are affected by many exogenous factors, and hence, are not deterministic in reality, demand was assumed deterministic. The problem was solved for small and medium-size samples. In real cases, the development of appropriate algorithms for solving large size samples is recommended.

 The basis of the proposed model is a study on a group of agricultural products from production to distribution, which can be applied for a real case study. This research influences business and the economy. It also proposes a model to build an effective collaboration between manufacturers and wholesalers to increase profitability.

This research tries to integrate decision-making in a supply chain and improve profitability. As a result, business improves and customer satisfaction increases. The model considers the waste of the deteriorating products, i.e. the destructive waste effects on the environment. Fuel consumption as a factor that harms the environment and depletes nonrenewable resources is also recognized. Moreover, possible price discounting can lead to profit increase, waste decrease, and satisfaction of economic or low-income customers. Considering the mentioned factors are substantial in a sustainable supply chain.

This paper presents a mathematical model (MILP) for a supply chain of deteriorating items such as agricultural products. Due to the existing unequal and disproportionate volume of deteriorating products transporting between producers and wholesalers, the transportation fleet is considered heterogeneous. The possibility of a price discount policy is assumed to increase the demand level and total profit and decrease overall waste. Environmental considerations in the form of a reduction in fuel consumption and pollutants in routing are also recognized. The centralized and decentralized cases were also compared.

This paper aims to design a fuzzy inference system to evaluate the green supply chain of export manufacturing companies. This research has been applied from the point of view of purpose. The statistical population of this study included export manufacturing companies in the northwest of the country. The statistical sample is targeted, and 143 companies are determined. A research questionnaire based on the research literature was used to collect the data. In order to examine the validity of the questionnaire, while using formal validity, the validity of the structure has been used based on confirmatory factor analysis. Cronbach's alpha coefficient was also used to evaluate the reliability of the questionnaire. The research questionnaires were distributed among the statistical sample members of the research after confirming the validity and reliability. In order to evaluate the green supply chain of companies, a fuzzy inference system has been used based on triangular membership functions and Mamdani inference. The results show that the designed system is able to show how green the supply chain of companies is based on numerical values ​​and linguistic terms.

Today's world is affected by issues such as global warming, various types of pollution, increasing greenhouse gas emissions, and causes these issues to increase normally, if not accepted by another human species. Therefore, environmental protection and related strategies soon became a priority of programs as an important organizational innovation. Organizations, on the one hand, had to focus on profitability and competitive advantage, on the other hand, eliminate or minimize waste (energy, greenhouse gas emissions, chemical / hazardous, solid waste). It was here that the idea of a green supply chain came up and soon caught everyone's eye. Green supply chain management is based on both integrating the supply chain management and environment management, controls the environmental effects of products in their life cycle via sharing the information and coordination. The purpose of this study is to investigate the effect of green supply chain management on the performance of airlines with the mediating role of customer relationship management.

This research is applied in terms of purpose and descriptive in terms of data collection method and is a causal-comparative branch based on structural equation analysis. The statistical population of the study is the managers of airlines, of which 125 people have been considered as a research sample using a simple random sampling method based on Cochran's formula.

The instrument used is a questionnaire in which the reliability of each of its variables was calculated above 0.7 and its validity was confirmed by the content and structure method. In the present study, in order to analyze the obtained data, inferential analysis methods have been used.

The results showed that green supply chain management has a positive and significant effect on organizational performance. The mediating role of customer relationship management was also confirmed using the Sobel test.

Increasing environmental pollution has caused global warming and consequently, it has endangered human health and animals. Hence, green concept has received much attention in recent studies. In this research, a multi-objective mathematical for a multi-level multi-product supply chain network is presented which aims to minimize the environmental impact and total costs of supply chain and maximize the customers' satisfaction level. On the other hand, due to the unspecified demands level, demand uncertainty has been considered in the problem with different scenarios. Regarding the complexity of the proposed mathematical model and difficulties in solving the problem with exact methods in large size, a NSGA II method has been proposed. Finally, the proposed NSGAII has shown as a reliable method to find efficient Pareto frontiers in a reasonable time. Therefore, it can be employed for solving large scale problems.

The purpose of this research is to develop a conceptual model and categorize the prerequisites and consequences of green supply chain in the parts manufacturing industry. A comprehensive and indigenous model is not provided. The method of studying qualitative content analysis and the main tools of data collection are semi-structured interviews. Data analysis was performed with combined and concise combined content analysis technique. The identified factors include 29 open codes, which are inserted in the form of seven main categories, and at the end, using Maxqda software; classification and conceptual model were drawn. In order to measure the reliability of the present coefficient, the calculated Kappa coefficient by SPSS software was equal to 0.960, which is at the level of excellent agreement. The results show that 7 components identified in the prerequisites and consequences of the green supply chain in the parts manufacturing industry include; Supplier and purchase of green, green design and packaging, green production, green distribution and marketing, environmental management, education and research, reverse logistics. The components of education and research and reverse logistics have emerged as new components in this research. Today, global organizations have found in a competitive environment that improving environmental performance can differentiate them from other competitors. The Green Supply Chain combines environmental concerns with the concept of supply chain through improved collaboration and coordination of supply chain members.