جستجوی مقالات مرتبط با کلیدواژه « زنجیره تامین » در نشریات گروه « مدیریت »

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.

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 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.

Todays, strategic foresight is known as an important and vital tool in organizations to deal with uncertainty in the future and stability in complex environments. The purpose of this research is to investigate the role of strategic foresight in supply chain performance. For this purpose, the moderating role of strategic flexibility has been used as a moderating factor. The statistical population of this research is all the members of the supply chain of the Iranian automobile industry, and two stages of simple random sampling and stratified sampling proportional to the volume have been used. 136 questionnaires were distributed and finally 125 questionnaires were analyzed. To test the 5 main hypotheses, structural equation modeling method based on variance (partial least square fan) and path analysis was used. The results and analysis of outputs showed that strategic flexibility and shared value creation have a positive and significant effect on supply chain performance. Among the indicators of strategic foresight, only formal organization has a negative effect on strategic flexibility, and the rest of the indicators have a positive effect. Strategic flexibility also has a positive and significant effect on the creation of shared value. The results of this research lead supply chain members to a correct understanding of the impact of strategic foresight on supply chain performance in order to improve future decisions.

Today, one of the main challenges facing organizations is to find methods for the production cycle that are in accordance with environmental standards. Therefore, using the green supply chain is considered as a suitable method. Paying attention to this philosophy in organizations has caused the workforce to be able to think, create and innovate better, and on the other hand, investment has become more targeted and productivity has increased. This research has been done with the aim of providing a model for evaluating green supply chain management and using the system dynamics method. For this purpose, the effective parameters in green supply chain management were identified and the relationship between them and their effect on each other were determined. Then the cause and effect diagram and green supply chain management flow diagram were designed and after validating the model, its simulation was done using Vensim software and in the time horizon ( 1395 - 1405 ). According to the validation of the model, green supply chain management policies were identified and the results were compared and analyzed.

The purpose of this research is analyzing the supply shain risk management based on resilience capabilities with TISM approach in Iran's National Oil Products Distribution Company and the gasoline supply chain.
Variables were identified through a multi-grounded theory.Then, the relationships between the dimensions of the structural model was determined through TISM.
The results showed that, inherent risks, socio-political risks and environmental risks are at the top of the model and have a greater impact on other risks. The occurrence of supply, demand and processes - operational risks lead to the emergence of organizational risks. A high level of risk in the organization causes disruptions in the supply chain.Therefore, in order to respond to risks and control them, resilience capabilities have been provided. The dimensions of resilience are affected by risks and react to control them. This issue can help the supply chain achieve its goals.

gray equations and gray matrices. The statistical population of this included the elites and experts of bank managers of the country who are aware of the field of research, which according to the sample size of Cochran in uncertain conditions, the number of 384 people was considered as a statistical sample. The collection tool in this research is a well-made questionnaire. The questionnaire is based on a 5-point Likert scale. In order to examine the data of this research, the multi-criteria decision making modeling method of Ashashri and software (MCMDsolver 2018) will be used. The results of the research show that the first rank is related to the component of developing resilience in crises, the second rank is the creation of a leadership character for banks, the third rank is having a suitable infrastructure, and the fourth rank is the bank's quick response factors to the external environment. Also, in the factor of creating a leadership character for banks, stabilization of programs and coordination among other actors was the most important factor. In the factor of having a suitable infrastructure, the subject of continuity of psychological support and counseling of the survivors had the highest score. Also, in the bank's quick response to the external environment, the functional dimensions of evaluation and monitoring were the most important factors. In the factor of developing resilience in crises, the continuation of psychological support and counseling of survivors show the highest points.

Due to increasing competition, it is necessary to focus on new technology in supply chain. Internet of things is one of the most innovative tools. Creation of appropriate factors in order to operationalization internet of things will lead to development of supply chain performance. Recognition of determining factors in order to use internet of things and awareness of effective result are essential. The purpose of this research is analysis of antecedents and outcomes of Internet of things in supply chain. This paper is based on mixed research including qualitative and quantitative parts. The statistical population of this paper in qualitative part is internal and external papers and that of quantitative part is university professors and industrial experts. This research based on judgmental sampling method as well as contains 22 articles in qualitative part and 10 persons in quantitative part. Library method is used to collect data in the qualitative part while researcher-made questionnaire is used to collect data in the quantitative part. Content analysis is allocated to qualitative part and interpretive structural modeling is assigned to quantitative part. Finally, the results of content analysis are presented in eight antecedents including cultural capital, financial capital, human capital, mental capital, communication capital, information technology infrastructure, legal facilities and environmental capabilities. Additionally, the seven main outcomes including economic performance, social performance, environmental performance, commercial performance, production and operational performance, office system performance and performance development. The most determining variables in antecedent section is information technology infrastructure and in outcome section is economic performance.

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

 New technologies have profoundly changed the way people communicate and interact with their surroundings. These technologies affect every industry. Now, if according to the common definition, we define the supply chain as a set of interconnected activities that include coordination, planning and control of products and services between suppliers and customers. Looking at technological advances, we realize that these traditional structures are no longer self-sufficient, because digitalization has affected almost all aspects of human life, especially supply chain processes. The technologies of the fourth generation of industry represent the industrial revolution that has combined the Internet of Things with automatic systems such as artificial intelligence and its subset of machine learning, which are self-adjusting and self-learning. Such technological systems can change the supply chain from a centralized state to a distributed state, in fact, the deployment of these technologies provides distribution and decentralization for supply chains. The globalization of the economy and the increase in commercial competition have increased the importance of using innovative methods to achieve the goals of the supply chain. With the automation of processes, business activities have moved from manual operations to electronic transactions and all organizational processes have benefited from information and communication technologies. Considering that the design of most processes is at the disposal of centralized centers; There are always problems such as: poor efficiency, coordination at a low level and poor cooperation between the departments of a business unit, the emergence of distributed frameworks such as the blockchain platform and 4.0 generation technologies in addition to Organizations are helped in having complete transparency in transactions and cooperation with each other. They can share transactions on a peer-to-peer page. The purpose of research is to identify the components of the intelligent distributed supply chain and provide the structure of causal relationships for them, as well as the analysis of each of them in the framework of the presented structure. In the present research, codes and categories were first identified using the grounded method, and then the fuzzy cognitive mapping method was used to determine causal-effect relationships.In order to design the structure of the cause-effect relationships of the components of the intelligent distributed supply chain, it was extracted according to the fuzzy cognitive mapping method. Collective mapping was obtained by calculating the average of experts' opinions. According to its components, distributed decentralized supply chain can lead to improvement in information flows, promote healthcare and provide fair access to medical services. Also, assigning treatment priority to patients according to their physical condition for medical care, complying with the terms and conditions of the production line, reducing fraud, detecting authorized hazardous substances and removing drugs that have been licensed outside of the legal criteria can influence the company. High rents in the supply, prescription and treatment of the country to a great extent. The components of the correct implementation of the guidelines for hazardous drugs, the correct implementation of GMP rules, improvement in demand forecasting, correct and timely response of suppliers and suppliers, transparency and traceability, reduction in executive costs, Reducing the risk of implementing projects and carrying out contracts, behavioral data analysis algorithms, error and fraud detection algorithms, processes of identification, discovery, analysis, redesign, implementation and deployment, execution and monitoring, analysis of purchase plans and Procurement provides the possibility of tracking the information, political, monetary and back and forth flows of medicine, which represents its supply and demand among the manufacturer, government sector, patients, pharmacies, insurers, retailers of raw materials and importers. and reduces the possibility of fraud and corruption.Also, allocating treatment priority to patients according to their physical condition for medical care, complying with the terms and conditions of the production line, reducing fraud, detecting authorized hazardous substances and removing drugs that have been licensed outside of the legal criteria can influence the company. High rents in the supply, prescription and treatment of the country will be reduced to a great extent, which can be more effective for special and incurable patients, we know for certain that the required medicine for import and production, it is difficult and sometimes impossible to correctly identify and choose, with these created solutions, transparency is determined in whether the goal of the treatment program has been taken into account. Because we know that the distribution of special benefits is under the control of government officials and they define the priorities of subsidy allocation according to their decision-making power; This can be considered as one of the cases of corruption in the country's pharmaceutical industry. In the end, the improvement in the stock of raw materials and finished products, the non-issue of licenses for non-hazardous production lines in line with the production of hazardous drugs, the non-importation of domestic similar drugs, the elimination of middlemen and backdoors, the transparency of production costs. Transparency in contracts, transparency in the interests of the involved parties, transparency in payment to pharmaceutical companies, transparency in payment of pharmaceutical centers to drug dealers, transparency in pharmacy drug items, transparency in the risks after taking drugs, transparency in the way the budget is spent, The transparent and traceable payment system makes it clear whether the distribution and granting of licenses to natural or legal persons is done based on legal criteria and competently, while the government authority and decision-maker to avoid disclosure or The monopoly of the market cannot limit the transaction within the circle of friends and acquaintances, the benefit of political influence for the production of drugs and the distribution of imported drugs has been greatly reduced, the privileges have been removed from the circle of friends and acquaintances and in a competitive environment, they are given to companies. It will be real or legal that provide fair access to medical services.

In this research, an optimal supply chain network for the collection and recycling of urban waste has been presented by using the double-objective mixed integer linear programming method. In the supply chain design of this research, in addition to the concept of recycling, the concept of a dedicated hub was also considered for each type of separated waste. The objective functions include an economic function to minimize investment costs and a social objective function to maximize the amount of recycling. To solve the large-scale problem accurately, the Lagrange release method has been used. To validate and confirm the efficiency, the model was implemented on a case study in the city of Karaj. According to the obtained results, in order to increase the amount of recycling in the waste supply chain network, more infrastructural and operational investments are needed in the area of forming hub centers. By increasing the amount of recycling, the harmful environmental and destructive effects caused by burying and burning mixed waste will be reduced. In this research, it was observed that the Lagrange release method is able to solve large-scale problems with appropriate accuracy and in less time compared to the commercial CPLEX solver. Therefore, the Lagrange release method can be used as an accurate solution to reduce the time of solving large-scale problems.

The smallest disruption in the process of a supply chain can be likened to a fault. A fault whose gap and depth can increase moment by moment. The resiliency of the supply chain of Iran's auto parts manufacturing industry, along with the possibility of dealing with these disturbances, leads to the development of exports in this supply chain. In this regard, this mixed research (qualitative-quantitative) aims to provide a model of the functional factors of sustainable resilience of the supply chain of the parts manufacturing industry. Iran's auto has done it with the approach of export development. First, in the qualitative section, 49 indicators were identified with the help of reviewing valid research records. Then, in the quantitative part, using the Delphi method and a panel of 19 experts, after three rounds, 24 important indicators were selected and the stability of the indicators was also confirmed by the opinion of the experts. In the continuation of the quantitative part of the research, the relationship between the variables was determined to achieve the pattern in the quantitative part by relying on the Interpretive Structural Modeling (ISM) method. The findings of the research were a ten-level model, where the most effective index in the tenth level was the prediction of crises such as unexpected events (storms, hailstorms, earthquakes, floods, droughts) and the most effective index was the speed and ability of emergency response.

Despite the fact that many researches have been conducted regarding cooperation in the supply chain; But research shows that collaborations in chains with asymmetric power structures, which lead to investment in research and development, have received less attention. This article deals with the development of a model for the supply chain of a complex product, which, in addition to operational decisions to supply the product to the market, also makes decisions regarding investment in research and development. Answering these questions by considering the different power structure in the supply chain and paying attention to cost sharing and revenue sharing contracts is one of the goals of this article: (1) determining the balance point between the amount of investment in research and development, product price and production amount (2) Investigating the impact of research and development uncertainty, buyer fairness and customer sensitivity to product technology level on supply chain performance

The risk of uncertainty in the output of the research and development process and the demand function dependent on the level of product technology are considered in the model. The model is developed under the asymmetric structure of power in the chain by considering various cooperation contracts including research and development cost sharing, production cost sharing, and revenue sharing. Each of the scenarios of this problem is presented as a non-linear two-level programming model. The two-level mathematical model was created with the Nash bargaining game approach and the simulation method was used in its optimization.

This research shows that the risk of uncertainty reduces the profit of the supply chain, but the provided cooperation contracts can improve the performance of the chain compared to the decentralized structure. It was also found that the revenue sharing contract can generate more profit for both the entire supply chain and the supplier. But from the point of view of the buyer and based on the bargaining power, when his bargaining power is relatively low, R&D cost sharing and production cost sharing contracts are more beneficial. Also, increasing the fairness of the buyer will improve the performance of the entire supply chain in the structures of revenue sharing and research and development cost sharing. It has also been shown that the market's sensitivity to the level of product technology improves the performance of the chain in the structure of production cost sharing contracts and research and development costs. But in the revenue sharing structure, all members of the chain may not benefit from the market's sensitivity to the level of product technology. In addition, the market's sensitivity to the price and the fairness of the buyer, respectively, always cause a decrease and an increase in the performance of the supply chain.

Due to the significant costs of research and development and production in complex products, paying attention to these costs in supply chain cooperation contracts and sharing them between the influential factors in the supply chain can lead to an increase in the performance of the supply chain. The bargaining power between the buyer and the seller in this type of chain can affect the type of contract. Considering the unknown nature of information for the supply chain parties, more models can be developed.

During the last decade, many organizations and industries have focused on financial indicators. However, they have recently found that in addition to financial indicators, economic, social and environmental factors should also be considered in the performance of supply chains as sustainability, which also affects the logistics network of the country's automotive industry. However, industries and organizations cannot ignore cost reduction in today's competitive environment. This paper also presents a model for evaluating the performance of a sustainable lean supply chain to improve productivity.

In terms of applied purpose, the present study is a descriptive survey in terms of data collection.

First, 36 indicators of lean supply chain were extracted based on the study of the background of related researches and then using Delphi method, , their sustainability dimensions were domesticated with the help of 18 experts and specialists in the field of supply chain. The identified factors were determined by interpretive structural method, the relations between and performance evaluation indicators of sustainable lean supply chain in the country's automotive industry. The result of this research is to achieve a model for evaluating the performance of sustainable lean supply chain by improving productivity in the Iranian automotive industry consisting of ten levels.

The increasing development of new digital technologies has caused changes in supply chain management. Therefore, the current research seeks to explain the evolution of supply chain management in the direction of intelligence: a study based on a scientific-metric approach.

The current research is descriptive and analytical, based on bibliometric analysis. The analysis started with the selection of 744 articles between the years 2002 and 2023 and then analyzed using VOSviewer software.

In this research, 15 leading magazines that have been widely published about emerging digital and smart technologies in the supply chain and also ten highly cited articles and keywords have been identified.

Originality: 

Research results based on the keywords, the literature of emerging digital and smart technologies in the supply chain and logistics on "blockchain", "big data", "sustainability", "artificial intelligence", "traceability", "Internet of Things" and "Industry 4.0" are focused

The main factor in successful supply chain financing services is the use of business-oriented information systems. The current research aimed to further associate blockchain technology with the Internet of Things (IoT) and apply them in the field of supply chain finance. The research presents a new information management framework based on blockchain technology and IoT, which contributes to information transparency in the supply chain financing process. By managing information based on blockchain technology and IoT, the operational cost of the entire supply chain can be greatly reduced due to the integration of capital, information, and commercial flows in the supply chain. The results can be summarized as follows: (1) In a symmetric information environment subject to the limitation of maximizing the expected return of all parties, the incentive subsidy under the compatible incentive mechanism has a positive relationship with the maturity of blockchain technology and the operational capability of small and medium-sized enterprises (SMEs) and a negative relationship with the action level coefficient, absolute risk aversion coefficient, and external uncertainty of these companies. (2) The expected income that satisfies the mechanism of incentive compatibility has a positive relationship with the maturity of the blockchain technology, the broker’s profitability, and the net profit received by the employer. (3) In an asymmetric information environment, a varied incentive subsidy is more effective than an equal incentive subsidy in different SMEs with different operational capabilities and provides different incentives for these companies. Therefore, it can be concluded that in a symmetrical information environment, the equal incentive subsidy is more effective, but in an asymmetric information environment, a varied incentive subsidy is more effective.

The emergence of numerous crises in supply chains has increased the importance of financial resilience, and this issue also applies to the supply chain of health tourism. Identifying and modeling the factors affecting the financial resilience of the health tourism supply chain is necessary to improve financial resilience. So far, no research has been done on this matter, as a result, the main goal of the research is to identify and model the factors affecting the financial resilience of Iran's health tourism supply chain in crisis conditions. In order to achieve the goal of the research, in the first stage, with a qualitative approach, factors affecting financial resilience were identified through semi-structured interviews with health tourism supply chain experts. The method of judgmental and snowball sampling and its volume was determined to be 25 people and thematic analysis was used to analyze the data. In the second stage, with a quantitative approach and the use of the comprehensive fuzzy interpretative structural modeling method, the model of relationships between factors was presented. Judgmental and snowball sampling method and its volume was determined to be 10 people. The research results show 33 factors affecting financial resilience, which were classified into 12 general categories. Finally, the model of effective factors was determined, according to which "financial thinking factor" has the most effect and the factors "debt management", "customer relationship management", "inventory management", "supplier management" and "liquidity management" have they are the most effective.

Uncertainty in the supply chain is considered as a fundamental and important issue in order to make appropriate decisions for supply chain managers and designers. In this article, in order to deal with this issue, a three-level supply chain under random demand is proposed using two decentralized and coordinated models, in which the profit increase of each actor in the chain (supplier-manufacturer-retailer) considered. In the decentralized model under the scenario-based stochastic demand, the retailer and the manufacturer separately decide on the order quantity and investment by considering the scenario-based stochastic CSR-sensitive demand. A wholesale price contract with two adjustable levels is proposed to persuade three levels to enter into a coordination scheme. According to the comparisons made between the results of the algorithms, it was found that the coordinated model performed better than the other algorithm in reducing chain costs and increasing profits. In particular, it can be acknowledged that the coordinated model performed better than the decentralized model by about 144.39% and was able to increase the profit of the chain.

The purpose of this research was to identify, modeling and scenario analysis of the acceptance factors of the Internet of Things in the supply chain of Iranian businesses.

To conduct this research, we used both qualitative and quantitative strategies combined. The statistical population in both stages consisted of experts; besides, judgmental and snowball sampling methods were used. In the first stage, acceptance factors were identified through semi-structured interviews. In the second stage, using fuzzy cognitive mapping approach, the acceptance factors were modeled, and the scenario was analyzed.

The results of the first phase show 58 factors of Internet of Things acceptance, which are categorized into 17 sub-themes and 5 main themes. The second-stage results show that the theme of expertise enjoys the highest degree of influence, then the theme of technology readiness comes next. Also, the overlapping of forward and backward scenarios indicates the importance of expertise and technological readiness.

Originality:

 Since there is little understanding of the factors affecting the acceptance of the Internet of Things at the supply chain level of Iranian businesses, this research has been able to add to the literature of this field and to fill the gap by identifying, modeling, and analyzing the scenario of these factors.

Implications:

 Changing recruitment and hiring policies to find and hire qualified personnel, using in-service training tools, and having access to a technological roadmap are the most important strategies of the supply chain, which can lead to organizational expertise and readiness.

The supply chain of machine-made carpets has faced many fluctuations in recent years. One of the most important fluctuations is the ripple effect that has been observed in recent years. The ripple effect has had many negative consequences for the machine made carpet supply chain, so future research of possible scenarios in the future is highly necessary and is the main purpose of this study. This study was conducted in the machine-made carpet industry of Iran. The data were collected in 4 stages based on the opinion of experts. Micmac and ScenarioWizard software were used for future research. The results of the interview showed that there are 15 drivers for the ripple effect in the supply chain, of which 12 drivers were selected as important drivers based on the output of Micmac software. Four consistent scenarios for the future of the ripple effect were identified as one favorable scenario (robust supply chain), two unfavorable scenarios (unstable supply chain and shaky supply chain) and one mid-range scenario (astonished supply chain). In order to achieve the desired scenario and prevent unfavorable scenarios, flexibility must be built in the supply chain. This is possible through the use of up-to-date technology, collaboration, and backup facilities.Keywords: supply chain; machine made carpet; ripple effect; future study