فصلنامه مدیریت زنجیره تامین
پیاپی 80 (پاییز 1402)

The dynamic of aviation industry services necessitates formulating a strategy to ensure the aviation sector's survival, productivity, and growth. This study examines the               importance-performance of the primary success criteria in the aviation industry's reverse supply chain. The study's statistical population includes university professors and aviation industry members. The current study's goal is to identify and prioritize enablers in the reverse supply chain of the aviation sector using a different strategy than previous studies. This study intends to take an essential step toward successfully creating and implementing aviation industry strategies by identifying practical elements and determining the value of each of those factors. In terms of the research approach, the current study is descriptive, and its objective is to be applied in the aviation sector. In this study, 24 indicators are found in three dimensions from the standpoint of expert members. Using the Danp technique, network relationships and prioritized enablers were determined. Academic experts determined the importance of the primary success variables, and aviation industry specialists determined the performance of the main success factors in the next step. Importance-Performance Analysis (IPA) was then applied to the main success factors identified using the paired t-test. Accordingly, the customers found the "safety and security" aspect to be closer to their expectations than other quality dimensions, and "responsiveness" was found to be far from their expectations compared to other dimensions, requiring more focus from the relevant aviation policymakers and executives.

The design of the integrated supply chain network plays a vital role in improving the operational efficiency of the company. In this regard, it is essential to integrate strategic issues such as location and transportation management with inventory management strategies in the design of the supply chain network. In the current research, the mathematical model of the three-level supply chain network, including supplier, warehouse, and retailer, has been developed by adopting two coordinated and non-coordinated inventory control strategies. The dynamic adaptive control approach is presented to deal with the uncertainty of the economic order quantity. The study's primary focus is examining the integrity or non-integrity of the inventory of supply chain echelons and its effect on the inventory allocation and the reliability levels of network storage points to guarantee a high level of service. A genetic meta-heuristic algorithm has been used to optimize the problem with an ample search space and provides reasonable solutions and reasonable improvement opportunities. The calculation results show that the amount of inventory and the costs of the entire supply chain network show a significant reduction using the coordinated inventory control strategy.

This research tries to analyze the agility of heavy transportation of a defense organization using the Performance Importance Analysis (IPA) method. Today, according to the speed of environmental changes, organizations must respond to various changes and demands with high responsiveness. In this regard, the role of transportation in defense organizations is very important and practical. Also, the agility of heavy transportation of defense organizations can increase the level of success of the organization and reduce the waste of its resources. In this research, first the concepts of agile transportation and then the criteria of agility of heavy transportation are explained. In the following, the agility of heavy transportation of a defense organization has been analyzed using the Performance Importance Analysis (IPA) method. In this research, field research was used with a questionnaire tool, and the statistical population of the research includes senior managers of logistics and transport and mobility experts of the studied defense organization. The results of the Performance Importance Analysis (IPA) method provide insight to managers to identify the organization's strengths and weaknesses and finally propose implementation solutions.

In this paper, the scheduling of inbound and outbound trucks in a cross-dock is investigated. The objective is to minimize the total cost of transportation from the supplier to the         cross-dock, transfer costs from the cross-dock to the retailers, fixed costs for selecting and contracting with the desired fleets, and also the waiting time of the trucks at the cross-dock. Also, the selection of more suitable fleets, as well as the selection and allocation of vehicles for each fleet to transport goods from each supplier, as well as the allocation of the appropriate vehicle to transport goods for each retail store, are calculated according to heterogeneous vehicles and the various orders of each retailer. Also, the appropriate allocation of trucks to the doors, the sequence of trucks in the queue, and the arrival time and departure time of the vehicles are calculated. A MIP model is formulated. Since this model is NP-Hard, the meta-heuristic method of the genetic algorithm is also presented to solve larger problems. Then, to confirm the effectiveness, several examples are examined and the results obtained from solving the mathematical model, and the meta-heuristic solution are compared. In the end, a detailed sensitivity analysis has been performed on the outputs, which shows that the proposed method is fully approved and works very close to the exact method in small dimensions, with the difference that it has the ability to solve larger problems as well.

The present research has done to  provide the  assessing model for the resilience of the supply chain in medical centers. The research is (quantitative-qualitative) in terms of purpose and mixed in terms of the nature of the data. The method of information collection is Library studies and field data collection method through semi-structured interview tool in the qualitative part and questionnaire in the quantitative part. The research community in the qualitative part of the experts includes senior managers and supply chain managers of medical centers, who were selected by non-probability purposeful sampling method and theoretical snowball technique in the number of 8 people based on theoretical saturation criteria. The findings of the qualitative section with the Foundation's data method, which included causal, contextual, and intervening factors and the central phenomenon, and the factors were identified. In the quantitative section, 23 experts were selected to design the model. In the inferential statistics section, the statistical population was 336 people from the supply chain managers and experts of public hospitals in Tehran province, based on Cochran's formula, 184 people were selected by stratified random method based on the number of hospital employees to evaluate the model. Based on the fuzzy Delphi results, 33 components were identified for supply chain resilience in medical centers. The findings of the comprehensive interpretive-structural modeling showed that the four dimensions of "supply chain support system", "risk management", "management of goods suppliers", "methods of supply chain management" in the independent category and four dimensions of "supply chain resilience strategies" ", "strategic supply chain strategies", "support-response strategies" and "supply chain resilience" are related. In the following, the designed model was explained and tested using the structural equation modeling method and Smart PLS software. The results of structural equation modeling showed that "Risk Management" is related to "Supply Chain Support System" and "Supplier Management"; "Supply Chain Support System" on "Supplier Management"; "Supplier Management" on "Supply Chain Management Methods"; And "supply chain management methods" have a positive and significant effect on "supply chain resilience strategies", "strategic supply chain strategies" and "response-support strategies". The results indicate that a higher level of risk management and supply chain support system can improve the resilience performance of the supply chain of medical centers and highlight the importance of strategies.

In recent years, the circular supply chain has attracted the attention of many researchers and experts as a new approach in response to the lack of resources and minimizing waste production, and it can be useful in achieving a sustainable society and economy. Many research studies consider the reason for the slow progress of circular supply chain implementation to be a set of obstacles that prevent its successful adoption. Despite the study of obstacles and challenges of circular supply chain implementation in different countries, due to the difference in laws, infrastructures and social and cultural conditions, it is necessary to examine these obstacles in Iran as well. Among different industries in Iran, the investigation of the obstacles of the rotating supply chain in the automotive industry has not been considered. Therefore, in order to address this research gap, the researchers assessed the obstacles of the revolving supply chain in Saipa Citroen Automobile Company. To implement this necessity, the multi-criteria group decision-making method and specifically the Ordinal Priority Approach have been used. The results showed that the barrier of lack of technology to design recyclable products with a weight of 0.106 is the most important compared to other barriers. The findings of this study provide a comprehensive list of obstacles for the adoption of the circular supply chain and help the managers and decision makers of the automotive industry to formulate strategies to eliminate or reduce the effect of the most effective ones.

The ability to monitor supplier performance is a critical capability to maintain a strong organization-supplier relationship, especially for organizations where supplier quality plays a significant role in their final product and market retention. In this article, a profile monitoring model in two phases is presented for monitoring the quality of products and supplier processes. In the first step, criteria and indicators for quality assessment are extracted according to library resources and the opinion of experts and elites of the industry. In the next phase, in the first phase of monitoring, the parameters of the model are calculated and monitored using the Kong Albain T^2 method, and in the second phase, the Hotling T^2 method is used to monitor the quality of the supplier over time, so that if there is a warning in the shortest time The control chart may show it. This model has been implemented in the automotive industry of Iran Khodro Company and the supplier of gearbox parts by Niromoharkeh Company.