Abstract: Today, the network has an important role in a system. Determining the efficiency of the system as well as the efficiency of the sub-sections of a network helps to effectively manage the network. If the optimal value of the sub-sections is not unique, an efficiency range can be obtained for them. In this paper, the performance of a network is analysis with the help of data envelopment analysis and performance intervals are determined for each of the sub- sections of the network. With help decomposition the performance of a network structure, the performance of its components was obtained. The relationship between component performance and interval value was calculated with the overall efficiency network. Manuscript profile

The outbreak of the coronavirus has caused a recession in most countries, reducing the budgets of organizations in all sectors, including government, business and academia. After the beginning of the epidemic, countries responded to the disease in various ways. This paper evaluates the performance of OECD member countries using network data envelopment analysis method. For this purpose, effective financial and health indicators were identified. Unfavorable and flexible data were identified in various stages and a suitable model was presented. The results of the implementation of the model provide a good insight into the financial and health policies of the above countries. Manuscript profile

Data envelopment analysis is one of the best methods to evaluate the performance of decision-making units. This method is also used for benchmarking. benchmarking is a tool to evaluate organizational performance with a learning approach from others, it is also one of the practical methods in continuous improvement of the benchmarking method. The importance of benchmarking in all industries is clear. This paper considers the after-sales service network of an automobile company in Iran to evaluate the model. According to the structure of this network, a hierarchical structure is considered for benchmarking. In this paper, the purpose is to provide a model for benchmarking decision-making units with hierarchical structure and dependent parameters. In the real world, most decision-making units have a hierarchical structure and this structure needs more attention by researchers also dependent parameters can have a high impact on benchmarking. The proposed model for the after-sales service network of an automobile company in Iran was implemented and the results show the high impact of dependent variables on benchmarking and has increased modeling accuracy. The accuracy of benchmarking is very important for the success of decision-making units and the results show that paying attention to the relationships between the parameters increases the accuracy of benchmarking and according to the proposed model, more accurate benchmarking can be achieved. Manuscript profile

Cross-efficiency is a frequently used method for ranking decision-making units in Data Envelopment Analysis (DEA). A fundamental weakness of this method which has been quite problematic is the presence of multiple optimal weights along with selection of zero values by many of these multiple weights in calculating cross-efficiency. In the current paper it is tried to provide a method which through utilizing fair distribution of weights resolve the mentioned problems and in this way give more validity to the cross-efficiency method in raking decision-making units. Manuscript profile

Benchmarking is a tool for evaluating organizational performance with a learning approach from others. The importance of benchmarking in every industry is clear for anyone. In the automotive industry, the performance of after-sales service agencies in Iran is evaluated every year by Iran Standard and Quality Inspection company. One of the ways to continuously improve in after-sales service agencies is benchmarking of successful and efficient examples in the network. In this paper, a benchmarking model is developed considering that the repair index and customer satisfaction are interdependent. To improve the accuracy and operationality of benchmarking, some constraints have been added to the model with the opinion of experts. Considering the dependent parameters, a data envelopment analysis model has been proposed and this model has been implemented to benchmark 20 after-sales service agencies of a car company. By solving the model and comparing it with the results of the original model, it was observed that the considered conditions changed the benchmarking and increased the accuracy. This paper discusses the concept of the impact and importance of dependent parameters in benchmarking, and with this concept, a benchmarking model for automotive after-sales service agencies is presented. Manuscript profile

In this paper using DEA technique, four-stage DEA model mooted in order to consider the situation in which returned products exist. Returned products are the inputs of the previous sub-processes that need to be reprocessed due to existence of flaws. Here, a supply chain with four stages as supplier, manufacture, distributor, and retailer with intermediate and return products has been considered and a DEA model formulated for performance analysis. Manuscript profile