In this article, Non radial method of Dynamic DEA with the parallel Network structure is presented and is used for calculation of relative efficiency measures when inputs and outputs do not change equally. In this model, DMU divisions under evaluation have been put together in parallel. But its Dynamic structure is assumed in series. Since in real applications there are undesirable inputs and outputs in the proposed model, the assumption of the existence of the intermediate products have been considered. After obtaining period–divisional efficiencies, by considering its weighted arithmetic mean, models are presented for the evaluation of period, divisional and overall efficiency for decision making unit.

This study introduces an advanced performance measurement system for 31 municipalities in Tehran and Shahriar, integrating the Balanced Scorecard (BSC) and Data Envelopment Analysis (DEA) methodologies. The combination of BSC and DEA was chosen because BSC offers a multidimensional framework for assessing performance from diverse perspectives, while DEA provides a quantitative tool for evaluating efficiency, particularly useful when DEAling with multiple inputs and outputs. Together, they allow for both qualitative and quantitative evaluation of municipal performance, addressing the need for comprehensive performance assessment. However, traditional DEA models often fail to account for Dynamic changes and intermediate linkages between these perspectives over time. The Dynamic Network Slacks-Based Model (DNSBM) of DEA, proposed in this study, addresses these limitations by incorporating both Network interdependencies and Dynamic changes in performance evaluation. Field studies and expert interviews revealed interconnections between BSC perspectives, and Dynamic changes were modeled by linking Networks over multiple periods. The model estimated efficiency values for each period, showing an average overall score of 0.857, with specific scores for financial (0.94), learning and growth (0.83), internal processes (0.96), and customer (0.34). Statistically significant correlations were found between most perspectives, except financial and learning/growth. The model identified Dynamic performance trends, inefficiency levels, and strategies to improve underperforming DMUs, offering a comprehensive approach to enhancing municipal performance.

Dynamic systems have always attracted much attention from researchers as a significant part of the various types of systems, and modeling of supply chain processes is considered as one of these due to the nature of its change over time, the volatility of customer demand is considered as one of these problems that have many effects on the system and its costs. In the present study, the SCOR Supply Chain is first modeled with the Dynamic Systems Approach (DSA) under specific parameters. We determine the control parameters of the studied policy using the DEA-SCOR model. We also Improvement the basic five-stage model to investigate models incorporating advanced demand information and evaluate the influence of demand variability on the system performance. Then, the evaluation and ranking of the supply chain Network of several distribution companies have been analyzed using the indicators of information sharing, based on the opinion of managers and experts familiar with the subject and by a combination of the data envelopment analysis (DEA)-SCOR and stochastic frontier analysis (SFA). By calculating total efficiency according to DEA-SCOR model in SCOR supply chain supply Network of oil products Distribution Companies, Falavarjan Branch and Tehran Office Branch, have the highest performance, and the lowest performance is observed in Lordegan, Shahriar branch. According to the results of the SFA method, Tehran Office Branch and Isfahan Branch had the highest performances, and Shahriyar and Tiran branches had the lowest performances. The performance level calculated using the SFA method is approximately the same as the performance level calculated using the DEA method. The performance calculated by the DEA method is less than that calculated by the SFA method in some cases. The average calculated performance in the DEA method equals 0. 80, and the average for the SFA method is 0. 82. Given the inadequacy of indicators and the improvement of these indices at each stage, the calculated efficiency in each Dynamic period gradually improves, and the average total performance in the Dynamic period is 0. 90.

In this article, by presenting the scope of national innovation capability in the context of a multi-sector system, a Dynamic Network model is introduced. In this system, to identify Iran's performance problem, at first by bibliometric studying and holding focus group sessions with experts, the steps and indicators of the processed model were identified and designed. Then, the Dynamic Network data envelopment analysis model was implemented to compare Iran's performance with other countries. The model results indicated that Iran's national innovation capability has a poor performance in the third phase of its three steps that include converting patents to hightech products and creative goods. Then, to present the proposed policy to enhance Iran’, s performance in the third step of the mentioned model, by using qualitative comparative analysis of fuzzy set (fSQCA), the combinations of institutional, human capital and research, infrastructure, market sophistication, and business sophistication dimensions were investigated. For calibration of these data, K-MEANS clustering method was used. The output of the mentioned comparative analysis indicated that the combination of the two dimensions of institutions and human capital and research in promoting the country's performance is sufficient.

The present study is an attempt towards remodeling cost, revenue and profit relationship within the Network process. The previous models of Data Envelopment Analysis (DEA) have been too general in their scope and focused on the input and the output within a black box system, therefore they have not been able to measure various phases simultaneously within a Network system. By using these models internal linking activities are neglected. A slacks-based Network DEA model is DEAlt with intermediate products (Tone, Tsutsui). In this development, each input and output can use situations where unit price and unit cost information are available. In this paper we introduce models of cost, revenue and profit efficiency in Network DEA. These models are illustrated by numerical examples and finally results of Constant Returns to Scale (CRS) are obtained. The findings could be used in minimizing the costs and maximizing the benefits in various organizations, public services, factories, and public and private sector companies.

In this paper, sustainability-related factors involved in the success of healthcare system management including a group of hospitals are considered. A three-pronged approach is adopted based on the internal functions of a hospital which affect such functions as social responsibility and the ones related to the services received from health centers. A novel comprehensive multi-period evaluation of hospital performance is applied to the proposed Dynamic Network. This hybrid data envelopment analysisbased fuzzy multi-criteria decision-making model incorporates fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL), and the best-worst method provides a number of useful managerial insights based on a realistic case study from Iran to ensure sustainable management of the healthcare system. Obtained results indicate the important role of considering potential inter-related relations between Network nodes to ensure a comprehensive performance assessment of the healthcare service system.