مقالات رزومه علیرضا امیرتیموری

Since the healthcare system is one of the most important pillars of community health, and considering that providing healthcare services to the people is one of the elements of individual development in any country, attention and supervision of this sector can lead to development and social welfare. To ensure better and higher quality healthcare services, performance evaluation in the health sector plays a crucial role. In order to achieve this, proper and proportional use of existing facilities and assets is inevitable. In this study, by introducing an application in the field of healthcare systems, the educational hospitals of the country have been measured in terms of performance and their managerial ability has been calculated. Additionally, by identifying and introducing the impact of contextual variables on the performance of decision-making units, their efficiency has been assessed. For this purpose, data related to educational hospitals in 31 provinces of the country was collected, and then by identifying contextual variables and with the presence of undesirable factors, the efficiency was evaluated and the managerial ability of each was calculated. To reach this goal, in the first step, technical efficiency with the presence of undesirable factors was calculated using data envelopment analysis technique, and then the logarithm of technical efficiency obtained from the first stage was regressed on a set of contextual variables that affect hospital performance. In the next stage, managerial ability was extracted from the residual of the regression obtained from the previous stage. Finally, a unique ranking based on the managerial ability of each unit was provided. Ultimately, the results obtained were analyzed and examined in order to provide valuable suggestions for managers and more efficient management of the country's hospitals to maintain public health. According to the study, without considering contextual variables, 25 effective units were evaluated, but by applying the effect of contextual variables on the efficiency index, no unit becomes effective, proving the high impact of such indices on the performance of units. Additionally, in the ranking of units based on managerial ability, Lorestan province ranked first and Golestan province ranked last.

The aim of this research is to design scenarios based on cooperative game theory models to investigate the observed rewards and penalties resulting from knowledge sharing or non-sharing among companies. The research population includes managers and experts from 30 top private companies active in the field of oil and gas projects. The research methodology is based on Kumar's classification, which is applied, interpretive, exploratory, and includes both quantitative and qualitative aspects. This study underscores the importance of efficient knowledge sharing as a means to foster collaboration among investors in the portfolios of the National Iranian Oil Company to compete with foreign competitors during sanctions.Upon reviewing the results of four scenarios derived from the game, it is observed that the rewards perceived by companies from knowledge sharing depend on the behavior resulting from knowledge sharing by other companies. The more capable an organization is in the influential factors of knowledge transfer and higher innovation, the greater the returns companies will obtain through cooperation. Sensitivity analysis regarding the costs of project cooperation, which arises due to the difficulty of implementing joint projects, shows that as costs increase, companies shift from a cooperation strategy towards a retaliation strategy and then towards a non-cooperation strategy. These strategies are determined based on aligning the results of the profit equation designed with three interrelated cooperative games: the prisoner's dilemma, the hawk-dove game, and assurance game.

The electricity industry plays a pivotal role in a country's economic growth and development. Therefore, it is imperative to assess its performance and identify the strengths and weaknesses of its different sectors, such as production, transmission, and distribution, to enhance economic growth in diverse areas. Given the significance of the transmission sector, this research focuses on analyzing and evaluating the performance of 16 regional electricity companies in Iran from 1390 to 1398, with the aim of comprehending the impact of contextual variables on efficiency. To achieve this, the study will utilize two techniques - Data Envelopment Analysis (DEA) and Ordinary Least Squares (OLS) - to determine the efficiency score and estimate the effect of contextual variables on efficiency, respectively. In the first stage, the DEA technique is employed to calculate the technical efficiency of each company, considering their specific inputs and outputs. In the second stage, the logarithm of the efficiency scores obtained is regressed on contextual variables to establish their effect on efficiency. The residual derived from the regression is referred to as managerial ability. Finally, the companies are ranked based on their modified efficiency after removing the impact of contextual variables.

Recognizing the significance of decisions and decision-making by the Islamic Parliament and their impact on human societies, it is crucial to evaluate the efficiency of different parliamentary terms, identify strengths and weaknesses, and determine influential factors for enhancing future performance. The reformation of the decision-making process is essential as it will result in sound decisions and elevate the political and economic conditions of the country. Thus, the objective of this research is to propose a two-stage data envelopment analysis (DEA) model to evaluate the performance of various periods of the Islamic Parliament (from the third to the tenth period) in terms of legislation and supervision. In the proposed approach, each term of the Islamic Parliament is considered a two-stage decision-making unit (DMU), with legislation as the first stage and supervision as the second stage. The results suggest that, generally, 50% of the periods are efficient, while the remaining 50% are inefficient. Specifically, Periods C, D, G, and H are identified as efficient periods across both dimensions. However, Period B, in terms of overall performance and the supervision dimension, and Period A, within the legislative dimension, are pinpointed as the most inefficient periods. Additionally, an analysis of the average efficiency scores in legislation and supervision underscores that, overall, the Islamic Parliament has demonstrated superior performance in legislation compared to supervision during various periods. This disparity in performance between the supervisory and legislative aspects has led to higher inefficiencies among the periods characterized as inefficient.

In the most investigations of sustainability, including environmental, social and economic issues, in addition to the desirable outputs, undesirable outputs are also presented, which is an obstacle to sustainable development. In this regard, the purpose of this paper is providing an approach based on Data Envelopment Analysis (DEA) with different forms of weak disposability of undesirable outputs to move towards sustainability.

Presenting a DEA-based model, the sustainability and performance of each dimension of sustainability are calculated simultaneously, while undesirable outputs are present with different forms of weak disposability. The sustainability performance of provincial gas companies is examined using the proposed technique.

The results show that the proposed method in the performance analysis of sustainability and its dimensions is efficient when undesirable outputs are presented.

Originality/Value:

 DEA provides a variety of disposability to minimize undesirable outputs and moves to optimize. In this study, an integrated approach with different forms of weak disposability is presented to analyze sustainability.

Estimating the revenue efficiency of entities under evaluation is one of the most important evaluations that can give valuable information about organizations provided that the output prices are known . In this research, a new definition of optimal scale size ( OSS ) based on maximizing the average revenue efficiency (ARE) is presented . Also , the ARE is defined in both convex and non - convex sets, which is independent of returns to scale and the assumption that the vector of input-output prices of units is uniform . Next, due to the presence of uncertain data in many real applications, the introduced ARE model is extended to evaluate systems with random inputs and outputs , and approaches are provided to calculate it . Finally , the proposed method is used in an experimental example and the ARE is calculated for a data set of postal areas in Iran .

Due to the complexity of the processes, analyzing the performance of the systems and examining the change in the scale of operations to improve productivity is a significant aspect. Therefore, in this research, a two-stage directional network data envelopment analysis approach is proposed to estimate the overall efficiency and the performance of each stage of two-stage processes, while undesirable outputs are produced in addition to desirable outputs. The proposed technology is based on the properties of the weak disposability of undesirable outputs and variable returns to scale. In addition, after presenting the response function, methods are proposed to calculate the right and left scale elasticities of overall efficient two-stage processes. In order to investigate the validity of the proposed method, a data set from 78 branches of the Iranian bank is used and their efficiency and scale elasticity are examined. The results show that the introduced method is useful and widely applicable to analyze the performance and scale of two-stage network systems in the presence of undesirable outputs.

The purpose of this study was to measure the relative efficiency of forest harvesting processing companies in Guilan province by considering pollution as an undesirable output. For this purpose, data envelopment analysis (DEA) method was used to evaluate the efficiency. In order to conduct this research, data from 12 forest harvesting companies in Guilan province were collected during 10-year period (2007-2016). First, the variable reduction method was used to reduce the indicators and then the units were ranked using the super-efficiency method. The results show that due to the importance of undesirable output, a number of companies have good ranks in terms of efficiency despite their high adverse undesirable output (air pollution) are in a good position in terms of efficiency (Iran Wood Coating Company and Layl Forest Cooperative). Due to the existence of undesirable output (air pollution) in forest exploitation companies, it is possible to improve the performance of companies with high efficiency along with undesirable output by reducing the amount of pollution.

In recent decades, the topic of performance measurement has been one of the popular topics for large companies and manufacturers managers . The range - adjusted measurement ( RAM ) model in data envelopment analysis (DEA) is a non - radial model used to evaluate the performance of firms. Due to the presence of uncertain data in many investigations, a fully fuzzy range-adjusted measurement model with strong complementary slackness conditions to find efficient two-stage systems in a reference set is presented in this paper and it is used to evaluate airline . Given that we have a multi-objective network model of fully fuzzy range - adjusted measurement with strong complementary slackness conditions, the proposed model is solved using the lexicograph method . We also compare it with the existing fully fuzzy network DEA - range adjusted measurement model. Finally, we apply this model using the data of 14 Iranian airlines.

In many production processes, the efficiency of decision-making units should be investigated in the presence of undesirable inputs and outputs and non-discretionary factors. It is also important for managers to examine the impact of changes on one index on another. Therefore, the purpose of this paper is to develop an approach to estimate the efficiency of systems with undesirable inputs and outputs and non-discretionary measures and also to analyze changes.

First, a novel approach based on data envelopment analysis was presented in order to analyze efficiency in the presence of undesirable input-output indices and non-discretionary factors. In fact, the new weak disposability axiom was used and the efficiency of the systems was investigated in the presence of undesirable input-output index and non-discretionary factors. Then the impact of changes of one non-discretionary index on another index was measured by maintaining efficiency, and the marginal rates of these changes were calculated.

In order to explain the proposed method in practice, an applied example provided based on 31 branches of Islamic Azad University (department of education) was presented and the results were discussed and analyzed. By using the suggested method, the efficiency scores and the impact of modifications were obtained.

Performance scores related to branches indicated that most of them behaved well. Also, it was observed that always increasing (decreasing) one index, while maintaining efficiency, does not end in an increase (decrease) in another index but it may remain unchanged or decreased (increased). Due to the inclusion of undesirable input and output measures and non-discretionary factors, the results of the proposed method were more acceptable than the classical DEA models.

Data envelopment analysis (DEA ) is a technique to evaluate the relative performance of a set of decision - making units ( DMUs ) . Corresponding to each inefficient DMU , an efficient benchmark on efficient frontier is determined and inefficient DMUs are projected to this benchmark by increasing their outputs and decreasing inputs . In this paper , a DEA - based procedure is proposed to determine an ideal benchmark to each inefficient unit . Our proposed benchmark dominates the unit under evaluation and it is a convex combination of projection points obtained from different aspects : cost, revenue efficiencies and the closest distance . A n important point is that although the obtained benchmark is not necessarily an efficient point, however , it dominates the unit under consideration . At the end of the paper , the proposed model would be implemented on a simple numerical example .

Data envelopment analysis is auseful method to measurement unified rational and operational and environmental efficiency a supply chain. Supply chain management divisions produce two types outputs based on economic activities and inputs separate into two categories under natural and managerial disposability. The current paper propose a new Data Envelopment Analysis based model to efficiency assessment a supply chain under investment on certain types of inputs to new technologic innovation. In hence, dual-role factors controls cleanup costs of flaring gas and the amount electricity consumptions of power plants also dual-role indices improve expertise in transmission entities. A real case study on Iran power industry is presented to demonstrate the applicability of the proposed model. To demonstrate the capability of the proposed approach this framework is implemented for the performance evaluation of a supply chain identified by oil and gas companies, power plants, transmissions companies, dispatching companies and final consumers in Iran.