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.

It is important to consider the uncertainty in the data, and know how to deal with it when evaluating efficiency by using data envelopment analysis; since the presence of small deviations in the data can lead to significant changes in efficiency results. However, in the real world in many cases, the data is uncertain. The purpose of this paper is to present a robust model of network data envelopment analysis in order to measure efficiency in the presence of uncertainty. A new approach to evaluate efficiency for network data envelopment analysis is first proposed. The definitive method presented in this paper involves undesirable output and can be used for different structures in network data envelopment analysis. Next by extending, the proposed model for uncertain data a new robust network data envelopment analysis model is presented for three-stage networks with undesirable outputs. The proposed model is used to evaluate the electricity regions of Iran. These regions involve a three-step process with undesirable outputs in some stages. The results show that the proposed model achieves the efficiency of the steps and the total efficiency simultaneously. In addition, the overall network efficiency score can be a basis to rank the areas.Originality/Value: The proposed model is a new model in the field of efficiency evaluation in conditions of uncertainty and having an undesirable output.

Supply chain management is essential for the success of firms and customer satisfaction. In addition, a suitable performance evaluation system is vital to the effective management of the supply chain. Due to the importance of cost management in the supply chain, an approach based on Data Envelopment Analysis (DEA) is proposed in the current study for evaluating the cost efficiency of closed-loop supply chains while dual-role factors and undesirable outputs exist. DEA is a beneficial mathematical programming method for evaluating and analyzing the relative efficiency of decision maker units with multiple inputs and outputs. Indeed, in this study, the cost efficiency scores of supply chains with three components, supplier, manufacturer and repair and recycling, as well as forward and reverse flows are measured using DEA technique. The assumption of weak disposability on undesirable outputs is considered. Also, a case study is provided to illustrate and to analyze the proposed method. The results show a correct identification of the role of the factors and the incorporation of the undesirable and reversible factors in supply chain systems play the important role in the correct calculation of the cost efficiency in each of components and whole supply chain. Moreover, in the introduced method, the overall cost efficiency can be represented as the weighted sum of the cost efficiency of components.

The purpose of this study was determine superefficiency and identify undesirable output factors the Olympic Federations the country. This study is type descriptive and retrospective the information was collected, to field. Statistical population study included was 25 Olympic federations of the country. Due to the low number of this population Sampling of the total number was used. Data was collected federations For the year 2017. In order to determine the efficiency of federations, the used DEA model. In Data envelopment analysis method is the first step in determining the inputs and outputs of the research. For this reason, strategies of the federations were determined by the balanced scorecard model in the form of a questionnaire distributed. In order to determine the input or output indicators of the evaluation the Chi square test, identify undesirable output factors of inefficient federations in two methods of CCR and BCC output-axis and in order to rank the federations' superefficiency score was used from the Anderson Peterson ranking model. SPSS and DEA Solver software were used to analyze the data. The results showed that in the CCR model, seven federations and in the BCC model, six federations were inefficient. Also, the ranking results showed that in CCR model, equestrian, weightlifting and hockey federations ranked first to third and in BCC model, football, wrestling and handball federations ranked first to third. It can be concluded that federations that their resources to produce optimal outputs have maximized their use, superefficiency scores earned and ranked higher.

The aim of this paper is to investigate congestion in undesirable outputs. The measurement of congestion is important for performance evaluation. In order to calculate the performance and allocate resources well، it is necessary to measure congestion. Data Envelopment Analysis (DEA) is one of the most appropriate tools for measuring performance. Many researchers have studied this topic by means of DEA. Inefficiency is a necessary condition for the existence of congestion. The managerial issue is defined as “evidence of congestion presents when increase in one input or more can be associated with decrease in one output or more، without worsening any other input or output or proceeding in reverse. However، in the scenario where desirable and undesirable outputs both exist، the definition of congestion is different because the desirable outputs are expected to be more، while the undesirable outputs are expected to be less. Therefore، we cannot apply the current theories and definitions directly for measuring congestion. The previous studies only pay attention to the framework of desirable outputs. In fact، undesirable outputs often accompany desirable outputs in production and services. In this study، a new approach for measuring congestion with undesirable outputs is proposed and applied to analyze congestion of the undesirable outputs and inputs in a department of university. The results indicate that all of inefficient departments that have congestion in undesirable output and also، particular congestion in undesirable outputs has the highest correlation with the efficiency.

Evaluation of performance and productivity and the process of its changes over time is considered essential in the process of improvement in organizations, production, industrial and service units. Regarding the calculation of productivity and changes in productivity over time, different models, methods, approaches, and indices have been presented; one of the most important, common and widely used is the Malmquist productivity index. On the other hand, during production processes, undesirable products and outputs are obtained simultaneously with desirable products. Therefore, an index called Malmquist Luenberger was presented with the development of Malmquist's productivity index, which took into account the undesirable outputs while seeking to reduce them and, at the same time, aimed at expanding the desirable outputs. Therefore, the current research has been compiled with the aim of a structured and systematic review and analysis of articles and research that have made a scientific effort on the subject of calculating productivity changes in units with undesirable output using the Malmquist productivity index and especially the Malmquist Luenberger productivity index. This research is based on PRISMA methodology with the aim of structured analysis of studies that have made a scientific effort in the field of calculating productivity changes in units with undesirable output using the Malmquist/Malmquist Luenberger productivity index. This research is a review type that was conducted through searching in domestic and foreign databases such as academic information, Scopus, Science Direct, Elsevier, and Google Scholar in the period from 1980 to 2022 with the approach of selecting the most important, valid, and prominent domestic and foreign scientific and applied articles and researches. In terms of the quantity and quality of the articles, the present article seems to be unprecedented and unique because, due to the breadth and diversity of published articles and research, the void of the current structured research among the published efforts is quite noticeable, and by using this article, on the one hand, researchers can study the latest actions and research efforts in the mentioned field in a completely categorized and structured manner, and on the other hand, the existing scientific gaps and future proposals regarding the evaluation of benefits. See the productivity using the Malmquist/Malmquist Luenberger productivity index, which is the result of the scientific investigations of the authors of this article. Therefore, this research, in the form of a structured review and analysis article, is considered a kind of road map for researchers interested in the field of productivity.Originality/Value: Considering that this article is a structured review of existing research, the output of the current research is a roadmap for researchers and researchers in the field of calculating productivity changes using the Malmquist/Malmquist Luenberger index in order to understand the current problems, challenges and problems of current research as well as future scientific proposals.

The aim of this study is to evaluate efficiency of the power industry using an integrated approach of Network DEA with a variety of outputs and Windows Analysis. This network system includes undesirable, final desirable and intermediate output in time interval of 2012 to 2014. Input and output variables of first and second stages were respectively considered as domestic consumption of power stations, fuel consumption, thermal output, efficiency, nominal power of power station and operational power of power station, maximum production, especial production and gross production, capacity of power transmission substations, and finally delivery energy and energy losses. The results indicate that due to the possibility of integration over three times, in terms of total efficiency and efficiency of production stage, there is highest number of efficient units. In 2013 However, compared to efficient frontier of three periods, electricity production stage had the greatest number of inefficient units and increasing the number of efficient units in the total efficiency stage is due to high efficiency of regional electricity companies.

The purpose of this research is to measure the efficiency of selected Iranian banks from 2010 to 2016. We estimate efficiency, productivity and efficiency changes under the Bayesian setting. In this research, we consider the Non-Performing Loans (NPLs) of banks as bad outputs, while good outputs are loans, off balance sheet assets and securities. Also, variables such as number of employees, bank capital, fixed assets and deposits play inputs role. Results show that the productivity changes of selected Iranian banks are positive over the period of the study, which is mainly due to the improvement in technology like e-banking services, while efficiency changes continued to be negative over the same period. It is observed that the average efficiency for banks is 85 percent. The Karafarin bank has the largest efficiency among selected banks while Refah Kargaran bank efficiency has the smallest one. Results also show that, during the specified period, private banks have a few better efficiency estimate in comparison with the efficiency of state owned banks.

Today, measuring efficiency is one of the most important methods of performance evaluation in any organization. The outputs obtained in all inputs represent the efficiency. Due to the comprehensiveness of the banking sector, it can be introduced as one of the main areas of economic development. In this paper, a data envelopment analysis (DEA) model in a Free Disposal Hull (FDH) network is presented considering the undesirable output for handling the status of the financial deposits in Saman Bank branches. Since the basic models calculate efficiency by considering the overall output and input and ignoring the internal relationships in the banking process flow system; therefore, by considering this issue, in this paper, we present a DEA model that calculates the efficiency score of the branches with the high accuracy. Then the proposed model is compared to the basic CCR model. Finally, the cross-performance method is used to rank the units of the branches.

Efficiency measurement is one of the most important methods for evaluation of organization performance. Data envelopment analysis (DEA), as a nonparametric method, that measures the relative efficiency of decision making units (DMUs) with multiple performance factors which are grouped into outputs and inputs, is one of the important methods that are highly used in this field. However, both desirable (good) and undesirable (bad) factors may be present and we must consider both of them. For example, if inefficiency exists in production processes where final products are manufactured with a production of wastes and pollutants, the outputs of wastes and pollutants are undesirable and should be reduced to improve the performance. This paper uses industry-level dataset of IRAN manufacturing industries during the period 2000-2006 to measure the efficiency of industrial sectors. The inputs are labor force, energy and raw material, and value added is desirable output (good) and pollutant emission for three atmospheric pollutants (CO2, SO2 and SPM) are undesirable output (bad). The results show that during this period only industry with code of 32 (Radio and Television) were efficient and also during this period from 21 industries more than 17 of them were inefficient. In fact, during this period, only 20% of manufacturing industries were efficient.