International Journal of Data Envelopment Analysis
Volume:7 Issue: 3, Summer 2019

As a non-parametric method of relative efficient measurement of a group of decision-making units (〖DMU〗_s), Data Envelopment Analysis (DEA) is one of the most important tools in efficiency computation. One of the main concerns dealt with in DEA is dealing with return to scale in two-stage processes in which, produced outputs of the first stage inputs are used as inputs for the second stage. The outputs of the first stage are considered as intermediate products. Therefore, the second stage uses these intermediate products for producing the outputs of the same stage. Based on this construction, the total process can be analyzed for efficiency production from two sub-processes. In this paper, a new model is proposed that eliminates the defections of the previous models and is used to determine the right and left return to scale in two-stage processes of decision-making units.

In some companies, undesirable costs are imposed for provision of services. It is required that current outputs of decision making units are produced at minimal undesirable cost. In this paper, a new method is proposed for evaluating the undesirable cost imposed on the units. Moreover, data is considered in fuzzy number form, due to the observed input-output data are sometimes imprecise in real applications. Applying the -level based approach, the proposed mode is solved to measure minimum undesirable cost. In this method, data information is supposed as triangular fuzzy numbers. Finally, the proposed method is illustrated by a real application.

Today the most organizations (e.g. banks and insurance institutes) consist of the various units which under the control of the main organization (unified management) act independently. Sometimes the manager presents some services which incur costs such as advertisement and introducing a new technology. Most organizations consist of several individual units. Resource allocation issue appears when requiring to determine an equitable share of costs for these independent units. Data Envelopment Analysis has been proved as a useful technique to solve allocation problems. This paper presents a linear programming model based on DEA methodology to find an equitable allocation. To compare obtained results, we use the proposed model to a data set of prior studies.

This paper presents a novel approach to achieving the goals of data envelopment analysis in the process of reconstruction and integration of decision-making units by using multiple objective linear programming. In this regard, first, we review inverse data envelopment analysis models for data reconstruction and integration. We present a model with multi-objective linear programming structure in inverse data envelopment analysis. The superiority of the model to prioritize inputs and outputs in the input and output data integration process. Finally, we used of bank data for showing the validity of proposed approach and we proposed results.

Data Envelopment Analysis (DEA) is one of the best methods for measuring the efficiency and productivity of Decision Making Units (DMU). Evaluating the efficiency of DMUs which have two or several stages by using the conventional DEA models, is equal to consider them as black box. This method, omits the effect of intermediate measure on efficiency. Therefore, just the first network inputs and the last network outputs will be effected on network efficiency. After solving each DEA model, in order to improving the DMUs efficiency, introduce one efficient market to evaluated DMU is so important. Conventional DEA network models cant ensures that the market of each evaluated is efficient .In this paper, by considering DMUs that have two stages network process, in order to find projection frontier point some models have been proposed. These models after finding the best intermediate product corresponded to each network, found the overall network efficiency and introduce one projection point for each DMU.

Measuring and improving the efficiency of organizations, as one of the most important parts of the organization's performance evaluation and a tool to control it, is a contemplative issue in order to survive and advance in the area of competition. Transportation is also a key element in the growth and development of countries that creates an unbreakable link among the various sections of the economy. Therefore, evaluating and improving the efficiency of the transportation industry, especially air transportation, as a fast and expensive method, is of particular importance in today's world. The purpose of this article was to evaluate and improve the efficiency of Iranian airlines, that for this purpose, the Data Envelopment Analysis (DEA) Method, as the most popular method of evaluating efficiency, has been selected. In recent years, network envelopment data analysis models have been developed, taking into account various parts of the organization's activity in computing efficiency. Also, undesirable outputs have been considered as the reality of the outside world in these models. In this article, the Slack-Based Measure (SBM) model as one of the newest data envelopment analysis models has been considered that simultaneously sought to increase outputs and reduce inputs, in a network form and associated with undesirable output as the basis of efficiency computations. The efficiency of 14 Iranian airlines was evaluated using the mentioned model.