DMUs In DEA Research Articles

A technical note on ‘erratum to “Finding the most efficient DMUs in DEA: An improved integrated model” [Comput. Indus. Eng. 52 (2007) 71–77

You et al. (2013) indicated two errors in Amin and Toloo (2007). The first error was the infeasibility of Amin and Toloo’s (2007) model and the second drawback was the lack of a suitable value for the non-Archimedean epsilon in the proposed approach of Amin and Toloo (2007). This paper deals with the raised issues and proves that the model of Amin and Toloo (2007) is always feasible. In addition, we also formulate a new model for finding a suitable value for the epsilon.

A modified model for sensitivity analysis of inefficient DMUs in DEA: a case study in hotel industry

Different models which have been introduced in data envelopment approach can help managers in decision making process in order to address efficient and inefficient units. But limited number of researches considers sensitivity analysis of enhanced efficiency. One of the important issues for a decision maker is to select an appropriate way to move an inefficient DMU toward efficiency frontier. In this paper a modified model is proposed to analyse sensitivity of inefficient units. In this model, instability radius of each inefficient DMU is determined in terms of variations in inputs and outputs. Also, management coefficients are applied to determine the possibility of variations in inputs and outputs variables. The main advantage of this model in comparison with other model is its flexibility in decision making process. Finally, the proposed model is examined in a case study in hotel industry to confirm the applicability of proposed model.

A New Measure for Detecting Influential DMUs in DEA

We discuss about influential DMUs and also we review some related studies in the literature. Then we propose a new method to detect influential DMUs, which is based on Euclidean distance and omitting the efficient DMUs by using single case deletion. Our method will be explained with an empirical example.

Interval data without sign restrictions in DEA

Conventional DEA models assume deterministic, precise and non-negative data for input and output observations. However, real applications may be characterized by observations that are given in form of intervals and include negative numbers. For instance, the consumption of electricity in decentralized energy resources may be either negative or positive, depending on the heat consumption. Likewise, the heat losses in distribution networks may be within a certain range, depending on e.g. external temperature and real-time outtake. Complementing earlier work separately addressing the two problems; interval data and negative data; we propose a comprehensive evaluation process for measuring the relative efficiencies of a set of DMUs in DEA. In our general formulation, the intervals may contain upper or lower bounds with different signs. The proposed method determines upper and lower bounds for the technical efficiency through the limits of the intervals after decomposition. Based on the interval scores, DMUs are then classified into three classes, namely, the strictly efficient, weakly efficient and inefficient. An intuitive ranking approach is presented for the respective classes. The approach is demonstrated through an application to the evaluation of bank branches.

Research on China’s Regional Cultural Industries’ Efficiency Based on Factor Analysis and BCC & Super Efficiency Model

Cultural industries are becoming important drivers for global economic growth. Competitiveness of cultural industries lies in its performance. This paper takes deep research on the cultural industries’ performance of 31 regions in China by the methods of factor analysis and super BCC efficiency model, using the whole statement data of 2010 from cultural industries. As the study shows, there are only 7 provinces which are efficient DMUS in DEA, and inefficacy in scale is one of the most important factors for cultural industries’ efficiency in China, and the short of output is more widespread and serious than redundancy of input. Some proposals are put forward. Firstly, output should be expanded based on completely digging and utilizing the present resources .Second, blind development and input should be avoided. Third, the northeast and central region should work hard to improve pure technical efficiency, and northeast and northwest region should improve scale efficiency.

Removing some DMUs in DEA

Removing some DMUs in DEA

A revised and generalized model with improved discrimination for finding most efficient DMUs in DEA

In this paper we first propose a generalized model which in its special case revises a recently proposed model for finding most BCC-efficient DMU. Then, by explaining about the drawbacks of existing approaches, an algorithm will be developed to consider all possible alternative optimal solutions and determine the set of most efficient DMUs. Another model also will be proposed to provide more discrimination which can be used to select a single most efficient DMU, when it is desirable. The proposed approaches of this paper are applicable for all assumptions about returns-to-scale, and can be utilized to select a DMU or provide a full ranking of DMUs. The contents of the paper are illustrated through numerical examples.

On the DEA total weight flexibility and the aggregation in cross-efficiency evaluations

This paper discusses the DEA total weight flexibility in the context of the cross-efficiency evaluation. The DMUs in DEA are often assessed with unrealistic weighting schemes in their attempt to achieve the best ratings in their self-evaluation. We claim here that in a peer-appraisal like the cross-efficiency evaluation the cross-efficiencies provided by such weights cannot play the same role as those obtained with more reasonable weights. To address this issue, we propose to calculate the cross-efficiency scores by means of a weighted average of cross-efficiencies, instead of with the usual arithmetic mean, so the aggregation weights reflect the disequilibrium in the profiles of DEA weights that are used. Thus, the cross-efficiencies provided by profiles with large differences in their weights, especially those obtained with zero weights, would be attached lower aggregation weights (less importance) than those provided by more balanced profiles of weights.

A new mixed integer linear model for selecting the best decision making units in data envelopment analysis

In a recent paper by Amin (Amin, Gholam R. (2009). Comment on finding the most efficient DMUs in DEA: An improved integrated model. Computers & Industrial Engineering, 56, 1701–1702), he proposed an improved approach to determine a single efficient DMU as the most (or the best) efficient DMU. It will be shown that this nonlinear mixed integer model may fail to produce a solution since it can be infeasible in some cases. In this paper, a linear mixed integer model is proposed which is feasible and can produce a single efficient DMU as well. The model can also be extended to rank all extreme efficient DMUs. Some properties and advantages of the model will be explained. The contents of the paper will be illustrated by some numerical examples including a real data set of nineteen facility layout alternatives.

Comments on finding the most efficient DMUs in DEA: An improved integrated model

This paper improves the integrated DEA model proposed for finding the most efficient DMUs introduced by Amin and Toloo, [Amin, Gholam R., Toloo, M. (2007). Finding the most efficient DMUs in DEA: An improved integrated model. Computers & Industrial Engineering, 52(2), 71–77]. The paper shows the problem of using the integrated DEA model and presents an improved integrated DEA model for determining a single efficient unit. Also the paper indicates the property of the improvements mathematically and a numerical example shows the usefulness and intelligibility of the study.

A new integrated DEA model for finding most BCC-efficient DMU

In many applications of widely recognized technique, DEA, finding the most efficient DMU is desirable for decision maker. Using basic DEA models, decision maker is not able to identify most efficient DMU. Amin and Toloo [Gholam R. Amin, M. Toloo, Finding the most efficient DMUs in DEA: an improved integrated model. Comput. Ind. Eng. 52 (2007) 71–77] introduced an integrated DEA model for finding most CCR-efficient DMU. In this paper, we propose a new integrated model for determining most BCC-efficient DMU by solving only one linear programming (LP). This model is useful for situations in which return to scale is variable, so has wider range of application than other models which find most CCR-efficient DMU. The applicability of the proposed integrated model is illustrated, using a real data set of a case study, which consists of 19 facility layout alternatives.

Finding the most efficient DMUs in DEA: An improved integrated model

In many applications of DEA finding the most efficient DMUs is desirable. This paper presents an improved integrated DEA model in order to detect the most efficient DMUs. The proposed integrated DEA model does not use the trial and error method in the objective function. Also, it is able to find the most efficient DMUs without solving the model n times (one linear programming (LP) for each DMU) and therefore allows the user to get faster results. It is shown that the improved integrated DEA model is always feasible and capable to rank the most efficient one. To illustrate the model capability the proposed methodology is applied to a real data set consisting of the 19 facility layout alternatives.