INTERNATIONAL JOURNAL OF DATA ENVELOPMENT ANALYSIS
Year:2016 | Volume:4 | Issue:1 (13)|Papers Count:6

Many studies have been conducted to determine the efficiency of two-stage network structures in the recent years. The two-stage network with additional inputs to the second stage, in which the second stage is independent of the first stage are one of these structures. Thus, there is a need for a model capable of calculating the efficiency of two-stage structures as well as efficiency of each stage which can then provide managers with recommendations to increase the efficiency of the entire system and its sub-processes. In this study, a non-cooperative game adapted from game theory and SBM approach is used to calculate the efficiency of a two-stage network structure to provide a unique analysis of the overall efficiency as the product of efficiency scores of the two stages. SBM approach is a non-radial DEA model capable of providing modification recommendations for inputs and outputs. The model then is implemented on 29 credit branches of an Iranian state bank in Guilan province and the results are analyzed.

The measurement of RTS amounts measures a relationship between inputs and outputs in a production structure. There are many different ways to calculate RTS in primal or dual space. But in more realistic cases, governments usually intervene on DMU’s behavior as regulatory agency, this clearly represent a set of limitations and restrictions on behaviors of DMUs, So very few decisions in DMUs are made without intersecting some regulations. Therefore it is essential to be able to assess the impact of regulation on the behavior of the DMUs, and this would be ideally done by estimating returns to scale with and without the effect of the regulation. In this paper we use additive model to provide an alternative approach for estimating returns to scale in regulated environments. The proposed model is developed to determining returns to scale in the presence of quasi-fixed inputs in Data Envelopment Analysis.

The problem of utilizing undesirable (bad) outputs in DEA models often need replacing the assumption of free disposability of outputs by weak disposability of outputs. The Kuosmanen technology is the only correct representation of the fully convex technology exhibiting weak disposability of bad and good outputs. Also, there are some specific features of non-radial data envelopment analysis (DEA) models for obtaining all projections of a decision making unit (DMU) on the boundary of production possibility set (PPS) or efficient frontier. Production technologies in DEA are modeled by polyhedral sets that envelop the observed DMUs. Because the efficient frontiers of DEA technologies are generally non-smooth and are characterized by different faces, thus, all projections of a DMU on efficient frontier can not belong to different faces that do not have common points. The rationale behind abovementioned statement is as follows: if all projections of a DMU belong to different faces then the interior points of PPS will become efficient that contradicts the principles of optimality conditions in linear programming models. Therefore all projections would belong to a unique face that is called minimum face. In this paper we propose a procedure to find minimum face and so all projections of a DMU on efficient frontiers in non-radial DEA models with undesirable outputs. This leads us to an interesting algorithm to obtain minimum face.

Data Envelopment Analysis (DEA) is an efficient method to perform evaluation of units. In DEA we try to evaluate units with undesirable factors in input & outputs by satisfaction function, testing some models. On the other hand benefiting this concept, we can identify non-efficient units. Also we can recognize why these units are inefficient and calculate the reason of their inefficiency and how they turn efficient. In DEA we cannot know why some units are non-efficient and how these units can be efficient, but by this paper we can do this work.

Data Envelopment Analysis (DEA) was developed to help compare the relative performance of decision-making units. It is a non-parametric method for performing frontier analysis. It uses linear programming to estimate the efficiency of multiple decision-making units and it is commonly used in production, management and economics [3]. DEA generates an efficiency score between 0 and 1 for each unit, indicating how effectively they are managing their resources. A compelling feature of DEA is it develops a unique rating system for each unit designed to make them look their best. This should facilitate acceptance of DEA within an organization [2].LINGO is a comprehensive tool designed to make building and solving mathematical optimization models easier and more efficient. In this paper, we have explained what DEA does? How DEA evaluates efficiency, how DEA identifies paths to improve efficiency using this LINGO software, and how to use DEA. We have considered a group of 3 technical colleges (campuses). We assume that each campus “converts” 2 inputs into 3 outputs. This will enable managers to explore and assess the value of using DEA in their service operations. This paper also shows that Lingo Model can offer more information than the standard LP approach with exclusion of Simulation modeling approach [4]. The advantages of this approach are modesty, flexibility and visualization. The results by comparison of educational campuses were helpful for organization management.

The portfolio is a perfect combination of stock or assets, which an investor buys them. The objective of the portfolio is to divide the investment risk among several shares. Using non-parametric DEA and DEA-R methods can be of great significance in estimating portfolio. In the present paper, the efficient portfolio is estimated by using non-radial DEA and DEA-R models. By proposing nonradial models in DEA-R when there is ratio data the efficient portfolio is determined. At the end of the study, an applicatory example based on article [2] with non-radial DEA and DEA-R models has been conducted and results are presented.