The banking industry has been the object of DEA analyses by a significant number of researchers and probably is the most heavily studied of all business sectors. Various DEA models have been applied in performance assessing problems, and the banks' complex production processes have further motivated the extension and improvement of DEA techniques. This paper surveys 80 published DEA applications in 24 countries/areas that specifically focus on bank branches. Key issues related to the design of DEA models in these studies are discussed. Much advice is included on how to design future experiments and studies in this domain. A number of areas where further research could be fruitful are suggested.

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A survey on bank branch efficiency and performance research with data envelopment analysis

A new method for solving fully fuzzy linear programming problems

Article history: Received January 20, 2014 Accepted 30 August 2014 Available online September 9 2014 Measuring the relative efficiency of similar units has been a popular research especially when the units were mostly non-financial. Even, similar financial units may not be necessarily evaluated based on traditional financial figures such as return of equities, return of assets, etc. In this paper, we present an empirical investigation to measure the relative efficiency of 30 branches of an Iranian bank named Bank Mellat. The study considers four inputs including operating expenses, interest paid, capital expenditures and fixed assets. In addition, we use customers’ bank deposit, commissions and loans paid as output parameters. Using three different data envelopment analyses, the study measures the relative efficiencies of all units. The preliminary results indicate that most banks were working under desirable level of efficiency. © 2014 Growing Science Ltd. All rights reserved. DEA Data envelopment analysis Efficiency Banking industry

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Bank branch operating efficiency: evaluation with data envelopment analysis

A new algorithm to solve fully fuzzy linear programming problems using the MOLP problem

Supplier evaluation plays a critical role in a successful supply chain management. Hence, the evaluation and selection of the right suppliers have become a central decision of manufacturing business activities around the world. Consequently, numerous individual and integrated methods have been presented to evaluate and select suppliers. The current literature shows that hybrid artificial intelligence (AI)-based models have received much attention for supplier evaluation. Integrated data envelopment analysis---artificial neural network (DEA---ANN) is one of the combined methods that have recently garnered great attention from academics and practitioners. However, DEA---ANN model has some drawbacks, which make some limitation in the evaluation process. In this study, we aim at improving the previous DEA---AI models by integrating the Kourosh and Arash method as a robust model of DEA with a new AI approach namely genetic programming (GP) to overcome the shortcomings of previous DEA---AI models in supplier selection. Indeed, in this paper, GP provides a robust nonlinear mathematical equation for the suppliers' efficiency using the determined criteria. To validate the model, adaptive neuro-fuzzy inference system as a powerful tool was used to compare the result with GP-based model. In addition, parametric analysis and unseen data set were used to validate the precision of the model.

An integrated model for green supplier selection under fuzzy environment: application of data envelopment analysis and genetic programming approach

Linear programming problems with fuzzy variables have been investigated by many researchers in the recent literature. Some methods to solve these problems, such as the primal simplex method and the dual simplex method, are based on the concept of comparison of fuzzy numbers by using ranking functions. In this paper, we give a new primal-dual algorithm for solving linear programming problems with fuzzy variables by using duality results, which was proposed by Mahdavi-Amiri and Nasseri (2007). This algorithm will be useful for sensitivity analysis when the activity vectors change for basic columns.

A primal-dual method for linear programming problems with fuzzy variables

Target setting in the general combined-oriented CCR model using an interactive MOLP method

Data envelopment analysis (DEA) and multiple objective linear programming (MOLP) are tools that can be used in management control and planning. While these two types of model are similar in structure, DEA is a performance measurement tool that was initially without consideration of the decision maker (DM)'s preference structure and is directed to assessing past performances as part of management control function and MOLP to planning future performance targets. This paper will establish an equivalence model between DEA and MOLP and show how a DEA problem can be solved interactively by transforming it into MOLP formulation. We will use Zionts-Wallenius (Z-W) method to reflecting the DM's preferences in the process of assessing efficiency. A case study will conducted to illustrate how DEA-oriented efficiency analysis can be conducted using the MOLP method.

Relationship between MOLP and DEA based on output-orientated CCR dual model

In most data envelopment analysis (DEA) models, the best performers have the full efficient status denoted by unity (or 100), and, from experience, we know that usually plural decision making units (DMUs) have this efficient status. Discriminating between these efficient DMUs is an interesting subject, and a large number of methods have been proposed for fully ranking both efficient and inefficient DMUs. This paper demonstrates the fact that the rank reversal phenomenon may occur in most DEA ranking methods; however, this study introduces some ranking methods which do not follow the procedure and lack this taint. Numerical examples are provided to clearly illustrate the above mentioned phenomenon in some DEA ranking methods. In fact, certain ranking methods are surveyed in DEA focusing on rank preservation and rank reversal phenomena.

Mehdi Soltanifar

Papers

A primal-dual method for linear programming problems with fuzzy variables

Target setting in the general combined-oriented CCR model using an interactive MOLP method

Relationship between MOLP and DEA based on output-orientated CCR dual model

Survey on rank preservation and rank reversal in data envelopment analysis

The voting analytic hierarchy process method for discriminating among efficient decision making units in data envelopment analysis