Data Envelopment Analysis Development in Banking Sector

2018 ◽  
pp. 462-484
Author(s):  
Sepideh Kaffash ◽  
Mehran Torshizi
Keyword(s):  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Banking Sector ◽  
Programming Model ◽  
Real Life ◽  
Relative Performance ◽  
Data Envelopment ◽  
Non Linear Programming ◽  
Dea Models ◽  
The Subject

Data Envelopment Analysis is a non-linear programming model introduced by Charnes, Cooper and Rhodes in 1978. It is used widely in literature to measure the relative performance of units in several various fields including the banking. The fascinating real life cases and problems needed to be solved, the nature of data and the types of indicators in the banking field makes it one the most popular fields for DEA researchers theoretically and empirically. DEA and its applications have been the subject of several reviews. However, in this paper the authors specifically review the classic and new DEA models and the applications of them in the banking field.

NEW APPROACHES FOR RESOURCE ALLOCATION VIA DEA MODELS

2012 ◽  
Vol 11 (01) ◽  
pp. 103-117 ◽  
Author(s):  
JIE WU ◽  
QINGXIAN AN
Keyword(s):  
Resource Allocation ◽  
Linear Programming ◽  
Programming Model ◽  
Multiple Objective Linear Programming ◽  
Data Envelopment ◽  
Integrated Models ◽  
Decision Making Unit ◽  
Dea Models ◽  
Pareto Efficient ◽  
Single Objective

This paper focuses on the problem of resource allocation through data envelopment analysis. We propose three integrated models for allocating resources. The first model aims at minimizing the input consumption, the second one aims at maximizing the total outputs within the current resources, and the last one aims at maximizing the total outputs using the predicted resources in the next production season. Since the number of inputs or outputs is usually more than one, the abovementioned issue is often a multiple objective linear programming (MOLP) problem. Through the proportion of inputs (outputs) of new decision making unit (DMU) to the total inputs (outputs) of all old DMUs, we transform the MOLP problem into a single objective linear programming model. We assume that decision maker must ensure that the expected outputs of each DMU after allocation in the next production season are not less than this production season. All these proposed models have the same advantage that the results gained from the models are Pareto efficient. A numerical example of 25 supermarkets is used to illustrate our proposed approach.

scholarly journals Linear programming problems with some multi-choice fuzzy parameters

2018 ◽  
Vol 28 (2) ◽  
pp. 249-264 ◽  
Author(s):  
Avik Pradhan ◽  
Biswal Prasad
Keyword(s):  
Linear Programming ◽  
Fuzzy Numbers ◽  
Programming Model ◽  
Real Life ◽  
Optimal Solution ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Non Linear Programming ◽  
A Value ◽  
Linear Programming Problems

In this paper, we consider some Multi-choice linear programming (MCLP) problems where the alternative values of the multi-choice parameters are fuzzy numbers. There are some real-life situations where we need to choose a value for a parameter from a set of different choices to optimize our objective, and those values of the parameters can be imprecise or fuzzy. We formulate these situations as a mathematical model by using some fuzzy numbers for the alternatives. A defuzzification method based on incentre point of a triangle has been used to find the defuzzified values of the fuzzy numbers. We determine an equivalent crisp multi-choice linear programming model. To tackle the multi-choice parameters, we use Lagranges interpolating polynomials. Then, we establish a transformed mixed integer nonlinear programming problem. By solving the transformed non-linear programming model, we obtain the optimal solution for the original problem. Finally, two numerical examples are presented to demonstrate the proposed model and methodology.

scholarly journals Inverse data envelopment analysis with stochastic data

2021 ◽  
Vol 55 (5) ◽  
pp. 2739-2762
Author(s):  
Ali Ghomi ◽  
Saeid Ghobadi ◽  
Mohammad Hassan Behzadi ◽  
Mohsen Rostamy-Malkhalifeh
Keyword(s):  
Data Envelopment Analysis ◽  
Banking Sector ◽  
Uncertain Data ◽  
Sufficient Conditions ◽  
Real Life ◽  
Efficiency Score ◽  
Data Envelopment ◽  
Stochastic Data ◽  
Level Of Significance ◽  
Necessary And Sufficient

The inverse Data Envelopment Analysis (InvDEA) is an exciting and significant topic in the DEA area. Also, uncertain data in various real-life applications can degrade the efficiency results. The current work addresses the InvDEA in the presence of stochastic data. Under maintaining the efficiency score, the inputs/outputs-estimation problem is investigated when some or all of its outputs/inputs increase. A novel optimality concept for multiple-objective programming problems, stochastic (weak) Pareto optimality in the level of significance α ∈[0,1], is introduced to derive necessary and sufficient conditions for input/output estimation. Furthermore, the performance of the developed theory in a banking sector application is verified.

scholarly journals The Combined Use of Balanced Scorecard and Data Envelopment Analysis in the Banking Industry

2020 ◽  
Vol 11 (1) ◽  
pp. 4-15 ◽  
Author(s):  
Aleksandra Bošković ◽  
Ana Krstić
Keyword(s):  
Data Envelopment Analysis ◽  
Balanced Scorecard ◽  
Banking Sector ◽  
Data Envelopment ◽  
Organizational Efficiency ◽  
Financial Indicators ◽  
The Balanced Scorecard ◽  
Combined Use ◽  
Dea Models ◽  
Single Method

AbstractBackground: Starting from the limitations of different single-method approaches to measuring the organizational efficiency, the paper is focused on covering both the financial and non-financial factors of this concept by combining two methods, namely the Balanced Scorecard (BSC) and Data Envelopment Analysis (DEA).Objectives: The main goal of the research in the paper is to show that certain deficiencies in the independent application of each method are eliminated by combining these methods.Methods/Approach: The paper combines two methods, BSC and DEA, to measure the relative efficiency of all branches of a bank in Serbia.Results: Results confirmed that the combined use of the named methods facilitates measurement of organizational efficiency by using both financial and non-financial indicators.Conclusions: The paper shows that it is possible to achieve synergetic effects in the evaluation of organizational efficiency in the banking sector if BSC is applied first, to define goals within four perspectives, and then four DEA models are developed to measure efficiency in each perspective.

scholarly journals Airports economic efficient frontier

2018 ◽  
Vol 11 (1) ◽  
pp. 26
Author(s):  
Decio Yoshimoto ◽  
Cláudio Jorge Pinto Alves ◽  
Mauro Caetano
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Production Function ◽  
Programming Model ◽  
Efficient Frontier ◽  
Data Envelopment ◽  
International Airport ◽  
Decision Making Unit ◽  
Terminal Area

<p>Studies about airport operational efficiency models generally disregard the correlation between operational efficiencies and economic drivers. The goal of this study is, firstly, to isolate and detail the key economic drivers and then find their efficient frontier. The methodology employed was Data Envelopment Analysis (DEA) as a non-parametric and linear programming model. It provides relative measures of efficiency using multiple inputs and outputs for a given Decision-Making Unit (DMU) without requiring a prior production function. The number of variables in this study was limited in function of the DMUs analyzed, which consisted of the following Brazilian airports: Congonhas Airport (CGH), Guarulhos International Airport (GRU) and Viracopos International Airport (VCP). Two of the airports, GRU and VCP, were found to be efficient considering this study’s combination of very limited variables, meaning that theses airports, from this isolated standpoint, are maximizing their commercial, passenger parking and marketing revenues, given their terminal area and the number of yearly passengers.</p>

scholarly journals Data Envelopment Analysis - Basic Models and their Utilization

Organizacija ◽  
2009 ◽  
Vol 42 (2) ◽  
pp. 37-43 ◽  
Author(s):  
Milan Martić ◽  
Marina Novaković ◽  
Alenka Baggia
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Efficiency Frontier ◽  
Dea Models ◽  
Decision Making Tool ◽  
Inputs And Outputs

Data Envelopment Analysis - Basic Models and their UtilizationData Envelopment Analysis (DEA) is a decision making tool based on linear programming for measuring the relative efficiency of a set of comparable units. Besides the identification of relatively efficient and inefficient units, DEA identifies the sources and level of inefficiency for each of the inputs and outputs. This paper is a survey of the basic DEA models. A comparison of DEA models is given. The effect of model orientation (input or output) on the efficiency frontier and the effect of the convexity requirements on returns to scale are examined. The paper also explains how DEA models can be used to assess efficiency.

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