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.

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.

scholarly journals Using Enhanced Russell Model to Solve Inverse Data Envelopment Analysis Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
G. R. Jahanshahloo ◽  
F. Hosseinzadeh Lotfi ◽  
M. Rostamy-Malkhalifeh ◽  
S. Ghobadi
Keyword(s):  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Sufficient Conditions ◽  
Necessary And Sufficient Conditions ◽  
Multiple Objective ◽  
Multiple Objective Linear Programming ◽  
Data Envelopment ◽  
Input Output ◽  
Pareto Solutions ◽  
Necessary And Sufficient

This paper studies the inverse data envelopment analysis using the nonradial enhanced Russell model. Necessary and sufficient conditions for inputs/outputs determination are introduced based on Pareto solutions of multiple-objective linear programming. In addition, an approach is investigated to identify extra input/lack output in each of input/output components (maximum/minimum reduction/increase amounts in each a of input/output components). In addition, the following question is addressed: if among a group of DMUs, it is required to increase inputs and outputs to a particular unit and assume that the DMU maintains its current efficiency level with respect to other DMUs, how much should the inputs and outputs of the DMU increase? This question is discussed as inverse data envelopment analysis problems, and a technique is suggested to answer this question. Necessary and sufficient conditions are established by employing Pareto solutions of multiple-objective linear programming as well.

scholarly journals Efficiency Measurement on Banking Sector in Bangladesh

2013 ◽  
Vol 61 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Md. Rashedul Hoque ◽  
Md. Israt Rayhan
Keyword(s):  
Data Envelopment Analysis ◽  
Banking Sector ◽  
Measurement Techniques ◽  
Returns To Scale ◽  
Efficiency Score ◽  
Annual Reports ◽  
Data Envelopment ◽  
Operating Profit ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

Nowadays banking sector in Bangladesh plays a considerable role in the economic development and business improvement, in this aspect ranking of banks is vital. In this study, an attempt has been made to rank some of the Bangladeshi Banks. Also, the most efficient bank is identified here. Data Envelopment Analysis is used for this purpose. The data from the annual reports of different banks are used in this study for the purpose of efficiency checking. In Data Envelopment Analysis two types measurement techniques are used – constant returns to scale and variable returns to scale. Since this study attempts to maximize output, that is, the operating profit, so the output oriented Data Envelopment Analysis is used here. The most efficient bank is identified here by the highest efficiency score obtained by that specific bank. Dhaka Univ. J. Sci. 61(1): 1-5, 2013 (January) DOI: http://dx.doi.org/10.3329/dujs.v61i1.15088

A Unified Mathematical Model for Stochastic Data Envelopment Analysis

2021 ◽  
Vol 12 (1) ◽  
pp. 127-141
Author(s):  
Basma E. El-Demerdash ◽  
Assem A. Tharwat ◽  
Ihab A. A. El-Khodary
Keyword(s):  
Data Envelopment Analysis ◽  
Organizational Performance ◽  
Real Life ◽  
Efficiency Measurement ◽  
Data Envelopment ◽  
Stochastic Dea ◽  
Chance Constrained Approach ◽  
Dea Efficiency ◽  
Stochastic Data ◽  
And Performance

Efficiency measurement is one aspect of organizational performance that managers are usually interested in determining. Data envelopment analysis (DEA) is a powerful quantitative tool that provides a means to obtain useful information about the efficiency and performance of organizations and all sorts of functionally similar, relatively autonomous operating units. DEA models are either with a constant rate of return (CRS) or variable return to scale (VRS). Furthermore, the models could be input-oriented or output-oriented. In many real-life applications, observations are usually random in nature; as a result, DEA efficiency measurement may be sensitive to such variations. The purpose of this study was to develop a unified stochastic DEA model that handles different natures of variables independently (random and deterministic) and can be adapted to model both input/output-oriented problems, whether it is CRS or VRS. The chance-constrained approach was adopted to handle the stochastic variables that exist in the model. The developed model is implemented through an illustrative example.

scholarly journals Autonomous Navigation of a Team of Unmanned Surface Vehicles for Intercepting Intruders on a Region Boundary

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 297
Author(s):  
Ali Marzoughi ◽  
Andrey V. Savkin
Keyword(s):  
Motion Control ◽  
Autonomous Vehicles ◽  
Autonomous Navigation ◽  
Control Algorithm ◽  
Autonomous Vehicle ◽  
Sufficient Conditions ◽  
Real Life ◽  
Unmanned Surface Vehicles ◽  
Necessary And Sufficient ◽  
See Region

We study problems of intercepting single and multiple invasive intruders on a boundary of a planar region by employing a team of autonomous unmanned surface vehicles. First, the problem of intercepting a single intruder has been studied and then the proposed strategy has been applied to intercepting multiple intruders on the region boundary. Based on the proposed decentralised motion control algorithm and decision making strategy, each autonomous vehicle intercepts any intruder, which tends to leave the region by detecting the most vulnerable point of the boundary. An efficient and simple mathematical rules based control algorithm for navigating the autonomous vehicles on the boundary of the see region is developed. The proposed algorithm is computationally simple and easily implementable in real life intruder interception applications. In this paper, we obtain necessary and sufficient conditions for the existence of a real-time solution to the considered problem of intruder interception. The effectiveness of the proposed method is confirmed by computer simulations with both single and multiple intruders.

Fuzzy preference programming formulation in data envelopment analysis for university department evaluation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dyanne Brendalyn Mirasol-Cavero ◽  
Lanndon Ocampo
Keyword(s):  
Data Envelopment Analysis ◽  
Real Life ◽  
The Philippines ◽  
Data Envelopment ◽  
Data Accessibility ◽  
Content Type ◽  
Proposed Model ◽  
University Department ◽  
Fuzzy Dea ◽  
Fuzzy Preference

Purpose University department efficiency evaluation is a performance assessment on how departments use their resources to attain their goals. The most widely used tool in measuring the efficiency of academic departments in data envelopment analysis (DEA) deals with crisp data, which may be, often, imprecise, vague, missing or predicted. Current literature offers various approaches to addressing these uncertainties by introducing fuzzy set theory within the basic DEA framework. However, current fuzzy DEA approaches fail to handle missing data, particularly in output values, which are prevalent in real-life evaluation. Thus, this study aims to augment these limitations by offering a fuzzy DEA variation. Design/methodology/approach This paper proposes a more flexible approach by introducing the fuzzy preference programming – DEA (FPP-DEA), where the outputs are expressed as fuzzy numbers and the inputs are conveyed in their actual crisp values. A case study in one of the top higher education institutions in the Philippines was conducted to elucidate the proposed FPP-DEA with fuzzy outputs. Findings Due to its high discriminating power, the proposed model is more constricted in reporting the efficiency scores such that there are lesser reported efficient departments. Although the proposed model can still calculate efficiency no matter how much missing and unavailable, and uncertain data, more comprehensive data accessibility would return an accurate and precise efficiency score. Originality/value This study offers a fuzzy DEA formulation via FPP, which can handle missing, unavailable and imprecise data for output values.

scholarly journals Cost efficiency of the Czech and Slovak banking sectors: an application of the data envelopment analysis

2016 ◽  
Author(s):  
Iveta Palecková
Keyword(s):  
Data Envelopment Analysis ◽  
Cost Efficiency ◽  
Commercial Banks ◽  
Banking Sector ◽  
Banking Industry ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Cost Efficient ◽  
The Cost ◽  
Variable Returns To Scale

The aim of the paper is to estimate the cost efficiency of the Czech and Slovak commercial banks within the period 2010-2014. For empirical analysis the Data Envelopment Analysis input-oriented model with variable returns to scale is applied on the data of the commercial banks. The intermediation approach is adopted to define the inputs and outputs. The Czech commercial banks are more cost efficient than Slovak commercial banks. The development of average cost efficiency is similar in the Czech and Slovak banking industry. The most efficient Czech banks are Ceská sporitelna and Sberbank in the Czech banking sector, the most efficient Slovak bank is Privatbanka with 100% efficiency.

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