Determining Closest Targets on the Extended Facet Production Possibility Set in Data Envelopment Analysis: Modeling and Computational Aspects

2021 ◽  
Author(s):  
Qingyuan Zhu ◽  
Juan Aparicio ◽  
Feng Li ◽  
Jie Wu ◽  
Gang Kou
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Production Possibility ◽  
Production Possibility Set ◽  
Computational Aspects

scholarly journals Novel models for obtaining the closest weak and strong efficient projections in data envelopment analysis

2021 ◽  
Vol 39 (5) ◽  
pp. 9-24
Author(s):  
Javad Vakili ◽  
Hanieh Amirmoshiri ◽  
Mir Kamal Mirnia
Keyword(s):  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Efficient Frontier ◽  
Data Envelopment ◽  
Nonparametric Method ◽  
Target Setting ◽  
Production Possibility ◽  
Production Possibility Set ◽  
And Performance ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a nonparametric method for measuring the relative efficiency and performance of Decision Making Units (DMUs). Traditionally, there are two issues regarding the DEA simultaneously i.e., the identification of a reference point on the efficient boundary of the production possibility set (PPS) and the use of some measures of distance from the unit under assessment to the efficient frontier. Due to its importance, in this paper, two alternative target setting models were developed to allow for lowefficient DMUs find the easiest way to improve its efficiency and reach to the efficient boundary. One seeks the closest weak efficient projection and the other suggests the most appropriate direction towards the strong efficient frontier surface. Both of these models provides the closest projection in one stage. Finally, a proposed problem is empirically checked by using a recent data related to 30 European airports.

scholarly journals Directional Slack-Based Measure for the Inverse Data Envelopment Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ali Mirsalehy ◽  
Mohd Rizam Abu Bakar ◽  
Lai Soon Lee ◽  
Azmi B. Jaafar ◽  
Maryam Heydar
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Efficiency Score ◽  
Data Envelopment ◽  
New Production ◽  
Production Possibility ◽  
Novel Technique ◽  
Decision Making Unit ◽  
Measure Model ◽  
Production Possibility Set

A novel technique has been introduced in this research which lends its basis to the Directional Slack-Based Measure for the inverse Data Envelopment Analysis. In practice, the current research endeavors to elucidate the inverse directional slack-based measure model within a new production possibility set. On one occasion, there is a modification imposed on the output (input) quantities of an efficient decision making unit. In detail, the efficient decision making unit in this method was omitted from the present production possibility set but substituted by the considered efficient decision making unit while its input and output quantities were subsequently modified. The efficiency score of the entire DMUs will be retained in this approach. Also, there would be an improvement in the efficiency score. The proposed approach was investigated in this study with reference to a resource allocation problem. It is possible to simultaneously consider any upsurges (declines) of certain outputs associated with the efficient decision making unit. The significance of the represented model is accentuated by presenting numerical examples.

New Models for Computing the Distance of DMUs to the Weak Efficient Boundary of Convex and Nonconvex PPSs in DEA

2017 ◽  
Vol 34 (06) ◽  
pp. 1750035
Author(s):  
J. Vakili
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Production Possibility ◽  
New Models ◽  
Production Possibility Set ◽  
Decision Making Units

In data envelopment analysis (DEA), calculating the distances of decision making units (DMUs) from the weak efficient boundary of a production possibility set (PPS) is a very important subject which has attracted increasing interest of researchers in recent years. The distances of DMUs to the weak efficient boundary of the PPS can be used to evaluate the performance of DMUs, obtain the closest efficient patterns and also assess the sensitivity and stability of efficiency classifications in DEA. The present study proposes some new models which compute the distances of DMUs from the weak efficient boundary of a PPS for both convex and nonconvex PPSs using Hölder norms. In fact, the presented models assist a DMU to improve its performance by an appropriate movement towards the weak efficient boundary.

DEA Efficiency Region for Variations of Inputs and Outputs

2021 ◽  
pp. 1-26
Author(s):  
Mohammad Khoveyni ◽  
Robabeh Eslami
Keyword(s):  
Decision Making ◽  
Czech Republic ◽  
Data Envelopment Analysis ◽  
Banking Industry ◽  
Data Envelopment ◽  
The Czech Republic ◽  
Production Possibility ◽  
Dea Efficiency ◽  
Production Possibility Set ◽  
Decision Making Units

Finding efficiency regions (ERs) for extremely efficient decision-making units (DMUs) is one of the important issues from the managerial and economic viewpoints. An extremely efficient DMU will remain efficient if and only if after changing its inputs and/or its outputs this DMU stays within its ER. Thus, by applying the ER information, decision maker(s) of the evaluated extremely efficient DMU can precisely understand the values of input(s) increment and output(s) decrement of this DMU so that it remains efficient. Hence, in this study, we propose a data envelopment analysis (DEA) approach based on the defining hyperplanes of the production possibility set (PPS), which is capable of finding the ERs of the DMUs when their inputs increase and/or their outputs decrease. To demonstrate the applicability of the proposed approach, in the real world, a numerical example and an empirical application to the banking industry in the Czech Republic are provided.

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