Performance measurement in data envelopment analysis without slacks: an application to electricity distribution companies

2018 ◽  
Vol 52 (4-5) ◽  
pp. 1069-1085
Author(s):  
Azam Pourhabib ◽  
Sohrab Kordrostami ◽  
Alireza Amirteimoori ◽  
Reza Kazemi Matin
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Measurement ◽  
Reference Points ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Electricity Distribution ◽  
Input Output ◽  
Target Setting ◽  
Dea Models ◽  
Weights Restrictions

In performance measurement of the firms using tools such as data envelopment analysis (DEA) models, weak efficient units are almost appeared as reference points in the models. To avoid zero weights or equivalently non-zero slacks in DEA assessment, weights restrictions are used frequently. In DEA literature, two-stage procedures are developed to deal with non-zero slacks based on restricting input/output weights in multiplier formulating the CCR DEA model. In this paper, a single-stage approach for efficiency evaluation is developed to ensure zero slacks in target setting and avoid weights dissimilarity. A real case on electricity distribution companies in Iran has been given to demonstrate the applicability of the proposed approach.

scholarly journals A full investigation of the directional congestion in data envelopment analysis

2019 ◽  
Author(s):  
somayeh khezri ◽  
Akram Dehnokhalaji ◽  
Farhad Hosseinzadeh Lotfi
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Input Output ◽  
Input And Output ◽  
Dea Models ◽  
Systems Of Inequalities ◽  
Full Investigation ◽  
Decision Making Units ◽  
Inputs And Outputs

One of interesting subjects in Data Envelopment Analysis (DEA) is estimation of congestion of Decision Making Units (DMUs). Congestion is evidenced when decreases (increases) in some inputs re- sult in increases (decreases) in some outputs without worsening (im- proving) any other input/output. Most of the existing methods for measuring the congestion of DMUs utilize the traditional de nition of congestion and assume that inputs and outputs change with the same proportion. Therefore, the important question that arises is whether congestion will occur or not if the decision maker (DM) increases or de- creases the inputs dis-proportionally. This means that, the traditional de nition of congestion in DEA may be unable to measure the con- gestion of units with multiple inputs and outputs. This paper focuses on the directional congestion and proposes methods for recognizing the directional congestion using DEA models. To do this, we consider two di erent scenarios: (i) just the input direction is available. (ii) none of the input and output directions are available. For each scenario, we propose a method consists in systems of inequalities or linear pro- gramming problems for estimation of the directional congestion. The validity of the proposed methods are demonstrated utilizing two nu- merical examples.

scholarly journals Uniformization of frontiers in non-radial ZSG-DEA models: an application to airport revenues

2010 ◽  
Vol 30 (1) ◽  
pp. 175-193 ◽  
Author(s):  
Aline Bandeira de Mello Fonseca ◽  
João Carlos Correia Baptista Soares de Mello ◽  
Eliane Gonçalves Gomes ◽  
Lidia Angulo Meza
Keyword(s):  
Data Envelopment Analysis ◽  
Theoretical Approach ◽  
Approximate Algorithm ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Dea Models ◽  
Weights Restrictions ◽  
Zero Sum

We propose in this paper an extension to the Zero Sum Gains Data Envelopment Analysis model (ZSG-DEA). The proposed approach takes into account, simultaneously, non-radial projections and cone-ratio weights restrictions. We developed an iterative approximate algorithm to solve this model, as in the case study it is oriented only to the constant sum output. The theoretical approach is applied to the concession of discounts and surcharges problem, in terms of airport fees.

Randomizing DEA Efficiency Scores with Beta Distribution

2014 ◽  
pp. 1977-1985
Author(s):  
P. Sunil Dharmapala
Keyword(s):  
Data Envelopment Analysis ◽  
Order Statistic ◽  
Beta Distribution ◽  
Data Envelopment ◽  
Random Errors ◽  
Input Output ◽  
Stochastic Dea ◽  
Dea Models ◽  
Dea Efficiency ◽  
Statistical Results

A criticism leveled against Data Envelopment Analysis (DEA) is that it is incapable of handling input/output data contaminated with random errors, and therefore, efficiency scores reported by DEA do not reflect reality. Several researchers have addressed this issue by incorporating statistical noise into DEA modeling, thus giving birth to Stochastic DEA. In this chapter, utilizing well known DEA models, we propose a method to randomize efficiency scores by treating each score as an order statistic of an underlying Beta distribution. In an application to a set of banks, we demonstrate how to do this randomization and derive some statistical results.

Input–output performance efficiency measurement of an electricity distribution utility using super-efficiency data envelopment analysis

2018 ◽  
Vol 22 (22) ◽  
pp. 7339-7353 ◽  
Author(s):  
Miriam F. Bongo ◽  
Lanndon A. Ocampo ◽  
Yannie Ann D. Magallano ◽  
Geraldine A. Manaban ◽  
Ezra Kim F. Ramos
Keyword(s):  
Data Envelopment Analysis ◽  
Efficiency Measurement ◽  
Data Envelopment ◽  
Electricity Distribution ◽  
Input Output ◽  
Super Efficiency ◽  
Output Performance ◽  
Efficiency Data

Measuring Performance of a Three-Stage Network Structure Using Data Envelopment Analysis and Nash Bargaining Game: A Supply Chain Application

2018 ◽  
Vol 17 (05) ◽  
pp. 1429-1467 ◽  
Author(s):  
Mohammad Amirkhan ◽  
Hosein Didehkhani ◽  
Kaveh Khalili-Damghani ◽  
Ashkan Hafezalkotob
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Nash Bargaining ◽  
Data Envelopment ◽  
Second Stage ◽  
Proposed Model ◽  
Nash Bargaining Game ◽  
Dea Models ◽  
Overall Efficiency

The issue of efficiency analysis of network and multi-stage systems, as one of the most interesting fields in data envelopment analysis (DEA), has attracted much attention in recent years. A pure serial three-stage (PSTS) process is a specific kind of network in which all the outputs of the first stage are used as the only inputs in the second stage and in addition, all the outputs of the second stage are applied as the only inputs in the third stage. In this paper, a new three-stage DEA model is developed using the concept of three-player Nash bargaining game for PSTS processes. In this model, all of the stages cooperate together to improve the overall efficiency of main decision-making unit (DMU). In contrast to the centralized DEA models, the proposed model of this study provides a unique and fair decomposition of the overall efficiency among all three stages and eliminates probable confusion of centralized models for decomposing the overall efficiency score. Some theoretical aspects of proposed model, including convexity and compactness of feasible region, are discussed. Since the proposed bargaining model is a nonlinear mathematical programming, a heuristic linearization approach is also provided. A numerical example and a real-life case study in supply chain are provided to check the efficacy and applicability of the proposed model. The results of proposed model on both numerical example and real case study are compared with those of existing centralized DEA models in the literature. The comparison reveals the efficacy and suitability of proposed model while the pitfalls of centralized DEA model are also resolved. A comprehensive sensitivity analysis is also conducted on the breakdown point associated with each stage.

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