The network data envelopment analysis models for non-homogenous decision making units based on the sun network structure

2018 ◽  
Vol 27 (4) ◽  
pp. 1221-1244 ◽  
Author(s):  
Qingyou Yan ◽  
Fei Zhao ◽  
Xu Wang ◽  
Guoliang Yang ◽  
Tomas Baležentis ◽  
...  
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Network Structure ◽  
Network Data ◽  
Data Envelopment ◽  
The Sun ◽  
Network Data Envelopment Analysis ◽  
Analysis Models ◽  
Decision Making Units

Fuzzy integer-valued data envelopment analysis

2018 ◽  
Vol 52 (4-5) ◽  
pp. 1429-1444 ◽  
Author(s):  
Sohrab Kordrostami ◽  
Alireza Amirteimoori ◽  
Monireh Jahani Sayyad Noveiri
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Real World ◽  
Data Envelopment ◽  
First Case ◽  
Dea Models ◽  
Analysis Models ◽  
Fuzzy Dea ◽  
Decision Making Units ◽  
Provided Examples

In conventional data envelopment analysis (DEA) models, the efficiency of decision making units (DMUs) is evaluated while data are precise and continuous. Nevertheless, there are occasions in the real world that the performance of DMUs must be calculated in the presence of vague and integer-valued measures. Therefore, the current paper proposes fuzzy integer-valued data envelopment analysis (FIDEA) models to determine the efficiency of DMUs when fuzzy and integer-valued inputs and/or outputs might exist. To illustrate, fuzzy number ranking and graded mean integration representation methods are used to solve some integer-valued data envelopment analysis models in the presence of fuzzy inputs and outputs. Two examples are utilized to illustrate and clarify the proposed approaches. In the provided examples, two cases are discussed. In the first case, all data are as fuzzy and integer-valued measures while in the second case a subset of data is fuzzy and integer-valued. The results of the proposed models indicate that the efficiency scores are calculated correctly and the projections of fuzzy and integer factors are determined as integer values, while this issue has not been discussed in fuzzy DEA, and projections may be estimated as real-valued data.

Evaluating after-sales service units by developing inverse network data envelopment analysis model

2019 ◽  
Vol 27 (2) ◽  
pp. 695-707 ◽  
Author(s):  
Reza Farzipoor Saen ◽  
Seyed Shahrooz Seyedi Hosseini Nia
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Efficiency Score ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Content Type ◽  
Network Data Envelopment Analysis ◽  
Decision Making Unit

Purpose The purpose of this paper is to develop an inverse network data envelopment analysis (INDEA) model to solve resource allocation problems. Design/methodology/approach The authors estimate inputs’ variations based on outputs so that the efficiencies of decision-making unit under evaluation (DMUo) and other decision-making units (DMUs) are constant. Findings The new INDEA model is developed to allocate resources such that inputs are not increased while efficiency scores of all DMUs remain constant. Furthermore, the authors obtain new combinations of inputs and outputs, together with a growth in efficiency score of DMUo such that efficiency scores of other DMUs are not changed. A case study is provided. Originality/value This paper proposes INDEA model to estimate inputs (outputs) without changing efficiency scores of DMUs.

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