scholarly journals A framework for performance evaluation of energy supply chain by a compatible Network Data Envelopment Analysis model

2016 ◽  
Vol 23 (4) ◽  
pp. 1904-1917 ◽  
Author(s):  
S. Shafiei Kaleibari ◽  
R. Gharizadeh Beiragh ◽  
R. Alizadeh ◽  
M. Solimanpur
Keyword(s):  
Supply Chain ◽  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Energy Supply ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Network Data Envelopment Analysis

scholarly journals Evaluation of post-graduate programs using a network data envelopment analysis model

DYNA ◽  
2018 ◽  
Vol 85 (204) ◽  
pp. 83-90 ◽  
Author(s):  
Lidia Angulo Meza ◽  
João Carlos Soares de Mello ◽  
Silvio Figueiredo Gomes Junior ◽  
Plácido Moreno
Keyword(s):  
Data Envelopment Analysis ◽  
Graduate Programs ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Network Dea ◽  
Post Graduate ◽  
Network Data Envelopment Analysis

A pesar de que los modelos estándar del Análisis Envolvente de Datos (DEA) han sido ampliamente utilizados en la evaluación de la eficiencia en educación, existen pocos estudios que utilizan modelos DEA en red (Network DEA – NDEA) en la evaluación educativa. En el presente trabajo, se ha propuesto una alternativa a la evaluación oficial realizada a cada tres años por la CAPES (agencia brasileña para la regulación de los programas de post-graduación) mediante un modelo DEA en red. El uso de NDEA se justifica ya que dependiendo del punto de vista algunas variables pueden ser consideradas como entradas o como salidas. El uso de NDEA evita la necesidad de decidir si una variable es una entrada o una salida de todo el proceso. Esto ocurre porque una variable puede ser tanto una salida para una etapa y una entrada para otro. Nuestro modelo relacional NDEA evalúa tanto la productividad como la calidad junto con la eficiencia global, a partir de datos bibliométricos.

Supply Chain Performance Evaluation With Rough Two-Stage Data Envelopment Analysis Model: Noncooperative Stackelberg Game Approach

2017 ◽  
Vol 17 (4) ◽  
Author(s):  
Morteza Shafiee
Keyword(s):  
Supply Chain ◽  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Rough Set Theory ◽  
Stackelberg Game ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Managerial Decision ◽  
Two Stage

Rapidly changing environment has affected organizations' ability to maintain viability. As a result, various criteria and uncertain situations in a complex environment encounter problems when using the traditional performance evaluation with precise and deterministic data. The purpose of this paper is to propose an applicable model for evaluating the performance of the overall supply chain (SC) network and its members. Performance evaluation methods, which do not include uncertainty, obtain inferior results. To overcome this, rough set theory (RST) was used to deal with such uncertain data and extend rough noncooperative Stackelberg data envelopment analysis (DEA) game to construct a model to evaluate the performance of supply chain under uncertainty. This applies the concept of Stackelberg game/leader–follower in order to develop models for measuring performance. The ranking method of noncooperative two-stage rough DEA model is discussed. While developing the model, which is suitable to evaluate the performance of the supply chain network and its members when it operates in uncertain situations and involves a high degree of vagueness. The application of this paper provides a valuable procedure for performance evaluation in other industries. The proposed model provides useful insights for managers on the measurement of supply chain efficiency in uncertain environment. This paper creates a new perspective into the use of performance evaluation model in order to support managerial decision-making in the dynamic environment and uncertain situations.

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