Scientia Iranica

Scientia Iranica

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

Authors
S. Shafiei Kaleibari 1
R. Gharizadeh Beiragh 2
R. Alizadeh 3
M. Solimanpur 4
1 Department of Industrial Engineering, Payam Nour University, Tabriz, Iran
2 Department of Industrial Engineering, Urmia University of Technology, Urmia, Iran
3 Technology Foresight Group, Department of Management Science and Technology, Amirkabir University of Technology, Tehran, Iran
4 Department of Industrial Engineering, Urmia University, Urmia, Iran
10.24200/sci.2016.3936
Abstract
Inadequate supply of energy due to consumers’ increasing demand has become one of the major problems in societies. Economic growth is a key reason for the increase in the energy consumption. Although different policies can be employed for resolving this problem, optimizing the efficiency of energy suppliers can be addressed as a key policy in this regard.  This paper presents an adjusted Network Data Envelopment Analysis (NDEA) model for evaluating performance of energy supply chain in Iran from production to distribution stages. Some suggestions are proposed to optimize the performance of the energy supply chain. The NDEA model is adjusted by using assurance region (AR) to achieve more real and scientific results. Borders of the assurance region obtained fromData Envelopment Analytic Hierarchy Process (DEAHP) method are entered into the NDEA model. The results obtained from this model are compared with those of conventional NDEA and technical efficiency in pairs. Finally, the Spearman and Kendall's-Tau correlation tests are used for validating the results.
Keywords
network data envelopment analysis (NDEA)
Assurance Region (AR)
Data Envelopment Analytic Hierarchy Process(DEAHP)
Energy Supply Chain
Technical Efficiency
Scientia Iranica
Volume 23, Issue 4 - Serial Number 4
Transactions on Industrial Engineering (E)
August 2016
Pages 1904-1917

  • Receive Date 26 July 2015
  • Accept Date 27 July 2017