Article: Developing new methods for determining weights of components in network data envelopment analysis Journal: International Journal of Operational Research (IJOR) 2018 Vol.32 No.2 pp.223 - 250 Abstract: Data envelopment analysis (DEA) is a powerful tool for measuring relative efficiency of decision-making units (DMUs). In many cases such DMUs have network structures with internal structures. Traditional DEA models, however, consider DMUs as black boxes without considering their internal structures. Furthermore, overall efficiency in multi component networks is based on efficiencies of their components. Cook et al. (2010) used the additive weighted average of components' efficiencies to calculate overall efficiency. They used the ratio of total weighted input of component to total weighted input of whole components as a weight of component. As an alternative approach, Faramarzi et al. (2014) proposed that the weights are the ratio of total weighted output at the ith component to total weighted output of whole components. In this paper, we propose three novel methods to obtain the weights of components. Then, to compare these three new methods and the methods proposed by Cook et al. (2010) and Faramarzi et al. (2014), we present a case study. Finally, using Spearman's rank correlation coefficient, we analyse the correlation among different approaches. Inderscience Publishers - linking academia, business and industry through research

Title: Developing new methods for determining weights of components in network data envelopment analysis

Authors: Hojatollah Rajabi Moshtaghi; Gholam Reza Faramarzi; Reza Farzipoor Saen

Addresses: Department of Industrial Management, Faculty of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran ' Young Researchers and Elites Club, Karaj Branch, Islamic Azad University, Karaj, Alborz, Iran ' Department of Industrial Management, Faculty of Management and Accounting, Karaj Branch, Islamic Azad University, P.O. Box 31485-313 Karaj, Iran

Abstract: Data envelopment analysis (DEA) is a powerful tool for measuring relative efficiency of decision-making units (DMUs). In many cases such DMUs have network structures with internal structures. Traditional DEA models, however, consider DMUs as black boxes without considering their internal structures. Furthermore, overall efficiency in multi component networks is based on efficiencies of their components. Cook et al. (2010) used the additive weighted average of components' efficiencies to calculate overall efficiency. They used the ratio of total weighted input of component to total weighted input of whole components as a weight of component. As an alternative approach, Faramarzi et al. (2014) proposed that the weights are the ratio of total weighted output at the i^th component to total weighted output of whole components. In this paper, we propose three novel methods to obtain the weights of components. Then, to compare these three new methods and the methods proposed by Cook et al. (2010) and Faramarzi et al. (2014), we present a case study. Finally, using Spearman's rank correlation coefficient, we analyse the correlation among different approaches.

Keywords: network data envelopment analysis; NDEA; refineries; multi-component network; Spearman's rank correlation.

DOI: 10.1504/IJOR.2018.092015

International Journal of Operational Research, 2018 Vol.32 No.2, pp.223 - 250

Received: 05 May 2015
Accepted: 25 Jul 2015
Published online: 30 May 2018 *

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Title: Developing new methods for determining weights of components in network data envelopment analysis

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