Performance analysis of sustainable supply networks with bounded, discrete, and joint factors

Monireh Jahani Sayyad Noveiri, Sohrab Kordrostami () and Alireza Amirteimoori
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Monireh Jahani Sayyad Noveiri: Islamic Azad University
Sohrab Kordrostami: Islamic Azad University
Alireza Amirteimoori: Islamic Azad University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2022, vol. 24, issue 1, No 10, 238-270

Abstract: Abstract The majority of data envelopment analysis (DEA) research studies evaluate the sustainability of processes with real-valued factors and individual role, while the investigation of sustainability of networks with bounded, discrete, and joint measures is necessary in many applications. Therefore, the purpose of this study is the examination of sustainability of supply networks and the network performance measurement when bounded, discrete, and joint variables are presented. Accordingly, an estimation approach derived from the DEA is developed in the current paper to performance assessment of sustainable supply networks (SSNs) that incorporate bounded and discrete measures as economic, social, and environmental dimensions. Moreover, the introduced approach is extended to handle situations that there are considered to be the joint factors between dimensions. The suggested approach is employed to a numerical example and the areas of sustainable banking sectors and sustainable soft drink supply networks. The reliability and performance of the proposed approach are investigated by comparison with one of the practical approaches. The findings show the proposed technique leads to creditable consequences and target points. This paper contributes by rendering a nonparametric approach based on non-radial measure to estimate efficiencies of SSNs and targets, whereas there are bounded, discrete, and/or joint attributes and also studying some applications.

Keywords: Sustainable supply network; Performance; Data envelopment analysis; Bounded measures; Discrete measures (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10668-021-01415-y

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