Title: Green supply chain performance benchmarking using integrated IVFN-TOPSIS methodology

Authors: Anoop Kumar Sahu; Saurav Datta; Siba Sankar Mahapatra

Addresses: Department of Mechanical Engineering, National Institute of Technology Rourkela, Odisha-769008, India ' Department of Mechanical Engineering, National Institute of Technology Rourkela, Odisha-769008, India ' Department of Mechanical Engineering, National Institute of Technology Rourkela, Odisha-769008, India

Abstract: In today's era of globalisation, manufacturing sectors are being forced towards managing environmental sustainability in account of leverage of numerous serious global warming issues. A multiple index-based green supply chain (GSC) performance appraisement framework has been conceptualised here from the resource literature survey to empirically investigate several sustainability issues related to environmental performance of preferred candidate alternative industries. In this reporting, the subjectivity of the evaluation information has been taken into consideration by deploying a hierarchical fuzzy-based computation module capable of dealing with uncertain environment. Due to inherent ambiguity, vagueness, impreciseness and inconsistency associated with subjective information of the GSC performance indices (metric and measures), the assessment of expert panels acquired for the preferred alternative in linguistic terms pointed out by the adaptation of interval-valued fuzzy number (IVFN). Therefore, a new interval-valued fuzzy number in conjunction with modified TOPSIS (IVFM-TOPSIS) method has been explored at the deployed (hierarchical) framework for appraisement and benchmarking of the preferred candidate alternative industries operating under the similar GSC hierarchy. Finally, an empirical study has led in order to exhibit the feasibility as well as effectiveness of the proposed methodology.

Keywords: green SCM; green supply chains; supply chain management; GSCM; interval-valued fuzzy number; IVFN; TOPSIS; supply chain performance; fuzzy logic.

DOI: 10.1504/IJPMB.2013.058272

International Journal of Process Management and Benchmarking, 2013 Vol.3 No.4, pp.511 - 551

Available online: 11 Dec 2013 *

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