ISM-fuzzy MICMAC approach for analysis of GSCM enablers

ISM-fuzzy MICMAC approach for analysis of GSCM enablers

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Article ID: iaor20162727
Volume: 24
Issue: 4
Start Page Number: 426
End Page Number: 451
Publication Date: Jun 2016
Journal: International Journal of Logistics Systems and Management
Authors: ,
Keywords: geography & environment, management, simulation
Abstract:

The object of this paper is to identify the enablers to implement green supply chain and to understand their mutual relationship. Green supply chain management (GSCM) enablers are identified using available GSCM literature and on consultations with experts from industry and academician. Interpretive structural model (ISM) was developed to identify the contextual relationship among these enablers. This paper has identified 14 key GSCMEs and developed an integrated model using ISM and the fuzzy MICMAC approach, which helps to identify and classify the important GSCMEs and reveal the direct and indirect effects of each GSCME on the GSCM implementation. ISM model provides only binary relationship among GSCMEs, while fuzzy MICMAC analysis provides precise analysis related to driving and dependence power of GSCME. To overcome this limitation, integrated approach is developed. This study has strong practical implications, for both practitioners as well as academicians. The practitioners need to concentrate on identified GSCMEs more cautiously during GSCM implementation in their organisations and the top management could formulate strategy for implementing these enablers obtained through ISM and fuzzy MICMAC analysis.

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