Analysis and modeling the enablers of Green Lean Six Sigma implementation using Interpretive Structural Modeling

Abstract

The changed customer perception and environmental regulations have enforced organizations to device the ways that remain sustainable and at the same time meet the expectations of customers. Green Lean Six Sigma (GLS) is one of the inclusive approaches that reduces the variations and wastes in the system and at the same time decreases the negative environmental impact. But, in order to implement a comprehensive GLS approach, it is indispensable to look at the enablers or foundations that consequently lead to the success of this program. The present work deals with GLS enablers identification and modeling using Interpretive Structural Modeling (ISM) to meticulously adjudicate interactions among the enablers. Besides, Impact Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) analysis has been used here to classify these enablers for better understanding. This work will facilitate the organizations to have a readiness for a strategic GLS implementation by detailed understanding of mutual relations among the enablers of GLS.