COMPUTING THE INTENSITY OF SUSTAINABLE LEAN SIX SIGMA ENABLERS TO ENHANCE ITS ADOPTION: AN INDIAN CONTEXT STUDY

Abstract It has been a common observation among the manufacturing organisations over the past decade that the estimated financial performance can be achieved when the organisation primarily focuses on the continuous improvement process and simultaneously consider the environmental and societal parts as a whole within the product development process. In this regard, sustainable lean six sigma (SLSS) has emerged as the most prominent solution to the above addressed context. Although, over the globe several manufacturing organisations in the emerging economies have reported that the SLSS adoption remains limited due to the complex interplay of multiple organisational, managerial, technological, and sustainability-related factors. Many research studies in literature also revealed that the lack of awareness of SLSS enablers has been a common reason behind its adoption failures. The present study helps to fulfil this gap an identifies the set of most critical SLSS enablers that influences its adoption. An exhaustive literature review is conducted in order to identify the key set of SLSS enablers that strategically fit into manufacturing environment. The identified set twenty-five critical enablers are further analysed through fuzzy analytical hierarchy process (FAHP) to obtain the enablers weights. An expert team is constituted to capture the multi-criteria decision-making inputs for the fuzzy AHP approach. The results reveal that strategic and managerial factors—such as top management commitment, organisational culture, employee training and competency development, and availability of resources—emerge as the most influential enablers. The study provides strong theoretical contributions by expanding SLSS literature and presents the SLSS adoption framework with the intensity of enablers associated in the adoption process. The study findings will be beneficial for both the researchers and practitioners working the domain of SLSS.