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1. Introduction
In the last decade, the economic downturn has led to a critical sense of incitement in organizations to increase productivity and cut costs, without compromising on the quality of output (Flynn and Flynn, 2005). Further, increasingly stringent customer demands and dynamic changes in the market’s environment have created more complexity and challenges for organizations in managing operations (Büyüközkan et al., 2015; Kenworthy and Balakrishnan, 2016). In this context, generating operational efficiencies alongside delivering effective output to the customers has become a vital need for survival. For that purpose, continuous improvement (CI) has been recognized as a successful management strategy in the manufacturing sector (Godinho Filho et al., 2016). Although various CI theories and practices have been used extensively, in the past few years, Lean Six Sigma (LSS) has been widely recognized and proved to be the most successful in improving a company’s operational efficiency, raising its productivity and lowering its costs (Snee, 2010; Sunder, 2016). LSS is a hybrid approach for CI, which integrates the speed of lean and the robustness of Six Sigma (Sheridan, 2000; George and George, 2003).
The roots of lean manufacturing can be attributed to the Toyota production system focusing on improving value and reducing waste in operations (Womack and Jones, 2005; Netland, 2016). For this purpose, lean processes internalize the main requirements and managerial dimensions identified in lean production principles and philosophy (Pakdil and Leonard, 2017). Literature shows evidence of lean principles as a bundle of associated practices, such as just-in-time, Kanban, total productive maintenance, 5S, etc., for implementation in companies (Browning and Heath, 2009; Köksal et al., 2011; Godinho Filho et al., 2016). Six Sigma is another well-established CI practice, with its origin at Motorola Inc. (Antony and Banuelas, 2002; Sreedharan et al., 2017). Six Sigma focuses on reducing process variation and defects in business processes, leading to customer satisfaction alongside creating bottom-line impact (Snee, 2004; Srinivas and Sreedharan, 2018). The Six Sigma methodology recommends two roadmaps for this purpose – Define-Measure Analyze-Improve-Control (DMAIC) and Define-Measure-Analyze-Design-Verify (DMADV). DMAIC is generally used as a roadmap to reduce process variation by making improvements or enhancements over the existing process, whereas DMADV (or its enhanced version DMADOV, where “O” stands for Optimize) is used predominantly...