Green lean six sigma practices: a scale development and measurement model from an engineer’s perspective

Abstract

Purpose

Since the advent of Industry 4.0, there has been a growing research interest in developing the Green Lean Six Sigma concept in the direction of achieving sustainable development, primarily aligned with Goal 12 of the agenda. Given that the concept is still in its early stages of exploration and requires further development through empirical validation, opportunities exist for innovative research. Yet, difficulties arise in adopting this green initiative due to an inadequate understanding of its strategic practices. Thus, this study aims to establish strategic practices facilitating its adoption in the Industry 4.0 era and develop a validated multi-item scale to measure the practices.

Design/methodology/approach

A three-phase methodological approach is designed to perform the techniques of exploratory and confirmatory analyses in the manufacturing context. To be a sound study, engineers have been involved since they play a pivotal role in the realm of manufacturing; however, the existing research on engineers' viewpoints on this subject is limited, emphasizing the need for further investigation.

Findings

Upon validation of the ultimate fallouts, the analyses demonstrated a confirmatory model with eighteen scales determining five practices: strategic integrity, human resource management, technologies and tools, eco-production, and eco-networks. The findings further revealed robust correlations among these core practices within the model.

Originality/value

The contribution of this study entails depicting and discussing a measurement model for future research since there is currently no empirically validated model available to measure this multidimensional green initiative.

Citation

Gholami, H., Lee, J.K.Y., Garza-Reyes, J.A. and Salameh, A.A. (2024), "Green lean six sigma practices: a scale development and measurement model from an engineer’s perspective", Journal of Manufacturing Technology Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JMTM-12-2023-0555