Assessing enablers of Green Lean Six Sigma: lessons from Indian micro, small, and medium enterprises

J. Mohan et al.

International Journal of Six Sigma and Competitive Advantage2025https://doi.org/10.1504/ijssca.2025.145632article
AJG 1
Weight
0.37

What the paper says

Green Lean Six Sigma (GLSS) is a noble approach that addresses modern challenges to manufacturing enterprises. The present research work investigates enablers of GLSS for micro, small, and medium enterprises (MSMEs). Systematic literature on GLSS has been conducted to identify different enablers of GLSS. Grey relational analysis (GRA) and TOPSIS have been used to analyse different enablers of GLSS about MSMEs. Twenty-three enablers of GLSS have been identified from the literature survey. GLSS enablers' prioritisation has been done using grey relational analysis (GRA) and results were further validated using the TOPSIS method. The ranking of GLSS enablers has identified that management commitment and proper fund allocation are the most remarkable enablers with grey relational grades of 0.903 and 0.883 respectively. The present research is of its first kind and investigates different enablers of GLSS about MSMEs and provides an impetus for the adoption of the GLSS approach. The study is of the first kind that explores enablers of Green Lean Six Sigma about MSMEs of India and provides guidelines for the effective execution of this sustainable approach.

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https://doi.org/https://doi.org/10.1504/ijssca.2025.145632

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@article{j.2025,
  title        = {{Assessing enablers of Green Lean Six Sigma: lessons from Indian micro, small, and medium enterprises}},
  author       = {J. Mohan et al.},
  journal      = {International Journal of Six Sigma and Competitive Advantage},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijssca.2025.145632},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.