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Drivers, Barriers and Enablers Influencing Green, Lean Six Sigma Adoption in the Construction Industry

A Developing Economy’s Perspective

Bibliographic Data

ID22006420
AuthorsKramat Hussain (0000-0001-5381-7872, Jiangsu University, corresponding author), Sun Huaping (Jiangsu University), Muhammad Waqas (0000-0001-6151-8864, Jiangsu University), Muzaffar Iqbal (0000-0001-5821-5600, Dalian Maritime University)
Year2025
Volume15
Issue4
Publication date2025-10-01
Open AccessYes
TypeARTICLE
VenueSAGE Open (JOURNAL)
Journal identifiersISSN: 2158-2440 • E-ISSN: 2158-2440
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/21582440251389696
OpenAlexW4415989859
LanguageEN
References cited92

The energy crisis, resource depletion, competition, and waste reduction challenges have pushed organizations to embrace sustainable practices. Green Lean Six Sigma adoption (GLSA) is crucial for sustainability. However, various factors impact GLSA, including driving forces (DFs), barriers, and enablers. This study aims to analyze and model how these factors affect GLSA by collecting data from 207 respondents and using Partial Least Square Structural Equation Modeling (PLS-SEM). The findings reveal that government-related barriers have a significant negative impact on GLSA. In contrast, industry, cost, and energy-related DFs, government policies/legislation, and capability/capacity-related enablers have a positive effect. Based on the findings, an adoption strategy for Green Lean Six Sigma is proposed. These insights are valuable for managers and policymakers struggling to promote GLS in the construction industry. This study contributes to the GLS literature by analyzing the quantitative influence of barriers, DFs, and enablers on GLSA and suggesting an adoption strategy. This study highlights the need for targeted government policies and industry initiatives to overcome barriers and leverage enablers for successful GLSA implementation in construction projects, thereby enhancing sustainability and operational efficiency

Lean Six Sigma · Six Sigma · Structural equation modeling · Sustainability · Environmental Sustainability in Business · Quality and Supply Management · Sustainable Supply Chain Management

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