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The objective of this article is to identify the relationships between the enablers in the implementation of Green Lean Six Sigma (GLSS) in the Mexican manufacturing industry (MMI).

To create the survey instrument, the authors did an extensive literature research, which they then applied in the MMI to find the relationships between enablers and their impact on the positive effects of implementing GLSS projects. Using exploratory and confirmatory factor analyses (EFA and CFA), the data were empirically and statistically corroborated. Furthermore, the authors validated the hypotheses that support the research using the structural equation modeling (SEM) approach in SPSS Amos.

The findings reveal that leadership has a positive impact on social and economic benefits (EcB), as well as an indirect impact on the environmental benefits (EB) of GLSS projects, with organizational involvement (OI) and performance measurement (PM) functioning as mediators.

This study represents an empirical reference for practitioners and researchers pursuing high-quality, low-cost, environmentally and socially sustainable products or processes through the implementation of GLSS projects in the manufacturing industry.

This study provides a statistically validated model using the SEM technique to represent the relationships between GLSS enablers in the MMI.

This paper aims to provide new and valuable insights for organizations that have decided to implement Lean Six Sigma (LSS) as a strategy for continuous improvement in search of business excellence. This objective is achieved through statistically modeling the causal relationships between the critical success factors (CSFs) of LSS for a successful deployment of this strategy.

A statistically validated questionnaire was used to collect information from LSS practitioners in manufacturing industries located on Mexico’s northern border. Some hypotheses for relationships between LSS CSFs are developed theoretically first and empirically tested later using the structural equation modeling technique.

Proposed relationships between LSS CSFs have been demonstrated to be statistically significant, making clear that this implementation should always begin with a strong and decided participation and commitment of top management. Later, other CSFs must be activated and put into operation in a specified order to increase the probability of a successful implementation reflected in well-executed continuous improvement projects and achieving the expected benefits.

This paper proposes a structural model which has been statistically validated with information directly collected from skilled practitioners who have developed continuous improvement projects using the LSS methodology. Further, some relationships between LSS CSFs that, to the best of the author’s knowledge, had not been demonstrated empirically are now explored and verified in our work.

This paper aims to identify the relationships among critical success factors (CSFs) for lean six sigma (LSS) implementation in higher education institutions (HEIs).

An extensive literature review was conducted to design the survey instrument, which the authors later administered in Mexican public HEIs to identify the existing relationships among the CSFs and their impact on the benefits obtained from implementing LSS projects. The data were empirically and statistically validated using exploratory and confirmatory factor analysis. Additionally, the authors applied the structural equation modeling (SEM) technique on SPSS Amos to validate the nine hypotheses supporting the research.

The results suggest that the success of LSS projects in HEIs is highly bound to a serious commitment from top management and several interrelated factors.

The main limitations of the study are that the research is cross-sectional in nature and regional in focus. Namely, the data used to validate the structural model were gathered from a small representative subset of the study population – i.e. Mexican public HEIs – and at a specific point in time.

The results reported here represent a reference framework for HEIs worldwide that wish to continuously improve their processes through LSS improvement projects.

This study proposes a statistically validated model using the SEM technique that depicts the relationships among LSS CSFs in HEIs.

The purpose of this paper aims at investigating which lean supply chain management (LSCM) practices efficiently improve the supply chain performance.

To achieve that, a cross-sectional survey was carried out with 113 manufacturing companies undergoing a lean implementation. The proposed method combines complementary methods of multivariate data analysis in order to determine which bundles of LSCM practices more efficiently entail improvements on supply chain performance.

The findings justify why some LSCM initiatives may find larger barriers than others, compromising their success due to misguided implementation efforts according to the desired performance improvement.

The empirical examination on the efficiency of LSCM practices with regards to a certain set of performance indicators provides guidelines with respect to LSCM implementation depending on which performance indicators are envisioned for improvement.

The objective of the study is to design and validate an instrument that allows organizations to assess their status regarding the adoption of the critical success factors (CSFs) that enable lean six sigma (LSS) implementation in order to achieve the expected benefits.

An extensive literature review was conducted to define the LSS CSFs that have to be considered for the development of the questionnaire that would later be applied across all manufacturing companies on the Northern Mexican border. Once the database was built, a statistical verification of the assumptions required for factor analysis took place. Finally, the due construct validation was carried out to verify whether the proposed instrument measured reliably what it is intended to.

A questionnaire measuring nine CSFs, as well as the benefits associated with the implementation of LSS, was designed and validated through 61 items.

The main limitations of this study are that the research is cross-sectional and that the study was carried out taking as a reference only exporting manufacturing companies located in the border area between Mexico and the United States.

The validated instrument is expected to serve as a useful tool for companies interested in the implementation of LSS.

This study introduces a validated tool for the analysis of LSS CSFs while providing evidence of construct validity and the solid structure of the factors.