Impact of Industry 4.0 and lean six sigma on circular operational excellence: evidence from a PLS-SEM and ANN analysis

Purpose This study aims to investigate the impact of lean six sigma (LSS) and Industry 4.0 technologies (I4T) on circular operational excellence through the adoption of circular economy practices. In addition, it examines the moderating role of organizational preparedness in strengthening the relationship between circular economy adoption and operational excellence. Design/methodology/approach This study adopts a quantitative research design based on a structured questionnaire survey administered to 300 respondents from technology-enabled and process-driven organizations in India. Partial least squares structural equation modeling (PLS-SEM), with 10,000 bootstrapping resamples, was used to test the hypothesized relationships and evaluate the model’s predictive and explanatory power. Complementarily, artificial neural network (ANN) analysis was used to capture potential nonlinear relationships and assess the relative importance of key predictors. Findings The results demonstrate that I4.0 technologies and LSS practices significantly drive the adoption of circular economy practices. Circular economy adoption is identified as the strongest predictor of circular operational excellence, underscoring its pivotal role in converting technological and process capabilities into enhanced performance outcomes. In addition, ANN analysis reveals that organizational preparedness, when combined with circular economy adoption, significantly influences circular operational excellence under nonlinear conditions. Research limitations/implications The results highlight that organizations pursuing circular operational excellence should adopt an integrated approach encompassing I4.0 technologies, LSS practices and organizational preparedness. Strengthening internal readiness is essential for effectively leveraging circular economy initiatives and enhancing performance outcomes. Nevertheless, the study is subject to certain limitations, including its cross-sectional research design and geographic focus on India, which may limit the generalizability of the findings. Future research may consider longitudinal designs and cross-country comparisons to validate and extend these results. Originality/value This study advances the literature by developing and empirically validating an integrated framework linking I4.0, LSS and circular economy practices in the context of circular operational excellence. It further contributes methodologically by combining PLS-SEM and ANN techniques to offer complementary explanatory and predictive insights.

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Publication Details

Journal
International Journal of Lean Six Sigma
Published
2026-08-14
DOI
https://doi.org/10.1108/ijlss-05-2026-0212
Primary Topic
Digital Transformation in Industry
Type
article
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article

Impact of Industry 4.0 and lean six sigma on circular operational excellence: evidence from a PLS-SEM and ANN analysis

Rekha Goyat, Arun Arora, Mahipal Singh, Shikha Khullar et al.
International Journal of Lean Six Sigma
Digital Transformation in Industry
article

Impact of Industry 4.0 and lean six sigma on circular operational excellence: evidence from a PLS-SEM and ANN analysis

Rekha Goyat, Arun Arora, Mahipal Singh, Shikha Khullar, Monika Sharma
article en

Abstract

Purpose This study aims to investigate the impact of lean six sigma (LSS) and Industry 4.0 technologies (I4T) on circular operational excellence through the adoption of circular economy practices. In addition, it examines the moderating role of organizational preparedness in strengthening the relationship between circular economy adoption and operational excellence. Design/methodology/approach This study adopts a quantitative research design based on a structured questionnaire survey administered to 300 respondents from technology-enabled and process-driven organizations in India. Partial least squares structural equation modeling (PLS-SEM), with 10,000 bootstrapping resamples, was used to test the hypothesized relationships and evaluate the model’s predictive and explanatory power. Complementarily, artificial neural network (ANN) analysis was used to capture potential nonlinear relationships and assess the relative importance of key predictors. Findings The results demonstrate that I4.0 technologies and LSS practices significantly drive the adoption of circular economy practices. Circular economy adoption is identified as the strongest predictor of circular operational excellence, underscoring its pivotal role in converting technological and process capabilities into enhanced performance outcomes. In addition, ANN analysis reveals that organizational preparedness, when combined with circular economy adoption, significantly influences circular operational excellence under nonlinear conditions. Research limitations/implications The results highlight that organizations pursuing circular operational excellence should adopt an integrated approach encompassing I4.0 technologies, LSS practices and organizational preparedness. Strengthening internal readiness is essential for effectively leveraging circular economy initiatives and enhancing performance outcomes. Nevertheless, the study is subject to certain limitations, including its cross-sectional research design and geographic focus on India, which may limit the generalizability of the findings. Future research may consider longitudinal designs and cross-country comparisons to validate and extend these results. Originality/value This study advances the literature by developing and empirically validating an integrated framework linking I4.0, LSS and circular economy practices in the context of circular operational excellence. It further contributes methodologically by combining PLS-SEM and ANN techniques to offer complementary explanatory and predictive insights.

International Journal of Lean Six Sigma
Lovely Professional University (IN), Technology Management Company (United States) (US), Lloyd's (GB), Poornima University (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Digital Transformation in Industry
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