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<p>Although lean manufacturing is increasingly linked to environmental performance, the sequential mechanism through which diagnostic tools deliver sustainability outcomes has not been empirically modeled. This study tests how gemba (GEM), value stream mapping (VSM), and 5 whys (5WHY) jointly shape environmental sustainability (ESU) in the manufacturing industry. A structural equation model integrating six hypotheses was validated with PLS-SEM using 834 responses from professionals in Mexican manufacturing firms, and all hypotheses were statistically supported. The GEM→VSM→5WHY→ESU sequence explained 46.4% of the variance in ESU. GEM exerted its strongest influence on VSM (β = 0.679), and its effect on ESU was predominantly indirect through VSM and 5WHY (β = 0.420 vs. a direct β = 0.152), indicating that observation alone is insufficient without systematic mapping and root cause analysis. Conditional probability analysis revealed asymmetry: the conditional probability of low ESU scores given low VSM scores was 0.672, the strongest risk association in the model. To the best of the authors’ knowledge, this is the first study to statistically model the hypothesized sequential relationships among GEM, VSM, 5WHY, and ESU with quantified probabilistic asymmetries that offer empirical evidence to prioritize environmental risk and provides a reference model for nested lean-sustainability relationships to SEM researchers.</p>

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Lean diagnostic tools and environmental sustainability: evidence from the manufacturing industry

  • 期刊论文

  • 发表日期：

    2026年7月18日

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  • Jorge Luis García Alcaraz,
  • Jorge Limon-Romero,
  • Yolanda Baez-Lopez,
  • Emilio Jiménez Macías,
  • Yashar Aryanfar,
  • Antonio Javier Barragán

摘要

Although lean manufacturing is increasingly linked to environmental performance, the sequential mechanism through which diagnostic tools deliver sustainability outcomes has not been empirically modeled. This study tests how gemba (GEM), value stream mapping (VSM), and 5 whys (5WHY) jointly shape environmental sustainability (ESU) in the manufacturing industry. A structural equation model integrating six hypotheses was validated with PLS-SEM using 834 responses from professionals in Mexican manufacturing firms, and all hypotheses were statistically supported. The GEM→VSM→5WHY→ESU sequence explained 46.4% of the variance in ESU. GEM exerted its strongest influence on VSM (β = 0.679), and its effect on ESU was predominantly indirect through VSM and 5WHY (β = 0.420 vs. a direct β = 0.152), indicating that observation alone is insufficient without systematic mapping and root cause analysis. Conditional probability analysis revealed asymmetry: the conditional probability of low ESU scores given low VSM scores was 0.672, the strongest risk association in the model. To the best of the authors’ knowledge, this is the first study to statistically model the hypothesized sequential relationships among GEM, VSM, 5WHY, and ESU with quantified probabilistic asymmetries that offer empirical evidence to prioritize environmental risk and provides a reference model for nested lean-sustainability relationships to SEM researchers.