Impact of JIT, TQM and green supply chain practices on environmental sustainability

Kenneth W. Green · R. Anthony Inman · Victor E. Sower · Pamela J. Zelbst

242 citations0/0 files storedJournal of Manufacturing Technology Management

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Sustainable Supply Chain Management Quality and Supply Management Environmental Sustainability in Business

Abstract

Purpose The purpose of this paper is to empirically assess the complementary impact of JIT, TQM and green supply chain practices on environmental performance. Design/methodology/approach Data from a sample of 225 US manufacturing managers are analyzed using a PLS-SEM methodology. Findings JIT and TQM are directly and positively associated with green supply chain management practices. JIT, TQM and green supply chain practices are complementary in that combined they provide a greater impact on environmental performance than if implemented individually. Research limitations/implications The sample is limited to US manufacturing managers, with a low response rate. Practical implications Successful implementations of JIT and TQM improvement programs support the implementation of green supply chain management practices leading to improved environmental performance. Social implications The combination of JIT, TQM and green manufacturing practices improves the environment by eliminating all forms of waste and providing customers with eco-friendly products and services. Originality/value This study is one of the first to empirically assess the complementary impact of JIT, TQM and green supply chain practices within the context of environmental sustainability.

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References

2011PLS-SEM: Indeed a Silver Bullet 1986Self-Reports in Organizational Research: Problems and Prospects 1977Estimating Nonresponse Bias in Mail Surveys 1977Estimating Nonresponse Bias in Mail Surveys 2001Accounting for common method variance in cross-sectional research designs.2011An assessment of the use of partial least squares structural equation modeling in marketing research 2009Using PLS Path Modeling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration1 2017An updated and expanded assessment of PLS-SEM in information systems research

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