4.7 Article

A gateway to realising sustainability performance via green supply chain management practices: A PLS-ANN approach

期刊

EXPERT SYSTEMS WITH APPLICATIONS
卷 107, 期 -, 页码 1-14

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2018.04.013

关键词

Green supply chain management (GSCM); Sustainability performance; Partial least squares structural equation modelling (PLS-SEM); Artificial neural network analysis (ANN); Manufacturers; Malaysia

资金

  1. UTAR Research Fund (UTARRF) grant [IPSR/RMC/UTARRF/2015-C2/F02]

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This study aims to critically evaluate whether the implementation of selected green supply chain management (GSCM) practices will drive and empower sustainability among IS014001-certified manufacturing firms in Malaysia. Besides this, the significance and strength of the relationships between GSCM practices and sustainability performance were also investigated and subsequently ranked using a two-stage PLSANN approach. Primary data was collected from 178 large 15014001-certified Malaysian manufacturers through self-administered survey questionnaires. PLS-SEM using SmartPLS 3.0 and artificial neural network analysis (ANN) served as statistical analysis tools. This study draws out the prominence of GSCM practices as strategies to achieve sustainability performance. However, the relationship between supplier selection and supplier evaluation with sustainability performance is surprisingly insignificant. Furthermore, cooperation with customers is found to be significantly but negatively related to sustainability performance. Nevertheless, this contributes new knowledge to the literature with sensible justifications being offered accordingly. (C) 2018 Elsevier Ltd. All rights reserved.

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