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

被引:126
|
作者
Foo, Pik-Yin [1 ]
Lee, Voon-Hsien [1 ]
Tan, Garry Wei-Han [1 ]
Ooi, Keng-Boon [2 ]
机构
[1] Univ Tunku Abdul Rahman, Fac Business & Finance, Petaling Jaya, Malaysia
[2] UCSI Univ, Fac Business & Informat Sci, Cheras, Malaysia
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; ARTIFICIAL-NEURAL-NETWORK; TRIPLE BOTTOM-LINE; ENVIRONMENTAL-MANAGEMENT; FRAMEWORK; IMPACT; RESOURCES; RESPONSIBILITY; IMPLEMENTATION; SATISFACTION; CAPABILITIES;
D O I
10.1016/j.eswa.2018.04.013
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:1 / 14
页数:14
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