Purpose

In today’s globalized and heavily industrialized economy, sustainability issues that negatively affect the human population and external environment are on the rise. This study aims to investigate a synergistic combination of supply chain management and quality management practices in strengthening the sustainability performance of Malaysian manufacturing firms.

Design/methodology/approach

A total sample of 177 usable surveys was collected. Given the contributions and acceptability of the artificial neural network (ANN) approach in evaluating the findings of this study, this study uses ANN to measure the relationship between each predictor (i.e. supply chain integration [SCI], quality leadership [QL], supplier focus [SF], customer focus (CF) and information sharing [IS]) and the dependent variable (i.e. sustainability performance). Via sensitivity analysis, the relative significance of each predictor variable is ranked based on the normalized importance value.

Findings

The sensitivity analysis indicates that CF has the greatest effect on sustainability performance (SP) with 100% normalized relative importance, followed by QL (75%), IS (61.5%), SF (57.3%) and SCI (46.7%).

Originality/value

The findings of this study have the potential to provide valuable guidance and insights that can help all manufacturing firms enhance their SP from the optimum combination of the selected SCQM practices with a focus on sustainability.

中文翻译：

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展开供应链质量管理实践对可持续性绩效的影响：人工神经网络方法

目的

在当今全球化和高度工业化的经济中，对人口和外部环境产生负面影响的可持续性问题正在上升。本研究旨在调查供应链管理和质量管理实践的协同组合，以加强马来西亚制造公司的可持续发展绩效。

设计/方法/方法

共收集了 177 个可用调查的样本。鉴于人工神经网络 (ANN) 方法在评估本研究结果方面的贡献和可接受性，本研究使用 ANN 来衡量每个预测器之间的关系（即供应链集成 [SCI]、质量领导 [QL]、供应商焦点） [SF]、客户关注 (CF) 和信息共享 [IS]) 和因变量（即可持续性绩效）。通过敏感性分析，根据归一化的重要性值对每个预测变量的相对显着性进行排序。

发现

敏感性分析表明，CF 对可持续性绩效 (SP) 的影响最大，归一化相对重要性为 100%，其次是 QL (75%)、IS (61.5%)、SF (57.3%) 和 SCI (46.7%)。

原创性/价值

这项研究的结果有可能提供有价值的指导和见解，可以帮助所有制造公司通过将重点放在可持续性上的选定 SCQM 实践的最佳组合来提高他们的 SP。