在制造业中将绿色供应链管理实践与环境绩效联系起来:混合SEM-ANN方法
Rashed Al Karim1, Mohammad Rokibul Kabir1,2, Md Karim Rabiul3
1School of Business Administration, East Delta University, Chattogram, Bangladesh.
Environmental science and pollution research international
|January 24, 2024
概括
绿色设计和制造提高了环境绩效,而合作则减轻了这些影响. 本研究使用先进的建模探索了孟加拉国的绿色供应链管理 (GSCM).
科学领域:
- 环境科学 环境科学
- 运营管理 运营管理
- 商业战略 商业战略
背景情况:
- 绿色供应链管理 (GSCM) 对于提高制造业环境绩效至关重要.
- 了解环境合作的调节作用对于有效实施GSCM至关重要.
- 现有的研究经常使用线性模型,需要复杂关系的先进方法.
研究的目的:
- 确定GSCM实践对环境绩效的影响.
- 调查供应链环境合作的温和效应.
- 使用混合PLS-SEM和人工神经网络 (ANN) 模型来探索这些关系.
主要方法:
- 调查数据来自370名孟加拉制造公司的员工.
- 部分最小平方结构方程建模 (PLS-SEM) 用于假设测试.
- 人工神经网络 (ANN) 用于检查非线性关系.
主要成果:
- 绿色设计和绿色制造显著提高了环境绩效.
- 绿色采购和绿色配送没有显著的直接影响.
- 环境合作积极调节了绿色设计/分销与环境绩效之间的联系.
结论:
- 具体的GSCM实践,如绿色设计和制造,是环境绩效的关键驱动因素.
- 供应链环境合作发挥着重要的调节作用,增强了某些GSCM影响.
- 混合PLS-SEM和ANN方法为GSCM环境绩效动态提供了更细致的理解.
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