通过动态数据分析释放可持续供应链绩效:可持续创新和供应链弹性多重调解模型
Arsalan Zahid Piprani1, Syed Abdul Rehman Khan2, Rabiya Salim3
1Department of Management, Sunway University, Selangor, Malaysia.
概括
动态数据分析能力增强了创新和弹性,从而带来了可持续的供应链性能. 这项研究首次揭示了顺序调解效应,指导企业走向数据驱动的创新和弹性战略.
科学领域:
- 供应链管理 供应链管理
- 业务分析 业务分析
- 组织行为 组织行为
背景情况:
- 集成动态数据分析能力 (DDAC) 与创新能力 (IC) 和供应链弹性 (RES) 是实现可持续供应链绩效 (SSCP) 的关键.
- 现有的文献缺乏对DDAC和SSCP之间IC和RES的顺序调解效应的经验研究.
- 了解这些关系对于优化数据驱动环境中的供应链可持续性至关重要.
研究的目的:
- 实证地研究创新能力和供应链弹性在动态数据分析能力和可持续供应链绩效之间的顺序调解效应.
- 为了解DDAC,IC,RES和SSCP之间的互连提供一个理论框架.
- 为寻求通过增强数据分析,创新和弹性来改善SSCP的企业提供实际指导.
主要方法:
- 使用来自259家巴基斯坦大型制造业公司的调查数据的定量方法.
- 部分最小平方结构方程建模 (PLS-SEM) 用于测试假设关系.
- 分析产品创新,流程创新和供应链弹性等产品创新,流程创新和供应链弹性的顺序调解作用.
主要成果:
- 动态数据分析能力对创新能力和供应链弹性都有积极的影响.
- 创新能力和供应链弹性顺序调解DDAC和SSCP之间的关系.
- 这些发现证实了DDAC通过创新和弹性相结合的途径对SSCP产生显著的积极影响.
结论:
- 将数据驱动的创新与供应链弹性相结合,对于实现卓越的可持续供应链性能至关重要.
- 企业应该采用整体方法,利用DDAC来促进创新和弹性,以提高可持续性成果.
- 该研究强调了产品,流程和弹性在DDAC-SSCP联系中的关键调解作用,为战略实施提供了可操作的见解.
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