供应链
计算机科学
钥匙(锁)
原型
供应链网络
可视化
实证研究
网络拓扑
供应链管理
供应网络
服务管理
拓扑(电路)
数据科学
分布式计算
功率(物理)
数据挖掘
业务
工程类
计算机网络
计算机安全
营销
艺术
哲学
文学类
物理
电气工程
认识论
量子力学
标识
DOI:10.1109/smrlo.2016.98
摘要
The idea of this research is to explore the evolution of a supply chain using an empirical approach. This can be achieved by harnessing the power of Bloomberg data with network visualization software. Such an investigation will help identify supply chain archetypes as well as lead to an understanding of how these supply chains might change over time. Coupled with additional secondary data sources, we could learn more about how these changes might be impacted by, and impact, firm performance. In this paper, we explore a number of supply networks and develop their associated supply chain maps. We use key metrics from social network analysis to quantify the nature of these networks and understand how they evolve. This empirical data is then used to create a paradigm which explains the structure of these supply networks. We use the maps and the metrics developed to describe them to draw preliminary conclusions about how supply network topology impacts its performance.
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