Visual analysis of supply network risks: Insights from the electronics industry

被引:45
|
作者
Basole, Rahul C. [1 ,2 ]
Bellamy, Marcus A. [3 ,4 ]
机构
[1] Georgia Inst Technol, Sch Interact Comp, Atlanta, GA 30332 USA
[2] Georgia Inst Technol, Tennenbaum Inst, Atlanta, GA 30332 USA
[3] Georgia Inst Technol, Scheller Coll Business, Atlanta, GA 30308 USA
[4] Georgia Inst Technol, Tennenbaum Inst, Atlanta, GA 30308 USA
关键词
Supply networks; Risk management; Visualization; Network analysis; Decision support; Electronics industry; COMPLEX ADAPTIVE SYSTEMS; CHAIN RISK; PERFORMANCE-MEASUREMENT; MANAGEMENT; EVOLUTION; COLLABORATION; FLEXIBILITY; INTEGRATION; CHALLENGES; KNOWLEDGE;
D O I
10.1016/j.dss.2014.08.008
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In today's complex, global supply networks it has become increasingly challenging to identify, evaluate, and mitigate risks of disruption. Traditional supply chain practices have primarily focused on dyadic risk management, rarely considering risks in the sub-tier supply network. However, this approach severely limits a decision maker's ability to understand the highly interconnected nature of systemic risks and develop corresponding mitigation strategies. Grounded in theories of supply chains as complex systems, network analysis, and risk management, we demonstrate the importance of visual decision support for supply network risk assessment. We empirically illustrate our approach with supply network visualization examples from the electronics industry. We conclude the study with implications for the design and implementation of visual supply network decision support systems and future research opportunities. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:109 / 120
页数:12
相关论文
共 50 条