Topological robustness of the global automotive industry

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• 作者：Alexandra Brintrup ; Anna Ledwoch ; Jose Barros
• 关键词：Complex network ; Supply ; Manufacturing ; Robustness
• 刊名：Logistics Research
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：9
• 期：1
• 全文大小：1,967 KB
• 参考文献：1.Amaral LAN, Scala A, Barthélémy M, Stanley HE (2000) Classes of small-world networks. Proc Natl Acad Sci USA 97(21):11149–11152CrossRef
  2.Barabási A, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509–512MathSciNet CrossRef
  3.Basole R, Bellamy MA (2014) Supply Chain Risk Diffusion. Decis Sci 45(4):753–789
  4.Blondel VD, Guillaume J, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. J Stat Mech Theory Exp 10(2008):P10008CrossRef
  5.Borgatti S, Li X (2009) On social network analysis in a supply chain context. J Supply Chain Manag 1(1):7–22
  6.Brintrup A, Kito T, New S, Reed-Tsochas F (2011) From transaction cost economics to food webs: a multi-disciplinary discussion on the length of supply chains. EUROMA, Cambridge
  7.Brintrup A, Wang Y, Tiwari A (2015) Supply networks as complex systems: a network-science-based characterization. IEEE Sys. doi:10.​1109/​JSYST.​2015.​2425137
  8.Carter CR, Ellram LM, Tate WL (2007) The use of social network analysis in logistics research. J Bus Logist 28(1):137–168CrossRef
  9.Chaturvedi A, Martínez-de-Albéniz V (2011) Optimal procurement design in the presence of supply risk. Manuf Serv Oper Manag 13(2):227–243
  10.Choi TY, Dooley KJ, Rungtusanatham M (2001) Supply networks and complex adaptive systems: control versus emergence. J Oper Manag 19(3):351–366CrossRef
  11.Costa LDF, Rodrigues FA, Travieso G, Villas Boas PR (2007) Characterization of complex networks: a survey of measurements. Adv Phys 56(1):167–242CrossRef
  12.Dueñas-Osorio L, Craig JI, Goodno BJ, Bostrom A (2007) Interdependent response of networked systems. J Infrastruct Syst 13(3):185–194CrossRef
  13.Girvan M, Newman MEJ (2002) Community structure in social and biological networks. Proc Natl Acad Sci USA 99:7821MATH MathSciNet CrossRef
  14.Kähkönen AK, Virolainen VM (2011) Sources of structural power in the context of value nets. J Purch Supply Manag 17(2):109–120CrossRef
  15.Keqiang W, Zhaofeng Z, Dongchuan S (2008) Structure analysis of supply chain networks based on complex network theory. In: Proceedings of the fourth international conference on semantics, knowledge and grid. IEEE Computer Society, Washington, pp 493–494
  16.Kim Y, Choi TY, Yan T, Dooley K (2011) Structural investigation of supply networks: a social network analysis approach. J Oper Manag 29(3):194–211CrossRef
  17.Kurtenbach E, Karty SS (2011) As Japan shutdowns drag on, auto crisis worsens, Bloomberg Business Week. http://​www.​businessweek.​com
  18.Lomi A, Pattison P (2006) Manufacturing relations: an empirical study of the organization of production across multiple networks. Organ Sci 17(3):313–332CrossRef
  19.Nair A, Vidal JM (2011) Supply network topology and robustness against disruptions–an investigation using multi-agent model. Int J Prod Res 49(5):1391–1404CrossRef
  20.Newman MEJ (2006) Modularity and community structure in networks. Proc Natl Acad Sci USA 103(23):8577CrossRef
  21.Newman MEJ (2010) Networks: an introduction. Oxford University Press, OxfordCrossRef
  22.Punter A, Coburn A, Ralph D, Tuveson M, Ruffle S, Browman G. (2013) Evolving risk frameworks: modelling resilient business systems as interconnected networks. In: Proceedings of the think outside the risk, aon benfield hazards conference, gold coast, Australia, 22–24 September 2013
  23.Saveedra S, Reed-Tsochas F, Uzzi B (2008) Asymmetric disassembly and robustness in declining networks. Proc Natl Acad Sci 105(43):16466–16471CrossRef
  24.Snyder LV, Atan Z, Peng P, Rong Y, Schmitt AJ, Sinsoysal B (2012) OR/MS models for supply chain disruptions: a review. Available at SSRN 1689882
  25.Thadakamaila HP, Raghavan UN, Kumara S, Albert R (2004) Survivability of multi agent-based supply networks: a topological perspective. IEEE Intell Syst 19(5):24–31CrossRef
  26.Tomlin BT (2006) On the value of mitigation and contingency strategies for managing supply chain disruption risks. Manag Sci 52(5):639–657MATH MathSciNet CrossRef
  27.Watts DJ (2004) The new science of networks. Annu Rev Sociol 30:243–270CrossRef
  28.Yang Z, Aydın G, Babich V, Beil DR (2009) Supply disruptions, asymmetric information, and a backup production option. Manag Sci 55(2):192–209MATH CrossRef
  29.Zeng Y, Xiao R (2014) Modelling of cluster supply network with cascading failure spread and its vulnerability analysis. Int J Prod Res 52(23):6938–6953CrossRef
  30.Zhao K (2011) Analyzing the resilience of complex supply network topologies against random and targeted disruptions. IEEE Syst J 5(1):28–39CrossRef
  
• 作者单位：Alexandra Brintrup (1) (2)
  Anna Ledwoch (1) (2)
  Jose Barros (1) (2)
  
  1. Manufacturing and Materials, Cranfield University, Cranfield, Bedfordshire, MK43 0AL, UK
  2. Institute for Manufacturing, University of Cambridge, Cambridge, CB3 0FS, UK
  
• 刊物类别：Engineering
• 刊物主题：Engineering Economics, Organization, Logistics and Marketing
  Production and Logistics
  Industrial and Production Engineering
  Philosophy of Language
  Operations Research/Decision Theory
  Commercial Law
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1865-0368

文摘

The manufacturing industry is characterized by large-scale interdependent networks as companies buy goods from one another, but do not control or design the overall flow of materials. The result is a complex emergent structure with which companies connect to each other. The topology of this structure impacts the industry’s robustness to disruptions in companies, countries, and regions. In this work, we propose an analysis framework for examining robustness in the manufacturing industry and validate it using an empirical dataset. Focusing on two key angles, suppliers and products, we highlight macroscopic and microscopic characteristics of the network and shed light on vulnerabilities of the system. It is shown that large-scale data on structural interdependencies can be examined with measures based on network science. Keywords Complex network Supply Manufacturing Robustness