Modeling a severe supply chain disruption and post-disaster decision making with application to the Japanese earthquake and tsunami

Modern supply chains are increasingly vulnerable to disruptions, and a disruption in one part of the world can cause supply difficulties for companies around the globe. This article develops a model of severe supply chain disruptions in which several suppliers suffer from disabled production facilities and firms that purchase goods from those suppliers may consequently suffer a supply shortage. Suppliers and firms can choose disruption management strategies to maintain operations. A supplier with a disabled facility may choose to move production to an alternate facility, and a firm encountering a supply shortage may be able to use inventory or buy supplies from an alternate supplier. The supplier’s and firm’s optimal decisions are expressed in terms of model parameters such as the cost of each strategy, the chances of losing business, and the probability of facilities reopening. The model is applied to a simulation based on the 2011 Japanese earthquake and tsunami, which closed several facilities of key suppliers in the automobile industry and caused supply difficulties for both Japanese and U.S. automakers.

[1]  Joost R. Santos,et al.  Measuring changes in international production from a disruption: Case study of the Japanese earthquake and tsunami , 2012 .

[2]  Ho-Yin Mak,et al.  Risk diversification and risk pooling in supply chain design , 2012 .

[3]  Kash Barker,et al.  Evaluating the Consequences of an Inland Waterway Port Closure With a Dynamic Multiregional Interdependence Model , 2012, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[4]  Haresh Gurnani,et al.  Sharing demand and supply risk in a supply chain , 2011 .

[5]  Kash Barker,et al.  Measuring the efficacy of inventory with a dynamic input-output model , 2010 .

[6]  Kash Barker,et al.  A Risk‐Based Approach for Identifying Key Economic and Infrastructure Systems , 2010, Risk analysis : an official publication of the Society for Risk Analysis.

[7]  Brian Tomlin,et al.  Impact of Supply Learning When Suppliers Are Unreliable , 2009, Manuf. Serv. Oper. Manag..

[8]  Jing-Sheng Song,et al.  Inventories with Multiple Supply Sources and Networks of Queues with Overflow Bypasses , 2009, Manag. Sci..

[9]  Serguei Netessine,et al.  Long-Term Contracts Under the Threat of Supplier Default , 2009, Manuf. Serv. Oper. Manag..

[10]  Tiaojun Xiao,et al.  Price competition, cost and demand disruptions and coordination of a supply chain with one manufacturer and two competing retailers , 2008 .

[11]  Wallace J. Hopp,et al.  Strategic Risk from Supply Chain Disruptions , 2008 .

[12]  Rajagopalan Srinivasan,et al.  Heuristic rescheduling of crude oil operations to manage abnormal supply chain events , 2007 .

[13]  Jennifer Blackhurst,et al.  The Severity of Supply Chain Disruptions: Design Characteristics and Mitigation Capabilities , 2007, Decis. Sci..

[14]  Volodymyr Babich,et al.  Competition and Diversification Effects in Supply Chains with Supplier Default Risk , 2006, Manuf. Serv. Oper. Manag..

[15]  Christopher S. Tang.  Perspectives in supply chain risk management , 2006 .

[16]  Gang Yu,et al.  Supply chain disruption management and evolutionarily stable strategies of retailers in the quantity-setting duopoly situation with homogeneous goods , 2006, European Journal of Operational Research.

[17]  A. Nagurney.  Supply Chain Network Economics: Dynamics of Prices, Flows and Profits , 2006 .

[18]  Brian Tomlin,et al.  On the Value of Mitigation and Contingency Strategies for Managing Supply Chain Disruption Risks , 2006, Manag. Sci..

[19]  Joseph Y.-T. Leung,et al.  Two Machine Scheduling under Disruptions with Transportation Considerations , 2006, J. Sched..

[20]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[21]  Anna Nagurney,et al.  Supply Chain Network Economics , 2006 .

[22]  Yossi Sheffi,et al.  The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage , 2005 .

[23]  Gang Yu,et al.  Coordination of a Supply Chain with One-Manufacturer and Two-Retailers Under Demand Promotion and Disruption Management Decisions , 2005, Ann. Oper. Res..

[24]  Martin Christopher,et al.  Logistics and supply chain management : creating value-adding networks , 2005 .

[25]  S. Chopra,et al.  Managing Risk To Avoid Supply-Chain Breakdown , 2004 .

[26]  Xiangtong Qi,et al.  Disruption Management: Framework, Models And Applications , 2004 .

[27]  Gang Yu,et al.  Real-time disruption management in a two-stage production and inventory system , 2004 .

[28]  Paul H. Zipkin,et al.  Inventory Control with Information About Supply Conditions , 1996 .

[29]  Kazuyoshi Ishii,et al.  Method of production smoothing for two-stage production and inventory system , 1993 .

[30]  James C. Bean,et al.  Matchup Scheduling with Multiple Resources, Release Dates and Disruptions , 1991, Oper. Res..

[31]  M. Parlar,et al.  Future supply uncertainty in EOQ models , 1991 .

[32]  C. C. Holt,et al.  A Linear Decision Rule for Production and Employment Scheduling , 1955 .