Simulating the impact of inventory on supply chain resilience with an algorithmic process based on the supply-side dynamic inoperability input–output model

ABSTRACT The interdependent nature of highly interconnected systems, such as supply chains, renders them incapable of quickly resuming operation following a disruptive event. In the context of supply chains, previous works have demonstrated the efficacy of inventory as a mitigation strategy to delay the impact of disruptive events. However, current methods tend to focus only on a demand-driven approach, which may be inappropriate for some systems where a value-added price perturbation represents an impact. Thus, this paper offers a methodology for understanding the role of inventory in the supply-side dynamic inoperability input–output model (DIIM). To demonstrate the applicability of the proposed model, an illustrative example is presented using data from the 2012 Philippines Input–Output (I-O) Table in five different scenarios. Given a predefined planning horizon, the results of this work can serve as guidelines for decision-makers for the provision of inventory that will keep the overall inoperability of an entire supply chain at a minimum.

[1]  Yacov Y. Haimes,et al.  Supply- and Output-Side Extensions to the Inoperability Input-Output Model for Interdependent Infrastructures , 2007 .

[2]  Joseph Sarkis,et al.  Quantitative models for managing supply chain risks: A review , 2015, Eur. J. Oper. Res..

[3]  Christoph Teller,et al.  Supply chain capabilities, risks, and resilience , 2017 .

[4]  Lanndon A. Ocampo,et al.  Novel approach for manufacturing supply chain risk analysis using fuzzy supply inoperability input-output model , 2017 .

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

[6]  L. Ocampo,et al.  Supply-side inoperability input–output model (SIIM) for risk analysis in manufacturing systems , 2016 .

[7]  Ligang He,et al.  Supply-driven dynamic inoperability input-output price model for interdependent infrastructure systems , 2011 .

[8]  D. Alexander.  Resilience and disaster risk reduction: an etymological journey , 2013 .

[9]  Robson Marinho da Silva,et al.  Application of an Agent-based Supply Chain to Mitigate Supply Chain Disruptions , 2015 .

[10]  Ian Goldin,et al.  Global Governance and Systemic Risk in the 21st Century: Lessons from the Financial Crisis , 2010 .

[11]  Arpita Ghosh,et al.  Input-Output Approach in an Allocation System , 1958 .

[12]  O. Tang,et al.  Identifying risk issues and research advancements in supply chain risk management , 2011 .

[13]  Joost R. Santos,et al.  INOPERABILITY INPUT-OUTPUT MODEL 2 . 1 . Background : Leontief Input-Output Model , 2005 .

[14]  D. C. Whybark,et al.  Issues in managing disaster relief inventories , 2007 .

[15]  Yuri Merkuryev,et al.  Supply Chain Risks Analysis of a Logging Company , 2017 .

[16]  Amanda J. Schmitt,et al.  OR/MS models for supply chain disruptions: a review , 2014 .

[17]  James H. Lambert,et al.  Inoperability Input-Output Model for Interdependent Infrastructure Sectors. II: Case Studies , 2005 .

[18]  M. Christopher,et al.  Building the Resilient Supply Chain , 2004 .

[19]  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.

[20]  Christopher S. Tang.  Robust strategies for mitigating supply chain disruptions , 2006 .

[21]  J. Ali,et al.  Framework for evaluating economic impact of IT based disasters on the interdependent sectors of the US economy , 2012, 2012 IEEE Systems and Information Engineering Design Symposium.

[22]  Hokey Min,et al.  Supply chain modeling: past, present and future , 2002 .

[23]  Y. Haimes,et al.  Leontief-Based Model of Risk in Complex Interconnected Infrastructures , 2001 .

[24]  Joost R. Santos,et al.  Modeling the Demand Reduction Input‐Output (I‐O) Inoperability Due to Terrorism of Interconnected Infrastructures * , 2004, Risk analysis : an official publication of the Society for Risk Analysis.

[25]  Yacov Y. Haimes,et al.  Managing the risk of terrorism to interdependent infrastructure systems through the dynamic inoperability input–output model , 2006, Syst. Eng..

[26]  Manlio Del Giudice,et al.  Comparing supply chain risks for multiple product categories with cognitive mapping and Analytic Hierarchy Process , 2017, Technological Forecasting and Social Change.

[27]  W. Leontief.  Quantitative Input and Output Relations in the Economic Systems of the United States , 1936 .

[28]  Ruhul A. Sarker,et al.  Managing risk and disruption in production-inventory and supply chain systems: A review , 2015 .