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Economic impact of production bottlenecks caused by disasters impacting interdependent industry sectors

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  • Baghersad, Milad
  • Zobel, Christopher W.

Abstract

This paper provides a new linear programming model, based on Leontief׳s input–output model, to investigate the economic consequences of production capacity bottlenecks caused by disasters. An important contribution of the paper is the incorporation of industry sectors׳ preferences in allocating limited products/services between final domestic demand, foreign final demand, and intermediate industries. This provides support for estimating some of the indirect economic impacts of disasters. The paper also considers recovery operations within disrupted sectors, from the standpoint of evaluating the performance of the economy during the transition period after a disaster. The models are implemented to investigate the economic consequences of electricity sector disruption in Singapore and, finally, computational results are reported.

Suggested Citation

  • Baghersad, Milad & Zobel, Christopher W., 2015. "Economic impact of production bottlenecks caused by disasters impacting interdependent industry sectors," International Journal of Production Economics, Elsevier, vol. 168(C), pages 71-80.
    • Handle: RePEc:eee:proeco:v:168:y:2015:i:c:p:71-80
    DOI: 10.1016/j.ijpe.2015.06.011
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    Cited by:

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    2. Pérez-Blanco, C. D & Standardi, G., 2019. "Farm waters run deep: a coupled positive multi-attribute utility programming and computable general equilibrium model to assess the economy-wide impacts of water buyback," Agricultural Water Management, Elsevier, vol. 213(C), pages 336-351.
    3. Niknejad, Ali & Petrovic, Dobrila, 2016. "A fuzzy dynamic Inoperability Input–output Model for strategic risk management in Global Production Networks," International Journal of Production Economics, Elsevier, vol. 179(C), pages 44-58.
    4. C. D. Pérez-Blanco & E. E. Koks & E. Calliari & J. Mysiak, 2018. "Economic Impacts of Irrigation-Constrained Agriculture in the Lower Po Basin," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-38, January.
    5. Raquel Sanchis & Raúl Poler, 2019. "Enterprise Resilience Assessment—A Quantitative Approach," Sustainability, MDPI, vol. 11(16), pages 1-13, August.
    6. Fraccascia, Luca & Yazan, Devrim Murat & Albino, Vito & Zijm, Henk, 2020. "The role of redundancy in industrial symbiotic business development: A theoretical framework explored by agent-based simulation," International Journal of Production Economics, Elsevier, vol. 221(C).
    7. Perez Blanco, C.D., 2018. "Waters run deep: A coupled Revealed Preference and CGE model to assess the economy-wide impacts of agricultural water buyback," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277028, International Association of Agricultural Economists.
    8. Krista Danielle S. Yu & Kathleen B. Aviso & Michael Angelo B. Promentilla & Joost R. Santos & Raymond R. Tan, 2016. "A weighted fuzzy linear programming model in economic input–output analysis: an application to risk management of energy system disruptions," Environment Systems and Decisions, Springer, vol. 36(2), pages 183-195, June.
    9. Alikhani, Reza & Torabi, S.Ali & Altay, Nezih, 2021. "Retail supply chain network design with concurrent resilience capabilities," International Journal of Production Economics, Elsevier, vol. 234(C).
    10. He, Peijun & Ng, Tsan Sheng & Su, Bin, 2017. "Energy-economic recovery resilience with Input-Output linear programming models," Energy Economics, Elsevier, vol. 68(C), pages 177-191.
    11. Darayi, Mohamad & Barker, Kash & Nicholson, Charles D., 2019. "A multi-industry economic impact perspective on adaptive capacity planning in a freight transportation network," International Journal of Production Economics, Elsevier, vol. 208(C), pages 356-368.

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