IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i5p4003-d1077038.html
   My bibliography  Save this article

A Demand-Side Inoperability Input–Output Model for Strategic Risk Management: Insight from the COVID-19 Outbreak in Shanghai, China

Author

Listed:
  • Jian Jin

    (School of Economics, Hebei University, Baoding 071002, China)

  • Haoran Zhou

    (School of Economics, Hebei University, Baoding 071002, China)

Abstract

This paper proposes the dynamic inoperability input–output model (DIIM) to analyze the economic impact of COVID-19 in Shanghai in the first quarter of 2022. Based on the input–output model, the DIIM model introduces the sector elasticity coefficient, assesses the economic loss of the system and the influence of disturbances on other sectors through sectoral dependence, and simulates the inoperability and economic loss changes through time series. A multi-evaluation examination of the results reveals that the degree of inoperability of sub-sectors is inconsistent with the ranking of economic losses and that it is hard to quantify the impact of each sector directly. Different from the traditional DIIM model that only considers the negative part of the disaster, the innovation of this paper is that the negative value of the inoperability degree is used to measure the indirect positive growth of sectors under the impact of the Shanghai pandemic shock. At the same time, policymakers need to consider multi-objective optimization when making risk management decisions. This study uses surrogate worth trade-off to construct a multi-objective risk management framework to expand the DIIM model to enable policymakers to quantify the trade-off between economic benefit and investment costs when making risk management decisions.

Suggested Citation

  • Jian Jin & Haoran Zhou, 2023. "A Demand-Side Inoperability Input–Output Model for Strategic Risk Management: Insight from the COVID-19 Outbreak in Shanghai, China," Sustainability, MDPI, vol. 15(5), pages 1-22, February.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4003-:d:1077038
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/5/4003/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/5/4003/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zaghini, Enrico, 1971. "Solow Prices and the Dual Stability Paradox in the Leontief Dynamic System," Econometrica, Econometric Society, vol. 39(3), pages 625-632, May.
    2. Adam Rose & Shu‐Yi Liao, 2005. "Modeling Regional Economic Resilience to Disasters: A Computable General Equilibrium Analysis of Water Service Disruptions," Journal of Regional Science, Wiley Blackwell, vol. 45(1), pages 75-112, February.
    3. Pu Jiang & Yacov Y. Haimes, 2004. "Risk Management for Leontief‐Based Interdependent Systems," Risk Analysis, John Wiley & Sons, vol. 24(5), pages 1215-1229, October.
    4. Geoffrey J. D. Hewings & Michael Sonis & Moss Madden & Yoshio Kimura (ed.), 1999. "Understanding and Interpreting Economic Structure," Advances in Spatial Science, Springer, number 978-3-662-03947-2, Fall.
    5. Andre F. T. Avelino & Sandy Dall'erba, 2019. "Comparing the Economic Impact of Natural Disasters Generated by Different Input–Output Models: An Application to the 2007 Chehalis River Flood (WA)," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 85-104, January.
    6. Joost R. Santos & Mark J. Orsi & Erik J. Bond, 2009. "Pandemic Recovery Analysis Using the Dynamic Inoperability Input‐Output Model," Risk Analysis, John Wiley & Sons, vol. 29(12), pages 1743-1758, December.
    7. Yasuhide Okuyama & Krista D. Yu, 2019. "Return of the inoperability," Economic Systems Research, Taylor & Francis Journals, vol. 31(4), pages 467-480, October.
    8. Amine El Haimar & Joost Santos, 2015. "A stochastic recovery model of influenza pandemic effects on interdependent workforce systems," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 987-1011, June.
    9. Zaghini, Enrico, 1971. "Solow Prices and the Dual Stability Paradox in the Leontief Dynamic System: A Reply," Econometrica, Econometric Society, vol. 39(3), pages 634-634, May.
    10. Joost R. Santos & Yacov Y. Haimes, 2004. "Modeling the Demand Reduction Input‐Output (I‐O) Inoperability Due to Terrorism of Interconnected Infrastructures," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1437-1451, December.
    11. Jan Oosterhaven, 2017. "On the limited usability of the inoperability IO model," Economic Systems Research, Taylor & Francis Journals, vol. 29(3), pages 452-461, July.
    12. Mark Skidmore & Hideki Toya, 2002. "Do Natural Disasters Promote Long-Run Growth?," Economic Inquiry, Western Economic Association International, vol. 40(4), pages 664-687, October.
    13. Chenyang Lian & Yacov Y. Haimes, 2006. "Managing the risk of terrorism to interdependent infrastructure systems through the dynamic inoperability input–output model," Systems Engineering, John Wiley & Sons, vol. 9(3), pages 241-258, September.
    14. Sharon M. Brucker & Steven E. Hastings & William R. Latham III, 1990. "The Variation of Estimated Impacts from Five Regional Input-Output Models," International Regional Science Review, , vol. 13(1-2), pages 119-139, April.
    15. Kousky, Carolyn, 2014. "Informing climate adaptation: A review of the economic costs of natural disasters," Energy Economics, Elsevier, vol. 46(C), pages 576-592.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Pradeep V. Mandapaka & Edmond Y. M. Lo, 2023. "Assessing Shock Propagation and Cascading Uncertainties Using the Input–Output Framework: Analysis of an Oil Refinery Accident in Singapore," Sustainability, MDPI, vol. 15(2), pages 1-24, January.
    3. Rui Huang & Arunima Malik & Manfred Lenzen & Yutong Jin & Yafei Wang & Futu Faturay & Zhiyi Zhu, 2022. "Supply-chain impacts of Sichuan earthquake: a case study using disaster input–output analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(3), pages 2227-2248, February.
    4. Joost R. Santos, 2006. "Inoperability input‐output modeling of disruptions to interdependent economic systems," Systems Engineering, John Wiley & Sons, vol. 9(1), pages 20-34, March.
    5. Monge, Juan J. & McDonald, Garry W., 2020. "The Economy-Wide Value-at-Risk from the Exposure of Natural Capital to Climate Change and Extreme Natural Events: The Case of Wind Damage and Forest Recreational Services in New Zealand," Ecological Economics, Elsevier, vol. 176(C).
    6. Hu, Xi & Pant, Raghav & Hall, Jim W. & Surminski, Swenja & Huang, Jiashun, 2019. "Multi-scale assessment of the economic impacts of flooding: evidence from firm to macro-level analysis in the Chinese manufacturing sector," LSE Research Online Documents on Economics 100534, London School of Economics and Political Science, LSE Library.
    7. 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.
    8. Suman K SHARMA, 2010. "Socio-Economic Aspects of Disaster’s Impact: An Assessment of Databases and Methodologies," Economic Growth Centre Working Paper Series 1001, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    9. Xi Hu & Raghav Pant & Jim W. Hall & Swenja Surminski & Jiashun Huang, 2019. "Multi-Scale Assessment of the Economic Impacts of Flooding: Evidence from Firm to Macro-Level Analysis in the Chinese Manufacturing Sector," Sustainability, MDPI, vol. 11(7), pages 1-18, April.
    10. Hallegatte, Stephane, 2014. "Economic resilience: definition and measurement," Policy Research Working Paper Series 6852, The World Bank.
    11. Krista Danielle S. Yu & Kathleen B. Aviso & Joost R. Santos & Raymond R. Tan, 2020. "The Economic Impact of Lockdowns: A Persistent Inoperability Input-Output Approach," Economies, MDPI, vol. 8(4), pages 1-14, December.
    12. Wenping Xu & Zongjun Wang & Liu Hong & Ligang He & Xueguang Chen, 2015. "The uncertainty recovery analysis for interdependent infrastructure systems using the dynamic inoperability input–output model," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(7), pages 1299-1306, May.
    13. Sellevåg, Stig Rune, 2021. "Changes in inoperability for interdependent industry sectors in Norway from 2012 to 2017," International Journal of Critical Infrastructure Protection, Elsevier, vol. 32(C).
    14. Tanaka, Ayumu, 2015. "The impacts of natural disasters on plants' growth: Evidence from the Great Hanshin-Awaji (Kobe) earthquake," Regional Science and Urban Economics, Elsevier, vol. 50(C), pages 31-41.
    15. Yasuhide Okuyama, 2015. "How shaky was the regional economy after the 1995 Kobe earthquake? A multiplicative decomposition analysis of disaster impact," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 55(2), pages 289-312, December.
    16. Qin Fan & Meri Davlasheridze, 2019. "Economic Impacts Of Migration And Brain Drain After Major Catastrophe: The Case Of Hurricane Katrina," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 1-21, February.
    17. Hiroki Onuma & Kong Joo Shin & Shunsuke Managi, 2021. "Short-, Medium-, and Long-Term Growth Impacts of Catastrophic and Non-catastrophic Natural Disasters," Economics of Disasters and Climate Change, Springer, vol. 5(1), pages 53-70, April.
    18. Emmanuel Apergis & Nicholas Apergis, 2021. "The impact of COVID-19 on economic growth: evidence from a Bayesian Panel Vector Autoregressive (BPVAR) model," Applied Economics, Taylor & Francis Journals, vol. 53(58), pages 6739-6751, December.
    19. Yasuyuki Todo & Kentaro Nakajima & Petr Matous, 2015. "How Do Supply Chain Networks Affect The Resilience Of Firms To Natural Disasters? Evidence From The Great East Japan Earthquake," Journal of Regional Science, Wiley Blackwell, vol. 55(2), pages 209-229, March.
    20. Yasuhide Okuyama & Michael Sonis & Geoffrey Hewings, 2006. "Typology of structural change in a regional economy: a temporal inverse analysis," Economic Systems Research, Taylor & Francis Journals, vol. 18(2), pages 133-153.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4003-:d:1077038. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.