IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v227y2020ics0925527320300517.html
   My bibliography  Save this article

Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure

Author

Listed:
  • Dixit, Vijaya
  • Verma, Priyanka
  • Tiwari, Manoj Kumar

Abstract

The present study assesses supply chain resilience based on network structural parameters. Resilience is computed as a composite effect of density, centrality, connectivity, and network size of the network. A simulation-based approach is adopted, wherein networks of 23 firms operating in India are subjected to risk combinations of five mutually inclusive independent scenarios of probability levels and five mutually exclusive and exhaustive impact levels. The worst-case performance of the supply chain network when subjected to high impact and low probability risks is captured using conditional-value at risk (CVaR). Results reveal that the firm which has the lowest density and centrality and the highest connectivity and network size, exhibits the highest resilience. Whereas, the firm which has the highest density and high centrality due to an aggregation node exhibits the lowest resilience.

Suggested Citation

  • Dixit, Vijaya & Verma, Priyanka & Tiwari, Manoj Kumar, 2020. "Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure," International Journal of Production Economics, Elsevier, vol. 227(C).
    • Handle: RePEc:eee:proeco:v:227:y:2020:i:c:s0925527320300517
    DOI: 10.1016/j.ijpe.2020.107655
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527320300517
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2020.107655?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ivanov, Dmitry & Sokolov, Boris, 2013. "Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty," European Journal of Operational Research, Elsevier, vol. 224(2), pages 313-323.
    2. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2018. "Ripple effect in the supply chain: an analysis and recent literature," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 414-430, January.
    3. Seyed Mohammad Khalili & Fariborz Jolai & Seyed Ali Torabi, 2017. "Integrated production–distribution planning in two-echelon systems: a resilience view," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1040-1064, February.
    4. Rudberg, Martin & Olhager, Jan, 2003. "Manufacturing networks and supply chains: an operations strategy perspective," Omega, Elsevier, vol. 31(1), pages 29-39, February.
    5. Dmitry Ivanov, 2018. "Supply Chain Management and Structural Dynamics Control," International Series in Operations Research & Management Science, in: Structural Dynamics and Resilience in Supply Chain Risk Management, chapter 0, pages 1-18, Springer.
    6. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    7. Salehi Sadghiani, N. & Torabi, S.A. & Sahebjamnia, N., 2015. "Retail supply chain network design under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 95-114.
    8. Belarmino Adenso-Díaz & Julio Mar-Ortiz & Sebastián Lozano, 2018. "Assessing supply chain robustness to links failure," International Journal of Production Research, Taylor & Francis Journals, vol. 56(15), pages 5104-5117, August.
    9. Michael Lim & Mark S. Daskin & Achal Bassamboo & Sunil Chopra, 2010. "A facility reliability problem: Formulation, properties, and algorithm," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(1), pages 58-70, February.
    10. Reyes Levalle, Rodrigo & Nof, Shimon Y., 2015. "Resilience by teaming in supply network formation and re-configuration," International Journal of Production Economics, Elsevier, vol. 160(C), pages 80-93.
    11. Sawik, Tadeusz, 2013. "Selection of resilient supply portfolio under disruption risks," Omega, Elsevier, vol. 41(2), pages 259-269.
    12. Kevin P. Scheibe & Jennifer Blackhurst, 2018. "Supply chain disruption propagation: a systemic risk and normal accident theory perspective," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 43-59, January.
    13. Lichun Chen & Elise Miller-Hooks, 2012. "Resilience: An Indicator of Recovery Capability in Intermodal Freight Transport," Transportation Science, INFORMS, vol. 46(1), pages 109-123, February.
    14. Chowdhury, Md. Maruf Hossan & Quaddus, Mohammed A., 2015. "A multiple objective optimization based QFD approach for efficient resilient strategies to mitigate supply chain vulnerabilities: The case of garment industry of Bangladesh☆,☆☆☆This manuscript was pro," Omega, Elsevier, vol. 57(PA), pages 5-21.
    15. Huang, Dashan & Zhu, Shushang & Fabozzi, Frank J. & Fukushima, Masao, 2010. "Portfolio selection under distributional uncertainty: A relative robust CVaR approach," European Journal of Operational Research, Elsevier, vol. 203(1), pages 185-194, May.
    16. Angappa Gunasekaran & Nachiappan Subramanian & Shams Rahman, 2015. "Supply chain resilience: role of complexities and strategies," International Journal of Production Research, Taylor & Francis Journals, vol. 53(22), pages 6809-6819, November.
    17. Boris Sokolov & Dmitry Ivanov & Alexandre Dolgui & Alexander Pavlov, 2016. "Structural quantification of the ripple effect in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 152-169, January.
    18. Brusset, Xavier & Teller, Christoph, 2017. "Supply chain capabilities, risks, and resilience," International Journal of Production Economics, Elsevier, vol. 184(C), pages 59-68.
    19. John R. Macdonald & Christopher W. Zobel & Steven A. Melnyk & Stanley E. Griffis, 2018. "Supply chain risk and resilience: theory building through structured experiments and simulation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(12), pages 4337-4355, June.
    20. Benjamin R. Tukamuhabwa & Mark Stevenson & Jerry Busby & Marta Zorzini, 2015. "Supply chain resilience: definition, review and theoretical foundations for further study," International Journal of Production Research, Taylor & Francis Journals, vol. 53(18), pages 5592-5623, September.
    21. Emma Brandon-Jones & Brian Squire & Yvonne G.T. Van Rossenberg, 2015. "The impact of supply base complexity on disruptions and performance: the moderating effects of slack and visibility," International Journal of Production Research, Taylor & Francis Journals, vol. 53(22), pages 6903-6918, November.
    22. Kamalahmadi, Masoud & Parast, Mahour Mellat, 2016. "A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research," International Journal of Production Economics, Elsevier, vol. 171(P1), pages 116-133.
    23. Jihee Han & KwangSup Shin, 2016. "Evaluation mechanism for structural robustness of supply chain considering disruption propagation," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 135-151, January.
    24. Ritesh Ojha & Abhijeet Ghadge & Manoj Kumar Tiwari & Umit S. Bititci, 2018. "Bayesian network modelling for supply chain risk propagation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5795-5819, September.
    25. Yi-Kuei Lin & Cheng-Fu Huang & Yi-Chieh Liao & Chih-Ching Yeh, 2017. "System reliability for a multistate intermodal logistics network with time windows," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1957-1969, April.
    26. Cardoso, Sónia R. & Paula Barbosa-Póvoa, Ana & Relvas, Susana & Novais, Augusto Q., 2015. "Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty," Omega, Elsevier, vol. 56(C), pages 53-73.
    27. Nader Azad & Georgios Saharidis & Hamid Davoudpour & Hooman Malekly & Seyed Yektamaram, 2013. "Strategies for protecting supply chain networks against facility and transportation disruptions: an improved Benders decomposition approach," Annals of Operations Research, Springer, vol. 210(1), pages 125-163, November.
    28. Snoeck, André & Udenio, Maximiliano & Fransoo, Jan C., 2019. "A stochastic program to evaluate disruption mitigation investments in the supply chain," European Journal of Operational Research, Elsevier, vol. 274(2), pages 516-530.
    29. Alexander, S. & Coleman, T.F. & Li, Y., 2006. "Minimizing CVaR and VaR for a portfolio of derivatives," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 583-605, February.
    30. Dias, Alexandra, 2016. "The economic value of controlling for large losses in portfolio selection," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 81-91.
    31. Rockafellar, R. Tyrrell & Uryasev, Stan & Zabarankin, Michael, 2006. "Master funds in portfolio analysis with general deviation measures," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 743-778, February.
    32. Dmitry Ivanov, 2017. "Simulation-based single vs. dual sourcing analysis in the supply chain with consideration of capacity disruptions, big data and demand patterns," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 11(1), pages 24-43.
    33. Dmitry Ivanov, 2018. "Structural Dynamics and Resilience in Supply Chain Risk Management," International Series in Operations Research and Management Science, Springer, number 978-3-319-69305-7, September.
    34. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    35. Kelle, Peter & Schneider, Helmut & Yi, Huizhi, 2014. "Decision alternatives between expected cost minimization and worst case scenario in emergency supply – Second revision," International Journal of Production Economics, Elsevier, vol. 157(C), pages 250-260.
    36. Chowdhury, Md Maruf H. & Quaddus, Mohammed, 2017. "Supply chain resilience: Conceptualization and scale development using dynamic capability theory," International Journal of Production Economics, Elsevier, vol. 188(C), pages 185-204.
    37. Sarah Yini Gao & David Simchi-Levi & Chung-Piaw Teo & Zhenzhen Yan, 2019. "Disruption Risk Mitigation in Supply Chains: The Risk Exposure Index Revisited," Operations Research, INFORMS, vol. 67(3), pages 831-852, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gu, Xinbing & Chan, Hing Kai & Thadani, Dimple R. & Chan, Faith Ka Shun & Peng, Yi, 2023. "The role of digital techniques in organisational resilience and performance of logistics firms in response to disruptive events: Flooding as an example," International Journal of Production Economics, Elsevier, vol. 266(C).
    2. Fan, Dongming & Sun, Bo & Dui, Hongyan & Zhong, Jilong & Wang, Ziyao & Ren, Yi & Wang, Zili, 2022. "A modified connectivity link addition strategy to improve the resilience of multiplex networks against attacks," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    3. Matthias Klumpp & Dominic Loske, 2021. "Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    4. Zarghami, Seyed Ashkan & Dumrak, Jantanee, 2021. "Unearthing vulnerability of supply provision in logistics networks to the black swan events: Applications of entropy theory and network analysis," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    5. Weiqiong Fu & Hanxiao Zhang & Fu Huang, 2022. "Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-18, January.
    6. Gaoke Wu & Bo Feng & Libin Guo, 2021. "Optimal Procurement Strategy for Supply Chain with Trade Credit and Backorder under CVaR Criterion," Sustainability, MDPI, vol. 13(18), pages 1-16, September.
    7. Lei Che & Jiangang Xu & Hong Chen & Dongqi Sun & Bao Wang & Yunuo Zheng & Xuedi Yang & Zhongren Peng, 2022. "Evaluation of the Spatial Effect of Network Resilience in the Yangtze River Delta: An Integrated Framework for Regional Collaboration and Governance under Disruption," Land, MDPI, vol. 11(8), pages 1-20, August.
    8. Mu, Dong & Ren, Huanyu & Wang, Chao & Yue, Xiongping & Du, Jianbang & Ghadimi, Pezhman, 2023. "Structural characteristics and disruption ripple effect in a meso-level electric vehicle Lithium-ion battery supply chain network," Resources Policy, Elsevier, vol. 80(C).
    9. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    10. Xiaojin Yuan & Chunbao Ge & Yapan Liu & Na Li & Ying Wang, 2022. "Evolution of Global Crude Oil Trade Network Structure and Resilience," Sustainability, MDPI, vol. 14(23), pages 1-21, December.
    11. Iftikhar, Anas & Purvis, Laura & Giannoccaro, Ilaria, 2021. "A meta-analytical review of antecedents and outcomes of firm resilience," Journal of Business Research, Elsevier, vol. 135(C), pages 408-425.
    12. Nishat Alam Choudhary & Shalabh Singh & Tobias Schoenherr & M. Ramkumar, 2023. "Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications," Annals of Operations Research, Springer, vol. 322(2), pages 565-607, March.
    13. Balan Sundarakani & Okey Peter Onyia, 2021. "Fast, furious and focused approach to Covid-19 response: an examination of the financial and business resilience of the UAE logistics industry," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 26(4), pages 237-258, December.
    14. Gaurav Kumar Badhotiya & Gunjan Soni & Vipul Jain & Rohit Joshi & Sameer Mittal, 2022. "Assessing supply chain resilience to the outbreak of COVID-19 in Indian manufacturing firms," Operations Management Research, Springer, vol. 15(3), pages 1161-1180, December.
    15. Sesini, Marzia & Giarola, Sara & Hawkes, Adam D., 2021. "Strategic natural gas storage coordination among EU member states in response to disruption in the trans Austria gas pipeline: A stochastic approach to solidarity," Energy, Elsevier, vol. 235(C).
    16. Taghizadeh, Elham & Venkatachalam, Saravanan & Chinnam, Ratna Babu, 2021. "Impact of deep-tier visibility on effective resilience assessment of supply networks," International Journal of Production Economics, Elsevier, vol. 241(C).
    17. Bag, Surajit & Rahman, Muhammad Sabbir & Srivastava, Gautam & Chan, Hau-Ling & Bryde, David J., 2022. "The role of big data and predictive analytics in developing a resilient supply chain network in the South African mining industry against extreme weather events," International Journal of Production Economics, Elsevier, vol. 251(C).
    18. Kayvan Miri Lavassani & Bahar Movahedi, 2021. "Firm-Level Analysis of Global Supply Chain Network: Role of Centrality on Firm’s Performance," International Journal of Global Business and Competitiveness, Springer, vol. 16(2), pages 86-103, December.
    19. Manupati, V.K. & Schoenherr, Tobias & Ramkumar, M. & Panigrahi, Suraj & Sharma, Yash & Mishra, Prakriti, 2022. "Recovery strategies for a disrupted supply chain network: Leveraging blockchain technology in pre- and post-disruption scenarios," International Journal of Production Economics, Elsevier, vol. 245(C).
    20. Wei Xu & Dong-Ping Song, 2022. "Integrated optimisation for production capacity, raw material ordering and production planning under time and quantity uncertainties based on two case studies," Operational Research, Springer, vol. 22(3), pages 2343-2371, July.
    21. Ali, Imran & Arslan, Ahmad & Tarba, Shlomo & Mainela, Tuija, 2023. "Supply chain resilience to climate change inflicted extreme events in agri-food industry: The role of social capital and network complexity," International Journal of Production Economics, Elsevier, vol. 264(C).
    22. Sharma, Amalesh & Pathak, Surya & Borah, Sourav Bikash & Adhikary, Anirban, 2022. "Collaboration strategies in buyer-supplier relational (BSR) networks and sustainable firm performance: A trade-off story," International Journal of Production Economics, Elsevier, vol. 253(C).

    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. Seyedmohsen Hosseini & Dmitry Ivanov, 2022. "A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach," Annals of Operations Research, Springer, vol. 319(1), pages 581-607, December.
    2. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    3. Ivanov, Dmitry & Dolgui, Alexandre, 2021. "OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications," International Journal of Production Economics, Elsevier, vol. 232(C).
    4. Alexander Pavlov & Dmitry Ivanov & Frank Werner & Alexandre Dolgui & Boris Sokolov, 2022. "Integrated detection of disruption scenarios, the ripple effect dispersal and recovery paths in supply chains," Annals of Operations Research, Springer, vol. 319(1), pages 609-631, December.
    5. Hosseini, Seyedmohsen & Morshedlou, Nazanin & Ivanov, Dmitry & Sarder, M.D. & Barker, Kash & Khaled, Abdullah Al, 2019. "Resilient supplier selection and optimal order allocation under disruption risks," International Journal of Production Economics, Elsevier, vol. 213(C), pages 124-137.
    6. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    7. Shashi & Piera Centobelli & Roberto Cerchione & Myriam Ertz, 2020. "Managing supply chain resilience to pursue business and environmental strategies," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1215-1246, March.
    8. Dmitry Ivanov & Boris Sokolov, 2019. "Simultaneous structural–operational control of supply chain dynamics and resilience," Annals of Operations Research, Springer, vol. 283(1), pages 1191-1210, December.
    9. K. Katsaliaki & P. Galetsi & S. Kumar, 2022. "Supply chain disruptions and resilience: a major review and future research agenda," Annals of Operations Research, Springer, vol. 319(1), pages 965-1002, December.
    10. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    11. João Pires Ribeiro & Ana Paula F. D. Barbosa-Póvoa, 2023. "A responsiveness metric for the design and planning of resilient supply chains," Annals of Operations Research, Springer, vol. 324(1), pages 1129-1181, May.
    12. Lohmer, Jacob & Bugert, Niels & Lasch, Rainer, 2020. "Analysis of resilience strategies and ripple effect in blockchain-coordinated supply chains: An agent-based simulation study," International Journal of Production Economics, Elsevier, vol. 228(C).
    13. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    14. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    15. Li, Yuhong & Zobel, Christopher W. & Seref, Onur & Chatfield, Dean, 2020. "Network characteristics and supply chain resilience under conditions of risk propagation," International Journal of Production Economics, Elsevier, vol. 223(C).
    16. Vijaya Dixit & Manoj Kumar Tiwari, 2020. "Project portfolio selection and scheduling optimization based on risk measure: a conditional value at risk approach," Annals of Operations Research, Springer, vol. 285(1), pages 9-33, February.
    17. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    18. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    19. Betto, Frida & Garengo, Patrizia, 2023. "A circular pathway for developing resilience in healthcare during pandemics," International Journal of Production Economics, Elsevier, vol. 266(C).
    20. Aghajani, Mojtaba & Ali Torabi, S. & Altay, Nezih, 2023. "Resilient relief supply planning using an integrated procurement-warehousing model under supply disruption," Omega, Elsevier, vol. 118(C).

    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:eee:proeco:v:227:y:2020:i:c:s0925527320300517. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.