1. Bandaly, D., Satir, A., Kahyaoglu, Y., & Shanker, L. (2012). Supply chain risk management I: Conceptualization, framework and planning process. Risk Management, 14(4), 249–271. https://doi.org/10.1057/rm.2012.7 2. Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. (2010). Discrete-Event System Simulation. 3. Battarra, M., Balcik, B., & Xu, H. (2018). Disaster preparedness using risk-assessment methods from earthquake engineering. European Journal of Operational Research, 269(2), 423–435. https://doi.org/10.1016/j.ejor.2018.02.014 4. Beamon, B. M. (1998). Supply chain design and analysis: Models and methods. International Journal of Production Economics, 55(3), 281–294. https://doi.org/10.1016/S0925-5273(98)00079-6 5. Bekker, J., & Guittet-Remaud, S. (2012). Simulation in Supply Chains: An Arena basis. The South African Journal of Industrial Engineering, 11(2). https://doi.org/10.7166/11-2-360 6. Ben-Haim, Y. (2012). Doing Our Best: Optimization and the Management of Risk. Risk Analysis, 32(8), 1326–1332. https://doi.org/10.1111/j.1539-6924.2012.01818.x 7. Bolstorff, P., & Rosenbaum, R. (2003). Supply chain excellence : a handbook for dramatic improvement using the SCOR model. Undefined. 8. Borshchev, A. (2014). Multi-method modelling: AnyLogic. In Discrete-Event Simulation and System Dynamics for Management Decision Making (Vol. 9781118349, Issue January). https://doi.org/10.1002/9781118762745.ch12 9. Bühler, A., Wallenburg, C. M., & Wieland, A. (2016). Accounting for external turbulence of logistics organizations via performance measurement systems. Supply Chain Management, 21(6), 694–708. https://doi.org/10.1108/SCM-02-2016-0040 10. Büyüközkan, G., & Göçer, F. (2018). Computers in Industry Digital Supply Chain : Literature review and a proposed framework for future research. 97, 157–177. 11. Carvalho, H., Barroso, A. P., Machado, V. H., Azevedo, S., & Cruz-machado, V. (2012). Computers & Industrial Engineering Supply chain redesign for resilience using simulation q. Computers & Industrial Engineering, 62(1), 329–341. https://doi.org/10.1016/j.cie.2011.10.003 12. Cavinato, J. L. (2004). Supply chain logistics risks: From the backroom to the board room. International Journal of Physical Distribution & Logistics Management, 34(5), 383–387. https://doi.org/10.1108/09600030410545427 13. Chattopadhyay, P., Glick, W. H., & Huber, G. P. (2001). Organizational actions in response to threats and opportunities. Academy of Management Journal, 44(5), 937–955. 14. Chellanthara, A. (2013). Evaluating car-sharing fleet management strategies using Discrete Event Simulation. 15. Choi, T. M., Wen, X., Sun, X., & Chung, S. H. (2019). The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era. Transportation Research Part E: Logistics and Transportation Review, 127(March), 178–191. https://doi.org/10.1016/j.tre.2019.05.007 16. Chopra, S., Sodhi. M. S. (2004). Supply-Chain Breakdown. 17. Chopra, S., & Sodhi, M. S. (2014). Reducing the Risk of Supply Chain Disruptions. 18. Christopher, M., & Lee, H. (2004). Mitigating supply chain risk through improved confidence. International Journal of Physical Distribution and Logistics Management, 34(5), 388–396. https://doi.org/10.1108/09600030410545436 19. Christopher, M., & Peck, H. (2004). International Journal of Logistics Management, Vol. 15, No. 2, pp1-13, 2004. 15(2), 1–13. 20. Cimino, A., Longo, F., & Mirabelli, G. (2010). A General Simulation Framework for Supply Chain Modeling: State of the Art and Case Study. 7(2). http://arxiv.org/abs/1004.3271 21. Cochran, L. (1997). Career counselling: A narrative approach. Sage publications. 22. Cohen, M. A., & Kunreuther, H. (2009). Operations Risk Management: Overview of Paul Kleindorfer’s Contributions. Production and Operations Management, 16(5), 525–541. https://doi.org/10.1111/j.1937-5956.2007.tb00278.x 23. CTV News. (2020). Paper towel shortage? Major Canadian manufacturer warns inventory “very tight.” CTV News. https://www.ctvnews.ca/health/coronavirus/is-a-paper-towel-shortage-nigh-major-canadian-manufacturer-warns-inventory-very-tight-1.5113891 24. Dehkhoda, K. (2016). Developing a framework on supply chain risk mapping, prioritization and engagement. 25. Dolgui, A., Ivanov, D., & Rozhkov, M. (2020). Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain†. International Journal of Production Research, 58(5), 1285–1301. https://doi.org/10.1080/00207543.2019.1627438 26. Drath, R., & Horch, A. (2014). Industrie 4.0: Hit or Hype? [Industry Forum]. June, 56–58. 27. Ebrahimi, D. S., David, P., & Alpan, G. (2012). A model-based specification for a decision support tool for supply chain risk management. Proceedings of International Conference on Computers and Industrial Engineering, CIE, 1(July), 251–265. 28. Ellram, L. M., & Cooper, M. C. (2014). Supply chain management: It’s all about the journey, not the destination. Journal of Supply Chain Management, 50(1), 8–20. https://doi.org/10.1111/jscm.12043 29. Fahimnia, B., Jabbarzadeh, A., & Sarkis, J. (2018). Greening versus resilience: A supply chain design perspective. Transportation Research Part E: Logistics and Transportation Review, 119(August 2017), 129–148. https://doi.org/10.1016/j.tre.2018.09.005 30. Fan, Y., & Stevenson, M. (2018). A review of supply chain risk management: definition, theory, and research agenda. International Journal of Physical Distribution and Logistics Management, 48(3), 205–230. https://doi.org/10.1108/IJPDLM-01-2017-0043 31. Fragapane, G., Ivanov, D., Peron, M., Sgarbossa, F., & Strandhagen, J. O. (2020). Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics. Annals of Operations Research. https://doi.org/10.1007/s10479-020-03526-7 32. Gao, S. Y., Simchi-Levi, D., Teo, C. P., & Yan, Z. (2019). Disruption risk mitigation in supply chains: The risk exposure index revisited. Operations Research, 67(3), 831–852. https://doi.org/10.1287/opre.2018.1776 33. Gaudenzi, B., & Borghesi, A. (2006). Managing risks in the supply chain using the AHP method. The International Journal of Logistics Management, 17(1), 114–136. https://doi.org/10.1108/09574090610663464 34. Ghadge, A., Er Kara, M., Moradlou, H., & Goswami, M. (2020). The impact of Industry 4.0 implementation on supply chains. Journal of Manufacturing Technology Management, 31(4), 669–686. https://doi.org/10.1108/JMTM-10-2019-0368 35. Golan, M. S., Jernegan, L. H., & Linkov, I. (2020). Trends and applications of resilience analytics in supply chain modelling: systematic literature review in the context of the COVID-19 pandemic. Environment Systems and Decisions, 40(2), 222–243. https://doi.org/10.1007/s10669-020-09777-w 36. Govindan, K., Fattahi, M., & Keyvanshokooh, E. (2017). Supply chain network design under uncertainty: A comprehensive review and future research directions. European Journal of Operational Research, 263(1), 108–141. https://doi.org/10.1016/j.ejor.2017.04.009 37. Guan, D., Wang, D., Hallegatte, S., Davis, S. J., Huo, J., Li, S., Bai, Y., Lei, T., Xue, Q., Coffman, D. M., Cheng, D., Chen, P., Liang, X., Xu, B., Lu, X., Wang, S., Hubacek, K., & Gong, P. (2020). Global supply-chain effects of COVID-19 control measures. Nature Human Behaviour, 4(6), 577–587. https://doi.org/10.1038/s41562-020-0896-8 38. Gümüş, M., Ray, S., & Gurnani, H. (2012). Supply-side story: Risks, guarantees, competition, and information asymmetry. Management Science, 58(9), 1694–1714. https://doi.org/10.1287/mnsc.1110.1511 39. Haimes, Y. Y., Kaplan, S., & Lambert, J. H. (2002). Risk Filtering, Ranking, and Management Framework Using Hierarchical Holographic Modeling. Risk Analysis, 22(2), 383–397. https://doi.org/10.1111/0272-4332.00020 40. Hanus, M. (2015). Customer order cycle of a production company, its bottlenecks and potential for improvements. July. 41. Harland, C., Brenchley, R., & Walker, H. (2003). Risk in supply networks. Journal of Purchasing and Supply Management, 9(2), 51–62. https://doi.org/10.1016/S1478-4092(03)00004-9 42. Harvard Business Review. (2020). Coronavirus + business. Harvard Business Review. 43. Heath, S. K., Brailsford, S. C., Buss, A., & Macal, C. M. (2011). Cross-paradigm simulation modelling: Challenges and successes. Proceedings - Winter Simulation Conference, 2783–2797. https://doi.org/10.1109/WSC.2011.6147983 44. Ho, W., Zheng, T., Yildiz, H., & Talluri, S. (2015). Supply chain risk management: A literature review. International Journal of Production Research, 53(16), 5031–5069. https://doi.org/10.1080/00207543.2015.1030467 45. Hobbs, J. E. (2020). Food supply chains during the COVID-19 pandemic. Canadian Journal of Agricultural Economics, 68(2), 171–176. https://doi.org/10.1111/cjag.12237 46. Hopp, W. J., Spearman, M. L., & Zhang, R. Q. (1997). Easily implementable inventory control policies. Operations Research, 45(3), 327–340. https://doi.org/10.1287/opre.45.3.327 47. Hunt, D. v. (1996). Process Mapping: How to Reengineer your Business Processes. undefined-undefined. https://www.mendeley.com/catalogue/8340d439-0327-3bd7-ad65-e8d28f6db84d/?utm_source=desktop&utm_medium=1.19.8&utm_campaign=open_catalog&userDocumentId=%7Bb46d99ec-8d83-38ec-9df1-96a6c8bde5f2%7D 48. Ivanov, D. (2017). Simulation-based ripple effect modelling in the supply chain. International Journal of Production Research, 7543, 0. https://doi.org/10.1080/00207543.2016.1275873 49. Ivanov, D. (2018). Revealing interfaces of supply chain resilience and sustainability: a simulation study. International Journal of Production Research, 56(10), 3507–3523. https://doi.org/10.1080/00207543.2017.1343507 50. Ivanov, D. (2020a). 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, 136, 101922. 51. Ivanov, D. (2020b). Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic. Annals of Operations Research. https://doi.org/10.1007/s10479-020-03640-6 52. Ivanov, D., & Das, A. (2020). Coronavirus (COVID-19/SARS-CoV-2) and supply chain resilience: a research note. International Journal of Integrated Supply Management, 13(1), 90. https://doi.org/10.1504/ijism.2020.107780 53. Ivanov, D., & Dolgui, A. (2020a). The Management of Operations A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4. 0. Production Planning & Control, 0(0), 1–14. https://doi.org/10.1080/09537287.2020.1768450 54. Ivanov, D., & Dolgui, A. (2020b). Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by the COVID-19 outbreak. International Journal of Production Research, 58(10), 1–12. https://doi.org/10.1080/00207543.2020.1750727 55. Ivanov, D., Dolgui, A., Das, A., & Sokolov, B. (2019). Handbook of Ripple Effects in the Supply Chain (Vol. 276). Springer International Publishing. https://doi.org/10.1007/978-3-030-14302-2 56. Ivanov, D., Dolgui, A., & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829–846. https://doi.org/10.1080/00207543.2018.1488086 57. Ivanov, D., Dolgui, A., Sokolov, B., & Ivanova, M. (2017). Literature review on disruption recovery in the supply chain*. International Journal of Production Research, 55(20), 6158–6174. https://doi.org/10.1080/00207543.2017.1330572 58. Jahangirian, M., Eldabi, T., Naseer, A., Stergioulas, L. K., & Young, T. (2010). Simulation in manufacturing and business: A review. European Journal of Operational Research, 203(1), 1–13. https://doi.org/10.1016/j.ejor.2009.06.004 59. Jbara, N. ben. (2018). Risk management in supply chains : a simulation and model-driven engineering approach. https://tel.archives-ouvertes.fr/tel-01730805 60. Jüttner, U., Peck, H., & Christopher, M. (2003). Supply chain risk management: outlining an agenda for future research. International Journal of Logistics Research and Applications, 6(4), 197–210. https://doi.org/10.1080/13675560310001627016 61. Karl, A. A., Micheluzzi, J., Leite, L. R., & Pereira, C. R. (2018). Supply chain resilience and key performance indicators: A systematic literature review. Producao, 28. https://doi.org/10.1590/0103-6513.20180020 62. Kelton, W. D. (2002). Simulation with ARENA. McGraw-hill. 63. Kenné, J. P., Dejax, P., & Gharbi, A. (2012). Production planning of a hybrid manufacturing system under uncertainty within a closed-loop supply chain. International Journal of Production Economics, 135(1), 81–93. https://doi.org/10.1016/j.ijpe.2010.10.026 64. Kinra, A., Ivanov, D., Das, A., & Dolgui, A. (2019). Ripple effect quantification by supplier risk exposure assessment. International Journal of Production Research, 0(0), 1–20. https://doi.org/10.1080/00207543.2019.1675919 65. Kleindorfer, P. R., & Saad, G. H. (2005). Managing disruption risks in supply chains. Production and Operations Management, 14(1), 53–68. https://doi.org/10.1111/j.1937-5956.2005.tb00009.x 66. Kliment, M., Popovič, R., & Janek, J. (2014). Analysis of the production process in the selected company and proposal a possible model optimization through PLM software module Tecnomatix Plant Simulation. Procedia Engineering, 96, 221–226. https://doi.org/10.1016/j.proeng.2014.12.147 67. Knemeyer, A. M., Zinn, W., & Eroglu, C. (2009). Proactive planning for catastrophic events in supply chains. Journal of Operations Management, 27(2), 141–153. https://doi.org/10.1016/j.jom.2008.06.002 68. Kr Sarmah, H., Sarmah, H. K., Bora Hazarika, B., & Choudhury, G. (2013). An investigation on the effect of bias on the determination of sample size on the basis of data related to the students of the school of Guwahati. In researchgate.net. https://www.researchgate.net/publication/303014899 69. Larue, B. (2020). Labour issues and COVID-19. Canadian Journal of Agricultural Economics, 68(2), 231–237. https://doi.org/10.1111/cjag.12233 70. Lavastre, O., Gunasekaran, A., & Spalanzani, A. (2012). Supply chain risk management in French companies. Decision Support Systems, 52(4), 828–838. https://doi.org/10.1016/j.dss.2011.11.017 71. Law, A. M., Kelton, W. D., & Kelton, W. D. (2000). Simulation modelling and analysis (Vol. 3). McGraw-Hill New York. 72. Liao, Y., Deschamps, F., Loures, E. de F. R., & Ramos, L. F. P. (2017). Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal. International Journal of Production Research, 55(12), 3609–3629. https://doi.org/10.1080/00207543.2017.1308576 73. Long, Q. (2014). Distributed supply chain network modelling and simulation: Integration of agent-based distributed simulation and improved SCOR model. International Journal of Production Research, 52(23), 6899–6917. https://doi.org/10.1080/00207543.2014.910623 74. Luxxeen Production. (2021). http://luxxeen.com/ 75. Manuj, I., & Mentzer, J. T. (2008). Global supply chain risk management strategies. International Journal of Physical Distribution and Logistics Management, 38(3), 192–223. https://doi.org/10.1108/09600030810866986 76. Marhavilas, P. K., Koulouriotis, D., & Gemeni, V. (2011). Risk analysis and assessment methodologies in the work sites: On a review, classification and comparative study of the scientific literature of the period 2000-2009. In Journal of Loss Prevention in the Process Industries (Vol. 24, Issue 5, pp. 477–523). Elsevier. https://doi.org/10.1016/j.jlp.2011.03.004 77. Marmolejo, J. A., & Hurtado, M. (2020). Digital Twins in Supply Chain Management : A Brief Literature Review. January. https://doi.org/10.1007/978-3-030-33585-4 78. Millet, P. A., Schmitt, P., & Botta-Genoulaz, V. (2009). The SCOR model for the alignment of business processes and information systems. Enterprise Information Systems, 3(4), 393–407. https://doi.org/10.1080/17517570903030833 79. Mishra, D., Sharma, R. R. K., Kumar, S., & Dubey, R. (2016). Bridging and buffering: Strategies for mitigating supply risk and improving supply chain performance. International Journal of Production Economics, 180, 183–197. https://doi.org/10.1016/j.ijpe.2016.08.005 80. Mollenkopf, D. A., Ozanne, L. K., & Stolze, H. J. (2020). A transformative supply chain response to COVID-19. Journal of Service Management. https://doi.org/10.1108/JOSM-05-2020-0143 81. Mrabet, W. el. (2012). Analysis of Supply Chain Models in a System of Systems Context. 82. Naing, N. N. (2003). Determination of sample size. Malaysian Journal of Medical Sciences, 10(2), 84–86. 83. Namdar, J., Li, X., Sawhney, R., & Pradhan, N. (2018). Supply chain resilience for single and multiple sourcing in the presence of disruption risks. International Journal of Production Research, 56(6), 2339–2360. https://doi.org/10.1080/00207543.2017.1370149 84. Norrman, A., & Jansson, U. (2004). Ericsson’s proactive supply chain risk management approach after a serious sub-supplier accident. International Journal of Physical Distribution and Logistics Management, 34(5), 434–456. https://doi.org/10.1108/09600030410545463 85. Oehmen, J., Ziegenbein, A., Alard, R., & Schönsleben, P. (2009). System-oriented supply chain risk management. Production Planning & Control, 20(4), 343–361. https://doi.org/10.1080/09537280902843789 86. Oliver, R. K., & Webber, M. D. (1982). Supply-chain management: logistics catches up with a strategy. Outlook, 5(1), 42–47. 87. Palma-Mendoza, J. A. (2014). Analytical hierarchy process and SCOR model to support supply chain re-design. International Journal of Information Management, 34(5), 634–638. https://doi.org/10.1016/j.ijinfomgt.2014.06.002 88. Paul, S. K., & Chowdhury, P. (2020a). A production recovery plan in manufacturing supply chains for a high-demand item during COVID-19. International Journal of Physical Distribution and Logistics Management. https://doi.org/10.1108/IJPDLM-04-2020-0127 89. Paul, S. K., & Chowdhury, P. (2020b). Strategies for Managing the Impacts of Disruptions During COVID-19: an Example of Toilet Paper. Global Journal of Flexible Systems Management, 21(3), 283–293. https://doi.org/10.1007/s40171-020-00248-4 90. Pettit, T. J., Croxton, K. L., & Fiksel, J. (2013). Ensuring supply chain resilience: Development and implementation of an assessment tool. Journal of Business Logistics, 34(1), 46–76. https://doi.org/10.1111/jbl.12009 91. Poluha, R. (2007). Application of the SCOR Model in Supply Chain Management. Cambria Press. 92. Popovic, V. M., Vasic, B. M., Rakicevic, B. B., & Vorotovic, G. S. (2012). Optimization of maintenance concept choice using risk-decision factor – a case study. International Journal of Systems Science, 43(10), 1913–1926. https://doi.org/10.1080/00207721.2011.563868 93. Quick reference guide. (1999). Nursing Standard, 13(42), 29–29. https://doi.org/10.7748/ns.13.42.29.s50 94. Rizou, M., Galanakis, I. M., Aldawoud, T. M. S., & Galanakis, C. M. (2020). Safety of foods, food supply chain and environment within the COVID-19 pandemic. Trends in Food Science and Technology, 102(June), 293–299. https://doi.org/10.1016/j.tifs.2020.06.008 95. Rogers, R. L., Broeckmann, B., & Maddison, N. (2000). Risk assessment standard for equipment for use in potentially explosive atmospheres: The RASE project. Institution of Chemical Engineers Symposium Series, 147, 337–350. 96. Sachdeva, A., Sharma, V., Arvind Bhardwaj, D., Kayis, B., & Dana Karningsih, P. (2012). SCRIS: A knowledge-based system tool for assisting manufacturing organizations in identifying supply chain risks. Journal of Manufacturing Technology Management, 23(7), 834–852. https://doi.org/10.1108/17410381211267682 97. Salman, F. S., & Yücel, E. (2015). Emergency facility location under random network damage: Insights from the Istanbul case. Computers and Operations Research, 62, 266–281. https://doi.org/10.1016/j.cor.2014.07.015 98. SCC, S. C. C. (2010). Supply chain operations reference model SCOR version 10.0. The Supply Chain Council, Inc. SCOR: The Supply Chain Reference ISBN 0-615-20259-4 (Binder). 99. Schmidt, J. W., & Taylor, R. E. (1970). Simulation and analysis of industrial systems. RD Irwin. 100. Schoenherr, T., Rao Tummala, V. M., & Harrison, T. P. (2008). Assessing supply chain risks with the analytic hierarchy process: Providing decision support for the offshoring decision by a US manufacturing company. Journal of Purchasing and Supply Management, 14(2), 100–111. https://doi.org/10.1016/j.pursup.2008.01.008 101. Spekman, R. E., & Davis, E. W. (2004). Risky business: Expanding the discussion on risk and the extended enterprise. International Journal of Physical Distribution and Logistics Management, 34(5), 414–433. https://doi.org/10.1108/09600030410545454 102. Spiegler, V. L. M., Naim, M. M., & Wikner, J. (2012). A control engineering approach to the assessment of supply chain resilience. International Journal of Production Research, 50(21), 6162–6187. https://doi.org/10.1080/00207543.2012.710764 103. Srai, J. S., Settanni, E., Tsolakis, N., & Aulakh, P. K. (2019). Supply Chain Digital Twins : Opportunities and Challenges Beyond the Hype. September 2019, 26–27. 104. Strozzi, F., Colicchia, C., Creazza, A., & Noè, C. (2017). Literature review on the ‘smart factory’ concept using bibliometric tools. International Journal of Production Research, 55(22), 1–20. https://doi.org/10.1080/00207543.2017.1326643 105. Tang, C. S., & Veelenturf, L. P. (2019). The strategic role of logistics in the industry 4.0 era. Transportation Research Part E: Logistics and Transportation Review, 129(July), 1–11. https://doi.org/10.1016/j.tre.2019.06.004 106. Thilakarathna, R. H., Dharmawardana, M. N., & Rupasinghe, T. (2015). The Supply Chain Operations Reference (SCOR) Model: A Systematic Review of Literature from the Apparel Industry. SSRN Electronic Journal, January. https://doi.org/10.2139/ssrn.2699886 107. Thomas Willemain, Ph. D. (2019). Top 3 Most Common Inventory Control Policies. https://smartcorp.com/b-policy/inventory-control-policies-software/ 108. Trkman, P., & McCormack, K. (2009). Supply chain risk in a turbulent environments-A conceptual model for managing supply chain network risk. International Journal of Production Economics, 119(2), 247–258. https://doi.org/10.1016/j.ijpe.2009.03.002 109. Tsai, M. C., Liao, C. H., & Han, C. S. (2008). Risk perception on logistics outsourcing of retail chains: Model development and empirical verification in Taiwan. Supply Chain Management, 13(6), 415–424. https://doi.org/10.1108/13598540810905679 110. Tuncel, G. (2010). Computers in Industry Risk assessment and management for supply chain networks : A case study. 61, 250–259. https://doi.org/10.1016/j.compind.2009.09.008 111. Uhlemann, T. H. J., Schock, C., Lehmann, C., Freiberger, S., & Steinhilper, R. (2017). The Digital Twin: Demonstrating the Potential of Real-Time Data Acquisition in Production Systems. Procedia Manufacturing, 9, 113–120. https://doi.org/10.1016/j.promfg.2017.04.043 112. Vaidya, S., Ambad, P., & Bhosle, S. (2018). Industry 4.0 - A Glimpse. Procedia Manufacturing, 20, 233–238. https://doi.org/10.1016/j.promfg.2018.02.034 113. Wagner, S. M., & Neshat, N. (2010). Assessing the vulnerability of supply chains using graph theory. International Journal of Production Economics, 126(1), 121–129. https://doi.org/10.1016/j.ijpe.2009.10.007 114. Windelberg, M. (2016). Objectives for managing cyber supply chain risk. International Journal of Critical Infrastructure Protection, 12, 4–11. https://doi.org/10.1016/j.ijcip.2015.11.003 115. Worldometers. (2021). COVID-19 Coronavirus Pandemic. https://www.worldometers.info/coronavirus/ 116. Wu, T., Blackhurst, J., & O’Grady, P. (2007). Methodology for supply chain disruption analysis. International Journal of Production Research, 45(7), 1665–1682. https://doi.org/10.1080/00207540500362138 117. Wu, Y. (2006). Robust optimization applied to uncertain production loading problems with import quota limits under the global supply chain management environment. International Journal of Production Research, 44(5), 849–882. https://doi.org/10.1080/00207540500285040 118. Xu, M., Wang, X., & Zhao, L. (2014). Predicted supply chain resilience based on structural evolution against random supply disruptions. 2674. https://doi.org/10.1080/23302674.2014.934748 119. Zsidisin, G. A., Ellram, L. M., Carter, J. R., & Cavinato, J. L. (2004). An analysis of supply risk assessment techniques. International Journal of Physical Distribution and Logistics Management, 34(5), 397–413. https://doi.org/10.1108/09600030410545445