Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak

References

• Agi. 2020. L'economia di guerra ci costa 100 miliardi al mese, dice Boccia. Accessed March 25, 2020. https://www.agi.it/economia/news/2020-03-23/coronavirus-boccia-costo-economia-di-guerra-7773008/.
   Google Scholar
• Altay, N., and W. G. Green. 2006. “OR/MS Research in Disaster Operations Management.” European Journal of Operational Research 175 (1): 475–493.
   Web of Science ®Google Scholar
• Anne, K. R., J. C. Chedjou, and K. Kyamakya. 2009. “Bifurcation Analysis and Synchronisation Issues in a Three-Echelon Supply Chain.” International Journal of Logistics Research and Applications 12 (5): 347–362.
   Web of Science ®Google Scholar
• Araz, O. M., T.-M. Choi, D. Olson, and F. S. Salman. 2020. “Data Analytics for Operational Risk Management.” Decision Sciences. Forthcoming
   Web of Science ®Google Scholar
• Aubin, J. P. 1991. Viability Theory. Boston: Birkhäuser.
   Google Scholar
• Basole, R. C., and M. A. Bellamy. 2014. “Supply Network Structure, Visibility, and Risk Diffusion: A Computational Approach.” Decision Sciences 45 (4): 1–49.
   Web of Science ®Google Scholar
• Baudrot, V., C. Fritsch, A. Perasso, M. Banerjee, and F. Raoul. 2018. “Effects of Contaminants and Trophic Cascade Regulation on Food Chain Stability: Application to Cadmium Soil Pollution on Small Mammals – Raptor Systems.” Ecological Modelling 382: 33–42.
   Web of Science ®Google Scholar
• Beer, S. 1981. Brain of the Firm. Chichester: Wiley.
   Google Scholar
• Bene, C., L. Doyen, and D. Gabay. 2001. “A Viability Analysis for a Bio-Economic Model.” Ecological Economics 36: 385–396.
   Web of Science ®Google Scholar
• Bier, T., A. Lange, and C. Glock. 2019. “Methods for Mitigating Disruptions in Complex Supply Chain Structures: A Systematic Literature Review.” International Journal of Production Research. doi:10.1080/00207543.2019.1687954.
   PubMed Web of Science ®Google Scholar
• Blackhurst, J., C. W. Craighead, D. Elkins, and R. Handfield. 2005. “An Empirically Derived Agenda of Critical Research Issues for Managing Supply-Chain Disruptions.” International Journal of Production Research 43 (19): 4067–4081.
   Web of Science ®Google Scholar
• Bode, C., and S. M. Wagner. 2015. “Structural Drivers of Upstream Supply Chain Complexity and the Frequency of Supply Chain Disruptions.” Journal of Operations Management 36: 215–228.
   Web of Science ®Google Scholar
• Bonneuil, N., and P. Saint-Pierre. 2005. “Population Viability in Three Trophic-Level Food Chains.” Applied Mathematics and Computation 169: 1086–1105.
   Web of Science ®Google Scholar
• Brintrup, A., Y. Wang, and A. Tiwari. 2015. “Supply Networks as Complex Systems: A Network Science-Based Characterization.” IEEE Systems Journal 99:1–12.
   Google Scholar
• Byrne, G., D. Dimitrov, L. Monostori, R. Teti, F. van Houten, and R. Wertheim. 2018. “Biologicalisation: Biological Transformation in Manufacturing.” CIRP Journal of Manufacturing Science and Technology 21: 1–32.
   Web of Science ®Google Scholar
• Camarinha-Matos, L. M., and H. Afsarmanesh. 2005. “Collaborative Networks: a new Scientific Discipline.” Journal of Intelligent Manufacturing 16: 439–452.
   Web of Science ®Google Scholar
• Castellanos, V., and R. E. Chan-López. 2017. “Existence of Limit Cycles in a Three Level Trophic Chain with Lotka–Volterra and Holling Type II Functional Responses.” Chaos, Solitons and Fractals 95: 157–167.
   Web of Science ®Google Scholar
• Chen, X., Z. Xi, and P. Jing. 2017. “A Unified Framework for Evaluating Supply Chain Reliability and Resilience.” IEEE Transactions on Reliability 66 (4): 1144–1156.
   Web of Science ®Google Scholar
• Chibani, A., X. Delorme, A. Dolgui, and H. Pierreval. 2018. “Dynamic Optimisation for Highly Agile Supply Chains in e-Procurement Context.” International Journal of Production Research 56 (17): 5904–5929.
   Web of Science ®Google Scholar
• Choi, T. Y., K. J. Dooley, and M. Rungtusanatham. 2001. “Supply Networks and Complex Adaptive Systems: Control Versus Emergence.” J Oper Manag 19 (3): 351–366.
   Web of Science ®Google Scholar
• Choi, T.-M., A. A. Taleizadeh, and X. Yue. 2020. “Game Theory Applications in Production Research in the Sharing and Circular Economy era.” International Journal of Production Research 58 (1): 118–127.
   Web of Science ®Google Scholar
• Craighead, C. W., J. Blackhurst, M. J. Rungtusanatham, and R. B. Handfield. 2007. “The Severity of Supply Chain Disruptions: Design Characteristics and Mitigation Capabilities.” Decision Sciences 38 (1): 131–156.
   Web of Science ®Google Scholar
• Dekkers, R. 2009. “Distributed Manufacturing as Co-Evolutionary System.” International Journal of Production Research 47 (8): 2031–2054.
   Web of Science ®Google Scholar
• Demirel, G., B. L. MacCarthy, D. Ritterskamp, A. Champneys, and T. Gross. 2019. “Identifying Dynamical Instabilities in Supply Networks Using Generalized Modeling.” Journal of Operations Management 65 (2): 136–159.
   Web of Science ®Google Scholar
• Dilao, R., and T. Domingos. 2000. “A General Approach to the Modelling of Trophic Chains.” Ecological Modelling 132: 191–202.
   Web of Science ®Google Scholar
• Dolgui, A., D. Ivanov, and M. Rozhkov. 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.
   Web of Science ®Google Scholar
• Dolgui, A., D. Ivanov, and B. Sokolov. 2018. “Ripple Effect in the Supply Chain: An Analysis and Recent Literature.” International Journal of Production Research 56 (1–2): 414–430.
   Web of Science ®Google Scholar
• Dolgui, A., and J.-M. Proth. 2010. Supply Chain Engineering: Useful Methods and Techniques. Berlin: Springer.
   Google Scholar
• Dong, M. C., Z. Liu, Y. Yu, and J.-H. Zheng. 2015. “Opportunism in Distribution Networks: The Role of Network Embeddedness and Dependence.” Production and Operations Management 24 (10): 1657–1670.
   Web of Science ®Google Scholar
• Dubey, R., and N. Altay. 2018. “Drivers of Coordination in Humanitarian Relief Supply Chains.” In The Palgrave Handbook of Humanitarian Logistics and Supply Chain Management, edited by G. Kovács, K. Spens, and M. Moshtari, 297–325. London: Palgrave Macmillan.
   Google Scholar
• Dubey, R., A. Gunasekaran, S. J. Childe, S. F. Wamba, D. Roubaud, and C. Foropon. 2019a. “Empirical Investigation of Data Analytics Capability and Organizational Flexibility as Complements to Supply Chain Resilience.” International Journal of Production Research. doi:10.1080/00207543.2019.1582820.
   PubMed Web of Science ®Google Scholar
• Dubey, R., A. Gunasekaran, and T. Papadopoulos. 2019b. “Disaster Relief Operations: Past, Present and Future.” Annals of Operations Research 283 (1-2): 1–8.
   Web of Science ®Google Scholar
• DuHadway, S., S. Carnovale, and B. Hazen. 2019. “Understanding Risk Management for Intentional Supply Chain Disruptions: Risk Detection, Risk Mitigation, and Risk Recovery.” Annals of Operations Research 283 (1–2): 179–198.
   Web of Science ®Google Scholar
• Fortune. 2020. Accessed March 10, 2020. https://fortune.com/2020/02/21/fortune-1000-coronavirus-china-supply-chain-impact/.
   Google Scholar
• Fraccascia, L., I. Giannoccaro, and V. Albino. 2017. “Rethinking Resilience in Industrial Symbiosis: Conceptualization and Measurements.” Ecological Economics 137: 148–162.
   Web of Science ®Google Scholar
• Getz, W. M., H. V. Westerhoff, J. H. S. Hofmeyr, and J. L. Snoep. 2003. “Control Analysis of Trophic Chains.” Ecological Modelling 168: 153–171.
   Web of Science ®Google Scholar
• Giannoccaro, I., A. Nair, and T. Choi. 2017. “The Impact of Control and Complexity on Supply Network Performance: An Empirically Informed Investigation Using NK Simulation Analysis.” Decision Science 49 (4): 625–659.
   Web of Science ®Google Scholar
• Gross, T., W. Ebenhöh, and U. Feudel. 2004. “Enrichment and Foodchain Stability: the Impact of Different Forms of Predator–Prey Interaction.” Journal of Theoretical Biology 227 (3): 349–358.
   PubMed Web of Science ®Google Scholar
• Gross, T., B. MacCarthy, and N. Wildgoose. 2018. “Introduction to Dynamics of Manufacturing Supply Networks.” Chaos 28 (9): 093111.
   PubMed Web of Science ®Google Scholar
• Gross, T., L. Rudolf, S. A. Levin, and U. Dieckmann. 2009. “Generalized Models Reveal Stabilizing Factors in Food Webs.” Science 325 (5941): 747–750.
   PubMed Web of Science ®Google Scholar
• Gupta, V., and D. Ivanov. 2020. “Dual Sourcing Under Supply Disruption with Risk-Averse Suppliers in the Sharing Economy.” International Journal of Production Research 58 (1): 291–307.
   Web of Science ®Google Scholar
• Harbour, L. 2020. “ The Coronavirus Impact on the Global Automotive Supply Chains.” Accessed March 24, 2020. https://www.forbes.com/sites/laurieharbour1/2020/03/13/the-coronavirus-impact-on-the-global-automotive-supply-chain/185153c8444e.
   Google Scholar
• Ho, W., T. Zheng, H. Yildiz, and S. Talluri. 2015. “Supply Chain Risk Management: a Literature Review.” International Journal of Production Research 53 (16): 5031–5069.
   Web of Science ®Google Scholar
• Holling, C. S. 1996. “Engineering Resilience Versus Ecological Resilience.” In Engineering Within Ecological Constraints, edited by P. C. Schulze. Washington, DC: National Academy Press.
   Google Scholar
• Hosseini, S., D. Ivanov, and A. Dolgui. 2019. “Review of Quantitative Methods for Supply Chain Resilience Analysis.” Transportation Research: Part E 125: 285–307.
   Google Scholar
• Ivanov, D. 2018. Structural Dynamics and Resilience in Supply Chain Risk Management. New York: Springer.
   Google Scholar
• Ivanov, D. 2019. “Disruption Tails and Revival Policies: A Simulation Analysis of Supply Chain Design and Production-Ordering Systems in the Recovery and Post-Disruption Periods.” Computers and Industrial Engineering 127: 558–570.
   Web of Science ®Google Scholar
• Ivanov, D. 2020. “Predicting the Impact of Epidemic Outbreaks on the Global Supply Chains: A Simulation-Based Analysis on the Example of Coronavirus (COVID-19 / SARS-CoV-2) Case.” Transportation Research – Part E 136: 101922. doi:10.1016/j.tre.2020.101922.
   Google Scholar
• Ivanov, D., A. Arkhipov, and B. Sokolov. 2004. “Intelligent Supply Chain Planning in Virtual Enterprises.” In Virtual Enterprises and Collaborative Networks, Proceedings of the IFIP Conference on Virtual Enterprises PRO-VE 2004, edited by L. Camarihna-Matos, 215–223. Berlin: Kluwer Academic Publishers.
   Google Scholar
• Ivanov, D., and A. Dolgui. 2019. “Low-Certainty-Need (LCN) Supply Chains: A new Perspective in Managing Disruption Risks and Resilience.” International Journal of Production Research 57 (15-16): 5119–5136.
   Web of Science ®Google Scholar
• Ivanov, D., and A. Dolgui. 2020. “ A Digital Supply Chain Twin for Managing the Disruptions Risks and Resilience in the Era of Industry 4.0.” Production Planning and Control, forthcoming.
   Google Scholar
• 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.
   Web of Science ®Google Scholar
• Ivanov, D., A. Dolgui, B. Sokolov, and M. Ivanova. 2017. “Literature Review on Disruption Recovery in the Supply Chain.” International Journal of Production Research 55 (20): 6158–6174.
   Web of Science ®Google Scholar
• Ivanov, D., J. Kaeschel, and B. Sokolov. 2009. “Structure Dynamics Control-Based Framework for Adaptive Reconfiguration of Collaborative Enterprise Networks.” International Journal of Manufacturing Technology and Management 17 (1-2): 23–41.
   Google Scholar
• Ivanov, D., J. Käschel, A. Arkhipov, B. Sokolov, and L. Zschorn. 2005. “Quantitative Models of Collaborative Networks.” In Collaborative Networks and Their Breeding Environments, Proceedings of the IFIP Conference on Virtual Enterprises PRO-VE 2005, edited by L. Camarihna-Matos and A. Ortiz Afsarmanesh, 387–394. Berlin: Springer.
   Google Scholar
• Ivanov, D., and B. Sokolov. 2012. “The Inter-Disciplinary Modelling of Supply Chains in the Context of Collaborative Multi-Structural Cyber-Physical Networks.” Journal of Manufacturing Technology Management 23 (8): 976–997.
   Google Scholar
• Ivanov, D., and B. Sokolov. 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 224 (2): 313–323.
   Web of Science ®Google Scholar
• Ivanov, D., B. Sokolov, and A. Dolgui. 2014a. “The Ripple Effect in Supply Chains: Trade-off ‘Efficiency-Flexibility-Resilience’ in Disruption Management.” International Journal of Production Research 52 (7): 2154–2172.
   Web of Science ®Google Scholar
• Ivanov, D., B. Sokolov, and J. Kaeschel. 2010. “A Multi-Structural Framework for Adaptive Supply Chain Planning and Operations with Structure Dynamics Considerations.” European Journal of Operational Research 200: 409–420.
   Web of Science ®Google Scholar
• Ivanov, D., B. Sokolov, and A. Pavlov. 2014b. “Optimal Distribution (re)Planning in a Centralized Multi-Stage Network Under Conditions of Ripple Effect and Structure Dynamics.” European Journal of Operational Research 237 (2): 758–770.
   Web of Science ®Google Scholar
• Kelly, K., and K. Marchese. 2015. Supply Chains and ISNs. Business Ecosystems Come of age. Deloitte University Press, pp. 55–65.
   Google Scholar
• Keogh, J. G. 2020. “ COVID-19. To Ensure the Supply of Food and Consumer Goods, We Must Change the Rules of the Game.” Accessed March 20, 2020. www.foodincanada.com.
   Google Scholar
• Kim, Y., Y. Chen, and K. Linderman. 2015. “Supply Network Distribution and Resilience: A Network Structural Perspective.” Journal of Operations Management 33: 43–59.
   Web of Science ®Google Scholar
• Li, Y., C. W. Zobel, O. Seref, and D. C. Chatfield. 2019. “Network Characteristics and Supply Chain Resilience Under Conditions of Risk Propagation.” International Journal of Production Economics. doi:10.1016/j.ijpe.2019.107529.
   Web of Science ®Google Scholar
• Liao, Y., Y. Deschamps, E. de Freitas, R. Loures, and L. F. P. Ramos. 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.
   Web of Science ®Google Scholar
• Linkov, I., and A. Kott. 2019. “Fundamental Concepts of Cyber Resilience: Introduction and Overview.” In Cyber Resilience of Systems and Networks, edited by A. Kott and I. Linkov, 1–25. Cham: Springer.
   Google Scholar
• Linton, T., and B. Vakil. 2020. Coronavirus Is Proving We Need More Resilient Supply Chains. Harward Business Review, March 5, 2020. Accessed March 10, 2020. https://hbr.
   Google Scholar
• Macdonald, J. R., C. W. Zobel, S. A. Melnyk, and S. E. Griffis. 2018. “Supply Chain Risk and Resilience: Theory Building Through Structured Experiments and Simulation.” International Journal of Production Research 56 (12): 4337–4355.
   Web of Science ®Google Scholar
• Mondal, S. 2019. “A new Supply Chain Model and its Synchronization Behavior.” Chaos, Solitons and Fractals 123: 140–148.
   Web of Science ®Google Scholar
• Nair, A., and F. Reed-Tsochas. 2019. “Revisiting the Complex Adaptive Systems Paradigm: Leading Perspectives for Researching Operations and Supply Chain Management Issues.” J Oper Man 65 (2): 80–92.
   Web of Science ®Google Scholar
• Nair, A., and J. M. Vidal. 2011. “Supply Network Topology and Robustness Against Disruptions – An Investigation Using a Multi-Agent Model.” International Journal of Production Research 49 (5): 1391–1404.
   Web of Science ®Google Scholar
• Niu, B., J. Li, J. Zhang, H. K. Cheng, and Y. Tan. 2019. “Strategic Analysis of Dual Sourcing and Dual Channel with an Unreliable Alternative Supplier.” Production and Operations Management 28 (3): 570–587.
   Web of Science ®Google Scholar
• Ojha, R., A. Ghadge, M. K. Tiwari, and U. S. Bititci. 2018. “Bayesian Network Modelling for Supply Chain Risk Propagation.” International Journal of Production Research 56 (17): 5795–5819.
   Web of Science ®Google Scholar
• Olson, D. L., D. Wu, Y. Shanlin, and J. H. Lambert. 2018. “Complex Product Manufacturing in the Intelligence-Connected era.” International Journal of Production Research 57 (21): 6702–6704.
   Web of Science ®Google Scholar
• Panetto, H., B. Iung, D. Ivanov, G. Weichhart, and X. Wang. 2019. “Challenges for the Cyber-Physical Manufacturing Enterprises of the Future.” Annual Reviews in Control 47: 200–213.
   Web of Science ®Google Scholar
• Pathak, S. D., H. Wu, and D. A. Johnston. 2014. “Toward a Structural View of Co-Opetition in Supply Networks.” Journal of Operations Management 32 (5): 254–226.
   Web of Science ®Google Scholar
• Pavlov, A., D. Ivanov, A. Dolgui, and B. Sokolov. 2018. “Hybrid Fuzzy-Probabilistic Approach to Supply Chain Resilience Assessment.” IEEE Transactions on Engineering Management 65 (2): 303–315.
   Web of Science ®Google Scholar
• Pavlov, A., D. Ivanov, F. Werner, A. Dolgui, and B. Sokolov. 2019a. “Integrated Detection of Disruption Scenarios, the Ripple Effect Dispersal and Recovery Paths in Supply Chains.” Annals of Operations Research. doi:10.1007/s10479-019-03454-1.
   Web of Science ®Google Scholar
• Pavlov, A., D. Ivanov, F. Werner, A. Dolgui, and B. Sokolov. 2019b. “Optimization of Network Redundancy and Contingency Planning in Sustainable and Resilient Supply Chain Resource Management Under Conditions of Structural Dynamics.” Annals of Operations Research. doi:10.1007/s10479-019-03182-6.
   Google Scholar
• Sarkis, J., S. Talluri, and A. Gunasekaran. 2007. “A Strategic Model for Agile Virtual Enterprise Partner Selection.” International Journal of Operations & Production Management 27 (11): 1213–1234.
   Web of Science ®Google Scholar
• Sawik, T. 2017. “A Portfolio Approach to Supply Chain Disruption Management.” International Journal of Production Research 55 (7): 1970–1991.
   Web of Science ®Google Scholar
• Scheibe, K. P., and J. Blackhurst. 2018. “Supply Chain Disruption Propagation: a Systemic Risk and Normal Accident Theory Perspective.” International Journal of Production Research 56 (1-2): 43–59.
   Web of Science ®Google Scholar
• Simchi-Levi, D., H. Wang, and Y. Wei. 2018. “Increasing Supply Chain Robustness Through Process Flexibility and Inventory.” Production and Operations Management 27 (8): 1476–1491.
   Web of Science ®Google Scholar
• Spiegler, V., M. Naim, and J. Wikner. 2012. “A Control Engineering Approach to the Assessment of Supply Chain Resilience.” International Journal of Production Research 50: 6162–6187.
   Web of Science ®Google Scholar
• Surana, A., S. Kumara, M. Greaves, and U. N. Raghavan. 2005. “ Supply-Chain Networks: a Complex Adaptive Systems Perspective.” International Journal of Production Research 43 (20): 4235–4265.
   Web of Science ®Google Scholar
• Tan, W. J., W. Cai, and A. N. Zhang. 2020. “Structural-aware Simulation Analysis of Supply Chain Resilience.” International Journal of Production Research. doi:10.1080/00207543.2019.1705421.
   PubMed Web of Science ®Google Scholar
• Tang, C. S., and L. P. Veelenturf. 2019. “The Strategic Role of Logistics in the Industry 4.0 era.” Trans-portation Research Part E: Logistics and Transportation Review 129: 1–11.
   Web of Science ®Google Scholar
• Wang, J., R. Dou, R. R. Muddada, and W. Zhang. 2018. “Management of a Holistic Supply Chain Network for Proactive Resilience: Theory and Case Study.” Computers and Industrial Engineering 125: 668–677.
   Web of Science ®Google Scholar
• Wang, J., R. R. Muddada, H. Wang, J. Ding, Y. Lin, C. Liu, and Wenjun Zhang. 2014. “Toward a Resilient Holistic Supply Chain NetworkSystem: Concept, Review and Future Direction.” IEEE Systems Journal 10 (2): 410–421.
   Web of Science ®Google Scholar
• Yoon, J., S. Talluri, H. Yildiz, and W. Ho. 2018. “Models for Supplier Selection and Risk Mitigation: A Holistic Approach.” International Journal of Production Research 56 (10): 3636–3661.
   Web of Science ®Google Scholar
• Zhao, K., Z. Zuo, and J. V. Blackhurst. 2019. “Modelling Supply Chain Adaptation for Disruptions: An Empirically Grounded Complex Adaptive Systems Approach.” Journal of Operations Management 65 (2): 190–212.
   Web of Science ®Google Scholar