Toward supply chain viability theory: from lessons learned through COVID-19 pandemic to viable ecosystems

Figures & data

Figure 1. Co-occurrence analysis in VOS viewer.

Co-occurence analysis for keywords related to supply chain viability research.

Table 1. A detailed summary of the papers in the special issue.

Citation	Practical context	Methodology	Contribution to viability theory	Managerial / policy insights
Sodhi, Tang, and Willenson (2021)	Shortages of personal protective equipment (PPE) in the United States during COVID-19 pandemic	Conceptual analysis	Research agenda and opportunities to develop responsive supply chains to fight future pandemics	Resilience management practices under COVID-19 pandemic conditions
Feizabadi, Gligor, and Choi (2021)	Automotive and ventilator supply networks	Network simulation / complex adaptive systems	Jury-rigging perspective on intertwined supply network (ISN) analysis	Effects of density in the ISNs on supply chain resilience
Sawik (2023)	Ripple effect and disruptions in the supply chain	Stochastic quadratic optimisation model	Viable trajectory-based approach to selection of resilient production policies in the supply chain	The analysis can help determine viable production policies and indicate when a severe disruption may push the production outside the viability region and cause greater losses
Klöckner, Schmidt, and Wagner (2022)	Shareholder value vulnerabilities during the COVID-19 pandemic	Econometrics	Conceptualisation of the impacts of dependence on physical assets, a trade cycle, and a degree of vertical integration on the shareholder value during a pandemic	Managers should reduce the dependency on physical assets, streamline trade cycles, and reduce supply chain complexity. Policy-makers should consider more industry-specific granularity of public support measures
Brusset et al. (2022)	Ripple effect during COVID-19 pandemic due to infection-triggered workforce vulnerabilities	Optimal control and epidemiological model	Novel approach to predict and control workforce vulnerabilities in the supply chain under pandemic conditions	The model can be used for predictive analysis and what-if scenarios to simulate the impact on the workforce vulnerabilities on the ripple effect identifying bottlenecks which would reduce the ability to serve customer demand.
Wang and Yao (2021)	Medical equipment ISN in southern China	Mixed-integer programming	Relationships between ISN structure and viability performance	Optimisation of ISN structures to dynamically provide flexible redundancy
Münch and Hartmann (2022)	Automotive, electronic, and medical supply chains in Germany	Case-study analysis	Supply chain viability capabilities	Capability groups for building resilience in ISNs during a pandemic outbreak
Salama and McGarvey (2021)	Supply chains for socially critical products, e.g. ventilators	Stochastic mixed integer linear programming	Effects of diversifying network node locations across different administrative regions on supply chain performance	Recommendations on pandemic impacts on supply chain, and strategic resilience policies
Ruel and El Baz (2021)	COVID-19 pandemic-driven reactions of firms to disruptions; 398 French firms	Dynamic capabilities view and organisational readiness for change theory	Role of supply chain disaster readiness in setting the stage for resilience and robustness	Impact on firms’ financial performance in the context of the COVID-19 pandemic
Paul et al. (2021)	Online business	Mathematical optimisation	Supply chain recovery strategy design under pandemic conditions	Model can assist decision-makers of online business operations facing a pandemic to decide on the optimal recovery plans
Shen et al. (2021)	N95 and surgical mask prices and demand under pandemic conditions	Game theory	Role of market and governmental mechanisms in ensuring protection of people through masks during a pandemic	Relationships between infection probability, mask retail price and demand dynamics
Mubarik et al. (2021)	Cross-industry analysis	Literature review and focused group discussions	Dimensions of supply chain mapping	The developed construct can be used to operationalise the supply chain mapping and to examine its antecedents and precedents
Jha et al. (2021)	Infection dynamics forecasting during the COVID-19 pandemic	Susceptible-exposed-infected-recovered (S-E-I-R) approach	Role of asymptotic infection number forecasting on supply chain disruptions	Analysis of asymptomatic cases when preparing long-term lockdown guidelines
Kähkönen et al. (2021)	COVID-19 pandemic-driven reactions of firms to disruptions	Dynamic capability view	A framework of capabilities related to supply chain resilience under pandemic conditions	Central role of adaptability to ensure resilience under pandemic conditions
Mohammed, Jabbour, and Diabat (2021)	COVID-19 pandemic-driven reactions of firms to disruptions	Dynamic capability view and multi-attribute decision making	Integrated methodology for diagnosing supply chain resilience in terms of internal dynamic capabilities of an enterprise, and resilience of its suppliers.	Development of internal resilience capabilities is an important condition for development of external resilience capabilities
Xu et al. (2021)	Platform business model with demand disruption	Game theory	Platform-based cooperation coordination	Recommendations on manufacturer's optimal operational decisions and selection of the platform's modes considering demand disruptions
Yue et al. (2022)	Ripple effect in TFT-LCD supply networks	Network theory	Dynamic ripple effect analysis with uncovering of ‘robust-yet-fragile’ configuration network configurations	Model to identify hidden risky sources in TFT-LCD supply networks
Cai et al. (2022)	Impact of social distancing measures during the COVID-19 pandemic on supply chains	Mixed-integer programming	Role of social distancing measures in ensuring supply chain viability	Model to predict ripple effect impact on global supply chains when the social distancing measures are imposed on firms at different supply chain echelons.
Sindhwani, Jayaram, and Saddikuti (2022)	Ripple effect in Indian pharmaceutical distribution network during COVID-19 pandemic	Bayesian network, mathematical optimisation, and discrete event simulation	Associative relationship between ripple effect mitigation capabilities and network design characteristics of upstream supply chain	Regional distribution centres and backup supply sources provide overall flexibility and improve occupational health and safety.

Table 2. Pillars of viable supply chain design and management research.

Pillars of viable supply chain design and management research	Example of problems
Viable supply chain design	Viable network design optimisation Stress-testing the supply chains to severe crises and deep uncertainty
	Stress-testing the supply chain for critical and rare materials
	Complex adaptive systems with applications to supply chain viability
	Dynamic analysis of the supply chain viability using control and simulation
Viability in process planning and control	Development of repurposing strategies
	Design of viable production control trajectories
	Process design with considerations of hedging instruments against energy, labour, capital, information, and material shortages
	Flexible and reconfigurable capacity and production systems to ensure long-term viability
Ripple effect	Ripple effect and supply chain viability
	Global ripple-effect resistant network designs
	Cross-sectoral ripple effect
Intertwined and reconfigurable supply networks	Cross-industry adaptation through intertwining of different supply chains (e.g. industrial and healthcare supply chains);
	Prioritising industry sectors and demand satisfaction equity
	Collaboration of humanitarian and business logistics for survivability
Ecosystems	Stress-testing ecosystem viability
	Supply chain and ecosystem viability analysis
	Collaboration within supply chain ecosystems (firms, governments, healthcare) for viability
Digital supply chain	Supply chain as a service / Cloud supply chain
	Role of new digital technologies (e.g. additive manufacturing) in viability and resilience increase
	Artificial intelligence-based algorithms for viable supply chain design and planning
Industry 5.0	Congruent and divergent capabilities of resilience and sustainability
	Human-centric, viable supply chain design and management

Sodhi, M. S., C. S. Tang, and E. T. Willenson. 2021. “Research Opportunities in Preparing Supply Chains of Essential Goods for Future Pandemics.” International Journal of Production Research, doi:10.1080/00207543.2021.1884310.

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Feizabadi, J., D. M. Gligor, and T. Y. Choi. 2021. “Examining the Resiliency of Intertwined Supply Networks: A Jury-Rigging Perspective.” International Journal of Production Research. URL. doi:10.1080/00207543.2021.1977865.

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Sawik, T. 2023. “A Stochastic Optimization Approach to Maintain Supply Chain Viability under the Ripple Effect.” International Journal of Production Research. doi:10.1080/00207543.2023.2172964.

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Klöckner, M., C. G. Schmidt, and S. M. Wagner. 2022. “The COVID-19 Pandemic and Shareholder Value: Impact and Mitigation.” International Journal of Production Research, doi:10.1080/00207543.2022.2147235.

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Brusset, X., M. Davari, A. Kinra, and D. La Torre. 2022. “Modelling Ripple Effect Propagation and Global Supply Chain Workforce Productivity Impacts in Pandemic Disruptions.” International Journal of Production Research, doi:10.1080/00207543.2022.2126021.

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Wang, M., and J. Yao. 2021. “Intertwined Supply Network Design under Facility and Transportation Disruption from the Viability Perspective.” International Journal of Production Research, doi:10.1080/00207543.2021.1930237.

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Münch, C., and E. Hartmann. 2022. “Transforming Resilience in the Context of a Pandemic: Results from a Cross-Industry Case Study Exploring Supply Chain Viability.” International Journal of Production Research, doi:10.1080/00207543.2022.2029610.

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Salama, M., and R. McGarvey. 2021. “Resilient Supply Chain to a Global Pandemic.” International Journal of Production Research, doi:10.1080/00207543.2021.1946726.

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Ruel, S., and J. El Baz. 2021. “Disaster Readiness’ Influence on the Impact of Supply Chain Resilience and Robustness on Firms’ Financial Performance: A COVID-19 Empirical Investigation.” International Journal of Production Research, doi:10.1080/00207543.2021.1962559.

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Paul, S., M. Moktadir, K. Sallam, T.-M. Choi, and R. Chakrabortty. 2021. “A Recovery Planning Model for Online Business Operations under the COVID-19 Outbreak.” International Journal of Production Research, doi:10.1080/00207543.2021.1976431.

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Shen, B., Y. Liu, V. Quan, and X. Wen. 2021. “Supplying Masks to Combat Respiratory Diseases: Safety Index, Welfare and Government Involvement.” International Journal of Production Research, doi:10.1080/00207543.2021.1943036.

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Mubarik, M., S. Kusi-Sarpong, K. Govindan, S. Khan, and A. Oyedijo. 2021. “Supply Chain Mapping: A Proposed Construct.” International Journal of Production Research, doi:10.1080/00207543.2021.1944390.

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Jha, P., S. Ghorai, R. Jha, R. Datt, G. Sulapu, and S. Singh. 2021. “Forecasting the Impact of Epidemic Outbreaks on the Supply Chain: Modelling Asymptomatic Cases of the COVID-19 Pandemic.” International Journal of Production Research, doi:10.1080/00207543.2021.1982152.

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Kähkönen, A., P. Evangelista, J. Hallikas, M. Immonen, and K. Lintukangas. 2021. “COVID-19 as a Trigger for Dynamic Capability Development and Supply Chain Resilience Improvement.” International Journal of Production Research, doi10.1080/00207543.2021.2009588.

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Mohammed, A., A. Jabbour, and A. Diabat. 2021. “COVID-19 Pandemic Disruption: A Matter of Building Companies’ Internal and External Resilience.” International Journal of Production Research, doi:10.1080/00207543.2021.1970848.

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Xu, X., Y. Chen, P. He, Y. Yu, and G. Bi. 2021. “The Selection of Marketplace Mode and Reselling Mode with Demand Disruptions under Cap-and-trade Regulation.” International Journal of Production Research, doi:10.1080/00207543.2021.1897175.

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Yue, X., D. Mu, C. Wang, H. Ren, and P. Ghadimi. 2022. “Topological Structure and COVID-19 Related Risk Propagation in TFT-LCD Supply Networks.” International Journal of Production Re-search, doi:10.1080/00207543.2022.2027039.

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Cai, Y., S. Wang, Z. Ouyang, and G. Huang. 2022. “Impacts of Social Distancing Measures on Global Supply Chain Configuration.” International Journal of Production Research, doi:10.1080/00207543.2022.2053604.

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Sindhwani, R., J. Jayaram, and V. Saddikuti. 2022. “Ripple Effect Mitigation Capabilities of a Hub and Spoke Distribution Network: An Empirical Analysis of Pharmaceutical Supply Chains in India.” International Journal of Production Research, doi:10.1080/00207543.2022.2098073.

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