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

Abstract

The COVID-19 pandemic has triggered new research areas in supply chain resilience. One of these new areas is viability. Viability extends the resilience understanding from performance-based assessment of firm’s responses to disruptions towards survivability of both supply chains and associated ecosystems not only during some short-term disruptions but also under conditions of long-term crises. To explore the state-of-the-art knowledge on methods, models, capabilities, and technologies of supply chain viability, we edited this important IJPR special issue. To introduce the special issue, we review the existing literature on supply chain viability, conceptualise seven major pillars of supply chain viability theory (i.e. viable supply chain design, viability in process planning and control, ripple effect, intertwined and reconfigurable supply networks, ecosystems, digital supply chain, and Industry 5.0), and establish some associated future research directions. The findings of this editorial paper, as well as the articles in the special issue, can be used by researchers and practitioners alike to consolidate recent advances and practices of viability in supply chain networks and lay the solid foundation for further developments in this area.

KEYWORDS:

• Supply chain resilience
• ripple effect
• viability
• Industry 5.0
• digital supply chain
• COVID-19

1. Introduction

Since early 2020, supply chains and production systems worldwide have experienced an unprecedented series of shocks caused by the COVID-19 pandemic – a new source of supply chain disruptions, quite unlike any seen in recent times (Choi 2020; Ivanov 2020; Dolgui and Ivanov 2021; Aldrighetti, Battini, and Ivanov 2023; Brusset et al. 2022; Delasay, Jain, and Kumar 2022; Paul et al. 2022). The COVID-19 outbreak has not only affected all areas of economy and society but also put the resilience of supply chains to the test (Simchi-Levi and Simchi-Levi 2020; Li et al. 2022; Ramani, Ghosh, and Sodhi 2022; Xu et al. 2022). The resulting supply chain adaptations have yielded a series of completely novel decision-making challenges for researchers and practitioners (Ivanov and Dolgui 2021a; Shen and Sun 2021; Müller, Hoberg, and Fransoo 2022; Rozhkov et al. 2022). In particular, the pandemic has motivated an extension of supply chain resilience (recovering from a disruption event) to a more complex and longer term notion which we call supply chain viability. Supply chain viability encompasses research at the intersection of resilience, adaptability, and sustainability (Ivanov and Dolgui 2020).

Viability extends resilience in two main directions:

1. Resilience is the ability to recover after a disruption (e.g., an earthquake) and return to some baseline, initial state. Viability is the ability to operate and continue to serve markets/customers with products and services in the presence of disruptions and long-term crises (i.e., the ability to survive in the long-term) through adaptation and reconfiguration changing states dynamically.

2. Resilience considers economic performance of individual supply chains. Viability integrates resilience and sustainability through a combination of economical and societal components. Viability refers not only to individual supply chains, but also to intertwined supply networks and ecosystems.

Supply chain viability extends resilience and risk management knowledge towards survivability under conditions of long-term and unpredictably scaling disruptions. According to Ivanov and Dolgui (2020, 2905), ‘viability is a behavior-driven property of a system with structural dynamics. It considers system evolution through disruption-reaction balancing in the open system context. The viability analysis is survival-oriented at a long-term scale’. Ivanov (2022c) defines viability as an ‘ability of a supply chain to maintain itself and survive in a changing environment through a redesign of structures and re-planning of performance with long-term impacts’.

A viable supply chain and its associated frameworks are proposed by Ivanov (2022c) and comprise not only the supply chain itself, but also the intertwined supply network (ISN). An ISN is an ‘entirety of interconnected supply chains which, in their integrity secure the provision of society and markets with goods and services’ (Ivanov and Dolgui 2020). An ISN is different from traditional supply chains of a company since it contains supply chains of different industry sectors that intersect sharing common nodes and links. Firms in the ISN may play different roles. For example, a firm can be a producer of displays in an electronic supply chain and a supplier of displays in a healthcare supply chain.

The principal ideas of the viable supply chain and ISN are adaptable structural supply chain designs for situational supply-demand allocations and, most importantly, the establishment and control of adaptive mechanisms for transitions between the structural designs (Ivanov 2022c). The viable supply chain model can help firms guide decisions on recovery and rebuilding of the supply chains after global, long-term crises. The firms in ISNs may exhibit multiple behaviours by changing the buyer-supplier roles in interconnected or even competing supply chains (Zhao, Zuo, and Blackhurst 2019). Fraccascia, Giannoccaro, and Albino (2017) point to the multiple, intersecting supply chains in the industrial symbiosis which are characterised by using the waste of some supply chain processes as the inputs into other supply chains. Choi, Taleizadeh, and Yue (2020) show different forms of supply chain interconnections in the sharing and circular economies.

Consideration of the ISN viability is as important as resilience of individual supply chains. ISNs viability is crucial for securing society’s needs in line with natural, economic, and governance interests at national and/or global scale (e.g. an agricultural ISN, a mobility ISN, and a healthcare ISN). Since supply chains of different industry sectors are intertwined, the issues of collaborative and collective survival in the presence of extra-ordinary conditions are very important. For example, suppliers in the automotive sector are at the same time producers of valves for respirators. Such an integrated consideration of viability and ISNs principally extends the classical supply chai resilience understanding. Therefore, it becomes a timely and crucial research task to develop a new thinking of resilience towards viability. Viability can extend the supply chain resilience toward survivability in the cases of extraordinary events (Dolgui, Ivanov, and Sokolov 2020; Ivanov 2021c). The supply chain survivability in the context of such extra-ordinary events goes beyond the achievement of mere economic goals and brings the discussion toward viability, which needs to be secured over a longer period.

The example of COVID-19 pandemic clearly shows the necessity of taking the viability perspective where substantial contributions can be done in the future. Ivanov and Keskin (2023) summarise some recent contributions in the development of supply chain viability theory. Moreover, the COVID-19 example clearly provides evidence for the existence of the ripple effect in global supply chains – firms had to stop production worldwide due to missing supply, quarantine measures and market disruptions (Dolgui, Ivanov, and Sokolov 2018; Ivanov 2020; Li et al. 2021; Park et al. 2022). The COVID-19 pandemic shows that in the case of extraordinary events, supply chain resistance to the ripple effect needs to be considered at the scale of survivability or viability to avoid supply chain and market collapses and secure the provision with goods and services. Recent literature argues that the ripple effect can even lead to shortage economy (Ivanov and Dolgui 2022b). Besides, ISNs form complex digital ecosystems. Related concepts are digital supply chain, which represents a combination of the physical supply chain (Ivanov, Dolgui, and Sokolov 2022; Maccarthy and Ivanov 2022a; MacCarthy and Ivanov 2022b); a cyber-physical system and a digital supply chain twin (Ivanov and Dolgui 2021b).

All the considerations above clearly show that supply chain viability is a timely and crucial topic. This editorial paper reviews in the following literature on supply chain viability with a special focus on the papers accepted for publication in this IJPR special issue ‘Viability of Supply Networks and Ecosystems: Lessons Learned From COVID-19 Outbreak’. The main objective is understanding of new theories and novel approaches concerning supply chain viability conceptualisation, its antecedents, drivers, economic, and social performance implications.

2. Literature review

2.1. SCOPUS search

To understand the state-of-the-art in research on supply chain viability, we run a SCOPUS search organised as follows: We searched for (TITLE (‘supply chain’) OR TITLE (‘supply network’) AND TITLE (‘viability’) OR TITLE (‘viable’)) on 24 January 2023. The search yielded 55 papers dated from 2002 to 2023, and 56 keywords used occurred minimum two times. Reading the papers from 2002 to 2019 has shown that terms ‘viability’ or ‘viable’ have been used rather randomly and sometimes out of context, without a clear reference to their meaning as compared to resilience. As such we further focused on papers published in 2020–2023 only. This limited the scope to 37 papers. The result of the VOS Viewer co-occurrence analysis after a manual refining the keyword list (i.e. removing irrelevant or repetitive keywords) is presented in Figure 1.

Figure 1. Co-occurrence analysis in VOS viewer.

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

It can be observed from Figure 1 that supply chain viability research is concerned with topics around resilience (the red cluster), the ripple effect (the purple cluster), sustainability, and digital technology/artificial intelligence (a mix of green and blue clusters). Three seminal publications that lay foundations of supply chain viability theory are the following ones.

Ivanov and Dolgui (2020) define the term of supply chain viability and proposed a biological system model for ISN viability extending the analysis from supply chain to ecosystem level. Ivanov (2022c) proposes a Viable Supply Chain Model. In the Viable Supply Chain Model, angles of sustainability and resilience are integrated and extended toward survivability. The Viable Supply Chain Model is based on adaptable structural network designs for situational supply-demand allocations and, most importantly, the establishment and control of adaptive mechanisms for transitions between the structural designs (Ivanov 2022c). Ruel et al. (2021) develop a measurement scale for supply chain viability contrasting it to resilience. In particular, they noted that ‘supply chain viability can be viewed from an overarching adaptation perspective that extends the supply chain resilience notion of a closed-system, “bounce-back” view, with a viable, open supply chain system perspective incorporating “bounce-forward-and-adapt” options’.

The research on supply chain viability has then grown fast covering several areas. First, COVID-19 impacts on supply chains have been studied from the perspective of viability (Ivanov 2021a; Nasir et al. 2022; Liu, Han, and Zhu 2022b; Kumar et al. 2022). Second, digital technology in supply chains (in particular, Blockchain and digital twins) has been examined as an enabler of supply chain viability (Lotfi et al. 2021; Yin and Ran 2021; Sheng and Saide 2021; Lotfi et al. 2022; Holzwarth, Staib, and Ivanov 2022; Zekhnini et al. 2022). Third, building viable supply chain designs has emerged as a new research area (Wang and Yao 2021; Ivanov 2022e; Kahr 2022). Fourth, financial viability became a focus of research (Taylor and Rosca 2022). Fifth, production and control related issues of viability have been addressed (Ansari and Kohl 2022). Sixth, a specific focus was driven to viability of different ecosystems, e.g. healthcare, mobility, and agriculture (Alizadeh et al. 2022; Ivanov and Dolgui 2022a; Münch and Hartmann 2022; Balezentis et al. 2023; Sardesai and Klingebiel 2023). Seventh, ripple effect research has been progressed in the context of viability (Ivanov 2022d; Liu et al. 2022a; Sawik 2023).

2.2. Papers in this special issue ‘viability of supply networks and ecosystems: lessons learned from COVID-19 outbreak’

For this special issue, we carefully selected 19 papers for publication after a rigorous review of numerous submissions. The papers included in the Special Issue all provide novel and innovative contributions with high practical relevance that are methodically rigorous and rooted in optimisation, network theory, game theory, data-driven analytics, and empirical research. We especially highlight that those papers have been induced by industrial context and practical applications showing industrial response to the COVID-19 pandemic and building SC viability in different manufacturing and service sectors across the globe. Most centrally, the papers in this special issue explicitly incorporate pandemic specifics identified above and go beyond resilience to singular-event disruptions.

In this section, we summarise major contextual, methodical, and managerial areas covered by the papers in this Special Issue. We particularly focus on the managerial insights and contribution to supply chain viability theory.

ManMohan S. Sodhi, Christopher S. Tang, and Evan T. Willenson analyse in their paper ‘Research opportunities in preparing supply chains of essential goods for future pandemics’ reasons for and consequences of severe and prolonged shortages of personal protective equipment (PPE) in the United States. Drawing from the lessons learned from the COVID-19 pandemic, they propose a research agenda and opportunities to develop responsive supply chains to fight future pandemics. These opportunities revolve around measures that are intended to improve the supply chain responsiveness of essential products to combat future pandemics and other major public health emergencies (Sodhi, Tang, and Willenson 2021).

Javad Feizabadi, David M. Gligor & Thomas Y. Choi offer in their paper ‘Examining the resiliency of intertwined supply networks: a jury-rigging perspective’ a novel lens of ISN analysis, namely the jury-rigging behaviour, tinkering with the parts and components and combining them in a manner that is not pre-specified to solve a problem encountering unknown-unknowns. Drawing on complex adaptive systems and Ashby’s law of requisite variety, the authors examine jury-rigging search behaviour and managing the interdependencies across the supply chains as two ex-ante adaptive mechanisms affecting the supply chain network adaptiveness and resiliency. First, they operationalise the biological-based notion of jury-rigging and isolated its effect on enhancing the complex adaptive system scale of resiliency in the supply chain network. Second, the effects of a density in the ISNs are highlighted demonstrating that the higher intensity level of coupling among the supply chains may not improve the system’s resiliency (Feizabadi, Gligor, and Choi 2021).

Tadeusz Sawik develops in his paper ‘A Stochastic Optimization Approach to Maintain Supply Chain Viability under the Ripple Effect’ a novel quantitative approach and stochastic quadratic optimisation model to achieve supply chain viability under the ripple effect. The proposed approach is based on establishment of viability boundaries on acceptable production states associated with two conflicting objectives (i.e. cost and customer service level) which makes it different to viability kernel commonly used in the viability theory. The model allows to select a viable production trajectory in-between the two boundary trajectories subject to cost-optimality and service-optimality. Keeping production trajectory in-between the two boundaries makes the supply chain more resilient to disruption risks, while the supply chain resilience declines as the production trajectory approaches a boundary trajectory. The analysis can help indicate when a severe disruption may push the production outside the viability region and cause greater losses (Sawik 2023).

Maximilian Klöckner, Christoph G. Schmidt, and Stephan M. Wagner examine in their paper ‘The COVID-19 pandemic and shareholder value: impact and mitigation’ shareholder value vulnerabilities during the COVID-19 pandemic (Klöckner, Schmidt, and Wagner 2022). Based on a sample of 4032 publicly traded U.S. and Chinese firms, they conduct an event study and find that the COVID-19 pandemic is associated with a substantial decrease in shareholder value, significantly varying between U.S. and Chinese firms and across industries. Dependence on physical assets, a trade cycle, and a degree of vertical integration are found to be the key determinants influencing the impact of the pandemic on the shareholder value. The authors conclude that 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

Xavier Brusset, Morteza Davari, Aseem Kinra, and Davide La Torre propose in their paper ‘Modelling ripple effect propagation and global supply chain workforce productivity impacts in pandemic disruptions’ an optimal control model for ripple effect analysis under pandemic settings which are modelled using an epidemiological model and influence the ripple effect through reducing the production workforce capacity (Brusset et al. 2022). 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.

Mozhu Wang and Jianming Yao develop in their paper ‘Intertwined supply network design under facility and transportation disruption from the viability perspective’ a mathematical model to capture the trade-off between total cost and viability performance under facility and transportation disruption. The authors propose an Lagrangian relaxation algorithm, combined with the sub-gradient method and the improved cellular genetic algorithm, to solve problems of different scales. To test the performance of the model and corresponding algorithms, they conduct a numerical analysis of the data from medical equipment ISN in southern China. The results indicate that the proposed ISN design model can effectively optimise ISN structures, which makes it possible to dynamically provide flexible redundancy. The relationship between ISN structure and viability performance is thus observed and explained (Wang and Yao 2021).

Christopher Münch and Evi Hartmann (2022) analyse in their paper ‘Transforming resilience in the context of a pandemic: results from a cross-industry case study exploring supply chain viability’ data collected during the COVID-19 pandemic in interviews with 18 supply chain and production experts in Germany directly involved in crisis management. The results revealed seven higher-level capability groups for building resilience in ISNs during a pandemic outbreak: agility, collaboration, digital preparedness, flexible redundancy, human resource management, contingency planning, and transparency and visibility (Münch and Hartmann 2022).

Mohamed R. Salama and Ronald G. McGarvey propose in their paper ‘Resilient supply chain to a global pandemic’ a stochastic mixed integer linear programming model aiming to maximise the conditional value at risk (CVaR) of supply chain profit for a set of COVID-19 pandemic scenarios. Supply chains for socially critical products, such as ventilators, are studied separately to examine the impact of network expansion on maximising demand satisfaction. Finally, they computationally investigate the effects of diversifying network node locations across different administrative regions on supply chain performance in order to obtain recommendations on pandemic impacts and strategic policies (Salama and McGarvey 2021).

Salomée Ruel & Jamal El Baz examine in their paper ‘Disaster readiness’ influence on the impact of supply chain resilience and robustness on firms’ financial performance: a COVID-19 empirical investigation’ the impacts of supply chain disaster readiness on network resilience and robustness. A particular focus is directed on the impact on firms’ financial performance in the context of the COVID-19 pandemic. Drawing on the dynamic capabilities view and organisational readiness for change theory, the authors develop a theoretical model and assess data gathered at 398 French firms using structural equation modelling. The findings corroborate the role of supply chain disaster readiness in setting the stage for resilience and robustness. In addition, the results indicate the positive influence of supply chain resilience on financial performance (Ruel and El Baz 2021).

Sanjoy Kumar Paul, Md. Abdul Moktadir, Karam Sallam, Tsan-Ming Choi, and Ripon Kumar Chakrabortty propose in their paper ‘A recovery planning model for online business operations under the COVID-19 outbreak’ a mathematical model for supply chain recovery optimisation. The modelling setting is complex and characterised by time-dependent and dynamic demand, supply, and warehouse capacity. To explore the impacts of the COVID-19 pandemic, several measures are used such as collaborating with emergency suppliers, increasing warehouse capacity, and considering back-orders and lost sales to frame the recovery strategies. Demand, supply, and warehouse capacities are considered as uncertain variables. Further, an innovative solution approach using an adapted differential evolution technique is proposed, which is capable of generating long-term recovery plans and solving both small- and large-scale problems. The proposed optimisation model can assist decision-makers of online business operations facing a pandemic to decide on the optimal recovery plans (Paul et al. 2021).

Bin Shen, Yang Liu, Vincent Quan, and Xin Wen analyse in their paper ‘Supplying masks to combat respiratory diseases: safety index, welfare and government involvement’ impacts of pandemic and infection dynamics on prices and demand of N95 and surgical masks. They use a game-theoretical approach and find that as the infection probability increases, both the retail price and demand for these masks will increase. When the infection probability is sufficiently low, those consumers who want to purchase masks are more likely to purchase N95 masks, but when the infection probability increases, surgical masks are more popular amongst consumers. The authors also develop a safety index that indicates the effectiveness of using masks in preventing respiratory disease infection. This index is especially crucial in cases where the infection probability is moderate. Finally, they examine the impacts of government involvement in handling the outbreak of respiratory diseases and conclude that providing consumer subsidies and promoting the social mask enterprise can effectively combat respiratory diseases (Shen et al. 2021).

Muhammad Shujaat Mubarik, Simonov Kusi-Sarpong, Kannan Govindan, Sharfuddin Ahmed Khan, and Adegboyega Oyedijo develop in their paper ‘Supply chain mapping: a proposed construct’ an approach to structure dimensions of supply chain mapping as a critical capability of crisis responses. Based on literature review and focused group discussions, they identify three major dimensions of supply chain mapping, namely upstream mapping, downstream mapping, and midstream mapping, with a total of 25 items. The developed construct can be used to operationalise the supply chain mapping and to examine its antecedents and precedents (Mubarik et al. 2021).

Pradeep K. Jha, Suvadip Ghorai, Rakhi Jha, Rajul Datt, Gowrishankar Sulapu, and Surya Prakash Singh consider in their paper ‘Forecasting the impact of epidemic outbreaks on the supply chain: modelling asymptomatic cases of the COVID-19 pandemic’ a distinct discrepancy between confirmed COVID-19 cases and already infected or asymptomatic cases when preparing long-term lockdown guidelines. The impact of asymptomatic cases on supply chain operations is examined using a generalised susceptible-exposed-infected-recovered (S-E-I-R) approach which is further applied to develop a mathematical model. The model can be used to assess the asymptomatic impacts on the supply chains and develop an action plan for reducing disruption in the supply chain (Jha et al. 2021).

Anni-Kaisa Kähkönen, Pietro Evangelista, Jukka Hallikas, Mika Immonen, and Katrina Lintukangas propose in their paper ‘COVID-19 as a trigger for dynamic capability development and supply chain resilience improvement’ a framework of capabilities related to supply chain resilience under pandemic conditions. Using survey data, they found that the impacts of the COVID-19 on a firm’s upstream supply chain influence firms’ capabilities to seize opportunities or neutralise threats. The central role is played by adaptability capabilities. The author conclude that upstream disruptions pushed companies to react to threats and opportunities in the supply market, while downstream disruptions leveraged reconfiguring capabilities (Kähkönen et al. 2021).

Ahmed Mohammed, Ana Beatriz Lopes de Sousa Jabbour, and Ali Diabat develop in their paper ‘COVID-19 pandemic disruption: a matter of building companies” internal and external resilience’ an integrated methodology for diagnosing supply chain resilience in terms of internal dynamic capabilities of an enterprise, and resilience of its suppliers. Multi-attribute decision making (MADM) algorithms are employed to quantify the relative importance and evaluate the internal and external resilience of an enterprise. The results show that development of internal resilience capabilities is an important condition for development of external resilience capabilities (Mohammed, Jabbour, and Diabat 2021).

Xiaoping Xu, Yujing Chen, Ping He, Yugang Yu, and Gongbing Bi examine in their paper ‘The selection of marketplace mode and reselling mode with demand disruptions under cap-and-trade regulation’ the cooperating mode selection problem of a manufacturer who sells its products through an offline channel and an online platform under cap-and-trade regulation. In particular, the focus of the study is directed on manufacturer’s optimal operational decisions and selection of the platform’s modes considering demand disruptions. The authors conclude that considering demand disruptions, the total profit with reselling mode in decentralised case is larger than that in centralised case under some situations (Xu et al. 2021).

Xiongping Yue, Dong Mu, Chao Wang, Huanyu Ren, and Pezhman Ghadimi (2022) examine in their paper ‘Topological structure and COVID-19 related risk propagation in TFT-LCD supply networks’ the topological structure and COVID-19-related ripple effects in TFT-LCD supply networks from a dynamic perspective. Using network analysis, they identify hidden risky sources in TFT-LCD supply networks by the proposed risk propagation model. Additionally, a ‘robust-yet-fragile’ configuration in these supply networks is uncovered, and the hidden risky interfirm cooperations are revealed. These findings can help managers reduce the vulnerability to disruptions and construct more robust and resilient networks (Yue et al. 2022).

Yiji Cai, Shuyi Wang, Zhiyuan Ouyang, and George Q. Huang develop in their paper ‘Impacts of social distancing measures on global supply chain configuration’ a mixed-integer programming model to integrate environment changes in lead time and cost for transportation and processing, market size, and the number of countries imposing social distancing measures. In particular, they examine propagation impacts (i.e. the ripple effect) on global supply chains when the social distancing measures are imposed on firms in different echelons in supply chains. They demonstrate that supply chain losses and disruptions from the COVID-19 pandemic-driven ripple effects primarily depend on the number of countries following restricted transportation, market size, and processing limitations. They note that social distancing restrictions in transportation in downstream echelons increase the propagation impacts. In addition, compared with elastic-demand supply chains, the fixed-demand one, e.g. food supply chain, suffers more significantly with the stringent social distancing measures and high inventory holding costs (Cai et al. 2022).

Rohit Sindhwani, Jayanth Jayaram, and Venkataramanaiah Saddikuti examine in their paper ‘Ripple effect mitigation capabilities of a hub and spoke distribution network: an empirical analysis of pharmaceutical supply chains in India’ the ripple effect in Indian pharmaceutical distribution network during COVID-19 pandemic. Using a hybrid methodology combining Bayesian network, mathematical optimisation, and discrete event simulation, the authors reveal an associative relationship between ripple effect mitigation capabilities and network design characteristics of upstream supply chains. They conclude that regional distribution centres and backup supply sources provide overall flexibility and improve occupational health and safety. Several relevant policy recommendations are derived as well (Sindhwani, Jayaram, and Saddikuti 2022).

In Table 1, we summarise major methodologies, contributions to viability theory, and managerial insights.

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.

3. Discussion

Analysis of the existing literature allows us to classify some major pillars of viable supply chain design and management research (Table 2).

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

From Table 2, seven major pillars of viable supply chain design and management research, namely viable supply chain design, viability in process planning and control, ripple effect, intertwined and reconfigurable supply networks, ecosystems, digital supply chain, and Industry 5.0, can be classified. We elaborate on some of them in more details. For example, the existing supply chain designs are not always capable to cope with this ‘new normal’ unless they are modified and adapted every day, which creates tremendous coordination efforts and results in time delays and shortages. Building dynamically adaptable and structurally changeable networks is one important determinant of supply chain viability (Aldrighetti et al. 2021; Ivanov 2021b; Babai, Ivanov, and Kwon 2023; Dolgui and Proth 2010;  Hägele, Grosse, and Ivanov 2023; Liu et al. 2022a; Sawik 2022). As noted in Ivanov and Keskin (2023), ‘further research is needed to understand viability and develop new methods for stress-testing supply chain well before a real shock hits and disrupts structures and operations’.

In addition, supply chains evolve toward technology-driven, digital ecosystems (Choi et al. 2022b; Choi et al. 2022a; Hosseini, Ivanov, and Blackhurst 2022; Ivanov 2022a; MacCarthy and Ivanov 2022b. In the ecosystems, different industries intersect with each other sharing common suppliers, manufacturers and warehouses. This cross-industry context of supply chain viability is a new and relevant research area. Finally, viability develops an integrative perspective spanning resilience, sustainability, and human-centricity. Industry 5.0 (Choi et al. 2022a) also follows this integration principle. In this setting, viability can be considered as a theoretical lens for supply chain research in relation to Industry 5.0 (Battini et al. 2022; Ivanov 2022b).

4. Conclusion

Supply chain viability theory is a new area of research in production, supply chain and operations management coined by Ivanov and Dolgui (2020) and Ivanov (2020). As noted in Ivanov and Keskin (2023), ‘the importance of SC viability within and beyond the pandemic context has become evident very quickly’. In this setting, the development of the supply chain viability theory targets developments of new methods, models, and technologies for creation and control of viable value-adding networks able to cope with severe crises and deep uncertainties.

Viability extends the resilience understanding from performance-based assessment of firm’s responses to disruptions towards survivability of both supply chains and associated ecosystems. In this paper, we reviewed the existing literature on supply chain viability in general and papers selected for this Special Issue ‘Viability of Supply Networks and Ecosystems: Lessons Learned From COVID-19 Outbreak’ in particular.

We conceptualised seven major pillars of supply chain viability theory – viable supply chain design, viability in process planning and control, ripple effect, intertwined and reconfigurable supply networks, ecosystems, digital supply chain, and Industry 5.0 – and outlined future research directions. This structure can be used by researchers and practitioners alike to systemise recent developments and practices of viability in supply chain networks.

Acknowledgements

We are grateful to all of the scholars for contributing their research on supply chain viability to this important special issue. Specifically, we appreciate the overflowing submissions to this special issue that enabled us to produce a complete coverage of the current landscape. We appreciate all of the reviewers for their timely and constructive reviews that elevated the quality of the final manuscripts.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Dmitry Ivanov

Dmitry Ivanov is a professor of supply chain and operations management at Berlin School of Economics and Law. He serves at the school as an Academic director of M.A. Global Supply Chain and Operations Management and B.Sc. International Sustainability Management as well as a Deputy Director of Institute for Logistics. His publication list includes around 400 publications, including over 130 papers in international academic journals and leading textbooks Global Supply Chain and Operations Management and Introduction to Supply Chain Resilience. His main research interests and results span resilience, viability and ripple effect in supply chains, risk analytics, and digital twins. Author of the Viable Supply Chain Model and founder of the ripple effect research in supply chains. Recipient of IISE Transactions Best Paper Award 2021, Best Paper and Most Cited Paper Awards of IJPR (2018,2019, 2020, 2021), OMEGA Best Paper Award 2022, Clarivate Highly Cited Researcher Award (2021, 2022). He co-edits IJISM and is an associate editor of the IJPR and OMEGA. He is Chairman of IFAC TC 5.2 “Manufacturing Modelling for Management and Control”.

Alexandre Dolgui

Alexandre Dolgui is an IISE Fellow, Distinguished Professor, and the Head of Automation, Production and Computer Sciences Department at the IMT Atlantique, France. His research focuses on manufacturing line design, production planning and supply chain optimization. His main results are based on the exact mathematical programming methods and their intelligent coupling with heuristics and metaheuristics algorithms. He is the co-author of 5 books, the co-editor of 27 books or conference proceedings, the author of over 300 refereed journal papers, as well as over 400 papers in conference proceedings. He is an Area Editor of Computers & Industrial Engineering, past Associate Editor of International Journal of Systems Science, IEEE Transactions on Industrial Informatics and Omega. He is Member of the Editorial Boards for 27 other journals, including the International Journal of Production Economics. He is an Active Fellow of the European Academy for Industrial Management, Member of the Board of the International Foundation for Production Research, former Chair of IFAC TC 5.2 Manufacturing Modelling for Management and Control (2011-2017, currently a vice-chair), Member of IFIP WG 5.7 Advances in Production Management Systems, IEEE System Council Analytics and Risk Technical Committee. He is the Editor-in-Chief of the International Journal of Production Research (IJPR).

Jennifer V. Blackhurst

Jennifer Blackhurst is the Associate Dean for Graduate Programs and the Leonard A. Hadley Professor of Business Analytics in Tippie College of Business. In her role as Associate Dean, she leads the efforts of the development and innovation of graduate education programs in the Tippie College. Blackhurst received her doctorate in Industrial Engineering from the University of Iowa in 2002. Her research is focused in the areas of supply chain risk and disruption management; supplier assessment and selection; and supply chain design and coordination. Blackhurst has also been actively involved in the national and international supply chain management discipline by serving on a variety of editorial review boards. She is associate editor for Decision Sciences Journal, Senior Editor for Journal of Business Logistics and she serves on the editorial review boards for Journal of Operations Management, Journal of Business Logistics, Journal of Supply Chain Management, and IEEE Transactions on Engineering Management. She has served on the Decision Sciences Board of Directors in a number of roles. In 2013 and again in 2017, Blackhurst was recognized as Outstanding Associate Editor for Decision Sciences Journal.

Tsan-Ming Choi

Tsan-Ming Choi is currently Chair in Operations and Supply Chain Management, and Director of Centre for Supply Chain Research at University of Liverpool Management School. Prof. Choi is a highly cited researcher who has published extensively in leading journals in the fields of operations management, engineering management, logistics, and supply chain management. He is currently serving the profession as the Co-Editor-in-Chief of Transportation Research Part E: Logistics and Transportation Review, a Department Editor of IEEE Transactions on Engineering Management, a Senior Editor of Production and Operations Management, and Decision Support Systems, an Associate Editor of Decision Sciences, and IEEE Transactions on Systems, Man and Cybernetics - Systems, and an editorial board member of International Journal of Production Economics, International Journal of Production Research, etc. He is also a member of the Engineering Panel of Research Grants Council of Hong Kong. He has taught at The Chinese University of Hong Kong, The Hong Kong Polytechnic University, National Taiwan University, and University of Liverpool Management School, altogether for more than 20 years.