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The COVID-19 pandemic's impacts have been devastating for the global economy, and particularly for manufacturing companies. Many firms were unprepared for a crisis of this magnitude and adapted their operations in an ad-hoc manner. Some of these adaptations were facilitated by digital technologies (DTs). This article examines extant literature using a systematic review methodology in order to extend our understanding of what DTs have been used in manufacturing companies during the pandemic, how DTs have helped manufacturing companies cope with the pandemic, and how these innovations can be used in the post-pandemic world. The major outcome of our study is a novel classification of DT applications in the pandemic setting in the manufacturing industry. In addition, we propose an agenda for future research. [ABSTRACT FROM AUTHOR]

Disruptions can adversely affect profitability, service level, and even the viability of supply networks (SNs). Natural disasters, the COVID-19 pandemic, and geopolitical tensions heightened disruption risks for SNs. We propose a methodological framework to guide the design of resilient SNs, with a focus on efficient resilience. In fact, despite an increasing economic and social interest in SN resilience and a large variety of qualitative resilience frameworks, there is a lack of model-based frameworks to guide decision makers in the complex task of designing resilient SNs. Differently to the existing literature, that mostly focuses on industry- or disruption-specific approaches, the framework of this paper is general, independent from sectors and causes. It consists of three steps to guide practitioners through model-based stress testing of their SNs: it integrates and organises methods from the literature, from the selection of data to be collected to the validation of the resilient and efficient SN. We illustrate the application of descriptive, predictive, and prescriptive analytics at each phase using real-life case studies data supplemented by literature references. Finally, we present an industrial case study with the step-by-step application of the framework highlighting its strengths and objectives. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

During a crisis, manufacturing processes in supply chains of different industries may network with each other as an adaptation response. We propose and examine a "network-of-networks" mechanism of such a cross-industry adaptation to learn about the value of reducing uncertainty through collaborative crisis preparedness and response during the COVID-19 pandemic. Our study allows revelation of the underlying trade-offs between the manufacturing capacity conversion time and effort required to adapt and the gains from collaborative preparedness to uncertainty. Through a real-life data-based analysis with the help of mathematical optimization, we connect the networks-of-networks coordination design and the outcomes of scenario modeling demonstrating a superiority of the coordinated capacity repurposing when compared to ad-hoc adaptation. We conclude that an appropriate collaboration of governmental agencies, healthcare, and industry is crucial for a prompt capacity conversion to healthcare production in a pandemic. Concrete implementation ways are visibility, healthcare inventory monitoring, technology backup plans, and repurposing contingency plans at the preparedness stage. At the response stage, a correct adaptation start time determines success. The results obtained can be instructive to develop technological and managerial plans for a cross-industry adaptation. The proposed "network-of-networks" perspective contributes to theory of supply chain viability and adaptation under disruptions using intertwined supply networks. [ABSTRACT FROM AUTHOR]

Supply chain (SC) and operations management has been developed for decades under the fundamental assumption of continuous availability (with some temporary fluctuations and disruptions) of resources to satisfy demand. Under extreme shocks and long-lasting disruptions, SCs and operations face long-term shortages of components, energy, capital, and labour, as well as rapidly rising prices. These long-term resource shortages and risks of hyper-inflation pose novel and unexpected challenges potentially leading to global ripple effects. In this conceptual paper, we first analyse and categorise the available literature on SC and operations management with resource shortages. We then systemise some managerial implications of resource shortages and rising inflation, conceptualising some potential research directions which appeared or may appear in the settings of shortage economy. We conclude that the shortage economy provides a distinct and specific context which goes beyond the conventional problems under constrained or disrupted resources – i.e. the long-term resource shortages with simultaneous disruptions in labour, material, energy, and capital availability. This paper could be useful for researchers and practitioners alike to systemise potential impacts of a shortage economy on SCs and operations, and to navigate adaptation and recovery processes in a structured way to help society cope with deep uncertainties. [ABSTRACT FROM AUTHOR]

Supply chains (SCs) are exposed to multiple risks and vulnerable to disruption propagation (i.e. the ripple effect). Despite established literature, quantitative analysis of the ripple effect in SCs considering simultaneous, long-term disruptions (i.e. induced by the COVID-19 pandemic) remains limited. This study defines, applies and demonstrates the capability of system dynamics modelling to recognise and visualise the ripple effect subject to supply, demand, and logistics disruptions as well as a combined, simultaneous disruption of supply, demand and logistics. Simulation results for these four risk scenarios indicate that disruption propagation and its impacts vary based on risk type, combination of risks and the impacting node. The bi-directional, increasing effect is significant for disruptions of longer duration. Retailers and manufacturers are most fragile to multiple disruptions due to broader risk exposure points. In generalised terms, systems theory-based study provides insights into the complex behaviour of simultaneous risks and associated disruptions occurring at a node and across the SC. The outcomes derived can help practitioners visualise and recognise the dynamic nature of the ripple effect cascading across the SC network. In addition, some novel insights on the systemic nature and delayed impact of disruption propagations are uncovered and discussed. [ABSTRACT FROM AUTHOR]

While the majority of companies anticipated the negative and severe impacts of the COVID-19 pandemic on the supply chains (SC), most of them lacked guidance on how to model disruptions and their performance impacts under pandemic conditions. Lack of such guidance resulted in delayed reactions, incomplete understanding of pandemic impacts, and late deployment of recovery actions. In this study, we offer a method of modelling and quantifying the SC disruption impacts in the wake of a pandemic. We develop a multi-layer Bayesian network (BN) model that can be used to identify SC disruption triggers and risk events amid the COVID-19 pandemic and quantify the consequences of pandemic disruptions. The unique features of BN, such as forward and backward propagation analysis, are utilised to simulate and measure the impact of different triggers on SC financial performance and business continuity. In this way, we combine resilience and viability SC perspectives and explicitly account for the pandemic settings. The outcomes of this research open a novel theoretical lens on application of BNs to SC disruption modelling in the pandemic setting. Our results can be used as a decision-support tool to predict and better understand the pandemic impacts on SC performance. [ABSTRACT FROM AUTHOR]

Although the World Health Organization has declared the end of the COVID-19 pandemic, doctors continue to register new cases of the disease among both adults and children. Unfortunately, the course of COVID-19 in children can have a severe form, with death being a potential outcome. The absence of published works discussing the pathological morphology of COVID-19 in children prevents the objective analysis of the disease's pathogenesis, including among the adult population. In this vein, the objective of our study is to identify the morphological features of the lungs' involvement and evaluate virus–host interactions in the case of COVID-19 in patients at a pediatric medical practice. We present the results of the study of the lungs of three children who died due to COVID-19, highlighting the predominant involvement of their respiratory organs at different stages of the disease (5, 21, and 50 days). This article presents data obtained from histopathological and immunohistochemical investigations, taking into account the results of clinical and laboratory indicators and intravital and postmortem SARS-CoV-2 PCR investigations. The common finding of all of the examined COVID-19 cases is the involvement of the endothelium in microcirculation vessels, which are considered to be a primary target of various pathogenic influencing factors. We also discuss both the significance of apoptosis as a result of virus–host interactions and the most likely cause of endothelium cell destruction. The results of this study could be useful for the development of endothelium-protective therapy to prevent the progression of disseminated intravascular coagulation syndrome. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has challenged supply chains (SC) on an unprecedented scale testing viability and adaptation under severe uncertainty. However, the literature on the adaptation strategies and quantification of their impacts is still scarce. Mixing literature analysis, case study approach, and quantitative techniques for performance assessment under disruptions, our study generalises four adaptations strategies – intertwining, scalability, substitution, and repurposing – to maintain SC viability when facing a pandemic, and offers a model to analyse and quantify deployment and impact of adaptation. First, we analyse the recent literature and identify some of the general characteristics of adaptation strategies during the COVID-19 pandemic. We then describe case studies to illustrate the practical context and supplement the literature analysis in order to derive relevant determinants for building of a conceptual framework and construction of a formal model. In the conceptual framework, we show how the adaptation strategies can be aligned with the SC viability, encompassing the levels of the ecosystem, network, and resources. In the generalised model, we formalise the impacts and efforts in deploying and assessing the adaptation strategies as both a process and an outcome. We close by proposing some open research questions and outline several future research directions. [ABSTRACT FROM AUTHOR]

Ripple effect is a specific area of SC disruptions and a strong stressor to SC resilience. Research on the ripple effect analyses how one or more disruptive events propagate through the SC and impact its resilience and performance. The phenomenon of the ripple effect, immensely existing in practice, has received great research interest in recent years. Ripple effect management, modelling and assessment became visible research avenues with a growing number and scope of contributions. This Special Issue presents recent developments on the ripple effect in SCs. The Special Issue focuses on studies that address the ripple effect and provide a comprehensive picture of the state of the art and future perspectives. The methodologies comprise of mathematical optimisation, simulation, game theory, control theoretic, data-driven analytics, network complexity, reliability theory research, and empirical research. Even though a variety of valuable insights have been developed in this area in recent years, new research avenues and ripple effect taxonomies are identified for further exploring the ripple effect in the settings of the COVID-19 pandemic, SC viability, viable SC model, and reconfigurable SCs. [ABSTRACT FROM AUTHOR]

Viability is the ability of a supply chain (SC) to maintain itself and survive in a changing environment through a redesign of structures and replanning of performance with long-term impacts. In this paper, we theorize a new notion—the viable supply chain (VSC). In our approach, viability is considered as an underlying SC property spanning three perspectives, i.e., agility, resilience, and sustainability. The principal ideas of the VSC model are adaptable structural SC designs for supply–demand allocations and, most importantly, establishment and control of adaptive mechanisms for transitions between the structural designs. Further, we demonstrate how the VSC components can be categorized across organizational, informational, process-functional, technological, and financial structures. Moreover, our study offers a VSC framework within an SC ecosystem. We discuss the relations between resilience and viability. Through the lens and guidance of dynamic systems theory, we illustrate the VSC model at the technical level. The VSC model can be of value for decision-makers to design SCs that can react adaptively to both positive changes (i.e., the agility angle) and be able to absorb negative disturbances, recover and survive during short-term disruptions and long-term, global shocks with societal and economical transformations (i.e., the resilience and sustainability angles). The VSC model can help firms in guiding their decisions on recovery and re-building of their SCs after global, long-term crises such as the COVID-19 pandemic. We emphasize that resilience is the central perspective in the VSC guaranteeing viability of the SCs of the future. Emerging directions in VSC research are discussed. [ABSTRACT FROM AUTHOR]

The coronavirus (COVID-19) outbreak shows that pandemics and epidemics can seriously wreak havoc on supply chains (SC) around the globe. Humanitarian logistics literature has extensively studied epidemic impacts; however, there exists a research gap in understanding of pandemic impacts in commercial SCs. To progress in this direction, we present a systematic analysis of the impacts of epidemic outbreaks on SCs guided by a structured literature review that collated a unique set of publications. The literature review findings suggest that influenza was the most visible epidemic outbreak reported, and that optimization of resource allocation and distribution emerged as the most popular topic. The streamlining of the literature helps us to reveal several new research tensions and novel categorizations/classifications. Most centrally, we propose a framework for operations and supply chain management at the times of COVID-19 pandemic spanning six perspectives, i.e., adaptation, digitalization, preparedness, recovery, ripple effect, and sustainability. Utilizing the outcomes of our analysis, we tease out a series of open research questions that would not be observed otherwise. Our study also emphasizes the need and offers directions to advance the literature on the impacts of the epidemic outbreaks on SCs framing a research agenda for scholars and practitioners working on this emerging research stream. [ABSTRACT FROM AUTHOR]

Purpose: Supply chain resilience capabilities are usually considered in light of some anticipated events and are as passive assets, which are "waiting" for use in case of an emergency. This, however, can be inefficient. Moreover, the current COVID-19 pandemic has revealed difficulties in the timely deployments of resilience assets and their utilization for value creation. We present a framework that consolidates different angles of efficient resilience and renders utilization of resilience capabilities for creation of value. Design/methodology/approach: We conceptualise the design of the AURA (Active Usage of Resilience Assets) framework for post-COVID-19 supply chain management through collating the extant literature on value creation-oriented resilience and practical examples and complementing our analysis with a discussion of practical implementations. Findings: Building upon and integrating the existing frameworks of VSC (Viable Supply Chain), RSC (Reconfigurable Supply Chain) and LCNSC (Low-Certainty-Need Supply Chain), we elaborate on a new idea in the AURA approach – to consider resilience as an inherent, active and value-creating component of operations management decisions, rather than as a passive "shield" to protect against rare, severe events. We identify 10 future research areas for lean resilience integrating management and digital platforms and technology. Practical implications: The outcomes of our study can be used by supply chain and operations managers to improve the efficiency and effectiveness by turning resilience from passive, cost-driving assets into a value-creating, inclusive decision-making paradigm. Originality/value: We propose a novel approach to bring more dynamics to the notion of supply chain resilience. We name our approach AURA and articulate its two major advantages as follows: (1) reduction of disruption prediction efforts and (2) value creation from resilience assets. We offer a discussion on ten future research directions towards a lean resilience. [ABSTRACT FROM AUTHOR]

A correction to this paper has been published: https://doi.org/10.1007/s11192-021-04042-6 [ABSTRACT FROM AUTHOR]

We theorize a notion of a digital supply chain (SC) twin – a computerized model that represents network states for any given moment in real time. We explore the conditions surrounding the design and implementation of the digital twins when managing disruption risks in SCs. The combination of model-based and data-driven approaches allows uncovering the interrelations of risk data, disruption modeling, and performance assessment. The SC shocks and adaptations amid the COVID-19 pandemic along with post-pandemic recoveries provide indisputable evidences for the urgent needs of digital twins for mapping supply networks and ensuring visibility. The results of this study contribute to the research and practice of SC risk management by enhancing predictive and reactive decisions to utilize the advantages of SC visualization, historical disruption data analysis, and real-time disruption data and ensure end-to-end visibility and business continuity in global companies. [ABSTRACT FROM AUTHOR]

This research focuses on the profound impact of the shocks caused by the COVID-19 pandemic on the accuracy of AI-based demand forecasting in the beauty care industry. It aims to understand the key factors that led to decreased forecasting accuracy during the pandemic and employs causal mediation analysis to systematically investigate this complex issue. The empirical analysis is conducted using extensive order data from a major beauty care product manufacturer and distributor, covering the pre-pandemic, pandemic, and post-pandemic periods. The findings reveal that it is primarily the increase in demand volatility, and not the surge in sales volume, that has led to an increase in forecasting errors. This research provides crucial insights into the nuanced effects of macroeconomic shocks and consumer behavior changes on AI-based forecasting within the beauty care industry. Furthermore, it highlights the importance of understanding the underlying mechanisms that drive forecasting errors, paving the way for more resilient and robust demand forecasting systems in the future. • Critical link between pandemic-induced demand volatility and AI forecasting accuracy. • Application of causal mediation analysis in exploring pandemic effects on AI forecasting. • Insights into forecasting model vulnerabilities during unprecedented disruptions. [ABSTRACT FROM AUTHOR]

• We uncover repurposing practices during the COVID-19 pandemic. • We examine case-studies from automotive industry. • We propose a framework to improve supply chain viability. • We define viability capabilities. Supply chain disruptions caused by the COVID-19 pandemic have drastically transformed the automotive industry by adversely affecting and seriously disrupting its global networks with regards to degree of severity and complexity, scale and impact duration. The conventional disruption mitigation measures showed to be inadequate in assisting businesses to survive in this extremely volatile and deeply uncertain environment. Through design of multiple case-studies and a cross-case analysis, we uncover repurposing practices, which have been used in the automotive industry to maintain operations and deliver highly demanded medical items. Our results show that a combination of repurposing, intertwining, scalability, and substitution represents the most effective way for increasing supply chain viability during a long-term crisis. The proposed conceptual framework consists of three constructs, namely adapting supply chains and operations, rethinking sourcing strategy and building intertwined supply networks, as well as five viability capabilities including adaptability, agility, flexibility, collaboration and visibility. The framework can be used by supply chain managers as a guidance for creating supply chain viability using adaptation-based principles. [ABSTRACT FROM AUTHOR]

• We examine the impact of the COVID-19 pandemic on food retail supply chains. • We use a digital SC twin for modeling and performance assessment. • We identify most severe scenarios of pandemic disruptions for food supply chains. • We propose a framework for resilience improvement. In this study, we examine the impact of the COVID-19 pandemic on food retail supply chains (SCs) and their resilience. Based on real-life pandemic scenarios encountered in Germany, we develop and use a discrete-event simulation model to examine SC operations and performance dynamics with the help of anyLogistix digital SC twin. The computational results show that food retail SC resilience at the upheaval times is triangulated by the pandemic intensity and associated lockdown/shutdown governmental measures, inventory-ordering dynamics in the SC, and customer behaviours. We observe that surges in demand and supplier shutdowns have had the highest impact on SC operations and performance, whereas the impact of transportation disruptions was rather low. Transportation costs have spiked because of chaotic inventory-ordering dynamics leading to more frequent and irregular shipments. On bright side, we observe the demand growth and utilization of online sales channels yielding higher revenues. We propose several directions and practical implementation guidelines to improve the food retail SC resilience. We stress the importance of SC digital twins and end-to-end visibility along with resilient demand, inventory, and capacity management. The outcomes of our study can be instructive for enhancing the resilience of food retail SCs in preparation for future pandemics and pandemic-like crises. [ABSTRACT FROM AUTHOR]

• Epidemic outbreaks are a special case of supply chain (SC) risks. • We articulate the specific features of epidemic outbreaks in SCs. • We demonstrate a simulation model for epidemic outbreak analysis. • We use an example of coronavirus COVID-19 outbreak. Epidemic outbreaks are a special case of supply chain (SC) risks which is distinctively characterized by a long-term disruption existence, disruption propagations (i.e., the ripple effect), and high uncertainty. We present the results of a simulation study that opens some new research tensions on the impact of COVID-19 (SARS-CoV-2) on the global SCs. First, we articulate the specific features that frame epidemic outbreaks as a unique type of SC disruption risks. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of epidemic outbreaks on the SC performance using the example of coronavirus COVID-19 and anyLogistix simulation and optimization software. We offer an analysis for observing and predicting both short-term and long-term impacts of epidemic outbreaks on the SCs along with managerial insights. A set of sensitivity experiments for different scenarios allows illustrating the model's behavior and its value for decision-makers. The major observation from the simulation experiments is that the timing of the closing and opening of the facilities at different echelons might become a major factor that determines the epidemic outbreak impact on the SC performance rather than an upstream disruption duration or the speed of epidemic propagation. Other important factors are lead-time, speed of epidemic propagation, and the upstream and downstream disruption durations in the SC. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of epidemic outbreaks on the SCs and develop pandemic SC plans. Our approach can also help to identify the successful and wrong elements of risk mitigation/preparedness and recovery policies in case of epidemic outbreaks. The paper is concluded by summarizing the most important insights and outlining future research agenda. [ABSTRACT FROM AUTHOR]

Objective: To study burnout of Russian physicians in the conditions of COVID-19 pandemic and how their work with coronavirus-infected patients influenced it. According to a three-factor model of burnout developed by Maslach and Jackson, this syndrome includes emotional exhaustion, depersonalization, and reduction of personal accomplishment. Design: A cross-sectional survey study. Setting: Large medical practice. Participants: Physicians of different specialties. Methods: Data collection was conducted from June 23 to July 12, 2020. We developed a Google form including a questionnaire and psychological inventories and placed it in a medical portal. Maslach Burnout Inventory -- Human Services Survey for Medical Personnel was used to study burnout; the Hospital Anxiety and Depression Scale was used to determine anxiety and depression. Results: Of all the physicians who took part in the study (N = 599), 31.2 % worked with coronavirus-infected patients. Of the medical personnel who treated COVID-19 patients, 63.6% noted increased workload during the pandemic. Compared to other physicians, they more often had a high degree of emotional exhaustion (43.3 % vs 33.0 %, φ* = 2.404, P ≤ 0.01) and depersonalization (41.7 % vs 34, 0%, φ* = 1.803, P ≤ 0.05). An overwhelming majority of physicians, without any dependence on work with infected patients, had an absence of anxiety and depression. The identified interrelations between the symptoms of burnout, anxiety, depression; age and career stage in medical personnel were identical, except for weak correlations between age and emotional exhaustion (rs = -0.097, P ≤ 0.05), as well as career stage and personal accomplishment (rs = 0.102, P ≤ 0.05) in those physicians who worked with COVID-19 patients. The structure of burnout was identical in all physicians and did not depend on interaction with the infected patients. Conclusion: Public health authorities should reduce the workload on physicians involved in treating infected patients against the backdrop of the pandemic. Psychotherapeutic measures focused on preventing burnout should reduce its number among physicians interacting with patients infected with the coronavirus. [ABSTRACT FROM AUTHOR]