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Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=tprs20 International Journal of Production Research ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/tprs20 Supply Chain Viability and the COVID-19 pandemic: a conceptual and formal generalisation of four major adaptation strategies Dmitry Ivanov To cite this article: Dmitry Ivanov (2021) Supply Chain Viability and the COVID-19 pandemic: a conceptual and formal generalisation of four major adaptation strategies, International Journal of Production Research, 59:12, 3535-3552, DOI: 10.1080/00207543.2021.1890852 To link to this article: https://doi.org/10.1080/00207543.2021.1890852 Published online: 09 Mar 2021. Submit your article to this journal Article views: 2241 View related articles View Crossmark data Citing articles: 23 View citing articles https://www.tandfonline.com/action/journalInformation?journalCode=tprs20 https://www.tandfonline.com/loi/tprs20 https://www.tandfonline.com/action/showCitFormats?doi=10.1080/00207543.2021.1890852 https://doi.org/10.1080/00207543.2021.1890852 https://www.tandfonline.com/action/authorSubmission?journalCode=tprs20&show=instructions https://www.tandfonline.com/action/authorSubmission?journalCode=tprs20&show=instructions https://www.tandfonline.com/doi/mlt/10.1080/00207543.2021.1890852 https://www.tandfonline.com/doi/mlt/10.1080/00207543.2021.1890852 http://crossmark.crossref.org/dialog/?doi=10.1080/00207543.2021.1890852&domain=pdf&date_stamp=2021-03-09 http://crossmark.crossref.org/dialog/?doi=10.1080/00207543.2021.1890852&domain=pdf&date_stamp=2021-03-09 https://www.tandfonline.com/doi/citedby/10.1080/00207543.2021.1890852#tabModule https://www.tandfonline.com/doi/citedby/10.1080/00207543.2021.1890852#tabModule INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2021, VOL. 59, NO. 12, 3535–3552 https://doi.org/10.1080/00207543.2021.1890852 Supply Chain Viability and the COVID-19 pandemic: a conceptual and formal generalisation of four major adaptation strategies Dmitry Ivanov Berlin School of Economics and Law, Supply Chain and Operations Management, Berlin, Germany ABSTRACT The COVID-19 pandemic has challenged supply chains (SC) on an unprecedented scale testing via- bility 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 via- bility 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 frame- work, 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. ARTICLE HISTORY Received 30 December 2020 Accepted 30 January 2021 KEYWORDS Supply chain dynamics; supply chain resilience; pandemic; COVID-19; adaptation; supply chain viability 1. Introduction The COVID-19 pandemic and measures for its con- trol have changed the ‘normal’, challenging the sup- ply chain (SC) ecosystems, networks, flows, and indi- vidual firms on an unprecedented scale under severe uncertainty (Ivanov and Dolgui 2021; Singh et al. 2020; Sodhi, Tang, and Willenson 2021). Carefully designed for both efficiency (Amiri 2006; Dolgui and Proth 2010) and resilience (i.e. the ability to cope and recover after singular-event-immediate-impact disruptions such as tsunamis or fires), SCs lacked the understanding and guidance on how to react and operate under pandemic conditions (Gholami-Zanjani et al. 2021; Golan, Jerne- gan, and Linkov 2020; Gupta, Ivanov, and Choi 2021; He et al. 2019; Hosseini, Ivanov, and Dolgui 2019; Tan, Cai, and Zhang 2020). While the majority of companies had anticipated the negative and severe impacts of the pan- demic, most of them have reacted in a delayed fashion causing production and delivery deviations, high coordi- nation efforts, and long shortage periods, as entailed by the late or misleading deployment of adaptation actions (El Baz and Ruel 2021; Ivanov et al. 2020; Yang et al. 2020; Queiroz et al. 2020; Tang, Sodhi, and Willenson 2021). CONTACT Dmitry Ivanov [email protected] Badensche Str. 50-51, 10825 Berlin, Germany This article has been corrected with minor changes. These changes do not impact the academic content of the article. The pandemic context has motivated a new rise in SC resilience research (Bier, Lange, and Glock 2020; Chauhan, Perera, and Brintrup 2020; Dolgui, Ivanov, and Sokolov 2020; Dubey et al. 2021; Lücker, Chopra, and Seifert 2020; Namdar et al. 2020; Sawik 2019; Sawik 2020; Xu et al. 2020). However, resilience theory lacks a con- ceptual lens related to pandemic-like disruptions. The new conceptual perspective of resilience, i.e. SC viabil- ity, has been positioned to close the research gap in the area of survivability under long-term, severe, and unpre- dictably scaling disruptions (Ivanov 2020b; Ivanov and Dolgui 2020b). Viability refers to the ‘ability of a supply chain to main- tain itself and survive in a changing environment through a redesign of structures and replanning of performance with long-term impacts’ (Ivanov and Dolgui 2020b). The examples of SC viability analysis can be found in the Viable SC model (Ivanov 2020b) and intertwined supply networks (ISN) (Ivanov and Dolgui 2020b). The Viable SC (VSC) model was proposed to address the issues of dynamically adaptable and structurally changeable value- adding networks. It is comprised of three major per- spectives, i.e. a viable SC ecosystem, a multi-level SC © 2021 Informa UK Limited, trading as Taylor & Francis Group http://www.tandfonline.com https://crossmark.crossref.org/dialog/?doi=10.1080/00207543.2021.1890852&domain=pdf&date_stamp=2021-06-02 http://orcid.org/0000-0003-4932-9627 mailto:[email protected] 3536 D. IVANOV network design, and a set of VSC capabilities (Ivanov 2020b, 2021a). The viability notion can be considered an extended resilience perspective with regards to survivability of firms and industrial sectors as a whole entailing a transition from a closed system, ‘bounce-back’ view to an open system, ‘bounce-forward-and-adapt’ notion (Ivanov 2020b; Ivanov and Dolgui 2020b). The viability notion shows some similarities to the socio-ecological resilience perspective and panarchy as a structure of adaptive cycles that are linked across different levels on scales of time, space, and meaning (Wieland 2021). Via- bility has some similarities to the meso level of resilience as proposed by Azadegan and Dooley (2021), and it is seen by practitioners and researchers alike as an impor- tant construct to be used for both acute survivability stages and as a strategic angle to ensure survival at the level of ecosystems, SCs, and firms in a long-term perspective (Hofmann and Langner 2020; Ruel et al. 2021). The design and management of an SC that is not only efficient and resilient but also viable and capable of oper- ations and demand fulfilment continuity despite severe super disruptions are imperative for firms to survive and provide society with essential goods and services during long-term crises (Hofmann and Langner 2020; Ruel et al. 2021). However, the COVID-19 pandemic has unveiled the lack of viability in many SCs, as complex networks failed from disruptions at local nodes, their propagation (i.e. the ripple effect), and the resulting missing connec- tivity. This study is related to SC adaptation and viability as novel context in decision-making in the wake of the COVID-19 pandemic, going beyond short-term, singu- lar event-driven disruptions toward long-term SC crises with inherent uncertainty about the present and future (Choi 2020; Mehrotra et al. 2020). The pandemic set- ting has some specific characteristics. First, a pandemic is characterised a long-term disruption the dynamics of which needs to be predicted (Barrett et al. 2020; Ivanov 2020a). This implies some possibilities for preparing the SC to cope with the pandemic, but also requires re- thinking the SC operations for a long period shaped by presence of a strong external stressor of an exogenous dynamics. Second, simultaneous disruptions at several SC echelons with simultaneous and/or sequential open- ings and closures of suppliers, facilities, and markets are characteristic for a pandemic (Ivanov and Das 2020). Third, recovery actions need to be planned and deployed in the presence of disruption, and its own dynamics. A pandemic does not always allow SCs to bounce back; fre- quently, the only way to survive is adaptation (Ruel et al. 2021). With regards to the pandemic context, we posit that adaptation plays the central role in SC operations during a pandemic and that certain aspects of this pandemic- related context can be approached using the notion of SC viability. Adaptation helps SCs survive and be viable at a longer timescale (Ivanov and Dolgui 2020b). The recent literature analysed different strategies to adapt SCs to instant disruptions and pandemic, observing that attempts to substitute supply resulted in designing ad- hoc SCs that used the resources and capacities of inter- twined and even competing networks (Hosseini, Ivanov, and Dolgui 2019; Snyder et al. 2016; Tang and Tomlin 2008; Tomlin 2006; Yoon et al. 2018). These strategies have been utilised in practice during the COVID-19 pan- demic. For example, ALDI and McDonald’s have jointly helped each other to compensate for workforce shortages (ESM 2020). Amazon has scaled up delivery capacities by developing its own logistics network to cope with drasti- cally increased demand (Statt 2020). Ford has repurposed its SC and production processes from car manufacturing to ventilator and face shields (Ford 2020). Furthermore, many European firms have found a backup supplier in Europe and substituted the supply from China. Many firms have also entered non-traditional supply markets for their existing products to meet disruption-induced surges in demand, as well as to compensate for sudden deficiencies in their regular supply chains. After losing about 50\% of its largely indoors business to COVID- 19, the Panera Bread chain adapted to a new SC to offer staple groceries along with the traditional soups and bread. Burger chain Fuddruckers, meanwhile, sold toilet paper, gloves, and bleach at specific locations – products far removed from its regular fast food product line, requiring entirely different SC infrastructure (Taylor 2020). Despite several useful studies and insights, the liter- ature on SC adaptation to the COVID-19 pandemic is still scarce and fragmented; examinations of individual adaptation strategies are scattered over different sources, and the results have not yet been generalised. Even if the general management literature has elaborated on the strategic view of firms’ responses to disruptions and crisis (Bode et al. 2011; Rindova and Courtney 2020; Ritter and Pedersen 2020), these results (e.g. Wenzel et al. (2020) identify that such types of strategic responses to crisis as retrenchment, persevering, innovating, and exit) are difficult to apply to operational adaptation. In turn, the research on the operational level of adaptation is still scarce. We address this gap and engage in collating the recent literature and practical case studies, covering the variety of SC adaptations to the pandemic from different perspectives and leading to a generalised formal descrip- tion of the adaptation impact modelling and assessment. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 3537 The distinct and substantial contribution of our study is the generalising of insights obtained in adapting SCs to the pandemic and the articulating of four major adapta- tion strategies – intertwining, scalability, substitution, and repurposing – that firms used to maintain SC viability under COVID-19 pandemic conditions. We show how these four strategies are associated with the framework of SC viability, comprehensively encompassing the lay- ers of ecosystem, network, and resources. We then offer a generalised model that articulates a logic of interde- pendencies between the impacts and efforts in deploying and assessing the adaptation strategies, and allows to analyse and quantify the adaptation strategy deployment and impact. Finally, we formulate a set of open research questions and outline several future research directions. The rest of this paper is organised as follows. Section 2 presents an analysis of the literature on the impacts of the COVID-19 pandemic on SCs and the associated adap- tation strategies. In Section 3, we describe case studies illustrating real-life adaptation strategies that have been utilised during the COVID-19 pandemic. In Section 4, we present a framework of SC adaptation strategies and formulate a generalised model and some associ- ated decision-making problems of SC adaptation to pan- demics. Section 5 is devoted to open research questions and future research directions. We conclude the paper by summarising major findings in Section 6. 2. Literature review In the wake of the COVID-19 pandemic, a series of papers have appeared between in 2020 trying to (1) con- ceptualise the impacts of the pandemic on SCs, (2) iden- tify the resulting research areas, (3) explain the immedi- ate effects observed in the first weeks and months of the pandemic, and (4) project the insights obtained at the pandemic times toward post-pandemic world. In terms of methodology, the existing literature can be classified into three groups, e.g. simulation and optimisation, con- ceptual frameworks, and empirical studies. We elaborate on some studies in each of these groups more detailed in this section. The first group of COVID-19 pandemic-related stud- ies comprised of simulation and optimisation research sought to examine the immediate impacts at the begin- ning of the pandemic. One of the first published research on the pandemic’s impacts on SCs, a study by Ivanov (2020a), utilised a discrete event simulation model using anyLogistix software to predict the impacts of the pan- demic on SC performance (i.e. service level, lead time, fulfilment rate). The author constructed three scenar- ios of the ripple effect (i.e. disruption propagations in the SCs) in global SCs, based on the research by Ivanov, Sokolov, and Dolgui (2014), Dolgui, Ivanov, and Sokolov (2018), and Li et al. (2020). Assuming different dura- tions of pandemic control measures and propagation speeds of the pandemic across the continents, Ivanov (2020a) observed that the timing of the closing and open- ing of facilities at different echelons with some overlap- ping time windows was a major factor in determining the COVID-19 outbreak’s impact on SC performance. These findings have motivated further research and been used in designing mathematical models. For example, Singh et al. (2020) developed a simulation model to analyse the responsiveness level of food SCs in India when confronting the COVID-19 pandemic. The authors observed that by centralising the warehouses, the scala- bility of SC capacity could improve responsiveness mea- sured through the service level. One important outcome of the studies by Ivanov (2020a), Ivanov and Das (2020), and Singh et al. (2020) was the observation that SC operations and performance undergo drastic degrada- tion under the pandemic conditions, thus positing the need for adaptation strategies. Paul and Chowdhury (2020a) analysed several adap- tation strategies for managing pandemic-related SC dis- ruption that involved intertwining and substitution, such as resource-sharing among manufacturers and the use of collective emergency sourcing. The authors analysed the impact of these strategies on the SC service levels and uncovered associations between the flexible usage of SC resources (i.e. by resource sharing among manufactur- ers) and responsiveness. Mehrotra et al. (2020) tackled SC adaptation by developing a stochastic optimisation model for allocating and sharing a critical resource under pandemic conditions. They elaborated on the impact and efforts to ramp-up ventilator production, finding that the timely deployment of an adaptation strategy (e.g. ramping-up production early in the planning cycle) reduces shortfalls of critical items in the SC significantly. Govindan, Mina, and Alavi (2020) proposed a decision support system based on a fuzzy inference system that could be used to manage demand and control the pan- demic outbreaks affecting healthcare SCs. Looking at the surges in demand, Paul and Chowdhury (2020b) simi- larly developed a production recovery model that could be utilised to revise production plans for a high-demand essential item during the COVID-19 pandemic. Their proposed model considers production capacity scala- bility, supply substitution by emergency sourcing, and collaboration among manufacturers as key activities to maintain operations continuity under severe surges in demand. Nagurney (2021), meanwhile, examined the role of labour constraint in an SC network during the COVID-19 pandemic using a game-theoretical study. The results pointed to a crucial role of scalability in SC 3538 D. IVANOV capacities when coping with super disruptions. Radanliev et al. (2020a) discussed COVID-19 pandemic and data mining visualisations to understand mortality, immunity and vaccine development processes during the first wave of the pandemic. Radanliev et al. (2020b, 2020c) elabo- rated on the role of digital technology in pandemic man- agement following the concepts of predictive, preventive and personalised medicine. The second area of research on the COVID-19 pan- demic and SCs is formed by conceptual frameworks. Ivanov and Dolgui (2020b) proposed the notion of SC viability with a particular emphasis on the viability of intertwined supply networks (ISNs) in the context of the COVID-19 pandemic. They used a trophic chain- based game theoretical model to show that intertwining as an adaptation strategy could help avoid SC disrup- tions in the case of a pandemic like COVID-19. Ivanov (2020b) further defined the concept of viable SCs (VSCs) to cope with super disruptions and SC crises associated with COVID-19. Three major components of the VSC model – SC ecosystems, multiple SC network designs, and viability capabilities – have been presented. Craig- head, Ketchen, and Darby (2020) offered the notion of transiliency to capture the ability to simultaneously restore some processes and change others through trans- formation and resilience. Queiroz et al. (2020), mean- while, performed a structured literature review and elab- orated on an emerging research agenda for SC and oper- ations management during pandemic outbreaks. The six areas of this agenda were as follows: (1) preparedness focus (i.e. pre-allocation of resources, product diversifi- cation, and substitution), (2) anticipation focus (i.e. flexi- ble production, re-allocations of supply and demand), (3) digital focus (i.e. digital manufacturing, data analytics), (4) ripple effect focus (i.e. control of disruption propa- gation, modelling of pandemic scenarios), (5) recovery focus (i.e. integral recovery of the workforce, capacities, and logistics), and (6) sustainability focus (i.e. viabil- ity analysis, intertwined supply networks). Ivanov and Dolgui (2021) conceptualised and summarised the appli- cations of OR/MS methods to control the ripple effect under pandemic conditions. They revealed managerial insights pertaining to network structural adaptation, SC process reconfiguration, and adapting production- inventory control policies at individual firms that can be used to adapt SCs amid a pandemic and during the post-pandemic recovery period. Choi (2020) conceptu- alised major research areas in the transportation liter- ature, highlighting the role of digital technologies and data-driven decision-making during the COVID-19 pan- demic. The third group consisted of empirical studies that were undertaken to uncover the antecedents and consequences of SC disruptions during the pandemic and suggest strategies for improvement. Yang et al. (2020) analysed the antecedents and consequences of SC risk management capabilities, using organic con- trol and mechanistic control to model SC disruption and SC visibility, respectively. El Baz and Ruel (2021), meanwhile, utilised a resource-based view and organi- sational information processing theory to examine the mitigating role of SC risk management practices dur- ing the COVID-19 pandemic. They identified recovery strategies as crucial decision-making areas to maintain SC continuity through the pandemic times. In addition, Chowdhury et al. (2020) used a case study methodology to articulate some common features among pandemic- related adaptation strategies. Their findings suggest that, along with building relationships with new distributors and trade partners, SC restructuring and reconfigura- tion have mostly been utilised by firms in the scope of their study. Wieland (2021) proposed a panarchy framework for SCs considering adaptive cycles that are linked across different levels on scales of time, space, and meaning. In his framework, structures and processes of SCs are reconfigurable (i.e. ‘fluid’), and interwoven with political-economic and planetary phenomena. Building on panarchy theory, Wieland reinterprets the SC as a social–ecological system and leaves behind a static view on the SC and its management, replacing it with a vision of ‘dancing the SC’ which is in line with the reconfig- urable SC framework by Dolgui, Ivanov, and Sokolov (2020) and viable SC framework by Ivanov (2020b). The author points to an unanswered question of ‘how SC management in the post-COVID-19 era can ‘build back better’ to deal with the large crises we are facing – and ignoring – right now’ meaning that the COVID-19 pan- demic is a wake-up call for SC managers to re-think and re-invent the current practices in light of future possible pandemics and climate change. Our literature analysis thus shows that, despite estab- lished resilience capabilities, such as pre-positioned inventory and backup infrastructures, many SCs have fre- quently demonstrated severe shortages, chaotic behavi- ours, and high exposure to the ripple effect due to the magnitude of the COVID-19 pandemic. The studies analysed differ in methodologies and scope of analysis but share a common set of adaptation strategies, includ- ing the intertwining of SCs (including cross-sectoral and competing networks), scalability in production, deliv- ery and sourcing capacities to cope with severe surges in demand and supply, structural SC reconfiguration and substitution of unavailable SC capacities by using backup facilities or building new relationships with sup- pliers, distributors and manufacturers, and the repur- posing of available capacities using the manufacturing INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 3539 and logistics flexibility of facilities and machines for new product compositions. Our analysis shows how the exist- ing literature addresses the four adaptation strategies, i.e. intertwining, scalability, substitution, and repurposing; however, a lack of collating these efforts and their gen- eralisations on the qualitative and quantitative levels can be observed. Our study aims to close this research gap. 3. Case studies Case studies have been considered an effective method in the SC literature to uncover practically relevant context to generalise associated decision-making problems (Wu and Choi 2005). Building on the results of our literature analysis, we now illustrate major SC adaptation strategies identified above using multiple case studies constructed with the use of secondary data. Through the case studies, we aim to illustrate the practical context and supplement the literature analysis to derive relevant determinants for building of the conceptual framework and construction of the formal model in Section 4. 3.1. Scalability in delivery capacity: Amazon Amazon’s SC network has been rated as one of the best in the world by Gartner (Gartner 2020). Even though Amazon was strongly challenged by demand surges and simultaneous lockdown and quarantine measures in the wake of the COVID-19 pandemic across the globe, they adapted in a timely manner (EDGE 2020). In anticipation of possible SC disruptions, Amazon placed last-minute orders with several suppliers that were still able to deliver. The company provided suppliers with five extra days to send inventory to the warehouses and waived late deliv- ery fees (Kulikowska-Wielgus 2020). In a public letter to the Amazon employees, CEO Bezos confirmed that adaptations in logistics, SC, purchasing, and third-party seller processes had been made to prioritise the stock- ing and delivery of essential items like health, medical and household supplies as well as groceries (Bezos 2020). These adaptation measures thus enabled a rapid order distribution (Wehner 2020). Scaling up the capacity, Amazon announced the open- ing of 100,000 new positions (with another 75,000 a month later), raised wages, and paid sick leaves for employees that tested positive for COVID-19 to cope with the increased customer demand and support exist- ing employees (Amazon 2020a, 2020b). From March through September 2020, Amazon increased the capac- ity of its grocery delivery service by 160\% and tripled the number of Whole Foods Market pickup locations to meet the rising demand (MarketUS 2020). Certain Amazon Fresh stores were temporarily made online-only stores that focused on the fulfilment of online orders exclusively. Doing this has allowed Amazon to further scale the deliv- ery capacity. Furthermore, COVID-19 health and safety measures have been implemented in their physical stores to protect employees and customers. These stores also offer dedicated shopping hours for the elderly, disabled, or people that are part of the high-risk group (Amazon 2020c). Amazon’s efforts to adapt have thus created a signifi- cant impact. Figure 1 illustrates Amazon’s growth in sales and profit amid the COVID-19 pandemic in Q1-Q3 2020. It can be observed in Figure 1 that both global net sales and income have been growing for the first three quarters of the COVID-19 pandemic in 2020 (to the date of writ- ing this paper the performance of the fourth quarter has not been announced yet). This confirms the positive per- formance impact of the Amazon’s scalability efforts, and in general, an association of the adaptation measures and performance impact in the presence of a pandemic. 3.2. Scalability in supply capacity: Johnson & Johnson Johnson & Johnson is one of the world’s leading health- care companies (Galea-Pace 2020). Owing in part to its response to the COVID-19 pandemic, Johnson & John- son earned their highest ever-ranking on the Gartner Top 25 Supply Chain list, with a third-place designa- tion (Gartner 2020; Johnson and Johnson 2020b). In the wake of the pandemic, Johnson & Johnson activated their global SC network business continuity plans to ensure the availability of key inventory at major distribution facili- ties (Johnson and Johnson 2020a). Historically, Johnson & Johnson has been exposed to events requiring a quick response from its SC. For example, after a hurricane wreaked havoc on Puerto Rico in 2017, the full operation of local SC facilities was restored rapidly. To help meet the demand, Johnson & Johnson activated backup facil- ities and supply channels. Even though the COVID-19 setting was different, the company was able to incor- porate past experiences in pandemic adaptation strate- gies (Johnson and Johnson 2020a). This is in line with the recent findings of Chen, Li, and Linderman (2020), which uncovered the role of learning in managing SC disruptions. Towards the beginning of the pandemic crisis, the company faced a 100\% increase in demand for their pain treatment drug Tylenol with an active ingredient Parac- etamol (Johnson and Johnson 2020b, 2020c). Although a scarcity was temporarily reported (Blankenship 2020), the SC reacted quickly to maximise the product avail- ability, letting plants and logistics expand their capacities (Johnson and Johnson 2020b). After the outbreak of the 3540 D. IVANOV Figure 1. Amazon’s financial performance in Q1-Q3 2020 (based on DigitalCommerce360.com/article/amazon-sales and https://www.statista.com/statistics/999686/amazons-net-revenue-by-product-group-quarter/). pandemic in Italy, SC managers learnt what they would have to cope with in the near future due to govern- ment regulations and the exposure of the people to the virus. 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