Synthesis of strategies in post-COVID-19 public sector supply chains under an intuitionistic fuzzy environment

Entities in public sector supply chains (SCs) often operate independently despite having interdependent objectives. Such a fragmented operational design poses several problems magnified by the presence of necessary public health measures fueled by COVID-19. This work contributes to the domain literature by introducing an overarching framework for synthesizing strategies in public sector SCs. The underlying component is the translation of information from the upstream to the downstream entities of the SCs, which is carried out by a Kano-enhanced quality function deployment. The proposed framework introduces intuitionistic fuzzy (IF) decision maps with the aid of the full consistency method to incorporate inherent interrelationships among strategies in the translation agenda. Under an IF environment that better captures judgment uncertainties, an actual case study of a multi-level public sector SC motivated by a government-funded project under the COVID-19 pandemic is demonstrated in this work. Findings of the case suggest that the government prioritizes meeting all project objectives. This requirement is reflected in the downstream SC. The project planning entity focuses on creating an overarching plan of operations, material request entity on complying with government procurement protocols, and maintaining public health and safety in operations for the procurement entity. Results show the effective synthesis of strategies across the SC, ensuring SC integration and collaboration. The case study demonstrates that maintaining public health and safety is a significant component of post-COVID-19 public sector SCs. Several practical insights on the synthesis of public sector SC strategies are also provided in this work.     

US state-level economic freedom during the COVID-19 pandemic

The COVID-19 pandemic led to extensive new government regulations and lockdown policies that significantly reduced economic freedom across US states. Many of these new pandemic-related regulatory restrictions on economic freedom varied significantly from state to state but are largely missed by the existing Economic Freedom of North America Report (EFNA). This paper adjusts the Our World in Data COVID-19 Stringency Index into a state-level measure of lockdown regulatory freedom and then merges it into the EFNA index to better measure relative economic freedom across US states in 2020. We find significant differences in the relative ranking of economic freedom between states once we adjust for lockdown regulatory restrictions.     

Reshaping healthcare supply chain using chain-of-things technology and key lessons experienced from COVID-19 pandemic

The COVID-19 (Corona virus disease 2019) pandemic continues to slash through the entire humanity on the earth causing an international health crisis and financial uncertainty. The pandemic has formed a colossal disruption in supply chain networks. It has caused piling higher mortality in patients with comorbidities and generated a surging demand for critical care equipment, vaccines, pharmaceuticals, and cutting-edge technologies. Personal protective equipment, masks, ventilators, testing kits, and even commodities required for daily care have been scarce as lockdown and social distancing guidelines have kicked in. Amidst COVID-19, implementing and executing key processes of the healthcare supply chain (HSC) in a secured, trusted, effective, universally manageable, and the traceable way is perplexing owing to the fragile nature of the HSC, which is susceptible to redundant efforts and systemic risks that can lead to adverse impacts on consumer health and safety. Though the crisis shone a harsh light on the cracks and weaknesses of the HSC, it brings some significant insights into how HSC can be made more resilient and how healthcare industries figure out solutions to mitigate disruptions. While there are innumerable experiences learned from the disruption of this crisis, in this paper, five important areas to analyze the most vital and immediate HSC enhancements including building a resilient supply chain, thinking localization, implementing reliable reverse logistics, breaking down extant silos to achieve end-to-end visibility, and redesigning HSC using digitalization are emphasized. This work identifies important features related to CoT and HSC. Also, this study links these lessons to a potential solution through Chain of Things (CoT) technology. CoT technology provides a better way to monitor HSC products by integrating the Internet of Things (IoT) with blockchain networks. However, such an integrated solution should not only focus on the required features and aspects but also on the correlation among different features. The major objective of this study is to reveal the influence path of CoT on smart HSC development. Hence, this study exploits (i) fuzzy set theory to eliminate redundant and unrelated features; (ii) the Decision-Making and Experimental Evaluation Laboratory (DEMATEL) method to handle the intricate correlation among different features. This fuzzy-DEMATEL (F-DEMATEL) model attempts to direct CoT technology towards smart HSC by identifying the most influencing factors and investors are recommended to contribute to the development of application systems. This work also demonstrates how CoT can act a vital role in handling the HSC issues triggered by the pandemic now and in the post-COVID-19 world. Also, this work proposes different CoT design patterns for increasing opportunities in the HSC network and applied them as imperative solutions for major challenges related to traditional HSC networks.     

The dynamic effects of infectious disease outbreaks: The case of pandemic influenza and human coronavirus

Pandemic influenza is a regularly recurring form of infectious disease; this work analyses its economic effects. Like many other infectious diseases influenza pandemics are usually of short, sharp duration. Human coronavirus is a less regularly recurring infectious disease. The human coronavirus pandemic of 2019 (COVID-19) has presented with seemingly high transmissibility and led to extraordinary socioeconomic disruption due to severe preventative measures by governments. To understand and compare these events, epidemiological and economic models are linked to capture the transmission of a pandemic from regional populations to regional economies and then across regional economies. In contrast to past pandemics, COVID-19 is likely to be of longer duration and more severe in its economic effects given the greater uncertainty surrounding its nature. The analysis indicates how economies are likely to be affected due to the risk-modifying behaviour in the form of preventative measures taken in response to the latest novel pandemic virus.     

COVID-19 crisis and the efficiency of Indian banks: Have they weathered the storm?

The purpose of this study is to determine whether Indian banks were able to weather the COVID-19 storm. We estimate banks’ deposits-generating and operating efficiencies using a two-stage directional distance function-based network data envelopment analysis (DDF-NDEA) approach and seek to capture the immediate impact of COVID-19 on these efficiency measures by comparing their magnitudes in the pre-pandemic (2014/15–2019/20), just 1-year prior to the pandemic (2019/20), and during the pandemic year (2020/21) periods. The study looks at whether the impact of the COVID-19 pandemic was uniform across ownership types and size classes. The empirical findings suggest that the Indian banking system was resilient and withstood the immediate impact of the COVID-19 pandemic. During the study period, however, the large and medium-sized banks experienced some efficiency losses. By and large, regardless of bank group, banks have shown resilience to the shock of the global health pandemic and improvements in efficiency.     

Strategies to develop a sustainable and resilient vaccine supply chain in the context of a developing economy

Developing a vaccine supply chain (VSC) is an intricate process due to product perishability issues and cross-border supply complexities. On top of that, developing a pandemic-driven VSC is more challenging due to having significant operational, infrastructural, and policy-related disruptions. From the perspective of a developing economy such as Bangladesh, handling the global COVID-19 pandemic through the proper establishment of a VSC has been disrupted by a multitude of organizational, economic, and policy barriers. This has hindered the process of establishing a resilient VSC let alone ensuring the sustainability of the supply chain (SC). Therefore, this study strives to identify the key VSC strategies and their interrelationships under four groups: Intra-organizational, Inter-organizational, Legislative, and Environmental, based on previous literature and the expert opinions of industrial practitioners and policymakers. 20 strategies are ranked, and their causal relationships are discussed using the fuzzy DEMATEL method. This study utilizes the fuzzy set theory to deal with the vagueness of human beings' perceptions, and the DEMATEL method to form a structural model to find out the cause (influencing and independent) and effect (influenced and dependent) relationships among different strategies. The outcome of this study shows that ‘developing local production facilities for vaccines’, ‘creating extensive governmental policy to ensure efficient distribution of vaccines’, ‘ensuring sustainable investment in vaccine manufacturing and distribution’, ‘integrating advanced data analytics for robust and resilient demand prediction’ and ‘promoting public-private-people partnership for sustainable investment’ are the most prominent strategies. The findings provide stakeholders and policymakers with a practical framework for developing a sustainable VSC prepared for any virus outbreak, such as COVID-19, while also achieving the Sustainable Development Goals (SDGs).     

The COVID-19 crisis: A public choice view

Many observers have been puzzled by the sight of otherwise freedom-loving citizens consenting to the stripping of their civil rights and the massive budgetary expansion of their governments in response to the COVID-19 pandemic. Conversely, governments who ‘kept their cool’ such as those of Brazil and Sweden were heavily criticised by the Western media. Adopting James Buchanan's contractarian approach, this article seeks to model how the interplay between citizens and their government is affected by a health crisis. Citizens' increased willingness to pay for improved control of risks is found to play a major role.     

The COVID-19 Pandemic and Sovereign Bond Risk

Governments around the world are tackling the COVID-19 pandemic with a mix of public health, fiscal, macroprudential, monetary, and/or market-based policies. We assess the impact of the pandemic in Europe on sovereign CDS spreads using an event study methodology. We find that a higher number of cases and deaths and public health containment responses significantly increase the uncertainty among investors in European government bonds. Other governmental policies magnify the effect in the short run as supply chains are disrupted. Moreover, an increased debt-to-GDP ratio significantly boosts the cumulative abnormal change of CDS spreads, which indicates that investors are concerned about countries that are too indebted and thus have a limited capacity to intervene and provide fiscal stimuli and emergency fiscal packages to businesses and households.     

Latent social distancing: Identification,causes and consequences

It is not directly observable how effectively a society practices social distancing during the COVID-19 pandemic. This paper proposes a novel and robust methodology to identify latent social distancing at the country level. We extend the Susceptible-Exposed-Infectious-Recovered-Deceased (SEIRD) model with a time-varying, country-specific distancing term, and derive the Model-Inferred DIStancing index (MIDIS) for 120 countries using readily available epidemiological data. The index is not sensitive to measurement errors in epidemiological data and to the values assigned to model parameters. The evolution of MIDIS shows that countries exhibit diverse patterns of distancing during the first wave of the COVID-19 pandemic—a persistent increase, a trendless fluctuation, and an inverted U are among these patterns. We then implement regression analyses using MIDIS and obtain the following results: First, MIDIS is strongly correlated with available mobility statistics, at least for high income countries. Second, MIDIS is also strongly associated with (i) the stringency of lockdown measures (governmental response), (ii) the cumulative number of deceased persons (behavioral response), and (iii) the time that passed since the first confirmed case (temporal response). Third, there is statistically significant regional variation in MIDIS, and more developed societies achieve higher distancing levels. Finally, MIDIS is used to explain output losses experienced during the pandemic, and it is shown that there is a robust positive relationship between the two, with sizable economic effects.     

Using trust-based philanthropy with community-based organizations during the COVID-19 pandemic

Community-based organizations (CBOs) fill a critical role in acting as public health partners and trusted resources for their communities, especially in an emergency. The CDC Foundation, an independent, nonprofit organization, used trust-based philanthropy to manage more than 110 COVID-19 grants focused on equitable vaccine information, outreach, and access. The CDC Foundation team uses a trust-based philanthropy paradigm by applying five out of six of the grantmaking practices: do the homework; simplify and streamline paperwork; be transparent and responsive; solicit and act on feedback; and offer support beyond the check. By applying trust-based philanthropy practices, the CDC Foundation is empowering CBOs through flexible grant management and more equitable power dynamics as grantee and grantor. This has been essential to CBOs in their efforts of tackling health inequities during the COVID-19 pandemic and improving community resilience. Lessons learned will inform future collaborations with CBOs where the power dynamics are shared.     

An extended picture fuzzy multicriteria group decision analysis with different weights: A case study of COVID-19 vaccine allocation

The high contagion rates of COVID-19 and the limited amounts of vaccines forced public health authorities to develop vaccinations strategies for minimizing mortality, avoiding the collapse of health care infrastructure, and reducing their negative impacts to societies and economies. We propose a Multi Criteria Group Decision Making for prioritizing a set of COVID-19 vaccination alternatives, under a picture fuzzy environment, where the weights for Decisions Experts (DE) and criteria are unknown. A panel of six DEs assess six criteria for prioritizing four groups for vaccination. The weights for DE and criteria are handled in the form of fuzzy sets. Three types of weights are calculated: subjective, objective, and mixture weights.According to our results, three out of the six criteria hold 60% of the strategic importance: 1) allocation and distribution, 2) COVID-19 strains and 3) capabilities and infrastructures. However, persons with comorbidities became the group with the highest priority, followed by essential workers, women, and adults older than 40 years. Governments, decision makers, and policy makers can find rigorous scientific evidence for articulating effective vaccinations campaigns from this work, and contribute to minimize undesired outputs, such as high mortality rates or collapse of hospitals.     

Leveraging multi-tier healthcare facility network simulations for capacity planning in a pandemic

The COVID-19 pandemic has placed severe demands on healthcare facilities across the world, and in several countries, makeshift COVID-19 centres have been operationalised to handle patient overflow. In developing countries such as India, the public healthcare system (PHS) is organised as a hierarchical network with patient flows from lower-tier primary health centres (PHC) to mid-tier community health centres (CHC) and downstream to district hospitals (DH). In this study, we demonstrate how a network-based modelling and simulation approach utilising generic modelling principles can (a) quantify the extent to which the existing facilities in the PHS can effectively cope with the forecasted COVID-19 caseload; and (b) inform decisions on capacity at makeshift COVID-19 Care Centres (CCC) to handle patient overflows. We apply the approach to an empirical study of a local PHS comprising ten PHCs, three CHCs, one DH and one makeshift CCC. Our work demonstrates how the generic modelling approach finds extensive use in the development of simulations of multi-tier facility networks that may contain multiple instances of generic simulation models of facilities at each network tier. Further, our work demonstrates how multi-tier healthcare facility network simulations can be leveraged for capacity planning in health crises.     

Prevention and mitigation of epidemics: Biodiversity conservation and confinement policies

This paper presents a first model integrating the relation between biodiversity loss and zoonotic pandemic risks in a general equilibrium dynamic economic set-up. The occurrence of pandemics is modeled as Poissonian leaps in economic variables. The planner can intervene in the economic and epidemiological dynamics in two ways: first (prevention), by deciding to conserve a greater quantity of biodiversity to decrease the probability of a pandemic occurring, and second (mitigation), by reducing the death toll through a lockdown policy, with the collateral effect of affecting negatively labor productivity. The policy is evaluated using a social welfare function embodying society’s risk aversion, aversion to fluctuations, degree of impatience and altruism towards future generations. The model is explicitly solved and the optimal policy described. The dependence of the optimal policy on natural, productivity and preference parameters is discussed. In particular the optimal lockdown is more severe in societies valuing more human life, and the optimal biodiversity conservation is larger for more “forward looking” societies, with a small discount rate and a high degree of altruism towards future generations. Moreover, societies accepting a large welfare loss to mitigate the pandemics are also societies doing a lot of prevention. After calibrating the model with COVID-19 pandemic data we compare the mitigation efforts predicted by the model with those of the recent literature and we study the optimal prevention–mitigation policy mix.     

An analysis of the thematic evolution of ageing and healthcare expenditure using word embedding: A scoping review of policy implications

Thanks to the advances in public health and medical sciences, the increasing of elderly has become a structural phenomenon in Europe and the rest of the World. This demographic age shift highlighted severe doubts about the sustainability of healthcare systems which see adult people as a burden rather than, if they are healthy and active, as an advantage for a country’s economic development. Safeguarding older people from infections is crucial, but supporting them during health emergencies is even more critical. Older adults, for example, became more at risk of death during the COVID-19 pandemic. Thus, the balance previously achieved between age-related diseases and healthy quality of life went under higher pressure. As a result, the potential impact of ageing on healthcare expenditure is increasingly debated. Starting from this background, we propose a bibliometric study based on word embedding techniques to identify the drivers that could influence this relationship and track their evolution in the health policy debate. The main findings of our research underline that given the upward impact on the growth in health spending due to population ageing, policies oriented to improve their access to health services through new technologies could better meet the elderly needs, moderating the cost growth. Protecting the health of older adults represents, in fact, a challenge for governments as well as proof of the quality of health systems management, especially during severe outbreaks such as the one caused by the coronavirus.     

One crisis,different paths to supply resilience: The case of ventilator procurement for the COVID-19 pandemic

This research explores supply resilience through an equifinality lens to establish how buying organizations impacted differently by the same extreme event can strategize and all successfully secure supply. We conduct case study research and use secondary data to investigate how three European governments sourced for ventilators during the first wave of COVID-19. The pandemic had an unprecedented impact on the ventilator market. It disrupted already limited supply and triggered a demand surge. We find multiple paths to supply resilience contingent on redundant capacity and local sourcing options at the pandemic's onset. Low redundancy combined with limited local sourcing options is associated with more diverse strategies and flexibility. The most notable strategy is spurring supplier innovation by fostering collaboration among actors in disparate industries. High redundancy combined with multiple local sourcing options is associated with more focused strategies and agility. One (counter-intuitive) strategy is the rationalization of the supply base.     

Building resilience for sustainability of MSMEs post COVID-19 outbreak: An Indian handicraft industry outlook

The handicraft business constitutes concept selling rather than mere product selling, which is highly dependent on demand. Handicrafts' Micro Small and Medium Enterprises (MSMEs) have an expanding market in developed countries. The impact of the pandemic on this industry is severe due to the industry's informal nature and seasonal demand. The survival and resilience of these handicraft MSMEs face many challenges in the post-COVID-19 outbreak. The focus of the present study is to understand and analyze the key challenges for building resilience in handicraft MSMEs by scrutinizing the existing literature and interactions with stakeholders. EFA and the Grey DEMATEL approach are used to analyze the challenges for the adoption of resilience. EFA is used to categorize the challenges into various dimensions. The study has divided the challenges for the inclusion of resilience into survivable, sustainable, and viable categories using EFA to plan for short- and long-term business growth. Grey DEMATEL is being utilized for understanding these contextual relationships for each resilience dimension. Grey systems theory is a methodology that enables the incorporation of improbability and vagueness into the analysis. Findings of the study revealed the influencing challenges for each of the dimensions such as competition from machine-made products, insufficient government support and incentives for export, and inefficient managerial concern and response to internationalization as the prominent challenges. The results of this study illustrate the causal relationships amongst the identified resilience challenges to the various stakeholders. These findings offer practical insights for the government to allocate resources and impose measures to ensure resilience, as well as understanding the cause-effect relationship. Managerial implications and Policy insights for building the resilience of handicraft MSMEs are discussed in detail.     

Impacts of COVID-19 on global stock sectors: Evidence from time-varying connectedness and asymmetric nexus analysis

In this paper, we analyze the impact of the COVID-19 crisis on global stock sectors from two perspectives. First, to measure the effect of the COVID-19 on the volatility connectedness among global stock sectors in the time–frequency domain, we combine the time-varying connectedness and frequency connectedness method and focus on the total, directional, and net connectedness. The empirical results indicate a dramatic rise in the total connectedness among the global stock sectors following the outbreak of COVID-19. However, the high level of the total connectedness lasted only about two months, representing that the impact of COVID-19 is significant but not durable. Furthermore, we observe that the directional and net connectedness changes of different stock sectors during the COVID-19 pandemic are heterogeneous, and the diverse possible driving factors. In addition, the transmission of spillovers among sectors is driven mainly by the high-frequency component (short-term spillovers) during the full sample time. However, the effects of the COVID-19 outbreak also persisted in the long term. Second, we explore how the changing COVID-19 pandemic intensity (represented by the daily new COVID-19 confirmed cases and the daily new COVID-19 death cases worldwide) affect the daily returns of the global stock sectors by using the Quantile-on-Quantile Regression (QQR) methodology of Sim and Zhou (2015). The results indicate the different characteristics in responses of the stock sectors to the pandemic intensity. Specifically, most sectors are severely impacted by the COVID-19. In contrast, some sectors (Necessary Consume and Medical & Health) that are least affected by the COVID-19 pandemic (especially in the milder stage of the COVID-19 pandemic) are those that are related to the provision of goods and services which can be considered as necessities and substitutes. These results also hold after several robustness checks. Our findings may help understand the sectoral dynamics in the global stock market and provide significant implications for portfolio managers, investors, and government agencies in times of highly stressful events like the COVID-19 crisis.     

How have the dependence structures between stock markets and economic factors changed during the COVID-19 pandemic?

This study investigates how the dependence structures between stock markets and economic factors have changed during the COVID-19 pandemic using the dynamic model averaging approach. A series of economic factors such as commodity markets, cryptocurrency, monetary policy, international capital flows, and market uncertainty indices are considered. We find that the importance of economic variables and the sign and size of their coefficients are significantly different from those before the COVID-19 pandemic. The stock markets are most influenced by economic factors during the COVID-19 outbreak.