A new vaccine supply chain network under COVID-19 conditions considering system dynamic: Artificial intelligence algorithms

With the discovery of the COVID-19 vaccine, what has always been worrying the decision-makers is related to the distribution management, the vaccination centers' location, and the inventory control of all types of vaccines. As the COVID-19 vaccine is highly demanded, planning for its fair distribution is a must. University is one of the most densely populated areas in a city, so it is critical to vaccinate university students so that the spread of this virus is curbed. As a result, in the present study, a new stochastic multi-objective, multi-period, and multi-commodity simulation-optimization model has been developed for the COVID-19 vaccine's production, distribution, location, allocation, and inventory control decisions. In this study, the proposed supply chain network includes four echelons of manufacturers, hospitals, vaccination centers, and volunteer vaccine students. Vaccine manufacturers send the vaccines to the vaccination centers and hospitals after production. The students with a history of special diseases such as heart disease, corticosteroids, blood clots, etc. are vaccinated in hospitals because of accessing more medical care, and the rest of the students are vaccinated in the vaccination centers. Then, a system dynamic structure of the prevalence of COVID -19 in universities is developed and the vaccine demand is estimated using simulation, in which the demand enters the mathematical model as a given stochastic parameter. Thus, the model pursues some goals, namely, to minimize supply chain costs, maximize student desirability for vaccination, and maximize justice in vaccine distribution. To solve the proposed model, Variable Neighborhood Search (VNS) and Whale Optimization Algorithm (WOA) algorithms are used. In terms of novelties, the most important novelties in the simulation model are considering the virtual education and exerted quarantine effect on estimating the number of the vaccines. In terms of the mathematical model, one of the remarkable contributions is paying attention to social distancing while receiving the injection and the possibility of the injection during working and non-working hours, and regarding the novelties in the solution methodology, a new heuristic method based on a meta-heuristic algorithm called Modified WOA with VNS (MVWOA) is developed. In terms of the performance metrics and the CPU time, the MOWOA is discovered with a superior performance than other given algorithms. Moreover, regarding the data, a case study related to the COVID-19 pandemic period in Tehran/Iran is provided to validate the proposed algorithm. The outcomes indicate that with the demand increase, the costs increase sharply while the vaccination desirability for students decreases with a slight slope.     

新冠疫情背景下芜湖市社区零售供应链调查研究

本文基于新冠肺炎疫情的背景,对安徽省芜湖市社区居民商品采购情况和商家零售情况进行调查研究,通过调查发现芜湖市社区零售存在零售模式传统、应急供应能力弱、产品质量参差不齐等问题,进而提出从发挥社区团购渠道优势、稳定供应商、实现商品溯源以及加强数字化供应链建设等方面措施,减轻疫情对社区零售供应链可持续运营的不利影响,力求提高...     

A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study

In uncertain circumstances like the COVID-19 pandemic, designing an efficient Blood Supply Chain Network (BSCN) is crucial. This study tries to optimally configure a multi-echelon BSCN under uncertainty of demand, capacity, and blood disposal rates. The supply chain comprises blood donors, collection facilities, blood banks, regional hospitals, and consumption points. A novel bi-objective Mixed-Integer Linear Programming (MILP) model is suggested to formulate the problem which aims to minimize network costs and maximize job opportunities while considering the adverse effects of the pandemic. Interactive possibilistic programming is then utilized to optimally treat the problem with respect to the special conditions of the pandemic. In contrast to previous studies, we incorporated socio-economic factors and COVID-19 impact into the BSCN design. To validate the developed methodology, a real case study of a Blood Supply Chain (BSC) is analyzed, along with sensitivity analyses of the main parameters. According to the obtained results, the suggested approach can simultaneously handle the bi-objectiveness and uncertainty of the model while finding the optimal number of facilities to satisfy the uncertain demand, blood flow between supply chain echelons, network cost, and the number of jobs created.     

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).     

Improving resilience of the healthcare supply chain in a pandemic: Evidence from Europe during the COVID-19 crisis

The severe scarcity of critical medical supplies caused by the COVID-19 pandemic led to considerable procurement challenges in the healthcare supply chain (HCSC). As ensuring the availability of such supplies during disruptions is critical, the debate on how to increase supply chain resilience in healthcare has gained new momentum. We present empirical evidence from a multi-tier case study spanning nine European medical supplies manufacturers and hospital groups. Based on the resource dependence theory, we investigated procurement-related strategies to improve medical supplies availability. We conducted semi-structured interviews with 39 procurement and supply chain management experts and derived seven propositions on buffering and bridging approaches for managing evolving resource dependencies and thereby strengthening supply chain resilience in a pandemic. Overall, we confirm the resource dependence theory's applicability for explaining companies' mitigation measures in a pandemic disruption. We find that bridging measures within the healthcare supply base, such as offering procurement support for suppliers or leveraging long-term buyer-supplier relationships, are more effective for securing medical supplies than buffering measures. Complementing bridging with buffering, such as extended upstream procurement or resource sharing among hospitals, can lead to superior risk mitigation as capacities of the present supplier base may not suffice. Furthermore, we extend the resource dependence theory by showing that the severity of disruptions caused by a pandemic triggers new forms of buffering external to the HCSC. Both traditional and new buffering measures establish novel flows of medical supplies in the HCSC that can enable higher supply security in a pandemic.     

Gaining from disorder: Making the case for antifragility in purchasing and supply chain management

The purchasing and supply chain management (P&SCM) discipline assumes that supply chains are fragile systems, hence taking a “negative” approach toward disorder. Building on Taleb’s concept of antifragility—the ability to gain from disorder rather than avoiding it—, we challenge this traditional assumption. The COVID-19 pandemic has revealed that some companies were indeed able to gain from disorder, whereas some of those that focused too much on robustness and resilience lost ground. Building robust and resilient supply chains may no longer be enough to thrive in today’s highly volatile business world. This article sparks a new debate by introducing antifragility to the P&SCM literature and provides new directions for future research.     

Impact of epidemic outbreaks (COVID-19) on global supply chains: A case of trade between Turkey and China

COVID-19 has negative impacts on supply chain operations between countries. The novelty of the study is to evaluate the sectoral effects of COVID-19 on global supply chains in the example of Turkey and China, considering detailed parameters, thanks to the developed System Dynamics (SD) model. During COVID-19 spread, most of the countries decided long period of lockdowns which impacted the production and supply chains. This had also caused decrease in capacity utilizations and industrial productions in many countries which resulted with imbalance of maritime trade between countries that increased the freight costs. In this study, cause and effect relations of trade parameters, supply chain parameters, demographic data and logistics data on disruptions of global supply chains have been depicted for specifically Turkey and China since China is the biggest importer of Turkey. Due to this disruption, mainly exports from Turkey to China has been impacted in food, chemical and mining sectors. This study is helpful to plan in which sectors; the actions should be taken by the government bodies or managers. Based on findings of this study, new policies such as onshore activities should consider to overcome the logistics and supply chain disruptions in global supply chains. This study has been presented beneficial implications for the government, policymakers and academia.     

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.     

The COVID-19 pandemic uncertainty,investor sentiment,and global equity markets: Evidence from the time-frequency co-movements

We use daily data of the Google search engine volume index (GSVI) to capture the pandemic uncertainty and examine its effect on stock market activity (return, volatility, and illiquidity) of major world economies while controlling the effect of the Financial and Economic Attitudes Revealed by Search (FEARS) sentiment index. We use a time–frequency based wavelet approach comprising wavelet coherence and phase difference for our empirical assessment. During the early spread of the COVID-19, our results suggest that pandemic uncertainty, and FEARS sentiment strongly co-move, and increased pandemic uncertainty leads to pessimistic investor sentiment. Furthermore, our partial wavelet analysis results indicate a synchronization relationship between pandemic uncertainty and stock market activities across G7 countries and the world market. Our results are robust to the inclusion of alternative pandemic fear measure in the form of equity market volatility infectious disease tracker. The pandemic uncertainty and associated sentiment implications could be one plausible reason for increased volatility and illiquidity in the market, and hence, policymakers should look upon this issue for the financial market stability perspective.     

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.     

Getting back into the swing of things: The adaptive path of purchasing and supply management in enhancing supply chain resilience

The COVID-19 crisis posed significant challenges to global supply chains (SCs) and exposed their vulnerability to disruption. As SCs have evolved into complex structures comprising a multitude of globally dispersed companies that collaborate closely with one another, purchasing and supply management (PSM) have played a key role in addressing the crisis. The existing PSM measures for increasing supply chain resilience (SCRES) were stress tested and it became evident that these methods are applicable only to a limited extent due to their static perspective and their lack of a network character. Thus, this paper examines the role of PSM by identifying implemented response measures. By conducting 40 semi-structured interviews with experts from original equipment manufacturers and first-tier suppliers in the German automotive industry, a comprehensive overview of the industry was obtained. To reflect the network nature of the industry and the adaptive path of PSM, the data analysis is framed by resource dependence theory and the adaptive cycle approach. The results of the study are 25 response measures of PSM to enhance SCRES, categorized into three waves of measures: initial measures upon the occurrence of the disruption, temporary measures during the disruption, and post-disruption measures. In this way, the study contributes to the existing literature by demonstrating that PSM takes on a major role in increasing resilience by implementing diverse response measures. In addition, the study shows that PSM follows the path of an adaptive cycle, and that after the disruption and the initial and temporary measures, PSM adapts, which is reflected in the post-disruption measures. For practitioners, the study provides a list of response measures to increase resilience that can be used to review existing measures or implement new ones.     

Adaptive market hypothesis: The story of the stock markets and COVID-19 pandemic

Since the level of markets’ information efficiency is key to profiteering by strategic players, Shocks; such as the COVID-19 pandemic, can play a role in the nature of markets’ information efficiency. The martingale difference and conditional heteroscedasticity tests are used to evaluate the Adaptive form of market efficiency for four (4) major stock market indexes in the top four affected economies during the COVID-19 pandemic (USA, Brazil, India, and Russia). Generally, based on the martingale difference spectral test, there is no evidence of a substantial change in the levels of market efficiency for the US and Brazilian stock markets in the short, medium, and long term. However, in the long term, the Indian stock markets became more information inefficient after the coronavirus outbreak while the Russian stock markets become more information efficient. Intuitively, these affect the forecastability and predictability of these markets’ prices and/or returns. Thereby, informing the strategic and trading actions of stock investors (including arbitrageurs) towards profit optimization, portfolio asset selection, portfolio asset adjustment, etc. Similar policy implications are further discussed.     

Linking forward and reverse supply chain investments: The role of business uncertainty

This paper explores managerial efforts in reverse supply chains (RSC), where the focus is on the capture and exploitation of used products and materials. The RSC can potentially reduce negative environmental impacts of extracting virgin raw materials and waste disposal. If so, investment in the reverse supply chain should not be made in isolation, but instead must be integrated with investments selected to improve the forward supply chain. After defining and operationalizing these constructs, a survey of plant managers was used to empirically assess the linkages between supply chain investments, organizational risk propensity (i.e., willingness to take risk) and business uncertainty. Reverse supply chain investment had two primary dimensions: reconditioning (i.e., high-value recovery) and recycling and waste management (i.e., low- or no-value recovery). Ongoing investment in the forward supply chain was significantly related to investment in recycling and waste management, but not to investment in reconditioning. Moreover, risk propensity was found to mediate the relationship between the external business uncertainty and investment in the forward and reverse supply chain.     

Business strategy for sustainable development: Impact of life cycle inventory and life cycle impact assessment steps in supply chain design and planning

Sustainability reporting has become a central instrument in displaying a company's strategy and engagement with a more sustainable society. Life cycle assessment (LCA) is an important tool in this context as it is aimed to analyze the entire life cycle of the product/service, instead of focusing on one focal firm. However, the lack of standardized guidelines in its application raises questions regarding the usefulness and validity of results. This study contributes to the improvement of sustainability reporting through the identification of the uncertainty sources in life cycle methodologies that have the biggest impact in the definition of business and environmental strategies, exploring a supply chain‐oriented analysis. The focus is on life cycle inventory (LCI) and life cycle impact assessment (LCIA). A multiobjective optimization‐based methodology is applied to a supply chain case study in the pulp and paper industry. Environmental and economic objectives are considered. Results show that different LCIA methods and different normalization data sets result in significantly different business and environmental strategies. However, different system models and cultural perspectives at the LCI step and variations in the characterization factors tend to lead to the same decisions. Important insights are gained regarding the impact of nonstandardized analysis of the application of LCA in supply chain design and planning decisions and consequently on business strategy definition and sustainability reporting. Furthermore, the importance of operations research methods to improve LCA‐based studies and of bridging the gap between LCA and supply chain management bodies of knowledge is highlighted in this work.