Supply chain analytics and post-pandemic performance: mediating role of triple-A supply chain strategies

PurposeThe abrupt outbreak of coronavirus disease (COVID-19) hit every nation in 2020–2021, causing a worldwide pandemic. The worldwide COVID-19 epidemic, described as a "black swan”, has severely disrupted manufacturing firms' supply chain. The purpose of this study is to investigate how supply chain data analytics enable the effective deployment of agility, adaptability and alignment (3As) strategies, resulting in improving post-COVID disruption performance. It also analyses the indirect effect of supply chain data analytics on disruption performance through the 3As supply chain strategies.Design/methodology/approachThe hypothesis and theoretical framework were tested using a questionnaire survey. The authors employed structural equation modelling through the SMART PLS version 3.2.7 to analyse data from 163 textile firms located in Pakistan.FindingsThe results revealed that the supply chain data analytics contributed positively and significantly to the agility and adaptability, while all 3As supply chain strategies impacted the PPERF substantially. Further, the connection between supply chain data analytics (SCDA) and disruption performance has substantially been influenced through 3As supply chain strategies.Practical implicationsThe results imply that in the event of low likelihood, high effect disruptions, managers and decision-makers should focus their efforts on integrating data analytics capabilities with 3As supply chain policies to ensure long-term company success.Originality/valueThis research sheds fresh light on the importance of data analytics in effectively implementing 3As strategies for sustaining company performance amid COVID-19 disruptions.

Ethical moments and institutional expertise in UK Government COVID-19 pandemic policy responses: where, when and how is ethical advice sought?

Background:The emergency response to the COVID-19 pandemic has required a rapid acceleration of policy decision making, and raised a wide range of ethical issues worldwide, ranging from vaccine prioritisation, welfare and public health ‘trade-offs', inequalities in policy impacts, and the legitimacy of scientific expertise.Aims and objectives:This paper explores the legacy of the pandemic for future science-advice-policy relationships by investigating how the UK government's engagement with ethical advice is organised institutionally. We provide an analysis of some key ethical moments in the UK Government response to the pandemic, and institutions and national frameworks which exist to provide ethical advice on policy strategies.Methods:We draw on literature review, documentary analysis of scientific advisory group reports, and a stakeholder workshop with government ethics advisors and researchers in England.Findings:We identify how particular types of ethical advice and expertise are sought to support decision making. Contrary to a prominent assumption in the extensive literature on ‘governing by expertise', ethical decisions in times of crisis are highly contingent.Discussion and conclusions:The paper raises an important set of questions for how best to equip policymakers to navigate decisions about values in situations characterised by knowledge deficits, complexity and uncertainty. We conclude that a clearer pathway is needed between advisory institutions and decision makers to ensure ethically-informed debate.

Framing blockchain-integrated digital twins for emergent healthcare management at local and city levels: A proof of concept

It has been witnessed that digital technology has the potential to improve the efficiency of emergent healthcare management in COVID-19, which however has not been widely adopted due to unclear definition and configuration. This research aims to propose a proof of concept of digital twins for emergent healthcare management through configuring the cyber and functional interdependencies of healthcare systems at local and city levels. Critical interdependencies of healthcare systems have been firstly identified at both levels, then the information and associated cyber and functional interdependencies embedded in seven critical hospital information systems (HISs) have been identified and mapped. The proposed conceptual digital twin-based approach has been then developed for information coordination amongst these critical HISs at both local and city levels based on permissioned blockchain to (1) integrate and manage the information from seven critical HISs, and further (2) predict the demands of medical resources according to patient trajectory. A case study has been finally conducted at three hospitals in London during the COVID-19 period, and the results showed that the developed framework of blockchain-integrated digital twins is a promising way to provide more accurate and timely procurement information to decision-makers and can effectively support evidence-based decisions on medical resource allocation in the pandemic. © 2023 ICE Publishing: All rights reserved.

Do Automated Market Makers in DeFi Ecosystem Exhibit Time-Varying Connectedness during Stressed Events?

We investigate the connectedness of automated market makers (AMM) that play a pivotal role in liquidity and ease of operations in the decentralized exchange (DEX). By applying the TVP-VAR model, our findings show higher level of connectivity during periods of turmoil (such as Delta, Omicron variants of SARS-Covid, and the Russia Ukraine conflict). Furthermore, risk transmission/reception is found to be independent of the platform on which they typically run (Ethereum based AMMs were both emitters as well as receivers). Pancake (a Binance based AMM) and Perpetual Protocol (Ethereum based AMM) emerged as moderate to high receivers of risk transmission, whereas all of the other AMMs, including Ethereum, were found to be risk emitters at varying degrees. We argue that AMMs typically depend on the underlying smart contracts. If the contract is flexible, AMMs can vary (either receiver or emitter), otherwise AMMs behave in tandem. © 2023 by the authors.

COVID-19 SEIAR Model with Sensitivity Analysis

Beside the unexpected toll of mortality and morbidity caused by COVID-19 worldwide, low- and middle-income countries are more suffering from the devastating issues on economic and social life. This disease has fostered mathematical modelling. In this paper, a SEIAR mathematical model is presented to illustrate how policymakers may apply efficient strategies to end or at least to control the devastating wide spread of COVID-19. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Digitalization of the supply chain: transformation factors

PurposeThere is an increasing interest in the supply chain's digitalization, yet the topic is still in the preliminary stages of academic research. The academic literature has no consensus and is still limited to research assessing the supply chain's digitalization of organizations. This study aims to explore the supply chain digitalization drivers to understand the emerging phenomena. More specifically, the authors devised from the literature the most common factors in assessing the readiness in scaling supply chain digitalization.Design/methodology/approachThis study followed a five-phased systematic literature review (SLR) methodology in this research: designing, analyzing, conducting, writing and assessing the quality of the review. The SLR is beneficial for justifying future research regardless of the complex process that requires dealing with high-level databases, information filtering and relevancies of the content. Through analysis of 347 titles and s and 40 full papers, the authors showed and discussed the supply chain digitalization: transformation factors.FindingsThe results generated three main themes: technology, people and processes. The study also generated ten subthemes/primary drivers for assessing the readiness for supply chain digitalization in organizations: IT infrastructure, cybersecurity systems, digitalization reskilling and upskilling, digitalization culture, top management support, digitalization and innovation strategy, integrated supply chain, digital innovation management, big data management and data analytics and government regulations. The importance of each factor was discussed, and future research agenda was presented.Research limitations/implicationsWhile the key drivers of the supply chain digitalization were identified, there is still a need to study the statistical correlation to confirm the interrelationships among factors. This study is also limited by the articles available in the databases and content extraction.Practical implicationsThis study supports decision-makers in understanding the critical drivers in digitalizing the supply chain. Once these factors are studied and comprehended, managers and decision-makers could better anticipate and allocate the proper resources to embark on the digitalization journey and make informed decisions.Originality/valueThe digitalization of the supply chain is more critical nowadays due to the global disruptions caused by the Coronavirus (COVID-19) pandemic and the surge of organizations moving toward the digital economy. There is a gap between the digital transformation pilot studies and implementation. The themes and factors unearthed in this study will serve as a foundation and guidelines for further theoretical research and practical implications.

The effect of increasing health disaster risk and public spending on economy conditions: a DSGE perspective

PurposeThe main motivation of the present study is to understand the severity of the effect of health shock on Iran's oil economy and analyze the role of government under these conditions.Design/methodology/approachDynamic stochastic general equilibrium (DSGE) models can show the precise interactions between market decision-makers in the context of general equilibrium. Since the duration of the virus outbreak and its effect on the economy is not known, it is more appropriate to use these models.FindingsThe results of the survey of hands-on policies scenarios compared to the state of hands-off policy indicate that the effect of government expending shocks on the economy under pandemic disease conditions has much less feedback on macroeconomic variables.Originality/valueAs a proposed policy, it is recommended that the government play a stabilizing role under pandemic disease conditions.Key messages There is no study regarding health shock and its economic effects in Iran using DSGE models. Also, in foreign studies, the health shock in an oil economy has not been modeled.The general idea in the present study is how the prevalence of a pandemic infectious disease affects the dynamics of macroeconomic variables.In three different scenarios, according to the persistence of health disaster risk and the deterioration rate of health capital due to this shock, the model is simulated.In modeling pandemic diseases, quarantine hours are considered as part of the total time of individuals.According to the research findings, it is recommended that the government, as a policy-maker, play a stabilizing role under pandemic crises conditions.

COVID-19 and the Indoor Environment - observations from a joint National Academies of Engineering seminar series

The SARS-CoV-2 virus and its variants and COVID-19 disease have affected every aspect of society. The US National Academy of Sciences has been providing scientific insights and advice to aid policymakers and researchers in their quest to respond to the pandemic. Since 2020, it has produced numerous reports and workshop proceedings intended to integrate science into national preparedness and response decision-making, to explore lessons learned and best practices from previous preparedness and response efforts, and to consider strategies for addressing misinformation (NASEM, 2021). Among these was a 2021 symposium series that analyzed engineering's role in catalyzing COVID-19 response, recovery, and resilience, examining topics including the mitigation of exposure in public transit systems, engineering solutions to managing pathogens indoors, and the factors influence the transmission of infectious diseases in cities. Speaker presentations addressing these indoor environment topics are summarized here. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

COVID-19 and the Motorcycle Taxi Sector in Sub-Saharan African Cities: A Key Stakeholders' Perspective

This article assesses the impact of the COVID-19 outbreak on the urban motorcycle taxi (MCT) sector in Sub-Saharan Africa (SSA). MCToperators in SSA provide essential transport services and have shown ingenuity and an ability to adapt and innovate when responding to different challenges, including health challenges. However, policymakers and regulators often remain somewhat hostile toward the sector. The article discusses the measures and restrictions put in place to reduce the spread of COVID-19 and key stakeholders' perspectives on these and on the sector's level of compliance. Primary data were collected in six SSA countries during the last quarter of 2020. Between 10 and 15 qualitative interviews with key stakeholders relevant to the urban MCT sector were conducted in each country. These interviews were conducted with stakeholders based in the capital city and a secondary city, to ensure a geographically broader understanding of the measures, restrictions, and perspectives. The impact of COVID-19 measures on the MCT and motor-tricycle taxi sector was significant and overwhelmingly negative. Lockdowns, restrictions on the maximum number of passengers allowed to be carried at once, and more generally, a COVID-19-induced reduction in demand, resulted in a drop in income for operators, according to the key stakeholders. However, some key stakeholders indicated an increase in MCT activity and income because of the motorcycles' ability to bypass police and army controls. In most study countries measures were formulated in a non-consultative manner. This, we argue, is symptomatic of governments' unwillingness to seriously engage with the sector. © National Academy of Sciences: Transportation Research Board 2021.

LSTM-based Forecasting using Policy Stringency and Time-varying Parameters of the SIR Model for COVID-19

Accurate forecasting of the number of infections is an important task that can allow health care decision makers to allocate medical resources efficiently during a pandemic. Two approaches have been combined, a stochastic model by Vega et al. for modelling infectious disease and Long Short-Term Memory using COVID-19 data and government's policies. In the proposed model, LSTM functions as a nonlinear adaptive filter to modify the outputs of the SIR model for more accurate forecasts one to four weeks in the future. Our model outperforms most models among the CDC models using the United States data. We also applied the model on the Canadian data from two provinces, Saskatchewan and Ontario where it performs with a low mean absolute percentage error. © 2023 IEEE.

A fuzzy multi-objective decision-making model for global green supplier selection and order allocation under quantity discounts

The selection of potential suppliers has recently become a big challenge for the manufacturing industries due to the rapid spread of covid-19 and the escalating frequency of natural calamities such as earthquakes and floods. When decision-makers (DMs) consider quantity discounts from multiple sources, things get much more complicated. Although previous studies have looked at selecting suitable suppliers from economic and environmental aspects, no one has considered foreign transportation risks while evaluating the textile industry's global green suppliers. In this regard, for the first time, this study combines economic and environmental factors with the foreign transportation risk criterion to develop a holistic model for global green supplier selection and order allocation (SS&OA) in the textile industry under all-unit quantity discounts. Initially, the fuzzy analytical hierarchy process (FAHP) method is used to calculate the relative weights of the criteria. Second, a multi-objective linear programming (MOLP) model is developed to reduce the total procurement cost, quality rejection rate, delivery lateness rate, greenhouse gas emissions from product procurement, and foreign transportation risks. Subsequently, the developed MOLP model is transformed into a fuzzy compromise programming (FCP) model to obtain order allocation quantities among selected suppliers with their offered quantity discount rates. A real-life case study of the Pakistani textile industry is presented to validate the proposed methodology's applicability by determining the optimal order allocation quantities among multiple suppliers based on two decision-making attitudes of DMs (neutral and risk-averse). Finally, sensitivity and comparative analyses are carried out to guarantee that the proposed technique produces accurate and optimal solutions. The final results of the proposed methodology show that it can effectively manage data uncertainties during SS&OA compared to other existing approaches. The suggested integrated methodology's outcomes can assist the supplier organization in overcoming its current shortcomings and developing a long-term relationship with the buyer organization. © 2023 Elsevier Ltd

Data-driven Analysis of Remote Work in China during the COVID-19 Pandemic

This paper leverages online content to investigate the biggest impact of COVID-19 - remote work, by using China as a primary case study. Telecommuting has become popular since February 2020 primarily due to the pandemic, and people have been slowly returning to their office from May 2020. This study focuses on two time windows in the year 2020 to calculate the growth of different job sectors. Our results indicate the negative impact of teleworking in manufacturing industry, but shows that information technology-related industries are less affected by working from home. This paper also investigates the impact of COVID-19 on the stock market and discussed what plan of action the policy makers should take to provide a good economic environment for the country. In addition to the overall economic situation, we observed how the psychological situation of employees could affect their job performance, indirectly affecting the development of certain industry sectors. Therefore, misinformation in certain Chinese social media channels was also studied in this paper specifically examining the rumors and their latent topics. We believe that our work will initiate a dialogue between scientists, policy makers and government officials to consider the observations highlighted in this paper. © 2022 IEEE Computer Society. All rights reserved.

Moderating effect of government policy on the relationship between low-cost housing demand-supply gap and COVID-19 impact

Purpose: The COVID-19 impact across major sectors did not exempt the low-cost housing (LCH) sub-sector. This may have increased the existing LCH demand-supply gap, especially in developing countries such as Malaysia. Studies showed that government policy (GP) aids in mitigating COVID-19 impact on goods and services, including housing-related issues. However, there is an academic literature scarcity regarding GP on LCH demand-supply gap during the COVID-19 crisis in Malaysia. Hence, this study aims to investigate the moderating effect of GP on the relationship between LCH demand-supply gap and COVID-19 impact in Malaysia. Design/methodology/approach: The research utilised a quantitative method in collating the data from four major cities in Malaysia. SmartPLS was utilised to analyse the usable 305 questionnaires retrieved from respondents. Structuralist Theory supported the developed framework. Findings: Findings show that GP moderates the relationships between the LCH demand-supply gap and COVID-19 impact on Malaysia's low-income groups' (LIGs) homeownership delivery. It implies that the study's findings provide more understanding of issues influencing LCH demand-supply gap in the COVID-19 era via applying GP to mitigate the gap and improve homeownership for the disadvantaged. Practical implications: The study intends to stir policymakers toward formulating policies and programmes that will mitigate LCH demand-supply gap during the present and future pandemics. Originality/value: Besides the theoretical value of the developed model, policymakers can use the study's recommendations to mitigate future LCH demand-supply gaps during pandemics in developing countries using Malaysia as a case study. © 2023, Emerald Publishing Limited.

India's public transportation system: the repercussions of COVID-19

The COVID-19 pandemic has left scars on the Indian public transportation system. In order to regain its original momentum, policymakers will need to assess the barriers hindering the effectiveness of the public transportation sector. In this regard, this article analyzes the various factors affecting the public transportation sector in India and determines their interrelationships. The research is presented in three steps. First, we review the literature to identify the factors that affect the public transportation system in India. Next, we propose an integrated model of grey-DEMATEL and ANP, grey-DANP, to calculate the priority ranking and weight of the factors. The grey-DEMATEL method is used to find the interrelationships among the factors, while ANP determines the local and global weights of the factors to form a priority order. Then, we present the interrelationships in the form of influential relation maps. Furthermore, we provide a sensitivity analysis to enhance the credibility of our study. The paper reveals that governmental regulations are the most influential factors in India's public transportation system. The transportation authorities and policymakers must also focus on improving the financial stability and enhancing the customer's trust in the public transportation system. The framework provided in this paper can be applied to other countries where similar hindrances in the public transportation system have been caused by COVID-19. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Applying an Epidemiological Model to Evaluate the Propagation of Toxicity related to COVID-19 on Twitter

The prevalence of social media has increased the propagation of toxic behavior among users. Toxicity can have detrimental effects on users' emotion and insight and disrupt beneficial discourse. Evaluating the propagation of toxic content on social networks such as Twitter can provide the opportunity to understand the characteristics of this harmful phenomena. Identifying a mathematical model that can describe the propagation of toxic content on social networks is a valuable approach to this evaluation. In this paper, we utilized the SEIZ (Susceptible, Exposed, Infected, Skeptic) epidemiological model to find a mathematical model for the propagation of toxic content related to COVID-19 topics on Twitter. We collected Twitter data based on specific hashtags related to different COVID-19 topics such as covid, mask, vaccine, and lockdown. The findings demonstrate that the SEIZ model can properly model the propagation of toxicity on a social network with relatively low error. Determining an efficient mathematical model can increase the understanding of the dynamics of the propagation of toxicity on a social network such as Twitter. This understanding can help researchers and policymakers to develop methods to limit the propagation of toxic content on social networks. © 2022 IEEE Computer Society. All rights reserved.

Rapid Convergence: The Outcomes of Making PPE During a Healthcare Crisis

The U.S. National Institute of Health (NIH) 3D Print Exchange is a public, open-source repository for 3D printable medical device designs with contributions from clinicians, expert-amateur makers, and people from industry and academia. In response to the COVID-19 pandemic, the NIH formed a collection to foster submissions of low-cost, locally manufacturable personal protective equipment (PPE). We evaluated the 623 submissions in this collection to understand: what makers contributed, how they were made, who made them, and key characteristics of their designs. We found an immediate design convergence to manufacturing-focused remixes of a few initial designs affiliated with NIH partners and major for-profit groups. The NIH worked to review safe, effective designs but was overloaded by manufacturing-focused design adaptations. Our work contributes insights into: the outcomes of distributed, community-based medical making;the features that the community accepted as "safe"making;and how platforms can support regulated maker activities in high-risk domains. © 2023 Copyright held by the owner/author(s).

Leverage points to address climate change risk in destinations

Transformational system change is required to respond to the current climate emergency and the COVID-19 induced structural break presents an opportunity to progress such change. While the tourism industry accepts the need for change, how this may look like remains unclear. This article contributes to identifying pathways by presenting critical reflections on the research process and findings from a three-year research project on reducing climate change risk in Vanuatu. The approach is anchored in systems thinking and draws on the concept of leverage points. Seven points are identified for intervening in the tourism system to reduce climate change risk and achieve varying levels of systemic change. Each is explored in the context of Vanuatu before its broader relevance is discussed. The findings highlight the importance of engaging with deeper influences of risk and unsustainable system outcomes. This has implications for how decision-makers approach crisis management and what ‘tourism recovery' means, especially when considering that system resilience might stand in the way of more profound transformational change required to address long-term risks.Alternate :中文摘要为了应对当前的气候突发事件, 需要进行转变性的制度变革。新型冠状肺炎引发的结构性突破为推动这种变化提供了机会。虽然旅游业接受了有必要进行改变, 但这可能会变成什么样子仍然是未知数。该文通过对一项为期三年的关于减少瓦努阿图气候变化风险研究项目过程和结果的批判性反思, 提出对气候变化进行转变性制度变革的路径。本文方法以系统思维为基础, 并借鉴杠杆点的概念, 提出对旅游系统进行干预的七个要点, 以减少气候变化风险, 实现不同程度的系统性变化。每个要点都是先在瓦努阿图的范围内进行探讨, 然后再讨论其更广泛的启发意义。研究结果强调应对风险和不可持续系统的更深层次影响因素的重要性。该研究结果对决策者如何处理危机管理和理解"旅游业复苏”的意义有启发, 尤其当决策者考虑到系统的弹性可能会阻碍解决长远风险所需要的更深远的转变性变革。

Analysis of the relationship between bitcoin, oil prices, and the Dow Jones Industrial Average using a wavelet-based approach

This paper analyzes the correlation between bitcoin, oil price fluctuations and the DOW Jones Industrial Index in the time-frequency framework. Coherent wavelet method applied to recent daily data in the United States (1863 in total). Our research has several implications and supports for policy makers and asset managers. We find that oil prices lead the U.S. market at both low and high frequencies throughout the observation period. This result suggests that sanctions against Russia by a number of countries, including the U.S., are influencing oil prices, while oil remains a major source of systemic risk to the U.S. economy and economic uncertainty between the international level is exacerbated by tensions between Russia and Ukraine. © COPYRIGHT SPIE.

Research on Measurement and Evaluation of High-Quality Entrepreneurship: A Review and Synthesis Prospectus

How to measure and evaluate the quality of entrepreneurial activities is not only an important academic issue in the field of entrepreneurship research but also an important practical problem faced by economic policymakers, especially in the context of the global Covid-19 epidemic and the shift of China's economy from the entrepreneurship high-rate growth stage to the high-quality grow stage. In this paper, we explore the development process of defining and measuring the high-quality entrepreneurial activities, discuss and synthesize the various measurement index for identifying the high-quality entrepreneurship in a complex and uncertain context, concluding that measurement and evaluation of high-quality measurement index experiencing the process of single index to composite index with the consideration of impact of general entrepreneurship policy and specific environment, and also the measurement and evaluation more and more focused on antecedent of entrepreneurial activities which can effectively predict the high quality of entrepreneurial activities from the onset of new firms instead of consequence of entrepreneurial activities. At the end of the article, we propose three viewpoints: First, entrepreneurial quality can be measured using quantitative methods;second, there are limitations for the evaluation of high-quality entrepreneurial quality in practice;third, entrepreneurship indicators should be continuously updated with the accumulation of practice. © 2023 The authors and IOS Press.

The perspective of energy poverty and 1st energy crisis of green transition

The role of energy transition amidst the energy crisis and how policymakers can drive down emissions while focusing on energy security are critical. Given the geo-political situation, energy crisis volatility, energy shortage and climate change all affect the green transition and the short-term priorities for energy companies and policymakers. Energy security is not an isolated issue but has widespread implications as various sectors depend on energy supply to function properly. Governments around the world are faced with this trilemma, how to balance energy security with energy sustainability while also considering energy affordability. Sustainability has been in focus for about a decade. However, energy security is suddenly becoming one of the most important priorities that policymakers need to consider. Unfortunately, the renewable energy infrastructure is not yet ready to replace the growing volume of energy demand from hydrocarbon, which the world has been dependent on. This means, for now, a surge in energy generation through hydrocarbon to meet the existing energy demand deficit. However, it is important not to lose focus on the challenge of energy sustainability and climate change adaption and mitigation. Where trends like carbon capture and storage;solar, wind, hydro, green hydrogen, etc.;renewable energy infrastructure and integrations, with supply chain and engineering services consideration [in aspect for the growing market in this space] need better attention with regards to investment and full-scale implementation. This paper aims to analyze this 1st energy crisis of green transition with a priori on energy poverty with consideration of major influences and associated impacts. Furthermore, it proposes a specific framework for inclusive investigations, which considers the entire energy ecosystem with consideration of major influences, to enable the policymakers to better drive the green transition. This involves formulating energy policies that are not entirely conservative towards renewable energy sources but instead promote investments in both green and relatively more environmentally benign energy sources compared to high emission hydrocarbons. In this regard, this paper renders exhaustive prospects and recommendations. © 2023 Elsevier Ltd