How can collaboration deliver? A structurational approach to understanding collaboration process and effectiveness

This study examines how a collaboration's internal and external factors interact over time and how the interactions affect the collaboration's process and effectiveness. Using a process-oriented case study, we examine how a voluntary collaboration that had made marginal gains over several years demonstrated significant progress during the COVID-19 pandemic and civil unrest following the murder of George Floyd on May 25, 2020. Drawing on strong structuration theory, we explore the collaboration's internal efforts, changes in the broader environment, and the interplay between them. Our findings reveal that collaboration's internal efforts and external environment enable and constrain each other, which shapes the collaboration's process and effectiveness. Based on these findings, we contribute to a more nuanced understanding of the collaboration process and effectiveness by (1) using a strong structurational approach to demonstrate processual mechanics of connecting processes and structures in collaboration, and (2) highlighting the emergent nature of collaboration and the importance of learning and adaptability for an effective and sustainable collaboration.

Heat waves accelerate the spread of infectious diseases.

COVID-19 pandemic appeared summer surge in 2022 worldwide and this contradicts its seasonal fluctuations. Even as high temperature and intense ultraviolet radiation can inhibit viral activity, the number of new cases worldwide has increased to >78% in only 1 month since the summer of 2022 under unchanged virus mutation influence and control policies. Using the attribution analysis based on the theoretical infectious diseases model simulation, we found the mechanism of the severe COVID-19 outbreak in the summer of 2022 and identified the amplification effect of heat wave events on its magnitude. The results suggest that approximately 69.3% of COVID-19 cases this summer could have been avoided if there is no heat waves. The collision between the pandemic and the heatwave is not an accident. Climate change is leading to more frequent extreme climate events and an increasing number of infectious diseases, posing an urgent threat to human health and life. Therefore, public health authorities must quickly develop coordinated management plans to deal with the simultaneous occurrence of extreme climate events and infectious diseases.

Worry about COVID-19 and other extreme events amongst educators in Australia

The significant disruption of COVID-19 on schooling has heightened concerns about its impact on educators' wellbeing. The current study examined how educators' worry regarding the COVID-19 pandemic compared to their worry about other extreme events, such as natural disasters and critical incidents (a death or suicide of a child, young person, or colleague). Educators report that they were most worried about COVID-19. Educators working in preschools were more worried about COVID-19 and natural disasters than those in primary and secondary schools. However, worry regarding critical incidents increased with the age of students taught. Worry was influenced by socio-economic advantage (SEIFA), whereby educators working in higher SEIFA communities were less worried about natural disasters and critical incidents but shared similar levels of worry about COVID-19 as educators in lower SEIFA communities. With a better understanding about how different types of worry and levels of worry vary across different educator groups and different contexts, more effective supports can be developed and offered. [ FROM AUTHOR] Copyright of Australian Journal of Education (Sage Publications Ltd.) is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Knowledge Systems and Risk Management: Threat Lessons Learned from COVID-19 in 2020-21

The year 2020-21 has shown us that the likelihood of extreme events is greater than we would have expected. When organizational resources are stretched to their limits due to extreme events, they are also more vulnerable to cyber-attacks and knowledge risks. Based on the events that took place during the 2020-21 period, we identify five knowledge risks and categorize them as technical, behavioral, and legal risks. We identify possible controls to mitigate these knowledge risks: proper knowledge identification, guidelines for employee knowledge behavior, identification and evaluation of online communication channels, and risk re-assessment to knowledge. © 2022 IEEE Computer Society. All rights reserved.

A spatiotemporal decay model of human mobility when facing large-scale crises.

A common feature of large-scale extreme events, such as pandemics, wildfires, and major storms is that, despite their differences in etiology and duration, they significantly change routine human movement patterns. Such changes, which can be major or minor in size and duration and which differ across contexts, affect both the consequences of the events and the ability of governments to mount effective responses. Based on naturally tracked, anonymized mobility behavior from over 90 million people in the United States, we document these mobility differences in space and over time in six large-scale crises, including wildfires, major tropical storms, winter freeze and pandemics. We introduce a model that effectively captures the high-dimensional heterogeneity in human mobility changes following large-scale extreme events. Across five different metrics and regardless of spatial resolution, the changes in human mobility behavior exhibit a consistent hyperbolic decline, a pattern we characterize as "spatiotemporal decay." When applied to the case of COVID-19, our model also uncovers significant disparities in mobility changes-individuals from wealthy areas not only reduce their mobility at higher rates at the start of the pandemic but also maintain the change longer. Residents from lower-income regions show a faster and greater hyperbolic decay, which we suggest may help account for different COVID-19 rates. Our model represents a powerful tool to understand and forecast mobility patterns post emergency, and thus to help produce more effective responses.

Volatility Forecasting during Extreme Market Events Using the Mid Cap Share Index

The JSE underperformance in 2010 to 2019 as a consequence of a collapse in mid-cap share investments signified a high risk of investing in mid-cap companies. The outbreak of Covid-19 affected the optimal lambda and mid-cap share price returns during the analysis that was extended to 31 July 2020. For this purpose, the objective of the study is to forecast volatility at the end of day n-1 using the exponential weighted moving average and the general autoregressive conditional heteroscedasticity using the mid-cap share index (J201). Furthermore, the study aims to calculate the optimal lambda during the Covid-19 global pandemic. The models examined the negative relationship between share price returns and volatility during extreme events which led to fat tailed distribution of returns in share price returns. On December 2020 an unfavourable South African investment grade of negative BBB was assigned by Fitch Ratings and the days following the Covid-19 lockdown, share price returns plunged encouraging panic selling by risk averse investors.

Revealing the Impact of Extreme Events on Electricity Consumption in Brazil: A Data-Driven Counterfactual Approach

The electric grid is uniquely susceptible to extreme events through both power supply and consumption pathways. Extreme events - like heatwaves and droughts - are expected to increase in frequency and severity due to climate change and are already causing consequences on power system operations and stability. Additionally, non-climate related events like the COVID-19 pandemic have had dramatic impacts on energy consumption patterns globally. We apply modern machine learning methods to model electricity consumption in Brazil, one of the largest generators of hydropower, to better understand the consumption-side effects of extreme national and regional events. After training on 20 years of historical data, we verify an R2of 0.848 and a MAPE of 2.6% for our counterfactual model and use it to assess impacts of historical events on electricity consumption. We then discuss how this approach can be applied toward measuring energy system responsiveness and resiliency on present and future scenarios. © 2022 IEEE.

Extreme events and carbon emissions: What we could learn from decomposition of national- and sector-carbon emission

The lockdown policies related with the COVID-19 pandemic brings carbon emissions slump, but emissions potentially restore to increase as lockdown policies relaxed and the economy recovers. In this context, this study aims to explore the changes in carbon emissions and their underlying factors in the post-COVID-19 era from a national and sectoral perspective by drawing on the experience of carbon emissions before and after the 2008 global crisis. The latest extreme event and carbon emission trends might provide some implications for curbing potential emission rebound after the pandemic. The results indicate that, (i) developing countries like China and India still struggle with carbon reduction, which need more efforts made to control continuously increased carbon emission;(ii) energy intensity and economic level are respectively major contributor and inhibitor to national and industrial emission reduction whether in developing or developed countries, while in developed countries, energy intensity has a slightly stronger impact on carbon emissions than economic level. Carbon intensity had both positive and negative impact on carbon emission, and population scale usually drove carbon emission increase, particularly in developing countries like India;(iii) Industrial carbon emissions vary widely across economies, but most industrial carbon emissions continue to decrease in developed countries while increase in developing countries. Therefore, we contend that energy intensity is the key point to prevent a potential rebound of emission in post-COVID-19 era. © 2022

Near-Surface Atmospheric Behavior over Complex Tropical Topography in Puerto Rico Dominated by Seasonal Patterns Despite Frequent Environmental Changes

Understanding near-surface atmospheric behavior in the tropics is imperative given the role of tropical energy fluxes in Earth’s climate cycles, but this area is complicated by a land–atmosphere interaction that includes rugged to-pography, seasonal weather drivers, and frequent environmental disturbances. This study examines variation in nearsurface atmospheric behaviors in northeastern Puerto Rico using a synthesis of data from lowland and montane locations under different land covers (forest, urban, and rural) during 2008–21, when a severe drought, large hurricanes (Irma and Maria), and the COVID-19 mobility-reducing lockdown occurred. Ceilometer, weather, air quality, radiosonde, and satellite data were analyzed for annual patterns and monthly time series of data and data correlations. The results showed a system that is strongly dominated by easterly trade winds transmitting regional oceanic patterns over terrain. Environmental disturbances affected land–atmosphere interaction for short time periods after events. Events that reduce the land signature (reducing greenness: e.g., drought and hurricanes, or reducing land pollution: e.g., COVID-19 lockdown) were evidenced to strengthen the transmission of the oceanic pattern. The most variation in near-surface atmospheric behavior was seen in the mountainous areas that were influenced by both factors: trade winds, and terrain-induced orographic lifting. As an exception to the rest of the near-surface atmospheric behavior, pollutants other than ozone did not correlate positively or negatively with stronger trade winds at all sites across the region. Instead, these pollutants were hypothesized to be more anthropogenically influenced. Once COVID-19 lockdown had persisted for 3 months, urban pollution decreased and cloud base may have increased. © 2022, American Meteorological Society. All rights reserved.

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.

Temperature Targets, Deep Uncertainty and Extreme Events in the Design of Optimal Climate Policy

We study optimal climate policy consistent with the constraint that average global temperature remains below 1.5 ∘ C relative to pre-industrial levels. We consider a holistic representation of uncertainty including traditional risk, deep uncertainty and stochastic arrivals of climate-related disasters. Using robust control methods, we derive optimal emission and carbon tax paths and calculate when temperature exceeds the target in the absence of the constraint. We show that policy under deep uncertainty requires strong action now relative to pure risk but the policy stringency is reversed later. Preliminary estimates suggest that the COVID-19 impact on attainment of the temperature target is negligible.

Price Volatility Dependence Structure Change Among Agricultural Commodity Futures Due to Extreme Event: An Analysis with the Vine Copula

Since the COVID-19 spreads, global food prices have continued to rise and become more volatile because of food security panic, global food supply chain disruption, and unfavorable weather conditions for cultivation. This paper aims to study and compare the dependence structure in price volatility among agricultural commodity futures before and during the COVID-19 pandemic, with different vine copulas, namely the R-vine, C-vine, and D-vine. The daily closing prices of the agricultural commodity futures are used in the investigation, including Corn, Wheat, Oat, Soybean, Rice, Sugar, Coffee, Cocoa, and Orange, traded in the Chicago Board of Trade (CBOT) from January 2016 to July 2021. The conditional volatilities were estimated using the best fit GARCH model with the student-t distribution. The empirical results highlight the dependence structures captured by the C-vine, D-vine, and R-vine copula-based models before and during the COVID-19 pandemic. Although the C-vine copula structures of the two different periods are unchanged, the details of the copula family in such a structure differ. In the case of D-vine and R-vine copulas, the details of the copula families and their vine structures of two different periods are significantly different, meaning that COVID-19 impacts the price volatility dependence structure among the agricultural commodity futures examined. Based on the AIC, the most appropriate dependence structure for pre-COVID-19 period is the C-vine copula, while the during-COVID-19 period is the D-vine copula. The dependence structure of agricultural commodity futures prices can be used in other risk analysis and management methods such as value at risk (VaR), portfolio optimization, and hedging. © 2022, Springer Nature Switzerland AG.

Humans and robots coping with crisis - Starship, Covid-19 and urban robotics in an unpredictable world

In 2018 "Starship"grocery delivery robots were first introduced in Milton Keynes (MK), a new town in England, to automate a task that is difficult to perform in a cost-effective manner by humans - that of on-demand grocery delivery. Two years later the Covid-19 pandemic rendered routine activities such as delivering groceries or visiting the supermarket unexpectedly unsafe. The ability of robots to operate in environments that are dangerous for humans was brought into sharp relief by the Covid-19 pandemic but it may also be relevant in other crisis situations such as those that may be caused by heat waves, blizzards and other extreme events associated with climate change. Drawing on a case study of Starship robots in MK, this contribution investigates the potential of robotic and autonomous systems to provide cities with tools for coping with such unexpected situations. © 2021 IEEE.

Extreme Events, Entrepreneurial Start-Ups, and Innovation: Theoretical Conjectures.

In light of the COVID-19 pandemic, we scrutinize what has been established in the literature on whether entrepreneurship can cause and resolve extreme events, the immediate and long-run impacts of extreme events on entrepreneurship, and whether extreme events can positively impact (some) entrepreneurship and innovation. Based on this, we utilize a partial equilibrium model to provide several conjectures on the impact of COVID-19 on entrepreneurship, and to derive policy recommendations for recovery. We illustrate that while entrepreneurship recovery will benefit from measures such as direct subsidies for start-ups, firms' revenue losses, and loan liabilities, it will also benefit from aggregate demand-side support and income redistribution measures, as well as from measures that facilitate the innovation-response to the Keynesian supply-shock caused by the pandemic, such as access to online retail and well-functioning global transportation and logistics.

Brent and WTI oil prices volatility during major crises and Covid-19

We provide novel evidence of two different types of volatility-patterns of oil spot prices that are generated depending on which is the predominant trigger: a) spikes of volatility (which are highly erratic) are produced during periods of supply/demand crises of oil disruptions (such as the 1990/91 First-Gulf-War, 2001 US-terrorist attack, the oil conflict of Saudi-Arabia with the US in 2014/16 and with Russia in 2020 -together with the Covid-19 impact-);while b) periods where economic/financial/stock market crises are the predominant trigger (such as the 1997/98 Asian and 2008/09 Global-Financial Crises and the 2017/19 oil conflicts including the 2018 stock market crisis) are associated to higher volatility persistence. Our results are very relevant since oil markets in the coming months/years are very likely to have a very high degree of uncertainty, and knowledge of the type of volatility that is generated under each of the different triggers and how it affects oil markets is very relevant for investors, speculators and policy makers.

The influence of extreme events such as Brexit and Covid-19 on equity markets.

In this article first, we show that the result that the PIIGS group had the largest negative unadjusted and abnormal returns on the day following the Brexit Referendum is robust to taking into account jointly other extreme events such as the Covid-19. Second, we provide evidence that the impact of the declaration of Covid-19 to be a global pandemic by the WHO - when global markets fell by nearly 15% - had a total different reaction in the financial markets to the one following the Brexit Referendum, impacting more negatively in countries where quarantine lockdowns were announced that day (i.e. Austria, Belgium, Brazil, Canada, Italy and Spain), independently on their debt-to GDP ratio. We also show that the day after Covid-19 was declared as a global pandemic, China and Japan (countries that already implemented lockdowns in the previous months) were the only analyzed countries that did not experience any evidence of abnormal returns in their financial markets. Moreover, during the three following days, the US was the only analyzed country showing no evidence of negative abnormal returns due to the declaration of the national emergency. These results suggest that government policies must take into account and monitor specially health-related news at global level, since they can have enormous impacts on portfolio allocations on stock markets, in order to take more informed decisions.

COVID-19 and financial market efficiency: Evidence from an entropy-based analysis.

This study assesses the market efficiency of S&P 500 Index, gold, Bitcoin and US Dollar Index during the extreme event of COVID-19 pandemic. Market efficiency is estimated by a multiscale entropy-based method for the scales of hourly and 1 to 30 business days. At all scales, four markets' efficiency decreases sharply and persistently during February-March 2020. Market efficiency decreases the most in S&P 500 Index and the least in Bitcoin market. Bitcoin market efficiency is more resilient than others during the extreme event, which is an attractive feature to serve as a safe haven asset.

Compound Risks of Hurricane Evacuation Amid the COVID-19 Pandemic in the United States.

The 2020 Atlantic hurricane season was extremely active and included, as of early November, six hurricanes that made landfall in the United States during the global coronavirus disease 2019 (COVID-19) pandemic. Such an event would necessitate a large-scale evacuation, with implications for the trajectory of the pandemic. Here we model how a hypothetical hurricane evacuation from four counties in southeast Florida would affect COVID-19 case levels. We find that hurricane evacuation increases the total number of COVID-19 cases in both origin and destination locations; however, if transmission rates in destination counties can be kept from rising during evacuation, excess evacuation-induced case numbers can be minimized by directing evacuees to counties experiencing lower COVID-19 transmission rates. Ultimately, the number of excess COVID-19 cases produced by the evacuation depends on the ability of destination counties to meet evacuee needs while minimizing virus exposure through public health directives. These results are relevant to disease transmission during evacuations stemming from additional climate-related hazards such as wildfires and floods.

Ten questions concerning occupant health in buildings during normal operations and extreme events including the COVID-19 pandemic.

Even before the COVID-19 pandemic, people spent on average around 90% of their time indoors. Now more than ever, with work-from-home orders in place, it is crucial that we radically rethink the design and operation of buildings. Indoor Environmental Quality (IEQ) directly affects the comfort and well-being of occupants. When IEQ is compromised, occupants are at increased risk for many diseases that are exacerbated by both social and economic forces. In the U.S. alone, the annual cost attributed to sick building syndrome in commercial workplaces is estimated to be between $10 billion to $70 billion. It is imperative to understand how parameters that drive IEQ can be designed properly and how buildings can be operated to provide ideal IEQ to safeguard health. While IEQ is a fertile area of scholarship, there is a pressing need for a systematic understanding of how IEQ factors impact occupant health. During extreme events, such as a global pandemic, designers, facility managers, and occupants need pragmatic guidance on reducing health risks in buildings. This paper answers ten questions that explore the effects of buildings on the health of occupants. The study establishes a foundation for future work and provides insights for new research directions and discoveries.