Strategic alliances and firms' chances to survive "black swans” in B2B industries

Purpose>This study aims to propose that, in business-to-business (B2B) industries, number of strategic alliances firms established before a "black swan” event enhances their chances to survive the black swan, and the enhancements take place through moderation effects. Changes in firms' core structures – their stated goals, authority structure, core technologies and marketing strategies – to adapt to business jolts have adverse effects on firm performance. Firms' existing B2B strategic alliances moderate the effects negatively by outsourcing different goals, authority structures, core technologies and marketing strategies to partners who fit the changed environment.Design/methodology/approach>This study collected quantitative data and analyzed the data with the regression method.Findings>Using data from Chinese firms in five technology industries during the 2007–2009 economic crisis, this study finds that firms' internal adaptation is negatively correlated with their performance during economic crises, and B2B strategic alliances negatively moderate this relationship.Research limitations/implications>First, this study focuses on B2B strategic alliances, and it is not clear whether the findings apply to B2C industries, where strategic alliances may not be common. Perhaps firms can use other means of survival in addition to strategic alliances in B2C industries. Second, this study does not differentiate between fast-moving and slow-moving industries, and it is not clear whether strategic alliances play the same role in both industries. Third, this study does not differentiate firm ages and sizes. It remains unclear how large, established and small, young firms differ when facing crises. Finally, this study is based on the Chinese setting, and it is not clear whether the findings apply to other markets as well. These issues should be explored in future studies.Practical implications>Changing firms' core structures harms their performance during black swan crises because such crises are unpredictable, and planned changes may not adapt firms to crises. Managers should not attempt to change their core structures during crises. B2B strategic alliances provide an effective means for firms to survive crises.Originality/value>This paper makes two contributions to the existing literature: First, this paper demonstrates that changes of one of the four core structures of a firm to cope with black swan events have negative impacts on firm performance. Second, this paper identifies the importance of holding a variety of strategic alliances previously to the black swan events to reduce the negative impacts of changing core structures.

Mental state, biological rhythm and social support among healthcare workers during the early stages of the COVID-19 epidemic in Wuhan.

Background: The COVID-19 pandemic has put the mental health of healthcare workers at risk. However, the potential psychosocial factors underlying mental health problems, such as depression and anxiety, require further investigation. The present study aimed to explore the factors that influence the mental state of healthcare workers. Methods: A total of 276 healthcare workers completed a set of online self-report questionnaires from February 4 to 7, 2020, in the following order: general information related to the COVID-19 outbreak, Biological Rhythms Interview of Assessment in Neuropsychiatry, Beck Depression Inventory-II, Beck Anxiety Inventory, and Social Support Rating Scale. Results: Our study revealed that both social support and age moderated the ability of biological rhythm disturbance to exacerbate depression (R2 = 0.47; effect size f2 = 0.85). Higher levels of social support buffered the amplification of depression associated with increased biological rhythm disturbance in all age groups, and especially in younger individuals (mean age = 26.57, se = 0.04). Depressive symptoms were predicted by both social and sleeping rhythms, whereas anxiety symptoms were predicted only by social rhythm. Married individuals had lower biological rhythm disturbance ratings and higher social support ratings. Females also reported higher ratings in social support. Conclusions: Our study suggests that biological rhythm intervention along with social support can reduce the negative effect of biological rhythm disturbance on mood disorders, especially in younger people. We also provide evidence for the ability of social support to buffer stress in a major health crisis and demonstrate the effects of marital status and sex, which provide a different perspective for studying mental crisis management.

Global low-carbon energy transition in the post-COVID-19 era.

The COVID-19 pandemic has created significant challenges for energy transition. Concerns about the overwhelming emphasis on economic recovery at the cost of energy transition progress have been raised worldwide. More voices are calling for "green" recovery scheme, which recovers the economy while not compromising on the environment. However, limited academic attention has been paid to comprehensively investigating the implications of COVID-19 for global energy transition. This study thus provides a comprehensive analysis of the dynamics between energy transition and COVID-19 around the world and proposes a low-carbon energy transition roadmap in the post-pandemic era. Using energy data from the International Energy Agency (IEA), we first summarized and reviewed the progress of energy transition prior to COVID-19. Building on prior progress, we identified the challenges for energy transition during the pandemic from the perspectives of government support, fossil fuel divestment, renewable energy production capacity, global supply chain, and energy poverty. However, the pandemic also generates opportunities for global energy transition. We hence also identified potential opportunities for energy transition presented by the pandemic from the perspectives of price competitiveness, policy implementation efficiency, and renewable energy strengths. We further provided an in-depth discussion on the impact of current worldwide economic recovery stimulus on energy transition. Based on the identified challenges and opportunities, we proposed the post-pandemic energy transition roadmap in terms of broadening green financing instruments, strengthening international cooperation, and enhancing green recovery plans. Our study sheds light on a global low-carbon energy transition framework and has practical implications for green recovery schemes in post-pandemic times.

Combating the Infodemic: A Chinese Infodemic Dataset for Misinformation Identification.

Misinformation posted on social media during COVID-19 is one main example of infodemic data. This phenomenon was prominent in China when COVID-19 happened at the beginning. While a lot of data can be collected from various social media platforms, publicly available infodemic detection data remains rare and is not easy to construct manually. Therefore, instead of developing techniques for infodemic detection, this paper aims at constructing a Chinese infodemic dataset, "infodemic 2019", by collecting widely spread Chinese infodemic during the COVID-19 outbreak. Each record is labeled as true, false or questionable. After a four-time adjustment, the original imbalanced dataset is converted into a balanced dataset by exploring the properties of the collected records. The final labels achieve high intercoder reliability with healthcare workers' annotations and the high-frequency words show a strong relationship between the proposed dataset and pandemic diseases. Finally, numerical experiments are carried out with RNN, CNN and fastText. All of them achieve reasonable performance and present baselines for future works.

Fighting mosquito bite during a crisis: capabilities of Florida mosquito control districts during the COVID-19 pandemic.

BACKGROUND: The stay-at-home orders imposed in early April 2020 due to the COVID-19 pandemic in various states complicated mosquito control activities across the United States (US), and Florida was no exception. Mosquito control programs are the first line of defense against mosquito-borne pathogens. The purpose of this study was to examine the capabilities of Florida mosquito programs to implement key mosquito measures during the COVID-19 pandemic lockdown. METHODS: Using a self-administered online survey, we examined the capabilities of all Florida mosquito control programs (both state-approved mosquito districts, N = 63; and open programs, N = 27) at a time when the state of Florida was still under heightened awareness of, stay-at-home orders and planning a phase 1 reopening over the COVID-19 pandemic (June to July 2020). The final sample included mosquito control programs structured as the Board of County Commissioners (BOCC) (n = 42), independent tax district (n = 16), municipal (n = 10), and health or emergency department (n = 5). We used descriptive statistics to summarize information about the characteristics of responding programs, their implemented mosquito control and surveillance activities.  wWe used bivariate analysis to compare the characteristics of responding programs and the self-reported mosquito measures. RESULTS: Of the recruited mosquito control programs, 73 completed the survey (81.1% response rate; 73/90). Of these, 57.5% (n = 42) were Board of County Commissioners (BOCC) mosquito control programs, 21.9% (n = 16) were independent tax district programs, 13.7% (n = 10) were municipal mosquito control programs, and only 6.8% (n = 5) were either health or emergency department mosquito control programs. Except for arbovirus surveillance, most programs either fully or partially performed larval (61.8%) and adult (78.9%) surveillance; most programs conducted species-specific control for Aedes aegypti (85.2%, n = 54), Aedes albopictus (87.3%, n = 55), Culex quinquefasciatus (92.1%, n = 58), and Culex nigripalpus (91.9%, n = 57). CONCLUSIONS: Findings underscore the importance of ongoing mosquito control activities, and suggest that Florida mosquito control programs are vigilant and have significant capability to handle potential mosquito-borne disease threats, but arbovirus surveillance systems (laboratory testing of mosquito pools and testing of human and nonhuman specimens for arboviruses) are needed during pandemics as well.

Alternations of cesarean section rates in a non-infected population after the outbreak of COVID-19: a cross-sectional study.

The pandemic of Coronavirus Disease 2019(COVID-19) could be sources of anxiety among pregnant women and health care workers, which might affect the decision making on the mode of delivery. The aim of this study was to explore whether the cesarean section rates had significantly increased after the outbreak of COVID-19. We analyzed the labor data with cesarean rates in a tertiary maternity center during COVID-19 epidemic months from January to March in 2020, compared with pre-epidemic parallel months in 2019 by using Z-score test for proportions. Even though none of the staff or patient suffered with COVID-19 in the hospital, we found the cesarean section rates slightly increased in a non-infected population after the outbreak of COVID-19. Obstetricians should beware of the possible effects of COVID-19 on the mode of delivery.

COVID-19 infodemic on Chinese social media: A 4P framework, selective review and research directions

During the outbreak of the COVID-19 (2019 coronavirus disease), misinformation related to the virus spread rapidly online and have led to serious difficulties in controlling the disease. The term infodemic is coined to outline the bad effect from the extensive dissemination of misinformation during the outbreak. With regards to this phenomenon, the World Health Organization emphasized the need to fight against infodemic and asked all countries not only to make efforts in slowing down the spread of the COVID-19 but also in countering the risk caused by infodemic. Due to its negative impact, this paper analyzes infodemic on Chinese social media at the initial stage of the COVID-19 outbreak and presents a 4P framework standing for the four features of Chinese infodemic: Prevention Attention, Problem Orientation, Patterns Interaction and Points Globalization. Furthermore, a selective review of existing datasets in the neural networks domain is synthesized based on the 4P framework. Finally, research directions, including recommendations, about constructing a large-scale dataset for Chinese infodemic automatic detection are proposed.

The impact of investor attention during COVID-19 on investment in clean energy versus fossil fuel firms.

The outbreak of the COVID-19 pandemic has had significant negative impacts on financial markets, including energy stock markets. However, recently proposed and implemented green recovery plans may mean that clean energy firms demonstrate better performance than fossil fuel firms after the pandemic. As more voices call for the update of clean energy, theory on investor attention suggests investors will pay more attention to the potential to invest in clean energy stocks. Using a sample period of eight weeks before and during the pandemic, we find that the negative impact of the outbreak on both clean energy and fossil fuel firms is more significant for fossil fuel firms. Our results further show that during the pandemic there have been improved returns for clean energy firms as a consequence of investor attention, but not for fossil fuel firms. Our findings provide empirical evidence for the advantages of green recovery schemes in influencing financial markets, especially for clean energy stocks. These results suggest there are benefits for further promotion and implementation of green recovery stimulus measures post-pandemic.

Association of Overlapped and Un-overlapped Comorbidities with COVID-19 Severity and Treatment Outcomes: A Retrospective Cohort Study from Nine Provinces in China.

OBJECTIVE: Several COVID-19 patients have overlapping comorbidities. The independent role of each component contributing to the risk of COVID-19 is unknown, and how some non-cardiometabolic comorbidities affect the risk of COVID-19 remains unclear. METHODS: A retrospective follow-up design was adopted. A total of 1,160 laboratory-confirmed patients were enrolled from nine provinces in China. Data on comorbidities were obtained from the patients' medical records. Multivariable logistic regression models were used to estimate the odds ratio ( OR) and 95% confidence interval (95% CI) of the associations between comorbidities (cardiometabolic or non-cardiometabolic diseases), clinical severity, and treatment outcomes of COVID-19. RESULTS: Overall, 158 (13.6%) patients were diagnosed with severe illness and 32 (2.7%) had unfavorable outcomes. Hypertension (2.87, 1.30-6.32), type 2 diabetes (T2DM) (3.57, 2.32-5.49), cardiovascular disease (CVD) (3.78, 1.81-7.89), fatty liver disease (7.53, 1.96-28.96), hyperlipidemia (2.15, 1.26-3.67), other lung diseases (6.00, 3.01-11.96), and electrolyte imbalance (10.40, 3.00-26.10) were independently linked to increased odds of being severely ill. T2DM (6.07, 2.89-12.75), CVD (8.47, 6.03-11.89), and electrolyte imbalance (19.44, 11.47-32.96) were also strong predictors of unfavorable outcomes. Women with comorbidities were more likely to have severe disease on admission (5.46, 3.25-9.19), while men with comorbidities were more likely to have unfavorable treatment outcomes (6.58, 1.46-29.64) within two weeks. CONCLUSION: Besides hypertension, diabetes, and CVD, fatty liver disease, hyperlipidemia, other lung diseases, and electrolyte imbalance were independent risk factors for COVID-19 severity and poor treatment outcome. Women with comorbidities were more likely to have severe disease, while men with comorbidities were more likely to have unfavorable treatment outcomes.

COVID-19 Docking Server: a meta server for docking small molecules, peptides and antibodies against potential targets of COVID-19.

MOTIVATION: The coronavirus disease 2019 (COVID-19) caused by a new type of coronavirus has been emerging from China and led to thousands of death globally since December 2019. Despite many groups have engaged in studying the newly emerged virus and searching for the treatment of COVID-19, the understanding of the COVID-19 target-ligand interactions represents a key challenge. Herein, we introduce COVID-19 Docking Server, a web server that predicts the binding modes between COVID-19 targets and the ligands including small molecules, peptides and antibodies. RESULTS: Structures of proteins involved in the virus life cycle were collected or constructed based on the homologs of coronavirus, and prepared ready for docking. The meta-platform provides a free and interactive tool for the prediction of COVID-19 target-ligand interactions and following drug discovery for COVID-19. AVAILABILITY AND IMPLEMENTATION: http://ncov.schanglab.org.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

[Mechanism of Xuanfei Baidu Tang in treatment of COVID-19 based on network pharmacology].

The study aimed to investigate the multi-constituent, multi-target mechanism of Xuanfei Baidu Tang(XFBD) in the treatment of coronavirus disease 2019(COVID-19), through exploring the main ingredients and effective targets of XFBD, as well as analyzing the correlation between XFBD targets and COVID-19. The compounds of each herb in XFBD were collected from TCM-PTD, ETCM, TCMSP and SymMap database. Next, the information of meridian tropisms was collected from Chinese Pharmacopoeia(2015 edition), and the target information of the major constituents of XFBD were obtained from TCM-PTD, ETCM, TCMSP and TargetNet database. Subsequently, the target network model and the major modules were generated by Cytoscape, and the functional enrichment analysis of XFBD targets were completed by DAVID and STRING. As a result, ten of the 13 herbs in XFBD belonged to the lung meridian, and 326 of the 1 224 putative XFBD targets were associated with the disease target of COVID-19, among which 109 targets were enriched in the disease pathways of viral infection and lung injury. The main biological pathways regulated by the key XFBD targets included viral infection, energy metabolism, immunity and inflammation, parasites and bacterial infections. In conclusion, the therapeutic mechanism of XFBD in COVID-19 showed a multi-herb, multi-constituent, multi-target pattern, with lung as the chief targeted organ. By regulating a series of biological pathways closely related to the occurrence and development of diseases, XFBD plays a role in balancing immunity, eliminating inflammation, regulating hepatic and biliary metabolism and recovering energy metabolism balance.