In this paper we explore a new technological intersection in the "big data revolution": the integration of two forms of data, genetic data and fitness tracking data. For example, a small number of direct-to-consumer (DTC) genetic testing companies have recently begun offering customers the ability to link their fitness tracking data with their genetic profile to get personalized diet and exercise recommendations. In this paper we put forward four ethical considerations that should inform potential uses of this health information. Those considerations are: the heightened risks to privacy resulting from combining sensitive data sets; the poor quality of health information that is possible at present in the realm of precision DTC genomics; the limited usefulness of the recommendations; and finally, the cultural assumptions about health and personal responsibility that are embedded within fitness genetic testing and fitness tracking. To conclude, we offer some guidance on how the benefits and risks of returning this type of health information can be weighed.

Although several studies have explored the effects of the pandemic on aviation, little remains known about whether members of the public are willing to fly again after they have been vaccinated. The current study uses the Health Belief Model (HBM) to fill this missing gap by manipulating the following variables: 1) whether or not the participant is vaccinated; 2) whether or not airlines require that all passengers and crew receive vaccinations; 3) length of flight; 4) destination; and 5) the number of passengers. The data from 678 participants revealed that willingness to fly is much higher if the participants themselves have been vaccinated, if the airlines require all passengers to be vaccinated, if the flight is short, if the destination is domestic, and if the number of passengers is low. These findings did not appear to differ as a function of flying business pleasure. We discuss the practical implications of these data as airlines struggle to bring back their customer base.

The COVID-19 pandemic has amplified the awareness and demand of public health worldwide. Based on the panel data of 81 developing countries from 2002 to 2019, this study probes into the effect of digitalization on public health and explores the mechanism through which digitalization affects public health from the perspective of income inequality. The results show that digitalization significantly enhances public health in developing countries, and this conclusion still holds after the robustness test. The heterogeneity analysis based on geographic location and income level indicates that the enhancing effect of digitalization on public health is most evident in Africa and middle-income countries. A further mechanism analysis suggests that digitalization can positively impact public health through the intermediary channel of suppressing income inequality. This study enriches the research on digitalization and public health and provides insights for comprehending public health needs and the powerful empowering effects of digitalization.

Some countries in the presence of unforeseen Coronavirus Disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have experienced lower total deaths, though higher numbers of COVID-19 related infections. Results here suggest that one of the explanations is the critical role of ventilator technology in clinical health environment to cope with the initial stage of COVID-19 pandemic crisis. Statistical evidence shows that a large number of ventilators or breathing devices in countries (26.76 units per 100,000 inhabitants) is associated with a fatality rate of 1.44% (December 2020), whereas a higher fatality rate given by 2.46% is in nations with lower numbers of ventilator devices (10.38 average units per 100,000 people). These findings suggest that a large number of medical ventilators in clinical setting has a high potential for more efficient healthcare and improves the effective preparedness of crisis management to cope with new respiratory pandemic diseases in society. Hence, a forward-thinking and technology-oriented strategy in healthcare sector, based on investments in high-tech ventilator devices and other new medical technologies, can help clinicians deliver effective care and reduce negative effects of present and future respiratory infectious diseases, in particular when new drugs and appropriate treatments are missing in clinical environment to face unknown respiratory viral agents .

This paper examines the effects of online campaigns celebrating frontline workers on COVID-19 outcomes regarding new cases, deaths, and vaccinations, using the United Kingdom as a case study. We implement text and sentiment analysis on Twitter data and feed the result into random regression forests and cointegration analysis. Our combined machine learning and econometric approach shows very weak effects of both the volume and the sentiment of Twitter discussions on new cases, deaths, and vaccinations. On the other hand, established relationships (such as between stringency measures and cases/deaths and between vaccinations and deaths) are confirmed. On the contrary, we find adverse lagged effects from negative sentiment to vaccinations and from new cases to negative sentiment posts. As we assess the knowledge acquired from the COVID-19 crisis, our findings can be used by policy makers, particularly in public health, and prepare for the next pandemic.

After the outbreak of Covid-19, the European Commission (EC) promptly took the initiative to lead and coordinate a common European response. The actions unfolded in several directions, paving the way to the uptake of AI-related solutions and placing hope in these tools to face crises, namely of a public health and global nature. In this article, we focus on initiatives for the uptake of AI-related solutions from the experimental level towards implementation. The Repository of AI and Robotics solutions, launched in 2020, is an example of an initiative put forth to leverage and disseminate knowledge on AI, expanding the fields of application and fostering the development and adaptation of cutting-edge technologies to explore how they can assist in tackling specific tasks during a public health crisis. Using this database, the article outlines the promise of AI as a hope for handling specific needs and tasks and how the uptake of such technologies was accelerated during the Covid-19 pandemic. In extension, we frame initiatives for the uptake of AI-enabled solutions from a governance perspective, focusing on the establishment of frameworks for ethical and trustworthy AI by defining principles and standards that aim to protect the underlying values deemed fundamental.

Motivated by the realistic demand of controlling the Internet public opinion risk caused by the local outbreak of COVID-19, this paper creatively proposes a COVID-19 local outbreak Internet public opinion risk grading research framework. The SMAA-FAHPSort II method combining Analytic Hierarchy Process Sort II (AHPSort II) method with Stochastic Multicriteria Acceptability Analysis (SMAA-2) method is introduced into this framework, to evaluate the Internet public opinion risk level of social media during the local outbreak of COVID-19. In addition, this framework is applied to a case of Internet public opinion risk evaluation on Microblog platform of China. According to the number of new cases per day in mainland China, this paper divides the period from May 7, 2020 to September 3, 2021 into seven stages. A total of more than 10,000 Microblog hot topics were collected, after screening and preprocessing, 5422 related topics are remained to help complete the Internet public opinion risk evaluation. The case study analysis results show that the number of days classified as moderate risk and above has reached more than 280. This proves that the local outbreak of COVID-19 will indeed increase the risk of Internet public opinion, and correlation analysis confirms that the level of public opinion risk is positively correlated with the severity of the epidemic in the real world. Furthermore, the effectiveness and advantages of the proposed method are verified by comparative analysis and sensitivity analysis. Finally, some effective public opinion management suggestions have been put forward. This paper can provide reference for the government to formulate or improve relevant strategies, and also has great significance for reducing the risk of Internet public opinion in social media.

We theoretically and empirically examine how acquiring new skills and increased financial worries influenced entrepreneurship entry and exit intentions during the pandemic. To that end, we analyze primary individual-level survey data we collected in the aftermath of the COVID-19's first wave in Russia, which has had one of the highest COVID-19 infection rates globally. Our results show that acquiring new skills during the pandemic helped owners keep their existing businesses and encouraged start-ups in sectors other than information technology (IT). For IT start-ups, having previous experience matters more than new skills. While the pandemic-driven financial worries are associated with business closure intentions, they also inspire new business start-ups, highlighting the pandemic's creative destruction power. Furthermore, preferences for formal employment and remote work also matter for entrepreneurial intentions. Our findings enhance the understanding of entrepreneurship formation and closure in a time of adversity and suggest that implementing entrepreneurship training and upskilling policies during recurring waves of the COVID-19 pandemic can be an important policy tool for innovative small business development.

Personal computers, tablets, and smartphones may support older adults' engagement when people are required to stay home and opportunities to engage in meaningful activities are reduced during the COVID-19 period. This study aims to screen older adults' technology-use characteristics across social, leisure, and education domains during the COVID-19 pandemic from a crosscultural viewpoint. The sample included 576 participants aged 60 and older from France ( = 62), Spain ( = 110), and Israel ( = 404). Participants completed the technology-use survey, which consists of questions about their facilities, technology usability, need for adaptations to support technology use, and changes in technology use since COVID-19. Significant differences were found between countries in facilities, χ (2) = 25.16,  < .001, and usability, χ (2) = 64.14,  < .001, across the three domains. Furthermore, 34% of technological usability was predicted by country and facilities, (4, 568) = 72.39, .001. Participants noted a willingness to use technology if it was adapted for social (61%-73%), leisure (51%-71%), or educational (67%-76%) activities and that they devoted substantially more time to technology across domains (>58%) due to COVID-19. These findings highlight culture and facilities as factors that play an imperative role in supporting and enhancing the usability of technology among older adults.

This study aims to understand the impact of the COVID-19 pandemic by comparing the performance of three major supermarkets in South Africa and addressing the following questions. 1) What is the impact of a supply chain disruption on the food system? 2) What interventions (short and long-term) are taken by the food supply chain to mitigate disruption? 3) What does the post-pandemic picture look like for the food retail sector? This study adopts a comparative research approach and investigates direct strategies adopted by various food supply chain actors to mitigate the impact of covid-19. This study compares how retailers Checkers, Woolworths, and Pick n Pay have adapted their business models to remain resilient during COVID-19 lockdown. The results show that the food supply chain remained resilient even with demand management challenges at the lockdown. Food supply chain issues came under a spotlight as borders and production plants were shut down or restricted to contain the spread of the virus. This study establishes that the food shortage is primarily caused by panic buying at the beginning of lockdown, causing shock in the supply chain cadence. The other aspect of food security issue is attributed to food availability and socioeconomic problems resulting from loss of income. On sustainability, there are fears that control measures such as packaging (increased use of plastic), cleaning chemicals, waste and sanitisation of space to maintain hygiene as required for covid-19 can undermine the gains towards preserving the environment.

In recent years, online learning in the education sector has increasingly become prominent. While many believe that online learning has the potential to reduce inequity, the debate on whether it bridges the gap or widens it continues to persist. This study examined equity issues in online learning in China during the COVID-19 pandemic. The study used data from the Online Learning Survey of High School Students in China to analyze the influencing factors of the first, second, and third-level digital divide. The study found that the digital divide existed in online learning during the pandemic. It was primarily presented as differences in equipment quantity and network quality, students' adaptability to online teaching, and their offline learning outcomes. These findings suggest that the development of online learning alone cannot eliminate achievement gaps. The promotion of education equity requires efforts from various stakeholders and interventions specifically targeting disadvantaged students.

This research aims to explore the usage of social networking sites in the midst of the COVID-19 pandemic. To achieve the objective, this study develops and validates a scale to measure the usage of social networking sites. Data was collected via a google form link through social networking sites in India viz. Facebook, Instagram, Twitter, Telegram and WhatsApp. A total of 204 responses were found accurate and useable for the study. The population of the study includes people residing in India. Data was analyzed applying SPSS 20 and AMOS 22.0. To design and validate the scale, both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used in conjunction with each other. The EFA results indicate a six-factor structure, explaining 73.43% of the cumulative variance, with all the items loading above 0.70. Thus, all the 20 items of six constructs meet this threshold limit. Therefore, this 20-items questionnaire emerges as an effective tool for assessing social networking usage. This study developed and validated the scale of usage of social networking sites to measure the six constructs informativeness, education, entertainment, shopping, socialization and social cause. Social media developers and analysts can use this scale from a technological standpoint to redesign and refine their websites for a better user interface. Since the research is primarily focused on India, extrapolating the results to other countries is difficult.

Self-service technologies (SSTs) are not new to modern consumers, yet the COVID-19 pandemic brings new motivations into SST usage. This study aims to revisit consumers' SST usage under the pandemic context, focusing on consumers' changing perceptions on social interactions (i.e. the 'self' element) and technologies. The impacts of social distancing, individualistic culture, self-identity as technology users, and innovativeness on consumers' SST usage are explored in the field of smart locker self-collection service. A survey instrument is designed for data collection, and the data are analysed through a hierarchical regression followed by latent class analysis. The findings confirm the contributing effects of the four proposed factors on consumers' SST usage. Further, four distinct SST user segments emerge which are labelled as: technology lovers, social excluders, SST embracers, and indifferent pandemic responders. This study contributes to the SST literature by emphasising the pandemic-induced effects on the consumption environment externally and individuals' self-perceptions internally, both leading to behavioural implications of SST usage.

Online reviews have been used effectively to understand customers' satisfaction and preferences. COVID-19 crisis has significantly impacted customers' satisfaction in several sectors such as tourism and hospitality. Although several research studies have been carried out to analyze consumers' satisfaction using survey-based methodologies, consumers' satisfaction has not been well explored in the event of the COVID-19 crisis, especially using available data in social network sites. In this research, we aim to explore consumers' satisfaction and preferences of restaurants' services during the COVID-19 crisis. Furthermore, we investigate the moderating impact of COVID-19 safety precautions on restaurants' quality dimensions and satisfaction. We applied a new approach to achieve the objectives of this research. We first developed a hybrid approach using clustering, supervised learning, and text mining techniques. Learning Vector Quantization (LVQ) was used to cluster customers' preferences. To predict travelers' preferences, decision trees were applied to each segment of LVQ. We used a text mining technique; Latent Dirichlet Allocation (LDA), for textual data analysis to discover the satisfaction criteria from online customers' reviews. After analyzing the data using machine learning techniques, a theoretical model was developed to inspect the relationships between the restaurants' quality factors and customers' satisfaction. In this stage, Partial Least Squares (PLS) technique was employed. We evaluated the proposed approach using a dataset collected from the TripAdvisor platform. The outcomes of the two-stage methodology were discussed and future research directions were suggested according to the limitations of this study.

Now more than ever it is critical for researchers and decision makers to work together to improve how we manage and preserve the planet's natural resources. Water managers in the western U.S., as in many regions of the world, are facing unprecedented challenges including increasing water demands and diminishing or unpredictable supplies. The transfer of knowledge (KT) and technology (TT) between researchers and entities that manage natural resources can help address these issues. However, numerous barriers impede the advancement of such transfer, particularly between organizations that do not operate in a profit-oriented context and for which best practices for university-industry collaborative engagement may not be sufficient. Frameworks designed around environmental KT - such as the recently-developed Research-Integration-Utilization (RIU) model - can be leveraged to address these barriers. Here, we examine two examples in which NASA Earth science satellite data and remote-sensing technology are used to improve the management of water availability and quality. Despite differences in scope and outcomes, both of these case studies adopt KT and TT best practices and can be further understood through the lens of the RIU model. We show how these insights could be adopted by NASA through a conceptual framework that charts individual- and organizational-level integration milestones alongside technical milestones. Environmental organizations can learn from this approach and adapt it to fit their own institutional needs, integrating KT/TT models and best practices while recognizing and leveraging existing institutional logics that suit their organization's unique history, technical capability and priorities.

- In the ongoing COVID-19 pandemic, people spread various COVID-19-related rumors and hoaxes that negatively influence human civilization through online social networks (OSN). The proposed research addresses the unique and innovative approach to controlling COVID-19 rumors through the power of opinion leaders (OLs) in OSN. The entire process is partitioned into two phases; the first phase describes the novel eputation-based pinion eader dentification algorithm, including a unique voting method to identify the top-T OLs in the OSN. The second phase describes the technique to measure the aggregated polarity score of each posted tweet/post and compute each user's reputation. The empirical reputation is utilized to calculate the user's trust, the post's entropy, and its veracity. If the experimental entropy of the post is lower than the empirical threshold value, the post is likely to be categorized as a rumor. The proposed approach operated on Twitter, Instagram, and Reddit social networks for validation. The ROLI algorithm provides 91% accuracy, 93% precision, 95% recall, and 94% F1-score over other Social Network Analysis (SNA) measures to find OLs in OSN. Moreover, the proposed approach's rumor controlling effectiveness and efficiency is also estimated based on three standard metrics; affected degree, represser degree, and diffuser degree, and obtained 26%, 22%, and 23% improvement, respectively. The concluding outcomes illustrate that the influence of OLs is exceptionally significant in controlling COVID-19 rumors.

Although the global green supply chain management (GSCM) practice has attracted considerable scholarly attention, its efficacy for environmental management systems (EMS) and market competitiveness during Covid-19 has not been fully capitalized. Therefore, the existing literature indicates that the important link between GSCM, EMS, and market competitiveness is missing as supply management is crucial to maintaining market competitiveness. To fill this research gap, the current study examines whether EMS affects the relationship between GSCM practices and market competitiveness. We also propose the moderating role of big data analytics and artificial intelligence (BDA-AI) and environmental visibility on these associations from a Covid-19 perspective. We tested a proposed model using the primary data () from regression-based structural equation modeling (SEM). The results provide empirical support for the impact of GSCM on ESM and market competitiveness. Furthermore, the results show that BDA-AI and environmental visibility strengthen the positive relationship between GSCM-EMS and EMS and market competitiveness, respectively. Current research provides thoughtful insights for supply chain practitioners, policymakers, managers, and academics that organizations should opt for formal EMS, BDA-AI, and environmental visibility to achieve market competitiveness, even in times of crisis such as Covid-19.

Confronting the COVID-19 health emergency has forced public administrations in Spain to work with various networks as a means of promoting their campaigns to citizens. This paper aims to analyse digital citizens' e-participation by focusing on the state health campaign #ThisIsNotAGame. This campaign was launched by the Spanish Ministry of Health in September 2020 via Twitter with the objective of reinforcing protection measures against the virus. A sample consisting of 19,576 tweets, sent from September 2020 to February 2021, was investigated and the results have indicated that, of 9133 users, 64.8% of citizens collaborated in the dissemination of tweets. It was observed that most messages supported the campaign by disseminating information on measures, data and news. Only 0.1% of the messages were aggressive. The conclusion is that, despite not having created a true form of communication between public institutions and citizens, e-participation has generated a functional connection between them. Citizens have acquired a responsible and participatory digital role which, although failing to show personal involvement in their comments, has been the main driving force behind the success of this campaign.

This article discusses the need for accelerated innovation in crisis situations and argues that collaboration plays an important role in enabling such acceleration. The central research question is: We draw on a phenomenon-driven, in-depth qualitative case study of seven initiatives that have developed alternative ventilators in the Netherlands during the COVID-19 crisis. Our results highlight how the COVID-19 pandemic has created a relatively short for accelerated innovation processes that is driven by the to develop solutions to the challenge at hand. Importantly, we show that when collaborative initiatives join other collaborative initiatives- what we define as -a forum for coordinated knowledge and resource exchange between the initiatives is created, increasing the potential for learning and accelerating the innovation process. Finally, we find that is an important intermediating mechanism to accelerate innovation as it enables non-competitive collaboration between the initiatives in favor of the public good. Our results have important implications for accelerated innovation processes to achieve societal missions, goals, or challenges.

To cope with the COVID-19 pandemic, the performing arts industry created new formats for delivering content via digital technology in the form of remote performances. This study examined the effect of remote performances on performers' satisfaction through the lens of the technology adoption model. Additionally, it investigated whether the performers' self-assessment of performance quality mediates the relationship between their technology acceptance and satisfaction. To this end, we collected the data from performers ( = 124) who experienced remote performances in Korea. Results showed that their satisfaction was a function of perceived usefulness and ease of use of the technology. However, the mediation effect by self-assessment was detected only on the relationship between the perceived ease of use and satisfaction. The results of the study suggest that event organizers offer an easy-to-operate technology allowing performers to better engage in remote performances. This also enables performers to self-assess their performances, which will enhance performance quality.

Touchless Technology is facilitating the move to Zero User Interface(UI) propelled by the COVID-19 pandemic which has accelerated the use of this technology due to hygiene requirements. Zero UI can be defined as a controlled interface that enables user interaction with technology through voice, gestures, hand interaction, eye tracking, and biometrics such as facial recognition and contactless fingerprints. Smart devices, IoT sensors, smart appliances, smart TVs, smart assistants and consumer robotics are predominant examples of devices in which Zero UI is becoming increasingly adopted. These control interfaces include natural interaction modes such as voice or gestures. Touchscreens and shared devices such as kiosks, self-service counters and interactive displays are present in our everyday lives. Each of these interactions however is a concern for consumers in a post-COVID-19 world where hygiene is of utmost importance. The one-stop solution to hygienic interactions includes touchless technology such as voice control, remote mobile screen take over, biometric, and gesture control as Zero User interfaces. With the breakthroughs in image recognition and natural language processing, powered by advanced computer vision and machine learning, "Zero UI" is becoming a new normal. This paper is focusing on the progress of the touchless interaction technology during the COVID-19 pandemic, which actually accelerated development in this concept and moved it from being a luxury to a life necessity.