Thusyanthy Lavan, Brett Martin, Weng Marc Lim, Linda D. Hollebeek
This study examines the impact of social isolation on risk-taking behavior in highly uncertain environments with the potential for significant gains and losses. We uncover both direct and indirect effects of social isolation on risk-taking behavior, mediated through perceived stress, sense of control, and neuroticism. The COVID-19 pandemic provides a pertinent context to explore these dynamics, while the volatile cryptocurrency market serves as a topical context for investigation. The analysis based on covariance-based structural equation modeling (CB-SEM) of survey responses from 216 consumers reveals that social isolation significantly increases risk-taking behavior, primarily mediated by heightened perceived stress. Contrary to expectations, sense of control and neuroticism did not mediate this relationship, indicating specific pathways through which isolation affects risk decision. This finding suggests that while social isolation intensifies perceived stress, yielding riskier purchase decisions, it does not universally impact other psychological aspects like resilience (sense of control) or vulnerability (neuroticism). The observed direct (main) and indirect (mediation) effects highlight the importance of targeted interventions to address psychological well-being, particularly at times of enforced isolation. Understanding these dynamics can help advisors (e.g., financial consultants), marketers, and policymakers (e.g., government agencies/lawmakers) formulate strategies to curb excessive risk-taking among isolated individuals, particularly in high-risk financial settings.
This paper seeks to address which business model in higher education that fosters SDG 4, is adequate for the post-pandemic period. To that end, it introduces the âBlockchain Business Model for Higher Educationâ (BBM-HE) and a transformed business model canvas framework based on existing literature, concepts, theories and findings relating to most of the pressing issues in higher education from the present study. To determine these issues, secondary data is used in the qualitative research design by applying inductive content analysis techniques to online reports. The originality of this study lies in the âadaptiveâ perspective to the requirements of the post-pandemic higher education landscape, which consists of modifications to the core elements of higher education, the integration of blockchain technology into the entire system, and a stronger approach to sustainability practice through sustainability tokens. The envisaged model sets out to provide a roadmap for all stakeholders, but most importantly, âdecentralizedâ higher education institutions of the future and the âemployable skills-seekingâ proactive students all over the world, as opposed to the former âsolely degree-focused and affluentâ consumers of educational offerings. This study contributes to higher education literature in terms of business models, blockchains, pandemics, and sustainability.
During the recent pandemic events and lockdown, most educational institutions have moved into online and distance learning. Certain institutions have been more ready than others to shift into full online learning and teaching mode. However, many technical and security challenges and issues related to the learning management system have been encountered. In this article, we investigate the technical benefits of blockchain, and we propose a secured and trusted online-leaning framework based on blockchain. Our proposal takes advantage of blockchain technology to ensure the expected standard of teaching and fairness of assessment while respecting the schedule of courses and exams. Through blockchainâs reward methods, it also motivates both students and teachers to persist in their efforts, even from home.
Because a fast vaccination rollout against coronavirus disease 2019 (COVID-19) is critical to restore daily life and avoid virus mutations, it is tempting to have a relaxed vaccination-administration management system. However, a rigorous management system can support the enforcement of preventive measures, and in turn, reduce incidence and deaths. Here, we model a trustable and reliable management system based on blockchain for vaccine distribution by extending the Susceptible-Exposed-Infected-Recovery (SEIR) model. The model includes prevention measures such as mask-wearing, social distancing, vaccination rate, and vaccination efficiency. It also considers negative social behavior, such as violations of social distance and attempts of using illegitimate vaccination proofs. By evaluating the model, we show that the proposed system can reduce up to 2.5 million cases and half a million deaths in the most demanding scenarios.
By law, schools are required to protect the well-being of students against problems such as on-campus bullying and physical abuse. In the UK, a report by the Office for Education (OfE) showed 17% of young people had been bullied during 2017â2018. This problem continues to prevail with consequences including depression, anxiety, suicidal thoughts, and eating disorders. Additionally, recent evidence suggests this type of victimisation could intensify existing health complications. This study investigates the opportunities provided by Internet of Medical Things (IoMT) data towards next-generation safeguarding. A new model is developed based on blockchain technology to enable real-time intervention triggered by IoMT data that can be used to detect stressful events, e.g., when bullying takes place. The model utilises private permissioned blockchain to manage IoMT data to achieve quicker and better decision-making while revolutionising aspects related to compliance, double-entry, confidentiality, and privacy. The feasibility of the model and the interaction between the sensors and the blockchain was simulated. To facilitate a close approximation of an actual IoMT environment, we clustered and decomposed existing medical sensors to their attributes, including their function, for a variety of scenarios. Then, we demonstrated the performance and capabilities of the emulator under different loads of sensor-generated data. We argue to the suitability of this emulator for schools and medical centres to conduct feasibility studies to address sensor data with disruptive data processing and management technologies.
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne
The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems to timely handle public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. On the one hand, blockchain can combat pandemics by enabling early detection of outbreaks, protecting user privacy, and ensuring reliable medical supply chain during the outbreak tracking. On the other hand, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Motivated by these, in this paper we present an extensive survey on the use of blockchain and AI for combating coronavirus (COVID-19) epidemics based on the rapidly emerging literature. First, we introduce a new conceptual architecture which integrates blockchain and AI specific for COVID-19 fighting. Particularly, we highlight the key solutions that blockchain and AI can provide to combat the COVID-19 outbreak. Then, we survey the latest research efforts on the use of blockchain and AI for COVID-19 fighting in a wide range of applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.
Open access
5 source records
Blockchain Technology Applications and Security
COVID-19 diagnosis using AI
Artificial Intelligence in Healthcare and Education