21 research outputs found

    Mobile Cryptocurrency for Development in Asia-Moderating Effects of Advantage, Complexity, and Compatibility

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    Information and communication technologies (ICTs) have been proven to promote the development of countries and regions. Asia is one of the leading regions in adopting new ICTs like mobile payment, artificial intelligence, and blockchain. The innovative technologies, relevant business values, and impacts related to blockchain are overestimated in the short term yet underestimated for a long time. While the blockchain is in the hype of both research and practice, there is minimal research related to the blockchain adoption. Among many blockchain-based applications, cryptocurrency been widely utilized in Asia. This Emergent Research Forum (ERF) Paper provides preliminary research in understanding how blockchain-based cryptocurrency revolutionizes ICT for development in Asia. This research introduces a model that considers Cryptocurrency/Bitcoin Innovation Factors (BIF), including cryptocurrency advantage, cryptocurrency complexity, and cryptocurrency compatibility as moderators. The survey method is selected and will be conducted in the future

    Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data

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    Background: Despite scientific evidence supporting the importance of wearing masks to curtail the spread of COVID-19, wearing masks has stirred up a significant debate particularly on social media. Objective: This study aimed to investigate the topics associated with the public discourse against wearing masks in the United States. We also studied the relationship between the anti-mask discourse on social media and the number of new COVID-19 cases. Methods: We collected a total of 51,170 English tweets between January 1, 2020, and October 27, 2020, by searching for hashtags against wearing masks. We used machine learning techniques to analyze the data collected. We investigated the relationship between the volume of tweets against mask-wearing and the daily volume of new COVID-19 cases using a Pearson correlation analysis between the two-time series. Results: The results and analysis showed that social media could help identify important insights related to wearing masks. The results of topic mining identified 10 categories or themes of user concerns dominated by (1) constitutional rights and freedom of choice; (2) conspiracy theory, population control, and big pharma; and (3) fake news, fake numbers, and fake pandemic. Altogether, these three categories represent almost 65% of the volume of tweets against wearing masks. The relationship between the volume of tweets against wearing masks and newly reported COVID-19 cases depicted a strong correlation wherein the rise in the volume of negative tweets led the rise in the number of new cases by 9 days. Conclusions: These findings demonstrated the potential of mining social media for understanding the public discourse about public health issues such as wearing masks during the COVID-19 pandemic. The results emphasized the relationship between the discourse on social media and the potential impact on real events such as changing the course of the pandemic. Policy makers are advised to proactively address public perception and work on shaping this perception through raising awareness, debunking negative sentiments, and prioritizing early policy intervention toward the most prevalent topics

    Blockchain Technology for Emergency Response

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    As unforeseen situations, emergencies threaten the environment, property, and people’s lives. Large emergencies are characterized by the demand for coordination of a variety of actors, such as civil defense or disaster relief. Communication and information exchange are crucial for coordination. Therefore, a solid, stable communication infrastructure is among the crucial factors for emergency response. New technologies that seem to ensure trustworthy communication must be evaluated constantly. Blockchain technology is widely applied in a broad variety of contexts and is commonly known for its decentralized and distributed governance. This is the motivation for the design and evaluation of a framework for the adoption of blockchain technology in the case of emergency response following a design science approach. Evaluation of the artifact using a specific evaluation framework clearly indicates the suitability of the case for application of blockchain technology

    Understanding the Determinants and Future Challenges of Cloud Computing Adoption for High Performance Computing

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    High performance computing (HPC) is widely recognized as a key enabling technology for advancing scientific progress, industrial competitiveness, national and regional security, and the quality of human life. Notwithstanding this contribution, the large upfront investment and technical expertise required has limited the adoption of HPC to large organizations, government bodies, and third level institutions. Recent advances in cloud computing and telecommunications have the potential to overcome the historical issues associated with HPC through increased flexibility and efficiency, and reduced capital and operational expenditure. This study seeks to advance the literature on technology adoption and assimilation in the under-examined HPC context through a mixed methods approach. Firstly, the determinants of cloud computing adoption for HPC are examined through a survey of 121 HPC decision makers worldwide. Secondly, a modified Delphi method was conducted with 13 experts to identify and prioritize critical issues in the adoption of cloud computing for HPC. Results from the quantitative phase suggest that only organizational and human factors significantly influence cloud computing adoption decisions for HPC. While security was not identified as a significant influencer in adoption decisions, qualitative research findings suggest that data privacy and security issues are an immediate and long-term concern

    Evaluating the impact of caching on the energy consumption and performance of progressive web apps

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    Context. Since today mobile devices have limited battery life, the energy consumption of the software running on them can play a strong role with respect to the success of mobile-based businesses. Progressive Web Applications (PWAs) are built using common web technologies like HTML, CSS, and JavaScript and are commonly used for providing a better user experience to mobile users. Caching is the main technique used by PWA developers for optimizing network usage and for providing a meaningful experience even when the user's device is offline. Goal. This paper aims at assessing the impact of caching on both the energy consumption and performance of PWAs. Method. We conducted an empirical experiment targeting 9 real PWAs developed by third-party developers. The experiment is designed as a 1 factor-2 treatments study, with the usage of caching as the single factor and the status of the cache as treatments (empty vs populated cache). The response variables of the experiment are (i) the energy consumption of the mobile device and (ii) the page load time of the PWAs. The experiment is executed on a real Android device running the Mozilla Firefox browser. Results. Our results show that PWAs do not consume significantly different amounts of energy when loaded either with an empty or populated cache. However, the page load time of PWAs is significantly lower when the cache is already populated, with a medium effect size. Conclusions. This study confirms that PWAs are promising in terms of energy consumption and provides evidence that caching can be safely exploited by PWA developers concerned with energy consumption. The study provides also empirical evidence that caching is an effective technique for improving the user experience in terms of page loading time of PWAs

    Goal Setting and Student Retention

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    Student retention has been a problem with which higher education institutions must face. Institutions have employed numerous different programs and services to improve student retention. This study sought to open up a new way to improve student retention by utilizing a goal-setting intervention that focused on creating SMART goals for student areas of weaknesses. This study employed the use of a quasi-experimental interrupted time series to better understand how goal-setting interventions could impact the participant attitudes correlated to retention. It was shown that goal-setting interventions had no significant impact on likelihood of retention but did exhibit improvement in client engagement with coursework, which is a positive indicator of student retention. It was concluded that more research should be done on goal-setting and student retention to better understand the impact goal-setting has on student likelihood of retention
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