Building Better Cities: Evaluating the Effect of Circular Economy City Construction on Air Quality via a Quasi-Natural Experiment.

The resource utilization of a circular economy should reflect both economic and environmental values. Resource utility can be measured by GDP in the short term, while environmental value is challenging to measure; that is, the improvement in air quality is not effectively evaluated. In order to examine this initiative, using China's pilot cities of circular economy as a quasi-natural experiment, we construct a difference-in-difference (DID) strategy for estimation. The results demonstrate the following: (1) the pollutant emissions of pilot cities decline by 2.92 percentage points (p < 0.01) compared to unpiloted cities, (2) the policies on pilot cities more rapidly enhanced air quality for central cities and those with a low level of economic development, and (3) pilot cities significantly enhance air quality by decreasing energy consumption per unit of GDP. We provide the first empirical evidence of the effectiveness of circular economy pilot cities in improving air quality.

Understanding terror states of online users in the context of COVID-19: An application of Terror Management Theory.

The COVID-19 pandemic has provided psych challenges for many in society. One such challenge is the anxiety that is created in many people faced with the risk of death from the disease. Another issue is understanding how individuals cope psychologically with the threat of death from the disease. In this study we examine the manifestation of death anxiety and various coping mechanisms through the lens of terror management theory (TMT) and online platforms. We take a novel approach to testing the theory using big data analytics and machine learning, focusing on the user-generated content of Twitter users. Based on a sample of all tweets in the UK mentioning COVID-19 terms over a 5-month period, we evaluate dictionary mentions of anxiety and death, and various TMT defense mechanisms, and calculate the pattern of latent death anxiety or 'terror' states of Twitter users via Hidden Markov Models. The research identifies four online 'terror' states, with high death and anxiety mentions during the peak of the pandemic. Further we examine various TMT defense mechanisms that have been proposed in the literature for coping with death anxiety and find that online social connection, achievement and religion all play important roles in improving the model and explaining movement between states. The paper concludes with various implications of the study for future research and practice.

Stuck in the past or living in the present? Temporal focus and the spread of COVID-19.

Research has shown that the temporal focus of individuals can have a real effect on behavior. In the context of the COVID-19 pandemic, this study posits that temporal focus will affect adherence behavior regarding health control measures, such as social distancing, hand washing and mask wearing, which will be manifested through the degree of spread of COVID-19. It is suggested that social media can provide an indicator of the general temporal focus of the population at a particular time. In this study, we examine the temporal focus of Twitter text data and the number of COVID-19 cases in the US over a 317-day period from the inception of the pandemic, using text analytics to classify the temporal content of 0.76 million tweets. The data is then analyzed using dynamic regression via advanced ARIMA modelling, differencing the data, removing weekly seasonality and creating a stationary time series. The result of the dynamic regression finds that past orientation does indeed have an effect on the growth of COVID-19 cases in the US. However, a present focus tends to reduce the spread of COVID cases. Future focus had no effect in the model. Overall, the research suggests that detecting and managing temporal focus could be an important tool in managing public health during a pandemic.

Big Data Analytics in the Fight against Major Public Health Incidents (Including COVID-19): A Conceptual Framework.

Major public health incidents such as COVID-19 typically have characteristics of being sudden, uncertain, and hazardous. If a government can effectively accumulate big data from various sources and use appropriate analytical methods, it may quickly respond to achieve optimal public health decisions, thereby ameliorating negative impacts from a public health incident and more quickly restoring normality. Although there are many reports and studies examining how to use big data for epidemic prevention, there is still a lack of an effective review and framework of the application of big data in the fight against major public health incidents such as COVID-19, which would be a helpful reference for governments. This paper provides clear information on the characteristics of COVID-19, as well as key big data resources, big data for the visualization of pandemic prevention and control, close contact screening, online public opinion monitoring, virus host analysis, and pandemic forecast evaluation. A framework is provided as a multidimensional reference for the effective use of big data analytics technology to prevent and control epidemics (or pandemics). The challenges and suggestions with respect to applying big data for fighting COVID-19 are also discussed.

Information management research and practice in the post-COVID-19 world.

COVID-19 has radically transformed many aspects of human life and global society both now and for many years to come. A key aspect of the transformation has been increased digitalization and the accelerated implementation of previously predicted trends that have been discussed for many years in the information management literature. Human endeavour has encouraged us to adapt to the "new normal" through immediate necessity in areas such as work, education, healthcare, entertainment and leisure, and online commerce. This new environment has provided unprecedented opportunities for the information management research community to develop research that will have a significant impact on practice in these and other areas. We are essentially at the pinnacle of new developments in the digital space and must seek to develop exemplars that can help to signpost the future direction of digital global society for the benefit of all. Notwithstanding, the problems of digitalization have also been exacerbated and must be further understood and ameliorated in the post-COVID world. This paper examines opportunities and problems in information management brought about by the COVID-19 pandemic. It details implications for research and practice.

A Secure Occupational Therapy Framework for Monitoring Cancer Patients' Quality of Life.

Once diagnosed with cancer, a patient goes through a series of diagnosis and tests, which are referred to as "after cancer treatment". Due to the nature of the treatment and side effects, maintaining quality of life (QoL) in the home environment is a challenging task. Sometimes, a cancer patient's situation changes abruptly as the functionality of certain organs deteriorates, which affects their QoL. One way of knowing the physiological functional status of a cancer patient is to design an occupational therapy. In this paper, we propose a blockchain and off-chain-based framework, which will allow multiple medical and ambient intelligent Internet of Things sensors to capture the QoL information from one's home environment and securely share it with their community of interest. Using our proposed framework, both transactional records and multimedia big data can be shared with an oncologist or palliative care unit for real-time decision support. We have also developed blockchain-based data analytics, which will allow a clinician to visualize the immutable history of the patient's data available from an in-home secure monitoring system for a better understanding of a patient's current or historical states. Finally, we will present our current implementation status, which provides significant encouragement for further development.

Understanding plastics pollution: The role of economic development and technological research.

Our world is awash with plastic. The massive increase in plastics production, combined with a shift to single-use, disposable plastics and widespread mismanagement of plastic waste, has created a huge "tragedy of the commons" (Hardin, 1968) in our oceans, seas and waterways. Plastics pollution is now a global externality that damages ecosystems, curtails biodiversity and ultimately has the potential to affect everyone on the planet. Although waste output is often modelled separately from environmental pollution in research, in the case of plastics, the waste problem has become one of global pollution. In this paper, we model the relationship between mismanaged plastic waste1 and income per capita for 151 countries, and for the first time find empirical support for the environmental Kuznets curve using plastics pollution data. Further, we find support for the hypothesis that a key instrument for reducing plastics pollution is investment in scientific and technological research. The paper concludes with a discussion of the results, limitations, and implications for future research and practice.

Experiences in case mix implementation: a case study.

The health sector, being information-intensive, has tremendous potential for harnessing the power of information systems (IS). However, ironically, it is also one of the late-comers to the information-revolution. Only in the last two decades have UK hospitals started to become heavy investors in IS, led by Government initiatives to provide overarching information infrastructure and to make public sector organisations more accountable. One of these was the Resource Management Initiative, accompanied by the Case Mix IS - an organisation-wide system to provide clinical and management audit. Case Mix experiences in UK hospitals have typically been poorly documented, and those that have, paint a grim picture. This paper focuses on a detailed qualitative case study of a UK hospital that had relative success in implementation. As such, it provides a number of lessons learnt for other hospitals embarking on similar projects.