This study examines the relationship between international tourism and COVID-19 cases and associated deaths in more than 90 nations. We use a cross-country regression analysis and find a positive correlation between international tourism and the cumulated level of COVID-19 confirmed cases and death by April 30, 2020. Our regression analyses show that countries exposed to high flows of international tourism are more prone to cases and deaths caused by the COVID-19 outbreak. This association is robust even after controlling for other socioeconomic determinants of COVID-19 outbreak and regional dummies. Based on our estimations, a 1% higher level of inbound and outbound tourism is associated with 1.2% and 1.4% higher levels of confirmed COVID-19 cases and death, respectively, controlling for other factors. When we normalize the number of cases and death by size of population, the statistical significance remains robust, especially for the COVID-19 deaths, while the effect size reduces.

The literature has mostly examined supply chain (SC) traceability and SC transparency separately, ignoring the mutually constitutive relationship of these two related constructs. We draw on the resource orchestration theory and the causal complexity perspective to conceptualize and validate SC traceability and SC transparency as interrelated organizational capabilities that may mutually enhance or compensate each other for competitive advantage. We constructed an original sample from two sources to empirically test this conceptualization using fuzzy set qualitative comparative analysis (fsQCA). Our empirical results reveal that the ability of firms to leverage SC traceability for a high financial performance is contingent upon creating a transparency perception of SC with a wide range of stakeholders. Our results also identified the firm size and its international presence, as having a significant bearing on the ability of firms to leverage SC traceability and SC transparency capabilities for a competitive advantage.

In this perspective paper, we want to highlight the potential benefits of incorporating digital twins to support better dementia care. In particular, we assert that, by doing so, it is possible to ensure greater precision regarding dementia care while simultaneously enhancing personalization. Digital twins have been used successfully in manufacturing to enable better prediction and tailoring of solutions to meet required needs, and thereby have enabled more effective and efficient deployment of resources. We develop a model for digital twin in the healthcare domain as a clinical decision support tool by extrapolating its current uses from the manufacturing domain. We illustrate the power of the developed model in the context of dementia. Given the rapid rise of chronic conditions and the pressures on healthcare delivery to provide high quality, cost-effective care anywhere and anytime, we assert that such an approach is consistent with a value-based healthcare philosophy and thus important as the numbers of people with dementia continues to grow exponentially and this pressing healthcare issue is yet to be optimally addressed. Further research and development in this rapidly evolving domain is a strategic priority for ensuring the delivery of superior dementia care.

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