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Special Issue "Artificial Intelligence and Technologies in Pandemic Management"

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".

Deadline for manuscript submissions: closed (30 October 2021).

Special Issue Editors

Prof. Dr. Kum Fai Yuen
E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: technology and innovation management; health behaviour and management; consumer psychology and behaviour; maritime transport
Special Issues, Collections and Topics in MDPI journals
Dr. Xueqin Wang
E-Mail Website
Guest Editor
Department of International Logistics, Chung-Ang University, Seoul 06974, Korea
Interests: logistics management; sustainable shipping practices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

As a result of the COVID-19 pandemic, a renewed emphasis has been placed on pandemic management. As an important measure, artificial intelligence (AI) and related technologies have been introduced to reduce the risk of spreading the virus, help businesses to remain successful and comply with health regulations, and improve the resilience of communities. For example, AI has been employed to produce dynamic, predictive heatmaps, ease strain on healthcare systems, enforce social distancing, and predict traffic and crowd movement. Similarly, some contactless technologies that have been employed for public health management purposes including remote tracing, online shopping and contactless deliveries, digital or contactless payments, remote working, distance learning, telehealth, online entertainment, robots, and drones. 

Undoubtedly, AI and related technologies are critical to public health management and are increasingly being integrated into various aspects of society. This trend is likely to continue into the post-COVID-19 era. 

This Special Issue aims to bring together recent theoretical, applied, or methodological studies concerning the intersections between AI and related technologies and public health or pandemic management. All topics addressing the interface between AI and related technologies and pandemic management, such as public policy, economic, societal, business, environmental, legal, and security concerns and issues, are welcome. 

Possible topics for this Special Issue include, but are not limited to, the following: 

  • Deployment of AI and related technologies
  • Efficacy of AI and related technologies
  • Societal or consumer acceptance of AI and related technologies
  • Contactless technologies for daily services
  • Interaction patterns between human and AI and related technologies
  • Design and optimisation of AI algorithm
  • Policies, practices, and business strategies to manage AI and related technologies
  • Resilience management of societies, businesses, and supply chains using health-related AI and related technologies
  • Technology-readiness and industry and workforce transformation

Prof. Dr. Kum Fai Yuen
Dr. Xueqin Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2300 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Pandemic management 
  • Public acceptance 
  • Public health 
  • Artificial intelligence 
  • Contactless technologies 
  • Service consumption 
  • Resilient society 
  • Human–computer interaction

Published Papers (4 papers)

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Research

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Article
Does COVID-19 Promote Self-Service Usage among Modern Shoppers? An Exploration of Pandemic-Driven Behavioural Changes in Self-Collection Users
Int. J. Environ. Res. Public Health 2021, 18(16), 8574; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18168574 - 13 Aug 2021
Viewed by 687
Abstract
Due to health concerns related to COVID-19, shoppers have learned to minimise social contact by adopting various contactless self-service technologies to fulfil their consumption needs. This study explores shoppers’ behavioural changes in relation to self-service, using the special research context of e-commerce self-collection [...] Read more.
Due to health concerns related to COVID-19, shoppers have learned to minimise social contact by adopting various contactless self-service technologies to fulfil their consumption needs. This study explores shoppers’ behavioural changes in relation to self-service, using the special research context of e-commerce self-collection services. By synthesising insights from the health psychology literature, this study proposes an affective-cognitive-social perspective to explain the pandemic-driven behavioural changes of self-collection users. The survey instrument is used for online data collection (n = 500), and a combined (descriptive and quantitative) method is adopted for data analysis. Our results suggest that, although with a relatively weak predictive power, the affective and cognitive appraisals of health risks lead to the reinforced usage of self-collection service. This also applies to the factors of action/coping planning and subjective norm. This study theoretically contributes to the self-service literature and creates managerial implications for retailers and logistics operators. Full article
(This article belongs to the Special Issue Artificial Intelligence and Technologies in Pandemic Management)
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Article
Using Mobile Phone Data to Estimate the Relationship between Population Flow and Influenza Infection Pathways
Int. J. Environ. Res. Public Health 2021, 18(14), 7439; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18147439 - 12 Jul 2021
Viewed by 948
Abstract
This study aimed to analyze population flow using global positioning system (GPS) location data and evaluate influenza infection pathways by determining the relationship between population flow and the number of drugs sold at pharmacies. Neural collective graphical models (NCGMs; Iwata and Shimizu 2019) [...] Read more.
This study aimed to analyze population flow using global positioning system (GPS) location data and evaluate influenza infection pathways by determining the relationship between population flow and the number of drugs sold at pharmacies. Neural collective graphical models (NCGMs; Iwata and Shimizu 2019) were applied for 25 cell areas, each measuring 10 × 10 km2, in Osaka, Kyoto, Nara, and Hyogo prefectures to estimate population flow. An NCGM uses a neural network to incorporate the spatiotemporal dependency issue and reduce the estimated parameters. The prescription peaks between several cells with high population flow showed a high correlation with a delay of one to two days or with a seven-day time-lag. It was observed that not much population flows from one cell to the outside area on weekdays. This observation may have been due to geographical features and undeveloped transportation networks. The number of prescriptions for anti-influenza drugs in that cell remained low during the observation period. The present results indicate that influenza did not spread to areas with undeveloped traffic networks, and the peak number of drug prescriptions arrived with a time lag of several days in areas with a high amount of area-to-area movement due to commuting. Full article
(This article belongs to the Special Issue Artificial Intelligence and Technologies in Pandemic Management)
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Article
How Does the Pandemic Facilitate Mobile Payment? An Investigation on Users’ Perspective under the COVID-19 Pandemic
Int. J. Environ. Res. Public Health 2021, 18(3), 1016; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18031016 - 24 Jan 2021
Cited by 13 | Viewed by 3385
Abstract
Owing to the convenience, reliability and contact-free feature of Mobile payment (M-payment), it has been diffusely adopted in China during the COVID-19 pandemic to reduce the direct and indirect contacts in transactions, allowing social distancing to be maintained and facilitating stabilization of the [...] Read more.
Owing to the convenience, reliability and contact-free feature of Mobile payment (M-payment), it has been diffusely adopted in China during the COVID-19 pandemic to reduce the direct and indirect contacts in transactions, allowing social distancing to be maintained and facilitating stabilization of the social economy. This paper aims to comprehensively investigate the technological and mental factors affecting users’ adoption intentions of M-payment under the COVID-19 pandemic, to expand the domain of technology adoption under the emergency situation. This study integrated Unified Theory of Acceptance and Use of Technology (UTAUT) with perceived benefits from Mental Accounting Theory (MAT), and two additional variables (perceived security and trust) to investigate 739 smartphone users’ adoption intentions of M-payment during the COVID-19 pandemic in China. The empirical results showed that users’ technological and mental perceptions conjointly influence their adoption intentions of M-payment during the COVID-19 pandemic, wherein perceived benefits are significantly determined by social influence and trust, corresponding with the situation of pandemic. This study initially integrated UTAUT with MAT to develop the theoretical framework for investigating users’ adoption intentions. Meanwhile, this study originally investigated the antecedents of M-payment adoption under the pandemic situation and indicated that users’ perceptions will be positively influenced when technology’s specific characteristics can benefit a particular situation. Full article
(This article belongs to the Special Issue Artificial Intelligence and Technologies in Pandemic Management)
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Review

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Review
Rise of ‘Lonely’ Consumers in the Post-COVID-19 Era: A Synthesised Review on Psychological, Commercial and Social Implications
Int. J. Environ. Res. Public Health 2021, 18(2), 404; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18020404 - 06 Jan 2021
Cited by 10 | Viewed by 2017
Abstract
Loneliness is a pervasive problem recognised as a serious social issue, and the prevailing COVID-19 pandemic has exacerbated loneliness to greater prominence and concern. We expect a rise of a massive group of ‘lonely’ consumers who are deeply entrenched in the social isolation [...] Read more.
Loneliness is a pervasive problem recognised as a serious social issue, and the prevailing COVID-19 pandemic has exacerbated loneliness to greater prominence and concern. We expect a rise of a massive group of ‘lonely’ consumers who are deeply entrenched in the social isolation caused by COVID-19. There is an urgent need to revisit the phenomenon of lonely consumers to better prepare academic researchers, public policy makers and commercial managers in the post-COVID-19 era. Thus, this study conducts a synthesised review on past studies of lonely consumers. Based on an inductive analysis of 56 articles, 74 key themes are identified. These key themes are further categorised into five major clusters by way of a co-occurrence network analysis. Respectively, the five clusters address the psychological implications related to the dynamics between nonhuman attachment and consumers’ loneliness, the commercial implications related to the paradoxical motivations of affiliation and self-affirmation in product selection and the dual information processing mechanism in response to advertisement appeals, and the social implications related to consumers’ well-being in an ageing society and the anthropomorphic companionship in a virtual world. A list of research questions is proposed that concludes the review study. Full article
(This article belongs to the Special Issue Artificial Intelligence and Technologies in Pandemic Management)
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