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This study aims to explore the adoption of contact tracing apps through a hybrid analysis of the collected data using structural equation modelling (SEM) and artificial neural networks (ANN), leading to the identification of the critical determinants for the adoption of contact tracing apps in Australia.

A research model is developed within the background of the unified theory of acceptance and use of technology (UTAUT) and the privacy calculus theory (PCT) for investigating the adoption of contact tracing apps. This model is then tested and validated using a hybrid SEM-ANN analysis of the survey data.

The study shows that effort expectancy, perceived value of information disclosure and social influence are critical for adopting contact tracing apps. It reveals that performance expectancy and perceived privacy risks are indirectly significant on the adoption through the influence of perceived value of information disclosure. Furthermore, the study finds out that facilitating condition is insignificant to the adoption of contact tracing apps.

The findings of the study can lead to the formulation of targeted strategies and policies for promoting the adoption of contact tracing apps and inform future epidemic control for better emergency management.

This study is the first attempt in integrating UTAUT and PCT for exploring the adoption of contact tracing apps in Australia. It combines SEM and ANN for analysing the survey data, leading to better understanding of the critical determinants for the adoption of contact tracing apps.

Understanding the privacy concerns of individuals in the adoption of contact tracing apps is critical for the successful control of pandemics like COVID-19. This paper explores the privacy paradox in the adoption of contact tracing apps in Australia.

A comprehensive review of the related literature has been conducted, leading to the development of a conceptual model based on the privacy calculus theory and the antecedent-privacy concern-outcome framework. Such a model is then tested and validated using structural equation modelling on the survey data collected in Australia.

The study shows that perceived benefit, perceived privacy risk and trust have significant influences on the adoption of contact tracing apps. It reveals that personal innovativeness and trust have significant and negative influences on perceived privacy risk. The study further finds out that personal innovativeness is insignificant to perceived benefit. It states that perceived ease of use has an insignificant influence on perceived privacy risk in the adoption of contact tracing apps.

This study is the first attempt to use the privacy calculus theory and the antecedent–privacy concern–outcome framework for exploring the privacy paradox in adopting contact tracing apps. This leads to a better understanding of the privacy concerns of individuals in the adoption of contact tracing apps. Such an understanding can help formulate targeted strategies and policies for promoting the adoption of contact tracing apps and inform future epidemic control through effective contact tracing for better emergency management.

During 2020, governments around the world introduced contact-tracing apps to fight the COVID-19 pandemic. In order for contact-tracing apps to be efficient tools in combatting pandemics, a significant proportion of the population has to install it. However, in many countries, the success of apps introduced during the COVID-19 pandemic has been limited due to lack of public support. This paper aims to better understand why consumers seem unwilling to install and use a contact-tracing app.

In this study, the authors test a number of determinants hypothesized to influence acceptance of contact-tracing apps based on the theory of privacy calculus (Dinev and Hart, 2006). Both perceived privacy concerns, as well as perceived hedonic, utilitarian and pro-social benefits are included. The hypotheses are tested through SEM analysis on a representative sample of 1,007 Swedish citizens.

The results indicate significant privacy concerns with using contact-tracing apps. However, this is to some extent offset by perceived hedonic and pro-social positive consequences of using the app. This study further shows that a general positive attitude towards innovation increases acceptance of the app.

The study contributes to research on consumer privacy, both in general in its application of the calculus model but also specifically in the context of contact-tracing apps. Moreover, as the results highlight which aspects that are important for consumers to accept and install an app of this kind, they also represent an important contribution to policymakers in countries around the world.

The Australian and New Zealand governments have released smartphone-based apps to complement contact tracing in the event that they face a resurgence of COVID-19 infections. The apps form part of both countries’ policies to support a return to social and economic engagement following extended lockdowns. This paper aims to investigate the extent to which the two approaches are fit for purpose and compare their functional characteristics.

Using process mapping and analysis, this paper evaluates the potential of the two apps to improve the performance of existing contact tracing systems across a range of efficiency and effectiveness criteria with an emphasis on the framework proposed by Verrall (2020).

The Bluetooth-based Australian app appears likely to assist that country’s contact tracing system to perform more efficiently and effectively in the event of a resurgence of the virus and should increase confidence in re-engagement. The New Zealand QR code-based app, however, is not well-aligned with these objectives. Its interaction with a range of other regulations and obligations, combined with the inconvenience it imposes on its users, is likely to militate against its use. Bluetooth-based apps based on interactions between individuals likely better support these population-based objectives than QR code-based location-specific apps.

This paper provides an original and extensive analysis of the functionality and effectiveness of Australia and New Zealand’s official contact-tracing apps.

The first case of coronavirus disease 2019 (COVID-19) was documented in China, and the virus was soon to be introduced to its neighboring country – South Korea. South Korea, one of the earliest countries to initiate a national pandemic response to COVID-19 with fairly substantial measures at the individual, societal and governmental level, is an interesting example of a rapid response by the Global South. The current study examines contact tracing mobile applications (hereafter, contact tracing apps) for those who were subject to self-quarantine through the lenses of dataveillance and datafication. This paper analyzes online/digital data from those who were mandatorily self-quarantined by the Korean government largely due to returning from overseas travel.

This study uses an Internet ethnography approach to collect and analyze data. To extract data for this study, self-quarantined Korean individuals' blog entries were collected and verified with a combination of crawling and manual checking. Content analysis was performed with the codes and themes that emerged. In the COVID-19 pandemic era, this method is particularly useful to gain access to those who are affected by the situation. This approach advances the author’s understandings of COVID-19 contact tracing mobile apps and the experiences of self-quarantined people who use them.

The paper shows Korean citizens' understandings and views of using the COVID-19 self-tracing application in South Korea through examining their experiences. The research argues that the application functions as a datafication tool that collects the self-quarantined people's information and performs dataveillance on the self-quarantined people. This research further offers insights for various agreements/disagreements at different actors (i.e. the self-quarantined, their families, contact tracers/government officials) in the process of contact tracing for COVID-19.

This study also provides insights into the implications of information and technology as they affect datafication and dataveillance conducted on the public. This study investigates an ongoing debate of COVID-19's contact tracing method concerning privacy and builds upon an emerging body of literature on datafication, dataveillance, social control and digital sociology.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2020-0377

Community health is placed under the limelight during the COVID-19 crisis, providing a unique context for investigating citizens' health-privacy tradeoff in accepting social surveillance technology. To elucidate this tradeoff dilemma, an extended privacy calculus framework integrated with the Health Belief Model, legislative protection, and individual collectivism was examined using the case of national contact-tracing apps.

The hypotheses were tested through PLS-SEM analysis with data collected from a survey on Bluezone – a national app in Vietnam.

The results indicated the negative impact of privacy concerns, which was offset by the positive effect of perceived benefits in using contact-tracing apps. The effect size of perceived benefits on usage frequency was twice as large as that of privacy concerns. Individual collectivism was revealed as a mitigator of the tradeoff dilemma, as it was positively associated with perceived benefits, whereas legislative protection had no such role. Citizens may perceive legislation protection as invalid when the technologies are developed, implemented, and monitored by the authorities.

The theoretical contributions lie in the extension of the privacy calculus model as well as its application in the context of mobile health apps and surveillance technology. The study empirically corroborated that the privacy calculus theory holds when technologies move along the pervasiveness spectrum. This study also provided actionable insights for policymakers and developers who advocate the mass acceptance of national contact-tracing apps.

The COVID-19 pandemic represents a unique challenge for public health worldwide. In this context, smartphone-based tracking apps play an important role in controlling transmission. However, privacy concerns may compromise the population’s willingness to adopt this mobile health (mHealth) technology. Based on the privacy calculus theory, this study aims to examine what factors drive or hinder adoption and disclosure, considering the moderating role of age and health status.

A cross-sectional survey was conducted in a European country hit by the pandemic that has recently launched a COVID-19 contact-tracing app. Data from 504 potential users was analyzed through partial least squares structural equation modeling.

Results indicate that perceived benefits and privacy concerns impact adoption and disclosure and confirm the existence of a privacy paradox. However, for young and healthy users, only benefits have a significant effect. Moreover, older people value more personal than societal benefits while for respondents with a chronical disease privacy concerns outweigh personal benefits.

The study contributes to consumer privacy research and to the mHealth literature, where privacy issues have been rarely explored, particularly regarding COVID-19 contact-tracing apps. The study re-examines the privacy calculus by incorporating societal benefits and moving from a traditional “self-focus” approach to an “other-focus” perspective. This study further adds to prior research by examining the moderating role of age and health condition, two COVID-19 risk factors. This study thus offers critical insights for governments and health organizations aiming to use these tools to reduce COVID-19 transmission rates.

The purpose of this study is to describe a comparative study of the perceptions of users and non-users of an early contact tracing application helping to prevent the spread of the COVID-19 pandemic. The unprecedented incidence of this disease warrants investigating theoretically the use of mobile contact tracing applications as a promising approach to curtail its transmission.

A consumption value-based model of the adoption and use of a contact tracing mobile application was built and tested through a cross-sectional survey conducted with 2 samples (of 309 already users and 306 non-users) in the Province of Alberta, Canada.

Utilitarian and social values together with health information seeking and perceived critical mass drive the use of the application while perceived privacy risk is an obstacle to usage for both users and non-users.

Study participants self-assessed their risk category of potential exposure to the COVID-19 virus, and this was a subjective measure including an emotional component.

No major differences in the approaches targeting users and non-users of a mobile contact tracing application to encourage its adoption and use are necessary.

Additional efforts are required to convey to people information on the benefits and current rate of use of such an application and to mitigate privacy risk concerns.

Overall, the study offers theoretical and practical contributions that may help improve the adoption and usage of contact tracing applications addressing the COVID-19 pandemic or other possible public health crises.

Despite numerous positive aspects of digital contact tracing, the implied nature of contact tracing is still viewed with skepticism. Those in favor of contact tracing often undermine various risks involved with it, while those against it often undermine its positive benefits. However, unless the government and the app makers can convince a significant section of the population to use digital contact apps, desired results cannot be achieved. This study aims to focus on analyzing the perception of citizens belonging to developing countries about digital contact tracing.

For this study, data were collected from Twitter. Tweets containing hashtag and the word “contact tracing” were crawled using Python library Tweepy. Tweets across the top five developing countries (India, Brazil, South Africa, Argentina and Columbia) with high COVID-19 cases were collected for this study. After eliminating tweets of other languages, we selected 50,000 unique English tweets for this study. Using the machine learning algorithm, we have detected the sentiment of all the tweets belonging to each country. Structural topic modeling was performed for the tweets to understand the concerns shared by citizens of the developing countries about digital contact tracing.

The study was conducted in two parts. Study 1 results show that Indians and Brazilians citizens record more negative sentiments toward “digital contact tracing” than other major developing countries. Surprisingly, the citizens of India and Brazil also records more positive sentiments about contact tracing. This shows the polarized nature of the population of both countries while dealing with digital contact tracing. Overall, only 33.3% of total tweets were positively related to contact tracing, while 53.7% of the total tweets were neutral. Study 2 results show that factors such as the reliability of the contact tracing apps, contact tracing may lead to unnecessary panic, invasion of privacy and data misuse as the prominent reasons why the citizens of the five countries feel pessimistic about contact tracing.

After the COVID-19 strikes, numerous studies were conducted to analyze and suggest the best possible way of implementing digital contact tracing to curb COVID. However, only a handful of studies were conducted examining how the general public perceives the concept of digital contact tracing, especially pertaining to developing countries. This study fills that gap.

Digital contact tracing technologies are critical to the fight against COVID-19 in many countries including the UK. However, a number of ethical, legal and socio-economic concerns that can affect uptake of the app have been raised. The purpose of this research is to explore the perceptions of the UK digital contact tracing app in the Black, Asian and Minority Ethnic (BAME) community in Leicester and how this can affect its deployment and implementation.

Data was collected through virtual focus groups in Leicester, UK. A total of 28 participants were recruited for the study. All participants are members of the BAME community, and data was thematically analysed with NVivo 11.

A majority of the participants were unwilling to download and use the app owing to legal and ethical concerns. A minority were willing to use the app based on the need to protect public health. There was a general understanding that lack of uptake will negatively affect the fight against COVID-19 in BAME communities and an acknowledgement of the need for the government to rebuild trust through transparency and development of regulatory safeguards to enhance privacy and prevent misuse.

To the best of the authors’ knowledge, the research makes original contributions being the first robust study conducted to explore perceptions of marginalised communities, particularly BAME which may be adversely impacted by the deployment of the app. By exploring community-based perceptions, this study further contributes to the emerging citizens’ perceptions on digital contact tracing which is crucial to the effectiveness and the development of an efficient, community-specific response to public attitudes towards the app. The findings can also help the development of responsible innovation approaches that balances the competing interests of digital health interventions with the needs and expectations of the BAME community in the UK.