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Contact tracing applications (CTAs) have been presented as important tools in the fight against the Covid-19 pandemic. In France, the government developed the ‘StopCovid' CTA which later became ‘TousAntiCovid.' This research aims at understanding the determinants of the use of this CTA and of the intention to integrate the health pass. To do that, this study focuses on the perceived value of its use based on the privacy calculus theory. A quantitative study was conducted using a sample of 779 French people. The results show that the use of the CTA and the intention to integrate the health pass are influenced, as hypothesized, by perceived value, distrust towards the government, and personal innovativeness. Perceived value is positively influenced by social and individual benefits, as well as social influence, and, to a lesser extent, negatively influenced by social risks but not by individual risks.
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PurposeCommunity 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.Design/methodology/approachThe hypotheses were tested through PLS-SEM analysis with data collected from a survey on Bluezone – a national app in Vietnam.FindingsThe 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.Originality/valueThe 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.
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The reliance on data donation from citizens as a driver for research, known as citizen science, has accelerated during the Sars-Cov-2 pandemic. An important enabler of this is Internet of Things (IoT) devices, such as mobile phones and wearable devices, that allow continuous data collection and convenient sharing. However, potentially sensitive health data raises privacy and security concerns for citizens, which research institutions and industries must consider. In e-commerce or social network studies of citizen science, a privacy calculus related to user perceptions is commonly developed, capturing the information disclosure intent of the participants. In this study, we develop a privacy calculus model adapted for IoT-based health research using citizen science for user engagement and data collection. Based on an online survey with 85 participants, we make use of the privacy calculus to analyse the respondents' perceptions. The emerging privacy personas are clustered and compared with previous research, resulting in three distinct personas which can be used by designers and technologists who are responsible for developing suitable forms of data collection. These are the 1) Citizen Science Optimist, the 2) Selective Data Donor, and the 3) Health Data Controller. Together with our privacy calculus for citizen science based digital health research, the three privacy personas are the main contributions of this study.
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PurposeToday, contactless businesses are becoming part of the "new normal” in daily life. Augmented reality-based services (ARBS) thus provide a mechanism for contactless commerce, offering customers access to sensory experiences, especially during the COVID-19 pandemic. However, privacy can be a key concern when consumers decide whether to continue using ARBS. Thus, drawing on the Appraisal Tendency Framework (ATF), the study aims to examine how augmentation quality (Aug-Q), discrete emotions (joy and frustration) and privacy perceptions influence users' ARBS continuing use intention.Design/methodology/approachA survey methodology with a well-designed online questionnaire was used for data collection. The data were analyzed using a structural equation model with Amos v. 22.0 software.FindingsThis study demonstrated that Aug-Q had a significant positive impact on joy and a significant negative impact on frustration. Additionally, joy was positively associated with the perception of privacy benefits and ARBS continuing use intention, while frustration was negatively associated with the perception of privacy benefits and ARBS continuing use intention. The results also indicate that (perceived privacy risks) PPR–benefits predict the likelihood of ARBS continuing use intention.Originality/valueThis study enhances understanding of users' ARBS continuing use intention from an integrative perspective based on the ATF, thus identifying the Aug-Q-induced emotions that subsequently influence privacy trade-offs and predict users' ARBS continuing use intention. The results provide evidence that privacy and emotions can be key determinants when consumers decide whether to continue using ARBS. The findings of this research may be beneficial for commercial companies in preventing the loss of ARBS users.
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Purpose>This study aims to empirically examine how consumer privacy concerns (CPC) impact smartphone usage for financial transactions. The study also investigates the moderating impact of regulations on this action.Design/methodology/approach>With the inputs from literature and related privacy theories, a theoretical model was developed. The model was later empirically validated using the partial least squares structural equation modeling technique with 367 respondents from India.Findings>The study finds that CPC significantly impacts on consumer behavior in using smartphones for financial transactions. The study also highlights that regulation has a moderating impact on consumer usage of smartphones for financial transactions.Research limitations/implications>This study provides valuable inputs to smartphone service providers, practitioners, regulatory authorities and policymakers on appropriate and secure usage of smartphones by consumers, ensuring privacy protection while making financial transactions.Originality/value>This study provides a unique model showing the antecedents of CPC to impact the behavioral reaction of smartphone users mediated through the ingredients of privacy calculus theory. Besides, this study analyzes the moderating effects of regulation on the use of smartphones for financial transactions. This is also a novel approach of this study.
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Purpose>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.Design/methodology/approach>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.Findings>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.Originality/value>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.
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During the COVID-19 pandemic, social media use increased significantly, and news media also reported increased levels of social shaming for behaviors that were now deemed high-risk for spreading or contracting the virus. This study examines how this pandemic-afflicted environment changed what and how individuals disclosed online during the 2020 holiday season. Using data collected at two time periods in December 2020 from Facebook and Instagram users, the data show that social calculus constructs comprise most of the significant predictors for online self-disclosure; evaluation apprehension is also a significant moderator. In a post-hoc analysis with 2019 disclosure data, this study finds that most of the significant predictors of behavior arise from privacy calculus, providing evidence of a shift in the salient predictors of online self-disclosure. The implications of this research to businesses and future research directions are discussed.
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Purpose 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. Design/methodology/approach The hypotheses were tested through PLS-SEM analysis with data collected from a survey on Bluezone - a national app in Vietnam. Findings 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. Originality/value 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.
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Purpose: 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. Design/methodology/approach: 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. Findings: 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. Originality/value: 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. © 2022, Emerald Publishing Limited.
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Taiwan has been a world leader in controlling the spread of SARS-CoV-2 during the COVID-19 pandemic. Recently, the Taiwan Government launched its COVID-19 tracing app, 'Taiwan Social Distancing App'; however, the effectiveness of this tracing app depends on its acceptance and uptake among the general population. We measured the acceptance of three hypothetical tracing technologies (telecommunication network tracing, a government app, and the Apple and Google Bluetooth exposure notification system) in four nationally representative Taiwanese samples. Using Bayesian methods, we found a high acceptance of all three tracking technologies, with acceptance increasing with the inclusion of additional privacy measures. Modeling revealed that acceptance increased with the perceived technology benefits, trust in the providers' intent, data security and privacy measures, the level of ongoing control, and one's level of education. Acceptance decreased with data sensitivity perceptions and a perceived low policy compliance by others among the general public. We consider the policy implications of these results for Taiwan during the COVID-19 pandemic and in the future.
Subject(s)
COVID-19 , Bayes Theorem , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Pandemics/prevention & control , SARS-CoV-2 , Taiwan/epidemiology , TechnologyABSTRACT
On June 16, 2020, the German government issued a coronavirus disease 19 (COVID-19) contact-tracing app whose privacy settings were fiercely debated in advance. Contrary, potential benefits regarding the acceleration of contact tracing were advertised. This study investigated the relative importance of privacy concerns and perceived benefits in relation to the decision to use the app adopting a privacy calculus perspective extended by trust in app privacy and technological knowledge about the app. Results of a representative German sample (N = 952) revealed that privacy concerns were negatively related to app usage, and perceived benefits and knowledge were positively related to actual app adoption. Additionally, perceiving app benefits was the most important factor for (continued) usage intention, while privacy concerns did not play a role anymore. Trust was strongly negatively associated with privacy concerns and strongly positively with perceived benefits. Results are discussed concerning consequences for communication strategies when launching technology whose adoption should help in mitigating dangers of pandemics. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
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We propose a conceptual model of acceptance of contact tracing apps based on the privacy calculus perspective. Moving beyond the duality of personal benefits and privacy risks, we theorize that users hold social considerations (i.e., social benefits and risks) that underlie their acceptance decisions. To test our propositions, we chose the context of COVID-19 contact tracing apps and conducted a qualitative pre-study and longitudinal quantitative main study with 589 participants from Germany and Switzerland. Our findings confirm the prominence of individual privacy calculus in explaining intention to use and actual behavior. While privacy risks are a significant determinant of intention to use, social risks (operationalized as fear of mass surveillance) have a notably stronger impact. Our mediation analysis suggests that social risks represent the underlying mechanism behind the observed negative link between individual privacy risks and contact tracing apps' acceptance. Furthermore, we find a substantial intention–behavior gap.
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The technology monitoring measures play an important role in COVID-19's prevention and control in China. However, some residents are unwilling to be monitored, and their willingness to disclose information is low, which hinders the promotion of technology monitoring. This research aims to analyze the influencing factors of residents' privacy information disclosure intention in epidemic environments based on the privacy calculus theory. Firstly, this research reviews the related research on privacy calculus, puts forward research hypotheses, and establishes a conceptual model. Then, the data were collected by questionnaire and the reliability and validity of the scale used were tested. Finally, this research uses the software of MPLUS to verify the overall fit of the model, and test the significance of the hypotheses. The research results show that information sensitivity and self-perceived efficiency will affect the privacy calculation, and then affect the residents' privacy information disclosure intention, and subjective norms, self-perceived efficacy, perceived benefits, and perceived risks will directly affect the residents' privacy information disclosure intention. These conclusions can provide guidance for the formulation of the promotion plan of technology monitoring, help the government to promote technology monitoring, improve the epidemic prevention and control ability of the society. © 2021 ACM.
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OBJECTIVE: The study sought to develop and empirically validate an integrative situational privacy calculus model for explaining potential users' privacy concerns and intention to install a contact tracing mobile application (CTMA). MATERIALS AND METHODS: A survey instrument was developed based on the extant literature in 2 research streams of technology adoption and privacy calculus. Survey participants (N = 853) were recruited from all 50 U.S. states. Partial least squares structural equation modeling was used to validate and test the model. RESULTS: Individuals' intention to install a CTMA is influenced by their risk beliefs, perceived individual and societal benefits to public health, privacy concerns, privacy protection initiatives (legal and technical protection), and technology features (anonymity and use of less sensitive data). We found only indirect relationships between trust in public health authorities and intention to install CTMA. Sex, education, media exposure, and past invasion of privacy did not have a significant relationship either, but interestingly, older people were slightly more inclined than younger people to install a CTMA. DISCUSSION: Our survey results confirm the initial concerns about the potentially low adoption rates of CTMA. Our model provides public health agencies with a validated list of factors influencing individuals' privacy concerns and beliefs, enabling them to systematically take actions to address these identified issues, and increase CTMA adoption. CONCLUSIONS: Developing CTMAs and increasing their adoption is an ongoing challenge for public health systems and policymakers. This research provides an evidence-based and situation-specific model for a better understanding of this theoretically and pragmatically important phenomenon.
Subject(s)
COVID-19 , Contact Tracing , Mobile Applications , Privacy , Trust , Adult , Aged , Contact Tracing/methods , Female , Humans , Male , Middle Aged , Pandemics , Psychological Theory , Surveys and Questionnaires , United StatesABSTRACT
Taiwan has been successful in controlling the spread of SARS-CoV-2 during the COVID-19 pandemic; however, without a vaccine the threat of a second outbreak remains. Young adults who show few to no symptoms when infected have been identified in many countries as driving the virus' spread through unidentifiable community transmission. Mobile tracking technologies register nearby contacts of a user and notifies them if one later tests positive to the virus, potentially solving this issue; however, the effectiveness of these technologies depends on their acceptance by the public. The current study assessed attitudes towards three tracking technologies (telecommunication network tracking, a government app, and Apple and Google's Bluetooth exposure notification system) among four samples of young Taiwanese adults (aged 25 years or younger). Using Bayesian methods, we find high acceptance for all three tracking technologies (>75%), with acceptance for each technology surpassing 90% if additional privacy measures were included. We consider the policy implications of these results for Taiwan and similar cultures.