Investigating privacy concerns related to mobile augmented reality Apps – A vignette based online experiment

Context-Contingent Privacy Concerns and Exploration of the Privacy Paradox in the Age of AI, Augmented Reality, Big Data, and the Internet of Things: Systematic Review

BACKGROUND

Despite extensive research into technology users' privacy concerns, a critical gap remains in understanding why individuals adopt different standards for data protection across contexts. The rise of advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR), and big data has created rapidly evolving and complex privacy landscapes. However, privacy is often treated as a static construct, failing to reflect the fluid, context-dependent nature of user concerns. This oversimplification has led to fragmented research, inconsistent findings, and limited capacity to address the nuanced challenges posed by these technologies. Understanding these dynamics is especially crucial in fields such as digital health and informatics, where sensitive data and user trust are central to adoption and ethical innovation.

OBJECTIVE

This study synthesized existing research on privacy behaviors in emerging technologies, focusing on IoT, AI, AR, and big data. Its primary objectives were to identify the psychological antecedents, outcomes, and theoretical frameworks explaining privacy behavior, and to assess whether insights from traditional online privacy literature, such as e-commerce and social networking, apply to these advanced technologies. It also advocates a context-dependent approach to understanding privacy.

METHODS

A systematic review of 179 studies synthesized psychological antecedents, outcomes, and theoretical frameworks related to privacy behaviors in emerging technologies. Following established guidelines and using leading research databases such as ScienceDirect (Elsevier), SAGE, and EBSCO, studies were screened for relevance to privacy behaviors, focus on emerging technologies, and empirical grounding. Methodological details were analyzed to assess the applicability of traditional privacy findings from e-commerce and social networking to today's advanced technologies.

RESULTS

The systematic review revealed key gaps in the privacy literature on emerging technologies, such as IoT, AI, AR, and big data. Contextual factors, such as data sensitivity, recipient transparency, and transmission principles, were often overlooked, despite their critical role in shaping privacy concerns and behaviors. The findings also showed that theories developed for traditional technologies often fall short in addressing the complexities of modern contexts. By synthesizing psychological antecedents, behavioral outcomes, and theoretical frameworks, this study underscores the need for a context-contingent approach to privacy research.

CONCLUSIONS

This study advances understanding of user privacy by emphasizing the critical role of context in data sharing, particularly amid ubiquitous and emerging health technologies. The findings challenge static views of privacy and highlight the need for tailored frameworks that reflect dynamic, context-dependent behaviors. Practical implications include guiding health care providers, policy makers, and technology developers toward context-sensitive strategies that build trust, enhance data protection, and support ethical digital health innovation.

TRIAL REGISTRATION

PROSPERO CRD420251037954; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251037954.

A privacy calculus model for contact tracing apps: Analyzing the use behavior of the German Corona-Warn-App with a longitudinal user study

The SARS-CoV-2 pandemic is a pressing societal issue today. The German government promotes a contract tracing app named Corona-Warn-App (CWA), aiming to change citizens' health behaviors during the pandemic by raising awareness about potential infections and enable infection chain tracking. Technical implementations, citizens' perceptions, and public debates around apps differ between countries, e. g., in Germany there has been a huge discussion on potential privacy issues of the app. Thus, we analyze effects of privacy concerns regarding the CWA, perceived CWA benefits, and trust in the German healthcare system to answer why citizens use the CWA. In our initial conference publication at ICT Systems Security and Privacy Protection - 37th IFIP TC 11 International Conference, SEC 2022, we used a sample with 1752 actual users and non-users of the CWA and and support for the privacy calculus theory, i. e., individuals weigh privacy concerns and benefits in their use decision. Thus, citizens privacy perceptions about health technologies (e. g., shaped by public debates) are crucial as they can hinder adoption and negatively affect future fights against pandemics. In this special issue, we adapt our previous work by conducting a second survey 10 months after our initial study with the same pool of participants (830 participants from the first study participated in the second survey). The goal of this longitudinal study is to assess changes in the perceptions of users and non-users over time and to evaluate the influence of the significantly lower hospitalization and death rates on the use behavior which we could observe during the second survey. Our results show that the privacy calculus is relatively stable over time. The only relationship which significantly changes over time is the effect of privacy concerns on the use behavior which significantly decreases over time, i. e., privacy concerns have a lower negative effect one the CWA use indicating that it did not play such an important role in the use decision at a later point in time in the pandemic. We contribute to the literature by introducing one of the rare longitudinal analyses in the literature focusing on the privacy calculus and changes over time in the relevant constructs as well as the relationships between the calculus constructs and target variables (in our case use behavior of a contact tracing app). We can see that the explanatory power of the privacy calculus model is relatively stable over time even if strong externalities might affect individual perceptions related to the model.

The Effect of Augmented Reality and Privacy Priming in a Fashion-Related App: An Application of Technology Acceptance Model

In this research, we tested (a) the effects of augmented reality (AR) and (b) how the effects of AR could be moderated by privacy perceptions. We used a 2 eyewear app type (AR vs. non-AR) by 2 privacy priming (prime vs. no prime) between-subject experimental design, and 114 Korean adults participated in the experiment. Results showed that AR had a main effect on perceived ease of use but not on perceived usefulness. Instead, the effect of AR on perceived usefulness was moderated by privacy priming such that the positive effect of AR on perceived usefulness was weaker when privacy concern was salient. Moreover, the results provided support for a moderated mediation model in which the indirect effect of AR on intent to use the app via perceived usefulness was moderated by privacy priming. Theoretical and practical implications are discussed.

How Augmented Reality Increases Engagement Through Its Impact on Risk and the Decision Process

Augmented reality (AR) overcomes one of the main limitations of e-commerce, such as the prepurchase trial. The consumer can virtually see how a product is integrated into the real world through this technology. Therefore, AR may reduce the perceived risk of buying a product online. Despite existing research, the impact of AR on the consumer decision process needs to be further explored. Consequently, this research aims to understand the impact of AR on the perception of risk and the purchase decision process, considering decision comfort and decision confidence. Through a between-subjects experiment, the results show that AR reduces the risk of online shopping. However, it has no direct effect on the decision process. Reducing risk and the comfort it brings generates decision confidence and satisfaction with the shopping experience. This satisfaction will generate engagement toward the online shop platform. The research highlights the process through which AR impacts the decision-making process. The implications for AR marketing theory and managerial implications in the age of the metaverse are discussed.

Why Individuals Do (Not) Use Contact Tracing Apps: A Health Belief Model Perspective on the German Corona-Warn-App

The World Health Organization declared the emergence of the novel coronavirus (SARS-CoV-2) in January 2020. To trace infection chains, Germany launched its smartphone contact tracing app, the "Corona-Warn-App" (CWA), in June 2020. In order to be successful as a tool for fighting the pandemic, a high adoption rate is required in the population. We analyse the respective factors influencing app adoption based on the health belief model (HBM) with a cross-sectional online study including 1752 participants from Germany. The study was conducted with a certified panel provider from the end of December 2020 to January 2021. This model is primarily known from evaluations of medical treatments, such as breast cancer screenings, but it was rarely applied in prior work for a health-related information system such as the CWA. Our results indicate that intrinsic and extrinsic motivation to use the CWA are the strongest drivers of app use. In contrast, technical barriers, privacy concerns and lower income are the main inhibitors. Our findings contribute to the literature on the adoption of contact tracing apps by questioning actual users and non-users of the CWA, and we provide valuable insights for policymakers regarding influences of adoption and potential user groups of disease prevention technologies in times of pandemics.

Proxies to the monthly active user number of Geo AR Mobile games - online search volume as a proposal

Mobile game metrics have received attention since the emergence of big data technology and data-based decision-making. Among different metrics, the monthly active user number is usually significant because it shows the level of players' engagement and the profit of this game as a business. Therefore, the monthly active user number is valuable for researchers, analysts, and decision-makers interested in the mobile game industry. However, the actual monthly active user number data typically have the accuracy, accessibility, granularity, and cost problems. Therefore, a proxy to the monthly active user number would be helpful to facilitate the decision-making process. This paper proposes to capture user activity through the searches on the Internet from an information-seeking perspective. And the online search volume, wiki page view, social media posts and views are proposed as potential proxies. This paper proposes that the online search volume is an acceptable proxy for the monthly active user number in the context of Geo Augmented Reality (AR) mobile games through data analysis.

Human Autonomy in the Era of Augmented Reality—A Roadmap for Future Work

Augmented reality (AR) has found application in online games, social media, interior design, and other services since the success of the smartphone game Pokémon Go in 2016. With recent news on the metaverse and the AR cloud, the contexts in which the technology is used become more and more ubiquitous. This is problematic, since AR requires various different sensors gathering real-time, context-specific personal information about the users, causing more severe and new privacy threats compared to other technologies. These threats can have adverse consequences on information self-determination and the freedom of choice and, thus, need to be investigated as long as AR is still shapeable. This communication paper takes on a bird’s eye perspective and considers the ethical concept of autonomy as the core principle to derive recommendations and measures to ensure autonomy. These principles are supposed to guide future work on AR suggested in this article, which is strongly needed in order to end up with privacy-friendly AR technologies in the future.