Perceived Privacy Risk Research Articles

Cultural differences in students’ privacy concerns in learning analytics across Germany, South Korea, Spain, Sweden, and the United States

Applications of learning analytics (LA) can raise concerns from students about their privacy in higher education contexts. Developing effective privacy-enhancing practices requires a systematic understanding of students’ privacy concerns and how they vary across national and cultural dimensions. We conducted a survey study with established instruments to measure privacy concerns and cultural values for university students in five countries (Germany, South Korea, Spain, Sweden, and the United States; N = 762). The results show that students generally trusted institutions with their data and disclosed information as they perceived the risks to be manageable even though they felt somewhat limited in their ability to control their privacy. Across the five countries, German and Swedish students stood out as the most trusting and least concerned, especially compared to US students who reported greater perceived risk and less control. Students in South Korea and Spain responded similarly on all five privacy dimensions (perceived privacy risk, perceived privacy control, privacy concerns, trusting beliefs, and non-self-disclosure behavior), despite their significant cultural differences. Culture measured at the individual level affected the antecedents and outcomes of privacy concerns. Perceived privacy risk and privacy control increase with power distance. Trusting beliefs increase with a desire for uncertainty avoidance and lower masculinity. Non-self-disclosure behaviors rise with power distance and masculinity and decrease with more uncertainty avoidance. Thus, cultural values related to trust in institutions, social equality and risk-taking should be considered when developing privacy-enhancing practices and policies in higher education.

Consumers’ perceptions of the environmental and public health benefits of last mile drone delivery

ABSTRACT Using Technology Acceptance Model, Theory of Planned Behavior, and Privacy Calculus as theoretical frameworks, this study examined environmental and public health/safety dispositions and environmental and public health/safety benefits, perceived usefulness, privacy risk, and trust as they relate to U.S consumers intention to adopt drone delivery services. This study employed Partial Least Squares – Structural Equation Modeling methods and data were collected online using Amazon Mechanical Turk, resulting in 687 respondents. The results show that the intention to use drones for delivery increases if consumers perceive drone delivery to be useful. Additionally, perceived usefulness was influenced by a person’s environmental and public health/safety dispositions along with related benefits. Additionally, as a person’s perceived usefulness increases their perceived privacy risk decreases. Further, this study found that organisational trust moderates the negative effect of privacy risk on drone adoption.

Spillover effects of data breach on consumer perceptions: evidence from the E-commerce industry

PurposeThis study aims to explore the spillover effects of data breaches from a consumer perspective in the e-commerce context. Specifically, we investigate how an online retailer’s data breach affects consumers’ privacy risk perceptions of competing firms, and further how it affects shopping intention for the competitors. We also examine how the privacy risk contagion effect varies depending on the characteristics of competitors and their competitive responses.Design/methodology/approachWe conducted two scenario-based experiments with surveys. To assess the spillover effects and the moderating effects, we employed an analysis of covariance. We also performed bootstrapping-based mediation analyses using the PROCESS macro.FindingsWe find evidence for the privacy risk contagion effect and demonstrate that it negatively influences consumers’ shopping intention for a competing firm. We also find that a competitor’s cybersecurity message is effective in avoiding the privacy risk contagion effect and the competitor even benefits from it.Originality/valueWhile previous studies have examined the impacts of data breaches on customer perceptions of the breached firm, our study focuses on customer perceptions of the non-breached firms. To the best of the authors’ knowledge, this study is one of the first to provide empirical evidence for the negative spillover effects of a data breach from a consumer perspective. More importantly, this study empirically demonstrates that the non-breached competitor’s competitive response is effective in preventing unintended negative spillover in the context of the data breach.

Investigating the Role of Perceived Convenience and Perceived Privacy Risks on E-Waste Disposal Behavior among Smartphone Users in Pakistan

Investigating the Role of Perceived Convenience and Perceived Privacy Risks on E-Waste Disposal Behavior among Smartphone Users in Pakistan

What drives consumers towards shared luxury services? A comparison of sequential versus simultaneous sharing

This study extends the nascent literature on luxury services and shared luxury by delving into how consumers are drawn to shared luxury services (SLS). Through a multigroup analysis on survey data from 803 consumers, we investigate whether diverse motivations affect consumers’ attitude and purchase intentions towards two different types of SLS reflecting different levels of sharing, namely simultaneous (i.e., when they are consumed in the presence of others – high sharing) and sequential (i.e., when they are consumed successively, without the concurrent presence of others – low sharing). Hedonism and environmental consciousness emerge as the main drivers of consumers’ attitudes towards both forms of SLS. Additionally, perceived privacy risk, need for uniqueness and bandwagon effect appear to drive consumers’ attitude towards simultaneous luxury. Overall, our findings advance knowledge vis-à-vis the changing nature of luxury services by highlighting the role of sharing level in shaping consumers’ attitudes towards sharing economy offerings.

Internet Users' Willingness to Disclose Biometric Data for Continuous Online Account Protection: An Empirical Investigation

Continuous authentication has emerged as a promising approach to increase user account security for online services. Unlike traditional authentication methods, continuous authentication provides ongoing security throughout the session, protecting against session takeover attacks due to illegitimate access. The effectiveness of continuous authentication systems relies on the continuous processing of users' sensitive biometric data. To balance security and privacy trade-offs, it's crucial to understand when users are willing to disclose biometric data for enhanced account security, addressing inevitable privacy concerns and user acceptance. To address this knowledge gap, we conducted an online study with 830 participants from the U.S., aiming to investigate user perceptions towards continuous authentication across different classes of online services. Our analysis identified four groups of biometric traits that directly reflect users' willingness to disclose them. Our findings demonstrate that willingness to disclose is influenced by both the specific biometric traits and the type of online service involved. User perceptions are strongly shaped by factors such as response efficacy, perceived privacy risks associated with the biometric traits, and concerns about the service providers' handling of such data. Our results emphasize the inadequacy of one-size-fits-all solutions and provide valuable insights for the design and implementation of continuous authentication systems.

The roles of trust and privacy calculus in citizen-centric services usage: evidence from the close contact query platform in China

ABSTRACT The mechanism of the ‘privacy calculus’ between privacy risks and benefits has gained attention in e-government service, but there were few empirical studies. Trust reduces perceived risk as well as enhances perceived benefits. However, the effects of different types of trust on privacy calculus are yet undefined. Regarding above issues, we build a research model based on the theoretical framework of ‘Antecedents → Privacy Concerns → Outcomes (APCO)’, theories of privacy calculus and e-government trustworthiness typology. We analyse survey data from the Close Contact Query Platform providing citizen-centric services for COVID-19 in China. Trust in transactions and information is increased by trust in government organisations. Trust in government organisations and transactions decrease perceived privacy risks, while trust in government organisations and information enhances perceived privacy benefits. Privacy risks and benefits significantly affect usage intentions, and the effect of privacy benefits is greater. We also identified mediating effects. Our findings have important implications regarding the unexplored inner mechanism of trust, the roles of privacy calculus in e-government adoption, and the expansion of the APCO framework. We offer recommendations for citizen-centric platform developers, administrators to design citizen-centric services, and offline public servants.

COVID-19 and online teaching: mainland Chinese students encounter Taiwanese teachers

ABSTRACT The COVID-19 pandemic has transferred university lecture to online teaching around the world. In Taiwan, a blended mode of online teaching, specifically serving overseas mainland Chinese students was applied. Meanwhile, the China factor, which refers to the Chinese government exporting self-censorship to other countries, was amplified during the pandemic, because of their tightening of ideological control. In order to examine the role of China factor in the process of online teaching in Taiwan, concepts such as perceived privacy risk, digital competence, identity disruption, fear of negative evaluation and self-censorship have been integrated with the theoretical framework. An online survey targeting lecturers has been conducted and confirmed the influence of the China factor. Meanwhile, perceived privacy risk and identity disruption positively influenced the level of fear of negative evaluation. Fear of negative evaluation is positively associated with the level of self-censorship. Discussions and implications were developed.

Understanding consumers’ intentions to use QR code menus in the post-COVID-19 pandemic

PurposeThis study aims to examine the factors influencing consumers’ intentions to use QR code menus in the post-COVID-19 pandemic using the unified theory of acceptance and use of technology and rational choice theory as the theoretical foundations.Design/methodology/approachUsing a survey method, 200 data are collected from consumers who had used QR code menus in the past. Partial least squares structural equation modelling is used to analyse the data.FindingsOur findings show that performance expectancy, effort expectancy, social influence, habit and perceived privacy protection have a significant positive influence on intentions. However, facilitating conditions, hedonic motivation and perceived privacy risk do not have a significant influence on intentions.Originality/valueThis study further extends the work of previous studies by using the unified theory of acceptance and use of technology model, with additional two new predictors, namely perceived privacy protection and perceived privacy risk, to understand consumers’ intentions to use QR code menus.

A case study on the implementation of location tracking technologies for productivity monitoring: understanding workers’ acceptance and socio-technical implications

Automated real-time data collection is becoming more prevalent in construction, with workers’ location data being a pivotal component in detecting poor logistics and inefficient construction flows. However, the collection of location data for productivity monitoring raises significant concerns about privacy and wellbeing implications for workers. Implementing such technological solutions requires an understanding of how humans may respond to sensor-based automated data collection, making this a socio-technical issue. This study identifies the drivers of construction workers’ acceptance of radio-based location tracking technology for productivity measurement using a modified Technology Acceptance Model (TAM) and offers a sociotechnical understanding of technology acceptance with implications for managing how new technologies are introduced on construction projects. Using a large residential project in Lima, Peru as a case study, construction workers were monitored using Bluetooth Low Energy (BLE) technology, and data were gathered using mixed methods. A k-means clustering analysis showed two forms of acceptance among workers: supporters (37%) and acceptance with reservations (63%). Partial least squares Structural Equation Modelling (PLS-SEM) results showed that perceived usefulness and perceived stress underpinned workers’ attitudes and intention to accept the technology. Perceived privacy risk, however, emerged as the sole most significant predictor at the end of the monitoring process. Findings further suggest that workers’ acceptance of the technology is influenced by the perception that it is also beneficial for safety management. Building on the preceding, the paper highlights the need for employee orientation focused on addressing perceived privacy concerns by leveraging positive perceptions about using monitoring technologies for improving onsite safety, logistics and productivity. This requires management of construction firms to develop narratives that reflect their goals for rolling out technologies in ways that ensure workers’ buy-in, and a re-focus on problem framing and collective approaches to identifying functional and less intrusive forms of monitoring technologies.

Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study.

Wearable insulin biosensors represent a novel approach that combines the benefits of real-time glucose monitoring and automated insulin delivery, potentially revolutionizing how individuals with diabetes manage their condition. To analyze the behavioral intentions of wearable insulin biosensors among diabetes patients, the factors that drive or hinder their usage, and the implications for diabetes management and healthcare outcomes. A cross-sectional survey design was adopted in this study. The validated questionnaire included 10 factors (Performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, perceived privacy risk, and personal innovativeness) affecting the acceptance of wearable insulin sensors. A total of 248 diabetic patients who had used wearable sensors participated in the study. Performance expectancy was rated the highest (Mean = 3.84 out of 5), followed by effort expectancy (Mean = 3.78 out of 5), and trust (Mean = 3.53 out of 5). Statistically significant differences (p < 0.05) were observed with respect to socio-demographic variables including age and gender on various influencing factors and adoption intentions. PE, EE, and trust were positively associated with adoption intentions. While wearable insulin sensors are positively perceived with respect to diabetes management, issues like privacy and security may affect their adoption.

DIPA2

The world today is increasingly visual. Many of the most popular online social networking services are largely powered by images, making image privacy protection a critical research topic in the fields of ubiquitous computing, usable security, and human-computer interaction (HCI). One topical issue is understanding privacy-threatening content in images that are shared online. This dataset article introduces DIPA2, an open-sourced image dataset that offers object-level annotations with high-level reasoning properties to show perceptions of privacy among different cultures. DIPA2 provides 5,897 annotations describing perceived privacy risks of 3,347 objects in 1,304 images. The annotations contain the type of the object and four additional privacy metrics: 1) information type indicating what kind of information may leak if the image containing the object is shared, 2) a 7-point Likert item estimating the perceived severity of privacy leakages, and 3) intended recipient scopes when annotators assume they are either image owners or allowing others to repost the image. Our dataset contains unique data from two cultures: We recruited annotators from both Japan and the U.K. to demonstrate the impact of culture on object-level privacy perceptions. In this paper, we first illustrate how we designed and performed the construction of DIPA2, along with data analysis of the collected annotations. Second, we provide two machine-learning baselines to demonstrate how DIPA2 challenges the current image privacy recognition task. DIPA2 facilitates various types of research on image privacy, including machine learning methods inferring privacy threats in complex scenarios, quantitative analysis of cultural influences on privacy preferences, understanding of image sharing behaviors, and promotion of cyber hygiene for general user populations.

Hey Google, I trust you! The consequences of brand anthropomorphism in voice-based artificial intelligence contexts

Users’ increasing adoption of voice assistant services is fostering the growth of a novel strand of marketing research on the branding implications of brand anthropomorphism (BA). However, the branding outcomes of brand anthropomorphization in this research area remain underinvestigated. Accordingly, in the name-brand voice assistant (NBVA) interaction field, this study tests a model of the consequences of brand anthropomorphism, outlining the relationships among brand anthropomorphism, brand trust, and multidimensional consumer–brand engagement (CBE), i.e., the relevant cognitive, affective, and behavioral dimensions, as well as the moderating role of perceived privacy risk. A survey of young adults shows that brand anthropomorphism positively affects brand trust as well as the affective and behavioral dimensions of CBE. Furthermore, perceived privacy risk positively moderates the relationship between brand anthropomorphism and brand trust. Specifically, the influence of brand anthropomorphism on brand trust is strengthened at higher levels of perceived privacy risk. This article thus enriches the understanding of brand anthropomorphism and user VA response by exploring underresearched branding outcomes of BA in the context of NBVA interaction.

Trust in AI-augmented design: Applying structural equation modeling to AI-augmented design acceptance

With the emergence of Artificial Intelligence (AI) 2.0, computers are now equipped with new creative capabilities and are playing an increasingly significant role in design. The use of AI augmentation has the potential to enhance design performance, however, there is limited research on the acceptance of AI-augmented design. The research gap under consideration in this study is addressed by presenting an acceptance model designed for AI-augmented design. This model integrates a range of variables including perceived privacy risk, enjoyment, perceived value, perceived usefulness, perceived ease of use, perceived behavioral control, social influence, and behavioral intention. The proposed model was validated through a questionnaire survey of 249 designers in China.The results reveal that enjoyment, perceived value, perceived ease of use, perceived behavioral control, and social influence have a significant positive impact on users' intention to use AI-augmented design, while perceived privacy risk has a significant negative impact. Perceived value was found to mediate the relationship between enjoyment and behavioral intention, while perceived behavioral control play a mediation role in the relationship between social influence and behavioral intention.In conclusion, this study highlights the variables that influence the acceptance of AI-augmented design and provides valuable insights into the potential benefits and drawbacks of integrating AI technologies in design. The proposed acceptance model serves as a framework for future research in this area and can guide the development of more user-friendly and effective AI-augmented design tools and technologies.

Perceived Privacy Risks and Trust Dynamics: Rethinking Mobile Payment Adoption in Indonesia

Purpose: This research aimed to explore and understand the intricacies of mobile payments within the Indonesian context, particularly focusing on the dynamic relationship between perceived privacy risks, trust, and the intention to adopt mobile payment services. &#x0D; Design/methodology/approach: The study employed a hybrid research methodology, integrating qualitative and quantitative analyses. Specifically, this research utilized Confirmatory Factor Analysis (CFA) model that evaluated the alignment of the proposed model with the observed data. The mobile payment privacy policies were analyzed through the identification of key textual features.&#x0D; Findings: The study revealed a revealed positive relationship between certain perceived risks (psychological and financial) and trust, suggesting that certain perceived risks might inadvertently foster trust. Conversely, time risk and performance risk negatively influence trust. This research also emphasized the pivotal role of trust in shaping user intentions toward mobile payments. Further findings highlighted the complex nature of privacy risks in the context of mobile payments and the significant surge in adoption rates during the COVID-19 pandemic.&#x0D; Research limitations/implications: This research was bound by a limited dataset size, which could influence the derived results. Potential inaccuracies from incomplete questionnaires might introduce non-statistical errors. With the ever-evolving nature of mobile payments, future studies could benefit from refining the research framework and incorporating additional variables.&#x0D; Originality/value: This study uniquely delves into the mobile payment scenario in Indonesia, challenging traditional views of risk and trust and offering fresh perspectives on consumer behavior. The innovative approach to analyzing mobile payment privacy policies and the spotlight on the role of perceived risks and trust in adoption intention set it apart. Its findings serve as a blueprint for both academics and practitioners in the mobile payment domain.

Factors Affecting the Adoption of Artificial Intelligence-Enabled Virtual Assistants for Leukemia Self-Management.

The purpose of this study is to analyze the various influencing factors affecting the adoption of artificial intelligence (AI)-enabled virtual assistants (VAs) for self-management of leukemia. A cross-sectional survey design is adopted in this study. The questionnaire included eight factors (performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, perceived privacy risk, and personal innovativeness) affecting the acceptance of AI-enabled virtual assistants. A total of 397 leukemia patients participated in the online survey. Performance expectancy (μ = 3.14), effort expectancy (μ = 3.05), and personal innovativeness (μ = 3.14) were identified to be the major influencing factors of AI adoption. Statistically significant differences (p < .05) were observed between the gender-based and age groups of the participants in relation to the various factors. In addition, perceived privacy risks were negatively correlated with all other factors. Although there are negative factors such as privacy risks and ethical issues in AI adoption, perceived effectiveness and ease of use among individuals are leading to greater adoption of AI-enabled VAs.

Artificial Intelligence and Patient Autonomy in Obesity Treatment Decisions: An Empirical Study of the Challenges.

Background This study aims to explore the factors associated with artificial intelligence (AI) and patient autonomy in obesity treatment decision-making. Methodology A cross-sectional, online, descriptive survey design was adopted in this study. The survey instrument incorporated the Ideal Patient Autonomy Scale (IPAS) and other factors affecting patient autonomy in the AI-patient relationship. The study participants included 74 physicians, 55 dieticians, and 273 obese patients. Results Different views were expressed in the scales AI knows the best (μ = 2.95-3.15) and the patient should decide (μ = 2.95-3.16). Ethical concerns (μ = 3.24) and perceived privacy risks (μ = 3.58) were identified as having a more negative influence on patient autonomy compared to personal innovativeness (μ = 2.41) and trust (μ = 2.85). Physicians and dieticians expressed significantly higher trust in AI compared to patients (p < 0.05). Conclusions Patient autonomy in the AI-patient relationship is significantly affected by privacy, trust, and ethical issues. As trust is a multifaceted factor and AI is a novel technology in healthcare, it is essential to fully explore the various factors influencing trust and patient autonomy.

Barriers and Facilitators of Artificial Intelligence in Family Medicine: An Empirical Study With Physicians in Saudi Arabia.

Artificial intelligence (AI) is a novel technology that has been widely acknowledged for its potential to improve the processes' efficiency across industries. However, its barriers and facilitators in healthcare are not completely understood due to its novel nature. The purpose of this study is to explore the intricate landscape of AI use in family medicine, aiming to uncover the factors that either hinder or enable its successful adoption. A cross-sectional survey design is adopted in this study. The questionnaire included 10 factors (performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, perceived privacy risk, personal innovativeness, ethical concerns, and facilitators) affecting the acceptance of AI. A total of 157 family physicians participated in the online survey. Effort expectancy (μ = 3.85) and facilitating conditions (μ = 3.77) were identified to be strong influence factors. Access to data (μ = 4.33), increased computing power (μ = 3.92), and telemedicine (μ = 3.78) were identified as major facilitators; regulatory support (μ = 2.29) and interoperability standards (μ = 2.71) were identified as barriers along with privacy and ethical concerns. Younger individuals tend to have more positive attitudes and expectations towardAI-enabled assistants compared to older participants (p < .05). Perceived privacy risk is negatively correlated with all factors. Although there are various barriers and concerns regarding the use of AI in healthcare, the preference for AI use in healthcare, especially family medicine, is increasing.

Protecting teenagers’ gaming privacy: the roles of parental mediation, platform protection, and risky encounters

ABSTRACT The popularity of mobile gaming among teenagers has raised concerns about privacy breaches. By integrating social cognitive theory and protection motivation theory, this study is the first to investigate how parental mediation, platform functions, and self-learning affect teen players’ risk perception and prevention in the gaming environment. We surveyed 561 high school students who play mobile games regularly aged between 15 and 19 in China. This study found that parental mediation increases teen players’ privacy risk perception and self-efficacy, while the ease of privacy functions provided by gaming platforms enhances young players’ self-efficacy and protective behaviours in gaming interactions. Teen players’ risky encounters in games were found to increase their privacy concerns. Additionally, our research indicated that optimistic bias negatively moderates the effect of privacy concerns on protective behaviours. The current study extended the social cognitive theory by assessing multiple roles in teen gamers’ social learning of privacy risks, including the platform, parental guidance, personal observation and revealed that both objective risk perceptions and biased optimistic perceptions could impact behavioural outcomes. Our findings offer practical implications for designing more user-friendly privacy features and enhancing parental mediation to promote responsible gaming among teenagers.

E-privacy concerns: a facet theoretical approach

Although the ubiquitous use of smartphones and social media poses serious risks to the privacy of users, research is sparse regarding how users perceive these risks. We present a study investigating the perception of e-privacy risks, assuming that risk perception depends on context and situation, and employing a facet theory approach to define and analyze privacy risk perceptions. Specifically, we define three facets that characterize situations involving an e-privacy risk: Facet A refers to the type of data disclosed, distinguishing three types: a person’s identity information, information about health, and information about private activities. Facet B refers to the type of actor misusing the information, distinguishing between commercial organizations, public authorities, social networks, and criminal actors. Facet C distinguishes three kinds of harm that might be experienced as a consequence: financial loss, physical harm, and negative psycho-social experiences. Questionnaire items were constructed by creating fictitious but realistic scenarios, each representing a combination of one element from each facet, yielding 36 (3 × 4 × 3) scenarios. For each scenario, respondents rated the likelihood and the negativity of experiencing that scenario. Following the facet theoretical paradigm, item intercorrelations were analyzed via ordinal multidimensional scaling. Results from a representative survey among 500 adult Norwegians yield a distinct partitioning with respect to Facets A and B, called a radex configuration. Facet B (actors) shows an angular partition. Facet C (type of harm) yields a contrast of financial versus psycho-social harm. In sum, we conclude that our three-faceted definition provides a satisfying first approximation to people’s perception of privacy risks on the Internet while remaining open for extensions with additional facets.