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This paper aimed to explain why individuals still tend to disclose their privacy information even when privacy risks are high and whether individuals disclose or withhold information following the same logic.

This study develops a configurational decision tree model (CDTM) for precisely understanding individuals' decision-making process of privacy disclosure. A survey of location-based social network service (LBSNS) users was conducted to collect data, and fuzzy-set qualitative comparative analysis (fsQCA) was adopted to validate the hypotheses.

This paper identified two configurations for high and low disclosure, respectively, and found that the benefits and the risks did not function independently but interdependently, and the justice would play a crucial role when both the benefits and the risks were high. Furthermore, the authors found that there were asymmetric mechanisms for high disclosure and low disclosure, and males focused more on perceived usefulness, while females concerned more about perceived enjoyment, privacy risks and perceived justice.

This paper further extends privacy calculus model (PCM) and deepens the understanding of the privacy calculus process from a configurational perspective. In addition, this study also provides guidance for future research on how to adopt the configurational approach with qualitative comparative analysis (QCA) to revise and improve relevant theories for information systems (IS) behavioral research.

Digital natives have become significant users of social network sites (SNSs); therefore, their disclosed personal information can be misused by SNS providers and/or other users. The purpose of this paper is to understand how digital natives make their self-disclosure decisions on SNSs, as well as whether the concept of culture can still be relevant to digital natives.

The hypotheses were tested with survey data collected from the USA and China.

The results show that trust in SNSs and trust in SNS users are positively related to social rewards. Social rewards are positively related to intention to self-disclose, while privacy risk is positively related to privacy concerns. Further, culture significantly moderates the relationship between trust and social rewards.

The study clarifies the effects of different types of trust on privacy in the context of SNSs. Further, the study shows the effects of culture when digital natives make self-disclosure decisions.

SNS providers also need to focus on different types of trust when operating in different cultural contexts. Further, SNS providers expanding their markets should emphasize social rewards to increase the likelihood of self-disclosure.

The results show that while culture can still be helpful to explain digital natives’ trust beliefs, digital natives have started to converge regarding their perceptions about privacy concerns and self-disclosure.

This study investigates how different parental mediation strategies (active versus restrictive) and teen Douyin users' privacy risk perceptions are associated with their privacy management behaviors.

An online survey with teen Douyin users (N = 500) was administered in mainland China.

Perceived privacy risk leads teenagers to implement stricter privacy management strategies. However, different types of parental mediation have different impacts on teens' privacy management behaviors. Discussion-based active mediation is positively correlated with privacy disclosure and privacy boundary linkage, while rule-based restrictive mediation is positively associated with privacy boundary control. In addition, active mediation encourages teens to use their own judgment about privacy risks when deciding how much personal information to disclose and with whom they want to share their information. Conversely, restrictive mediation results in teens making decisions about disclosing private information without taking their own risk assessments into account.

Video-sharing social media platforms like TikTok and Douyin have become a cultural trend among teen social media users. However, loss of privacy is a potentially serious downside of using such platforms. Despite the platforms' popularity among this age group, little is known about the ways teens manage their privacy on such social media platforms. By examining how teens' privacy risk perception and parental intervention shape three different aspects of privacy boundary management (i.e. privacy disclosure, privacy boundary linkage, and privacy boundary control), this study provides a comprehensive understanding of teen Douyin users' privacy management.

Based on communication privacy management (CPM) theory, this study aimed to explore how gender and age criteria, motivational criterion (locatability), benefit-risk ratio criteria (perceived benefits of privacy information disclosure and privacy concerns), contextual criteria (privacy experience) and boundary coordination and turbulence (perceived effectiveness of privacy policy) interact and combine in leading to voice assistant (VA) users' intention to reveal or conceal their privacy information.

A questionnaire was designed and distributed to car drivers who have intelligent VA use experience while driving. A total of 230 valid responses were collected. The fuzzy-set qualitative comparative analysis (fsQCA) approach was used to analyse the data.

Via configuration analysis with fsQCA, five equivalent configurations leading to the high intention of disclosing privacy information, and one configuration leading to the intention of concealing privacy information were identified. Four theoretical configurational propositions were proposed. Moreover, the theoretical and practical implications of the findings are discussed.

This study offers some insightful implications in the field of private information communication in artificial intelligence applications as well as practical implications for intelligent VA application design. The findings provide empirical evidence of privacy communication management in the context of smart VA usage.

Given the importance of online social network (OSN) media features, many studies have focused on how different types of OSNs with various media features influence users’ usage and engagement. However, a recent literature review indicates that few empirical studies have considered how different types of OSNs with different information accessibility levels influence users’ beliefs and self-disclosure. By comparing two OSN platforms (OSNs with high-level information accessibility vs OSNs with low-level information accessibility), the purpose of this paper is to address this opportunity by investigating the differential impacts of the two platforms on individuals’ psychological cognition – particularly users’ social exchange beliefs – and explaining how these beliefs translate into OSN self-disclosure.

This study used a factorial design approach in an experimental setting to examine how different levels of information accessibility (high vs low), influence the social exchange beliefs (i.e. perceived social capital bridging, perceived social capital bonding and perceived privacy risks) of OSN users and subsequently influence OSN self-disclosure.

The results show that users on OSNs with high-level information accessibility express significantly higher perceived social capital bridging and perceived privacy risks than users on OSNs with low-level information accessibility. However, users on OSNs with low-level information accessibility express higher social bonding beliefs than users on OSNs with high-level information accessibility, indicating that there are different effect mechanisms toward OSN self-disclosure.

The focus of this research helps unveil the complex relationships between OSN design features (e.g. information accessibility), psychological cognition (e.g. social capital bridging, social capital bonding and privacy risks) and OSN self-disclosure. First, it clarifies the relationship between information accessibility and self-disclosure by examining the mediating effect of three core social exchange beliefs. Second, it uncovers the distinct effects of high-level information-accessible OSNs and low-level information-accessible OSNs on OSN self-disclosure.

The purpose of this paper is to analyse the problem of privacy disclosure of third party applications in online social networks (OSNs) through Facebook, investigate the limitations in the existing models to protect users privacy and propose a permission-based access control (PBAC) model, which gives users complete control over users’ data when accessing third party applications.

A practical model based on the defined permission policies is proposed to manage users information accessed by third party applications and improve user awareness in sharing sensitive information with them. This model is a combination of interfaces and internal mechanisms which can be adopted by any OSN having similar architecture to Facebook in managing third party applications, without much structural changes. The model implemented in Web interface connects with Facebook application programming interface and evaluates its efficacy using test cases.

The results show that the PBAC model can facilitate user awareness about privacy risks of data passed on to third party applications and allow users who are more concerned about their privacy from releasing such information to those applications.

The study provides further research in protecting users’ privacy in OSNs and thus avoid the risks associated with that, thereby increasing users’ trust in using OSNs.

The research has proven to be useful in improving user awareness on the risk associated with sharing private information on OSNs, and the practically implemented PBAC model guarantees full user privacy from unwanted disclosure of personal information to third party applications.

“Smart devices think you're “too lazy” to opt out of privacy defaults” was the headline of a recent news report indicating that individuals might be too lazy to stop disclosing their private information and therefore to protect their information privacy. In current privacy research, privacy concerns and self-disclosure are central constructs regarding protecting privacy. One might assume that being concerned about protecting privacy would lead individuals to disclose less personal information. However, past research has shown that individuals continue to disclose personal information despite high privacy concerns, which is commonly referred to as the privacy paradox. This study introduces laziness as a personality trait in the privacy context, asking to what degree individual laziness influences privacy issues.

After conceptualizing, defining and operationalizing laziness, the authors analyzed information collected in a longitudinal empirical study and evaluated the results through structural equation modeling.

The findings show that the privacy paradox holds true, yet the level of laziness influences it. In particular, the privacy paradox applies to very lazy individuals but not to less lazy individuals.

With these results one can better explain the privacy paradox and self-disclosure behavior.

The state might want to introduce laws that not only bring organizations to handle information in a private manner but also make it as easy as possible for individuals to protect their privacy.

Based on a literature review, a clear research gap has been identified, filled by this research study.

Many online transactions and digital services depend on consumers’ willingness to take privacy risks, such as when shopping online, joining social networks, using online banking or interacting with e-health platforms. Their decisions depend on not only how much they would suffer if their data were revealed but also how uncomfortable they feel about taking such a risk. Such an aversion to risk is a neglected factor when evaluating the value of privacy. The aim of this paper is to propose an empirical method to measure both privacy risk aversion and privacy worth and how those affect privacy decisions.

The authors let individuals play privacy lotteries and derive a measure of the value of privacy under risk (VPR) and empirically test the validity of this measure in a laboratory experiment with 148 participants. Individuals were asked to make a series of incentivized decisions on whether to incur the risk of revealing private information to other participants.

The results confirm that the willingness to incur a privacy risk is driven by a complex array of factors, including risk aversion, self-reported value for private information and general attitudes to privacy (derived from surveys). The VPR does not depend on whether there is a preexisting threat to privacy. The authors find qualified support for the existence of an order effect, whereby presenting financial choices prior to privacy ones leads to less concern for privacy.

Attitude to risk in the domain of privacy decisions is largely understudied. In this paper, the authors take a first step toward closing this empirical and methodological gap by offering (and validating) a method for the incentivized elicitation of the implicit VPR and proposing a robust and meaningful monetary measure of the level of aversion to privacy risks. This measure is a crucial step in designing and implementing the practical strategies for evaluating privacy as a competitive advantage and designing markets for privacy risk regulations (e.g. through cyber insurances).

The present study advances research on the economics of consumer privacy – one of the most controversial topics in the digital age. In light of the proliferation of privacy regulations, the mentioned method for measuring the VPR provides an important instrument for policymakers’ informed decisions regarding what tradeoffs consumers consider beneficial and fair and where to draw the line for violations of consumers’ expectations, preferences and welfare.

The authors present a novel method to measure the VPR that takes account of both the value of private information to consumers and their tolerance for privacy risks. The authors explain how this method can be used more generally to elicit attitudes to a wide range of privacy risks involving exposure of various types of private information.

Facial recognition systems represent a viable solution to today’s hotels’ security and service challenges. The purpose of this study was to build and empirically validate a conceptual model that examined consumers’ willingness to create a profile based on biometric information disclosed via facial recognition systems.

Data were collected from 421 US general population consumers who stayed in hotels. The study used a confirmatory factor analysis to test the measurement model and a structural equation modeling approach to empirically validate the structural model.

It was found that the benefit of information disclosure was the strongest predictor of value of disclosure and that value of disclosure and privacy concerns influenced consumers’ willingness to disclose biometric information. In turn, consumers’ willingness to disclose biometric information and their desire to be loyal to hotels influenced consumers’ willingness to create a profile.

To the best of the author’s knowledge, this is the first study to examine profile creation and biometric information disclosure via facial recognition systems in hotels, a technology that is likely to disrupt the current authentication and service quality models in hotels. This study also advances the literature by expanding the scope of the privacy calculus by adding social rewards, and by elucidating the role of desires in service contexts.

The collection and use of personal medical information for mobile health (mHealth) service raise significant privacy concerns. In this context, this study aims to explore the privacy paradox and its impact from the perspective of paradox resolution.

Based on social support theory and privacy calculus theory, this study first studies the effect of social support on perceived benefits, and explores the moderating effect of perceived health status on the privacy trade-off process. Secondly, the study examines the path of “privacy concerns – disclosure intention – disclosure behavior” to verify the existence of the privacy paradox. Following this, based on rational choice theory, the rationality degree is introduced as a moderating variable to investigate both its impact on the central route and the strength of this impact on the privacy paradox.

Empirical results show that informational support and emotional support influence perceived benefits significantly. Perceived benefits significantly influence privacy concerns, and perceived health status has a significant positive moderating effect. The authors further find that there is a privacy paradox within the mHealth context, and the privacy paradox is moderated negatively by rationality degree. The findings indicate that the impact strength of the privacy paradox will decrease with increases in rationality degree.

The findings indicate that it is crucial to evaluate the privacy paradox and its impact from the perspective of paradox resolution.

This study offers a complete comprehension of the privacy paradox in mHealth and provides several valuable recommendations for enhancing both mHealth services and privacy controls.