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The privacy calculus based on a single stakeholder failed to explain users' co-owned information disclosure owing to the uniqueness of co-owned information. Drawing on collective privacy calculus theory and impression management theory, this study attempts to explore the co-owned information disclosure of social network platform users from a collective perspective rather than an individual perspective.

Drawing on collective privacy calculus theory and impression management theory, this study explores the co-owned information disclosure of social network platform users from a collective perspective rather than an individual perspective based on a survey of 740 respondents.

This study finds that self-presentation and others presentation directly positively affect users' co-owned information disclosure. Also, self-presentation, others presentation and relationship presentation indirectly positively affect users' co-owned information disclosure via relationship support. Furthermore, personal privacy concern, others' privacy concern and relationship privacy concern indirectly negatively affect users' co-owned information disclosure via relationship risk.

The findings develop the theory of collective privacy calculus and impression management, which offer insights into the design of the collective privacy protection function of social network platform service providers.

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.

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.

Considering that users’ information privacy concerns may affect the development of e-commerce, the purpose of this paper is to explore what drives internet users’ willingness to provide personal information; further, the paper examines how extrinsic rewards moderate the relationship between users’ information privacy concerns and willingness to provide personal information.

Data collected from 345 valid internet users in the context of electronic commerce were analyzed using the partial least squares approach.

The result showed that agreeableness, risk-taking propensity and experience of privacy invasion were three main antecedents of information privacy concerns among the seven individual factors. Additionally, information privacy concerns did not significantly affect users’ willingness to provide personal information in the privacy calculation mechanism; however, extrinsic rewards directly affected users’ disclosure intention. The authors found that extrinsic rewards had not moderated the relationship between users’ information privacy concerns and their willingness to provide personal information.

This study is an exploratory effort to develop and validate a model for explaining why internet users were willing to provide personal information. The results of this study are helpful to researchers in developing theories of information privacy concerns and to practitioners in promoting internet users’ willingness to provide personal information in an e-commerce context.

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 paper is to explore the antecedents of self-disclosure intention on mobile social applications. This study integrates privacy calculus model and elaboration likelihood theory to reconcile the rational and heuristic views of privacy decision making.

Using a “random dialing” sampling method, an empirical survey with 913 respondents was conducted. A series of regression models were employed to test the proposed relationships. Robust checks with sub-group analysis were conducted.

Self-disclosure intention develops along a dual route including the central route and the peripheral route. When the central route predominates, social media users form their attitudes toward self-disclosure based on a rational calculus of the privacy concern and perceived rewards. When the peripheral route predominates, users perform a more heuristic evaluation of relevant informational cues (information about privacy harms, the extent of information asymmetry between users and operators) and contextual cues (flow experience, privacy disclosure of friends). Peripheral cues moderate the relationships between central cues and self-disclosure intention.

This paper extends the Elaboration Likelihood Model by investigating the interaction between the central route and peripheral route. The results provide alternative explanations on the renowned “privacy paradox” phenomenon.

In the paradox of personalized services and privacy risks, what factors influence users’ decisions is considered an interesting issue worth exploring. The current study aims to empirically explore privacy behavior of social media users by developing a theoretical model based on privacy calculus theory.

Privacy risks, conceptualized as natural risks and integrated risks, were proposed to affect the intention of privacy disclosure and protection. The model was validated through a hybrid approach of structural equation modeling (SEM)-artificial neural network (ANN) to analyze the data collected from 527 effective responses.

The results from the SEM analysis indicated that social interaction and perceived enjoyment were strong determinants of perceived benefits, which in turn played a dominant role in the intention to disclose the privacy in social media. Similarly, trust and privacy invasion experience were significantly related to perceived risks that had the most considerable effect on users’ privacy protection intention. And the following ANN models revealed consistent relationships and rankings with the SEM results.

This study broadened the application perspective of privacy calculus theory to identify both linear and non-linear effects of privacy risks and privacy benefits on users’ intention to disclose or protect their privacy by using a state-of-the-art methodological approach combining SEM and ANN.

This study aims to explain how hotel guests form attitudes toward facial recognition technology in Singapore by integrating technology acceptance model (TAM), privacy calculus theory and personal innovativeness.

A self-administered online questionnaire was developed with measurements adopted from past research. Guests who stayed in four- or five-star hotels in Singapore were recruited via systematic random sampling. Structural equation modeling was conducted to examine the proposed integrated models.

Results showed that hotel guests performed calculative cognitive processes, weighing the benefits and risks of using facial recognition check-in system. Contradictory to the past research which suggested that trust activates both perceived risk and benefits, this study demonstrated that trust independently directed consumer attention on the benefits gained while risk perception was triggered by privacy concern. Furthermore, the current study revealed that the ease of use of facial recognition check-in system could possibly backfire.

The research indicates that the effort to adopt new technology in the hotel industry is promising in view of the growing millennials and Generation Z population who are digital natives. Furthermore, the current study highlights ways to elevate institutional trust and divert consumers’ attention from risk perception to enhance their positive attitude and behavior toward accepting facial recognition check-in system.

This study integrated TAM with privacy calculus theory and personal innovativeness in examining the acceptance of facial recognition check-in system in the hotel industry in Singapore. This study is also the first, to the best of the authors’ knowledge, to investigate the relationships among privacy concern, perceived risk, institutional trust and perceived benefits, as well as their effects on consumers’ attitudes and behavior toward the biometric system.

In this research, the authors focus on mobile cloud computing (MCC) collaboration apps that are multiplatform and send the users’ data to the cloud. Despite their benefits, MCC collaboration apps raise privacy concerns, as the users’ information is sent to the cloud where users lack direct control. This study aims to investigate why users disclose information to MCC apps despite privacy concerns and examine the effect of security and assurance mechanisms (i.e. privacy policies and ISO/IEC 27018 certification) on users’ perceptions and information disclosure. Based on three surveys conducted in 2016 (n = 515), 2017 (n = 505) and 2018 (n = 543), this study finds mixed results regarding the relationships among security, assurance mechanisms, utilitarian benefits and information disclosure.

This study conducted three scenario-based surveys in the USA in 2016 (n = 515), 2017 (n = 505) and 2018 (n = 543).

This study finds mixed results of relationships among security, assurance mechanisms, utilitarian benefit and information disclosure.

With proliferation of MCC apps, the investigation of how users make privacy decision to disclose personal information to these apps is sparse. This study, for the first time, investigates whether the signals of assurance mechanism decrease users’ privacy concerns. This study also examines the interplay between security and privacy within information disclosure behavior. Finally, this study was conducted in 3 years to enhance the generalizability and robustness of findings.

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.

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.

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.

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.

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.