Privacy paradox resolution in mHealth: the moderating effect of rationality degree

Zhu, Guang; Li, Fengjing; Yan, Yi; Guenis, Hustin

doi:10.1108/jeim-03-2023-0119

Cited by 3 publications

(1 citation statement)

References 73 publications

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“…Disclosure behavior could be primarily motivated by the benefits of social media use rather than by privacy risks. This may be attributed to the overestimation of perceived benefits and underestimation privacy risks due to incomplete information and bounded rationality (Zhu et al. , 2023b).…”

Section: Discussionmentioning

confidence: 99%

To disclose or to protect? Predicting social media users’ behavioral intention toward privacy

Chen,

Huang,

2024

IMDS

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PurposeIn 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.Design/methodology/approachPrivacy 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.FindingsThe 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.Originality/valueThis 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.

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Section: Discussionmentioning

confidence: 99%

To disclose or to protect? Predicting social media users’ behavioral intention toward privacy

Chen,

Huang,

2024

IMDS

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What decision-making process do mHealth users go through when faced with privacy disclosure behaviors? A dual trade-off perspective

Xin,

Liu,

Wei

2024

AJIM

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PurposeThis paper proposes that the trade-off between medical benefits and privacy concerns among mHealth users extends to their disclosure intentions, manifested as individuals simultaneously holding intentions to tend to disclose in the near future and to reduce disclosure in the distant future. Consequently, this paper aims to explore the privacy decision-making process of mHealth users from the perspective of a dual trade-off.Design/methodology/approachThis paper constructs the model using the privacy calculus theory and the antecedent-privacy concern-outcome framework. It employs the construal level theory to evaluate the impact of privacy calculus on two types of disclosure intentions. The study empirically tests the model using a data sample of 386 mHealth users.FindingsThe results indicate that perceived benefits positively affect both near-future and distant-future disclosure intentions. In contrast, perceived risks just negatively affect distant-future disclosure intention. Additionally, perceived benefits, near-future and distant-future disclosure intentions positively affect disclosure behavior. The findings also reveal that privacy management perception positively affects perceived benefits. Personalized services and privacy invasion experience positively affect perceived benefits and risks, while trust negatively affects perceived risks.Originality/valueThis paper considers the trade-off in the privacy calculus phase as the first trade-off. On this basis, this trade-off will extend to the disclosure intention. The individuals’ two times of trade-offs between privacy concerns and medical benefits constitute the dual trade-off perspective. This paper first uses this perspective to explore the privacy decision-making process of mHealth users. This paper employs the construal level theory to effectively evaluate the impact of privacy calculus on both disclosure intentions in mHealth, extending the theory’s applicability. Moreover, we introduce antecedents of privacy calculus from the perspectives of platform, society, and individuals, enhancing the study’s realism. The research findings provide a basis for mHealth platforms to better cater to users’ privacy needs.

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Unveiling the dark and scary side of metaverse: an in-depth qualitative investigation

Kumar,

Shankar,

Mehrotra

et al. 2024

JEIM

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PurposeMetaverse is one of the decade’s most exciting and transformative technological innovations. While the metaverse holds immense promise, it has potential risks and dark sides. This research aims to investigate and identify the crucial dark dimensions associated with the metaverse platforms.Design/methodology/approachEmploying a qualitative phenomenological methodology, the authors interviewed 45 metaverse users to unravel dark dimensions related to the metaverse. Analyzing the themes extracted from the participants' insights revealed an alignment with the underpinnings of the Technology Threat Avoidance (TTA) theory.FindingsThe findings of this study revealed seven major dark dimensions: addiction and dependency, isolation and loneliness, mental health issues, privacy and security, cyberbullying and harassment, digital identity theft and financial exploitation.Practical implicationsThe study helps organizations and metaverse platforms understand the crucial dark dimensions of the metaverse. This study concludes by synthesizing prevalent themes and proposing propositions, offering insights for practical application and policy considerations.Originality/valueThis study provides a deeper understanding of the dark side of the metaverse environment from a user perspective using the underpinnings of TTA theory.

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Privacy paradox resolution in mHealth: the moderating effect of rationality degree

Cited by 3 publications

References 73 publications

To disclose or to protect? Predicting social media users’ behavioral intention toward privacy

To disclose or to protect? Predicting social media users’ behavioral intention toward privacy

What decision-making process do mHealth users go through when faced with privacy disclosure behaviors? A dual trade-off perspective

Unveiling the dark and scary side of metaverse: an in-depth qualitative investigation

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