Search results

The privacy paradox refers to the situation where users of online services continue to disclose personal information even when they are concerned about their privacy. One recent study of Facebook users published in Internet Research concludes that laziness contributes to the privacy paradox. The purpose of this study is to challenge the laziness explanation. To do so, we adopt a cognitive dispositions perspective and examine how a person’s external locus of control influences the privacy paradox, beyond the trait of laziness.

A mixed method approach is adopted. We first develop a research model which hypothesises the moderating effects of both laziness and external locus of control on privacy issues. We quantitatively test the research model through a two-phase survey of 463 Facebook users using the Hayes PROCESS macro. We then conduct a qualitative study to verify and develop the findings from the quantitative phase.

The privacy paradox holds true. The findings confirm the significant influence of external locus of control on the privacy paradox. While our quantitative findings suggest laziness does not affect the association between privacy concerns and self-disclosure, our qualitative data does provide some support for the laziness explanation.

Our study extends existing research by showing that a person’s external locus of control provides a stronger explanation for the privacy paradox than the laziness perspective. As such, this study further reveals the boundary conditions on which the privacy paradox exists for some users of social networking sites, but not others. Our study also suggests cognitive dissonance coping strategies, which are largely absent in prior investigations, may influence the privacy paradox.

This study aims to investigate the implications, risks and challenges of data privacy due to the use of immersive technology in the hospitality industry.

The authors adopt a mixed-method approach. Study 1 is a focus group. The authors then provide external and ecological validity with a field experiment conducted with 139 hotel clients at a three-star continental European hotel.

Collecting biometric data results in unbalanced privacy compared to biographic data, as it diminishes individuals’ control over their data and grants organizations absolute power. This unbalanced privacy directly influences consumers’ willingness to disclose information, affecting their choice of hotels and access to services.

Hotels should redesign their strategies to accommodate heightened privacy risks with biometric data. This can be obtained by introducing systems that foster customer confidence in data usage and facilitate customers’ willingness to disclose biometrics through immersive technology or biographic data.

This study introduces unbalanced privacy as a unique state due to sharing biometric data. The authors propose a novel doctrine, the uncontrollable privacy paradox, which is a shift from the privacy paradox. The uncontrollable privacy paradox addresses the unbalanced privacy envisaged through consumer powerlessness in data management. This research addresses the literature gap on the privacy paradox by offering a broader perspective, including business, industry and mixed reality considerations.

This paper aims to propose a solution for dissolving the “privacy paradox” in social networks, and explore the feasibility of adopting a synergistic mechanism of “deep-learning algorithms” and “differential privacy algorithms” to dissolve this issue.

To validate our viewpoint, this study constructs a game model with two algorithms as the core strategies.

The “deep-learning algorithms” offer a “profit guarantee” to both network users and operators. On the other hand, the “differential privacy algorithms” provide a “security guarantee” to both network users and operators. By combining these two approaches, the synergistic mechanism achieves a balance between “privacy security” and “data value”.

The findings of this paper suggest that algorithm practitioners should accelerate the innovation of algorithmic mechanisms, network operators should take responsibility for users’ privacy protection, and users should develop a correct understanding of privacy. This will provide a feasible approach to achieve the balance between “privacy security” and “data value”.

These findings offer some insights into users’ privacy protection and personal data sharing.

While research on privacy concerns is rich in understanding and depth, there is still not a clear understanding of why people express having privacy concerns, but do not behave consistently with their concern. We propose that this misalignment derives from a diverse set of privacy boundaries, depending on the user. This research builds on prior Communication Privacy Management Theory research to further define individual privacy boundaries. Beyond that, we evaluate the relationship between the privacy boundaries people set, and their ability to protect themselves.

A survey was conducted to assess how private individuals find twenty items. Along with measuring the sensitivity of information, we collected responses on the Online Privacy Information Literacy test to measure differences in sensitivity based on privacy knowledge. 285 participant’s responses were evaluated using exploratory factor analysis and K-means clustering.

We identify five different groups of privacy indicators. Our findings also suggest that users have limited understanding of how to keep data private, even if they have high privacy concerns.

We contribute to theory by offering guidance on how to better apply theoretical understanding, based on our results. More explicitly, we offer analysis that suggests boundary conditions might be absent from current theoretical understanding. Practically, we offer guidance for understanding privacy differences, which is important to understanding how to implement privacy protection laws.

The widespread application of smart technologies in services not only brings efficiency and convenience to consumers but also inevitably comes with negative effects. Therefore, this article aims to illustrate the impact of privacy invasion on consumers' intention to use smart services. Using distrust as a mediating variable, compare two different modes of interaction between voice and text, and study the positive impact of privacy commitment. This study aims to provide recommendations for smart service providers to make the consumer experience better.

This paper adopts an experimental approach, with data collection and hypothesis analysis by designing four different experiments.

The results show that the negative impact of privacy invasion on consumers' intention to use smart services is moderated by privacy commitments and interaction modes. This article verifies the mediating effect of distrust on consumers' intention to use when privacy invasion occurs and verifies the moderating effect of the interaction modes by comparing voice interaction with text interaction and demonstrates that text interaction mode will attenuate the mediating role of distrust in the path in privacy invasion. Besides, it also indicates that privacy commitments can moderate the relationship between privacy invasion’s effect on distrust and intention to use.

Focusing on privacy invasion, this study explores consumers' intention to use smart services, compares the two interaction modes of voice and text to explore their moderating effects, deeply explores consumer psychology and studies the mediating role of distrust and the moderating role of privacy commitment.

The purpose of this study was to investigate the roles of employee experience and top management commitment in the relationship between human resource (HR) records management culture and HR records privacy control in organisations in Ghana.

Structural equation modelling was used in analysing the data. Following the specification of the model, three main types of analyses were carried out. They were reflective measurement model analyses to test reliability and validity; formative measurement model analyses to test redundancy, collinearity, significance and relevance of the lower-order constructs; and structural model analyses to ascertain the explanatory and predictive powers of the model, significance of the hypotheses and their effect sizes.

The study confirmed that communication, privacy awareness and training and risk assessment are dimensions of HR records management culture. Concerning the hypotheses, it was established that HR records management culture is related to HR records privacy control. Also, the study showed that employee experience positively moderated the relationship HR records management culture has with HR records privacy control. However, top management commitment negatively moderated the relationship HR records management culture has with HR records privacy control.

Organisations committed to the privacy control of HR records need to ensure the retention of their employees, as the longer they stay with the organisation, the more they embody the HR records management culture which improves the privacy control of HR records. For top management commitment, it should be restricted to providing strategic direction for HR records privacy control, as the day-to-day influence of top management commitment on the HR records management culture does not improve the privacy control of HR records.

This study demonstrates that communication, privacy awareness and training and risk assessment are dimensions of HR record management culture. Also, the extent of employee experience and top management commitment required in the relationship between HR records management culture and HR records privacy control is revealed.

The COVID-19 pandemic has had far-reaching effects on society and will continue to be a subject of study for researchers in the years to come. Businesses have implemented technologies that reduce reliance on physical currencies, such as e-commerce sites and contactless payments. This study aims to examine the users’ attitudes and behaviors toward mobile payments. The focus is on identifying the most effective techniques and approaches that businesses can use to encourage user adoption of mobile payments.

This study uses survey data from 396 active mobile payment users across the mid-west region of the USA to test the proposed hypothesis. The snowball sampling approach is used to sample the participants for the data collection. This study uses partial least squares structural equation modeling to test the ten hypotheses proposed in this study.

This study finds that organizational commitment and privacy customization can significantly overcome users’ protective attitudes toward mobile payments during the pandemic. In addition, providing users with privacy customization options can significantly encourage self-disclosure, which is crucial for transaction authentication and fraud detection.

Envisioned in the backdrop of the COVID pandemic, this is one of the earliest studies investigating the role of privacy customization, self-disclosure and organizational commitment on mobile payment adoption.

In the online environment, consumers increasingly feel vulnerable due to firms’ expanding capabilities of collecting and using their data in an unsanctioned manner. Drawing from gossip theory, this research focuses on two key suppressors of consumer vulnerability: transparency and control. Previous studies conceptualize transparency and control from rationalistic approaches that overlook individual experiences and present a unidimensional conceptualization. This research aims to understand how individuals interpret transparency and control concerning privacy vulnerability in the online environment. Additionally, it explores strategic approaches to communicating the value of transparency and control.

An interpretivism paradigm and phenomenology were adopted in the research design. Data were collected through semi-structured interviews with 41 participants, including consumers and experts, and analyzed through thematic analysis.

The findings identify key conceptual dimensions of transparency and control by adapting justice theory. They also reveal that firms can communicate assurance, functional, technical and social values of transparency and control to address consumer vulnerability.

This research makes the following contributions to the data privacy literature. The findings exhibit multidimensional and comprehensive conceptualizations of transparency and control, including user, firm and information perspectives. Additionally, the conceptual framework combines empirical insights from both experiencers and observers to offer an understanding of how transparency and control serve as justice mechanisms to effectively tackle the issue of unsanctioned transmission of personal information and subsequently address vulnerability. Lastly, the findings provide strategic approaches to communicating the value of transparency and control.

A wealth of studies have identified numerous antecedents to online self-disclosure. However, the number of competing theoretical perspectives and inconsistent findings have hampered efforts to obtain a clear understanding of what truly influences online self-disclosure. To address this gap, this study draws on the antecedent-privacy concern-outcome (APCO) framework in a one-stage meta-analytical structural equation modeling (one-stage MASEM) study to test a nomological online self-disclosure model that assesses the factors affecting online self-disclosure.

Using the one-stage MASEM technique, this study conducts a meta-analysis of online self-disclosure literature that comprises 130 independent samples extracted from 110 articles reported by 53,024 individuals.

The results reveal that trust, privacy concern, privacy risk and privacy benefit are the important antecedents of online self-disclosure. Privacy concern can be influenced by general privacy concern, privacy experience and privacy control. Furthermore, moderator analysis indicates that technology type has moderating effects on the links between online self-disclosure and some of its drivers.

First, with the guidance of the APCO framework, this study provides a comprehensive framework that connects the most relevant antecedents underlying online self-disclosure using one-stage MASEM. Second, this study identifies the contextual factors that influence the effectiveness of the antecedents of online self-disclosure.

This 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.

This 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.

The 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.

This 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.