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This study aims to empirically examine the relationship between Internet use and personal privacy risk perceptions, the mediating effect of trust and the moderating effect of satisfaction on that relationship, which is exactly conducive to the practice of personal information protection.

A moderated mediation model will be employed to test the hypothesized relationships using the 2017 Chinese Society Survey data.

The authors find that Internet use positively relates to citizens' risk perceptions toward privacy security, and trust partially mediates the relationship between Internet use and privacy risk perception. In addition, the analysis of moderating effects showed that satisfaction with social life significantly enhances the negative impact on individuals' privacy risk perceptions of interpersonal trust. The positively moderating effect of satisfaction with local governments' work mainly reveals the relationship between interpersonal trust (or institutional trust) and citizens' privacy risk perception. Moreover, satisfaction with Internet platforms positively moderates the relationship between consumer trust and privacy risk perception.

This article contributes to the social risk amplification framework by applying it to the personal privacy information protection field, which was rarely discussed before. It also enriches privacy research by identifying the internal mechanism of how Internet use influences citizens' risk perceptions towards privacy information leakage.

The promotion of autonomous vehicles introduces privacy and security risks, underscoring the pressing need for responsible innovation implementation. To more effectively address the societal risks posed by autonomous vehicles, considering collaborative engagement of key stakeholders is essential. This study aims to provide insights into the governance of potential privacy and security issues in the innovation of autonomous driving technology by analyzing the micro-level decision-making processes of various stakeholders.

For this study, the authors use a nuanced approach, integrating key stakeholder theory, perceived value theory and prospect theory. The study constructs a model based on evolutionary game for the privacy and security governance mechanism of autonomous vehicles, involving enterprises, governments and consumers.

The governance of privacy and security in autonomous driving technology is influenced by key stakeholders’ decision-making behaviors and pivotal factors such as perceived value factors. The study finds that the governmental is influenced to a lesser extent by the decisions of other stakeholders, and factors such as risk preference coefficient, which contribute to perceived value, have a more significant influence than appearance factors like participation costs.

This study lacks an investigation into the risk sensitivity of various stakeholders in different scenarios.

The study delineates the roles and behaviors of key stakeholders and contributes valuable insights toward addressing pertinent risk concerns within the governance of autonomous vehicles. Through the study, the practical application of Responsible Innovation theory has been enriched, addressing the shortcomings in the analysis of micro-level processes within the framework of evolutionary game.

Smartphone apps collect users' personal information, which triggers privacy concerns for app users. Consequently, app users restrict apps from accessing their personal information. This may impact the effectiveness of in-app advertising. However, research has not yet demonstrated what factors impact app users' decisions to use apps with restricted permissions. This study is aimed to bridge this gap.

Using a quantitative research method, the authors collected the data from 384 app users via a structured questionnaire. The data were analysed using AMOS and fuzzy-set qualitative comparative analysis (fsQCA).

The findings suggest privacy concerns and risks have a significant positive effect on app usage with restricted permissions, whilst reputation, trust and perceived benefits have significant negative impact on it. Some app-related factors, such as the number of apps installed and type of apps, also impact app usage with restricted permissions.

Based on the findings, the authors provided several implications for app stores, app developers and app marketers.

This study examines the factors that influence smartphone users' decisions to use apps with restricted permission requests. By doing this, the authors' study contributes to the consumer behaviour literature in the context of smartphone app usage. Also, by explaining the underlying mechanisms through which the principles of communication privacy management theory operate in smartphone app context, the authors' research contributes to the communication privacy management theory.

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 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.

Considering the limited understanding of determinants influencing the adoption of smart mobile tourism app (SMTA) featuring augmented reality (AR) and big data analytics (BDA), privacy concern (PC) and the risk of privacy information disclosure (PI) have threatened SMTA adoption. This study aims to propose an expanded consumer acceptance and use of information technology (UTAUT2) model by including new contextual components, integrated with privacy calculus theory (PCT) model to examine the determinants influencing behavioural intention (BI) to use SMTA.

Personal innovativeness (IN) and privacy information disclosure (PI) are incorporated in UTAUT2 model to determine its effect on SMTA featuring AR and BDA technologies from smart perspective. Both privacy concern (PC) and privacy risk (PR) derived from PCT model are also included to determine its influences on an individual's willingness to disclose privacy information for better-personalised services. We collected responses from 392 targeted participants, resulting in a strong response rate of 84.66%. These responses were analysed statistically using structural equation modeling in both SPSS 22.0 and SmartPLS 3.0.

Findings showed that personal innovativeness (IN), habit (HT) and performance expectancy (PE) significantly affect behavioural intention (BI) while privacy concern (PC) significantly affect privacy information disclosure (PI) to use SMTA. In contrast, effort expectancy (EE), hedonic motivation (HM) and privacy information disclosure (PI) had no significant effects on behavioural intention (BI) while privacy risk (PR) had no significant effects on privacy information disclosure (PI) to use SMTA.

The study findings help tourism practitioners in better comprehending recent trends of SMTA adoption for establishing targeted marketing strategies on apps to improve service quality. In addition, it enables app development companies acquire app users’ preferences to enhance their app development for leading app usage.

The purpose of this study is to investigate the determinants of behavioral intention to use smartphone diet applications within the emerging market. Specifically, it focuses on the Privacy Calculus Model constructs, encompassing perceived risk and perceived benefit, as well as the pivotal elements of trust and self-efficacy. It also explores the moderating influence of experience on the influencing factors and intention to use a diet application.

In a survey with 572 respondents, data analysis was conducted using partial least squares (PLS) structural equation modeling.

The findings reveal that perceived risk exerts a significant negative influence on behavioral intention. Conversely, perceived benefit, trust and self-efficacy exhibit a positive impact on behavioral intention. Moreover, the study delves into the moderating role of users' experience, which is found to significantly influence these relationships, suggesting that user experience plays a pivotal role in shaping the adoption dynamics of diet applications.

The limitations of this study may include the sample size and the specific focus on the emerging market of Saudi Arabia. The implications of the findings are relevant for scholars, developers, marketers, and policymakers seeking to promote the use of smartphone diet applications.

This study adds value by exploring the determinants of behavioral intention in the context of smartphone diet applications, and it is a first attempt to test the moderating role of users' experiences, providing valuable insights for various stakeholders in the field.

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.

This study aims to understand the extent of privacy concerns regarding voice-activated personal assistants (VAPAs) on Twitter. It investigates three key areas: (1) the effect of privacy-related press coverage on public sentiment and discussion volume; (2) the comparative negativity of privacy-focused conversations versus general conversations; and (3) the specific privacy-related topics that arise most frequently and their impact on sentiment and discussion volume.

A dataset of 441,427 tweets mentioning Amazon Alexa, Google Assistant, and Apple Siri from July 1, 2019 to June 30, 2021 were collected. Privacy-related press coverage has also been monitored. Sentiment analysis was conducted using the dictionary-based software LIWC and VADER, whereas text mining packages in R were used to identify privacy-related issues.

Negative privacy-related news significantly increases both negativity and volume in Twitter conversations, whereas positive news only boosts volume. Privacy-related tweets were notably more negative than general tweets. Specific keywords were found to either increase or decrease the sentiment and discussion volume. Additionally, a temporal evolution in sentiment, with general attitudes toward VAPAs becoming more positive, but privacy-specific discussions becoming more negative was observed.

This research augments the existing online privacy literature by employing text mining methodologies to gauge consumer sentiments regarding privacy concerns linked to VAPAs, a topic currently underexplored. Furthermore, this research uniquely integrates established theories from privacy calculus and social contract theory to deepen our analysis.

Online privacy pertains to an individual’s capacity to regulate and oversee the gathering and distribution of online information. Conversely, online privacy concern (OPC) pertains to the protection of personal information, along with the worries or convictions concerning potential risks and unfavorable outcomes associated with its collection, utilization and distribution. With a holistic approach to these relationships, this study aims to model the relationships between digital literacy (DL), digital data security awareness (DDSA) and OPC and how these relationships vary by gender.

The participants of this study are 2,835 university students. Data collection tools in the study consist of personal information form and three different scales. Partial least squares (PLS), structural equation modeling (SEM) and multi-group analysis (MGA) were used to test the framework determined in the context of the research purpose and to validate the proposed hypotheses.

DL has a direct and positive effect on digital data security awareness (DDSA), and DDSA has a positive effect on OPC. According to the MGA results, the hypothesis put forward in both male and female sub-samples was supported. The effect of DDSA on OPC is higher for males.

This study highlights the positive role of DL and perception of data security on OPC. In addition, MGA findings by gender reveal some differences between men and women.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2023-0122