A meta-analysis to explore privacy cognition and information disclosure of internet users

Privacy Relevance and Disclosure Intention in Mobile Apps: The Mediating and Moderating Roles of Privacy Calculus and Temporal Distance

In digital societies, users' privacy decisions not only affect personal information security and application sustainability, but also profoundly influence the formulation and enforcement of relevant laws. However, existing research mainly adopts a dichotomous perspective of rationality and bounded rationality, lacking an integrated framework to explain the complexity of users' privacy decisions. Therefore, this study integrates privacy calculus theory and Psychological Distance Theory within the Elaboration Likelihood Model (ELM) framework to explore their mediating and moderating roles in the relationship between perceived privacy relevance and disclosure intention. To achieve the research objectives, we employed the vignette method to design an online survey with a 2 (perceived relevance: low vs. high) × 2 (temporal distance: near vs. distant) between-subjects design, ultimately collecting 293 valid responses. The conclusions are as follows: (1) perceived relevance positively affects users' privacy disclosure intention, and perceived benefits and perceived risks play a partial mediating role between them; (2) contrary to individuals' common preference for near temporal distance (immediate rewards), distant temporal distance (delayed rewards) have a more pronounced enhancing effect on the positive relationship between perceived relevance and perceived benefits; (3) the results excluded the influence of control variables such as gender, age, and education level on privacy disclosure intention. This study not only proposes an integrated analytical framework, revealing that users' privacy decisions are jointly influenced by both rational and irrational factors, but also provides practical insights for application developers and regulatory agencies. Finally, we also discuss the limitations of this study and directions for future research.

Antecedents predicting digital contact tracing acceptance: a systematic review and meta-analysis

An awareness of antecedents of acceptance of digital contact tracing (DCT) can enable healthcare authorities to design appropriate strategies for fighting COVID-19 or other infectious diseases that may emerge in the future. However, mixed results about these antecedents are frequently reported. Most prior DCT acceptance review studies lack statistical synthesis of their results. This study aims to undertake a systematic review and meta-analysis of antecedents of DCT acceptance and investigate potential moderators of these antecedents. By searching multiple databases and filtering studies by using both inclusion and exclusion criteria, 76 and 25 studies were included for systematic review and meta-analysis, respectively. Random-effects models were chosen to estimate meta-analysis results since Q, I 2, and H index signified some degree of heterogeneity. Fail-safe N was used to assess publication bias. Most DCT acceptance studies have focused on DCT related factors. Included antecedents are all significant predictors of DCT acceptance except for privacy concerns and fear of COVID-19. Subgroup analysis showed that individualism/collectivism moderate the relationships between norms/privacy concerns and intention to use DCT. Based on the results, the mean effect size of antecedents of DCT acceptance and the potential moderators may be more clearly identified. Appropriate strategies for boosting the DCT acceptance rate can be proposed accordingly.

Too Tired and in Too Good of a Mood to Worry About Privacy: Explaining the Privacy Paradox Through the Lens of Effort Level in Information Processing

Policy-oriented Abstract

Data privacy is one of the most pressing issues today. The world is thirsty for novel, effective, and efficient policies to strike an appropriate balance between protecting individuals’ privacy and creating economic value from their personal information. Whereas governmental efforts, such as the enaction of General Data Protection Regulation, California Consumer Privacy Act, and other privacy regulations, have been pushing boundaries to strike this balance, the effects of these types of initiatives on individuals’ privacy awareness and behavior are uncertain, likely to be nuanced, and will take time to sort out. In this paper, we explain the privacy paradox, a phenomenon with important implications that apply to policymakers, industry professionals, and individuals. The privacy paradox refers to a mismatch between individuals’ stated privacy concerns and their actual disclosure behaviors. In three behavioral experiments, we show how the paradox is revealed when individuals are cognitively tired especially when they are in a good mood. These findings do not indicate that individuals do not care about privacy because they do when they are not cognitively tired especially when they are in a bad mood. By explaining the privacy paradox, we inform existing and future privacy policies to strike that balance we all strive for.

Effect of perceived risks, perceived benefits and regulatory events on users’ supervision intention towards e-hailing platforms: A mixed method

Research on platform governance has gained extensive scholarly interest. However, studies on user participation intention towards platform supervision remain underexplored. In this study, a mixed method approach, including qualitative and quantitative methods, is used to explore the factors influencing the supervision intention of e-hailing users. A preliminary interview study is conducted to determine what factors impact users’ supervision intention, and an SEM model is tested using 359 survey data to examine how perceived government regulation, perceived risks/benefits and regulatory events impact supervision intention. Results indicate that perceived government regulation reduces perceived risks and increases the perceived benefits from participation into supervision, perceived risks weakened users’ supervision intention, whereas perceived benefits stimulated it. Perceived risks and perceived benefits positively mediated the relationship between perceived government regulation and users’ supervision intention. Regulatory events have a negative moderating effect on the relationship between e-hailing users’ perceived risks (benefits) and supervision intention.

Research on the influencing factors of users’ information processing in online health communities based on heuristic-systematic model

With the rapid development of the Internet and the normalization of COVID-19 epidemic prevention and control, Online health communities (OHCs) have gradually become one of the important ways for people to obtain health information, and users have to go through a series of information processing when facing the massive amount of data. Understanding the factors influencing user information processing is necessary to promote users’ health literacy, health knowledge popularization and health behavior shaping. Based on the Heuristic-Systematic Model (HSM), Information Ecology Theory, Privacy Trade-Off and Self-Efficacy Theory, we constructed a model of factors influencing user information processing in online health communities. We found that information quality and emotional support had indirect effects on heuristic and systematic information processing, and these effects were mediated by privacy concerns and self-efficacy. In our research model, systematic information processing was most positively influenced directly by self-efficacy. Privacy concerns had a direct negative correlation with both dual information processing pathways. Therefore, OHCs managers should develop relevant regulations to ensure the information quality in OHCs and improve privacy protection services to promote user information processing by improving users’ self-efficacy and reducing their privacy concerns. Providing a user-friendly and interactive environment for users is also recommended to create more emotional support, thus facilitating more systematic information processing.

Biometrics Innovation and Payment Sector Perception

This paper presents an analysis of innovations in the biometrics market, which have started to play a very important role in personal identification and identification systems. The aim of the study was to analyze current customs and opinions regarding payment methods, as well as to identify threats and opportunities for new biometric solutions in this area. First, the history of the biometrics market is presented. Acceptance patterns of new technologies are explored and modified. The authors used literature reviews, qualitative research (focus groups), and quantitative research (questionnaire survey) as methods. The main value and importance of biometrics is the uniqueness of biometric patterns (e.g., face, fingerprint, iris, etc.), which takes the security of these systems to a new level. The results of the quantitative study based on the qualitative survey show positive verification of the hypothesized reasons; e.g., importantly, that the age of potential users of biometric payments influences the fear about personal data. Fear of losing personal data affects the perceived safety of biometric payments. Perceived security has a very strong influence on attitudes towards biometric payments, which is the strongest predictor of behavioral intention to use biometric payments.

Harnessing Soft Logic to Represent the Privacy Paradox

The digital era introduces a significant issue concerning the preservation of individuals’ privacy. Each individual has two autonomous traits, privacy concern which indicates how anxious that person is about preserving privacy, and privacy behavior which refers to the actual actions the individual takes to preserve privacy. The significant gap between these two traits is called the privacy paradox. While the existence and the extensive distribution of the privacy paradox is widely-considered in both academic and public discussion, no convincing explanation of the phenomenon has been provided. In this study we harness a new mathematical approach, “soft logic,” to better represent the reality of the privacy paradox. Soft numbers extend zero from a singularity to an infinite one-dimensional axis, thus enabling the representation of contradictory situations that exist simultaneously, i.e., a paradox. We develop a mathematical model for representing the privacy paradox with soft numbers, and demonstrate its application empirically. This new theory has the potential to address domains that mix soft human reality with robust technological reality.

An Investigation Into the Sensitivity of Personal Information and Implications for Disclosure: A UK Perspective

The perceived sensitivity of information is a crucial factor in both security and privacy concerns and the behaviors of individuals. Furthermore, such perceptions motivate how people disclose and share information with others. We study this topic by using an online questionnaire where a representative sample of 491 British citizens rated the sensitivity of different data items in a variety of scenarios. The sensitivity evaluations revealed in this study are compared to prior results from the US, Brazil and Germany, allowing us to examine the impact of culture. In addition to discovering similarities across cultures, we also identify new factors overlooked in the current research, including concerns about reactions from others, personal safety or mental health and finally, consequences of disclosure on others. We also highlight a difference between the regulatory perspective and the citizen perspective on information sensitivity. We then operationalized this understanding within several example use-cases exploring disclosures in the healthcare and finance industry, two areas where security is paramount. We explored the disclosures being made through two different interaction means: directly to a human or chatbot mediated (given that an increasing amount of personal data is shared with these agents in industry). We also explored the effect of anonymity in these contexts. Participants showed a significant reluctance to disclose information they considered “irrelevant” or “out of context” information disregarding other factors such as interaction means or anonymity. We also observed that chatbots proved detrimental to eliciting sensitive disclosures in the healthcare domain; however, within the finance domain, there was less effect. This article's findings provide new insights for those developing online systems intended to elicit sensitive personal information from users.

User concerns regarding information sharing on social networking sites: The user's perspective in the context of national culture

Information sharing via social networking systems (SNS) is a common practice among academics, as well as others, that brings substantial benefits. At the same time, privacy concerns are widespread among SNS users, which may tend to inhibit their maximising the benefit from using the systems. This paper investigates the proposition that SNS user attitudes and behaviour are affected by privacy concerns, and that the effects are subject to significant cultural factors. A broad assessment of the literature provides the context for the study. Working in the context of Saudi Arabia, we apply a mixed-methods approach beginning with in-depth interviews, exposing in detail a range of views and concerns about privacy and SNS use, also allowing us to identify three key factors that bear on SNS usage and users’ concerns. Analysis of these factors in the light of the “theory of reasoned action” derives a structural model predicting several hypotheses relating the factors and users’ attitudes and behaviour. We assess the model through development of a questionnaire, administered to a large pool of academic participants, that allows us to examine how the model responds in general, and via multigroup partial least squares analyses, differentially to gender and to culturally distinct (Arab vs. non-Arab) constituents of the participant group. Results show good support for the hypotheses and clear gender and culture effects. Picking up issues from the interviews, discussion focuses on users’ views about SNS providers’ privacy policies and their inadequacy regarding culturally specific ethical concerns. We argue that these views may reflect different regulatory environments in combination with other cultural factors.

When Job Candidates Experience Social Media Privacy Violations

This study uses a cross-cultural sample from the U.S. and China to compare information privacy-protective responses to a breach in privacy during a job interview. Using a job recruitment scenario, the relationships among individuals' concern for information privacy, disposition to trust, judgment of moral issues, and their information privacy-protective responses were examined. Based on the multiple group analysis results, this paper find that the privacy-protective responses significantly vary between the American and Chinese cultures. The findings shed light on individuals' responses to privacy issues in the United States and China.

Measuring the impact and reach of informal educational videos on YouTube: The case of Scientific Animations Without Borders

Given the popularity, reach, and variable accessibility of online platforms as channels for informal education by higher-education institutions (HEIs), it becomes practically and theoretically important to better understand the factors that affect the impact and reach of any such Internet-delivered ICT informal learning. Accordingly, this study analysed viewer data from one informal, science animation educational channel on currently the most-watched online platform, YouTube, to measure characteristics affecting the videos’ impact and reach. Results from the study identified the most watched videos on the channel—including survival gardening using drip irrigation, charcoal water filtration, and tuberculosis prevention—and characteristic demand, time, location, and volume of video access. While the basic findings reaffirm prior research measuring statistically significant correlations between user-activity and YouTube engagement metrics (including watch-time, view counts, likes, and subscribers), they also demonstrate the and ability to make such content broadly applicable across demographics and globally. Offering some measure of insights for boosting HEI participation in informal educational science animation and ICT learning practices using platforms like YouTube—especially around the topics of water, agriculture, food security, and improved health outcomes—the findings also point to where improved methods for reaching the intended recipients of informal education online are needed to best leverage the potential of such platforms.

Citizen Adoption in E-Government Systems

Electronic Government (e-Government) refers to a system of information, communication and interaction between government and its citizens. E-Government adoption has been studied for more than a decade with several meta-analytic studies being produced in that time. This study is differentiated from prior meta-analyses as it splits the empirical studies into pre-adoption and post-adoption studies to allow a clearer model of e-Government. We found different determinants and distinct models for pre- and post-adoption of e-Government. In the two models (pre-adoption and post-adoption) trust is only related to pre-adoption studies. Originally, 98 studies were coded but with the focus on pre-adoption and post-adoption, 53 were used in the final models as they contained the attributes of interest.

How privacy concerns and cultural differences affect public opinion during the COVID-19 pandemic: a case study

Purpose

COVID-19, an infectious disease first identified in China, has resulted in an ongoing pandemic all over the world. Most of the countries have been experiencing a difficult period during the fighting of this pandemic. The purpose of this study is to explore the effect of privacy concerns and cultural differences on public opinion related to the pandemic. The authors conducted a comparative analysis of public opinion in the US and in China as a case study, in order to determine the results.

Design/methodology/approach

National policies on important issues faced during the COVID-19 pandemic in the US and in China were examined through a comparative analysis. The authors used text clustering and visualization to mine public opinion on two popular social media platforms, Twitter and Weibo. From the perspectives of concern for privacy and of national culture, this study combines qualitative and quantitative analysis to discover the acceptance level of national policies by the public in the two countries.

Findings

The anti-pandemic policies and measures of the US and China reflect the different characteristics of their respective political systems and national cultures. When considering the culture of the US, it is hard to establish and enforce a rigorous regulation on either mask wearing in public or home quarantine on the national level. The opinions of US people are diverse, regarding national COVID-19 policies, but they are rather unified on privacy issues. On the other hand, Chinese people show a high acceptance of national policies based on their mask-wearing customs and their culture of collectivism.

Originality/value

Prior studies have paid insufficient attention to the ways in which user privacy and cultural difference affect public opinion on national policies between the US and China. This case study that compares public opinion on current and topical issues which are closely bound up with public life shows originality, as it innovatively provides a cross-cultural perspective on the research of public opinion dissemination during emergencies by considering the ongoing COVID-19 pandemic.

Digital Identity Management on Social Media: Exploring the Factors That Influence Personal Information Disclosure on Social Media

A number of social media platforms have emerged as dominant medium for societal discourse, enabling significant user involvement in creation and shaping of social media contents. However, the phenomenon raises the challenge of digital identity management on such platforms in order to maintain reputations and ensure information privacy preservation. This study examined the factors that influence users’ decision to disclose personal information on Social Media and their antecedents. We employed a mixed-methods approach based on analysis of data of 250 respondents from tertiary institutions in Ghana, and 8 focus group discussions comprising 86 participants. The results revealed a lack of user awareness and appreciation of the limitations of the privacy settings on social media platforms. Secondly, we observed that users’ ability to establish the legitimacy of parties to social media interactions are fundamental requirements in how individuals engage social media. Finally, there is a disparity between information privacy concerns and actual privacy practices of users on social media.