Investigating Privacy and Information Disclosure Behavior in Social Electronic Commerce

Research on user's highly sensitive privacy disclosure intention in home intelligent health service system: A perspective from trust enhancement mechanism

Objective

The aim is to investigate the determinants and mechanisms that influence user's highly sensitive privacy disclosure intention (HSPDI) in home intelligent health service system (HIHSS).

Methods

This study improves the privacy calculus theory by considering the influence of service providers' trust enhancement mechanism besides benefit and risk factors and investigates their impact on users' HSPDIs. This study takes perceived valence and perceived security as the trade-off result among perceived benefits, perceived risks, financial trust enhancement mechanism, and the technical trust enhancement mechanism and suggests that perceived valence and perceived security further affect users' HSPDI in HIHSS. Moreover, the common and differential effects of the perceived justice of privacy violation compensation (PJOPVC) and the perceived effectiveness of privacy protection technologies (PEOPPTs) are studied. The structural equation model is used to analyze 204 valid samples to test the proposed model.

Results

The results show that perceived benefits and perceived risks are important predictors of perceived valence and perceived security, and further affect users' HSPDI. We find PJOPVC has a greater impact on perceived valence while PEOPPT has a greater impact on perceived security.

Conclusions

We recommend that the HSPDI of users with low perceived valence can be improved by providing privacy violation compensation while the HSPDI of users with low perceived security can be enhanced by popularizing relevant knowledge of privacy protection technologies.

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.

On Students' Willingness to Use Online Learning: A Privacy Calculus Theory Approach

Online learning platforms frequently collect and store learners' data to personalize content and improve learning analytics, but this also increases the likelihood of privacy breaches which may reduce learners' willingness to use online learning. This study aims to examine how perceptions of benefits, privacy, risk, and trust affect students' willingness to use online learning. We used the Privacy Calculus Theory as a theoretical framework for this study. To test the model, we surveyed 203 undergraduate students who used online learning. The results of the AMOS analysis revealed that students' risk perception has a significant negative effect on their willingness to use online learning, while their benefit perception and trust perception have positive effects. Furthermore, the study found that improved trust can reduce perceived risk and improve willingness to use online learning. Interestingly, privacy perception is not a significant predictor of students' willingness to use online learning, although it is a high concern factor. Discussion and conclusion are discussed at the end.

Models of Privacy and Disclosure on Social Networking Sites: A Systematic Literature Review

Social networking sites (SNSs) are used widely, raising new issues in terms of privacy and disclosure. Although users are often concerned about their privacy, they often publish information on social networking sites willingly. Due to the growing number of users of social networking sites, substantial research has been conducted in recent years. In this paper, we conducted a systematic review of papers that included structural equations models (SEM), or other statistical models with privacy and disclosure constructs. A total of 98 such papers were found and included in the analysis. In this paper, we evaluated the presentation of results of the models containing privacy and disclosure constructs. We carried out an analysis of which background theories are used in such studies and have also found that the studies have not been carried out worldwide. Extending the research to other countries could help with better user awareness of the privacy and self-disclosure of users on SNSs.

Intelligent Information Network Security Management Strategy for Service Innovation of Manufacturing Enterprises Under Blockchain

Since the beginning of the new century, all manufacturing enterprises have been seeking ways to transform and upgrade the systems to maintain their competitive advantages. In the process of transformation and upgrading, service innovation has become more vital. In the service innovation mode, customers and suppliers are mainly involved in the manufacture of products. In the process of communication, these suppliers and customers need to rely on public key infrastructure (PKI) for data encryption and identity authentication operations, thereby achieving reliable information exchange and identity authentication in an untrusted environment. Therefore, ensuring the security of network communication for various types of users is crucial. The purpose of this paper is to solve the problem that results when a tampered certificate is difficult to trace due to the single point of failure and vulnerability of the current settlement and authentication system. In this scenario, the user's identity information is leaked in the certificate application. Resolving this problem is necessary to ensure the security of the information network.

Consumer Privacy Protection With the Growth of AI-Empowered Online Shopping Based on the Evolutionary Game Model

Social distancing due to the COVID-19 pandemic has driven some consumers to online shopping, and concerns about pandemic risks and personal hygiene have increased the demand for e-commerce. Providing personalized recommendations seems quite profitable for e-commerce platforms, and consumers also benefit from personalized content with the advancement of AI technologies. However, this possible win-win situation is marred by the increase in consumers' privacy concerns. Technical solutions have been widely studied to protect consumer privacy, while few analyses have been conducted from the perspective of psychological and behavioral implications. In this paper, an evolutionary game model of privacy protection between e-commerce platforms and consumers is established to determine the mechanisms by which various factors exert influence, and evolutionary stable strategies are obtained from equilibrium points. Then, the strategy selections are simulated with MATLAB 2020 software. Based on the results, the following conclusions are drawn: (1) the application of AI technologies in e-commerce will fundamentally benefit consumers, which makes them actively share personal information with e-commerce platforms with incentives for generous rewards; (2) it is profitable for e-commerce platforms to conduct data mining by improving the ability to use AI technologies and making efforts to reduce technical costs; and (3) regulators should improve the level of supervision instead of imposing a large penalty to enhance consumer trust, which could effectively increase the profits of e-commerce platforms and protect consumers' privacy.

Understanding the Key Antecedents of Users’ Disclosing Behaviors on Social Networking Sites: The Privacy Paradox

This study explored the formation mechanisms of users’ disclosing behaviors from the perspectives of the privacy paradox. The theoretical framework incorporates perceived control over personal information and subjective norms into the privacy calculus model. The proposed theoretical framework was empirically tested using survey data collected from 350 Facebook users. The findings show that users’ intention to disclose personal information has a marginally significant effect on users’ disclosing behaviors. The analysis results reveal that privacy concerns negatively affect the intention to disclose personal information while they are not significantly related to users’ disclosing behaviors. This study found that perceived control over personal information plays a significant role in enhancing trust in social network site (SNS) providers, users’ intention to disclose personal information, and users’ disclosing behaviors. Moreover, perceived control over personal information mitigates the level of privacy concerns. Several implications for research and practice are described.

Perceived Mental Benefit in Electronic Commerce: Development and Validation

There is no denying that electronic commerce has brought many benefits to consumers. In the competitive market, capturing the benefit that customers perceived will be the best way for the sustainability of online businesses. However, in the context of increasing human life quality, re-examining the beneficial dimensions of electronic commerce (e-commerce) is a necessity. This study aims to develop and validate a perceived benefit scale of e-commerce concerning the mental viewpoint. The qualitative research and quantitative research method are used according to the development and validation procedure proposed by Churchill in 1979. The research result indicates that the perceived mental benefit of online shopping is in the second-order concept of four dimensions, including perceived shopping enjoyment, perceived social interaction, perceived discreet shopping, and perceived control. Some research and managerial implications are proposed.