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This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.

Increasing incidents of privacy invasion on social networking sites (SNS) are intensifying the concerns among stakeholders about the misuse of personal data. However, there seems to be limited research on exploring the impact of specific privacy concerns on users’ intention to engage in various privacy protection behaviors. This study aims to examine the role of social privacy concerns, institutional privacy concerns and privacy self-efficacy as antecedents of privacy protection–related control activities intention among young adults active on SNS.

Data collected from 284 young adults active on SNS was analyzed through partial least squares structural equation modeling using Smart PLS.

The results indicate that institutional privacy concerns, social privacy concerns and privacy self-efficacy positively influence the control activities intention of SNS users. The extent of privacy self-efficacy and privacy protection-related control activities intention differs among users based on gender.

This study is limited to a population of young adults in the age group of 18–25 years.

The findings of this study form the basis for specific recommendations addressing the different types of privacy concerns experienced by social media users, promoting responsible privacy control behaviors on online platforms and discouraging the possible misuse of information by third parties.

This study validates a theoretical framework that can contribute to future investigations concerning the use of SNS. The study findings form the basis for a set of practical recommendations for policymakers, SNS platforms and users.

This study aims to propose an innovative model that integrates variables and examines the influence of internet usage expertise, perceived risk and attitude toward information control on privacy concerns (PC) and, consequently, in consumers’ willingness to disclose personal information online. The authors also propose to test the mediation role of trust between PCs and willingness to disclose information. Trust is not a predictor of PC but a causal mechanism – considering that the focus is to understand consumers’ attitudes and behavior regarding the virtual environment (not context-specific) (Martin, 2018).

The authors developed a survey questionnaire based on the constructs that compose the proposed model to collect data from 864 respondents. The survey questionnaire included the following scales: internet usage expertise from Ohanian (1990); perceived risk, attitude toward information control, trust and willingness to disclose personal information online from Malhotra et al. (2004); and PC from Castañeda and Montoro (2007). All items were measured on a Likert seven-point scale (1 = totally disagree; 7 = totally agree). To obtain Westin’s attitudinal categories toward privacy, respondents answered Westin’s three-item privacy index. For data analysis, the authors applied covariance-based structural equation modeling.

First, the proposed model explains the drivers of consumers’ disposition to provide personal information at a level that surpasses specific contexts (Martin, 2018), bringing the analysis to consumers’ level and considering their general perceptions toward data privacy. Second, the findings provide inputs to propose a better definition of Westin’s attitudinal categories toward privacy, which used to be defined only by individuals’ information privacy perception. Consumers’ perceptions about their abilities in using the internet, the risks, their beliefs toward information control and trust also help to delimitate and distinguish the fundamentalists, the pragmatics and the unconcerned.

Some limitations weigh the theoretical and practical implications of this study. The sample size of pragmatic and unconcerned respondents was substantially smaller than that of fundamentalists. It might be explained by applying Westin’s self-report index to classify the groups according to their score regarding PCs. Most individuals affirm having a great concern for their data privacy but still provide online information for the benefit of personalization – known as the privacy paradox (Zeng et al., 2021). It leads to another limitation of this research, given the lack of measures that classify respondents by considering their actual behavior toward privacy.

PC emerges as an important predictor of consumer trust and willingness to disclose their data online, and trust also influences this disposition. Managers need to implement actions that effectively reduce consumers’ concerns about privacy and increase their trust in the company – e.g. adopting a clear and transparent policy on how the data collected is stored, treated, protected and used to benefit the consumer. Regarding the perception of risk, if managers convince consumers that the data collected on the internet is protected, they tend to be less concerned about privacy.

The results suggest different aspects influencing the willingness to disclose personal information online, including different responses considering consumers’ PCs. Through their policies and legislation, the authors understand that governments must be attentive to this aspect, establishing regulations that protect consumers’ data in the virtual environment. In addition to regulatory policies, education campaigns can be carried out for both consumers and managers to raise the discussion about privacy and the availability of information in the online environment, demonstrating the importance of protecting personal data to benefit the government, consumers and organizations.

Although there is increasing research on consumers’ privacy, studies have not considered their attitudinal classifications – high, moderate and low concern – as moderators of willingness to disclose information online. Researchers have also increased attention to the antecedents of PCs and disclosure of information but overlooked possible mechanisms that explain the relationship between them.

The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.

Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.

Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.

Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.

Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.

Research on online user privacy shows that empirical evidence on how privacy literacy relates to users' information privacy empowerment is missing. To fill this gap, this paper investigated the respective influence of two primary dimensions of online privacy literacy – namely declarative and procedural knowledge – on online users' information privacy empowerment.

An empirical analysis is conducted using a dataset collected in Europe. This survey was conducted in 2019 among 27,524 representative respondents of the European population.

The main results show that users' procedural knowledge is positively linked to users' privacy empowerment. The relationship between users' declarative knowledge and users' privacy empowerment is partially supported. While greater awareness about firms and organizations practices in terms of data collections and further uses conditions was found to be significantly associated with increased users' privacy empowerment, unpredictably, results revealed that the awareness about the GDPR and user’s privacy empowerment are negatively associated. The empirical findings reveal also that greater online privacy literacy is associated with heightened users' information privacy empowerment.

While few advanced studies made systematic efforts to measure changes occurred on websites since the GDPR enforcement, it remains unclear, however, how individuals perceive, understand and apply the GDPR rights/guarantees and their likelihood to strengthen users' information privacy control. Therefore, this paper contributes empirically to understanding how online users' privacy literacy shaped by both users' declarative and procedural knowledge is likely to affect users' information privacy empowerment. The study empirically investigates the effectiveness of the GDPR in raising users' information privacy empowerment from user-based perspective. Results stress the importance of greater transparency of data tracking and processing decisions made by online businesses and services to strengthen users' control over information privacy. Study findings also put emphasis on the crucial need for more educational efforts to raise users' awareness about the GDPR rights/guarantees related to data protection. Empirical findings also show that users who are more likely to adopt self-protective approaches to reinforce personal data privacy are more likely to perceive greater control over personal data. A broad implication of this finding for practitioners and E-businesses stresses the need for empowering users with adequate privacy protection tools to ensure more confidential transactions.

Based on the cognition–affect–conation pattern, this study explores the factors that affect the intention to use facial recognition services (FRS). The study adopts the driving factor perspective to examine how network externalities influence FRS use intention through the mediating role of satisfaction and the barrier factor perspective to analyze how perceived privacy risk affects FRS use intention through the mediating role of privacy cynicism.

The data collected from 478 Chinese FRS users are analyzed via partial least squares-based structural equation modeling (PLS-SEM).

The study produces the following results. (1) FRS use intention is motivated directly by the positive affective factor of satisfaction and the negative affective factor of privacy cynicism. (2) Satisfaction is affected by cognitive factors related to network externalities. Perceived complementarity and perceived compatibility, two indirect network externalities, positively affect satisfaction, whereas perceived critical mass, a direct network externality, does not significantly affect satisfaction. In addition, perceived privacy risk generates privacy cynicism. (3) Resistance to change positively moderates the relationship between privacy cynicism and intention to use FRS.

This study extends knowledge on people's use of FRS by exploring affect- and cognitive-based factors and finding that the affect-based factors (satisfaction and privacy cynicism) play fully mediating roles in the relationship between the cognitive-based factors and use intention. This study also expands the cognitive boundaries of FRS use by exploring the functional condition between affect-based factors and use intention, that is, the moderating role of resistance to use.

During the past few years, social media has faced the challenge of maintaining its user base. Reports show that the social media giants such as Facebook and Twitter experienced a decline in their users. Taking WhatsApp's recent change of its terms of use as the case of this study and using the push-pull-mooring model and a configurational perspective, this study aims to identify pathways for switching intentions.

Data were collected from 624 WhatsApp users recruited from Amazon Mechanical Turk and analyzed using fuzzy set qualitative comparative analysis (fsQCA).

The findings identify seven configurations for high switching intentions and four configurations for low intentions to switch. Firm reputation and critical mass increase intention to switch, while low firm reputation and absence of attractive alternatives hinder switching.

This study extends extant literature on social media migration by identifying configurations that result in high and low switching intention among messaging applications.

The study identifies factors the technology service providers should consider to attract new users and retain existing users.

This study complements the extant literature on switching intention that explains the phenomenon based on a net-effect approach by offering an alternative view that focuses on the existence of multiple pathways to social media switching. It further advances the authors’ understanding of the relevant importance of switching factors.

Online advertising becomes an essential tool to reach the target audience. One of the most widely used strategies is re-targeting. Firstly, this study explores the impact of ethics, privacy and ads' perceived benefits (ad effectiveness and ad relevance) on consumers' attitudes toward online advertising. Secondly, the study investigates the mediating effect of attitudes toward re-targeting online advertising on consumers' purchase intentions. Finally, the study investigates the moderating effect of the perceived ethicality of re-targeting online advertising on consumers' purchase intentions.

Participants (n = 307) were recruited through an online survey platform (MTurk) in the USA. The sample consisted of 65% male and 35% female respondents. The majority are aged 25–34 years, followed by 35–44 years (20%), 45–54 years (14%), 18–24 years (8%) and 55 years and older (6%).

The results show that ad effectiveness and ad relevance influenced consumers' attitudes toward re-targeting. This study shows that consumers are willing to trade their privacy for better search quality. Moreover, perceptions toward the ethicality of re-targeting ads moderated the relationship between consumers' attitudes and purchase intentions.

This study will make several contributions. First, the study will extend the consequential theory in the context of online advertising. Second, the study will assist companies in using re-targeting strategies. The results will reveal which factor is the most important factor impacting consumers' attitudes toward re-targeting strategies.

This is one of the first few papers investigating consumers' perceptions of the ethicality of re-targeting online advertising.

For the provision of smart library services to end users, tools of the Internet of Things (IoT) play a significant role. The study aims to discover the factors influencing the adoption of IoT in university libraries, investigate the impact of IoT on university library services and identify challenges to adopt IoT applications in university libraries.

A systematic literature review was carried out to address the objectives of the study. The 40 most relevant research papers published in the world’s leading digital databases were selected to conduct the study.

The findings illustrated that rapid growth in technology, perceived benefits, the networked world and the changing landscape of librarianship positively influenced the adoption of IoT in university libraries. The study also displayed that IoT supported library professionals to initiate smart library services, assisted in service efficiency, offered context-based library services, provided tracking facilities and delivered effective management of library systems. Results also revealed that a lack of technical infrastructure, security and privacy concerns, a lack of technological skills and unavailability of policy and strategic planning caused barriers to the successful adoption of IoT applications in university libraries.

The study has provided theoretical implications through a valuable addition to the current literature. It has also offered managerial implications for policymakers to construct productive policies for the implementation of IoT applications in university libraries for the attainment of fruitful outcomes. Finally, the study provides a baseline for understanding the adoption of IoT in academic libraries.

This study aims to reveal how mobile app stickiness is formed and how the stickiness formation process differs for apps of different social levels.

This study proposed and validated a stickiness formation model following the cognitive–affective–conative framework. Data were collected from surveys of 1,240 mobile app users and analyzed using structural equation modeling. Multigroup analysis was applied to contrast the stickiness formation process among apps of different social levels.

This study revealed a causal link between cognitive, affective and conative factors. It found partial mediation effects of trust in the association between perceptions and satisfaction, and the full mediation role of satisfaction and personal investment (PI) in the effects of subjective norm (SN) on stickiness. The multigroup analysis results suggested that social media affordances benefit stickiness through increased PI and strengthened effects of SN on PI. However, it damages stickiness through increased perceived privacy risk (PPR), decreased trust and strengthened effects of PPR on trust.

This study contributes to both stickiness scholars and practitioners, as it builds a model to understand the stickiness formation process and reveals the effects of the “go social” strategy. The novelty of this study is that it examined social influences, considered privacy issues and revealed two mediation mechanisms. The findings can guide the improvement of mobile app stickiness and the application of the “go social” strategy.