Perceived Privacy Risk Research Articles

Investigating the Drivers of E-Commerce Continuance Intentions Among Older Consumers in Latin America

This study investigates the drivers of e-commerce continuance intentions among older consumers in Latin America. It employs the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) to develop and test a conceptual model of e-commerce adoption for older adults in Chile. Data were collected through an online survey involving 202 participants aged 65 and over. The findings reveal that attitude toward e-commerce and three UTAUT2 predictors—performance expectancy, effort expectancy, and social influence—are significantly related to e-commerce continuance intentions. Consumer innovativeness also has an indirect relationship through its impact on attitudes toward e-commerce. Additionally, facilitating conditions and habit are indirectly and significantly related to e-commerce continuance intentions through their influence on effort expectancy. However, hedonic motivation, perceived privacy risk, and health condition do not serve as significant predictors of e-commerce continuance intentions. This study enhances the understanding of older consumers’ intentions to continue adopting e-commerce in a Latin American country.

Does telemedicine hold the key for reproductive health care? A quantitative examination of women's intentions toward use and accurate information disclosure.

To investigate women's perceptions of telemedicine for reproductive health care services, focusing on how perceived benefits and privacy risks influence their intentions to adopt telemedicine and their willingness to disclose personal health information. A cross-sectional survey was conducted. The study applied the privacy calculus theory to the context of telemedicine for reproductive health, using adapted, validated variables to develop the survey. Outcome variables included intentions to adopt telemedicine and willingness to disclose accurate personal health information. Data were collected in May and June 2023 using Qualtrics online panel services, targeting women across the United States who had not used telemedicine for reproductive health. The sample comprised 847 women aged 18 and older. Structural equation modeling was employed using AMOS v28.0 to test the hypothesized relationships between perceived benefits, perceived risks, and adoption intentions. The analysis controlled for age, household income, political affiliation, religious views, and prior births. Perceived benefits were positively related to intention to adopt telemedicine for reproductive care (β: 0.600, p < 0.001), and willingness to disclose accurate personal health information (β: 0.453, p < 0.001). Unexpectedly, perceived privacy risks were positively related to adoption intentions (β: 0.128, p < 0.001), but negatively related to willingness to disclose (β: -0.282, p < 0.001). Intentions to adopt were positively associated with willingness to disclose (β: 0.089, p < 0.05). Lastly, older women and women located in states with abortion restrictions expressed lower intentions to adopt. The model explained 40.2% of variance in intention to adopt and 38.3% of variance in willingness to disclose. The study demonstrates the importance of perceived benefits and privacy risks in driving telemedicine adoption and disclosure intentions among women in the reproductive health context. These findings suggest the need for targeted strategies to address privacy concerns and support telemedicine adoption, particularly in restrictive regulatory environments.

Intention to Use Leucorrheea Self-Test Innovation Kit and Collection Data through Mobile Application in Bangkok

Leukorrhea, or abnormal vaginal discharge (fungi, bacteria, and protozoa), can be indicated bacterial vaginosis or STIs. If not treated, these infections may lead to complications impacted fertility such as pelvic inflammatory disease (PID). Therefore, the goal is to develop a self-test kit for vaginal discharge detecting all three pathogens in one device. This study examines the acceptance of innovative technologies and factors affecting the intention to self-administered leucorrhoea test kits (SALTK) with results presentation and data transmission via mobile phones. Factors influencing such intention included technology acceptance (Technology Acceptance Model: TAM), facilitating conditions, social influence, and perceived privacy risk. The data were collected using an online Google Form questionnaire. A total of 450 valid questionnaires were used for analysis. The descriptive statistics employed in this study included percentage, means, and standard deviation, and the hypothesis was tested using multiple regression analysis. It was found that the factors impacting the intention to use SALTK with a statistical significance level of .05 were facilitating condition, social influence, perceived privacy risk, and three key technology acceptance components, namely perceived usefulness, perceived ease of use, and attitude toward using, respectively. SALTK modulates the beneficial for public health policies in Thailand and government agencies, the Food and Drug Administration and the Department of Disease Control, establishing prevention to reach the international standards.

Weighing user's privacy calculus on personal information disclosure: the moderating effect of social media identification

PurposeWith the widespread collection and utilization of user data, privacy security has become a crucial factor influencing online engagement. In response to the growing concern about privacy security issues on social media, this research aims to examine the key causes of social media users' privacy calculus and how the balance between perceived privacy risks and benefits affects users' privacy concerns and their subsequent willingness to disclose personal information.Design/methodology/approachThe characteristics of the privacy calculus were extracted through partially structured interviews. A research model derived from privacy calculus theory was constructed, and latent variable modeling was employed to validate the proposed hypotheses.FindingsInformation sensitivity, experiences of privacy violations, social influence and the effectiveness of privacy policies influence users' privacy calculus. Privacy risk positively influences privacy concerns. Personal information disclosure willingness is positively influenced by privacy benefits and negatively influenced by privacy concerns, with both paths moderated by social media identification.Originality/valueThis study explores the key antecedents of users' privacy calculus and how these factors influence privacy concerns and subsequent willingness to disclose information on social media. It offers new insights into the privacy paradox observed within social media by validating the moderating role of social media identification on users' information disclosure willingness.

That uncanny valley of mind: when anthropomorphic AI agents disrupt personalized advertising

This research, grounded in privacy calculus theory, examines how the anthropomorphization of AI agents affects consumers’ perceptions of privacy risks associated with personalized ads. Specifically, it explores strategies to reduce potential negative impacts. In Study 1, participants expressed concerns that highly anthropomorphized chatbots might possess human-like autonomous intentions to misuse personal data, a phenomenon referred to as the ‘uncanny valley of mind’. In contrast, participants felt more secure, in control, and less concerned about privacy when interacting with a mechanized, less human-like chatbot. To address this backfiring effect, Study 2 explored the role of algorithmic disclosure – where companies provide transparent information about the underlying algorithms, data handling procedures, and personalization criteria. This strategy effectively mitigated privacy concerns, thereby preventing the negative effects associated with highly anthropomorphized AI chatbots. These findings offer valuable insights for marketers utilizing AI chatbots to craft effective, personalized messages based on social media data.

Bridging the Intention–Behavior Gap in Facial Recognition Payment from an Innovation Resistance Perspective: A Mixed-Method Approach

Face Recognition Payment (FRP) technology and devices in the offline market continue to mature and popularize, and how to further promote the use of FRP deserves our attention. Previous studies have focused more on the antecedent elements that influence users’ intention to use FRP. To date, we still know little about what motivates the gap between FRP use intention and behavior. We conduct a two-stage study using a mixed-methods approach. We conduct 142 interviews in Study 1 to identify barriers to this study. Based on this, the appropriate research model is formulated. In study 2, we collect a valid sample of 275 data points and employ regression analysis to examine the model. To answer this question, this study adopts innovation resistance theory (IRT) to develop a research model. The results suggest that the degree of influence of FRP use intention on use behavior depends on users’ habits, complexity, embarrassment, perceived privacy risk, and expected switching costs. All of these factors negatively influence the extent to which intention acts on behavior. This study helps bridge the FRP use intention–behavior gap and provides practical suggestions for offline retailers and design units in designing and marketing FRP technology in a rational way.

Acceptance of AI-powered facial recognition technology in surveillance scenarios: Role of trust, security, and privacy perceptions

The study examines the roles of various layers of trust, as well as privacy and security concerns, in shaping the acceptance of AI-powered facial recognition technology (FRT) in three surveillance scenarios—public spaces, hospitals, and schools. Based on survey data from 575 U S. participants, we found that the context in which FRT is deployed shapes people's perceptions and acceptance of the technology. People perceived greater safety gains in schools and greater privacy risks in public spaces. Trust in officials, familiarity with FRT, and perceived security benefits positively predicted acceptance, while distrust and perceived privacy risks negatively predicted acceptance. These findings offer insights for stakeholders of FRT, policymakers, and organizations that seek to implement AI-powered surveillance, emphasizing the need to address public trust and privacy concerns.

Promoting Consumers’ Adoption of Buy-Now-Pay-Later Feature while Using E-wallet Application: The Case of Gen Z in Vietnam

The Buy-Now-Pay-Later (BNPL) feature has emerged as a popular payment innovation, offering users convenience and flexibility in their purchasing behavior. However, consumers' adoption of BNPL is often limited due to the trust issue usually associated with electronic payment. Previous studies have highlighted personal traits that affect consumers’ trust in adopting BNPL, such as risky indebtedness behaviour or privacy concern. Adopting the Stimulus-Organism-Response framework, this study investigates environmental factors influencing consumers’ attitudes and perceptions of privacy risks and trust. The main objective of this study is to identify these factors, which can be valuable to practitioners in promoting consumers' intention to adopt BNPL. The model was tested based on data collected from 430 young Vietnamese consumers. Data analysis is conducted using SmartPLS 4.0. The study's findings, which are significant in consumer behavior, confirm that behavior intention to use BNPL results from attitude, trust, and perceived risk, which were influenced by perceived ease of use and subjective norms. These findings provide actionable insights for practitioners in the field, equipping them with the knowledge to promote BNPL adoption effectively. One notable result of the research is that perceived ease of use has a negative impact on privacy risk. This finding implies that users’ primary apprehension in using the E-wallet BNPL feature pertains to the risk of losing their privacy. It strongly recommends that developers create a more user-friendly and transparent BNPL experience to alleviate privacy concerns and enhance user trust, thereby promoting the adoption of BNPL.

Exploring the Impact of Social Robot Design Characteristics on Users’ Privacy Concerns: Evidence from PLS-SEM and FsQCA

Although an increasing number of studies explore the factors influencing users’ privacy concerns regarding social robots, the existing understanding of this issue remains largely fragmented. Previous studies have mainly focused on the "net effect" between variables, leaving the complexity of causal configurations, and the holistic impact of design characteristics of social robots on user privacy concerns remains unclear. Based on the Stimuli-Organism-Response (S-O-R) framework and Communication Privacy Management Theory (CPMT), this study integrates social robot design characteristics such as Anthropomorphism, Warmth, Competence, and Transparency into causal configurations, and uses Perceived Privacy Risk and Perceived Privacy Control as mediating variables to propose a Comprehensive conceptual model. Based on valid data from a sample of 198 Chinese social robot users, this study conducted empirical analyses of the conceptual model using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (FsQCA). PLS-SEM results show that anthropomorphism, warmth, competence, and transparency are key factors influencing privacy concerns, and perceived privacy risk mediates the relationship between warmth, information transparency, and privacy concerns. The FsQCA results further validated the findings of PLS-SEM and identified five configurations of factor combinations that led to higher levels of user privacy concerns. Among them, the combination of high anthropomorphism design, high competence, and low warmth of social robots is the core configuration that leads to users’ privacy concerns. Overall, this study broadens our understanding of social robot users’ privacy concerns and reveals the causal complexity behind social robot users’ privacy concerns. It provides some theoretical and practical insights for subsequent scholars and designers.

User-centric design experience or privacy risk perception? The dual pathways of tourism platform’s AI capability to perceived user value

ABSTRACT According to the theory of data network effect, this study investigates the dual-pathway impact mechanism of a platform’s artificial intelligence (AI) capability on the users’ perceived value of tourism platforms through experienced user-centric design and perceived private privacy. A sample of 220 users from tourism platforms were surveyed using a two-wave survey method to test the hypotheses. The results indicate that the AI capability of a platform positively influenced perceived user value through experienced user-centric design, while negatively affecting perceived user value through perceived privacy risk. Additionally, the findings suggest that data stewardship strengthens the relationship between AI capability and experienced user-centric design. Unexpectedly, data stewardship also strengthens the relationship between AI capability and perceived privacy risk. We also discussed the theoretical and practical implications of the findings on the dual-pathway effect of platforms’ AI capability, as well as suggestions for future research.

Unlocking Generation Y’s continuance intentions in personal cloud storage services: an extended expectation confirmation model analysis

PurposeThis study aims to investigate the factors that influence the continuance intention to use personal cloud storage services among Generation Y.Design/methodology/approachA quantitative online survey was carried out to collect data from 271 respondents. Structural equation modelling with SmartPLS 4.0 software was used to run the analysis and examine the hypothesized relationships in the research model.FindingsThe study revealed that both satisfaction and habit exert a significant influence on continuance intention, whereas self-efficacy does not demonstrate a significant effect. In addition, satisfaction was found to be influenced by confirmation, perceived usefulness and perceived security. Furthermore, confirmation and cloud storage service quality were found to impact perceived usefulness, while confirmation also had an effect on perceived security. However, the hypothesized moderating role of perceived privacy risk in the relationship between perceived usefulness, perceived security and satisfaction was not supported.Originality/valueThis study advances the field by adapting an expanded expectation-confirmation model that delineates the nuanced impacts of habit, user satisfaction and self-efficacy on Generation Y’s continuance intention to use personal cloud storage services. It challenges the conventional wisdom regarding self-efficacy’s influence on technology adoption, offering a more intricate portrayal of its role. This research contributes a distinctive theoretical perspective, emphasizing the complex interplay of factors that inform sustained user engagement with cloud technologies.

Rounding for Warmth, Angling for Fluency: How Shapes, Cognitive Load, and Privacy Risk Influence App Adoption

Delving into corner shapes in interface design (i.e., circular vs. angular), we experimentally delineated two routes whereby users with strong privacy risk beliefs can be persuaded into adopting a mobile payment app through a bill-split use case. By introducing cognitive load as an ability factor and perceived privacy risk as a motivation force, this study bridges literature on user interface design with social psychology to unpack how subtle design cues impact app adoption through the lens of privacy assurance. The interplay among shapes, tasks, and user traits demonstrates the contextual efficacy of circular design to evoke social presence and the benefit of angular design to enhance processing fluency, which tap into users’ affective and cognitive needs in face of privacy risks under varied cognitive demands to encourage adoption.

The Effect of Brand Heritage on Social Commerce Site Privacy Risk, Brand Equity, and Brand Advocacy

This study applies the Stimuli-Organism-Response (S-O-R) Theory to examine the impact of brand heritage of social commerce sites on consumers' perceived privacy risk, and the impact of this perceived risk on brand equity and brand advocacy. This study extends brand heritage research by exploring brand heritage in a new context (social commerce sites). To test the hypotheses, an online survey was conducted, and a total of 321 responses were collected from Amazon users in the US. The data were analyzed by using the Partial Least Squares-Structural Equation Modelling (PLS-SEM). Findings revealed that the brand heritage of social commerce sites has a significant negative influence on consumers' perceived privacy risk, which in turn has a significant negative impact on brand equity and brand advocacy.

How consumers' privacy perceptions influenced mobile payment acceptance during the COVID-19 pandemic

PurposeOur research investigated how the perceived effectiveness of privacy, perceived privacy risk, and perceived security influenced consumers' behavioral intention to use mobile payment applications during the COVID-19 pandemic.Design/methodology/approachWe applied a quantitative method using a cross-sectional online survey conducted over three years. We collected a sample of 1,471 survey responses focused on ages 18–39. Using descriptive statistics, confirmatory factor analysis, and structural equation modeling, we tested our hypotheses with SPSS 27 and AMOS 27.FindingsResults of the study indicate that the perceived effectiveness of privacy positively influences perceived privacy risk, perceived security, and behavioral intention. Moreover, perceived privacy risk has a positive effect on perceived security. We found no significant relationship between perceived privacy risk and behavioral intention, although perceived security has a positive effect on behavioral intention. Further mediation analyses showed that perceived privacy risk and perceived security mediate the relationship between the perceived effectiveness of privacy and behavioral intention.Originality/valueThis research sheds new light on the role of perceived privacy effectiveness in mobile payment adoption in Hungary, particularly during the COVID-19 pandemic. Our research also explains why and how perceived privacy effectiveness influences consumers' perceived privacy risk, perceived security, and behavioral intention.

Coping Responses to the Stress of Using News Platforms’ Recommendation Algorithms

Drawing on the stressor–strain–outcome (SSO) framework, this study examined how information-related stressors (perceived information overload, information quality deterioration, and information narrowing) and privacy-related stressor (perceived privacy risk) in using news platforms’ recommendation algorithms trigger users’ psychological reactance, which leads to their active coping, expressive coping, or avoidance coping with their stress in using such recommendation algorithms. Using a sample of 352 valid research responses, this study found that users’ psychological reactance is positively influenced by perceived information quality deterioration, followed by perceived information overload and perceived privacy risk. Meanwhile, perceived information narrowing has no significant impact on psychological reactance. In turn, psychological reactance exerts a stronger impact on expressive coping and avoidance coping responses than on active coping response. This study enriches the literature on the stress in algorithm usage at the individual level and provides practical insights for the providers of news platforms which have applied recommendation algorithms.

Consumer Acceptance of Drones for Last-Mile Delivery in Jeddah, Saudi Arabia

The number of industries using drones is increasing. Although early research was conducted on drones, the prior literature has not emphasized consumer adoption of drones for item delivery. Consequently, this study investigates whether customers are open to receiving packages from drones. This study also examines the elements that influence customers’ willingness to adopt drone package delivery. This study fills a gap in the logistics and service research by examining people’s concerns regarding using drones. The unified theory of acceptance and use of technology (UTAUT2) serves as the basis for the conceptual framework. A self-administered online survey is deployed. The results demonstrate that perceived privacy risks negatively influence performance and effort expectancy as well as facilitating conditions and social influence. This study further validates the UTAUT2 by confirming the influence of performance expectancy and facilitating conditions on attitudes toward adopting drones. Moreover, this study confirms the positive influence of attitude on behavior. This study has managerial implications, one of which is the suggestion that the deployment and use of drones should minimize interference with people’s privacy.

The Perceived Privacy Risk in the Modern Society (Case in Customer E-Commerce)

The Perceived Privacy Risk in the Modern Society (Case in Customer E-Commerce)

Factors Influencing the Adoption of Mobile Banking Applications in Yemen Using an Extended Technology Acceptance Model

Factors Influencing the Adoption of Mobile Banking Applications in Yemen Using an Extended Technology Acceptance Model

Privacy or trust: understanding the privacy paradox in users intentions towards e-pharmacy adoption through the lens of privacy-calculus model

Purpose This study aims to present a comprehensive investigation into users’ behavioural intentions to use e-pharmacies through the lens of the privacy calculus model. The present study also investigates the effects of perceived benefit, perceived privacy risk, timeliness and perceived app quality on e-pharmacy usage through the mediating role of trustworthiness. Design/methodology/approach The study used a deductive approach and collected data from 338 respondents using the purposive sampling technique. partial least squares structural equation modelling was applied to analyse the data. Findings The findings of the study indicate that perceived benefit, perceived privacy risk, timeliness and perceived app quality do not directly impact users’ behavioural intentions towards e-pharmacy adoption. Instead, it demonstrated that perceived benefit, perceived privacy risk, timeliness and perceived app quality influenced behavioural intention indirectly through the mediating role of trustworthiness Originality/value This study offers valuable insights to entrepreneurs, marketers and policymakers, enabling them to develop regulations, guidelines and policies that cultivate trust, safeguard privacy, ensure prompt services and create an enabling environment for the adoption of e-pharmacies. The present study also contributes to the existing literature by extending the privacy calculus model with the integration of timeliness and perceived app quality to explain users’ adoption behaviour towards e-pharmacy.

Unlock Happy Interactions: Voice Assistants Enable Autonomy and Timeliness

This study examines the effects of three interactive voice assistant (VA) features (responsiveness, ubiquitous connectivity, and personalization) on consumer happiness. An online survey was administered to 316 VA consumers, and the data were analyzed using structural equation modeling with SmartPLS 4 software. The results indicate that VA responsiveness, ubiquitous connectivity, and personalization have significant effects on consumer happiness. This study also provides evidence that consumer happiness is influenced by VA features through the mediating roles of autonomy and timeliness. Notably, perceived privacy risk has a dual effect, negatively affecting happiness but positively moderating the relationship between autonomy and happiness, suggesting a complex interplay between benefits and concerns in user interactions with VAs. This study highlights the need for VA businesses to consider both the enhancing and mitigating factors of technology for user experiences. Furthermore, our findings have significant implications for VA businesses and executives, suggesting that improved interactions through these VA features can better serve consumers and enhance their experiences.