Privacy Calculus Theory Research Articles

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.

Disclosing Personal Health Information to Emotional Human Doctors or Unemotional AI Doctors? Experimental Evidence Based on Privacy Calculus Theory

The commercialization of artificial intelligence (AI) in healthcare is accelerating, yet academic research on its users remains scarce. To what extent are they willing to disclose personal health privacy to AI doctors compared to traditional human doctors? What factors are shaping these decisions? The lack of user research has left these questions unanswered. This article, based on privacy calculus theory, conducted a multi-factorial between-subjects online experiment (N = 582) with a 2 (medical provider: AI vs. human) × 2 (emotional support: low vs. high) × 2 (information sensitivity: low vs. high) design. The results indicated that AI doctors lead participants to perceive both lower health benefits and privacy risks. Emotional support is not always beneficial. On one hand, high emotional support can provide patients with more health benefits, but on the other hand, it also poses higher levels of privacy risks. Additionally, high emotional support responses from AI doctors could enhance patients’ health benefits, trust, and willingness to disclose health privacy, while the opposite was observed for human doctors.

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.

Privacy Awareness and Social Media: Personal Data Protection among Facebook** and Instagram** Users

This study investigated the level of awareness of personal data protection among Facebook** and Instagram** users. The research evaluated the number of Facebook and Instagram users who have taken precautions to secure their personal data, why they did so, and the identification of regulatory authorities responsible for data protection in Nigeria. The Privacy Calculus Theory was used as the theoretical framework. The survey research design was used for this study, with the web-based questionnaire as the instrument for data collection. A sample size of 396 was drawn from the student population at the University of Port Harcourt. The data were analyzed in tables using frequency and percentage. The results indicated that users are strongly aware of the significance of safeguarding personal data on Facebook and Instagram. The users acknowledged implementing precautionary steps to safeguard their personal data. However, they still need to determine the specific agencies and regulatory entities accountable for ensuring the safety of personal data. In order to tackle this problem, the study recommended that the University management and student bodies should organize specific educational workshops to promote understanding of the pertinence of safeguarding personal data on social media platforms (Solove, 2021), create easily accessible materials and guidelines on the University of Port Harcourt portal designed for social media users, outlining the best methods for protecting personal data, including personal data protection awareness in its orientation programs and student events and also set up a system for reporting potential data breaches and offer assistance to affected users. ** – A social network owned by “Meta”, which is recognized as extremist in Russia

Sell your soul for a pot of gold: Privacy paradox in surveillance capitalism

The current study aims to examine the underlying psychological processes involved in privacy protection behaviors among tourists in retail environments using surveillance technologies. Protection Motivation Theory (PMT) and Privacy Calculus Theory (PCT) were employed to understand threat and coping appraisals, benefits (control vs monetary), and their relationships with protective behavioral intentions and actual behaviors. Data was collected from 554 respondents who had visited a retail store while traveling in the past 6 months using an online questionnaire. Three structural equation models, full mediation, partial mediation, and moderated mediation were tested and compared. The partial mediation model exhibited the best fit. Perceived severity and susceptibility increased protective behavioral intentions, while self-efficacy decreased intentions. Control compensation positively influenced intentions only. Behavioral intentions partially mediated relationships between independent variables and actual protective behaviors. No significant moderation effects were found. Integrating PMT and PCT addresses a significant gap in examining tourists’ privacy-protective behaviors in retail surveillance contexts. Additionally, it clarifies the effectiveness of control and monetary benefits in mitigating privacy concerns.

The effects of motivated consumer innovativeness on consumer acceptance of autonomous delivery robots

This research aimed to examine the impacts of motivated consumer innovativeness on customers’ acceptance of autonomous delivery robots (ADRs) using the privacy calculus theory (PCT) and motivated consumer innovativeness theory (MCI). It was suggested that this impact was mediated by perceived risks and perceived cooperativeness. Four hundred and fifty survey responses were gathered through a stratified random sampling approach to effectively represent the population of Singapore, ensuring the sample’s representativeness. The acquired data underwent analysis via structural equation modelling, uncovering that motivated consumer innovativeness (MCI) (i.e. functional MCI, hedonic MCI, cognitive MCI, and social MCI) influences the perceived (privacy) risks of using ADRs. In addition, the perceived risks influence the perceived cooperativeness of ADRs. Furthermore, the perceived risks and perceived cooperativeness both influence the consumers’ acceptance of ADRs. The combination of theories is highly effective in explaining consumers’ acceptance of ADRs, accounting for a substantial 78.3% of the variance. These findings highlight the significant impact of enhancing perceptions of ADR cooperativeness and transparent communication about privacy and safety on consumer acceptance. This, in turn, informs effective policy and strategic decisions for ADR development and deployment.

How to Balance Privacy and (Health) Benefits: Privacy Calculus and the Intention to Use Health Tracking at the Workplace

To address increasing pressures experienced in the workplace, the use of wearables as part of workplace health promotion programs is on the rise. Even though the benefits are well-known, participation rates are often low due to privacy-related issues. Therefore, this study illuminates the area of privacy further by investigating the influence of the wearable’s additional private use and limited data access on employees’ intended use. Based on technology acceptance and Privacy Calculus Theory, this study applied a factorial survey experiment to test several literature-driven hypotheses. While restricting data access to the employee has a positive impact on employees’ privacy concerns, perceived benefits, and intended use, the possibility of private use is only of secondary relevance for individuals’ privacy perceptions and intention to use. The results provide empirical evidence on how the design of digital workplace health promotion programs can increase conscious participation.

Influence of personality traits on generation Z consumers' click-through intentions towards personalized advertisements: A mixed-methods study

Personalized social media advertisements (PSMAs) are developed by using consumers' personal information like names, demographic details, location, past buying history, and lifestyle interests to quickly grab consumers' attention within the cluttered space of digital advertisements. Generation Z consumers are highly connected to social media. Hence, this study attempts to understand how Generation Z consumers with different personality traits perceive personalized advertisements (PAs) on Facebook, and subsequently, how their perceived personalization influences their intention to click on PAs based on perceived usefulness and privacy concerns associated with those advertisements. The theoretical underpinning of this research is based on the self-congruency theory and privacy-calculus theory. An explanatory sequential mixed-methods design has been adopted, where a quantitative analysis (Study 1) is followed by a qualitative approach (Study 2). For Study 1, responses were collected from 324 Generation Z consumers through a structured questionnaire and the data was analyzed using the structural equation modeling technique to measure relationships among the constructs. Further, in Study 2, in-depth interviews were conducted with 15 Generation Z consumers, a purposively selected subset of informants from Study 1, to explore the potential causes of those relationships observed in Study 1. It has been found from the study that consumers' perception of PSMAs varies based on their personality traits. Consumers with dominant extraversion, conscientiousness, and neurotic personality traits perceive PSMAs positively whereas the openness to experience and agreeableness dominant consumers perceive those negatively. Positive perception of PSMAs among consumers increases the perceived usefulness of communications and subsequently improves the click-through intentions of the consumers. Generation Z Consumers' perception of PSMAs does not have any influence on their privacy concerns. Consumers’ high privacy concerns reduce the click-through intention rate toward PSMAs. The study will help digital marketing managers to strategically deliver PSMAs, thereby enhancing the efficiency of their advertisements.

To disclose or to protect? Predicting social media users’ behavioral intention toward privacy

PurposeIn the paradox of personalized services and privacy risks, what factors influence users’ decisions is considered an interesting issue worth exploring. The current study aims to empirically explore privacy behavior of social media users by developing a theoretical model based on privacy calculus theory.Design/methodology/approachPrivacy risks, conceptualized as natural risks and integrated risks, were proposed to affect the intention of privacy disclosure and protection. The model was validated through a hybrid approach of structural equation modeling (SEM)-artificial neural network (ANN) to analyze the data collected from 527 effective responses.FindingsThe results from the SEM analysis indicated that social interaction and perceived enjoyment were strong determinants of perceived benefits, which in turn played a dominant role in the intention to disclose the privacy in social media. Similarly, trust and privacy invasion experience were significantly related to perceived risks that had the most considerable effect on users’ privacy protection intention. And the following ANN models revealed consistent relationships and rankings with the SEM results.Originality/valueThis study broadened the application perspective of privacy calculus theory to identify both linear and non-linear effects of privacy risks and privacy benefits on users’ intention to disclose or protect their privacy by using a state-of-the-art methodological approach combining SEM and ANN.

An investigation into factors affecting the willingness to disclose personal health information when using AI-enabled caregiver robots

PurposeThe 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.Design/methodology/approachDrawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.FindingsEmpirical 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.Practical implicationsGiven 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.Originality/valueConsidering 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.

Self-Disclosure on Social Media: Do Personality Traits Matter?

The aim of this study is to integrate the privacy calculus theory with the Big Five Personality Traits Theory and to investigate the direct and moderating effects of the Big Five personality traits (openness, neuroticism, agreeableness, extraversion, and conscientiousness) on the relationship between the privacy calculus structural factors (Perceived Risk and Perceived Benefits) and disclosure of personal information on social network sites. A survey was conducted to collect data from 379 social network sites users. The sample is composed of 225 females and 154 males. The survey was designed in Qualtrics and distributed on WhatsApp using the snowball sampling technique. The measurements of the research model and the hypotheses related to the direct and moderating effects were tested using SmartPLS software. We found that perceived risk was a strong inhibitor, while perceived benefit was a strong facilitator for the disclosure of personal information. In contrast to our expectation, we found no indication that the Big Five personality traits moderate the disclosure of personal information. However, agreeableness had a positive direct effect on information disclosure. These results have implications for privacy policy makers in organizations in modifying policies and strategies for users based on their unique personality traits.

Generation Z's perception of privacy on social media: Examining the impact of personalized advertising, interpersonal relationships, reference group dynamics, social isolation, and anxiety on self-disclosure willingness

Research background: Consumers frequently exchange personal data for limited benefits from digital services, despite privacy concerns. This data enables digital providers to tailor content and enhance marketing communication, and digital services' effectiveness and efficiency. Purpose of the article: Utilizing the principles of privacy calculus theory, this study aims to identify how attitudes towards advertising (ATT), perception of advertising credibility (CRE), consumer susceptibility to interpersonal (II) and reference group influence (RGI), social isolation (SI) and social anxiety (SA) influence the willingness of Generation Z to disclose personal information on social media derived from the Generation Z privacy concerns (PC) and develop a prediction model for such behavior. Methods: Data was gathered using an online self-administered questionnaire from a sample of 451 Generation Z individuals. A non-random convenient sampling technique and binary logistic regression were used to quantify the influence of selected independent variables on the dispersion of values in the dependent variable under investigation. Findings &amp; value added: The results highlight that Generation Z's self-disclosure willingness on social media is significantly influenced by attitudes toward advertising and consumer susceptibility to reference group influence. The effect of social isolation was also close to the required level of statistical significance. It means that positive attitudes towards advertising and high susceptibility to influence from reference groups enhance the probability of personal information disclosure. Being one of the few studies to address factors that influence the willingness of Generation Z to disclose personal information on social media, this study stands out for its holistic approach. Thus, combining various interconnected elements provides a fresh perspective to comprehend the intricate dynamics of Generation Z's relationship with privacy on social media.

Drivers and consequences of borrowers' voluntary privacy information disclosure—Evidence from a Chinese online consumer financing platform

AbstractThis study explores the drivers and consequences of consumers' voluntary information disclosure in the context of online consumer financing. Using unique secondary data from a Chinese online consumer financing company, we uncover a non‐linear relationship between borrowers' credit ratings and the quantity of voluntary information disclosure, and an inverted U‐shaped relationship between the amount of information disclosure and loan default. Specifically, low‐credit borrowers who opt for more voluntary information disclosure manifest a higher likelihood of default than those who disclose less, suggesting a strategic inclination toward information disclosure. Finally, we identify that disclosing high‐cost information reduces loan default, whereas disclosing low‐cost information increases default. Our findings enrich the existing literature on consumer information disclosure by providing insights into the underlying motivation and highlighting the applicability of signaling theory and privacy calculus theory. This has practical implications for lenders, borrowers, and regulators in overcoming barriers in online lending.

The moderating role of e-lifestyle on disclosure intention in mobile banking: A privacy calculus perspective

Advancements in information and communication technologies (ICT) have transformed the financial industry into “Fintech” and mobile banking. The COVID-19 pandemic has accelerated the adoption of mobile commerce services, with privacy and security concerns arising among consumers. This study adapted the privacy calculus theory to investigate the factors influencing consumers' willingness to provide personal information in mobile banking. It also examines the moderating role of e-lifestyle in the relationship between perceived benefits and risks and the intention to use mobile banking. The results show that perceived benefits outweigh perceived risks, motivating users to provide personal data and use mobile banking. E-lifestyle clusters also moderate consumer attitudes towards mobile banking adoption, with different effects for Mobile Service Enthusiasts and Neutrals. Financial institutions can enhance user trust and adoption by understanding these factors and tailoring mobile banking experiences to users' preferences and lifestyles.

Enhancing recommendation acceptance: Resolving the personalization–privacy paradox in recommender systems: A privacy calculus perspective

The concept of recommendation acceptance intention (RAI) refers to the willingness of an individual to adopt and use recommender systems. However, contemporary recommender systems, relying solely on accuracy as an evaluation metric have demonstrated subpar performance. The evolving landscape requires the integration of multiple objectives, including relevance, diversity, novelty, and coverage. This study investigates the influence of distinct product organization formats (similar vs. related products) on consumer reactions, aiming to reduce privacy concerns while achieving objectives such as relevance and variety. Grounded in the privacy calculus theory and personalization–privacy paradox framework, this study asserts that organization formats prompt consumers to evaluate a recommender system, considering both privacy risks and personalization benefits. Findings from three experiments and one qualitative study indicate that a related product organization format effectively decreases consumer perceptions of privacy violation while enhancing their perceptions of variety compared to a similar product organization format. This result contributes to RAI and shapes consumer preferences for recommender systems. Moreover, this research distinguishes the mechanisms underlying the influence of organization formats on RAI in the context of different product types, such as durable goods and consumables. This distinction enhances implications for designing recommender systems in e-commerce.

The host experience in the meal-sharing economy: the other side of the medallion

ABSTRACT This current study attempts to ascertain hosts’ meal-sharing experiences to suggest a broader comprehension of the meal-sharing experience in the informal economy. Drawing on a qualitative research method, 12 interviews with meal-sharing hosts were conducted in Istanbul, Türkiye. The data was analysed using the theme analysis method, foregrounded five main themes, i.e. fellowship, cross-cultural learning, money-making, patriotism, and gastronomic identity. This study is the first attempt to focus on the hosts’ perception of the meal-sharing experience, thereby providing a missing piece to wholly complete the theoretical understanding of the meal-sharing experience through the lens of the actor – network theory (ANT) and the privacy – calculus theory (PCT). It also offers several practical implications for sharing economy platform operators to boost their hosts’ experiences in their sharing activities.

Thin privacy boundaries: proximity and accessibility of E-commerce privacy policy in young consumers of Indonesia

PurposePrivacy is a sensitive issue in business because it involves how a platform uses consumer personal data. In terms of consumer rights, personal information needs to be protected in the privacy policy (PP). This study describes several aspects of the PP that consumers need to pay attention to, especially points prone to misuse of personal information.Design/methodology/approachThis research used a taxonomy of consumer privacy concerns in e-commerce to reveal general and specific privacy concerns. The privacy calculus theory was also applied to explore consumer rationalization using (1) consumer knowledge about PP, (2) subjective perception, and (3) proximity to the PP features. Furthermore, the netnographic approach was used to combine the interrelation between technology and social construction. A sample of 378 young consumers in several major cities in Indonesia participated online and offline. Semi-structured interviews were also conducted to gain more in-depth comprehension.FindingsThe results showed that most young consumers have sufficient basic knowledge of the important points of PP. Furthermore, they tend not to read the PP because it is long and cumbersome, and therefore do not wish to expend much cognitive effort on it.Originality/valueThis study provides several results that can be utilized by policymakers or e-commerce companies to pay more attention to PPs for young groups. In addition, e-commerce companies can increase the knowledge of the privacy situation of Internet users in general.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0740

How Peer Privacy Concerns Affect Active and Passive Uses of Social Networking Sites: A Dual Peer Privacy Calculus Model

Social networking sites (SNSs) have emerged as parallel societies, providing individuals with a platform to interact with peers and construct their desired self-identities. However, maintaining a positive image and safeguarding oneself from social judgment often necessitate self-censorship in self-identity expression. Drawing upon the privacy calculus theory, this study investigates how SNS users engage in a rational cost–benefit analysis between peer privacy concerns and self-presentation when deciding whether to actively or passively use SNSs. Findings from a variance-based analysis—partial least squares structural equation modeling (PLS-SEM)—to a sample of 394 Facebook users revealed that active use was primarily driven by perceived benefits, while passive use was triggered by perceived privacy costs. However, employing a case-based analysis—fuzzy-set qualitative comparative analysis (fsQCA), the present study uncovered that while some SNS users do not conform to the privacy calculus, many others do, thereby confirming the proposed dual privacy calculus model for SNS use. These findings resolve the contradictory findings from previous research on the privacy calculus model. This study extends the literature on the privacy calculus theory by developing a dual peer privacy calculus model to understand SNS users’ passive and active uses and validate the significance of peer privacy concerns on these behavioral patterns. This study underscores critical factors influencing SNS usage patterns, empowering platform developers to provide users with effective tools to combat privacy violations by peers, thereby promoting increased active engagement.

Soft Biometrics in Retail Service: Understanding Privacy Paradox and Cross-Cultural Differences Regarding 3D Body Scanning Technology

This study aims to explore the privacy paradox and cultural difference associated with integrating soft biometric information through 3D body scanning technologies into personalized shopping services. By incorporating the theory of Concerns for Information Privacy and the Unified Theory of Acceptance and Use of Technology into the Privacy Calculus Theory, the purpose of this study is to understand fashion consumers’ privacy paradox and investigate cultural differences (U.S. vs. China). A partial least squares structural equation modeling and multigroup analysis was conducted from two data sets collected online (N U.S.= 525, N China = 484). Results show that consumer concerns toward data management (i.e., collection, error, secondary use) and service excellence expectations (i.e., perceived expectance, facilitation condition, hedonic motivation) explain the privacy calculus (i.e., risk and benefit) in consumer decisions. The results indicate that error management is critical to understanding Chinese consumers’ privacy calculus, while secondary use is important for U.S. consumers.