The willingness to disclose personal information

2019 ◽  
Vol 28 (2) ◽  
pp. 161-181 ◽  
Author(s):  
Ibrahim M. Al-Jabri ◽  
Mustafa I. Eid ◽  
Amer Abed
Keyword(s):  
Saudi Arabia ◽  
Information Disclosure ◽  
Personal Information ◽  
Negative Relationship ◽  
Extensive Literature ◽  
Privacy Concern ◽  
Content Type ◽  
Privacy Concerns ◽  
Positive Effects ◽  
Willingness To Disclose

Purpose Customer privacy and security are major concerns. Online firms worldwide collect customer data for various reasons. This study aims to investigate factors that motivate and hinder a customer’s willingness to disclose personal information (WTD) to online firms on e-commerce websites. Design/methodology/approach Based on an extensive literature review, three sets of factors have been identified. These sets of factors are privacy concern, perceived disclosure benefits and privacy assurances. It is hypothesized that privacy concerns negatively affect the disclosure of personal information, while the perceived benefits of disclosure have positive effects. Privacy assurances would positively affect information disclosure and attenuate the negative effect of privacy concerns on the disclosure of personal information. The authors gathered data from 253 online customers in Saudi Arabia. Findings The results indicate that perceived disclosure benefits and privacy concerns have a significant positive and negative relationship, respectively, with WTD online. Privacy assurances had neither a direct nor a moderating effect on information disclosure. Research limitations/implications The findings will inform online firms about the factors that prevent or motivate customers to disclose personal information. Originality/value The effect of privacy concerns and benefits on personal information disclosure are not fully understood in Saudi Arabia. This study reveals more insights into the specific factors that make online customers reluctant or motivated to disclose their personal information.

Why people need privacy? The role of privacy fatigue in app users' intention to disclose privacy: based on personality traits

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jie Tang ◽  
Umair Akram ◽  
Wenjing Shi
Keyword(s):  
Personality Traits ◽  
Information Disclosure ◽  
Personal Information ◽  
Mobile Apps ◽  
Equation Modeling ◽  
Content Type ◽  
Privacy Concerns ◽  
Positive Effects ◽  
Novel Concept ◽  
The Impact

PurposeMobile Applications (App) privacy has become a prominent social problem. Compared with privacy concerns, this study examines a relatively novel concept of privacy fatigue and explores its effect on the users’ intention to disclose their personal information via mobile Apps. In addition, the personality traits are proposed as antecedents that will induce the personal perception of privacy fatigue and privacy concerns differently.Design/methodology/approachData were collected from 426 respondents. Structure equation modeling was used to test the hypotheses.FindingsThe findings describe that App users’ intention toward personal information disclosure is determined by privacy fatigue and privacy concerns, but the former has a greater impact. With minor exceptions, the two factors are also influenced by different personality traits. Specifically, neuroticism has positive effects on privacy fatigue, but agreeableness and extraversion have presented the opposite results on the two variables.Practical implicationsThis research is very scarce to examine the joint effects of privacy fatigue, privacy concerns and personality traits on App users’ disclosing intention. In doing so, these results will be of benefit to App providers and platform managers and can be the basis for a variety of follow-up studies.Originality/valueWhile previous research just focuses on privacy concerns, this study explores the critical roles of privacy fatigue and opens up a new avenue of emotion-attitude analysis that can further increase the specificity and richness of users’ privacy research. Additionally, implications for personality traits as antecedents in the impact of App users’ privacy emotions and attitudes are discussed.

Understanding the influence of privacy protection functions on continuance usage of push notification service

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhou Cheng ◽  
Kai Li ◽  
Ching-I Teng
Keyword(s):  
Self Efficacy ◽  
Privacy Protection ◽  
Privacy Concern ◽  
Perceived Fairness ◽  
Negative Effects ◽  
Content Type ◽  
Privacy Concerns ◽  
Positive Effects ◽  
Continuance Usage ◽  
Important Approach

PurposePush notification service (PNS) is an important approach to distribute personalized information to users timely and is getting more and more popular. However, users' privacy concerns are a major inhibiting factor in their continuance usage of PNS. This study investigates the effect of privacy protection functions provided by PNS sites in enhancing users' perceived fairness on the basis of justice theory to mitigate users' concerns of information privacy. The mechanism underlying such influence on users' continuance usage of PNS comprises privacy concern and privacy-control self-efficacy.Design/methodology/approachFour scenario-based surveys are conducted to test the proposed hypotheses. The authors test the research model with a sample of 360 participants by ANOVA and PLS.FindingsResults show that the proposed privacy protection functions have direct positive effects on users' privacy-control self-efficacy, negative effects on privacy concern and indirectly affect their continuance usage of PNS. Furthermore, the interaction effects between two approaches have different impacts on users' privacy concern and privacy-control self-efficacy.Originality/valueThis study provides some suggestions and guidance for PNS providers to design effective privacy protection technologies.

Information disclosure willingness and mobile cloud computing collaboration apps: the impact of security and assurance mechanisms

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hamid Reza Nikkhah ◽  
Rajiv Sabherwal
Keyword(s):  
Cloud Computing ◽  
Information Disclosure ◽  
Mobile Cloud Computing ◽  
Personal Information ◽  
Security And Privacy ◽  
Mobile Cloud ◽  
Content Type ◽  
Privacy Concerns ◽  
Security Assurance ◽  
The Impact

PurposeIn this research, the authors focus on mobile cloud computing (MCC) collaboration apps that are multiplatform and send the users’ data to the cloud. Despite their benefits, MCC collaboration apps raise privacy concerns, as the users’ information is sent to the cloud where users lack direct control. This study aims to investigate why users disclose information to MCC apps despite privacy concerns and examine the effect of security and assurance mechanisms (i.e. privacy policies and ISO/IEC 27018 certification) on users’ perceptions and information disclosure. Based on three surveys conducted in 2016 (n = 515), 2017 (n = 505) and 2018 (n = 543), this study finds mixed results regarding the relationships among security, assurance mechanisms, utilitarian benefits and information disclosure.Design/methodology/approachThis study conducted three scenario-based surveys in the USA in 2016 (n = 515), 2017 (n = 505) and 2018 (n = 543).FindingsThis study finds mixed results of relationships among security, assurance mechanisms, utilitarian benefit and information disclosure.Originality/valueWith proliferation of MCC apps, the investigation of how users make privacy decision to disclose personal information to these apps is sparse. This study, for the first time, investigates whether the signals of assurance mechanism decrease users’ privacy concerns. This study also examines the interplay between security and privacy within information disclosure behavior. Finally, this study was conducted in 3 years to enhance the generalizability and robustness of findings.

Privacy Concern of Health Information Disclosure in mHealth: The Moderate Effect of Social Support (Preprint)

2020 ◽  
Author(s):  
Yuanyuan Dang ◽  
Shanshan Guo ◽  
Xitong Guo
Keyword(s):  
Social Support ◽  
Health Information ◽  
Emotional Support ◽  
Information Disclosure ◽  
Perceived Health ◽  
Privacy Concern ◽  
Informational Support ◽  
Privacy Concerns ◽  
Information Sensitivity ◽  
Moderate Effect

BACKGROUND The mobile health (mHealth) provides a new opportunity for patients’ disease prediction and health self-management. At the same time, privacy problems in mHealth have brought forth significant attention concerning patients' online health information disclosure and hindered mHealth development. OBJECTIVE Privacy calculus theory (PCT) has been widely used to understand personal information disclosure behaviors with the basic assumption of a national and linear decision-making process. However, people’s cognitive behavior processes are complex and mutual. In attempting to close this knowledge gap, we further optimize the information disclosure model of patients based on PCT by identifying the mutual relationship between costs (privacy concerns) and benefits. Social support, which has been proved to be a distinct and significant disclosure benefit of mHealth, was chosen to be the representative benefit of information disclosure in mHealth. METHODS From an individual perspective, a structural equation model with privacy concerns, health information disclosure intention in mHealth, and social support from mHealth has been examined. RESULTS 253 randomly selected participants provided validated questionnaire. The result indicated that perceived health information sensitivity positively enhances the privacy concern (0.505, p<0.01), and higher privacy concern levels will decrease the health information disclosure intention (-0.338, p<0.01). Various aspects of individual characters influence perceived health information sensitivity in different ways. The informational support has a negatively moderate on reduce the positive effect between perceived health information sensitivity and privacy concerns (-0.171, p<0.1) and will decrease the negative effect between privacy concerns and health information disclosure intention(-0.105, p<0.1). However, emotional support has no directly moderate effect on both privacy concerns and health information disclosure intention. CONCLUSIONS The results indicate that social support can be regarded as a disutility reducer, that is, on the one hand, it reduces the privacy concerns of patients; on the other hand, it also reduces the negative impact of privacy concerns on information disclosure intention. Moreover, the moderate effect of social support is partially supported. Informational support, one demission of social support, is significant, while the other demission, emotional support, is not significant in mHealth. Furthermore, the results are different among patients with different individual characteristics. This study also provides specific theoretical and practical implications to enhance the development of mHealth.

Understanding the disclosure of personal data online

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Heather J. Parker ◽  
Stephen Flowerday
Keyword(s):  
Social Media ◽  
Information Disclosure ◽  
Cost Benefit Analysis ◽  
Personal Information ◽  
Personal Data ◽  
Cost Benefit ◽  
Content Type ◽  
Privacy Violation ◽  
The Cost ◽  
Insight Into

Purpose Social media has created a new level of interconnected communication. However, the use of online platforms brings about various ways in which a user’s personal data can be put at risk. This study aims to investigate what drives the disclosure of personal information online and whether an increase in awareness of the value of personal information motivates users to safeguard their information. Design/methodology/approach Fourteen university students participated in a mixed-methods experiment, where responses to Likert-type scale items were combined with responses to interview questions to provide insight into the cost–benefit analysis users conduct when disclosing information online. Findings Overall, the findings indicate that users are able to disregard their concerns due to a resigned and apathetic attitude towards privacy. Furthermore, subjective norms enhanced by fear of missing out (FOMO) further allows users to overlook potential risks to their information in order to avoid social isolation and sanction. Alternatively, an increased awareness of the personal value of information and having experienced a previous privacy violation encourage the protection of information and limited disclosure. Originality/value This study provides insight into privacy and information disclosure on social media in South Africa. To the knowledge of the researchers, this is the first study to include a combination of the theory of planned behaviour and the privacy calculus model, together with the antecedent factors of personal valuation of information, trust in the social media provider, FOMO.

AI and privacy concerns: a smart meter case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jillian Carmody ◽  
Samir Shringarpure ◽  
Gerhard Van de Venter
Keyword(s):  
Private Information ◽  
Personal Information ◽  
Consumer Information ◽  
Data Sets ◽  
Smart Meter ◽  
Smart Meters ◽  
Content Type ◽  
Privacy Concerns ◽  
Privacy Legislation

Purpose The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence (AI) technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach The authors illustrate how, through smart meter obtained energy data, home energy providers can use AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers.

scholarly journals Leadership-promoted diversity climate and group identification

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jana Žnidaršič ◽  
Sabina Bogilović ◽  
Matej Černe ◽  
Roopak Kumar Gupta
Keyword(s):  
Crucial Role ◽  
Group Identification ◽  
Negative Relationship ◽  
Diversity Climate ◽  
Negative Consequences ◽  
Content Type ◽  
Positive Effects ◽  
Categorization Theory ◽  
Transnational Companies ◽  
Work Units

PurposeBesides diversity's positive effects, groups of “we” against “them” may form in accordance with social categorization theory, showing diversity's negative consequences. The authors aim to reconcile these results and examine their boundary conditions.Design/methodology/approachThe authors studied 584 working professionals from five contexts (transnational companies dealing with multicultural interactions) and analyzed data using moderated-mediation procedures.FindingsA leader-promoting diversity climate plays a crucial role in moderating the negative relationship between perceived dissimilarity and group identification, which is mediated by value dissimilarity.Originality/valueThis study mainly contributes by treating dissimilarity as a multicomponent construct, emphasizing the crucial differences embodied in various conceptualizations of dissimilarity – namely visible and value dissimilarity. For dissimilarity to result in group identification, the results highlight leaders' crucial role, beyond that of organizations and individuals, in stimulating a diversity-embracing climate in work units.

Will it be Disclosure or Fabrication of Personal Information?

2010 ◽  
pp. 231-254 ◽  
Author(s):  
Xun Li ◽  
Radhika Santhanam
Keyword(s):  
Personal Information ◽  
Personal Data ◽  
Job Applicants ◽  
Accurate Information ◽  
Hiring Decisions ◽  
Job Applicant ◽  
Privacy Concerns ◽  
Willingness To Disclose ◽  
Information Sensitivity ◽  
Theoretical Foundations

Individuals are increasingly reluctant to disclose personal data and sometimes even intentionally fabricate information to avoid the risk of having it compromised. In this context, organizations face an acute dilemma: they must obtain accurate job applicant information in order to make good hiring decisions, but potential employees may be reluctant to provide accurate information because they fear it could be used for other purposes. Building on theoretical foundations from social cognition and persuasion theory, we propose that, depending on levels of privacy concerns, organizations could use appropriate strategies to persuade job applicants to provide accurate information. We conducted a laboratory experiment to examine the effects of two different persuasion strategies on prospective employees’ willingness to disclose information, measured as their intentions to disclose or falsify information. Our results show support for our suggestion As part of this study, we propose the term information sensitivity to identify the types of personal information that potential employees are most reluctant to disclose.

The dilemma of social commerce

2020 ◽  
Vol 30 (3) ◽  
pp. 1059-1080 ◽  
Author(s):  
Xiaodong Li ◽  
Chuang Wang ◽  
Yanping Zhang
Keyword(s):  
Avoidance Behavior ◽  
Information Overload ◽  
Negative Relationship ◽  
Underlying Mechanism ◽  
Tie Strength ◽  
Related Factor ◽  
Social Commerce ◽  
Content Type ◽  
Positive Effects ◽  
Shared Language

PurposeDue to customers' extensive avoidance behavior, social commerce may be less successful than anticipated. This study investigates the underlying mechanism and antecedents that influence customers' avoidance of peer-generated advertisements.Design/methodology/approachBased on the general framework of avoidance behavior, we propose a theoretical model for the context of a mobile social network, with tie strength as the user-related factor and violation of shared language, advertisement relevance and information overload as contextual variables. Using survey data collected from 334 customers on WeChat, we empirically examine the research model and hypotheses.FindingsTie strength and advertisement relevance are negatively associated with avoidance behavior, whereas information overload and violation of shared language have significantly positive effects. Furthermore, tie strength weakens the negative relationship between violation of shared language and avoidance behavior but strengthens the positive relationship between advertisement relevance and avoidance behavior.Originality/valueThe findings extend understanding of advertisement avoidance behavior and can guide practitioners' improvement of advertising efficiency in mobile social networks.

Understanding determinants of social networking service fatigue: an interpretive structural modeling approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lin Xiao ◽  
Ting Pan ◽  
Jian Mou ◽  
Lihua Huang
Keyword(s):  
Social Networking ◽  
Impression Management ◽  
Structural Model ◽  
Structural Modeling ◽  
Extensive Literature ◽  
Privacy Concern ◽  
Social Networking Service ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Factors Influencing

PurposeThe purpose of this paper is to build a comprehensive structural model to demonstrate the interrelationships of factors influencing social networking service (SNS) fatigue and to identify the varying degrees of influence.Design/methodology/approachA total of 14 factors influencing SNS fatigue are identified through an extensive literature review. Interpretive structural modeling (ISM) and Matrice d'Impacts Croisés Multiplication Appliqué à un Classement (MICMAC) analysis are employed to build a hierarchical model and classify these factors into four clusters.FindingsThe results revealed that ubiquitous connectivity and immediacy of feedback are key factors contributing to SNS fatigue through their strong influence on other factors. Privacy concern, impression management concern and work–life conflict lead directly to SNS fatigue. In contrast, system feature overload and system pace of change are relatively insignificant in generating SNS fatigue.Originality/valueThis study represents an initial step toward comprehensively understanding the interrelationships among the factors leading to SNS fatigue and reveals how determinants of SNS fatigue are hierarchically organized, thus extending existing research on SNS fatigue. It also provides logical consistency in the ISM-based model for SNS fatigue by grouping identified factors into dependent and independent categories. Moreover, it extends the applicability of the integration of the ISM and MICMAC approaches to the phenomenon of SNS fatigue.

Sign in / Sign up

Export Citation Format

Share Document