Privacy Maintenance in Self-Digitization

2021 ◽  
Vol 52 (2) ◽  
pp. 7-24
Author(s):  
France Bélanger ◽  
Robert E. Crossler ◽  
John Correia
Keyword(s):  
Personal Information ◽  
Empirical Support ◽  
Privacy Concern ◽  
Perceived Benefit ◽  
Willingness To Disclose ◽  
Other Information ◽  
Continued Use ◽  
Iot Devices ◽  
Fitness Tracker ◽  
Intention To Continue

Individuals are increasingly using personal Internet of Things (IoT) devices that digitize their day-to-day lives. Those devices, however, often require substantial personal information to generate their intended benefits. For example, fitness technologies collect health, sleep, personal, and a vast array of other information ubiquitously, creating possible privacy issues for the users when fitness technology platform providers store or share their information, whether users know this or not. To explore the role of privacy perceptions in the context of continued use of fitness technologies, this study collected data from 212 fitness tracker users. We find empirical support for the importance of privacy perceptions in a user's intention to continue to use their fitness tracker. More specifically, consistent with privacy calculus research, privacy concern is negatively related to willingness to disclose information while perceived benefit is positively related to it. As an extension to calculus variables, users' expectations towards the data sharing practices of organizations also influences their willingness to disclose information. Importantly, willingness to disclose information has a direct effect on continued use intentions but also moderates the relationship between perceived benefit and users' intentions to continue using a fitness tracker. We discuss the implications of these findings for research and practice.

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.

Exploring the Influences of Service Characteristics on Individuals’Use Intention of Mobile Health Services (Preprint)

2020 ◽  
Author(s):  
Fei Liu ◽  
Pengkun Wu ◽  
Xitong Guo
Keyword(s):  
Personal Information ◽  
New Technology ◽  
Information Service ◽  
Health Care Research ◽  
Privacy Concern ◽  
Service Adoption ◽  
Service Characteristics ◽  
Research Areas ◽  
New Information ◽  
The Relationship

BACKGROUND Service characteristic factors are verified as the determinants for influencing people’s use intention of mHealth. Exploration of the interactions among the service characteristics of users can play an important role in improving service adoption rate. mHealth service appears to be an emerging new technology that presents a new pattern of healthcare service; however, users have concerns that their personal information might be disclosed and used without permission. This concern hinders people’s adoption behavior of mHealth services. OBJECTIVE The objective of this study is to explore how service characteristics (service relevance and service accuracy) interact to influence individuals’ use intention of mHealth services. This study also investigates the moderating roles of innovativeness and privacy concern. METHODS To meet these objectives, six hypotheses thus developed were empirically validated using a survey to test the effects of service characteristics and personal traits on use intention of mHealth. RESULTS We confirm that service relevance and service accuracy positively and directly influence individuals’ use intention of mHealth services. In addition, innovativeness positively affects the relationship between service relevance and use intention. Privacy concern negatively influences the relationship between service relevance and use intention, but positively influences the relationship between service accuracy and use intention. CONCLUSIONS The present study provides new insights into the influencing factors of individuals’ usage behaviour toward mHealth services. Such insight could provide further understanding of how individuals adopt new information service or technologies, which contribute to both information system and health care research areas in a very promising way.

scholarly journals An Empirical Justification for the Use of Racially Distinctive Names to Signal Race in Experiments

2017 ◽  
Vol 25 (1) ◽  
pp. 122-130 ◽  
Author(s):  
Daniel M. Butler ◽  
Jonathan Homola
Keyword(s):  
Socioeconomic Status ◽  
Racial Discrimination ◽  
Empirical Support ◽  
Public Records ◽  
Empirical Justification ◽  
Political Resources ◽  
Other Information

Researchers studying discrimination and bias frequently conduct experiments that use racially distinctive names to signal race. The ability of these experiments to speak to racial discrimination depends on the excludability assumption that subjects’ responses to these names are driven by their reaction to the individual’s putative race and not some other factor. We use results from an audit study with a large number of aliases and data from detailed public records to empirically test the excludability assumption undergirding the use of racially distinctive names. The detailed public records allow us to measure the signals about socioeconomic status and political resources that each name used in the study possibly could send. We then reanalyze the audit study to see whether these signals predict legislators’ likelihood of responding. We find no evidence that politicians respond to this other information, thus providing empirical support for the excludability assumption.

scholarly journals Ethnic Discrimination in the Dutch Labor Market: Differences Between Ethnic Minority Groups and the Role of Personal Information About Job Applicants—Evidence from a Field Experiment

2020 ◽  
Author(s):  
Lex Thijssen ◽  
Marcel Coenders ◽  
Bram Lancee
Keyword(s):  
Labor Market ◽  
Field Experiment ◽  
Ethnic Minority ◽  
Large Scale ◽  
Minority Groups ◽  
Personal Information ◽  
Empirical Support ◽  
Ethnic Discrimination ◽  
Ethnic Minority Groups ◽  
Large Scale Field

AbstractIn this study, we present the results of a large-scale field experiment on ethnic discrimination in the Dutch labor market. We sent fictitious job applications (N = 4211) to vacancies for jobs in ten different occupations in the Netherlands. By examining 35 different ethnic minority groups, we detect considerable differences in discrimination rates, predominantly between Western and non-Western minorities. Furthermore, we find little systematic variation in discrimination patterns with regard to gender, regions, and occupations, pointing to the existence of an ethnic hierarchy that is widely shared among employers. Finally, we do not find empirical support for the hypothesis that adding personal information in job applications reduces discrimination.

Analysis of Vulnerabilities in IoT and Its Solutions

2021 ◽  
pp. 157-177
Author(s):  
Puspanjali Mallik
Keyword(s):  
Security And Privacy ◽  
Heterogeneous Structure ◽  
Privacy Concern ◽  
Security Vulnerabilities ◽  
Smart Vehicles ◽  
Security Issues ◽  
Smart Healthcare ◽  
Wide Range ◽  
Main Motive ◽  
Iot Devices

The internet of things (IoT) fulfils abundant demands of present society by facilitating the services of cutting-edge technology in terms of smart home, smart healthcare, smart city, smart vehicles, and many more, which enables present day objects in our environment to have network communication and the capability to exchange data. These wide range of applications are collected, computed, and provided by thousands of IoT elements placed in open spaces. The highly interconnected heterogeneous structure faces new types of challenges from a security and privacy concern. Previously, security platforms were not so capable of handling these complex platforms due to different communication stacks and protocols. It seems to be of the utmost importance to keep concern about security issues relating to several attacks and vulnerabilities. The main motive of this chapter is to analyze the broad overview of security vulnerabilities and its counteractions. Generally, it discusses the major security techniques and protocols adopted by the IoT and analyzes the attacks against IoT devices.

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.

scholarly journals Methods of personal information environment evaluation

2019 ◽  
Vol 292 ◽  
pp. 01036
Author(s):  
Pavel Valášek
Keyword(s):  
Information And Communication Technology ◽  
Communication Technology ◽  
Technology Use ◽  
General Public ◽  
Personal Information ◽  
Information Environment ◽  
Assessment And Evaluation ◽  
Environment Assessment ◽  
Other Information ◽  
Information And Communication

Current condition of information and communication technology use by general public is suitable for a research of other information phenomena such as personal information environment. As a continuation of the broader study concerning this topic, in this article are discussed various methods of personal information environment assessment and evaluation. Data were collected by the means of survey and supervised tasks. Established differences between selected methods are presented. This study may be seen as suitable preparative study of this field.

An Empirical Investigation of the Antecedents and Consequences of Privacy Uncertainty in the Context of Mobile Apps

2020 ◽  
Vol 31 (4) ◽  
pp. 1037-1063
Author(s):  
Sameh Al-Natour ◽  
Hasan Cavusoglu ◽  
Izak Benbasat ◽  
Usman Aleem
Keyword(s):  
Perceived Risk ◽  
Empirical Investigation ◽  
Mobile Apps ◽  
Information Privacy ◽  
Personal Finance ◽  
Mobile App ◽  
Potential Consumer ◽  
Continued Use ◽  
Antecedents And Consequences ◽  
Intention To Continue

When using mobile apps that extensively collect user information, privacy uncertainty, which is consumers’ difficulty in assessing the privacy of the data they entrust to others, is a major concern. Using a simulated app-buying experiment, we find that privacy uncertainty, which is mainly driven by uncertainty about what data are collected and how they are used and protected, is indeed a significant influencer of one’s intentions to use a mobile app and the perceived risk associated with that use, as well as the price a potential consumer is willing to pay for an app. Our results further show that the uncertainty concerning the data collected while using a mobile app drives consumers’ decisions more than the uncertainty regarding data that are collected at the time an app is downloaded. To investigate whether privacy uncertainty continues to be a factor after a consumer has already started using an app, we conducted a survey of users of wellness and personal finance apps. The results indicate that privacy uncertainty is a lingering concern because it continues to influence a user’s intention to continue using an app and the perceived risk associated with that continued use.

scholarly journals Self-Controllable Mobile App Protection Scheme Based on Binary Code Splitting

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Sungtae Kim ◽  
Taeyong Park ◽  
Geochang Jeon ◽  
Jeong Hyun Yi
Keyword(s):  
Personal Information ◽  
Mobile Apps ◽  
Mobile App ◽  
Self Control ◽  
Protection Scheme ◽  
Tablet Pcs ◽  
Android Apps ◽  
Dynamic Analyses ◽  
Iot Devices ◽  
Parameter Dependency

Mobile apps are booming with the expansion of mobile devices such as smartphones, tablet PCs, smartwatches, and IoT devices. As the capabilities of mobile apps and the types of personal information required to run apps have diversified, the need for increased security has grown. In particular, Android apps are vulnerable to repackaging attacks, so various code protection techniques such as obfuscation and packing have been applied. However, apps protected with these techniques can also be disabled with static and dynamic analyses. In recent years, instead of using such application level protection techniques, a number of approaches have been adopted to monitor the behavior of apps at the platform level. However, in these cases, not only incompatibility of system software due to platform modification, but also self-control functionality cannot be provided at the user level and is very inconvenient. Therefore, in this paper we propose an app protection scheme that can split a part of the app code, store it in a separate IoT device, and self-control the split code through the partial app. In the proposed scheme, the partial app is executed only when it matches the split code stored in the IoT device. It does not require complicated encryption techniques to protect the code like the existing schemes. It also provides solutions to the parameter dependency and register reallocation issues that must be considered when implementing the proposed code splitting scheme. Finally, we present and analyze the results of experimenting the proposed scheme on real devices.

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