“Now that you mention it”: A survey experiment on information, inattention and online privacy

Marreiros, Hélia; Tonin, Mirco; Vlassopoulos, Michael; schraefel, m.c.

doi:10.1016/j.jebo.2017.03.024

Cited by 105 publications

(63 citation statements)

References 44 publications

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“…In the dissemination phase, only a small number of tool users filled out their personal and family information and reviewed the final health insurance plan recommendations. This may indicate that people are reluctant to disclose personal health information online [30]. Prior studies have found that people's perceived health information sensitivity influences their intention to disclose health information [31], and online users chose to share private information when the perceived benefits outweighed perceived risks [32,33].…”

Section: Discussionmentioning

confidence: 99%

Dissemination of a Web-Based Tool for Supporting Health Insurance Plan Decisions (Show Me Health Plans): Cross-Sectional Observational Study (Preprint)

Zhao¹,

Mir²,

Ackermann³

et al. 2018

Preprint

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Background: The rate of uninsured has decreased dramatically since the passage of the Affordable Care Act. To make an informed decision, consumers need assistance to understand the advantages and disadvantages of health insurance plans and select a suitable plan. The Show Me Health Plans (SMHP) web-based decision support tool was developed to improve health insurance decision quality. In response to the promising effectiveness of SMHP in a randomized controlled trial (RCT) and the growing need for web-based health insurance decision support, the study team used expert recommendations for dissemination and implementation processes, engaged external stakeholders, and released the SMHP tool so that it was available to the general public.

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Section: Discussionmentioning

confidence: 99%

Dissemination of a Web-Based Tool for Supporting Health Insurance Plan Decisions (Show Me Health Plans): Cross-Sectional Observational Study (Preprint)

Zhao¹,

Mir²,

Ackermann³

et al. 2018

Preprint

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show abstract

“…This could be the result of shying away from discussing any issues that might lower participation. Indeed, it has been demonstrated that making privacy issues salient immediately before disclosure, even if the matter is raised in a positive tone, can cause participants to become more cautious about disclosure [23]. This approach however, presents two problems.…”

Section: Related Work Citizen Science and Data Privacymentioning

confidence: 99%

Why Do You Need This?

Rudnicka

Cox

Gould

2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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Recent scandals involving data from participatory research have contributed to broader public concern about online privacy. Such concerns might make people more reluctant to participate in research that asks them to volunteer personal data, compromising many researchers' data collection. We tested several motivational messages that encouraged participation in a citizen science project. We measured people's willingness to disclose personal information. While participants were less likely to share sensitive data than neutral data, disclosure behaviour was not affected by attitudes to privacy. Importantly, we found that citizen scientists who were exposed to a motivational message that emphasised 'learning' were more likely to share sensitive information than those presented with other types of motivational cues. Our results suggest that priming individuals with motivational messages can increase their willingness to contribute personal data to a project, even if the request pertains to sensitive information.

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“…A recent experiment shows how the willingness to provide sensitive data is drastically reduced when the term privacy is made salient, even in a positive context. 34 This would seem to indicate that people are often inattentive and that hidden privacy concerns arise only when consumers are asked a specific question.…”

Section: Range Of Antitrust Actionmentioning

confidence: 99%

Big Data Competition and Market Power

Gambaro

2019

mclawreview

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Big data are considered at the same time a promising driver of economic development and a concern for possible manipulation and privacy intrusion. Data diffusion and their uncertain appropriability can make property rights regarding data less precise than those regarding traditional goods. The article reviews some economic features of data. In many digital markets data can be considered a relevant input for production but hardly an essential facility. Many data are collected in two-sided market platforms and on the one side, they are used to personalise services and to add quality, while on the other side of the platform they contribute to make advertising collection more efficient. So, the transfer of personal data can be considered an implicit price for many free information services. Consumers are usually unaware of subsequent pervasive use of their personal data, and therefore give them away easily. Big data can amplify competitive advantages and related dominant positions, leveraging on information asymmetries. A dominant position obtained through collection and processing of big amounts of personal data allow practices such as first-degree price discrimination, personalised advertising, and artificial degradation of services that can sometimes be considered competitive abuse, but it is difficult that data alone allow to maintain a true dominant position.

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“Now that you mention it”: A survey experiment on information, inattention and online privacy

Cited by 105 publications

References 44 publications

Dissemination of a Web-Based Tool for Supporting Health Insurance Plan Decisions (Show Me Health Plans): Cross-Sectional Observational Study (Preprint)

Dissemination of a Web-Based Tool for Supporting Health Insurance Plan Decisions (Show Me Health Plans): Cross-Sectional Observational Study (Preprint)

Why Do You Need This?

Big Data Competition and Market Power

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