Understanding the Valuation of Location Privacy:  a Crowdsourcing-Based Approach

Poikela, Maija; Toch, Eran

doi:10.24251/hicss.2017.241

Cited by 13 publications

(10 citation statements)

References 25 publications

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“…Smith, et al [23] give an interdisciplinary review of privacy-related research. Most of the prior literature focus on privacy concerns of information collected online [22,9,6] and location-based privacy [31,29,19]. In addition, Xu et al [29] extended the privacy calculus model by including personality characteristics (previous privacy experience, coupon proneness, and personal innovativeness) and different methods of personalization (covert and overt) for locationaware marketing.…”

Section: Conceptual Backgroundmentioning

confidence: 99%

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Privacy Concerns Regarding Wearable IoT Devices: How it is Influenced by GDPR?

Paul

Scheibe

Nilakanta

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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Internet of Things (IoT) devices have implications for health and fitness. Fitness wearables can promote healthy behavior and improve an individual's overall health and quality of life. Even though fitness wearables have various benefits, privacy concerns regarding the data collected remain as a major barrier to adoption of fitness wearables. Intrinsic factors like disposition to value privacy and extrinsic factors like privacy policies and General Data Protection Regulation (GDPR) can influence users' privacy concerns. This research uses experimental design to understand how these factors influence privacy concerns.The results suggest that GDPR reduces the average privacy concerns of users. The study also shows that higher perception of effectiveness of privacy policy reduces the perception of privacy risks and increases the perception of privacy control. This study illustrates the effect of users' perceptions on factors like privacy policy, privacy control and GDPR on mitigating privacy concerns.

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Section: Conceptual Backgroundmentioning

confidence: 99%

“…Many studies have shown that privacy concerns affect behavioral intentions like intent to adopt and intent to use [31,22,14,26,19]. According to the APCO model, privacy concerns negatively influence behavioral intentions.…”

Section: Behavioral Intentionsmentioning

confidence: 99%

Privacy Concerns Regarding Wearable IoT Devices: How it is Influenced by GDPR?

Paul

Scheibe

Nilakanta

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Former studies of the privacy field have used crowdsourcing methodologies to investigate different privacy aspects, including users' valuations of location privacy [47], users' privacy expectations of mobile apps [36] and crowdsourced recommendation system development for privacy protection settings used in popular apps [2]. For our purposes we recruited adult participants via AMT.…”

Section: Recruitmentmentioning

confidence: 99%

“…Over-stepping users' expectations of privacy can be costly. Surprising users by sharing their data with unexpected people and organizations or using data in unexpected ways can deter users from using a system [21,36] or push them to choose other alternatives [19,47]. Privacy-by-design (PbD) initiatives propose a design and development framework that aids in the production of privacy-respectful systems [10,34].…”

Section: Introductionmentioning

confidence: 99%

Crowdsourcing Privacy Design Critique: An Empirical Evaluation of Framing Effects

Ayalon¹,

Toch²

2018

Proceedings of the Annual Hawaii International Conference on System Sciences

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When designed incorrectly, information systems can thwart people's expectations of privacy. An emerging technique for evaluating systems during the development stage is the crowdsourcing design critique, in which design evaluations are sourced using crowdsourcing platforms. However, we know that information framing has a serious effect on decisionmaking and can steer design critiques in one way or another. We investigate how the framing of design cases can influence the outcomes of privacy design critiques. Specifically, we test whether 'Personas', a central User-Centered Design tool for describing users, can inspire empathy in users while criticizing privacy designs. In an experiment on Amazon Mechanical Turk workers (n=456), we show that describing design cases by using personas causes intrusive designs to be criticized more harshly. We discuss how our results can be used to enhance privacy-by-design processes and encourage usercentered privacy engineering.

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“…Dobson and Fisher [48] see this as a kind of new panopticon ("panopticon III") in which, for the first time, benefits are available both for the watchers and those that are being watched. We allow the creation of the big spatial datasets that are the result of the big "data grab" [49] for a multitude of reasons, seemingly without much thought and hesitation and even when users are not visibly compensated for relinquishing their location privacy [50]. Behavior such as this is consistent with the way software functions are perceived-they hide from our conscious thoughts, retreating into the background hum of the ever-present technology and become visible only in its brief moments of failure [51,52].…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Care, Indifference and Anxiety—Attitudes toward Location Data in Everyday Life

Rzeszewski

Luczys

2018

IJGI

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Modern mobile devices are replete with advanced sensors that expand the array of possible methods of locating users. This can be used as a tool to gather and use spatial information, but it also brings with it the specter of “geosurveillance” in which the “location” becomes a product in itself. In the realm of software developers, space/place has been reduced and discretized to a set of coordinates, devoid of human experiences and meanings. To function in such digitally augmented realities, people need to adopt specific attitudes, often marked with anxiety. We explored attitudes toward location data collection practices using qualitative questionnaire surveys (n = 280) from Poznan and Edinburgh. The prevailing attitude that we identified is neutral with a strong undertone of resignation—surrendering personal location is viewed as a form of digital currency. A smaller number of people had stronger, emotional views, either very positive or very negative, based on uncritical technological enthusiasm or fear of privacy violation. Such a wide spectrum of attitudes is not only produced by interaction with technology but can also be a result of different values associated with space and place itself. Those attitudes can bring additional bias into spatial datasets that is not related to demographics.

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Understanding the Valuation of Location Privacy: a Crowdsourcing-Based Approach

Abstract: Abstract

Cited by 13 publications

References 25 publications

Privacy Concerns Regarding Wearable IoT Devices: How it is Influenced by GDPR?

Privacy Concerns Regarding Wearable IoT Devices: How it is Influenced by GDPR?

Crowdsourcing Privacy Design Critique: An Empirical Evaluation of Framing Effects

Care, Indifference and Anxiety—Attitudes toward Location Data in Everyday Life

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