Money Walks: A Human-Centric Study on the Economics of Personal Mobile Data

In the context of a myriad of mobile apps which collect personally identifiable information (PII) and a prospective market place of personal data, we investigate a user-centric monetary valuation of mobile PII. During a 6-week long user study in a living lab deployment with 60 participants, we collected their daily valuations of 4 categories of mobile PII (communication, e.g. phonecalls made/received, applications, e.g. time spent on different apps, location and media, photos taken) at three levels of complexity (individual data points, aggregated statistics and processed, i.e. meaningful interpretations of the data). In order to obtain honest valuations, we employ a reverse second price auction mechanism. Our findings show that the most sensitive and valued category of personal information is location. We report statistically significant associations between actual mobile usage, personal dispositions, and bidding behavior. Finally, we outline key implications for the design of mobile services and future markets of personal data.Comment: 15 pages, 2 figures. To appear in ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp 2014

Exploring Consumers’ Attitudes of Smart TV Related Privacy Risks

A number of privacy risks are inherent in the Smart TV ecosystem. It is likely that many consumers are unaware of these privacy risks. Alternatively, they might be aware but consider the privacy risks acceptable. In order to explore this, we carried out an online survey with 200 participants to determine whether consumers were aware of Smart TV related privacy risks. The responses revealed a meagre level of awareness. We also explored consumers’ attitudes towards specific Smart TV related privacy risks. We isolated a number of factors that influenced rankings and used these to develop awareness-raising messages. We tested these messages in an online survey with 155 participants. The main finding was that participants were generally unwilling to disconnect their Smart TVs from the Internet because they valued the Smart TV’s Internet functionality more than their privacy. We subsequently evaluated the awareness-raising messages in a second survey with 169 participants, framing the question differently. We asked participants to choose between five different Smart TV Internet connection options, two of which retained functionality but entailed expending time and/or effort to preserve privacy

Privacy Utility and Privacy Disutility Expectancy: An Empirical Study on Social App Usage

Social apps fundamentally transform the way individuals manage their online identities through proxy-disclosure. While individuals do enjoy the potential enhancement to reputation that is realized through social app postings, they could have their privacy threatened when these apps make posting in an uncontrolled fashion. Drawing on the APCO model, this research elucidates the impact of the two key aspects of online proxy-disclosure on privacy expectancy formulation, which in turn influence usage intention of social apps. A survey was conducted to operationalize the research model. Results provide strong evidence that the two determinants of privacy expectancy strongly influence individuals’ perceptions of privacy utility and privacy disutility. Furthermore, the two types of privacy utility powerful drive usage intention of social apps. The implications of the findings are discussed

Return on Data: Personalizing Consumer Guidance in Data Exchanges

Consumers routinely supply personal data to technology companies in exchange for services. Yet, the relationship between the utility (U) consumers gain and the data (D) they supply — “return on data” (ROD) — remains largely unexplored. Expressed as a ratio, ROD = U / D. While lawmakers strongly advocate protecting consumer privacy, they tend to overlook ROD. Are the benefits of the services enjoyed by consumers, such as social networking and predictive search, commensurate with the value of the data extracted from them? How can consumers compare competing data-for-services deals? Currently, the legal frameworks regulating these transactions, including privacy law, aim primarily to protect personal data

Big Data's Impact on Privacy, Security and Consumer Welfare

The purpose of this paper is to highlight the costs, benefits, and externalities associated with organizations? use of big data. Specifically, it investigates how various inherent characteristics of big data are related to privacy, security and consumer welfare. The relation between characteristics of big data and privacy, security and consumer welfare issues are examined from the standpoints of data collection, storing, sharing and accessibility. The paper also discusses how privacy, security and welfare effects of big data are likely to vary across consumers of different levels of sophistication, vulnerability and technological savviness

Facebook’s Anticompetitive Lean in Strategies

Facebook is under fire on several fronts and with good reason. Regulators strive to make sense of and address a plethora of seemingly unrelated issues that arise from the operation of its platform. These range from antitrust, privacy violations, dissemination of harmful content and speech, deception and polarisation to political manipulation. This paper identifies Facebook’s unrestricted and excessive data collection as a unifying theme that requires immediate antitrust action. Once a privacy-oriented social network, Facebook soon mutated into a surveillance machine designed to hoover people’s personal data to identify and understand people’s interests, preferences and emotions and turn that knowledge into profit through the sale of targeted ads. Since people’s innate preference for privacy stood in the way of Facebook’s growth, Facebook resorted to privacy intrusions and deception to access as much user data as possible, thereby gaining market power. Currently, its overwhelming dominant position in the social media market means that no matter how much data Facebook extracts from users, how transparent its information about its data processing practices is and how many privacy scandals ensue from its reckless handling of data, users have nowhere else to go. This paper provides a course of action to correct this unacceptable anticompetitive outcome. The imposition of unfair commercial terms on consumers, the distortion of the competitive process through privacy violations and misleading practices, the squeezing of news publishers’ traffic and foreclosure of actual and potential competitors by Facebook, can be stopped. A combination of data and consumer protection measures alone cannot stop Facebook’s actions, but antitrust enforcement can be used to curb Facebook’s ability to reinforce its data-driven abuse of its market power

a two-facet privacy concern perspective

Neves, J., Turel, O., & Oliveira, T. (2022). SNS use reduction: a two-facet privacy concern perspective. Internet Research. https://doi.org/10.1108/INTR-01-2022-0012. ---- Funding: This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project –UIDB/04152/2020 – Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS.Purpose: While social networking sites (SNS) have many positive aspects, they can have several adverse outcomes, among which privacy violations are a vital concern. The authors first posit that concerns regarding privacy violations can drive attempts to reduce SNS use. Next, the authors note that these violations can have two sources: peers and the social media provider. Thus, there is a need to understand how this complex system of privacy concerns affects use reduction decisions. To do so, this paper aims to examine the separate and joint roles of institutional and peer privacy concerns in driving SNS use reduction. Design/methodology/approach: Based on privacy calculus theory, the authors propose a theoretical model to explain SNS use reduction, with institutional and peer privacy concerns as independent variables. The authors empirically examine the research model using a sample of 258 SNS users. Findings: This study reveals that institutional and peer privacy concerns independently increase one's intention to reduce SNS use and that institutional privacy concern strengthen the relation between peer privacy concern and the intention to reduce SNS use. Originality/value: Research thus far has not examined how the two facets of privacy work in tandem to affect 'users' decisions to change their behaviors on SNS platforms. Considering the unique and joint effect of these facets can thus provide a more precise and realistic perspective. This paper informs theories and models of privacy and online user behavior change.authorsversionepub_ahead_of_prin