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

What is Your Selfie Worth? A Field Study on Individuals’ Valuation of Personal Data

Referred to as the new oil, undoubtedly personal data is a valuable resource for organizations. Contrary, it is still blurred, to what extent individuals value their data even though, in a digitized world, users are requested to exchange their data for adequate services. Former research on individuals’ valuation of personal data result in scattered, partly contradictious values, depending on the data type, context, and the measurement method. In this study, we aimed to facilitate the valuation for individuals by applying a new and promising measurement methodology: the participants of our field experiment had the chance to sell their selfies in a name-your-own-price auction with repeated bidding and feedback loops. As a result, 39% of our participants were willing to donate or sell their selfies with a median of 5€. Additionally, bidding clusters were identified. Implications for research on the valuation of personal data in terms of privacy are discussed

Putting a Price Tag on Personal Information - A Literature Review

In the digital age, personal information is claimed to be the new commodity with a rising market demand and profitability for businesses. Simultaneously, people are becoming aware of the value of their personal information while being concerned about their privacy. This increases the demand of direct compensation or protection. In response to the commodification of privacy and the increased demand for compensation, a number of scholars have shed light on the value people assign to their personal information. However, these findings remain controversial as their results differ tremendously due to different research methods and contexts. To address this gap, we conducted a systematic literature review to gain insights into the current research state and to identify further research avenues. By synthesizing and analyzing 37 publications, we provide an integrative framework along with seven contextual factors affecting individuals’ valuation of privacy

Valuation of Personal Data in the Age of Data Ownership

In order to tackle uncertainties about data ownership and data misuse, more accessible and competitive data markets are proposed, especially concerning the use and access rights of data generated by the Internet of Things (IoT) devices. Legal proposals suggest that companies and individuals become owners of their self-generated data, enabling new ways of data monetization. Still, individuals are often uncertain about the value and price of their own generated data. This research builds on construal level theory to propose influencing factors fostering an understanding of intraindividual data value. The results of a pilot study survey (n = 104), conducted during the ICIS 2022, show that data proximity and data sensitivity factors significantly influence intraindividual data value. Our research extends the knowledge on data value from individual perspectives and builds the foundation for future work on data valuation and pricing in intraindividual data trading

Online Personal Data Processing and EU Data Protection Reform. CEPS Task Force Report, April 2013

This report sheds light on the fundamental questions and underlying tensions between current policy objectives, compliance strategies and global trends in online personal data processing, assessing the existing and future framework in terms of effective regulation and public policy. Based on the discussions among the members of the CEPS Digital Forum and independent research carried out by the rapporteurs, policy conclusions are derived with the aim of making EU data protection policy more fit for purpose in today’s online technological context. This report constructively engages with the EU data protection framework, but does not provide a textual analysis of the EU data protection reform proposal as such

UNCOVERING THE PRIVACY PARADOX: THE INFLUENCE OF DISTRACTION ON DATA DISCLOSURE DECISIONS

The discrepancy between individuals’ intention to disclose data and their actual disclosure behaviour is called the privacy paradox. Although a wide range of research has investigated the privacy para-dox, it remains insufficiently understood due to mental processes’ role in decision-making being most-ly neglected. This research-in-progress provides a theoretical concept that examines the cognitive processes underlying data disclosure decisions to provide a better understanding of the privacy para-dox. We apply the Elaboration Likelihood Model (ELM), which suggests that the mental shortcuts that individuals take when making their actual data disclosure decision, which differs from their self-reported data disclosure intention, cause the privacy paradox. We propose a two-step, mixed method approach comprising a survey and an online experiment to empirically explore the intended and actu-al data disclosure. The study takes theoretical and methodological issues in prior literature into ac-count and enhances our understanding of individuals’ paradoxical data disclosure behaviour from a psychological point of view

Your Privacy Is Your Friend's Privacy: Examining Interdependent Information Disclosure on Online Social Networks

The highly interactive nature of interpersonal communication on online social networks (OSNs) impels us to think about privacy as a communal matter, with users' private information being revealed by not only their own voluntary disclosures, but also the activities of their social ties. The current privacy literature has identified two types of information disclosures in OSNs: self-disclosure, i.e., the disclosure of an OSN user's private information by him/herself; and co-disclosure, i.e., the disclosure of the user's private information by other users. Although co-disclosure has been increasingly identified as a new source of privacy threat inherent to the OSN context, few systematic attempts have been made to provide a framework for understanding the commonalities and distinctions between self- vs. co-disclosure, especially pertaining to different types of private information. To address this gap, this paper presents a data-driven study that builds upon an innovative measurement for quantifying the extent to which others' co-disclosure could lead to actual privacy harm. The results demonstrate the significant harm caused by co-disclosure and illustrate the differences between the identity elements revealed through self- and co-disclosure

Impulsivity and Information Disclosure: Implications for Privacy Paradox

Privacy paradox refers to the inconsistency that sometimes exists between individuals’ expressed privacy concern and the willingness to divulge personal information. Several arguments have been proposed to explain the inconsistency. One set of arguments centers around the effects of individual differences in personality characteristics, e.g., the Big Five. In the current article, we examine the role of a personality characteristic, impulsivity, in explaining the relationship between privacy concern and information disclosure. We report the results of a survey-based study that consisted of two hundred and forty-two (242) usable responses from subjects recruited on Amazon Mechanical Turk. The results show that one of the three dimensions of impulsivity, motor impulsivity, directly influences the extent of information disclosure, and, also moderates the relationship between privacy concern and information disclosure. Furthermore, our study shows impulsivity explains more variance in information disclosure than explained by the Big Five factors only

Your Privacy Is Your Friend\u27s Privacy: Examining Interdependent Information Disclosure on Online Social Networks

The highly interactive nature of interpersonal communication on online social networks (OSNs) impels us to think about privacy as a communal matter, with users\u27 private information being revealed by not only their own voluntary disclosures, but also the activities of their social ties. The current privacy literature has identified two types of information disclosures in OSNs: self-disclosure, i.e., the disclosure of an OSN user\u27s private information by him/herself; and co-disclosure, i.e., the disclosure of the user\u27s private information by other users. Although co-disclosure has been increasingly identified as a new source of privacy threat inherent to the OSN context, few systematic attempts have been made to provide a framework for understanding the commonalities and distinctions between self- vs. co-disclosure, especially pertaining to different types of private information. To address this gap, this paper presents a data-driven study that builds upon an innovative measurement for quantifying the extent to which others\u27 co-disclosure could lead to actual privacy harm. The results demonstrate the significant harm caused by co-disclosure and illustrate the differences between the identity elements revealed through self- and co-disclosure

Exploring the economic value of personal information from firms' financial statements

Currently personal data gathering in online markets is done on a far larger scale and much cheaper and faster than ever before. Within this scenario, a number of highly relevant companies for whom personal data is the key factor of production have emerged. However, up to now, the corresponding economic analysis has been restricted primarily to a qualitative perspective linked to privacy issues. Precisely, this paper seeks to shed light on the quantitative perspective, approximating the value of personal information for those companies that base their business model on this new type of asset. In the absence of any systematic research or methodology on the subject, an ad hoc procedure is developed in this paper. It starts with the examination of the accounts of a number of key players in online markets. This inspection first aims to determine whether the value of personal information databases is somehow reflected in the firms’ books, and second to define performance measures able to capture this value. After discussing the strengths and weaknesses of possible approaches, the method that performs best under several criteria (revenue per data record) is selected. From here, an estimation of the net present value of personal data is derived, as well as a slight digression into regional differences in the economic value of personal information